diff --git a/.env.example b/.env.example index a0963187fb..c7c533a3b1 100644 --- a/.env.example +++ b/.env.example @@ -1,41 +1,47 @@ # ============================================================================= -# MEMORA ENVIRONMENT CONFIGURATION +# HINDSIGHT ENVIRONMENT CONFIGURATION # ============================================================================= # Copy this file to .env and update with your values # Both services (API and Control Plane) read from this single file # ============================================================================= -# API SERVICE (MEMORA_API_*) +# API SERVICE (HINDSIGHT_API_*) # ============================================================================= # Database -MEMORA_API_DATABASE_URL=postgresql://memora:memora_dev@localhost:5432/memora +# Use "pg0" to start an embedded PostgreSQL instance via pg0 +# Or provide a full connection URL for external PostgreSQL +#HINDSIGHT_API_DATABASE_URL=postgresql://hindsight:hindsight_dev@localhost:5432/hindsight +HINDSIGHT_API_DATABASE_URL=pg0 + +# pg0 data directory (only used when HINDSIGHT_API_DATABASE_URL=pg0) +# HINDSIGHT_API_PG0_DATA_DIR=/path/to/pg_data # LLM Provider: "openai", "groq", or "ollama" -MEMORA_API_LLM_PROVIDER=groq +HINDSIGHT_API_LLM_PROVIDER=groq # LLM Model (provider-specific) -MEMORA_API_LLM_MODEL=openai/gpt-oss-20b +HINDSIGHT_API_LLM_MODEL=openai/gpt-oss-20b # API Key (not needed for ollama) -MEMORA_API_LLM_API_KEY=your_api_key_here +HINDSIGHT_API_LLM_API_KEY=your_api_key_here # Optional: Custom base URL (for ollama or custom endpoints) -# MEMORA_API_LLM_BASE_URL=http://localhost:11434/v1 +# HINDSIGHT_API_LLM_BASE_URL=http://localhost:11434/v1 # API Server Configuration (optional) -# MEMORA_API_HOST=0.0.0.0 -# MEMORA_API_PORT=8080 +# HINDSIGHT_API_HOST=0.0.0.0 +# HINDSIGHT_API_PORT=8888 -MEMORA_API_MCP_ENABLED=true +HINDSIGHT_API_MCP_ENABLED=true # ============================================================================= -# CONTROL PLANE SERVICE (MEMORA_CP_*) +# CONTROL PLANE SERVICE (HINDSIGHT_CP_*) # ============================================================================= # Dataplane API URL (where the control plane connects to) -MEMORA_CP_DATAPLANE_API_URL=http://localhost:8080 +HINDSIGHT_CP_DATAPLANE_API_URL=http://localhost:8888 # Control Plane Server Configuration (optional) -# MEMORA_CP_PORT=3000 -# MEMORA_CP_HOSTNAME=0.0.0.0 +# HINDSIGHT_CP_PORT=3000 +# HINDSIGHT_CP_HOSTNAME=0.0.0.0 diff --git a/.github/workflows/deploy-docs.yml b/.github/workflows/deploy-docs.yml index 0ac74e05dc..8da3581108 100644 --- a/.github/workflows/deploy-docs.yml +++ b/.github/workflows/deploy-docs.yml @@ -2,9 +2,10 @@ name: Deploy Docs to GitHub Pages on: push: - branches: [main] + branches: [main, renaming-pre-launch] paths: - - 'memora-docs/**' + - 'hindsight-docs/**' + - '.github/workflows/deploy-docs.yml' workflow_dispatch: permissions: @@ -21,20 +22,19 @@ jobs: runs-on: ubuntu-latest defaults: run: - working-directory: memora-docs + working-directory: hindsight-docs steps: - uses: actions/checkout@v4 - uses: actions/setup-node@v4 with: node-version: 20 cache: npm - cache-dependency-path: memora-docs/package-lock.json + cache-dependency-path: hindsight-docs/package-lock.json - run: npm ci - run: npm run build - uses: actions/upload-pages-artifact@v3 with: - path: memora-docs/build - + path: hindsight-docs/build deploy: environment: name: github-pages diff --git a/.github/workflows/release.yml b/.github/workflows/release.yml index 4b829e87f2..2a835adecb 100644 --- a/.github/workflows/release.yml +++ b/.github/workflows/release.yml @@ -22,15 +22,15 @@ jobs: with: python-version-file: ".python-version" - - name: Build memora package - working-directory: ./memora + - name: Build hindsight package + working-directory: ./hindsight run: uv build - name: Upload artifacts uses: actions/upload-artifact@v4 with: - name: python-memora-dist - path: memora/dist/* + name: python-hindsight-dist + path: hindsight/dist/* retention-days: 30 build-rust-cli: @@ -40,16 +40,16 @@ jobs: include: - os: ubuntu-latest target: x86_64-unknown-linux-gnu - artifact_name: memora - asset_name: memora-linux-amd64 + artifact_name: hindsight + asset_name: hindsight-linux-amd64 - os: macos-latest target: x86_64-apple-darwin - artifact_name: memora - asset_name: memora-darwin-amd64 + artifact_name: hindsight + asset_name: hindsight-darwin-amd64 - os: macos-latest target: aarch64-apple-darwin - artifact_name: memora - asset_name: memora-darwin-arm64 + artifact_name: hindsight + asset_name: hindsight-darwin-arm64 steps: - uses: actions/checkout@v4 @@ -74,17 +74,17 @@ jobs: - name: Cache cargo build uses: actions/cache@v4 with: - path: memora-cli/target + path: hindsight-cli/target key: ${{ runner.os }}-cargo-build-target-${{ hashFiles('**/Cargo.lock') }} - name: Build - working-directory: memora-cli + working-directory: hindsight-cli run: cargo build --release --target ${{ matrix.target }} - name: Prepare artifact run: | mkdir -p artifacts - cp memora-cli/target/${{ matrix.target }}/release/${{ matrix.artifact_name }} artifacts/${{ matrix.asset_name }} + cp hindsight-cli/target/${{ matrix.target }}/release/${{ matrix.artifact_name }} artifacts/${{ matrix.asset_name }} chmod +x artifacts/${{ matrix.asset_name }} - name: Upload artifacts @@ -135,7 +135,7 @@ jobs: id: meta uses: docker/metadata-action@v5 with: - images: ghcr.io/${{ github.repository_owner }}/memora-${{ matrix.component }} + images: ghcr.io/${{ github.repository_owner }}/hindsight-${{ matrix.component }} tags: | type=semver,pattern={{version}},value=${{ steps.get_version.outputs.VERSION }} type=semver,pattern={{major}}.{{minor}},value=${{ steps.get_version.outputs.VERSION }} @@ -179,11 +179,11 @@ jobs: - name: Lint Helm chart run: | - helm lint helm/memora + helm lint helm/hindsight - name: Package Helm chart run: | - helm package helm/memora --destination ./helm-packages + helm package helm/hindsight --destination ./helm-packages - name: Upload Helm chart artifact uses: actions/upload-artifact@v4 @@ -208,26 +208,26 @@ jobs: - name: Download Python package uses: actions/download-artifact@v4 with: - name: python-memora-dist - path: ./artifacts/python-memora-dist + name: python-hindsight-dist + path: ./artifacts/python-hindsight-dist - name: Download Rust CLI (Linux) uses: actions/download-artifact@v4 with: - name: rust-cli-memora-linux-amd64 - path: ./artifacts/rust-cli-memora-linux-amd64 + name: rust-cli-hindsight-linux-amd64 + path: ./artifacts/rust-cli-hindsight-linux-amd64 - name: Download Rust CLI (macOS Intel) uses: actions/download-artifact@v4 with: - name: rust-cli-memora-darwin-amd64 - path: ./artifacts/rust-cli-memora-darwin-amd64 + name: rust-cli-hindsight-darwin-amd64 + path: ./artifacts/rust-cli-hindsight-darwin-amd64 - name: Download Rust CLI (macOS ARM) uses: actions/download-artifact@v4 with: - name: rust-cli-memora-darwin-arm64 - path: ./artifacts/rust-cli-memora-darwin-arm64 + name: rust-cli-hindsight-darwin-arm64 + path: ./artifacts/rust-cli-hindsight-darwin-arm64 - name: Download Helm chart uses: actions/download-artifact@v4 @@ -239,11 +239,11 @@ jobs: run: | mkdir -p release-assets # Python package - cp artifacts/python-memora-dist/* release-assets/ + cp artifacts/python-hindsight-dist/* release-assets/ # Rust CLI binaries - cp artifacts/rust-cli-memora-linux-amd64/memora-linux-amd64 release-assets/ - cp artifacts/rust-cli-memora-darwin-amd64/memora-darwin-amd64 release-assets/ - cp artifacts/rust-cli-memora-darwin-arm64/memora-darwin-arm64 release-assets/ + cp artifacts/rust-cli-hindsight-linux-amd64/hindsight-linux-amd64 release-assets/ + cp artifacts/rust-cli-hindsight-darwin-amd64/hindsight-darwin-amd64 release-assets/ + cp artifacts/rust-cli-hindsight-darwin-arm64/hindsight-darwin-arm64 release-assets/ # Helm chart cp artifacts/helm-chart/*.tgz release-assets/ @@ -251,68 +251,68 @@ jobs: id: release_notes run: | cat << EOF > release-notes.md - # Memora v${{ steps.get_version.outputs.VERSION }} + # Hindsight v${{ steps.get_version.outputs.VERSION }} ## ๐Ÿ“ฆ Release Artifacts ### Python Package - - \`memora-${{ steps.get_version.outputs.VERSION }}-py3-none-any.whl\` - - \`memora-${{ steps.get_version.outputs.VERSION }}.tar.gz\` + - \`hindsight-${{ steps.get_version.outputs.VERSION }}-py3-none-any.whl\` + - \`hindsight-${{ steps.get_version.outputs.VERSION }}.tar.gz\` ### CLI Binaries - - \`memora-linux-amd64\` - Linux x86_64 - - \`memora-darwin-amd64\` - macOS Intel - - \`memora-darwin-arm64\` - macOS Apple Silicon + - \`hindsight-linux-amd64\` - Linux x86_64 + - \`hindsight-darwin-amd64\` - macOS Intel + - \`hindsight-darwin-arm64\` - macOS Apple Silicon ### Helm Chart - - \`memora-${{ steps.get_version.outputs.VERSION }}.tgz\` + - \`hindsight-${{ steps.get_version.outputs.VERSION }}.tgz\` ### Docker Images Docker images are published to GitHub Container Registry: - - \`ghcr.io/${{ github.repository_owner }}/memora-api:${{ steps.get_version.outputs.VERSION }}\` - - \`ghcr.io/${{ github.repository_owner }}/memora-control-plane:${{ steps.get_version.outputs.VERSION }}\` + - \`ghcr.io/${{ github.repository_owner }}/hindsight-api:${{ steps.get_version.outputs.VERSION }}\` + - \`ghcr.io/${{ github.repository_owner }}/hindsight-control-plane:${{ steps.get_version.outputs.VERSION }}\` ## ๐Ÿš€ Installation ### Python Package \`\`\`bash - pip install memora==${{ steps.get_version.outputs.VERSION }} + pip install hindsight==${{ steps.get_version.outputs.VERSION }} \`\`\` ### CLI \`\`\`bash # macOS (Apple Silicon) - curl -L https://github.com/${{ github.repository }}/releases/download/v${{ steps.get_version.outputs.VERSION }}/memora-darwin-arm64 -o memora - chmod +x memora - sudo mv memora /usr/local/bin/ + curl -L https://github.com/${{ github.repository }}/releases/download/v${{ steps.get_version.outputs.VERSION }}/hindsight-darwin-arm64 -o hindsight + chmod +x hindsight + sudo mv hindsight /usr/local/bin/ # macOS (Intel) - curl -L https://github.com/${{ github.repository }}/releases/download/v${{ steps.get_version.outputs.VERSION }}/memora-darwin-amd64 -o memora - chmod +x memora - sudo mv memora /usr/local/bin/ + curl -L https://github.com/${{ github.repository }}/releases/download/v${{ steps.get_version.outputs.VERSION }}/hindsight-darwin-amd64 -o hindsight + chmod +x hindsight + sudo mv hindsight /usr/local/bin/ # Linux - curl -L https://github.com/${{ github.repository }}/releases/download/v${{ steps.get_version.outputs.VERSION }}/memora-linux-amd64 -o memora - chmod +x memora - sudo mv memora /usr/local/bin/ + curl -L https://github.com/${{ github.repository }}/releases/download/v${{ steps.get_version.outputs.VERSION }}/hindsight-linux-amd64 -o hindsight + chmod +x hindsight + sudo mv hindsight /usr/local/bin/ \`\`\` ### Helm Chart \`\`\`bash - helm install memora memora-${{ steps.get_version.outputs.VERSION }}.tgz + helm install hindsight hindsight-${{ steps.get_version.outputs.VERSION }}.tgz \`\`\` ### Docker \`\`\`bash # Pull API image - docker pull ghcr.io/${{ github.repository_owner }}/memora-api:${{ steps.get_version.outputs.VERSION }} + docker pull ghcr.io/${{ github.repository_owner }}/hindsight-api:${{ steps.get_version.outputs.VERSION }} # Pull Control Plane image - docker pull ghcr.io/${{ github.repository_owner }}/memora-control-plane:${{ steps.get_version.outputs.VERSION }} + docker pull ghcr.io/${{ github.repository_owner }}/hindsight-control-plane:${{ steps.get_version.outputs.VERSION }} # Or use latest - docker pull ghcr.io/${{ github.repository_owner }}/memora-api:latest - docker pull ghcr.io/${{ github.repository_owner }}/memora-control-plane:latest + docker pull ghcr.io/${{ github.repository_owner }}/hindsight-api:latest + docker pull ghcr.io/${{ github.repository_owner }}/hindsight-control-plane:latest \`\`\` EOF cat release-notes.md @@ -333,7 +333,7 @@ jobs: echo "# Release v${{ steps.get_version.outputs.VERSION }} Published Successfully" >> $GITHUB_STEP_SUMMARY echo "" >> $GITHUB_STEP_SUMMARY echo "## ๐Ÿ“ฆ Components" >> $GITHUB_STEP_SUMMARY - echo "- โœ… Python package (memora)" >> $GITHUB_STEP_SUMMARY + echo "- โœ… Python package (hindsight)" >> $GITHUB_STEP_SUMMARY echo "- โœ… Rust CLI (Linux amd64, macOS amd64, macOS arm64)" >> $GITHUB_STEP_SUMMARY echo "- โœ… Docker images (API, Control Plane)" >> $GITHUB_STEP_SUMMARY echo "- โœ… Helm chart" >> $GITHUB_STEP_SUMMARY diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml index bb09ac5ada..84c41014bd 100644 --- a/.github/workflows/test.yml +++ b/.github/workflows/test.yml @@ -16,7 +16,7 @@ jobs: env: POSTGRES_USER: postgres POSTGRES_PASSWORD: postgres - POSTGRES_DB: memora_test + POSTGRES_DB: hindsight_test options: >- --health-cmd pg_isready --health-interval 10s @@ -26,10 +26,10 @@ jobs: - 5432:5432 env: - MEMORA_API_DATABASE_URL: postgresql://postgres:postgres@localhost:5432/memora_test - MEMORA_API_LLM_PROVIDER: groq - MEMORA_API_LLM_API_KEY: ${{ secrets.GROQ_API_KEY }} - MEMORA_API_LLM_MODEL: openai/gpt-oss-20b + HINDSIGHT_API_DATABASE_URL: postgresql://postgres:postgres@localhost:5432/hindsight_test + HINDSIGHT_API_LLM_PROVIDER: groq + HINDSIGHT_API_LLM_API_KEY: ${{ secrets.GROQ_API_KEY }} + HINDSIGHT_API_LLM_MODEL: openai/gpt-oss-20b steps: - uses: actions/checkout@v4 @@ -48,9 +48,9 @@ jobs: run: uv sync --extra test - name: Run migrations - working-directory: ./memora + working-directory: ./hindsight run: | uv run alembic upgrade head - name: Run tests - run: uv run pytest memora/tests -v + run: uv run pytest hindsight/tests -v diff --git a/CLAUDE.md b/CLAUDE.md deleted file mode 100644 index a1612c1fd0..0000000000 --- a/CLAUDE.md +++ /dev/null @@ -1,8 +0,0 @@ -# Documentation -Do not write any markdown file, just write the code. - -# Workflow -- After your changes, make sure everything is working fine by running the tests. -- keep the readme.md architecture section up to date when you change the implementation -- when changing an implemetation, do not keep the old one as fallback -- to run test, use uv run pytest tests \ No newline at end of file diff --git a/README.md b/README.md index 2f2b12fead..0b3045dac1 100644 --- a/README.md +++ b/README.md @@ -1,64 +1,57 @@ -# Memora +# Hindsight **Long-term memory for AI agents.** -AI assistants forget everything between sessions. Memora fixes that with a memory system that handles temporal reasoning, entity connections, and personality-aware responses. +AI assistants forget everything between sessions. Hindsight fixes that with a memory system that handles temporal reasoning, entity connections, and personality-aware responses. -## Why Memora? +## Why Hindsight? - **Temporal queries** โ€” "What did Alice do last spring?" requires more than vector search - **Entity connections** โ€” Knowing "Alice works at Google" + "Google is in Mountain View" = "Alice works in Mountain View" - **Agent opinions** โ€” Agents form and recall beliefs with confidence scores - **Personality** โ€” Big Five traits influence how agents process and respond to information -## 5-Minute Setup +## 60-seconds step -### 1. Start the server + +### 1. Install the Hindsight All package (client + API) ```bash -# Clone and start with Docker -git clone https://github.com/anthropics/memora.git -cd memora/docker -./start.sh +pip install hindsight-all ``` -Server runs at `http://localhost:8080` - -### 2. Install the Python client - +### 2. Import your OpenAI API key ```bash -pip install memora-client +export OPENAI_API_KEY=xx ``` -### 3. Use it +### 3. Run embedded server and client ```python -from memora_client import Memora - -client = Memora(base_url="http://localhost:8080") - -# Store memories -client.store(agent_id="my-agent", content="Alice works at Google") -client.store(agent_id="my-agent", content="Bob prefers Python over JavaScript") +import os +from hindsight import HindsightServer, HindsightClient + +with HindsightServer(llm_provider="openai", llm_model="gpt-5.1-mini", llm_api_key=os.environ["OPENAI_API_KEY"]) as server: + client = HindsightClient(base_url=server.url) + + client.put(agent_id="my-agent", content="Alice works at Google") + client.put(agent_id="my-agent", content="Bob prefers Python over JavaScript") + + client.search(agent_id="my-agent", query="What does Alice do?") + + client.think(agent_id="my-agent", query="Tell me about Alice") +``` -# Search memories -results = client.search(agent_id="my-agent", query="What does Alice do?") -for r in results: - print(f"{r['text']} ({r['weight']:.2f})") -# Generate personality-aware responses -answer = client.think(agent_id="my-agent", query="Tell me about Alice") -print(answer["text"]) -``` ## Documentation -Full documentation: [memora-docs](./memora-docs) +Full documentation: [hindsight-docs](./hindsight-docs) -- [Architecture](./memora-docs/docs/developer/architecture.md) โ€” How ingestion, storage, and retrieval work -- [Python Client](./memora-docs/docs/sdks/python.md) โ€” Full API reference -- [API Reference](./memora-docs/docs/api-reference/index.md) โ€” REST API endpoints -- [Personality](./memora-docs/docs/developer/personality.md) โ€” Big Five traits and opinion formation +- [Architecture](./hindsight-docs/docs/developer/architecture.md) โ€” How ingestion, storage, and retrieval work +- [Python Client](./hindsight-docs/docs/sdks/python.md) โ€” Full API reference +- [API Reference](./hindsight-docs/docs/api-reference/index.md) โ€” REST API endpoints +- [Personality](./hindsight-docs/docs/developer/personality.md) โ€” Big Five traits and opinion formation ## License diff --git a/RELEASE.md b/RELEASE.md index 0a7fe3f5c1..a11db94e86 100644 --- a/RELEASE.md +++ b/RELEASE.md @@ -6,7 +6,7 @@ ```bash uv sync -cd memora-dev +cd hindsight-dev uv run generate-openapi cd .. ``` @@ -24,7 +24,7 @@ This regenerates Python and TypeScript clients from `openapi.json`. ### 3. Commit Everything ```bash -git add openapi.json memora-clients/ +git add openapi.json hindsight-clients/ git commit -m "Update OpenAPI spec and regenerate clients" ``` @@ -47,7 +47,7 @@ This will: ### Publish Python Client to PyPI ```bash -cd memora-clients/python +cd hindsight-clients/python uv build uv publish ``` @@ -55,7 +55,7 @@ uv publish ### Publish TypeScript Client to NPM ```bash -cd memora-clients/typescript +cd hindsight-clients/typescript npm install npm run build npm publish --access public @@ -65,7 +65,7 @@ npm publish --access public ## Pre-Release Checklist -- [ ] Tests passing: `cd memora && uv run pytest tests` +- [ ] Tests passing: `cd hindsight-api && uv run pytest tests` - [ ] No uncommitted changes: `git status` - [ ] On `main` branch @@ -98,7 +98,7 @@ git status ``` **GitHub Actions failed:** -- Check: https://github.com/nicoloboschi/memora/actions +- Check: https://github.com/vectorize-io/hindsight/actions - Re-run failed jobs or fix and release new patch version **Rollback:** @@ -116,13 +116,13 @@ git push ```bash # Full release workflow uv sync -cd memora-dev && uv run generate-openapi && cd .. +cd hindsight-dev && uv run generate-openapi && cd .. ./scripts/generate-clients.sh -git add openapi.json memora-clients/ +git add openapi.json hindsight-clients/ git commit -m "Update OpenAPI spec and regenerate clients" ./scripts/release.sh 0.0.6 # After GH Actions complete: -cd memora-clients/python && uv build && uv publish +cd hindsight-clients/python && uv build && uv publish cd ../typescript && npm run build && npm publish --access public ``` diff --git a/docker/README.md b/docker/README.md deleted file mode 100644 index 8cecd57ad5..0000000000 --- a/docker/README.md +++ /dev/null @@ -1,175 +0,0 @@ -# Memora Docker Setup - -Complete Docker Compose setup for running all Memora services locally. - -## Services - -This setup includes: -- **PostgreSQL** with pgvector extension (port 5432) -- **API Service** - FastAPI backend (port 8080) -- **Control Plane** - Next.js web UI (port 3000) - -## Quick Start - -1. **Configure environment variables:** - ```bash - cp .env.example .env - # Edit .env and set your API keys - ``` - -2. **Start all services:** - ```bash - ./start.sh - ``` - -3. **Access the services:** - - Control Plane: http://localhost:3000 - - API: http://localhost:8080 - - PostgreSQL: localhost:5432 - -## Scripts - -### `./start.sh` -Build and start all services. Waits for all services to be healthy. - -### `./stop.sh` -Stop all services (keeps data). - -### `./clean.sh` -Stop all services and remove all data (destructive). - -### `./logs.sh [service]` -View logs for all services or a specific service: -```bash -./logs.sh # All services -./logs.sh api # API only -./logs.sh postgres # PostgreSQL only -./logs.sh control-plane # Control plane only -``` - -## Manual Docker Compose Commands - -```bash -# Start services -docker-compose up -d - -# Stop services -docker-compose down - -# Rebuild and start -docker-compose up --build -d - -# View logs -docker-compose logs -f - -# Remove everything including data -docker-compose down -v -``` - -## Database - -### Connection Info -- **Host:** localhost -- **Port:** 5432 -- **Database:** memora -- **User:** memora -- **Password:** memora_dev - -### Migrations - -Database migrations run automatically when the API service starts. The API uses Alembic to: -1. Check the current schema version -2. Run any pending migrations -3. Initialize the database if it's empty - -Extensions (pgvector, uuid-ossp) are created automatically by the first migration. - -## Environment Variables - -Required in `.env` file: - -```bash -# API Service Configuration -MEMORA_API_DATABASE_URL=postgresql://memora:memora_dev@localhost:5432/memora -MEMORA_API_LLM_PROVIDER=groq -MEMORA_API_LLM_API_KEY=your-api-key-here -MEMORA_API_LLM_MODEL=openai/gpt-oss-120b - -# Optional: Custom LLM endpoint -# MEMORA_API_LLM_BASE_URL=http://localhost:11434/v1 - -# Control Plane Configuration -MEMORA_CP_DATAPLANE_API_URL=http://localhost:8080 -``` - -## Troubleshooting - -### Services won't start -Check logs for errors: -```bash -./logs.sh -``` - -### Database connection issues -Ensure PostgreSQL is healthy: -```bash -docker exec memora-postgres pg_isready -U memora -``` - -### API won't connect to database -Check if migrations ran successfully: -```bash -./logs.sh api -``` - -### Control plane can't reach API -Verify the API is running: -```bash -curl http://localhost:8080/ -``` - -### Reset everything -```bash -./clean.sh -./start.sh -``` - -## Development - -### Rebuilding after code changes - -**API changes:** -```bash -docker-compose up --build -d api -``` - -**Control Plane changes:** -```bash -docker-compose up --build -d control-plane -``` - -### Accessing the database -```bash -docker exec -it memora-postgres psql -U memora -d memora -``` - -### Inspecting containers -```bash -docker-compose ps -docker-compose exec api bash -docker-compose exec control-plane sh -``` - -## Data Persistence - -PostgreSQL data is persisted in a Docker volume named `postgres_data`. This data survives container restarts but not `docker-compose down -v`. - -To backup data: -```bash -docker exec memora-postgres pg_dump -U memora memora > backup.sql -``` - -To restore data: -```bash -docker exec -i memora-postgres psql -U memora memora < backup.sql -``` diff --git a/docker/api.Dockerfile b/docker/api.Dockerfile index 70edfece2b..36d9d96c6f 100644 --- a/docker/api.Dockerfile +++ b/docker/api.Dockerfile @@ -9,15 +9,15 @@ RUN apt-get update && apt-get install -y \ WORKDIR /app # Copy only dependency files first for better caching -COPY memora/pyproject.toml memora/README.md /app/memora/ -COPY memora/memora /app/memora/memora -COPY memora/alembic /app/memora/alembic +COPY hindsight-api/pyproject.toml hindsight-api/README.md /app/hindsight-api/ +COPY hindsight-api/hindsight_api /app/hindsight-api/hindsight_api +COPY hindsight-api/alembic /app/hindsight-api/alembic # Install uv for faster dependency installation RUN pip install --no-cache-dir uv # Install Python dependencies to a virtual environment -WORKDIR /app/memora +WORKDIR /app/hindsight-api RUN uv venv /opt/venv && \ . /opt/venv/bin/activate && \ uv pip install --no-cache -e . @@ -33,19 +33,19 @@ RUN apt-get update && apt-get install -y \ # Copy virtual environment from builder COPY --from=builder /opt/venv /opt/venv -COPY --from=builder /app/memora /app/memora +COPY --from=builder /app/hindsight-api /app/hindsight-api # Set working directory -WORKDIR /app/memora +WORKDIR /app/hindsight-api # Expose API port -EXPOSE 8080 +EXPOSE 8888 # Set environment variables ENV PYTHONUNBUFFERED=1 -ENV DATABASE_URL=postgresql://memora:memora_dev@postgres:5432/memora +ENV DATABASE_URL=postgresql://hindsight:hindsight_dev@postgres:5432/hindsight ENV PATH="/opt/venv/bin:$PATH" -ENV PYTHONPATH=/app/memora +ENV PYTHONPATH=/app/hindsight-api # Run the API server -CMD ["python", "-m", "memora.web.server", "--host", "0.0.0.0", "--port", "8080"] +CMD ["python", "-m", "hindsight_api.web.server", "--host", "0.0.0.0", "--port", "8888"] diff --git a/docker/clean.sh b/docker/clean.sh index d78a0b46f3..c39653aaac 100755 --- a/docker/clean.sh +++ b/docker/clean.sh @@ -3,7 +3,7 @@ set -e cd "$(dirname "$0")" -echo "๐Ÿงน Cleaning Memora Services" +echo "๐Ÿงน Cleaning Services" echo "============================" echo "" echo "This will:" @@ -20,7 +20,7 @@ fi echo "" echo "๐Ÿ—‘๏ธ Removing services and data..." -docker-compose down -v +docker compose down -v echo "" echo "โœ… All services and data removed" diff --git a/docker/control-plane.Dockerfile b/docker/control-plane.Dockerfile index 55309122be..85a884b894 100644 --- a/docker/control-plane.Dockerfile +++ b/docker/control-plane.Dockerfile @@ -31,9 +31,9 @@ COPY --from=builder --chown=nextjs:nodejs /app/.next/static ./.next/static USER nextjs -EXPOSE 3000 +EXPOSE 9999 -ENV PORT=3000 +ENV PORT=9999 ENV HOSTNAME="0.0.0.0" CMD ["node", "server.js"] diff --git a/docker/docker-compose.yml b/docker/docker-compose.yml index e9617eb3dd..54ccbfc85d 100644 --- a/docker/docker-compose.yml +++ b/docker/docker-compose.yml @@ -1,78 +1,78 @@ services: postgres: image: pgvector/pgvector:pg16 - container_name: memora-postgres + container_name: hindsight-postgres environment: - POSTGRES_USER: memora - POSTGRES_PASSWORD: memora_dev - POSTGRES_DB: memora + POSTGRES_USER: hindsight + POSTGRES_PASSWORD: hindsight_dev + POSTGRES_DB: hindsight ports: - "5432:5432" volumes: - postgres_data:/var/lib/postgresql/data healthcheck: - test: ["CMD-SHELL", "pg_isready -U memora"] + test: ["CMD-SHELL", "pg_isready -U hindsight"] interval: 5s timeout: 5s retries: 5 networks: - - memora-network + - hindsight-network api: build: context: .. dockerfile: docker/api.Dockerfile - container_name: memora-api + container_name: hindsight-api environment: - MEMORA_API_DATABASE_URL: postgresql://memora:memora_dev@postgres:5432/memora - MEMORA_API_LLM_PROVIDER: ${MEMORA_API_LLM_PROVIDER:-groq} - MEMORA_API_LLM_API_KEY: ${MEMORA_API_LLM_API_KEY} - MEMORA_API_LLM_MODEL: ${MEMORA_API_LLM_MODEL:-openai/gpt-oss-120b} - MEMORA_API_LLM_BASE_URL: ${MEMORA_API_LLM_BASE_URL} - MEMORA_API_HOST: ${MEMORA_API_HOST:-0.0.0.0} - MEMORA_API_PORT: ${MEMORA_API_PORT:-8080} + HINDSIGHT_API_DATABASE_URL: postgresql://hindsight:hindsight_dev@postgres:5432/hindsight + HINDSIGHT_API_LLM_PROVIDER: ${HINDSIGHT_API_LLM_PROVIDER:-groq} + HINDSIGHT_API_LLM_API_KEY: ${HINDSIGHT_API_LLM_API_KEY} + HINDSIGHT_API_LLM_MODEL: ${HINDSIGHT_API_LLM_MODEL:-openai/gpt-oss-20b} + HINDSIGHT_API_LLM_BASE_URL: ${HINDSIGHT_API_LLM_BASE_URL} + HINDSIGHT_API_HOST: 0.0.0.0 + HINDSIGHT_API_PORT: 8888 ports: - - "8080:8080" + - "8888:8888" depends_on: postgres: condition: service_healthy healthcheck: - test: ["CMD", "curl", "-f", "http://localhost:8080/api/v1/agents"] + test: ["CMD", "curl", "-f", "http://localhost:8888/api/v1/agents"] interval: 10s timeout: 5s retries: 5 start_period: 30s networks: - - memora-network + - hindsight-network restart: unless-stopped control-plane: build: - context: ../memora-control-plane + context: ../hindsight-control-plane dockerfile: ../docker/control-plane.Dockerfile - container_name: memora-control-plane + container_name: hindsight-control-plane environment: NODE_ENV: production - MEMORA_CP_HOSTNAME: ${MEMORA_CP_HOSTNAME:-0.0.0.0} - MEMORA_CP_PORT: ${MEMORA_CP_PORT:-3000} - MEMORA_CP_DATAPLANE_API_URL: ${MEMORA_CP_DATAPLANE_API_URL:-http://api:8080} + HOSTNAME: 0.0.0.0 + PORT: 9999 + HINDSIGHT_CP_DATAPLANE_API_URL: http://api:8888 ports: - - "3000:3000" + - "9999:9999" depends_on: api: condition: service_healthy healthcheck: - test: ["CMD", "wget", "--no-verbose", "--tries=1", "--spider", "http://localhost:3000/"] + test: ["CMD", "wget", "--no-verbose", "--tries=1", "--spider", "http://localhost:9999/"] interval: 10s timeout: 5s retries: 5 start_period: 30s networks: - - memora-network + - hindsight-network restart: unless-stopped networks: - memora-network: + hindsight-network: driver: bridge volumes: diff --git a/docker/logs.sh b/docker/logs.sh index cb705dfb15..5039f449ae 100755 --- a/docker/logs.sh +++ b/docker/logs.sh @@ -8,9 +8,9 @@ SERVICE=$1 if [ -z "$SERVICE" ]; then echo "๐Ÿ“‹ Showing logs for all services..." echo "" - docker-compose logs -f + docker compose logs -f else echo "๐Ÿ“‹ Showing logs for $SERVICE..." echo "" - docker-compose logs -f "$SERVICE" + docker compose logs -f "$SERVICE" fi diff --git a/docker/start.sh b/docker/start.sh index 3983dff6a4..45f4b01b82 100755 --- a/docker/start.sh +++ b/docker/start.sh @@ -3,7 +3,7 @@ set -e cd "$(dirname "$0")" -echo "๐Ÿš€ Starting Memora Services" +echo "๐Ÿš€ Starting Hindsight Services" echo "============================" echo "" @@ -15,14 +15,14 @@ if [ ! -f ../.env ]; then cp ../.env.example ../.env echo "" echo "โš ๏ธ Please edit .env and set your API keys:" - echo " - MEMORA_API_LLM_API_KEY" + echo " - HINDSIGHT_API_LLM_API_KEY" echo "" echo "Then run this script again." exit 1 fi echo "๐Ÿ“ฆ Building and starting services..." -docker-compose --env-file ../.env up --build -d +docker compose --env-file ../.env up --build -d echo "" echo "โณ Waiting for services to be healthy..." @@ -30,21 +30,21 @@ echo "" # Wait for PostgreSQL echo " Waiting for PostgreSQL..." -until docker exec memora-postgres pg_isready -U memora > /dev/null 2>&1; do +until docker exec hindsight-postgres pg_isready -U hindsight > /dev/null 2>&1; do sleep 1 done echo " โœ… PostgreSQL is ready" # Wait for API echo " Waiting for API..." -until curl -f http://localhost:8080/api/v1/agents > /dev/null 2>&1; do +until curl -f http://localhost:8888/api/v1/agents > /dev/null 2>&1; do sleep 2 done echo " โœ… API is ready" # Wait for Control Plane echo " Waiting for Control Plane..." -until curl -f http://localhost:3000 > /dev/null 2>&1; do +until curl -f http://localhost:9999 > /dev/null 2>&1; do sleep 2 done echo " โœ… Control Plane is ready" @@ -53,12 +53,12 @@ echo "" echo "โœ… All services are running!" echo "" echo "๐Ÿ“Š Service URLs:" -echo " Control Plane: http://localhost:3000" -echo " API: http://localhost:8080" +echo " Control Plane: http://localhost:9999" +echo " API: http://localhost:8888" echo " PostgreSQL: localhost:5432" echo "" echo "๐Ÿ” View logs:" -echo " docker-compose logs -f" +echo " docker compose logs -f" echo "" echo "๐Ÿ›‘ Stop services:" echo " ./stop.sh" diff --git a/docker/stop.sh b/docker/stop.sh index d563d26c09..ec1d589014 100755 --- a/docker/stop.sh +++ b/docker/stop.sh @@ -3,15 +3,15 @@ set -e cd "$(dirname "$0")" -echo "๐Ÿ›‘ Stopping Memora Services" +echo "๐Ÿ›‘ Stopping Services" echo "============================" echo "" -docker-compose down +docker compose down echo "" echo "โœ… All services stopped" echo "" echo "๐Ÿ’ก To remove data volumes as well, run:" -echo " docker-compose down -v" +echo " docker compose down -v" echo "" diff --git a/helm/INSTALL.txt b/helm/INSTALL.txt index 05bfd5d33a..5f625a238c 100644 --- a/helm/INSTALL.txt +++ b/helm/INSTALL.txt @@ -1,4 +1,4 @@ -MEMORA HELM CHART INSTALLATION GUIDE +HINDSIGHT HELM CHART INSTALLATION GUIDE ===================================== PREREQUISITES @@ -13,42 +13,42 @@ BASIC INSTALLATION 1. Install with default values (requires external PostgreSQL): - helm install memora ./memora \ + helm install hindsight ./hindsight \ --set postgresql.external.host=your-postgres-host \ --set postgresql.external.password=your-password \ --set api.secrets.MEMORY_LLM_API_KEY=your-api-key 2. Install with custom values file: - helm install memora ./memora -f memora/values-production.yaml + helm install hindsight ./hindsight -f hindsight/values-production.yaml 3. Install in a specific namespace: - kubectl create namespace memora - helm install memora ./memora -n memora + kubectl create namespace hindsight + helm install hindsight ./hindsight -n hindsight CONFIGURATION OPTIONS --------------------- Development setup (using values-development.yaml): - helm install memora ./memora -f memora/values-development.yaml + helm install hindsight ./hindsight -f hindsight/values-development.yaml Production setup (using values-production.yaml): - helm install memora ./memora -f memora/values-production.yaml + helm install hindsight ./hindsight -f hindsight/values-production.yaml Custom LLM provider: - helm install memora ./memora \ + helm install hindsight ./hindsight \ --set api.env.MEMORY_LLM_PROVIDER=openai \ --set api.env.MEMORY_LLM_MODEL=gpt-4 \ --set api.secrets.MEMORY_LLM_API_KEY=sk-your-key Enable ingress: - helm install memora ./memora \ + helm install hindsight ./hindsight \ --set ingress.enabled=true \ - --set ingress.hosts[0].host=memora.example.com + --set ingress.hosts[0].host=hindsight.example.com Enable autoscaling: - helm install memora ./memora \ + helm install hindsight ./hindsight \ --set autoscaling.enabled=true \ --set autoscaling.minReplicas=2 \ --set autoscaling.maxReplicas=10 @@ -57,43 +57,43 @@ UPGRADE ------- Upgrade existing installation: - helm upgrade memora ./memora + helm upgrade hindsight ./hindsight Upgrade with new values: - helm upgrade memora ./memora -f memora/values-production.yaml + helm upgrade hindsight ./hindsight -f hindsight/values-production.yaml UNINSTALL --------- Remove the Helm release: - helm uninstall memora + helm uninstall hindsight Remove with namespace: - helm uninstall memora -n memora + helm uninstall hindsight -n hindsight TESTING ------- Test the installation with dry-run: - helm install memora ./memora --dry-run --debug + helm install hindsight ./hindsight --dry-run --debug Validate templates: - helm template memora ./memora + helm template hindsight ./hindsight Lint the chart: - helm lint ./memora + helm lint ./hindsight ACCESSING THE SERVICES ---------------------- Port-forward control plane: - kubectl port-forward svc/memora-control-plane 3000:3000 + kubectl port-forward svc/hindsight-control-plane 3000:3000 Port-forward API: - kubectl port-forward svc/memora-api 8080:8080 + kubectl port-forward svc/hindsight-api 8888:8888 Get service URLs: - helm status memora + helm status hindsight DATABASE INITIALIZATION ----------------------- @@ -102,16 +102,16 @@ NOTE: Database migrations now run automatically when the API service starts. You typically don't need to run migrations manually. If you want to pre-initialize the database before deploying (optional): - kubectl run memora-init --rm -it --restart=Never \ - --image=memora/api:latest \ - --env="DATABASE_URL=postgresql://user:pass@host:5432/memora" \ - -- python -c "from memora.migrations import run_migrations; run_migrations()" + kubectl run hindsight-init --rm -it --restart=Never \ + --image=hindsight/api:latest \ + --env="DATABASE_URL=postgresql://user:pass@host:5432/hindsight" \ + -- python -c "from hindsight.migrations import run_migrations; run_migrations()" TROUBLESHOOTING --------------- Check pod status: - kubectl get pods -l app.kubernetes.io/name=memora + kubectl get pods -l app.kubernetes.io/name=hindsight View logs for API: kubectl logs -l app.kubernetes.io/component=api @@ -123,8 +123,8 @@ Describe a pod: kubectl describe pod Check configuration: - kubectl get configmap memora-config -o yaml - kubectl get secret memora-secret -o yaml + kubectl get configmap hindsight-config -o yaml + kubectl get secret hindsight-secret -o yaml NOTES ----- diff --git a/helm/memora/.helmignore b/helm/hindsight/.helmignore similarity index 100% rename from helm/memora/.helmignore rename to helm/hindsight/.helmignore diff --git a/helm/hindsight/Chart.yaml b/helm/hindsight/Chart.yaml new file mode 100644 index 0000000000..5f050c9793 --- /dev/null +++ b/helm/hindsight/Chart.yaml @@ -0,0 +1,13 @@ +apiVersion: v2 +name: hindsight +description: A Helm chart for Hindsight - temporal-semantic-entity memory system for AI agents +type: application +version: 0.0.7 +appVersion: "0.0.7" +keywords: + - ai + - memory + - llm + - agents +maintainers: + - name: Hindsight Team diff --git a/helm/memora/templates/NOTES.txt b/helm/hindsight/templates/NOTES.txt similarity index 79% rename from helm/memora/templates/NOTES.txt rename to helm/hindsight/templates/NOTES.txt index 141170e3f6..fd9aec4a70 100644 --- a/helm/memora/templates/NOTES.txt +++ b/helm/hindsight/templates/NOTES.txt @@ -18,13 +18,13 @@ The application is accessible via the following URL(s): 1. Get the Control Plane URL by running these commands: {{- if contains "NodePort" .Values.controlPlane.service.type }} - export NODE_PORT=$(kubectl get --namespace {{ .Release.Namespace }} -o jsonpath="{.spec.ports[0].nodePort}" services {{ include "memora.fullname" . }}-control-plane) + export NODE_PORT=$(kubectl get --namespace {{ .Release.Namespace }} -o jsonpath="{.spec.ports[0].nodePort}" services {{ include "hindsight.fullname" . }}-control-plane) export NODE_IP=$(kubectl get nodes --namespace {{ .Release.Namespace }} -o jsonpath="{.items[0].status.addresses[0].address}") echo "Control Plane URL: http://$NODE_IP:$NODE_PORT" {{- else if contains "LoadBalancer" .Values.controlPlane.service.type }} NOTE: It may take a few minutes for the LoadBalancer IP to be available. - You can watch the status by running 'kubectl get --namespace {{ .Release.Namespace }} svc -w {{ include "memora.fullname" . }}-control-plane' - export SERVICE_IP=$(kubectl get svc --namespace {{ .Release.Namespace }} {{ include "memora.fullname" . }}-control-plane --template "{{"{{ range (index .status.loadBalancer.ingress 0) }}{{.}}{{ end }}"}}") + You can watch the status by running 'kubectl get --namespace {{ .Release.Namespace }} svc -w {{ include "hindsight.fullname" . }}-control-plane' + export SERVICE_IP=$(kubectl get svc --namespace {{ .Release.Namespace }} {{ include "hindsight.fullname" . }}-control-plane --template "{{"{{ range (index .status.loadBalancer.ingress 0) }}{{.}}{{ end }}"}}") echo "Control Plane URL: http://$SERVICE_IP:{{ .Values.controlPlane.service.port }}" {{- else if contains "ClusterIP" .Values.controlPlane.service.type }} export POD_NAME=$(kubectl get pods --namespace {{ .Release.Namespace }} -l "app.kubernetes.io/component=control-plane,app.kubernetes.io/instance={{ .Release.Name }}" -o jsonpath="{.items[0].metadata.name}") @@ -35,19 +35,19 @@ The application is accessible via the following URL(s): 2. Get the API URL by running these commands: {{- if contains "NodePort" .Values.api.service.type }} - export NODE_PORT=$(kubectl get --namespace {{ .Release.Namespace }} -o jsonpath="{.spec.ports[0].nodePort}" services {{ include "memora.fullname" . }}-api) + export NODE_PORT=$(kubectl get --namespace {{ .Release.Namespace }} -o jsonpath="{.spec.ports[0].nodePort}" services {{ include "hindsight.fullname" . }}-api) export NODE_IP=$(kubectl get nodes --namespace {{ .Release.Namespace }} -o jsonpath="{.items[0].status.addresses[0].address}") echo "API URL: http://$NODE_IP:$NODE_PORT" {{- else if contains "LoadBalancer" .Values.api.service.type }} NOTE: It may take a few minutes for the LoadBalancer IP to be available. - You can watch the status by running 'kubectl get --namespace {{ .Release.Namespace }} svc -w {{ include "memora.fullname" . }}-api' - export SERVICE_IP=$(kubectl get svc --namespace {{ .Release.Namespace }} {{ include "memora.fullname" . }}-api --template "{{"{{ range (index .status.loadBalancer.ingress 0) }}{{.}}{{ end }}"}}") + You can watch the status by running 'kubectl get --namespace {{ .Release.Namespace }} svc -w {{ include "hindsight.fullname" . }}-api' + export SERVICE_IP=$(kubectl get svc --namespace {{ .Release.Namespace }} {{ include "hindsight.fullname" . }}-api --template "{{"{{ range (index .status.loadBalancer.ingress 0) }}{{.}}{{ end }}"}}") echo "API URL: http://$SERVICE_IP:{{ .Values.api.service.port }}" {{- else if contains "ClusterIP" .Values.api.service.type }} export POD_NAME=$(kubectl get pods --namespace {{ .Release.Namespace }} -l "app.kubernetes.io/component=api,app.kubernetes.io/instance={{ .Release.Name }}" -o jsonpath="{.items[0].metadata.name}") export CONTAINER_PORT=$(kubectl get pod --namespace {{ .Release.Namespace }} $POD_NAME -o jsonpath="{.spec.containers[0].ports[0].containerPort}") - echo "API URL: http://127.0.0.1:8080" - kubectl --namespace {{ .Release.Namespace }} port-forward $POD_NAME 8080:$CONTAINER_PORT + echo "API URL: http://127.0.0.1:8888" + kubectl --namespace {{ .Release.Namespace }} port-forward $POD_NAME 8888:$CONTAINER_PORT {{- end }} {{- end }} @@ -62,10 +62,10 @@ Please ensure that: Database migrations run automatically when the API service starts. If you want to pre-initialize the database before deploying (optional): - kubectl run --namespace {{ .Release.Namespace }} memora-init --rm -it --restart=Never \ + kubectl run --namespace {{ .Release.Namespace }} hindsight-init --rm -it --restart=Never \ --image={{ .Values.api.image.repository }}:{{ .Values.api.image.tag }} \ - --env="DATABASE_URL={{ include "memora.databaseUrl" . }}" \ - -- python -c "from memora.migrations import run_migrations; run_migrations()" + --env="DATABASE_URL={{ include "hindsight.databaseUrl" . }}" \ + -- python -c "from hindsight.migrations import run_migrations; run_migrations()" {{- end }} -For more information, visit: https://github.com/yourusername/memora +For more information, visit: https://github.com/yourusername/hindsight diff --git a/helm/memora/templates/_helpers.tpl b/helm/hindsight/templates/_helpers.tpl similarity index 100% rename from helm/memora/templates/_helpers.tpl rename to helm/hindsight/templates/_helpers.tpl diff --git a/helm/memora/templates/api-deployment.yaml b/helm/hindsight/templates/api-deployment.yaml similarity index 70% rename from helm/memora/templates/api-deployment.yaml rename to helm/hindsight/templates/api-deployment.yaml index 893940382a..441777c2b2 100644 --- a/helm/memora/templates/api-deployment.yaml +++ b/helm/hindsight/templates/api-deployment.yaml @@ -2,16 +2,16 @@ apiVersion: apps/v1 kind: Deployment metadata: - name: {{ include "memora.fullname" . }}-api + name: {{ include "hindsight.fullname" . }}-api labels: - {{- include "memora.api.labels" . | nindent 4 }} + {{- include "hindsight.api.labels" . | nindent 4 }} spec: {{- if not .Values.autoscaling.enabled }} replicas: {{ .Values.api.replicaCount }} {{- end }} selector: matchLabels: - {{- include "memora.api.selectorLabels" . | nindent 6 }} + {{- include "hindsight.api.selectorLabels" . | nindent 6 }} template: metadata: annotations: @@ -21,10 +21,10 @@ spec: {{- toYaml . | nindent 8 }} {{- end }} labels: - {{- include "memora.api.selectorLabels" . | nindent 8 }} + {{- include "hindsight.api.selectorLabels" . | nindent 8 }} spec: {{- if .Values.serviceAccount.create }} - serviceAccountName: {{ include "memora.serviceAccountName" . }} + serviceAccountName: {{ include "hindsight.serviceAccountName" . }} {{- end }} securityContext: {{- toYaml .Values.podSecurityContext | nindent 8 }} @@ -39,37 +39,37 @@ spec: containerPort: {{ .Values.api.service.targetPort }} protocol: TCP env: - - name: MEMORA_API_DATABASE_URL - value: {{ include "memora.databaseUrl" . | quote }} + - name: HINDSIGHT_API_DATABASE_URL + value: {{ include "hindsight.databaseUrl" . | quote }} {{- if not .Values.postgresql.enabled }} - name: POSTGRES_PASSWORD valueFrom: secretKeyRef: - name: {{ include "memora.fullname" . }}-secret + name: {{ include "hindsight.fullname" . }}-secret key: postgres-password {{- end }} - - name: MEMORA_API_LLM_PROVIDER + - name: HINDSIGHT_API_LLM_PROVIDER valueFrom: configMapKeyRef: - name: {{ include "memora.fullname" . }}-config + name: {{ include "hindsight.fullname" . }}-config key: llm-provider - - name: MEMORA_API_LLM_MODEL + - name: HINDSIGHT_API_LLM_MODEL valueFrom: configMapKeyRef: - name: {{ include "memora.fullname" . }}-config + name: {{ include "hindsight.fullname" . }}-config key: llm-model - {{- if and .Values.api.secrets (hasKey .Values.api.secrets "MEMORA_API_LLM_API_KEY") }} - - name: MEMORA_API_LLM_API_KEY + {{- if and .Values.api.secrets (hasKey .Values.api.secrets "HINDSIGHT_API_LLM_API_KEY") }} + - name: HINDSIGHT_API_LLM_API_KEY valueFrom: secretKeyRef: - name: {{ include "memora.fullname" . }}-secret + name: {{ include "hindsight.fullname" . }}-secret key: llm-api-key {{- end }} - {{- if and .Values.api.secrets (hasKey .Values.api.secrets "MEMORA_API_LLM_BASE_URL") }} - - name: MEMORA_API_LLM_BASE_URL + {{- if and .Values.api.secrets (hasKey .Values.api.secrets "HINDSIGHT_API_LLM_BASE_URL") }} + - name: HINDSIGHT_API_LLM_BASE_URL valueFrom: secretKeyRef: - name: {{ include "memora.fullname" . }}-secret + name: {{ include "hindsight.fullname" . }}-secret key: llm-base-url {{- end }} livenessProbe: diff --git a/helm/memora/templates/api-service.yaml b/helm/hindsight/templates/api-service.yaml similarity index 59% rename from helm/memora/templates/api-service.yaml rename to helm/hindsight/templates/api-service.yaml index ecfa9dd6f5..e2a5f88953 100644 --- a/helm/memora/templates/api-service.yaml +++ b/helm/hindsight/templates/api-service.yaml @@ -2,9 +2,9 @@ apiVersion: v1 kind: Service metadata: - name: {{ include "memora.fullname" . }}-api + name: {{ include "hindsight.fullname" . }}-api labels: - {{- include "memora.api.labels" . | nindent 4 }} + {{- include "hindsight.api.labels" . | nindent 4 }} spec: type: {{ .Values.api.service.type }} ports: @@ -13,5 +13,5 @@ spec: protocol: TCP name: http selector: - {{- include "memora.api.selectorLabels" . | nindent 4 }} + {{- include "hindsight.api.selectorLabels" . | nindent 4 }} {{- end }} diff --git a/helm/hindsight/templates/configmap.yaml b/helm/hindsight/templates/configmap.yaml new file mode 100644 index 0000000000..ccd2036912 --- /dev/null +++ b/helm/hindsight/templates/configmap.yaml @@ -0,0 +1,15 @@ +apiVersion: v1 +kind: ConfigMap +metadata: + name: {{ include "hindsight.fullname" . }}-config + labels: + {{- include "hindsight.labels" . | nindent 4 }} +data: + # API configuration + llm-provider: {{ .Values.api.env.HINDSIGHT_API_LLM_PROVIDER | quote }} + llm-model: {{ .Values.api.env.HINDSIGHT_API_LLM_MODEL | quote }} + + # Control plane configuration + node-env: {{ .Values.controlPlane.env.NODE_ENV | quote }} + hostname: {{ .Values.controlPlane.env.HINDSIGHT_CP_HOSTNAME | quote }} + control-plane-port: {{ .Values.controlPlane.env.HINDSIGHT_CP_PORT | quote }} diff --git a/helm/memora/templates/controlplane-deployment.yaml b/helm/hindsight/templates/controlplane-deployment.yaml similarity index 73% rename from helm/memora/templates/controlplane-deployment.yaml rename to helm/hindsight/templates/controlplane-deployment.yaml index 0890da4b68..d11616c14d 100644 --- a/helm/memora/templates/controlplane-deployment.yaml +++ b/helm/hindsight/templates/controlplane-deployment.yaml @@ -2,16 +2,16 @@ apiVersion: apps/v1 kind: Deployment metadata: - name: {{ include "memora.fullname" . }}-control-plane + name: {{ include "hindsight.fullname" . }}-control-plane labels: - {{- include "memora.controlPlane.labels" . | nindent 4 }} + {{- include "hindsight.controlPlane.labels" . | nindent 4 }} spec: {{- if not .Values.autoscaling.enabled }} replicas: {{ .Values.controlPlane.replicaCount }} {{- end }} selector: matchLabels: - {{- include "memora.controlPlane.selectorLabels" . | nindent 6 }} + {{- include "hindsight.controlPlane.selectorLabels" . | nindent 6 }} template: metadata: annotations: @@ -20,10 +20,10 @@ spec: {{- toYaml . | nindent 8 }} {{- end }} labels: - {{- include "memora.controlPlane.selectorLabels" . | nindent 8 }} + {{- include "hindsight.controlPlane.selectorLabels" . | nindent 8 }} spec: {{- if .Values.serviceAccount.create }} - serviceAccountName: {{ include "memora.serviceAccountName" . }} + serviceAccountName: {{ include "hindsight.serviceAccountName" . }} {{- end }} securityContext: {{- toYaml .Values.podSecurityContext | nindent 8 }} @@ -41,20 +41,20 @@ spec: - name: NODE_ENV valueFrom: configMapKeyRef: - name: {{ include "memora.fullname" . }}-config + name: {{ include "hindsight.fullname" . }}-config key: node-env - - name: MEMORA_CP_HOSTNAME + - name: HINDSIGHT_CP_HOSTNAME valueFrom: configMapKeyRef: - name: {{ include "memora.fullname" . }}-config + name: {{ include "hindsight.fullname" . }}-config key: hostname - - name: MEMORA_CP_PORT + - name: HINDSIGHT_CP_PORT valueFrom: configMapKeyRef: - name: {{ include "memora.fullname" . }}-config + name: {{ include "hindsight.fullname" . }}-config key: control-plane-port - - name: MEMORA_CP_DATAPLANE_API_URL - value: {{ include "memora.apiUrl" . | quote }} + - name: HINDSIGHT_CP_DATAPLANE_API_URL + value: {{ include "hindsight.apiUrl" . | quote }} livenessProbe: {{- toYaml .Values.controlPlane.livenessProbe | nindent 10 }} readinessProbe: diff --git a/helm/memora/templates/controlplane-service.yaml b/helm/hindsight/templates/controlplane-service.yaml similarity index 58% rename from helm/memora/templates/controlplane-service.yaml rename to helm/hindsight/templates/controlplane-service.yaml index 87ac76009c..a8e601cb69 100644 --- a/helm/memora/templates/controlplane-service.yaml +++ b/helm/hindsight/templates/controlplane-service.yaml @@ -2,9 +2,9 @@ apiVersion: v1 kind: Service metadata: - name: {{ include "memora.fullname" . }}-control-plane + name: {{ include "hindsight.fullname" . }}-control-plane labels: - {{- include "memora.controlPlane.labels" . | nindent 4 }} + {{- include "hindsight.controlPlane.labels" . | nindent 4 }} spec: type: {{ .Values.controlPlane.service.type }} ports: @@ -13,5 +13,5 @@ spec: protocol: TCP name: http selector: - {{- include "memora.controlPlane.selectorLabels" . | nindent 4 }} + {{- include "hindsight.controlPlane.selectorLabels" . | nindent 4 }} {{- end }} diff --git a/helm/memora/templates/hpa.yaml b/helm/hindsight/templates/hpa.yaml similarity index 83% rename from helm/memora/templates/hpa.yaml rename to helm/hindsight/templates/hpa.yaml index bfb8739491..97b16888af 100644 --- a/helm/memora/templates/hpa.yaml +++ b/helm/hindsight/templates/hpa.yaml @@ -3,14 +3,14 @@ apiVersion: autoscaling/v2 kind: HorizontalPodAutoscaler metadata: - name: {{ include "memora.fullname" . }}-api + name: {{ include "hindsight.fullname" . }}-api labels: - {{- include "memora.api.labels" . | nindent 4 }} + {{- include "hindsight.api.labels" . | nindent 4 }} spec: scaleTargetRef: apiVersion: apps/v1 kind: Deployment - name: {{ include "memora.fullname" . }}-api + name: {{ include "hindsight.fullname" . }}-api minReplicas: {{ .Values.autoscaling.minReplicas }} maxReplicas: {{ .Values.autoscaling.maxReplicas }} metrics: @@ -34,14 +34,14 @@ spec: apiVersion: autoscaling/v2 kind: HorizontalPodAutoscaler metadata: - name: {{ include "memora.fullname" . }}-control-plane + name: {{ include "hindsight.fullname" . }}-control-plane labels: - {{- include "memora.controlPlane.labels" . | nindent 4 }} + {{- include "hindsight.controlPlane.labels" . | nindent 4 }} spec: scaleTargetRef: apiVersion: apps/v1 kind: Deployment - name: {{ include "memora.fullname" . }}-control-plane + name: {{ include "hindsight.fullname" . }}-control-plane minReplicas: {{ .Values.autoscaling.minReplicas }} maxReplicas: {{ .Values.autoscaling.maxReplicas }} metrics: diff --git a/helm/memora/templates/ingress.yaml b/helm/hindsight/templates/ingress.yaml similarity index 82% rename from helm/memora/templates/ingress.yaml rename to helm/hindsight/templates/ingress.yaml index 81905e137f..fdbe17d22b 100644 --- a/helm/memora/templates/ingress.yaml +++ b/helm/hindsight/templates/ingress.yaml @@ -2,9 +2,9 @@ apiVersion: networking.k8s.io/v1 kind: Ingress metadata: - name: {{ include "memora.fullname" . }} + name: {{ include "hindsight.fullname" . }} labels: - {{- include "memora.labels" . | nindent 4 }} + {{- include "hindsight.labels" . | nindent 4 }} {{- with .Values.ingress.annotations }} annotations: {{- toYaml . | nindent 4 }} @@ -34,11 +34,11 @@ spec: backend: service: {{- if eq .service "api" }} - name: {{ include "memora.fullname" $ }}-api + name: {{ include "hindsight.fullname" $ }}-api port: number: {{ $.Values.api.service.port }} {{- else if eq .service "controlPlane" }} - name: {{ include "memora.fullname" $ }}-control-plane + name: {{ include "hindsight.fullname" $ }}-control-plane port: number: {{ $.Values.controlPlane.service.port }} {{- end }} diff --git a/helm/memora/templates/secret.yaml b/helm/hindsight/templates/secret.yaml similarity index 85% rename from helm/memora/templates/secret.yaml rename to helm/hindsight/templates/secret.yaml index 89433dda07..243fe3b859 100644 --- a/helm/memora/templates/secret.yaml +++ b/helm/hindsight/templates/secret.yaml @@ -1,9 +1,9 @@ apiVersion: v1 kind: Secret metadata: - name: {{ include "memora.fullname" . }}-secret + name: {{ include "hindsight.fullname" . }}-secret labels: - {{- include "memora.labels" . | nindent 4 }} + {{- include "hindsight.labels" . | nindent 4 }} type: Opaque data: {{- if and .Values.api.secrets (hasKey .Values.api.secrets "MEMORY_LLM_API_KEY") }} diff --git a/helm/memora/templates/serviceaccount.yaml b/helm/hindsight/templates/serviceaccount.yaml similarity index 66% rename from helm/memora/templates/serviceaccount.yaml rename to helm/hindsight/templates/serviceaccount.yaml index fb6d1b0955..6efb531620 100644 --- a/helm/memora/templates/serviceaccount.yaml +++ b/helm/hindsight/templates/serviceaccount.yaml @@ -2,9 +2,9 @@ apiVersion: v1 kind: ServiceAccount metadata: - name: {{ include "memora.serviceAccountName" . }} + name: {{ include "hindsight.serviceAccountName" . }} labels: - {{- include "memora.labels" . | nindent 4 }} + {{- include "hindsight.labels" . | nindent 4 }} {{- with .Values.serviceAccount.annotations }} annotations: {{- toYaml . | nindent 4 }} diff --git a/helm/memora/values.yaml b/helm/hindsight/values.yaml similarity index 83% rename from helm/memora/values.yaml rename to helm/hindsight/values.yaml index bc3be3f72c..687ac84d55 100644 --- a/helm/memora/values.yaml +++ b/helm/hindsight/values.yaml @@ -1,4 +1,4 @@ -# Default values for memora +# Default values for hindsight # Global settings replicaCount: 1 @@ -8,14 +8,14 @@ api: enabled: true replicaCount: 1 image: - repository: memora/api + repository: hindsight/api pullPolicy: IfNotPresent tag: "latest" service: type: ClusterIP - port: 8080 - targetPort: 8080 + port: 8888 + targetPort: 8888 # Resource limits and requests resources: @@ -30,7 +30,7 @@ api: livenessProbe: httpGet: path: / - port: 8080 + port: 8888 initialDelaySeconds: 30 periodSeconds: 10 timeoutSeconds: 5 @@ -39,7 +39,7 @@ api: readinessProbe: httpGet: path: / - port: 8080 + port: 8888 initialDelaySeconds: 10 periodSeconds: 5 timeoutSeconds: 3 @@ -47,20 +47,20 @@ api: # Environment variables env: - MEMORA_API_LLM_PROVIDER: "groq" - MEMORA_API_LLM_MODEL: "openai/gpt-oss-120b" + HINDSIGHT_API_LLM_PROVIDER: "groq" + HINDSIGHT_API_LLM_MODEL: "openai/gpt-oss-120b" # Secret environment variables secrets: - # MEMORA_API_LLM_API_KEY: "your-api-key" - # MEMORA_API_LLM_BASE_URL: "https://api.groq.com/openai/v1" + # HINDSIGHT_API_LLM_API_KEY: "your-api-key" + # HINDSIGHT_API_LLM_BASE_URL: "https://api.groq.com/openai/v1" # Image settings for control plane controlPlane: enabled: true replicaCount: 1 image: - repository: memora/memora-control-plane + repository: hindsight/hindsight-control-plane pullPolicy: IfNotPresent tag: "latest" @@ -100,8 +100,8 @@ controlPlane: # Environment variables env: NODE_ENV: "production" - MEMORA_CP_HOSTNAME: "0.0.0.0" - MEMORA_CP_PORT: "3000" + HINDSIGHT_CP_HOSTNAME: "0.0.0.0" + HINDSIGHT_CP_PORT: "3000" # PostgreSQL configuration postgresql: @@ -113,8 +113,8 @@ postgresql: external: host: "postgresql" port: 5432 - database: "memora" - username: "memora" + database: "hindsight" + username: "hindsight" # Password should be provided via secret # password: "" @@ -130,7 +130,7 @@ ingress: # nginx.ingress.kubernetes.io/ssl-redirect: "true" hosts: - - host: memora.example.com + - host: hindsight.example.com paths: - path: / pathType: Prefix @@ -140,9 +140,9 @@ ingress: service: api tls: [] - # - secretName: memora-tls + # - secretName: hindsight-tls # hosts: - # - memora.example.com + # - hindsight.example.com # Service Account serviceAccount: diff --git a/helm/memora/Chart.yaml b/helm/memora/Chart.yaml deleted file mode 100644 index 160423380c..0000000000 --- a/helm/memora/Chart.yaml +++ /dev/null @@ -1,13 +0,0 @@ -apiVersion: v2 -name: memora -description: A Helm chart for Memora - temporal-semantic-entity memory system for AI agents -type: application -version: 0.0.7 -appVersion: "0.0.7" -keywords: - - ai - - memory - - llm - - agents -maintainers: - - name: Memora Team diff --git a/helm/memora/templates/configmap.yaml b/helm/memora/templates/configmap.yaml deleted file mode 100644 index bb7f2c59e1..0000000000 --- a/helm/memora/templates/configmap.yaml +++ /dev/null @@ -1,15 +0,0 @@ -apiVersion: v1 -kind: ConfigMap -metadata: - name: {{ include "memora.fullname" . }}-config - labels: - {{- include "memora.labels" . | nindent 4 }} -data: - # API configuration - llm-provider: {{ .Values.api.env.MEMORA_API_LLM_PROVIDER | quote }} - llm-model: {{ .Values.api.env.MEMORA_API_LLM_MODEL | quote }} - - # Control plane configuration - node-env: {{ .Values.controlPlane.env.NODE_ENV | quote }} - hostname: {{ .Values.controlPlane.env.MEMORA_CP_HOSTNAME | quote }} - control-plane-port: {{ .Values.controlPlane.env.MEMORA_CP_PORT | quote }} diff --git a/memora/README.md b/hindsight-api/README.md similarity index 100% rename from memora/README.md rename to hindsight-api/README.md diff --git a/memora/alembic/README b/hindsight-api/alembic/README similarity index 100% rename from memora/alembic/README rename to hindsight-api/alembic/README diff --git a/memora/alembic/env.py b/hindsight-api/alembic/env.py similarity index 89% rename from memora/alembic/env.py rename to hindsight-api/alembic/env.py index 8c71ffcc56..77b54d98ab 100644 --- a/memora/alembic/env.py +++ b/hindsight-api/alembic/env.py @@ -14,13 +14,13 @@ from dotenv import load_dotenv # Import your models here -from memora.models import Base +from hindsight_api.models import Base -# Load environment variables based on MEMORA_API_DATABASE_URL env var or default to local +# Load environment variables based on HINDSIGHT_API_DATABASE_URL env var or default to local def load_env(): """Load environment variables from .env""" - # Check if MEMORA_API_DATABASE_URL is already set (e.g., by CI/CD) - if os.getenv("MEMORA_API_DATABASE_URL"): + # Check if HINDSIGHT_API_DATABASE_URL is already set (e.g., by CI/CD) + if os.getenv("HINDSIGHT_API_DATABASE_URL"): return # Look for .env file in the parent directory (root of the workspace) @@ -58,11 +58,11 @@ def get_database_url() -> str: # Get database URL from config (set programmatically) or environment database_url = config.get_main_option("sqlalchemy.url") if not database_url: - database_url = os.getenv("MEMORA_API_DATABASE_URL") + database_url = os.getenv("HINDSIGHT_API_DATABASE_URL") if not database_url: raise ValueError( "Database URL not found. " - "Set MEMORA_API_DATABASE_URL environment variable or pass database_url to run_migrations()." + "Set HINDSIGHT_API_DATABASE_URL environment variable or pass database_url to run_migrations()." ) # For migrations, use psycopg2 (sync driver) to avoid pgbouncer prepared statement issues diff --git a/memora/alembic/script.py.mako b/hindsight-api/alembic/script.py.mako similarity index 100% rename from memora/alembic/script.py.mako rename to hindsight-api/alembic/script.py.mako diff --git a/memora/alembic/versions/01f989db9079_fix_memory_links_entity_id_to_be_.py b/hindsight-api/alembic/versions/01f989db9079_fix_memory_links_entity_id_to_be_.py similarity index 100% rename from memora/alembic/versions/01f989db9079_fix_memory_links_entity_id_to_be_.py rename to hindsight-api/alembic/versions/01f989db9079_fix_memory_links_entity_id_to_be_.py diff --git a/memora/alembic/versions/0e96398aae9e_add_async_operations_table.py b/hindsight-api/alembic/versions/0e96398aae9e_add_async_operations_table.py similarity index 100% rename from memora/alembic/versions/0e96398aae9e_add_async_operations_table.py rename to hindsight-api/alembic/versions/0e96398aae9e_add_async_operations_table.py diff --git a/memora/alembic/versions/1680fc9768b4_add_agents_table.py b/hindsight-api/alembic/versions/1680fc9768b4_add_agents_table.py similarity index 100% rename from memora/alembic/versions/1680fc9768b4_add_agents_table.py rename to hindsight-api/alembic/versions/1680fc9768b4_add_agents_table.py diff --git a/memora/alembic/versions/1a35a4fa1950_add_bm25_fulltext_search.py b/hindsight-api/alembic/versions/1a35a4fa1950_add_bm25_fulltext_search.py similarity index 100% rename from memora/alembic/versions/1a35a4fa1950_add_bm25_fulltext_search.py rename to hindsight-api/alembic/versions/1a35a4fa1950_add_bm25_fulltext_search.py diff --git a/memora/alembic/versions/217b2227771f_merge_agents_and_temporal_ranges_.py b/hindsight-api/alembic/versions/217b2227771f_merge_agents_and_temporal_ranges_.py similarity index 100% rename from memora/alembic/versions/217b2227771f_merge_agents_and_temporal_ranges_.py rename to hindsight-api/alembic/versions/217b2227771f_merge_agents_and_temporal_ranges_.py diff --git a/memora/alembic/versions/2a76a5bc2f09_add_status_and_error_to_async_operations.py b/hindsight-api/alembic/versions/2a76a5bc2f09_add_status_and_error_to_async_operations.py similarity index 100% rename from memora/alembic/versions/2a76a5bc2f09_add_status_and_error_to_async_operations.py rename to hindsight-api/alembic/versions/2a76a5bc2f09_add_status_and_error_to_async_operations.py diff --git a/memora/alembic/versions/3b9c4d8e7f21_add_name_to_agents.py b/hindsight-api/alembic/versions/3b9c4d8e7f21_add_name_to_agents.py similarity index 100% rename from memora/alembic/versions/3b9c4d8e7f21_add_name_to_agents.py rename to hindsight-api/alembic/versions/3b9c4d8e7f21_add_name_to_agents.py diff --git a/memora/alembic/versions/4a8b3c5d6e7f_add_metadata_to_memory_units.py b/hindsight-api/alembic/versions/4a8b3c5d6e7f_add_metadata_to_memory_units.py similarity index 100% rename from memora/alembic/versions/4a8b3c5d6e7f_add_metadata_to_memory_units.py rename to hindsight-api/alembic/versions/4a8b3c5d6e7f_add_metadata_to_memory_units.py diff --git a/memora/alembic/versions/8c55f5602451_remove_entity_type_column.py b/hindsight-api/alembic/versions/8c55f5602451_remove_entity_type_column.py similarity index 100% rename from memora/alembic/versions/8c55f5602451_remove_entity_type_column.py rename to hindsight-api/alembic/versions/8c55f5602451_remove_entity_type_column.py diff --git a/memora/alembic/versions/9d42e6f91234_add_temporal_ranges_to_memory_units.py b/hindsight-api/alembic/versions/9d42e6f91234_add_temporal_ranges_to_memory_units.py similarity index 100% rename from memora/alembic/versions/9d42e6f91234_add_temporal_ranges_to_memory_units.py rename to hindsight-api/alembic/versions/9d42e6f91234_add_temporal_ranges_to_memory_units.py diff --git a/memora/alembic/versions/af0413383b3e_initial_schema.py b/hindsight-api/alembic/versions/af0413383b3e_initial_schema.py similarity index 100% rename from memora/alembic/versions/af0413383b3e_initial_schema.py rename to hindsight-api/alembic/versions/af0413383b3e_initial_schema.py diff --git a/memora/memora/__init__.py b/hindsight-api/hindsight_api/__init__.py similarity index 66% rename from memora/memora/__init__.py rename to hindsight-api/hindsight_api/__init__.py index 191fd1b082..559d28c57c 100644 --- a/memora/memora/__init__.py +++ b/hindsight-api/hindsight_api/__init__.py @@ -3,8 +3,8 @@ Temporal + Semantic Memory Architecture using PostgreSQL with pgvector. """ -from .temporal_semantic_memory import TemporalSemanticMemory -from .search_trace import ( +from .engine.memory_engine import MemoryEngine +from .engine.search_trace import ( SearchTrace, QueryInfo, EntryPoint, @@ -15,11 +15,12 @@ SearchSummary, SearchPhaseMetrics, ) -from .search_tracer import SearchTracer -from .embeddings import Embeddings, SentenceTransformersEmbeddings +from .engine.search_tracer import SearchTracer +from .engine.embeddings import Embeddings, SentenceTransformersEmbeddings +from .engine.llm_wrapper import LLMConfig __all__ = [ - "TemporalSemanticMemory", + "MemoryEngine", "SearchTrace", "SearchTracer", "QueryInfo", @@ -32,5 +33,6 @@ "SearchPhaseMetrics", "Embeddings", "SentenceTransformersEmbeddings", + "LLMConfig", ] __version__ = "0.1.0" diff --git a/memora/memora/api/__init__.py b/hindsight-api/hindsight_api/api/__init__.py similarity index 79% rename from memora/memora/api/__init__.py rename to hindsight-api/hindsight_api/api/__init__.py index d598b5db84..5868851dbf 100644 --- a/memora/memora/api/__init__.py +++ b/hindsight-api/hindsight_api/api/__init__.py @@ -1,5 +1,5 @@ """ -Unified API module for Memora. +Unified API module for Hindsight. Provides both HTTP REST API and MCP (Model Context Protocol) server. """ @@ -7,13 +7,13 @@ from typing import Optional from fastapi import FastAPI -from memora import TemporalSemanticMemory +from hindsight_api import MemoryEngine logger = logging.getLogger(__name__) def create_app( - memory: TemporalSemanticMemory, + memory: MemoryEngine, http_api_enabled: bool = True, mcp_api_enabled: bool = False, mcp_mount_path: str = "/mcp", @@ -21,10 +21,10 @@ def create_app( initialize_memory: bool = True ) -> FastAPI: """ - Create and configure the unified Memora API application. + Create and configure the unified Hindsight API application. Args: - memory: TemporalSemanticMemory instance (already initialized with required parameters) + memory: MemoryEngine instance (already initialized with required parameters) http_api_enabled: Whether to enable HTTP REST API endpoints (default: True) mcp_api_enabled: Whether to enable MCP server (default: False) mcp_mount_path: Path to mount MCP server (default: /mcp) @@ -56,7 +56,7 @@ def create_app( logger.info("HTTP REST API enabled") else: # Create minimal FastAPI app - app = FastAPI(title="Memora API", version="0.0.7") + app = FastAPI(title="Hindsight API", version="0.0.7") logger.info("HTTP REST API disabled") # Mount MCP server if enabled @@ -67,12 +67,12 @@ def create_app( # Create MCP server with shared memory instance mcp_server = create_mcp_server(memory=memory) - # Mount at specified path - app.mount(mcp_mount_path, mcp_server.sse_app()) - logger.info(f"MCP server enabled at {mcp_mount_path}/sse") + # Mount at specified path using http_app (modern non-SSE alternative) + app.mount(mcp_mount_path, mcp_server.http_app()) + logger.info(f"MCP server enabled at {mcp_mount_path}") except ImportError as e: logger.error(f"MCP server requested but dependencies not available: {e}") - logger.error("Install with: pip install memora[mcp]") + logger.error("Install with: pip install hindsight-api[mcp]") raise return app @@ -87,6 +87,8 @@ def create_app( BatchPutRequest, ThinkRequest, ThinkResponse, + CreateAgentRequest, + PersonalityTraits, ) __all__ = [ @@ -98,4 +100,6 @@ def create_app( "BatchPutRequest", "ThinkRequest", "ThinkResponse", + "CreateAgentRequest", + "PersonalityTraits", ] diff --git a/memora/memora/api/http.py b/hindsight-api/hindsight_api/api/http.py similarity index 82% rename from memora/memora/api/http.py rename to hindsight-api/hindsight_api/api/http.py index 9308ec9f45..9aec70eaa5 100644 --- a/memora/memora/api/http.py +++ b/hindsight-api/hindsight_api/api/http.py @@ -14,29 +14,41 @@ from fastapi import FastAPI, HTTPException, Query from fastapi.staticfiles import StaticFiles from fastapi.responses import FileResponse -from pydantic import BaseModel, Field +from pydantic import BaseModel, Field, ConfigDict -from memora import TemporalSemanticMemory +from hindsight_api import MemoryEngine +from hindsight_api.engine.db_utils import acquire_with_retry class MetadataFilter(BaseModel): """Filter for metadata fields. Matches records where (key=value) OR (key not set) when match_unset=True.""" + model_config = ConfigDict(json_schema_extra={ + "example": { + "key": "source", + "value": "slack", + "match_unset": True + } + }) + key: str = Field(description="Metadata key to filter on") value: Optional[str] = Field(default=None, description="Value to match. If None with match_unset=True, matches any record where key is not set.") match_unset: bool = Field(default=True, description="If True, also match records where this metadata key is not set") - class Config: - json_schema_extra = { - "example": { - "key": "source", - "value": "slack", - "match_unset": True - } - } - class SearchRequest(BaseModel): """Request model for search endpoint.""" + model_config = ConfigDict(json_schema_extra={ + "example": { + "query": "What did Alice say about machine learning?", + "fact_type": ["world", "agent"], + "thinking_budget": 100, + "max_tokens": 4096, + "trace": True, + "question_date": "2023-05-30T23:40:00", + "metadata_filter": [{"key": "source", "value": "slack", "match_unset": True}] + } + }) + query: str fact_type: Optional[List[str]] = None # List of fact types to search (defaults to all if not specified) thinking_budget: int = 100 @@ -45,19 +57,6 @@ class SearchRequest(BaseModel): question_date: Optional[str] = None # ISO format date string (e.g., "2023-05-30T23:40:00") metadata_filter: Optional[List[MetadataFilter]] = Field(default=None, description="Filter by metadata. Multiple filters are ANDed together.") - class Config: - json_schema_extra = { - "example": { - "query": "What did Alice say about machine learning?", - "fact_type": ["world", "agent"], - "thinking_budget": 100, - "max_tokens": 4096, - "trace": True, - "question_date": "2023-05-30T23:40:00", - "metadata_filter": [{"key": "source", "value": "slack", "match_unset": True}] - } - } - class SearchResult(BaseModel): """Single search result item.""" @@ -87,93 +86,100 @@ class SearchResult(BaseModel): class SearchResponse(BaseModel): """Response model for search endpoints.""" - results: List[SearchResult] - trace: Optional[Dict[str, Any]] = None - - class Config: - json_schema_extra = { - "example": { - "results": [ - { - "id": "123e4567-e89b-12d3-a456-426614174000", - "text": "Alice works at Google on the AI team", - "type": "world", - "context": "work info", - "event_date": "2024-01-15T10:30:00Z" - } - ], - "trace": { - "query": "What did Alice say about machine learning?", - "num_results": 1, - "time_seconds": 0.123 + model_config = ConfigDict(json_schema_extra={ + "example": { + "results": [ + { + "id": "123e4567-e89b-12d3-a456-426614174000", + "text": "Alice works at Google on the AI team", + "type": "world", + "context": "work info", + "event_date": "2024-01-15T10:30:00Z" } + ], + "trace": { + "query": "What did Alice say about machine learning?", + "num_results": 1, + "time_seconds": 0.123 } } + }) + + results: List[SearchResult] + trace: Optional[Dict[str, Any]] = None class MemoryItem(BaseModel): """Single memory item for batch put.""" + model_config = ConfigDict(json_schema_extra={ + "example": { + "content": "Alice mentioned she's working on a new ML model", + "event_date": "2024-01-15T10:30:00Z", + "context": "team meeting", + "metadata": {"source": "slack", "channel": "engineering"} + } + }) + content: str event_date: Optional[datetime] = None context: Optional[str] = None metadata: Optional[Dict[str, str]] = None - class Config: - json_schema_extra = { - "example": { - "content": "Alice mentioned she's working on a new ML model", - "event_date": "2024-01-15T10:30:00Z", - "context": "team meeting", - "metadata": {"source": "slack", "channel": "engineering"} - } - } - class BatchPutRequest(BaseModel): """Request model for batch put endpoint.""" + model_config = ConfigDict(json_schema_extra={ + "example": { + "items": [ + { + "content": "Alice works at Google", + "context": "work" + }, + { + "content": "Bob went hiking yesterday", + "event_date": "2024-01-15T10:00:00Z" + } + ], + "document_id": "conversation_123" + } + }) + items: List[MemoryItem] document_id: Optional[str] = None - class Config: - json_schema_extra = { - "example": { - "items": [ - { - "content": "Alice works at Google", - "context": "work" - }, - { - "content": "Bob went hiking yesterday", - "event_date": "2024-01-15T10:00:00Z" - } - ], - "document_id": "conversation_123" - } - } - class BatchPutResponse(BaseModel): """Response model for batch put endpoint.""" + model_config = ConfigDict(json_schema_extra={ + "example": { + "success": True, + "message": "Successfully stored 2 memory items", + "agent_id": "user123", + "document_id": "conversation_123", + "items_count": 2 + } + }) + success: bool message: str agent_id: str document_id: Optional[str] = None items_count: int - class Config: - json_schema_extra = { - "example": { - "success": True, - "message": "Successfully stored 2 memory items", - "agent_id": "user123", - "document_id": "conversation_123", - "items_count": 2 - } - } - class BatchPutAsyncResponse(BaseModel): """Response model for async batch put endpoint.""" + model_config = ConfigDict(json_schema_extra={ + "example": { + "success": True, + "message": "Batch put task queued for background processing", + "agent_id": "user123", + "document_id": "conversation_123", + "items_count": 2, + "queued": True + } + }) + success: bool message: str agent_id: str @@ -181,36 +187,23 @@ class BatchPutAsyncResponse(BaseModel): items_count: int queued: bool - class Config: - json_schema_extra = { - "example": { - "success": True, - "message": "Batch put task queued for background processing", - "agent_id": "user123", - "document_id": "conversation_123", - "items_count": 2, - "queued": True - } - } - class ThinkRequest(BaseModel): """Request model for think endpoint.""" + model_config = ConfigDict(json_schema_extra={ + "example": { + "query": "What do you think about artificial intelligence?", + "thinking_budget": 50, + "context": "This is for a research paper on AI ethics", + "metadata_filter": [{"key": "source", "value": "slack", "match_unset": True}] + } + }) + query: str thinking_budget: int = 50 context: Optional[str] = None metadata_filter: Optional[List[MetadataFilter]] = Field(default=None, description="Filter by metadata. Multiple filters are ANDed together.") - class Config: - json_schema_extra = { - "example": { - "query": "What do you think about artificial intelligence?", - "thinking_budget": 50, - "context": "This is for a research paper on AI ethics", - "metadata_filter": [{"key": "source", "value": "slack", "match_unset": True}] - } - } - class OpinionItem(BaseModel): """Model for an opinion with confidence score.""" @@ -220,67 +213,75 @@ class OpinionItem(BaseModel): class ThinkFact(BaseModel): """A fact used in think response.""" + model_config = ConfigDict(json_schema_extra={ + "example": { + "id": "123e4567-e89b-12d3-a456-426614174000", + "text": "AI is used in healthcare", + "type": "world", + "context": "healthcare discussion", + "event_date": "2024-01-15T10:30:00Z" + } + }) + id: Optional[str] = None text: str type: Optional[str] = None # fact type: world, agent, opinion context: Optional[str] = None event_date: Optional[str] = None - class Config: - json_schema_extra = { - "example": { - "id": "123e4567-e89b-12d3-a456-426614174000", - "text": "AI is used in healthcare", - "type": "world", - "context": "healthcare discussion", - "event_date": "2024-01-15T10:30:00Z" - } - } - class ThinkResponse(BaseModel): """Response model for think endpoint.""" + model_config = ConfigDict(json_schema_extra={ + "example": { + "text": "Based on my understanding, AI is a transformative technology...", + "based_on": [ + { + "id": "123", + "text": "AI is used in healthcare", + "type": "world" + }, + { + "id": "456", + "text": "I discussed AI applications last week", + "type": "agent" + } + ], + "new_opinions": [ + "AI has great potential when used responsibly" + ] + } + }) + text: str based_on: List[ThinkFact] = [] # Facts used to generate the response new_opinions: List[str] = [] # Simplified to list of opinion strings - class Config: - json_schema_extra = { - "example": { - "text": "Based on my understanding, AI is a transformative technology...", - "based_on": [ - { - "id": "123", - "text": "AI is used in healthcare", - "type": "world" - }, - { - "id": "456", - "text": "I discussed AI applications last week", - "type": "agent" - } - ], - "new_opinions": [ - "AI has great potential when used responsibly" - ] - } - } - class AgentsResponse(BaseModel): """Response model for agents list endpoint.""" - agents: List[str] - - class Config: - json_schema_extra = { - "example": { - "agents": ["user123", "agent_alice", "agent_bob"] - } + model_config = ConfigDict(json_schema_extra={ + "example": { + "agents": ["user123", "agent_alice", "agent_bob"] } + }) + + agents: List[str] class PersonalityTraits(BaseModel): """Personality traits based on Big Five model.""" + model_config = ConfigDict(json_schema_extra={ + "example": { + "openness": 0.8, + "conscientiousness": 0.6, + "extraversion": 0.5, + "agreeableness": 0.7, + "neuroticism": 0.3, + "bias_strength": 0.7 + } + }) + openness: float = Field(ge=0.0, le=1.0, description="Openness to experience (0-1)") conscientiousness: float = Field(ge=0.0, le=1.0, description="Conscientiousness (0-1)") extraversion: float = Field(ge=0.0, le=1.0, description="Extraversion (0-1)") @@ -288,43 +289,30 @@ class PersonalityTraits(BaseModel): neuroticism: float = Field(ge=0.0, le=1.0, description="Neuroticism (0-1)") bias_strength: float = Field(ge=0.0, le=1.0, description="How strongly personality influences opinions (0-1)") - class Config: - json_schema_extra = { - "example": { + +class AgentProfileResponse(BaseModel): + """Response model for agent profile.""" + model_config = ConfigDict(json_schema_extra={ + "example": { + "agent_id": "user123", + "name": "Alice", + "personality": { "openness": 0.8, "conscientiousness": 0.6, "extraversion": 0.5, "agreeableness": 0.7, "neuroticism": 0.3, "bias_strength": 0.7 - } + }, + "background": "I am a software engineer with 10 years of experience in startups" } + }) - -class AgentProfileResponse(BaseModel): - """Response model for agent profile.""" agent_id: str name: str personality: PersonalityTraits background: str - class Config: - json_schema_extra = { - "example": { - "agent_id": "user123", - "name": "Alice", - "personality": { - "openness": 0.8, - "conscientiousness": 0.6, - "extraversion": 0.5, - "agreeableness": 0.7, - "neuroticism": 0.3, - "bias_strength": 0.7 - }, - "background": "I am a software engineer with 10 years of experience in startups" - } - } - class UpdatePersonalityRequest(BaseModel): """Request model for updating personality traits.""" @@ -333,40 +321,38 @@ class UpdatePersonalityRequest(BaseModel): class AddBackgroundRequest(BaseModel): """Request model for adding/merging background information.""" + model_config = ConfigDict(json_schema_extra={ + "example": { + "content": "I was born in Texas", + "update_personality": True + } + }) + content: str = Field(description="New background information to add or merge") update_personality: bool = Field( default=True, description="If true, infer Big Five personality traits from the merged background (default: true)" ) - class Config: - json_schema_extra = { - "example": { - "content": "I was born in Texas", - "update_personality": True - } - } - class BackgroundResponse(BaseModel): """Response model for background update.""" - background: str - personality: Optional[PersonalityTraits] = None - - class Config: - json_schema_extra = { - "example": { - "background": "I was born in Texas. I am a software engineer with 10 years of experience.", - "personality": { - "openness": 0.7, - "conscientiousness": 0.6, - "extraversion": 0.5, - "agreeableness": 0.8, - "neuroticism": 0.4, - "bias_strength": 0.6 - } + model_config = ConfigDict(json_schema_extra={ + "example": { + "background": "I was born in Texas. I am a software engineer with 10 years of experience.", + "personality": { + "openness": 0.7, + "conscientiousness": 0.6, + "extraversion": 0.5, + "agreeableness": 0.8, + "neuroticism": 0.4, + "bias_strength": 0.6 } } + }) + + background: str + personality: Optional[PersonalityTraits] = None class AgentListItem(BaseModel): @@ -381,137 +367,144 @@ class AgentListItem(BaseModel): class AgentListResponse(BaseModel): """Response model for listing all agents.""" - agents: List[AgentListItem] - - class Config: - json_schema_extra = { - "example": { - "agents": [ - { - "agent_id": "user123", - "name": "Alice", - "personality": { - "openness": 0.5, - "conscientiousness": 0.5, - "extraversion": 0.5, - "agreeableness": 0.5, - "neuroticism": 0.5, - "bias_strength": 0.5 - }, - "background": "I am a software engineer", - "created_at": "2024-01-15T10:30:00Z", - "updated_at": "2024-01-16T14:20:00Z" - } - ] - } + model_config = ConfigDict(json_schema_extra={ + "example": { + "agents": [ + { + "agent_id": "user123", + "name": "Alice", + "personality": { + "openness": 0.5, + "conscientiousness": 0.5, + "extraversion": 0.5, + "agreeableness": 0.5, + "neuroticism": 0.5, + "bias_strength": 0.5 + }, + "background": "I am a software engineer", + "created_at": "2024-01-15T10:30:00Z", + "updated_at": "2024-01-16T14:20:00Z" + } + ] } + }) + + agents: List[AgentListItem] class CreateAgentRequest(BaseModel): """Request model for creating/updating an agent.""" + model_config = ConfigDict(json_schema_extra={ + "example": { + "name": "Alice", + "personality": { + "openness": 0.8, + "conscientiousness": 0.6, + "extraversion": 0.5, + "agreeableness": 0.7, + "neuroticism": 0.3, + "bias_strength": 0.7 + }, + "background": "I am a creative software engineer with 10 years of experience" + } + }) + name: Optional[str] = None personality: Optional[PersonalityTraits] = None background: Optional[str] = None - class Config: - json_schema_extra = { - "example": { - "name": "Alice", - "personality": { - "openness": 0.8, - "conscientiousness": 0.6, - "extraversion": 0.5, - "agreeableness": 0.7, - "neuroticism": 0.3, - "bias_strength": 0.7 - }, - "background": "I am a creative software engineer with 10 years of experience" - } - } - class GraphDataResponse(BaseModel): """Response model for graph data endpoint.""" + model_config = ConfigDict(json_schema_extra={ + "example": { + "nodes": [ + {"id": "1", "label": "Alice works at Google", "type": "world"}, + {"id": "2", "label": "Bob went hiking", "type": "world"} + ], + "edges": [ + {"from": "1", "to": "2", "type": "semantic", "weight": 0.8} + ], + "table_rows": [ + {"id": "abc12345...", "text": "Alice works at Google", "context": "Work info", "date": "2024-01-15 10:30", "entities": "Alice (PERSON), Google (ORGANIZATION)"} + ], + "total_units": 2 + } + }) + nodes: List[Dict[str, Any]] edges: List[Dict[str, Any]] table_rows: List[Dict[str, Any]] total_units: int - class Config: - json_schema_extra = { - "example": { - "nodes": [ - {"id": "1", "label": "Alice works at Google", "type": "world"}, - {"id": "2", "label": "Bob went hiking", "type": "world"} - ], - "edges": [ - {"from": "1", "to": "2", "type": "semantic", "weight": 0.8} - ], - "table_rows": [ - {"id": "abc12345...", "text": "Alice works at Google", "context": "Work info", "date": "2024-01-15 10:30", "entities": "Alice (PERSON), Google (ORGANIZATION)"} - ], - "total_units": 2 - } - } - class ListMemoryUnitsResponse(BaseModel): """Response model for list memory units endpoint.""" + model_config = ConfigDict(json_schema_extra={ + "example": { + "items": [ + { + "id": "550e8400-e29b-41d4-a716-446655440000", + "text": "Alice works at Google on the AI team", + "context": "Work conversation", + "date": "2024-01-15T10:30:00Z", + "fact_type": "world", + "entities": "Alice (PERSON), Google (ORGANIZATION)" + } + ], + "total": 150, + "limit": 100, + "offset": 0 + } + }) + items: List[Dict[str, Any]] total: int limit: int offset: int - class Config: - json_schema_extra = { - "example": { - "items": [ - { - "id": "550e8400-e29b-41d4-a716-446655440000", - "text": "Alice works at Google on the AI team", - "context": "Work conversation", - "date": "2024-01-15T10:30:00Z", - "fact_type": "world", - "entities": "Alice (PERSON), Google (ORGANIZATION)" - } - ], - "total": 150, - "limit": 100, - "offset": 0 - } - } - class ListDocumentsResponse(BaseModel): """Response model for list documents endpoint.""" + model_config = ConfigDict(json_schema_extra={ + "example": { + "items": [ + { + "id": "session_1", + "agent_id": "user123", + "content_hash": "abc123", + "created_at": "2024-01-15T10:30:00Z", + "updated_at": "2024-01-15T10:30:00Z", + "text_length": 5420, + "memory_unit_count": 15 + } + ], + "total": 50, + "limit": 100, + "offset": 0 + } + }) + items: List[Dict[str, Any]] total: int limit: int offset: int - class Config: - json_schema_extra = { - "example": { - "items": [ - { - "id": "session_1", - "agent_id": "user123", - "content_hash": "abc123", - "created_at": "2024-01-15T10:30:00Z", - "updated_at": "2024-01-15T10:30:00Z", - "text_length": 5420, - "memory_unit_count": 15 - } - ], - "total": 50, - "limit": 100, - "offset": 0 - } - } - class DocumentResponse(BaseModel): """Response model for get document endpoint.""" + model_config = ConfigDict(json_schema_extra={ + "example": { + "id": "session_1", + "agent_id": "user123", + "original_text": "Full document text here...", + "content_hash": "abc123", + "created_at": "2024-01-15T10:30:00Z", + "updated_at": "2024-01-15T10:30:00Z", + "memory_unit_count": 15 + } + }) + id: str agent_id: str original_text: str @@ -520,40 +513,26 @@ class DocumentResponse(BaseModel): updated_at: str memory_unit_count: int - class Config: - json_schema_extra = { - "example": { - "id": "session_1", - "agent_id": "user123", - "original_text": "Full document text here...", - "content_hash": "abc123", - "created_at": "2024-01-15T10:30:00Z", - "updated_at": "2024-01-15T10:30:00Z", - "memory_unit_count": 15 - } - } - class DeleteResponse(BaseModel): """Response model for delete operations.""" + model_config = ConfigDict(json_schema_extra={ + "example": { + "success": True, + "message": "Resource deleted successfully" + } + }) + success: bool message: str - class Config: - json_schema_extra = { - "example": { - "success": True, - "message": "Resource deleted successfully" - } - } - -def create_app(memory: TemporalSemanticMemory, run_migrations: bool = True, initialize_memory: bool = True) -> FastAPI: +def create_app(memory: MemoryEngine, run_migrations: bool = True, initialize_memory: bool = True) -> FastAPI: """ Create and configure the FastAPI application. Args: - memory: TemporalSemanticMemory instance (already initialized with required parameters) + memory: MemoryEngine instance (already initialized with required parameters) run_migrations: Whether to run database migrations on startup (default: True) initialize_memory: Whether to initialize memory system on startup (default: True) @@ -572,14 +551,16 @@ async def lifespan(app: FastAPI): Note: This only fires when running the app standalone, not when mounted. """ # Startup: Initialize database and memory system + if initialize_memory: + await memory.initialize() + logging.info("Memory system initialized") + if run_migrations: - from memora.migrations import run_migrations as do_migrations + from hindsight_api.migrations import run_migrations as do_migrations do_migrations(memory.db_url) logging.info("Database migrations applied") - if initialize_memory: - await memory.initialize() - logging.info("Memory system initialized") + yield @@ -860,7 +841,7 @@ async def api_stats(agent_id: str): """Get statistics about memory nodes and links for an agent.""" try: pool = await app.state.memory._get_pool() - async with pool.acquire() as conn: + async with acquire_with_retry(pool) as conn: # Get node counts by fact_type node_stats = await conn.fetch( """ @@ -1195,7 +1176,7 @@ async def api_batch_put_async(agent_id: str, request: BatchPutRequest): # Insert operation record into database BEFORE scheduling task pool = await app.state.memory._get_pool() - async with pool.acquire() as conn: + async with acquire_with_retry(pool) as conn: await conn.execute( """ INSERT INTO async_operations (id, agent_id, task_type, items_count, document_id) @@ -1245,7 +1226,7 @@ async def api_list_operations(agent_id: str): """List all async operations (pending and failed) for an agent.""" try: pool = await app.state.memory._get_pool() - async with pool.acquire() as conn: + async with acquire_with_retry(pool) as conn: operations = await conn.fetch( """ SELECT id, agent_id, task_type, items_count, document_id, created_at, status, error_message @@ -1296,7 +1277,7 @@ async def api_cancel_operation(agent_id: str, operation_id: str): raise HTTPException(status_code=400, detail=f"Invalid operation_id format: {operation_id}") pool = await app.state.memory._get_pool() - async with pool.acquire() as conn: + async with acquire_with_retry(pool) as conn: # Check if operation exists and belongs to this agent result = await conn.fetchrow( "SELECT agent_id FROM async_operations WHERE id = $1 AND agent_id = $2", @@ -1468,7 +1449,7 @@ async def api_create_or_update_agent( # Update name if provided if request.name is not None: pool = await app.state.memory._get_pool() - async with pool.acquire() as conn: + async with acquire_with_retry(pool) as conn: await conn.execute( """ UPDATE agents @@ -1492,7 +1473,7 @@ async def api_create_or_update_agent( # Update background if provided (replace, not merge) if request.background is not None: pool = await app.state.memory._get_pool() - async with pool.acquire() as conn: + async with acquire_with_retry(pool) as conn: await conn.execute( """ UPDATE agents diff --git a/memora/memora/api/mcp.py b/hindsight-api/hindsight_api/api/mcp.py similarity index 91% rename from memora/memora/api/mcp.py rename to hindsight-api/hindsight_api/api/mcp.py index c4c7ba9492..f9d7c83822 100644 --- a/memora/memora/api/mcp.py +++ b/hindsight-api/hindsight_api/api/mcp.py @@ -1,30 +1,30 @@ -"""Memora MCP Server implementation using FastMCP.""" +"""Hindsight MCP Server implementation using FastMCP.""" import json import logging from fastmcp import FastMCP -from memora import TemporalSemanticMemory +from hindsight_api import MemoryEngine logging.basicConfig(level=logging.INFO) logger = logging.getLogger(__name__) -def create_mcp_server(memory: TemporalSemanticMemory) -> FastMCP: +def create_mcp_server(memory: MemoryEngine) -> FastMCP: """ - Create and configure the Memora MCP server. + Create and configure the Hindsight MCP server. Args: - memory: TemporalSemanticMemory instance (required) + memory: MemoryEngine instance (required) Returns: Configured FastMCP server instance """ # Create FastMCP server - mcp = FastMCP("memora-mcp-server") + mcp = FastMCP("hindsight-mcp-server") @mcp.tool() - async def memora_put(agent_id: str, content: str, context: str, explanation: str = "") -> str: + async def hindsight_put(agent_id: str, content: str, context: str, explanation: str = "") -> str: """ **CRITICAL: Store important user information to long-term memory.** @@ -74,7 +74,7 @@ async def memora_put(agent_id: str, content: str, context: str, explanation: str return f"Error: {str(e)}" @mcp.tool() - async def memora_search(agent_id: str, query: str, max_tokens: int = 4096, explanation: str = "") -> str: + async def hindsight_search(agent_id: str, query: str, max_tokens: int = 4096, explanation: str = "") -> str: """ **CRITICAL: Search user's memory to provide personalized, context-aware responses.** @@ -112,7 +112,7 @@ async def memora_search(agent_id: str, query: str, max_tokens: int = 4096, expla """ try: # Log all parameters for debugging - logger.info(f"memora_search called with: query={query!r}, max_tokens={max_tokens}, explanation={explanation!r}") + logger.info(f"hindsight_search called with: query={query!r}, max_tokens={max_tokens}, explanation={explanation!r}") # Log explanation if provided if explanation: diff --git a/hindsight-api/hindsight_api/engine/__init__.py b/hindsight-api/hindsight_api/engine/__init__.py new file mode 100644 index 0000000000..e567147097 --- /dev/null +++ b/hindsight-api/hindsight_api/engine/__init__.py @@ -0,0 +1,47 @@ +""" +Memory Engine - Core implementation of the memory system. + +This package contains all the implementation details of the memory engine: +- MemoryEngine: Main class for memory operations +- Utility modules: embedding_utils, link_utils, think_utils, agent_utils +- Supporting modules: embeddings, cross_encoder, entity_resolver, etc. +""" + +from .memory_engine import MemoryEngine +from .db_utils import acquire_with_retry +from .embeddings import Embeddings, SentenceTransformersEmbeddings +from .search_trace import ( + SearchTrace, + QueryInfo, + EntryPoint, + NodeVisit, + WeightComponents, + LinkInfo, + PruningDecision, + SearchSummary, + SearchPhaseMetrics, +) +from .search_tracer import SearchTracer +from .llm_wrapper import LLMConfig +from .response_models import SearchResult, ThinkResult, MemoryFact + +__all__ = [ + "MemoryEngine", + "acquire_with_retry", + "Embeddings", + "SentenceTransformersEmbeddings", + "SearchTrace", + "SearchTracer", + "QueryInfo", + "EntryPoint", + "NodeVisit", + "WeightComponents", + "LinkInfo", + "PruningDecision", + "SearchSummary", + "SearchPhaseMetrics", + "LLMConfig", + "SearchResult", + "ThinkResult", + "MemoryFact", +] diff --git a/hindsight-api/hindsight_api/engine/agent_utils.py b/hindsight-api/hindsight_api/engine/agent_utils.py new file mode 100644 index 0000000000..6cc28401b5 --- /dev/null +++ b/hindsight-api/hindsight_api/engine/agent_utils.py @@ -0,0 +1,426 @@ +""" +Agent profile utilities for personality and background management. +""" + +import json +import logging +import re +from typing import Dict, Optional +from pydantic import BaseModel, Field +from .db_utils import acquire_with_retry + +logger = logging.getLogger(__name__) + +DEFAULT_PERSONALITY = { + "openness": 0.5, + "conscientiousness": 0.5, + "extraversion": 0.5, + "agreeableness": 0.5, + "neuroticism": 0.5, + "bias_strength": 0.5, +} + + +class PersonalityTraits(BaseModel): + """Big Five personality traits with bias strength (all values 0.0-1.0).""" + openness: float = Field(description="Creativity, curiosity, openness to new ideas (0.0-1.0)") + conscientiousness: float = Field(description="Organization, discipline, goal-directed (0.0-1.0)") + extraversion: float = Field(description="Sociability, assertiveness, energy from others (0.0-1.0)") + agreeableness: float = Field(description="Cooperation, empathy, consideration (0.0-1.0)") + neuroticism: float = Field(description="Emotional sensitivity, anxiety, stress response (0.0-1.0)") + bias_strength: float = Field(description="How much personality influences opinions (0.0-1.0)") + + +class BackgroundMergeResponse(BaseModel): + """LLM response for background merge with personality inference.""" + background: str = Field(description="Merged background in first person perspective") + personality: PersonalityTraits = Field(description="Inferred Big Five personality traits") + + +async def get_agent_profile(pool, agent_id: str) -> Dict: + """ + Get agent profile (name, personality + background). + Auto-creates agent with default values if not exists. + + Args: + pool: Database connection pool + agent_id: Agent identifier + + Returns: + Dict with 'name' (str), 'personality' (dict) and 'background' (str) keys + """ + async with acquire_with_retry(pool) as conn: + # Try to get existing agent + row = await conn.fetchrow( + """ + SELECT name, personality, background + FROM agents + WHERE agent_id = $1 + """, + agent_id + ) + + if row: + # asyncpg returns JSONB as a string, so parse it + personality_data = row["personality"] + if isinstance(personality_data, str): + personality_data = json.loads(personality_data) + + return { + "name": row["name"], + "personality": personality_data, + "background": row["background"] + } + + # Agent doesn't exist, create with defaults + await conn.execute( + """ + INSERT INTO agents (agent_id, name, personality, background) + VALUES ($1, $2, $3::jsonb, $4) + ON CONFLICT (agent_id) DO NOTHING + """, + agent_id, + agent_id, # Default name is the agent_id + json.dumps(DEFAULT_PERSONALITY), + "" + ) + + return { + "name": agent_id, + "personality": DEFAULT_PERSONALITY.copy(), + "background": "" + } + + +async def update_agent_personality( + pool, + agent_id: str, + personality: Dict[str, float] +) -> None: + """ + Update agent personality traits. + + Args: + pool: Database connection pool + agent_id: Agent identifier + personality: Dict with Big Five traits + bias_strength (all 0-1) + """ + # Ensure agent exists first + await get_agent_profile(pool, agent_id) + + async with acquire_with_retry(pool) as conn: + await conn.execute( + """ + UPDATE agents + SET personality = $2::jsonb, + updated_at = NOW() + WHERE agent_id = $1 + """, + agent_id, + json.dumps(personality) + ) + + +async def merge_agent_background( + pool, + llm_config, + agent_id: str, + new_info: str, + update_personality: bool = True +) -> dict: + """ + Merge new background information with existing background using LLM. + Normalizes to first person ("I") and resolves conflicts. + Optionally infers personality traits from the merged background. + + Args: + pool: Database connection pool + llm_config: LLM configuration for background merging + agent_id: Agent identifier + new_info: New background information to add/merge + update_personality: If True, infer Big Five traits from background (default: True) + + Returns: + Dict with 'background' (str) and optionally 'personality' (dict) keys + """ + # Get current profile + profile = await get_agent_profile(pool, agent_id) + current_background = profile["background"] + + # Use LLM to merge backgrounds and optionally infer personality + result = await _llm_merge_background( + llm_config, + current_background, + new_info, + infer_personality=update_personality + ) + + merged_background = result["background"] + inferred_personality = result.get("personality") + + # Update in database + async with acquire_with_retry(pool) as conn: + if inferred_personality: + # Update both background and personality + await conn.execute( + """ + UPDATE agents + SET background = $2, + personality = $3::jsonb, + updated_at = NOW() + WHERE agent_id = $1 + """, + agent_id, + merged_background, + json.dumps(inferred_personality) + ) + else: + # Update only background + await conn.execute( + """ + UPDATE agents + SET background = $2, + updated_at = NOW() + WHERE agent_id = $1 + """, + agent_id, + merged_background + ) + + response = {"background": merged_background} + if inferred_personality: + response["personality"] = inferred_personality + + return response + + +async def _llm_merge_background( + llm_config, + current: str, + new_info: str, + infer_personality: bool = False +) -> dict: + """ + Use LLM to intelligently merge background information. + Optionally infer Big Five personality traits from the merged background. + + Args: + llm_config: LLM configuration to use + current: Current background text + new_info: New information to merge + infer_personality: If True, also infer personality traits + + Returns: + Dict with 'background' (str) and optionally 'personality' (dict) keys + """ + if infer_personality: + prompt = f"""You are helping maintain an agent's background/profile and infer their personality. You MUST respond with ONLY valid JSON. + +Current background: {current if current else "(empty)"} + +New information to add: {new_info} + +Instructions: +1. Merge the new information with the current background +2. If there are conflicts (e.g., different birthplaces), the NEW information overwrites the old +3. Keep additions that don't conflict +4. Output in FIRST PERSON ("I") perspective +5. Be concise - keep merged background under 500 characters +6. Infer Big Five personality traits from the merged background: + - Openness: 0.0-1.0 (creativity, curiosity, openness to new ideas) + - Conscientiousness: 0.0-1.0 (organization, discipline, goal-directed) + - Extraversion: 0.0-1.0 (sociability, assertiveness, energy from others) + - Agreeableness: 0.0-1.0 (cooperation, empathy, consideration) + - Neuroticism: 0.0-1.0 (emotional sensitivity, anxiety, stress response) + - Bias Strength: 0.0-1.0 (how much personality influences opinions) + +CRITICAL: You MUST respond with ONLY a valid JSON object. No markdown, no code blocks, no explanations. Just the JSON. + +Format: +{{ + "background": "the merged background text in first person", + "personality": {{ + "openness": 0.7, + "conscientiousness": 0.6, + "extraversion": 0.5, + "agreeableness": 0.8, + "neuroticism": 0.4, + "bias_strength": 0.6 + }} +}} + +Trait inference examples: +- "creative artist" โ†’ openness: 0.8+, bias_strength: 0.6 +- "organized engineer" โ†’ conscientiousness: 0.8+, openness: 0.5-0.6 +- "startup founder" โ†’ openness: 0.8+, extraversion: 0.7+, neuroticism: 0.3-0.4 +- "risk-averse analyst" โ†’ openness: 0.3-0.4, conscientiousness: 0.8+, neuroticism: 0.6+ +- "rational and diligent" โ†’ conscientiousness: 0.7+, openness: 0.6+ +- "passionate and dramatic" โ†’ extraversion: 0.7+, neuroticism: 0.6+, openness: 0.7+""" + else: + prompt = f"""You are helping maintain an agent's background/profile. + +Current background: {current if current else "(empty)"} + +New information to add: {new_info} + +Instructions: +1. Merge the new information with the current background +2. If there are conflicts (e.g., different birthplaces), the NEW information overwrites the old +3. Keep additions that don't conflict +4. Output in FIRST PERSON ("I") perspective +5. Be concise - keep it under 500 characters +6. Return ONLY the merged background text, no explanations + +Merged background:""" + + try: + # Prepare messages + messages = [{"role": "user", "content": prompt}] + + if infer_personality: + # Use structured output with Pydantic model for personality inference + try: + parsed = await llm_config.call( + messages=messages, + response_format=BackgroundMergeResponse, + scope="agent_background", + temperature=0.3, + max_tokens=8192 + ) + logger.info(f"Successfully got structured response: background={parsed.background[:100]}") + + # Convert Pydantic model to dict format + return { + "background": parsed.background, + "personality": parsed.personality.model_dump() + } + except Exception as e: + logger.warning(f"Structured output failed, falling back to manual parsing: {e}") + # Fall through to manual parsing below + + # Manual parsing fallback or non-personality merge + content = await llm_config.call( + messages=messages, + scope="agent_background", + temperature=0.3, + max_tokens=8192 + ) + + logger.info(f"LLM response for background merge (first 500 chars): {content[:500]}") + + if infer_personality: + # Parse JSON response - try multiple extraction methods + result = None + + # Method 1: Direct parse + try: + result = json.loads(content) + logger.info("Successfully parsed JSON directly") + except json.JSONDecodeError: + pass + + # Method 2: Extract from markdown code blocks + if result is None: + # Remove markdown code blocks + code_block_match = re.search(r'```(?:json)?\s*(\{.*?\})\s*```', content, re.DOTALL) + if code_block_match: + try: + result = json.loads(code_block_match.group(1)) + logger.info("Successfully extracted JSON from markdown code block") + except json.JSONDecodeError: + pass + + # Method 3: Find nested JSON structure + if result is None: + # Look for JSON object with nested structure + json_match = re.search(r'\{[^{}]*"background"[^{}]*"personality"[^{}]*\{[^{}]*\}[^{}]*\}', content, re.DOTALL) + if json_match: + try: + result = json.loads(json_match.group()) + logger.info("Successfully extracted JSON using nested pattern") + except json.JSONDecodeError: + pass + + # All parsing methods failed - use fallback + if result is None: + logger.warning(f"Failed to extract JSON from LLM response. Raw content: {content[:200]}") + # Fallback: use new_info as background with default personality + return { + "background": new_info if new_info else current if current else "", + "personality": DEFAULT_PERSONALITY.copy() + } + + # Validate personality values + personality = result.get("personality", {}) + for key in ["openness", "conscientiousness", "extraversion", + "agreeableness", "neuroticism", "bias_strength"]: + if key not in personality: + personality[key] = 0.5 # Default to neutral + else: + # Clamp to [0, 1] + personality[key] = max(0.0, min(1.0, float(personality[key]))) + + result["personality"] = personality + + # Ensure background exists + if "background" not in result or not result["background"]: + result["background"] = new_info if new_info else "" + + return result + else: + # Just background merge + merged = content + if not merged or merged.lower() in ["(empty)", "none", "n/a"]: + merged = new_info if new_info else "" + return {"background": merged} + + except Exception as e: + logger.error(f"Error merging background with LLM: {e}") + # Fallback: just append new info + if current: + merged = f"{current} {new_info}".strip() + else: + merged = new_info + + result = {"background": merged} + if infer_personality: + result["personality"] = DEFAULT_PERSONALITY.copy() + return result + + +async def list_agents(pool) -> list: + """ + List all agents in the system. + + Args: + pool: Database connection pool + + Returns: + List of dicts with agent_id, name, personality, background, created_at, updated_at + """ + async with acquire_with_retry(pool) as conn: + rows = await conn.fetch( + """ + SELECT agent_id, name, personality, background, created_at, updated_at + FROM agents + ORDER BY updated_at DESC + """ + ) + + result = [] + for row in rows: + # asyncpg returns JSONB as a string, so parse it + personality_data = row["personality"] + if isinstance(personality_data, str): + personality_data = json.loads(personality_data) + + result.append({ + "agent_id": row["agent_id"], + "name": row["name"], + "personality": personality_data, + "background": row["background"], + "created_at": row["created_at"].isoformat() if row["created_at"] else None, + "updated_at": row["updated_at"].isoformat() if row["updated_at"] else None, + }) + + return result diff --git a/memora/memora/cross_encoder.py b/hindsight-api/hindsight_api/engine/cross_encoder.py similarity index 100% rename from memora/memora/cross_encoder.py rename to hindsight-api/hindsight_api/engine/cross_encoder.py diff --git a/hindsight-api/hindsight_api/engine/db_utils.py b/hindsight-api/hindsight_api/engine/db_utils.py new file mode 100644 index 0000000000..89059d77d2 --- /dev/null +++ b/hindsight-api/hindsight_api/engine/db_utils.py @@ -0,0 +1,93 @@ +""" +Database utility functions for connection management with retry logic. +""" +import asyncio +import logging +from contextlib import asynccontextmanager +import asyncpg + +logger = logging.getLogger(__name__) + +# Default retry configuration for database operations +DEFAULT_MAX_RETRIES = 3 +DEFAULT_BASE_DELAY = 0.5 # seconds +DEFAULT_MAX_DELAY = 5.0 # seconds + +# Exceptions that indicate transient connection issues worth retrying +RETRYABLE_EXCEPTIONS = ( + asyncpg.exceptions.InterfaceError, + asyncpg.exceptions.ConnectionDoesNotExistError, + asyncpg.exceptions.TooManyConnectionsError, + OSError, + ConnectionError, + asyncio.TimeoutError, +) + + +async def retry_with_backoff( + func, + max_retries: int = DEFAULT_MAX_RETRIES, + base_delay: float = DEFAULT_BASE_DELAY, + max_delay: float = DEFAULT_MAX_DELAY, + retryable_exceptions: tuple = RETRYABLE_EXCEPTIONS, +): + """ + Execute an async function with exponential backoff retry. + + Args: + func: Async function to execute + max_retries: Maximum number of retry attempts + base_delay: Initial delay between retries (seconds) + max_delay: Maximum delay between retries (seconds) + retryable_exceptions: Tuple of exception types to retry on + + Returns: + Result of the function + + Raises: + The last exception if all retries fail + """ + last_exception = None + for attempt in range(max_retries + 1): + try: + return await func() + except retryable_exceptions as e: + last_exception = e + if attempt < max_retries: + delay = min(base_delay * (2 ** attempt), max_delay) + logger.warning( + f"Database operation failed (attempt {attempt + 1}/{max_retries + 1}): {e}. " + f"Retrying in {delay:.1f}s..." + ) + await asyncio.sleep(delay) + else: + logger.error( + f"Database operation failed after {max_retries + 1} attempts: {e}" + ) + raise last_exception + + +@asynccontextmanager +async def acquire_with_retry(pool: asyncpg.Pool, max_retries: int = DEFAULT_MAX_RETRIES): + """ + Async context manager to acquire a connection with retry logic. + + Usage: + async with acquire_with_retry(pool) as conn: + await conn.execute(...) + + Args: + pool: The asyncpg connection pool + max_retries: Maximum number of retry attempts + + Yields: + An asyncpg connection + """ + async def acquire(): + return await pool.acquire() + + conn = await retry_with_backoff(acquire, max_retries=max_retries) + try: + yield conn + finally: + await pool.release(conn) diff --git a/hindsight-api/hindsight_api/engine/embedding_utils.py b/hindsight-api/hindsight_api/engine/embedding_utils.py new file mode 100644 index 0000000000..ca460a98d9 --- /dev/null +++ b/hindsight-api/hindsight_api/engine/embedding_utils.py @@ -0,0 +1,54 @@ +""" +Embedding generation utilities for memory units. +""" + +import asyncio +import logging +from typing import List + +logger = logging.getLogger(__name__) + + +def generate_embedding(embeddings_backend, text: str) -> List[float]: + """ + Generate embedding for text using the provided embeddings backend. + + Args: + embeddings_backend: Embeddings instance to use for encoding + text: Text to embed + + Returns: + Embedding vector (dimension depends on embeddings backend) + """ + try: + embeddings = embeddings_backend.encode([text]) + return embeddings[0] + except Exception as e: + raise Exception(f"Failed to generate embedding: {str(e)}") + + +async def generate_embeddings_batch(embeddings_backend, texts: List[str]) -> List[List[float]]: + """ + Generate embeddings for multiple texts using the provided embeddings backend. + + Runs the embedding generation in a thread pool to avoid blocking the event loop + for CPU-bound operations. + + Args: + embeddings_backend: Embeddings instance to use for encoding + texts: List of texts to embed + + Returns: + List of embeddings in same order as input texts + """ + try: + # Run embeddings in thread pool to avoid blocking event loop + loop = asyncio.get_event_loop() + embeddings = await loop.run_in_executor( + None, # Use default thread pool + embeddings_backend.encode, + texts + ) + return embeddings + except Exception as e: + raise Exception(f"Failed to generate batch embeddings: {str(e)}") diff --git a/memora/memora/embeddings.py b/hindsight-api/hindsight_api/engine/embeddings.py similarity index 100% rename from memora/memora/embeddings.py rename to hindsight-api/hindsight_api/engine/embeddings.py diff --git a/memora/memora/entity_resolver.py b/hindsight-api/hindsight_api/engine/entity_resolver.py similarity index 97% rename from memora/memora/entity_resolver.py rename to hindsight-api/hindsight_api/engine/entity_resolver.py index 13b6876904..c560d042ac 100644 --- a/memora/memora/entity_resolver.py +++ b/hindsight-api/hindsight_api/engine/entity_resolver.py @@ -8,6 +8,7 @@ from typing import List, Dict, Optional, Set from difflib import SequenceMatcher from datetime import datetime, timezone +from .db_utils import acquire_with_retry # Load spaCy model (singleton) @@ -56,7 +57,7 @@ async def resolve_entities_batch( return [] if conn is None: - async with self.pool.acquire() as conn: + async with acquire_with_retry(self.pool) as conn: return await self._resolve_entities_batch_impl(conn, agent_id, entities_data, context, unit_event_date) else: return await self._resolve_entities_batch_impl(conn, agent_id, entities_data, context, unit_event_date) @@ -220,7 +221,7 @@ async def resolve_entity( Returns: Entity ID (creates new entity if needed) """ - async with self.pool.acquire() as conn: + async with acquire_with_retry(self.pool) as conn: # Find candidate entities with similar name candidates = await conn.fetch( """ @@ -366,7 +367,7 @@ async def link_unit_to_entity(self, unit_id: str, entity_id: str): unit_id: Memory unit ID entity_id: Entity ID """ - async with self.pool.acquire() as conn: + async with acquire_with_retry(self.pool) as conn: # Insert unit-entity link await conn.execute( """ @@ -434,7 +435,7 @@ async def link_units_to_entities_batch(self, unit_entity_pairs: List[tuple[str, return if conn is None: - async with self.pool.acquire() as conn: + async with acquire_with_retry(self.pool) as conn: return await self._link_units_to_entities_batch_impl(conn, unit_entity_pairs) else: return await self._link_units_to_entities_batch_impl(conn, unit_entity_pairs) @@ -499,7 +500,7 @@ async def get_units_by_entity(self, entity_id: str, limit: int = 100) -> List[st Returns: List of unit IDs """ - async with self.pool.acquire() as conn: + async with acquire_with_retry(self.pool) as conn: rows = await conn.fetch( """ SELECT unit_id @@ -527,7 +528,7 @@ async def get_entity_by_text( Returns: Entity ID if found, None otherwise """ - async with self.pool.acquire() as conn: + async with acquire_with_retry(self.pool) as conn: row = await conn.fetchrow( """ SELECT id FROM entities diff --git a/memora/memora/fact_extraction.py b/hindsight-api/hindsight_api/engine/fact_extraction.py similarity index 100% rename from memora/memora/fact_extraction.py rename to hindsight-api/hindsight_api/engine/fact_extraction.py diff --git a/hindsight-api/hindsight_api/engine/link_utils.py b/hindsight-api/hindsight_api/engine/link_utils.py new file mode 100644 index 0000000000..4bd278b360 --- /dev/null +++ b/hindsight-api/hindsight_api/engine/link_utils.py @@ -0,0 +1,541 @@ +""" +Link creation utilities for temporal, semantic, and entity links. +""" + +import time +import logging +from typing import List +from datetime import timedelta + +logger = logging.getLogger(__name__) + + +def _log(log_buffer, message, level='info'): + """Helper to log to buffer if available, otherwise use logger.""" + if log_buffer is not None: + log_buffer.append(message) + else: + if level == 'info': + logger.info(message) + else: + logger.debug(message) + + +async def extract_entities_batch_optimized( + entity_resolver, + conn, + agent_id: str, + unit_ids: List[str], + sentences: List[str], + context: str, + fact_dates: List, + llm_entities: List[List[dict]], + log_buffer: List[str] = None, +) -> List[tuple]: + """ + Process LLM-extracted entities for ALL facts in batch. + + Uses entities provided by the LLM (no spaCy needed), then resolves + and links them in bulk. + + Args: + entity_resolver: EntityResolver instance for entity resolution + conn: Database connection + agent_id: Agent identifier + unit_ids: List of unit IDs + sentences: List of fact sentences + context: Context string + fact_dates: List of fact dates + llm_entities: List of entity lists from LLM extraction + log_buffer: Optional buffer for logging + + Returns: + List of tuples for batch insertion: (from_unit_id, to_unit_id, link_type, weight, entity_id) + """ + try: + # Step 1: Convert LLM entities to the format expected by entity resolver + substep_start = time.time() + all_entities = [] + for entity_list in llm_entities: + # Convert List[Entity] or List[dict] to List[Dict] format + formatted_entities = [] + for ent in entity_list: + # Handle both Entity objects and dicts + if hasattr(ent, 'text'): + formatted_entities.append({'text': ent.text, 'type': ent.type}) + elif isinstance(ent, dict): + formatted_entities.append({'text': ent.get('text', ''), 'type': ent.get('type', 'CONCEPT')}) + all_entities.append(formatted_entities) + + total_entities = sum(len(ents) for ents in all_entities) + _log(log_buffer, f" [6.1] Process LLM entities: {total_entities} entities from {len(sentences)} facts in {time.time() - substep_start:.3f}s") + + # Step 2: Resolve entities in BATCH (much faster!) + substep_start = time.time() + step_6_2_start = time.time() + + # [6.2.1] Prepare all entities for batch resolution + substep_6_2_1_start = time.time() + all_entities_flat = [] + entity_to_unit = [] # Maps flat index to (unit_id, local_index) + + for unit_id, entities, fact_date in zip(unit_ids, all_entities, fact_dates): + if not entities: + continue + + for local_idx, entity in enumerate(entities): + all_entities_flat.append({ + 'text': entity['text'], + 'type': entity['type'], + 'nearby_entities': entities, + }) + entity_to_unit.append((unit_id, local_idx, fact_date)) + _log(log_buffer, f" [6.2.1] Prepare entities: {len(all_entities_flat)} entities in {time.time() - substep_6_2_1_start:.3f}s") + + # Resolve ALL entities in one batch call + if all_entities_flat: + # [6.2.2] Batch resolve entities + substep_6_2_2_start = time.time() + # Group by date for batch resolution (most will have same date) + entities_by_date = {} + for idx, (unit_id, local_idx, fact_date) in enumerate(entity_to_unit): + date_key = fact_date + if date_key not in entities_by_date: + entities_by_date[date_key] = [] + entities_by_date[date_key].append((idx, all_entities_flat[idx])) + + _log(log_buffer, f" [6.2.2] Grouped into {len(entities_by_date)} date buckets, resolving...") + + # Resolve each date group in batch + resolved_entity_ids = [None] * len(all_entities_flat) + for date_idx, (fact_date, entities_group) in enumerate(entities_by_date.items(), 1): + date_bucket_start = time.time() + indices = [idx for idx, _ in entities_group] + entities_data = [entity_data for _, entity_data in entities_group] + + batch_resolved = await entity_resolver.resolve_entities_batch( + agent_id=agent_id, + entities_data=entities_data, + context=context, + unit_event_date=fact_date, + conn=conn + ) + + for idx, entity_id in zip(indices, batch_resolved): + resolved_entity_ids[idx] = entity_id + + _log(log_buffer, f" [6.2.2.{date_idx}] Resolved {len(entities_data)} entities in {time.time() - date_bucket_start:.3f}s") + + _log(log_buffer, f" [6.2.2] Resolve entities: {len(all_entities_flat)} entities in {time.time() - substep_6_2_2_start:.3f}s") + + # [6.2.3] Create unit-entity links in BATCH + substep_6_2_3_start = time.time() + # Map resolved entities back to units and collect all (unit, entity) pairs + unit_to_entity_ids = {} + unit_entity_pairs = [] + for idx, (unit_id, local_idx, fact_date) in enumerate(entity_to_unit): + if unit_id not in unit_to_entity_ids: + unit_to_entity_ids[unit_id] = [] + + entity_id = resolved_entity_ids[idx] + unit_to_entity_ids[unit_id].append(entity_id) + unit_entity_pairs.append((unit_id, entity_id)) + + # Batch insert all unit-entity links (MUCH faster!) + await entity_resolver.link_units_to_entities_batch(unit_entity_pairs, conn=conn) + _log(log_buffer, f" [6.2.3] Create unit-entity links (batched): {len(unit_entity_pairs)} links in {time.time() - substep_6_2_3_start:.3f}s") + + _log(log_buffer, f" [6.2] Entity resolution (batched): {len(all_entities_flat)} entities resolved in {time.time() - step_6_2_start:.3f}s") + else: + unit_to_entity_ids = {} + _log(log_buffer, f" [6.2] Entity resolution (batched): 0 entities in {time.time() - step_6_2_start:.3f}s") + + # Step 3: Create entity links between units that share entities + substep_start = time.time() + # Collect all unique entity IDs + all_entity_ids = set() + for entity_ids in unit_to_entity_ids.values(): + all_entity_ids.update(entity_ids) + + _log(log_buffer, f" [6.3] Creating entity links for {len(all_entity_ids)} unique entities...") + + # Find all units that reference these entities (ONE batched query) + entity_to_units = {} + if all_entity_ids: + query_start = time.time() + import uuid + entity_id_list = [uuid.UUID(eid) if isinstance(eid, str) else eid for eid in all_entity_ids] + rows = await conn.fetch( + """ + SELECT entity_id, unit_id + FROM unit_entities + WHERE entity_id = ANY($1::uuid[]) + """, + entity_id_list + ) + _log(log_buffer, f" [6.3.1] Query unit_entities: {len(rows)} rows in {time.time() - query_start:.3f}s") + + # Group by entity_id + group_start = time.time() + for row in rows: + entity_id = row['entity_id'] + if entity_id not in entity_to_units: + entity_to_units[entity_id] = [] + entity_to_units[entity_id].append(row['unit_id']) + _log(log_buffer, f" [6.3.2] Group by entity_id: {time.time() - group_start:.3f}s") + + # Create bidirectional links between units that share entities + link_gen_start = time.time() + links = [] + for entity_id, units_with_entity in entity_to_units.items(): + # For each pair of units with this entity, create bidirectional links + for i, unit_id_1 in enumerate(units_with_entity): + for unit_id_2 in units_with_entity[i+1:]: + # Bidirectional links + links.append((unit_id_1, unit_id_2, 'entity', 1.0, entity_id)) + links.append((unit_id_2, unit_id_1, 'entity', 1.0, entity_id)) + + _log(log_buffer, f" [6.3.3] Generate {len(links)} links: {time.time() - link_gen_start:.3f}s") + _log(log_buffer, f" [6.3] Entity link creation: {len(links)} links for {len(all_entity_ids)} unique entities in {time.time() - substep_start:.3f}s") + + return links + + except Exception as e: + logger.error(f"Failed to extract entities in batch: {str(e)}") + import traceback + traceback.print_exc() + raise + + +async def create_temporal_links_batch_per_fact( + conn, + agent_id: str, + unit_ids: List[str], + time_window_hours: int = 24, + log_buffer: List[str] = None, +): + """ + Create temporal links for multiple units, each with their own event_date. + + Queries the event_date for each unit from the database and creates temporal + links based on individual dates (supports per-fact dating). + + Args: + conn: Database connection + agent_id: Agent identifier + unit_ids: List of unit IDs + time_window_hours: Time window in hours for temporal links + log_buffer: Optional buffer for logging + """ + if not unit_ids: + return + + try: + import time as time_mod + + # Get the event_date for each new unit + fetch_dates_start = time_mod.time() + rows = await conn.fetch( + """ + SELECT id, event_date + FROM memory_units + WHERE id::text = ANY($1) + """, + unit_ids + ) + new_units = {str(row['id']): row['event_date'] for row in rows} + _log(log_buffer, f" [7.1] Fetch event_dates for {len(unit_ids)} units: {time_mod.time() - fetch_dates_start:.3f}s") + + # Fetch ALL potential temporal neighbors in ONE query (much faster!) + # Get time range across all units + all_dates = list(new_units.values()) + min_date = min(all_dates) - timedelta(hours=time_window_hours) + max_date = max(all_dates) + timedelta(hours=time_window_hours) + + fetch_neighbors_start = time_mod.time() + all_candidates = await conn.fetch( + """ + SELECT id, event_date + FROM memory_units + WHERE agent_id = $1 + AND event_date BETWEEN $2 AND $3 + AND id::text != ALL($4) + ORDER BY event_date DESC + """, + agent_id, + min_date, + max_date, + unit_ids + ) + _log(log_buffer, f" [7.2] Fetch {len(all_candidates)} candidate neighbors (1 query): {time_mod.time() - fetch_neighbors_start:.3f}s") + + # Filter and create links in memory (much faster than N queries) + link_gen_start = time_mod.time() + links = [] + for unit_id, unit_event_date in new_units.items(): + # Filter candidates within this unit's time window + time_lower = unit_event_date - timedelta(hours=time_window_hours) + time_upper = unit_event_date + timedelta(hours=time_window_hours) + + matching_neighbors = [ + (row['id'], row['event_date']) + for row in all_candidates + if time_lower <= row['event_date'] <= time_upper + ][:10] # Limit to top 10 + + for recent_id, recent_event_date in matching_neighbors: + # Calculate temporal proximity weight + time_diff_hours = abs((unit_event_date - recent_event_date).total_seconds() / 3600) + weight = max(0.3, 1.0 - (time_diff_hours / time_window_hours)) + links.append((unit_id, str(recent_id), 'temporal', weight, None)) + + _log(log_buffer, f" [7.3] Generate {len(links)} temporal links: {time_mod.time() - link_gen_start:.3f}s") + + if links: + insert_start = time_mod.time() + await conn.executemany( + """ + INSERT INTO memory_links (from_unit_id, to_unit_id, link_type, weight, entity_id) + VALUES ($1, $2, $3, $4, $5) + ON CONFLICT (from_unit_id, to_unit_id, link_type, COALESCE(entity_id, '00000000-0000-0000-0000-000000000000'::uuid)) DO NOTHING + """, + links + ) + _log(log_buffer, f" [7.4] Insert {len(links)} temporal links: {time_mod.time() - insert_start:.3f}s") + + except Exception as e: + logger.error(f"Failed to create temporal links: {str(e)}") + import traceback + traceback.print_exc() + raise + + +async def create_semantic_links_batch( + conn, + agent_id: str, + unit_ids: List[str], + embeddings: List[List[float]], + top_k: int = 5, + threshold: float = 0.7, + log_buffer: List[str] = None, +): + """ + Create semantic links for multiple units efficiently. + + For each unit, finds similar units and creates links. + + Args: + conn: Database connection + agent_id: Agent identifier + unit_ids: List of unit IDs + embeddings: List of embedding vectors + top_k: Number of top similar units to link + threshold: Minimum similarity threshold + log_buffer: Optional buffer for logging + """ + if not unit_ids or not embeddings: + return + + try: + import time as time_mod + import numpy as np + + # Fetch ALL existing units with embeddings in ONE query + fetch_start = time_mod.time() + all_existing = await conn.fetch( + """ + SELECT id, embedding + FROM memory_units + WHERE agent_id = $1 + AND embedding IS NOT NULL + AND id::text != ALL($2) + """, + agent_id, + unit_ids + ) + _log(log_buffer, f" [8.1] Fetch {len(all_existing)} existing embeddings (1 query): {time_mod.time() - fetch_start:.3f}s") + + # Convert to numpy for vectorized similarity computation + compute_start = time_mod.time() + all_links = [] + + if all_existing: + # Convert existing embeddings to numpy array + existing_ids = [str(row['id']) for row in all_existing] + # Stack embeddings as 2D array: (num_embeddings, embedding_dim) + embedding_arrays = [] + for row in all_existing: + raw_emb = row['embedding'] + # Handle different pgvector formats + if isinstance(raw_emb, str): + # Parse string format: "[1.0, 2.0, ...]" + import json + emb = np.array(json.loads(raw_emb), dtype=np.float32) + elif isinstance(raw_emb, (list, tuple)): + emb = np.array(raw_emb, dtype=np.float32) + else: + # Try direct conversion (works for numpy arrays, pgvector objects, etc.) + emb = np.array(raw_emb, dtype=np.float32) + + # Ensure it's 1D + if emb.ndim != 1: + raise ValueError(f"Expected 1D embedding, got shape {emb.shape}") + embedding_arrays.append(emb) + + if not embedding_arrays: + existing_embeddings = np.array([]) + elif len(embedding_arrays) == 1: + # Single embedding: reshape to (1, dim) + existing_embeddings = embedding_arrays[0].reshape(1, -1) + else: + # Multiple embeddings: vstack + existing_embeddings = np.vstack(embedding_arrays) + + # For each new unit, compute similarities with ALL existing units + for unit_id, new_embedding in zip(unit_ids, embeddings): + new_emb_array = np.array(new_embedding) + + # Compute cosine similarities (dot product for normalized vectors) + similarities = np.dot(existing_embeddings, new_emb_array) + + # Find top-k above threshold + # Get indices of similarities above threshold + above_threshold = np.where(similarities >= threshold)[0] + + if len(above_threshold) > 0: + # Sort by similarity (descending) and take top-k + sorted_indices = above_threshold[np.argsort(-similarities[above_threshold])][:top_k] + + for idx in sorted_indices: + similar_id = existing_ids[idx] + similarity = float(similarities[idx]) + all_links.append((unit_id, similar_id, 'semantic', similarity, None)) + + _log(log_buffer, f" [8.2] Compute similarities & generate {len(all_links)} semantic links: {time_mod.time() - compute_start:.3f}s") + + if all_links: + insert_start = time_mod.time() + await conn.executemany( + """ + INSERT INTO memory_links (from_unit_id, to_unit_id, link_type, weight, entity_id) + VALUES ($1, $2, $3, $4, $5) + ON CONFLICT (from_unit_id, to_unit_id, link_type, COALESCE(entity_id, '00000000-0000-0000-0000-000000000000'::uuid)) DO NOTHING + """, + all_links + ) + _log(log_buffer, f" [8.3] Insert {len(all_links)} semantic links: {time_mod.time() - insert_start:.3f}s") + + except Exception as e: + logger.error(f"Failed to create semantic links: {str(e)}") + import traceback + traceback.print_exc() + raise + + +async def insert_entity_links_batch(conn, links: List[tuple]): + """ + Insert all entity links in a single batch. + + Args: + conn: Database connection + links: List of tuples (from_unit_id, to_unit_id, link_type, weight, entity_id) + """ + if not links: + return + + try: + await conn.executemany( + """ + INSERT INTO memory_links (from_unit_id, to_unit_id, link_type, weight, entity_id) + VALUES ($1, $2, $3, $4, $5) + ON CONFLICT (from_unit_id, to_unit_id, link_type, COALESCE(entity_id, '00000000-0000-0000-0000-000000000000'::uuid)) DO NOTHING + """, + links + ) + except Exception as e: + logger.warning(f"Failed to insert entity links: {str(e)}") + + +async def create_causal_links_batch( + conn, + unit_ids: List[str], + causal_relations_per_fact: List[List[dict]], +) -> int: + """ + Create causal links between facts based on LLM-extracted causal relationships. + + Args: + conn: Database connection + unit_ids: List of unit IDs (in same order as causal_relations_per_fact) + causal_relations_per_fact: List of causal relations for each fact. + Each element is a list of dicts with: + - target_fact_index: Index into unit_ids for the target fact + - relation_type: "causes", "caused_by", "enables", or "prevents" + - strength: Float in [0.0, 1.0] representing relationship strength + + Returns: + Number of causal links created + + Causal link types: + - "causes": This fact directly causes the target fact (forward causation) + - "caused_by": This fact was caused by the target fact (backward causation) + - "enables": This fact enables/allows the target fact (enablement) + - "prevents": This fact prevents/blocks the target fact (prevention) + """ + if not unit_ids or not causal_relations_per_fact: + return 0 + + try: + import time as time_mod + create_start = time_mod.time() + + # Build links list + links = [] + for fact_idx, causal_relations in enumerate(causal_relations_per_fact): + if not causal_relations: + continue + + from_unit_id = unit_ids[fact_idx] + + for relation in causal_relations: + target_idx = relation['target_fact_index'] + relation_type = relation['relation_type'] + strength = relation.get('strength', 1.0) + + # Validate target index + if target_idx < 0 or target_idx >= len(unit_ids): + logger.warning(f"Invalid target_fact_index {target_idx} in causal relation from fact {fact_idx}") + continue + + to_unit_id = unit_ids[target_idx] + + # Don't create self-links + if from_unit_id == to_unit_id: + continue + + # Add the causal link + # link_type is the relation_type (e.g., "causes", "caused_by") + # weight is the strength of the relationship + links.append((from_unit_id, to_unit_id, relation_type, strength, None)) + + logger.debug(f"Generated {len(links)} causal links in {time_mod.time() - create_start:.3f}s") + + if links: + insert_start = time_mod.time() + await conn.executemany( + """ + INSERT INTO memory_links (from_unit_id, to_unit_id, link_type, weight, entity_id) + VALUES ($1, $2, $3, $4, $5) + ON CONFLICT (from_unit_id, to_unit_id, link_type, COALESCE(entity_id, '00000000-0000-0000-0000-000000000000'::uuid)) DO NOTHING + """, + links + ) + logger.debug(f"Inserted {len(links)} causal links in {time_mod.time() - insert_start:.3f}s") + + return len(links) + + except Exception as e: + logger.error(f"Failed to create causal links: {str(e)}") + import traceback + traceback.print_exc() + raise diff --git a/memora/memora/llm_wrapper.py b/hindsight-api/hindsight_api/engine/llm_wrapper.py similarity index 92% rename from memora/memora/llm_wrapper.py rename to hindsight-api/hindsight_api/engine/llm_wrapper.py index 0745c8627a..cfda7add37 100644 --- a/memora/memora/llm_wrapper.py +++ b/hindsight-api/hindsight_api/engine/llm_wrapper.py @@ -182,10 +182,10 @@ async def call( @classmethod def for_memory(cls) -> "LLMConfig": """Create configuration for memory operations from environment variables.""" - provider = os.getenv("MEMORA_API_LLM_PROVIDER", "groq") - api_key = os.getenv("MEMORA_API_LLM_API_KEY") - base_url = os.getenv("MEMORA_API_LLM_BASE_URL") - model = os.getenv("MEMORA_API_LLM_MODEL", "openai/gpt-oss-120b") + provider = os.getenv("HINDSIGHT_API_LLM_PROVIDER", "groq") + api_key = os.getenv("HINDSIGHT_API_LLM_API_KEY") + base_url = os.getenv("HINDSIGHT_API_LLM_BASE_URL") + model = os.getenv("HINDSIGHT_API_LLM_MODEL", "openai/gpt-oss-120b") # Set default base URL if not provided if not base_url: @@ -211,10 +211,10 @@ def for_judge(cls) -> "LLMConfig": Falls back to memory LLM config if judge-specific config not set. """ # Check if judge-specific config exists, otherwise fall back to memory config - provider = os.getenv("MEMORA_API_JUDGE_LLM_PROVIDER", os.getenv("MEMORA_API_LLM_PROVIDER", "groq")) - api_key = os.getenv("MEMORA_API_JUDGE_LLM_API_KEY", os.getenv("MEMORA_API_LLM_API_KEY")) - base_url = os.getenv("MEMORA_API_JUDGE_LLM_BASE_URL", os.getenv("MEMORA_API_LLM_BASE_URL")) - model = os.getenv("MEMORA_API_JUDGE_LLM_MODEL", os.getenv("MEMORA_API_LLM_MODEL", "openai/gpt-oss-120b")) + provider = os.getenv("HINDSIGHT_API_JUDGE_LLM_PROVIDER", os.getenv("HINDSIGHT_API_LLM_PROVIDER", "groq")) + api_key = os.getenv("HINDSIGHT_API_JUDGE_LLM_API_KEY", os.getenv("HINDSIGHT_API_LLM_API_KEY")) + base_url = os.getenv("HINDSIGHT_API_JUDGE_LLM_BASE_URL", os.getenv("HINDSIGHT_API_LLM_BASE_URL")) + model = os.getenv("HINDSIGHT_API_JUDGE_LLM_MODEL", os.getenv("HINDSIGHT_API_LLM_MODEL", "openai/gpt-oss-120b")) # Set default base URL if not provided if not base_url: diff --git a/memora/memora/temporal_semantic_memory.py b/hindsight-api/hindsight_api/engine/memory_engine.py similarity index 89% rename from memora/memora/temporal_semantic_memory.py rename to hindsight-api/hindsight_api/engine/memory_engine.py index fcb260fa23..74550ff263 100644 --- a/memora/memora/temporal_semantic_memory.py +++ b/hindsight-api/hindsight_api/engine/memory_engine.py @@ -1,5 +1,5 @@ """ -Temporal + Semantic + Entity Memory System for AI Agents. +Memory Engine for AI Agents. This implements a sophisticated memory architecture that combines: 1. Temporal links: Memories connected by time proximity @@ -8,6 +8,7 @@ 4. Spreading activation: Search through the graph with activation decay 5. Dynamic weighting: Recency and frequency-based importance """ +import json import os from datetime import datetime, timedelta, timezone from typing import Any, Dict, List, Optional, Tuple, Union @@ -19,18 +20,26 @@ import numpy as np import uuid import logging +from pydantic import BaseModel, Field +from .query_analyzer import QueryAnalyzer from .utils import ( extract_facts, calculate_recency_weight, calculate_frequency_weight, ) from .entity_resolver import EntityResolver -from .operations import EmbeddingOperationsMixin, LinkOperationsMixin, ThinkOperationsMixin, AgentOperationsMixin +from . import ( + embedding_utils, + link_utils, + think_utils, + agent_utils, +) from .llm_wrapper import LLMConfig from .response_models import SearchResult as SearchResultModel, ThinkResult, MemoryFact from .task_backend import TaskBackend, AsyncIOQueueBackend from .search.reranking import CrossEncoderReranker +from ..pg0 import EmbeddedPostgres def utcnow(): @@ -41,8 +50,10 @@ def utcnow(): # Logger for memory system logger = logging.getLogger(__name__) -# Tiktoken for token budget filtering +from .db_utils import acquire_with_retry, retry_with_backoff + import tiktoken +from dateutil import parser as date_parser # Cache tiktoken encoding for token budget filtering (module-level singleton) _TIKTOKEN_ENCODING = None @@ -55,20 +66,15 @@ def _get_tiktoken_encoding(): return _TIKTOKEN_ENCODING -class TemporalSemanticMemory( - EmbeddingOperationsMixin, - LinkOperationsMixin, - ThinkOperationsMixin, - AgentOperationsMixin, -): +class MemoryEngine: """ Advanced memory system using temporal and semantic linking with PostgreSQL. - Uses mixin architecture for code organization: - - EmbeddingOperationsMixin: Embedding generation - - LinkOperationsMixin: Entity, temporal, and semantic link creation - - ThinkOperationsMixin: Think operations for formulating answers with opinions - - AgentOperationsMixin: Agent profile and personality management + This class provides: + - Embedding generation for semantic search + - Entity, temporal, and semantic link creation + - Think operations for formulating answers with opinions + - Agent profile and personality management """ def __init__( @@ -80,7 +86,7 @@ def __init__( memory_llm_base_url: Optional[str] = None, embeddings: Optional[Embeddings] = None, cross_encoder: Optional[CrossEncoderModel] = None, - query_analyzer: Optional["QueryAnalyzer"] = None, + query_analyzer: Optional[QueryAnalyzer] = None, pool_min_size: int = 5, pool_max_size: int = 100, task_backend: Optional[TaskBackend] = None, @@ -104,8 +110,15 @@ def __init__( Increase for parallel think/search operations (e.g., 200-300 for 100+ parallel thinks) task_backend: Custom task backend for async task execution. If not provided, uses AsyncIOQueueBackend """ + # Track pg0 instance (if used) + self._pg0: Optional[EmbeddedPostgres] = None + # Initialize PostgreSQL connection URL - self.db_url = db_url + # "pg0" or "embedded-pg" are special values that trigger embedded PostgreSQL via pg0 + # The actual URL will be set during initialize() after starting the server + self._use_pg0 = db_url in ("pg0", "embedded-pg") + self.db_url = db_url if not self._use_pg0 else None + # Set default base URL if not provided if memory_llm_base_url is None: @@ -135,7 +148,7 @@ def __init__( if query_analyzer is not None: self.query_analyzer = query_analyzer else: - from memora.query_analyzer import TransformerQueryAnalyzer + from .query_analyzer import TransformerQueryAnalyzer self.query_analyzer = TransformerQueryAnalyzer() # Initialize LLM configuration @@ -188,7 +201,7 @@ async def _handle_access_count_update(self, task_dict: Dict[str, Any]): try: # Convert string UUIDs to UUID type for faster matching uuid_list = [uuid.UUID(nid) for nid in node_ids] - async with pool.acquire() as conn: + async with acquire_with_retry(pool) as conn: await conn.execute( "UPDATE memory_units SET access_count = access_count + 1 WHERE id = ANY($1::uuid[])", uuid_list @@ -242,7 +255,7 @@ async def execute_task(self, task_dict: Dict[str, Any]): if operation_id: try: pool = await self._get_pool() - async with pool.acquire() as conn: + async with acquire_with_retry(pool) as conn: result = await conn.fetchrow( "SELECT id FROM async_operations WHERE id = $1", uuid.UUID(operation_id) @@ -297,7 +310,7 @@ async def _delete_operation_record(self, operation_id: str): """Helper to delete an operation record from the database.""" try: pool = await self._get_pool() - async with pool.acquire() as conn: + async with acquire_with_retry(pool) as conn: await conn.execute( "DELETE FROM async_operations WHERE id = $1", uuid.UUID(operation_id) @@ -314,7 +327,7 @@ async def _mark_operation_failed(self, operation_id: str, error_message: str, er full_error = f"{error_message}\n\nTraceback:\n{error_traceback}" truncated_error = full_error[:5000] if len(full_error) > 5000 else full_error - async with pool.acquire() as conn: + async with acquire_with_retry(pool) as conn: await conn.execute( """ UPDATE async_operations @@ -333,6 +346,13 @@ async def initialize(self): if self._initialized: return + # Start pg0 embedded PostgreSQL if configured + if self._use_pg0: + logger.info("Starting pg0 embedded PostgreSQL...") + self._pg0 = EmbeddedPostgres() + self.db_url = await self._pg0.ensure_running() + logger.info(f"pg0 PostgreSQL running at: {self.db_url}") + # Create connection pool # For read-heavy workloads with many parallel think/search operations, # we need a larger pool. Read operations don't need strong isolation. @@ -341,7 +361,8 @@ async def initialize(self): min_size=self._pool_min_size, max_size=self._pool_max_size, command_timeout=60, - statement_cache_size=0 # Disable prepared statement cache + statement_cache_size=0, # Disable prepared statement cache + timeout=30, # Connection acquisition timeout (seconds) ) # Initialize entity resolver with pool @@ -360,6 +381,20 @@ async def _get_pool(self) -> asyncpg.Pool: await self.initialize() return self._pool + async def _acquire_connection(self): + """ + Acquire a connection from the pool with retry logic. + + Returns an async context manager that yields a connection. + Retries on transient connection errors with exponential backoff. + """ + pool = await self._get_pool() + + async def acquire(): + return await pool.acquire() + + return await _retry_with_backoff(acquire) + async def close(self): """Close the connection pool and shutdown background workers.""" logger.info("close() started") @@ -379,6 +414,14 @@ async def close(self): logger.debug("no pool to close") self._initialized = False + + # Stop pg0 if we started it + if self._pg0 is not None: + logger.info("Stopping pg0...") + await self._pg0.stop() + self._pg0 = None + logger.info("pg0 stopped") + logger.debug("close() completed") async def wait_for_background_tasks(self): @@ -729,7 +772,8 @@ async def _put_batch_async_internal( log_buffer.append(f"{'='*60}") # Get agent name for fact extraction - profile = await self.get_agent_profile(agent_id) + pool = await self._get_pool() + profile = await agent_utils.get_agent_profile(pool, agent_id) agent_name = profile["name"] # Step 1: Extract facts from ALL contents in parallel @@ -774,7 +818,7 @@ async def _put_batch_async_internal( all_fact_texts.append(fact_dict['fact']) # Extract temporal fields (new schema with ranges) - from dateutil import parser as date_parser + try: # Try new schema first (occurred_start/end) occurred_start = date_parser.isoparse(fact_dict['occurred_start']) @@ -855,14 +899,14 @@ async def _put_batch_async_internal( # Step 2b: Generate ALL embeddings in ONE batch using augmented texts (HUGE speedup!) step_start = time.time() - all_embeddings = await self._generate_embeddings_batch(augmented_texts) + all_embeddings = await embedding_utils.generate_embeddings_batch(self.embeddings, augmented_texts) log_buffer.append(f"[2] Generate embeddings (parallel): {len(all_embeddings)} embeddings in {time.time() - step_start:.3f}s") # Step 3: Process everything in ONE database transaction logger.debug("Getting connection pool") pool = await self._get_pool() logger.debug("Acquiring connection from pool") - async with pool.acquire() as conn: + async with acquire_with_retry(pool) as conn: logger.debug("Starting transaction") async with conn.transaction(): logger.debug("Inside transaction") @@ -1035,8 +1079,8 @@ async def _put_batch_async_internal( # Process entities for ALL units logger.debug("Processing entities") step_start = time.time() - all_entity_links = await self._extract_entities_batch_optimized( - conn, agent_id, created_unit_ids, filtered_sentences, "", filtered_dates, filtered_entities, log_buffer + all_entity_links = await link_utils.extract_entities_batch_optimized( + self.entity_resolver, conn, agent_id, created_unit_ids, filtered_sentences, "", filtered_dates, filtered_entities, log_buffer ) logger.debug(f"Entity processing complete: {len(all_entity_links)} links") log_buffer.append(f"[6] Process entities (batched): {time.time() - step_start:.3f}s") @@ -1044,14 +1088,14 @@ async def _put_batch_async_internal( # Create temporal links logger.debug("Creating temporal links") step_start = time.time() - await self._create_temporal_links_batch_per_fact(conn, agent_id, created_unit_ids, log_buffer=log_buffer) + await link_utils.create_temporal_links_batch_per_fact(conn, agent_id, created_unit_ids, log_buffer=log_buffer) logger.debug("Temporal links complete") log_buffer.append(f"[7] Batch create temporal links: {time.time() - step_start:.3f}s") # Create semantic links logger.debug("Creating semantic links") step_start = time.time() - await self._create_semantic_links_batch(conn, agent_id, created_unit_ids, filtered_embeddings, log_buffer=log_buffer) + await link_utils.create_semantic_links_batch(conn, agent_id, created_unit_ids, filtered_embeddings, log_buffer=log_buffer) logger.debug("Semantic links complete") log_buffer.append(f"[8] Batch create semantic links: {time.time() - step_start:.3f}s") @@ -1059,14 +1103,14 @@ async def _put_batch_async_internal( logger.debug("Inserting entity links") step_start = time.time() if all_entity_links: - await self._insert_entity_links_batch(conn, all_entity_links) + await link_utils.insert_entity_links_batch(conn, all_entity_links) logger.debug("Entity links inserted") log_buffer.append(f"[9] Batch insert entity links: {time.time() - step_start:.3f}s") # Create causal links logger.debug("Creating causal links") step_start = time.time() - causal_link_count = await self._create_causal_links_batch( + causal_link_count = await link_utils.create_causal_links_batch( conn, created_unit_ids, filtered_causal_relations ) logger.debug(f"Causal links complete: {causal_link_count} links created") @@ -1261,7 +1305,7 @@ async def _search_with_retries( try: # Step 1: Generate query embedding (for semantic search) step_start = time.time() - query_embedding = self._generate_embedding(query) + query_embedding = embedding_utils.generate_embedding(self.embeddings, query) step_duration = time.time() - step_start log_buffer.append(f" [1] Generate query embedding: {step_duration:.3f}s") @@ -1593,7 +1637,7 @@ async def get_document(self, document_id: str, agent_id: str) -> Optional[Dict[s Dictionary with document info or None if not found """ pool = await self._get_pool() - async with pool.acquire() as conn: + async with acquire_with_retry(pool) as conn: doc = await conn.fetchrow( """ SELECT d.id, d.agent_id, d.original_text, d.content_hash, @@ -1631,7 +1675,7 @@ async def delete_document(self, document_id: str, agent_id: str) -> Dict[str, in Dictionary with counts of deleted items """ pool = await self._get_pool() - async with pool.acquire() as conn: + async with acquire_with_retry(pool) as conn: async with conn.transaction(): # Count units before deletion units_count = await conn.fetchval( @@ -1666,7 +1710,7 @@ async def delete_memory_unit(self, unit_id: str) -> Dict[str, Any]: Dictionary with deletion result """ pool = await self._get_pool() - async with pool.acquire() as conn: + async with acquire_with_retry(pool) as conn: async with conn.transaction(): # Delete the memory unit (cascades to links and associations) deleted = await conn.fetchval( @@ -1700,7 +1744,7 @@ async def delete_agent(self, agent_id: str, fact_type: Optional[str] = None) -> Dictionary with counts of deleted items """ pool = await self._get_pool() - async with pool.acquire() as conn: + async with acquire_with_retry(pool) as conn: async with conn.transaction(): try: if fact_type: @@ -1751,7 +1795,7 @@ async def get_graph_data(self, agent_id: Optional[str] = None, fact_type: Option Dict with nodes, edges, and table_rows """ pool = await self._get_pool() - async with pool.acquire() as conn: + async with acquire_with_retry(pool) as conn: # Get memory units, optionally filtered by agent_id and fact_type query_conditions = [] query_params = [] @@ -1922,7 +1966,7 @@ async def list_memory_units( Dict with items (list of memory units) and total count """ pool = await self._get_pool() - async with pool.acquire() as conn: + async with acquire_with_retry(pool) as conn: # Build query conditions query_conditions = [] query_params = [] @@ -2036,7 +2080,7 @@ async def list_documents( Dict with items (list of documents without original_text) and total count """ pool = await self._get_pool() - async with pool.acquire() as conn: + async with acquire_with_retry(pool) as conn: # Build query conditions query_conditions = [] query_params = [] @@ -2153,7 +2197,7 @@ async def get_document( Dict with document details including original_text, or None if not found """ pool = await self._get_pool() - async with pool.acquire() as conn: + async with acquire_with_retry(pool) as conn: doc = await conn.fetchrow(""" SELECT id, @@ -2336,7 +2380,7 @@ async def _reinforce_opinions_async( logger.debug(f"[REINFORCE] Starting opinion reinforcement for {len(entity_names)} entities") pool = await self._get_pool() - async with pool.acquire() as conn: + async with acquire_with_retry(pool) as conn: # Find all opinions related to these entities opinions = await conn.fetch( """ @@ -2439,3 +2483,229 @@ async def _reinforce_opinions_async( import traceback traceback.print_exc() + # ==================== Agent Profile Methods ==================== + + async def get_agent_profile(self, agent_id: str) -> Dict: + """ + Get agent profile (name, personality + background). + Auto-creates agent with default values if not exists. + + Args: + agent_id: Agent identifier + + Returns: + Dict with 'name' (str), 'personality' (dict) and 'background' (str) keys + """ + pool = await self._get_pool() + return await agent_utils.get_agent_profile(pool, agent_id) + + async def update_agent_personality( + self, + agent_id: str, + personality: Dict[str, float] + ) -> None: + """ + Update agent personality traits. + + Args: + agent_id: Agent identifier + personality: Dict with Big Five traits + bias_strength (all 0-1) + """ + pool = await self._get_pool() + await agent_utils.update_agent_personality(pool, agent_id, personality) + + async def merge_agent_background( + self, + agent_id: str, + new_info: str, + update_personality: bool = True + ) -> dict: + """ + Merge new background information with existing background using LLM. + Normalizes to first person ("I") and resolves conflicts. + Optionally infers personality traits from the merged background. + + Args: + agent_id: Agent identifier + new_info: New background information to add/merge + update_personality: If True, infer Big Five traits from background (default: True) + + Returns: + Dict with 'background' (str) and optionally 'personality' (dict) keys + """ + pool = await self._get_pool() + return await agent_utils.merge_agent_background( + pool, self._llm_config, agent_id, new_info, update_personality + ) + + async def list_agents(self) -> list: + """ + List all agents in the system. + + Returns: + List of dicts with agent_id, name, personality, background, created_at, updated_at + """ + pool = await self._get_pool() + return await agent_utils.list_agents(pool) + + # ==================== Think Methods ==================== + + async def think_async( + self, + agent_id: str, + query: str, + thinking_budget: int = 50, + context: str = None, + ) -> ThinkResult: + """ + Think and formulate an answer using agent identity, world facts, and opinions. + + This method: + 1. Retrieves agent facts (agent's identity and past actions) + 2. Retrieves world facts (general knowledge) + 3. Retrieves existing opinions (agent's formed perspectives) + 4. Uses LLM to formulate an answer + 5. Extracts and stores any new opinions formed during thinking + 6. Returns plain text answer and the facts used + + Args: + agent_id: Agent identifier + query: Question to answer + thinking_budget: Number of memory units to explore + context: Additional context string to include in LLM prompt (not used in search) + + Returns: + ThinkResult containing: + - text: Plain text answer (no markdown) + - based_on: Dict with 'world', 'agent', and 'opinion' fact lists (MemoryFact objects) + - new_opinions: List of newly formed opinions + """ + # Use cached LLM config + if self._llm_config is None: + raise ValueError("Memory LLM API key not set. Set HINDSIGHT_API_LLM_API_KEY environment variable.") + + # Steps 1-3: Run multi-fact-type search (12-way retrieval: 4 methods ร— 3 fact types) + search_result = await self.search_async( + agent_id=agent_id, + query=query, + thinking_budget=thinking_budget, + max_tokens=4096, + enable_trace=False, + fact_type=['agent', 'world', 'opinion'] + ) + + all_results = search_result.results + logger.info(f"[THINK] Search returned {len(all_results)} results") + + # Split results by fact type for structured response + agent_results = [r for r in all_results if r.fact_type == 'agent'] + world_results = [r for r in all_results if r.fact_type == 'world'] + opinion_results = [r for r in all_results if r.fact_type == 'opinion'] + + logger.info(f"[THINK] Split results - agent: {len(agent_results)}, world: {len(world_results)}, opinion: {len(opinion_results)}") + + # Format facts for LLM + agent_facts_text = think_utils.format_facts_for_prompt(agent_results) + world_facts_text = think_utils.format_facts_for_prompt(world_results) + opinion_facts_text = think_utils.format_facts_for_prompt(opinion_results) + + logger.info(f"[THINK] Formatted facts - agent: {len(agent_facts_text)} chars, world: {len(world_facts_text)} chars, opinion: {len(opinion_facts_text)} chars") + + # Get agent profile (name, personality + background) + profile = await self.get_agent_profile(agent_id) + name = profile["name"] + personality = profile["personality"] + background = profile["background"] + + # Build the prompt + prompt = think_utils.build_think_prompt( + agent_facts_text=agent_facts_text, + world_facts_text=world_facts_text, + opinion_facts_text=opinion_facts_text, + query=query, + name=name, + personality=personality, + background=background, + context=context, + ) + + logger.info(f"[THINK] Full prompt length: {len(prompt)} chars") + logger.debug(f"[THINK] Prompt preview (first 500 chars): {prompt[:500]}") + + system_message = think_utils.get_system_message(personality) + + answer_text = await self._llm_config.call( + messages=[ + {"role": "system", "content": system_message}, + {"role": "user", "content": prompt} + ], + scope="memory_think", + temperature=0.9, + max_tokens=1000 + ) + + answer_text = answer_text.strip() + + # Submit form_opinion task for background processing + logger.debug(f"[THINK] Submitting form_opinion task for agent {agent_id}") + await self._task_backend.submit_task({ + 'type': 'form_opinion', + 'agent_id': agent_id, + 'answer_text': answer_text, + 'query': query + }) + logger.debug(f"[THINK] form_opinion task submitted") + + # Return response with facts split by type + return ThinkResult( + text=answer_text, + based_on={ + "world": world_results, + "agent": agent_results, + "opinion": opinion_results + }, + new_opinions=[] # Opinions are being extracted asynchronously + ) + + async def _extract_and_store_opinions_async( + self, + agent_id: str, + answer_text: str, + query: str + ): + """ + Background task to extract and store opinions from think response. + + This runs asynchronously and does not block the think response. + + Args: + agent_id: Agent identifier + answer_text: The generated answer text + query: The original query + """ + try: + logger.debug(f"[THINK] Extracting opinions from answer for agent {agent_id}") + # Extract opinions from the answer + new_opinions = await think_utils.extract_opinions_from_text( + self._llm_config, text=answer_text, query=query + ) + logger.debug(f"[THINK] Extracted {len(new_opinions)} opinions") + + # Store new opinions + if new_opinions: + from datetime import datetime, timezone + current_time = datetime.now(timezone.utc) + for opinion_dict in new_opinions: + await self.put_async( + agent_id=agent_id, + content=opinion_dict["text"], + context=f"formed during thinking about: {query}", + event_date=current_time, + fact_type_override='opinion', + confidence_score=opinion_dict["confidence"] + ) + + logger.debug(f"[THINK] Extracted and stored {len(new_opinions)} new opinions") + except Exception as e: + logger.warning(f"[THINK] Failed to extract/store opinions: {str(e)}") + diff --git a/memora/memora/query_analyzer.py b/hindsight-api/hindsight_api/engine/query_analyzer.py similarity index 100% rename from memora/memora/query_analyzer.py rename to hindsight-api/hindsight_api/engine/query_analyzer.py diff --git a/memora/memora/response_models.py b/hindsight-api/hindsight_api/engine/response_models.py similarity index 59% rename from memora/memora/response_models.py rename to hindsight-api/hindsight_api/engine/response_models.py index 85c7e9cf94..758d1ea41c 100644 --- a/memora/memora/response_models.py +++ b/hindsight-api/hindsight_api/engine/response_models.py @@ -1,13 +1,13 @@ """ -Core response models for Memora memory system. +Core response models for Hindsight memory system. -These models define the structure of data returned by the core TemporalSemanticMemory class. +These models define the structure of data returned by the core MemoryEngine class. API response models should be kept separate and convert from these core models to maintain API stability even if internal models change. """ from typing import Optional, List, Dict, Any -from pydantic import BaseModel, Field +from pydantic import BaseModel, Field, ConfigDict class MemoryFact(BaseModel): @@ -17,6 +17,19 @@ class MemoryFact(BaseModel): This represents a unit of information stored in the memory system, including both the content and metadata. """ + model_config = ConfigDict(json_schema_extra={ + "example": { + "id": "123e4567-e89b-12d3-a456-426614174000", + "text": "Alice works at Google on the AI team", + "fact_type": "world", + "context": "work info", + "event_date": "2024-01-15T10:30:00Z", + "document_id": "session_abc123", + "metadata": {"source": "slack"}, + "activation": 0.95 + } + }) + id: str = Field(description="Unique identifier for the memory fact") text: str = Field(description="The actual text content of the memory") fact_type: str = Field(description="Type of fact: 'world', 'agent', or 'opinion'") @@ -31,20 +44,6 @@ class MemoryFact(BaseModel): # Internal metrics (used by system but may not be exposed in API) activation: Optional[float] = Field(None, description="Internal activation score") - class Config: - json_schema_extra = { - "example": { - "id": "123e4567-e89b-12d3-a456-426614174000", - "text": "Alice works at Google on the AI team", - "fact_type": "world", - "context": "work info", - "event_date": "2024-01-15T10:30:00Z", - "document_id": "session_abc123", - "metadata": {"source": "slack"}, - "activation": 0.95 - } - } - class SearchResult(BaseModel): """ @@ -53,28 +52,27 @@ class SearchResult(BaseModel): Contains a list of matching memory facts and optional trace information for debugging and transparency. """ - results: List[MemoryFact] = Field(description="List of memory facts matching the query") - trace: Optional[Dict[str, Any]] = Field(None, description="Trace information for debugging") - - class Config: - json_schema_extra = { - "example": { - "results": [ - { - "id": "123e4567-e89b-12d3-a456-426614174000", - "text": "Alice works at Google on the AI team", - "fact_type": "world", - "context": "work info", - "event_date": "2024-01-15T10:30:00Z", - "activation": 0.95 - } - ], - "trace": { - "query": "What did Alice say about machine learning?", - "num_results": 1 + model_config = ConfigDict(json_schema_extra={ + "example": { + "results": [ + { + "id": "123e4567-e89b-12d3-a456-426614174000", + "text": "Alice works at Google on the AI team", + "fact_type": "world", + "context": "work info", + "event_date": "2024-01-15T10:30:00Z", + "activation": 0.95 } + ], + "trace": { + "query": "What did Alice say about machine learning?", + "num_results": 1 } } + }) + + results: List[MemoryFact] = Field(description="List of memory facts matching the query") + trace: Optional[Dict[str, Any]] = Field(None, description="Trace information for debugging") class ThinkResult(BaseModel): @@ -84,6 +82,28 @@ class ThinkResult(BaseModel): Contains the formulated answer, the facts it was based on (organized by type), and any new opinions that were formed during the thinking process. """ + model_config = ConfigDict(json_schema_extra={ + "example": { + "text": "Based on my knowledge, machine learning is being actively used in healthcare...", + "based_on": { + "world": [ + { + "id": "123e4567-e89b-12d3-a456-426614174000", + "text": "Machine learning is used in medical diagnosis", + "fact_type": "world", + "context": "healthcare", + "event_date": "2024-01-15T10:30:00Z" + } + ], + "agent": [], + "opinion": [] + }, + "new_opinions": [ + "Machine learning has great potential in healthcare" + ] + } + }) + text: str = Field(description="The formulated answer text") based_on: Dict[str, List[MemoryFact]] = Field( description="Facts used to formulate the answer, organized by type (world, agent, opinion)" @@ -93,29 +113,6 @@ class ThinkResult(BaseModel): description="List of newly formed opinions during thinking" ) - class Config: - json_schema_extra = { - "example": { - "text": "Based on my knowledge, machine learning is being actively used in healthcare...", - "based_on": { - "world": [ - { - "id": "123e4567-e89b-12d3-a456-426614174000", - "text": "Machine learning is used in medical diagnosis", - "fact_type": "world", - "context": "healthcare", - "event_date": "2024-01-15T10:30:00Z" - } - ], - "agent": [], - "opinion": [] - }, - "new_opinions": [ - "Machine learning has great potential in healthcare" - ] - } - } - class Opinion(BaseModel): """ @@ -124,13 +121,12 @@ class Opinion(BaseModel): Opinions represent the agent's formed perspectives on topics, with a confidence level indicating strength of belief. """ + model_config = ConfigDict(json_schema_extra={ + "example": { + "text": "Machine learning has great potential in healthcare", + "confidence": 0.85 + } + }) + text: str = Field(description="The opinion text") confidence: float = Field(description="Confidence score between 0.0 and 1.0") - - class Config: - json_schema_extra = { - "example": { - "text": "Machine learning has great potential in healthcare", - "confidence": 0.85 - } - } diff --git a/memora/memora/search/__init__.py b/hindsight-api/hindsight_api/engine/search/__init__.py similarity index 100% rename from memora/memora/search/__init__.py rename to hindsight-api/hindsight_api/engine/search/__init__.py diff --git a/memora/memora/search/reranking.py b/hindsight-api/hindsight_api/engine/search/reranking.py similarity index 96% rename from memora/memora/search/reranking.py rename to hindsight-api/hindsight_api/engine/search/reranking.py index 71a57a3cc3..732f73350f 100644 --- a/memora/memora/search/reranking.py +++ b/hindsight-api/hindsight_api/engine/search/reranking.py @@ -24,7 +24,7 @@ def __init__(self, cross_encoder=None): SentenceTransformersCrossEncoder with ms-marco-MiniLM-L-6-v2 """ if cross_encoder is None: - from ..cross_encoder import SentenceTransformersCrossEncoder + from hindsight_api.engine.cross_encoder import SentenceTransformersCrossEncoder cross_encoder = SentenceTransformersCrossEncoder() self.cross_encoder = cross_encoder diff --git a/memora/memora/search/retrieval.py b/hindsight-api/hindsight_api/engine/search/retrieval.py similarity index 94% rename from memora/memora/search/retrieval.py rename to hindsight-api/hindsight_api/engine/search/retrieval.py index 6aa5b2fcf0..c3010017c4 100644 --- a/memora/memora/search/retrieval.py +++ b/hindsight-api/hindsight_api/engine/search/retrieval.py @@ -11,6 +11,7 @@ from typing import List, Dict, Any, Tuple, Optional from datetime import datetime import asyncio +from ..db_utils import acquire_with_retry async def retrieve_semantic( @@ -241,11 +242,6 @@ async def retrieve_temporal( if end_date.tzinfo is None: end_date = end_date.replace(tzinfo=timezone.utc) - # Find entry points: facts in date range with semantic relevance - import logging - logger = logging.getLogger(__name__) - logger.info(f"Temporal retrieval: searching for facts between {start_date} and {end_date} (agent={agent_id}, fact_type={fact_type})") - entry_points = await conn.fetch( """ SELECT id, text, context, event_date, occurred_start, occurred_end, mentioned_at, access_count, embedding, fact_type, document_id, @@ -274,8 +270,6 @@ async def retrieve_temporal( query_emb_str, agent_id, fact_type, start_date, end_date, semantic_threshold ) - logger.info(f"Temporal retrieval: found {len(entry_points)} entry points") - if not entry_points: # Check if there are ANY memories with temporal metadata for this agent total_with_dates = await conn.fetchval( @@ -284,7 +278,6 @@ async def retrieve_temporal( AND (occurred_start IS NOT NULL OR occurred_end IS NOT NULL OR mentioned_at IS NOT NULL)""", agent_id, fact_type ) - logger.info(f"Temporal retrieval: agent has {total_with_dates} total memories with temporal metadata (fact_type={fact_type})") return [] # Calculate temporal scores for entry points @@ -442,26 +435,20 @@ async def retrieve_parallel( query_text, reference_date=question_date, analyzer=query_analyzer ) - if temporal_constraint: - logger.info(f"Temporal constraint detected in retrieve_parallel: {temporal_constraint[0]} to {temporal_constraint[1]}") - else: - logger.info("No temporal constraint in retrieve_parallel") - - # Each retrieval needs its own connection async def run_semantic(): - async with pool.acquire() as conn: + async with acquire_with_retry(pool) as conn: return await retrieve_semantic(conn, query_embedding_str, agent_id, fact_type, limit=thinking_budget) async def run_bm25(): - async with pool.acquire() as conn: + async with acquire_with_retry(pool) as conn: return await retrieve_bm25(conn, query_text, agent_id, fact_type, limit=thinking_budget) async def run_graph(): - async with pool.acquire() as conn: + async with acquire_with_retry(pool) as conn: return await retrieve_graph(conn, query_embedding_str, agent_id, fact_type, budget=thinking_budget) async def run_temporal(start_date, end_date): - async with pool.acquire() as conn: + async with acquire_with_retry(pool) as conn: return await retrieve_temporal( conn, query_embedding_str, agent_id, fact_type, start_date, end_date, budget=thinking_budget, semantic_threshold=0.4 diff --git a/memora/memora/search/temporal_extraction.py b/hindsight-api/hindsight_api/engine/search/temporal_extraction.py similarity index 87% rename from memora/memora/search/temporal_extraction.py rename to hindsight-api/hindsight_api/engine/search/temporal_extraction.py index 4ad57ed019..af506c46b6 100644 --- a/memora/memora/search/temporal_extraction.py +++ b/hindsight-api/hindsight_api/engine/search/temporal_extraction.py @@ -7,7 +7,7 @@ from typing import Optional, Tuple from datetime import datetime import logging -from memora.query_analyzer import QueryAnalyzer, TransformerQueryAnalyzer +from hindsight_api.engine.query_analyzer import QueryAnalyzer, TransformerQueryAnalyzer logger = logging.getLogger(__name__) @@ -59,8 +59,6 @@ def extract_temporal_constraint( analysis.temporal_constraint.start_date, analysis.temporal_constraint.end_date ) - logger.info(f"Temporal constraint extracted: {result[0].strftime('%Y-%m-%d')} to {result[1].strftime('%Y-%m-%d')}") return result - logger.info("No temporal constraint found in query") return None diff --git a/memora/memora/search_helpers.py b/hindsight-api/hindsight_api/engine/search_helpers.py similarity index 100% rename from memora/memora/search_helpers.py rename to hindsight-api/hindsight_api/engine/search_helpers.py diff --git a/memora/memora/search_trace.py b/hindsight-api/hindsight_api/engine/search_trace.py similarity index 100% rename from memora/memora/search_trace.py rename to hindsight-api/hindsight_api/engine/search_trace.py diff --git a/memora/memora/search_tracer.py b/hindsight-api/hindsight_api/engine/search_tracer.py similarity index 100% rename from memora/memora/search_tracer.py rename to hindsight-api/hindsight_api/engine/search_tracer.py diff --git a/memora/memora/task_backend.py b/hindsight-api/hindsight_api/engine/task_backend.py similarity index 98% rename from memora/memora/task_backend.py rename to hindsight-api/hindsight_api/engine/task_backend.py index 20972aaa4d..051e6cd15d 100644 --- a/memora/memora/task_backend.py +++ b/hindsight-api/hindsight_api/engine/task_backend.py @@ -23,7 +23,7 @@ class TaskBackend(ABC): 2. Execute tasks through a provided executor callback The backend treats tasks as pure dictionaries that can be serialized - and sent over the network. The executor (typically TemporalSemanticMemory.execute_task) + and sent over the network. The executor (typically MemoryEngine.execute_task) receives the dict and routes it to the appropriate handler. """ diff --git a/hindsight-api/hindsight_api/engine/think_utils.py b/hindsight-api/hindsight_api/engine/think_utils.py new file mode 100644 index 0000000000..04d0504368 --- /dev/null +++ b/hindsight-api/hindsight_api/engine/think_utils.py @@ -0,0 +1,255 @@ +""" +Think operation utilities for formulating answers based on agent and world facts. +""" + +import asyncio +import logging +import re +from datetime import datetime, timezone +from typing import Dict, List, Any +from pydantic import BaseModel, Field + +from .response_models import ThinkResult, MemoryFact + +logger = logging.getLogger(__name__) + + +class Opinion(BaseModel): + """An opinion formed by the agent.""" + opinion: str = Field(description="The opinion or perspective with reasoning included") + confidence: float = Field(description="Confidence score for this opinion (0.0 to 1.0, where 1.0 is very confident)") + + +class OpinionExtractionResponse(BaseModel): + """Response containing extracted opinions.""" + opinions: List[Opinion] = Field( + default_factory=list, + description="List of opinions formed with their supporting reasons and confidence scores" + ) + + +def describe_trait(name: str, value: float) -> str: + """Convert trait value to descriptive text.""" + if value >= 0.8: + return f"very high {name}" + elif value >= 0.6: + return f"high {name}" + elif value >= 0.4: + return f"moderate {name}" + elif value >= 0.2: + return f"low {name}" + else: + return f"very low {name}" + + +def build_personality_description(personality: Dict) -> str: + """Build a personality description string from personality traits.""" + return f"""Your personality traits: +- {describe_trait('openness to new ideas', personality['openness'])} +- {describe_trait('conscientiousness and organization', personality['conscientiousness'])} +- {describe_trait('extraversion and sociability', personality['extraversion'])} +- {describe_trait('agreeableness and cooperation', personality['agreeableness'])} +- {describe_trait('emotional sensitivity', personality['neuroticism'])} + +Personality influence strength: {int(personality['bias_strength'] * 100)}% (how much your personality shapes your opinions)""" + + +def format_facts_for_prompt(facts: List[MemoryFact]) -> str: + """Format facts as JSON for LLM prompt.""" + import json + + if not facts: + return "[]" + formatted = [] + for fact in facts: + fact_obj = { + "text": fact.text + } + + # Add context if available + if fact.context: + fact_obj["context"] = fact.context + + # Add event_date if available + if fact.event_date: + event_date = fact.event_date + if isinstance(event_date, str): + fact_obj["event_date"] = event_date + elif isinstance(event_date, datetime): + fact_obj["event_date"] = event_date.strftime('%Y-%m-%d %H:%M:%S') + + # Add activation if available + if fact.activation is not None: + fact_obj["score"] = fact.activation + + formatted.append(fact_obj) + + return json.dumps(formatted, indent=2) + + +def build_think_prompt( + agent_facts_text: str, + world_facts_text: str, + opinion_facts_text: str, + query: str, + name: str, + personality: Dict, + background: str, + context: str = None, +) -> str: + """Build the think prompt for the LLM.""" + personality_desc = build_personality_description(personality) + + name_section = f""" + +Your name: {name} +""" + + background_section = "" + if background: + background_section = f""" + +Your background: +{background} +""" + + context_section = "" + if context: + context_section = f""" +ADDITIONAL CONTEXT: +{context} + +""" + + return f"""Here's what I know and have experienced: + +MY IDENTITY & EXPERIENCES: +{agent_facts_text} + +WHAT I KNOW ABOUT THE WORLD: +{world_facts_text} + +MY EXISTING OPINIONS & BELIEFS: +{opinion_facts_text} + +{context_section}{name_section}{personality_desc}{background_section} + +QUESTION: {query} + +Based on everything I know, believe, and who I am (including my name, personality and background), here's what I genuinely think about this question. I'll draw on my experiences, knowledge, opinions, and personal traits to give you my honest perspective.""" + + +def get_system_message(personality: Dict) -> str: + """Get the system message for the think LLM call.""" + bias_strength = personality['bias_strength'] + if bias_strength >= 0.7: + personality_instruction = "Your personality strongly influences your thinking. Let your traits guide how you interpret facts and form opinions. Don't be afraid to be biased based on your personality." + elif bias_strength >= 0.4: + personality_instruction = "Your personality moderately influences your thinking. Balance your personal traits with objective analysis." + else: + personality_instruction = "Your personality has minimal influence on your thinking. Focus primarily on facts while keeping your traits in mind." + + return f"You are a person with your own thoughts, experiences, opinions, and personality. When asked a question, respond naturally like a human would - share what you genuinely think based on what you know and have experienced. {personality_instruction} Be direct, express your views confidently, and use 'I think', 'I believe', 'in my view', etc. Respond in plain text without markdown formatting." + + +async def extract_opinions_from_text( + llm_config, + text: str, + query: str +) -> List[Dict[str, Any]]: + """ + Extract opinions with reasons and confidence from text using LLM. + + Args: + llm_config: LLM configuration to use + text: Text to extract opinions from + query: The original query that prompted this response + + Returns: + List of dicts with keys: 'text' (opinion with reasons), 'confidence' (score 0-1) + """ + extraction_prompt = f"""Extract any NEW opinions or perspectives from the answer below and rewrite them in FIRST-PERSON as if YOU are stating the opinion directly. + +ORIGINAL QUESTION: +{query} + +ANSWER PROVIDED: +{text} + +Your task: Find opinions in the answer and rewrite them AS IF YOU ARE THE ONE SAYING THEM. + +An opinion is a judgment, viewpoint, or conclusion that goes beyond just stating facts. + +IMPORTANT: Do NOT extract statements like: +- "I don't have enough information" +- "The facts don't contain information about X" +- "I cannot answer because..." + +ONLY extract actual opinions about substantive topics. + +CRITICAL FORMAT REQUIREMENTS: +1. **ALWAYS start with first-person phrases**: "I think...", "I believe...", "In my view...", "I've come to believe...", "Previously I thought... but now..." +2. **NEVER use third-person**: Do NOT say "The speaker thinks..." or "They believe..." - always use "I" +3. Include the reasoning naturally within the statement +4. Provide a confidence score (0.0 to 1.0) + +CORRECT Examples (โœ“ FIRST-PERSON): +- "I think Alice is more reliable because she consistently delivers on time and writes clean code" +- "Previously I thought all engineers were equal, but now I feel that experience and track record really matter" +- "I believe reliability is best measured by consistent output over time" +- "I've come to believe that track records are more important than potential" + +WRONG Examples (โœ— THIRD-PERSON - DO NOT USE): +- "The speaker thinks Alice is more reliable" +- "They believe reliability matters" +- "It is believed that Alice is better" + +If no genuine opinions are expressed (e.g., the response just says "I don't know"), return an empty list.""" + + try: + result = await llm_config.call( + messages=[ + {"role": "system", "content": "You are converting opinions from text into first-person statements. Always use 'I think', 'I believe', 'I feel', etc. NEVER use third-person like 'The speaker' or 'They'."}, + {"role": "user", "content": extraction_prompt} + ], + response_format=OpinionExtractionResponse, + scope="memory_extract_opinion" + ) + + # Format opinions with confidence score and convert to first-person + formatted_opinions = [] + for op in result.opinions: + # Convert third-person to first-person if needed + opinion_text = op.opinion + + # Replace common third-person patterns with first-person + def singularize_verb(verb): + if verb.endswith('es'): + return verb[:-1] # believes -> believe + elif verb.endswith('s'): + return verb[:-1] # thinks -> think + return verb + + # Pattern: "The speaker/user [verb]..." -> "I [verb]..." + match = re.match(r'^(The speaker|The user|They|It is believed) (believes?|thinks?|feels?|says|asserts?|considers?)(\s+that)?(.*)$', opinion_text, re.IGNORECASE) + if match: + verb = singularize_verb(match.group(2)) + that_part = match.group(3) or "" # Keep " that" if present + rest = match.group(4) + opinion_text = f"I {verb}{that_part}{rest}" + + # If still doesn't start with first-person, prepend "I believe that " + first_person_starters = ["I think", "I believe", "I feel", "In my view", "I've come to believe", "Previously I"] + if not any(opinion_text.startswith(starter) for starter in first_person_starters): + opinion_text = "I believe that " + opinion_text[0].lower() + opinion_text[1:] + + formatted_opinions.append({ + "text": opinion_text, + "confidence": op.confidence + }) + + return formatted_opinions + + except Exception as e: + logger.warning(f"Failed to extract opinions: {str(e)}") + return [] diff --git a/memora/memora/utils.py b/hindsight-api/hindsight_api/engine/utils.py similarity index 100% rename from memora/memora/utils.py rename to hindsight-api/hindsight_api/engine/utils.py diff --git a/memora/memora/migrations.py b/hindsight-api/hindsight_api/migrations.py similarity index 87% rename from memora/memora/migrations.py rename to hindsight-api/hindsight_api/migrations.py index ca3502f486..94688cdda1 100644 --- a/memora/memora/migrations.py +++ b/hindsight-api/hindsight_api/migrations.py @@ -37,14 +37,14 @@ def run_migrations(database_url: str, script_location: Optional[str] = None) -> Args: database_url: SQLAlchemy database URL (e.g., "postgresql://user:pass@host/db") script_location: Path to alembic migrations directory (e.g., "/path/to/alembic"). - If None, defaults to memora/alembic directory. + If None, defaults to hindsight-api/alembic directory. Raises: RuntimeError: If migrations fail to complete FileNotFoundError: If script_location doesn't exist Example: - # Using default location (memora package) + # Using default location (hindsight_api package) run_migrations("postgresql://user:pass@host/db") # Using custom location (when importing from another project) @@ -56,9 +56,9 @@ def run_migrations(database_url: str, script_location: Optional[str] = None) -> try: # Determine script location if script_location is None: - # Default: use the alembic directory in the memora package - # This file is in: memora/memora/migrations.py - # Default location is: memora/alembic + # Default: use the alembic directory in the hindsight_api package + # This file is in: hindsight-api/hindsight_api/migrations.py + # Default location is: hindsight-api/alembic package_root = Path(__file__).parent.parent script_location = str(package_root / "alembic") @@ -86,6 +86,9 @@ def run_migrations(database_url: str, script_location: Optional[str] = None) -> # Uses Python's logging system instead of alembic.ini alembic_cfg.set_main_option("prepend_sys_path", ".") + # Set path_separator to avoid deprecation warning + alembic_cfg.set_main_option("path_separator", "os") + # Run migrations to head (latest version) # Note: Alembic may call sys.exit() on errors instead of raising exceptions # We rely on the outer try/except and logging to catch issues @@ -110,7 +113,7 @@ def check_migration_status(database_url: Optional[str] = None, script_location: Check current database schema version and latest available version. Args: - database_url: SQLAlchemy database URL. If None, uses MEMORA_API_DATABASE_URL env var. + database_url: SQLAlchemy database URL. If None, uses HINDSIGHT_API_DATABASE_URL env var. script_location: Path to alembic migrations directory. If None, uses default location. Returns: @@ -124,9 +127,9 @@ def check_migration_status(database_url: Optional[str] = None, script_location: # Get database URL if database_url is None: - database_url = os.getenv("MEMORA_API_DATABASE_URL") + database_url = os.getenv("HINDSIGHT_API_DATABASE_URL") if not database_url: - logger.warning("Database URL not provided and MEMORA_API_DATABASE_URL not set, cannot check migration status") + logger.warning("Database URL not provided and HINDSIGHT_API_DATABASE_URL not set, cannot check migration status") return None, None # Get current revision from database @@ -148,6 +151,7 @@ def check_migration_status(database_url: Optional[str] = None, script_location: # Create config programmatically alembic_cfg = Config() alembic_cfg.set_main_option("script_location", script_location) + alembic_cfg.set_main_option("path_separator", "os") script = ScriptDirectory.from_config(alembic_cfg) head_rev = script.get_current_head() diff --git a/memora/memora/models.py b/hindsight-api/hindsight_api/models.py similarity index 100% rename from memora/memora/models.py rename to hindsight-api/hindsight_api/models.py diff --git a/hindsight-api/hindsight_api/pg0.py b/hindsight-api/hindsight_api/pg0.py new file mode 100644 index 0000000000..c8b8f46b33 --- /dev/null +++ b/hindsight-api/hindsight_api/pg0.py @@ -0,0 +1,416 @@ +import asyncio +import json +import logging +import os +import platform +import shutil +import stat +import subprocess +import sys +from pathlib import Path +from typing import Optional + +import httpx + +logger = logging.getLogger(__name__) + +DEFAULT_DATA_DIR = Path(os.environ.get("HINDSIGHT_API_PG0_DATA_DIR", Path.home() / ".hindsight" / "pg_data")) +DEFAULT_INSTALL_DIR = Path.home() / ".hindsight" / "bin" +BINARY_NAME = "pg0" +DEFAULT_PORT = 5555 +DEFAULT_USERNAME = "hindsight" +DEFAULT_PASSWORD = "hindsight" +DEFAULT_DATABASE = "hindsight" + + +def get_platform_binary_name() -> str: + """Get the appropriate binary name for the current platform. + + Supported platforms: + - macOS ARM64 (darwin-aarch64) + - Linux x86_64 + - Windows x86_64 + """ + system = platform.system().lower() + machine = platform.machine().lower() + + # Normalize architecture names + if machine in ("x86_64", "amd64"): + arch = "x86_64" + elif machine in ("arm64", "aarch64"): + arch = "aarch64" + else: + raise RuntimeError( + f"Embedded PostgreSQL is not supported on architecture: {machine}. " + f"Supported architectures: x86_64/amd64 (Linux, Windows), aarch64/arm64 (macOS)" + ) + + if system == "darwin" and arch == "aarch64": + return "pg0-darwin-aarch64" + elif system == "linux" and arch == "x86_64": + return "pg0-linux-x86_64" + elif system == "windows" and arch == "x86_64": + return "pg0-windows-x86_64.exe" + else: + raise RuntimeError( + f"Embedded PostgreSQL is not supported on {system}-{arch}. " + f"Supported platforms: darwin-aarch64 (macOS ARM), linux-x86_64, windows-x86_64" + ) + + +def get_download_url( + version: str = "latest", + repo: str = "vectorize-io/pg0", +) -> str: + """ + """ + # Check for direct URL override + binary_name = get_platform_binary_name() + + if version == "latest": + return f"https://github.com/{repo}/releases/latest/download/{binary_name}" + else: + return f"https://github.com/{repo}/releases/download/{version}/{binary_name}" + + +class EmbeddedPostgres: + """ + Manages an embedded PostgreSQL server instance. + + This class handles: + - Downloading and installing the embedded-postgres CLI + - Starting/stopping the PostgreSQL server + - Getting the connection URI + + Example: + pg = EmbeddedPostgres(data_dir="~/.myapp/data") + await pg.ensure_installed() + await pg.start() + uri = await pg.get_uri() + # ... use uri with asyncpg ... + await pg.stop() + """ + + def __init__( + self, + data_dir: Optional[Path] = None, + install_dir: Optional[Path] = None, + version: str = "latest", + port: int = DEFAULT_PORT, + username: str = DEFAULT_USERNAME, + password: str = DEFAULT_PASSWORD, + database: str = DEFAULT_DATABASE, + ): + """ + Initialize the embedded PostgreSQL manager. + + Args: + data_dir: Directory to store PostgreSQL data. Defaults to ~/.hindsight/pg_data + install_dir: Directory to install the CLI binary. Defaults to ~/.hindsight/bin + version: Version of embedded-postgres to use. Defaults to "latest" + port: Port to listen on. Defaults to 5555 + username: Username for the database. Defaults to "hindsight" + password: Password for the database. Defaults to "hindsight" + database: Database name to create. Defaults to "hindsight" + """ + self.data_dir = Path(data_dir or DEFAULT_DATA_DIR).expanduser() + self.install_dir = Path(install_dir or DEFAULT_INSTALL_DIR).expanduser() + self.version = version + self.port = port + self.username = username + self.password = password + self.database = database + + # Binary path + binary_name = "pg0.exe" if platform.system() == "Windows" else "pg0" + self.binary_path = self.install_dir / binary_name + + self._process: Optional[subprocess.Popen] = None + + def is_installed(self) -> bool: + """Check if the embedded-postgres CLI is installed.""" + return self.binary_path.exists() and os.access(self.binary_path, os.X_OK) + + async def ensure_installed(self) -> None: + """ + Ensure the embedded-postgres CLI is installed. + + Downloads and installs the binary if not already present. + """ + if self.is_installed(): + logger.debug(f"pg0 already installed at {self.binary_path}") + return + + logger.info("Installing pg0 CLI...") + + # Create install directory + self.install_dir.mkdir(parents=True, exist_ok=True) + + # Download the binary + download_url = get_download_url(self.version) + logger.info(f"Downloading from {download_url}") + + try: + async with httpx.AsyncClient(follow_redirects=True, timeout=300.0) as client: + response = await client.get(download_url) + response.raise_for_status() + + # Write binary to disk + with open(self.binary_path, "wb") as f: + f.write(response.content) + + # Make executable on Unix + if platform.system() != "Windows": + st = os.stat(self.binary_path) + os.chmod(self.binary_path, st.st_mode | stat.S_IEXEC) + + logger.info(f"Installed pg0 to {self.binary_path}") + + except httpx.HTTPError as e: + raise RuntimeError(f"Failed to download pg0: {e}") from e + + def _run_command(self, *args: str, capture_output: bool = True) -> subprocess.CompletedProcess: + """Run an embedded-postgres command synchronously.""" + cmd = [str(self.binary_path), *args] + + return subprocess.run( + cmd, + capture_output=capture_output, + text=True, + ) + + async def _run_command_async(self, *args: str) -> tuple[int, str, str]: + """Run an embedded-postgres command asynchronously.""" + cmd = [str(self.binary_path), *args] + + process = await asyncio.create_subprocess_exec( + *cmd, + stdout=asyncio.subprocess.PIPE, + stderr=asyncio.subprocess.PIPE, + ) + + stdout, stderr = await process.communicate() + return process.returncode, stdout.decode(), stderr.decode() + + async def start(self) -> str: + """ + Start the PostgreSQL server. + + Returns: + The connection URI for the started server. + + Raises: + RuntimeError: If the server fails to start. + """ + if not self.is_installed(): + raise RuntimeError("pg0 is not installed. Call ensure_installed() first.") + + # Create data directory + self.data_dir.mkdir(parents=True, exist_ok=True) + + logger.info(f"Starting embedded PostgreSQL (data: {self.data_dir}, port: {self.port})...") + + returncode, stdout, stderr = await self._run_command_async( + "start", + "--port", str(self.port), + "--username", self.username, + "--password", self.password, + "--database", self.database, + "--data-dir", self.data_dir.as_posix() + ) + + if returncode != 0: + raise RuntimeError(f"Failed to start PostgreSQL: {stderr}") + + logger.info("Embedded PostgreSQL started") + + # Get and return the URI + return await self.get_uri() + + async def stop(self) -> None: + """ + Stop the PostgreSQL server. + + Raises: + RuntimeError: If the server fails to stop. + """ + if not self.is_installed(): + return + + logger.info("Stopping embedded PostgreSQL...") + + returncode, stdout, stderr = await self._run_command_async("stop") + + if returncode != 0: + # Don't raise if server wasn't running + if "not running" in stderr.lower(): + logger.debug("PostgreSQL was not running") + return + raise RuntimeError(f"Failed to stop PostgreSQL: {stderr}") + + logger.info("Embedded PostgreSQL stopped") + + async def _get_info(self) -> dict: + """ + Get info from pg0 using the `info -o json` command. + + Returns: + Dictionary with 'running' (bool) and 'uri' (str) keys. + + Raises: + RuntimeError: If unable to get info. + """ + if not self.is_installed(): + raise RuntimeError("pg0 is not installed.") + + returncode, stdout, stderr = await self._run_command_async( + "info", "-o", "json") + + if returncode != 0: + raise RuntimeError(f"Failed to get PostgreSQL info: {stderr}") + + try: + return json.loads(stdout.strip()) + except json.JSONDecodeError as e: + raise RuntimeError(f"Failed to parse pg0 info output: {e}") + + async def get_uri(self) -> str: + """ + Get the connection URI for the PostgreSQL server. + + Returns: + PostgreSQL connection URI (e.g., postgresql://user:pass@localhost:5432/db) + + Raises: + RuntimeError: If unable to get the URI or server is not running. + """ + info = await self._get_info() + uri = info.get("uri") + if not uri: + raise RuntimeError("PostgreSQL server is not running or URI not available") + return uri + + async def status(self) -> dict: + """ + Get the status of the PostgreSQL server. + + Returns: + Dictionary with status information including 'running' boolean and 'uri'. + """ + if not self.is_installed(): + return {"installed": False, "running": False} + + try: + info = await self._get_info() + return { + "installed": True, + "running": info.get("running", False), + "uri": info.get("uri"), + "data_dir": str(self.data_dir), + "binary_path": str(self.binary_path), + } + except RuntimeError: + return { + "installed": True, + "running": False, + "data_dir": str(self.data_dir), + "binary_path": str(self.binary_path), + } + + async def is_running(self) -> bool: + """Check if the PostgreSQL server is currently running.""" + if not self.is_installed(): + return False + try: + info = await self._get_info() + return info.get("running", False) + except RuntimeError: + return False + + async def ensure_running(self) -> str: + """ + Ensure the PostgreSQL server is running. + + Installs if needed, starts if not running. + + Returns: + The connection URI. + """ + await self.ensure_installed() + + if await self.is_running(): + return await self.get_uri() + + return await self.start() + + def uninstall(self) -> None: + """Remove the embedded-postgres binary.""" + if self.binary_path.exists(): + self.binary_path.unlink() + logger.info(f"Removed {self.binary_path}") + + def clear_data(self) -> None: + """Remove all PostgreSQL data (destructive!).""" + if self.data_dir.exists(): + shutil.rmtree(self.data_dir) + logger.info(f"Removed data directory {self.data_dir}") + + +# Convenience functions for simple usage + +_default_instance: Optional[EmbeddedPostgres] = None + + +def get_embedded_postgres( + data_dir: Optional[Path] = None, + install_dir: Optional[Path] = None, +) -> EmbeddedPostgres: + """ + Get or create the default EmbeddedPostgres instance. + + Args: + data_dir: Override default data directory + install_dir: Override default install directory + + Returns: + EmbeddedPostgres instance + """ + global _default_instance + + if _default_instance is None or data_dir or install_dir: + _default_instance = EmbeddedPostgres( + data_dir=data_dir, + install_dir=install_dir, + ) + + return _default_instance + + +async def start_embedded_postgres( + data_dir: Optional[Path] = None, +) -> str: + """ + Quick start function for embedded PostgreSQL. + + Downloads, installs, and starts PostgreSQL in one call. + + Args: + data_dir: Directory to store PostgreSQL data + + Returns: + Connection URI string + + Example: + db_url = await start_embedded_postgres() + conn = await asyncpg.connect(db_url) + """ + pg = get_embedded_postgres(data_dir=data_dir) + return await pg.ensure_running() + + +async def stop_embedded_postgres() -> None: + """Stop the default embedded PostgreSQL instance.""" + global _default_instance + + if _default_instance: + await _default_instance.stop() \ No newline at end of file diff --git a/memora/memora/web/__init__.py b/hindsight-api/hindsight_api/web/__init__.py similarity index 51% rename from memora/memora/web/__init__.py rename to hindsight-api/hindsight_api/web/__init__.py index fd2f26cdad..a5ff6a4f7a 100644 --- a/memora/memora/web/__init__.py +++ b/hindsight-api/hindsight_api/web/__init__.py @@ -3,10 +3,10 @@ Provides FastAPI app and visualization interface. """ -from memora.api import create_app +from hindsight_api.api import create_app # Note: Don't import app from .server here to avoid circular import warnings -# when running with `python -m memora.web.server` -# If you need the app, import it directly: from memora.web.server import app +# when running with `python -m hindsight_api.web.server` +# If you need the app, import it directly: from hindsight_api.web.server import app __all__ = ["create_app"] diff --git a/memora/memora/web/server.py b/hindsight-api/hindsight_api/web/server.py similarity index 58% rename from memora/memora/web/server.py rename to hindsight-api/hindsight_api/web/server.py index 4d89883dd8..064e9dd6d1 100644 --- a/memora/memora/web/server.py +++ b/hindsight-api/hindsight_api/web/server.py @@ -4,27 +4,68 @@ Provides REST API endpoints for memory operations and serves the interactive visualization interface. """ +import warnings + +# Filter deprecation warnings from third-party libraries +warnings.filterwarnings("ignore", message="websockets.legacy is deprecated") +warnings.filterwarnings("ignore", message="websockets.server.WebSocketServerProtocol is deprecated") + +import asyncio +import atexit import logging import os import argparse +import signal +import sys -from memora import TemporalSemanticMemory -from memora.api import create_app +from hindsight_api import MemoryEngine +from hindsight_api.api import create_app # Disable tokenizers parallelism to avoid warnings os.environ["TOKENIZERS_PARALLELISM"] = "false" + +def _cleanup_pg0(): + """Synchronous cleanup function to stop pg0 on exit.""" + global _memory + if _memory is not None and _memory._pg0 is not None: + try: + # Run async stop in a new event loop + loop = asyncio.new_event_loop() + loop.run_until_complete(_memory._pg0.stop()) + loop.close() + print("\npg0 stopped.") + except Exception as e: + print(f"\nError stopping pg0: {e}") + + +# Register cleanup on normal exit +atexit.register(_cleanup_pg0) + + +def _signal_handler(signum, frame): + """Handle SIGINT/SIGTERM to ensure pg0 cleanup.""" + print(f"\nReceived signal {signum}, shutting down...") + _cleanup_pg0() + sys.exit(0) + + +# Register signal handlers for graceful shutdown +signal.signal(signal.SIGINT, _signal_handler) +signal.signal(signal.SIGTERM, _signal_handler) + + # Create app at module level (required for uvicorn import string) -_memory = TemporalSemanticMemory( - db_url=os.getenv("MEMORA_API_DATABASE_URL"), - memory_llm_provider=os.getenv("MEMORA_API_LLM_PROVIDER", "groq"), - memory_llm_api_key=os.getenv("MEMORA_API_LLM_API_KEY"), - memory_llm_model=os.getenv("MEMORA_API_LLM_MODEL", "openai/gpt-oss-120b"), - memory_llm_base_url=os.getenv("MEMORA_API_LLM_BASE_URL") or None, +_memory = MemoryEngine( + db_url=os.getenv("HINDSIGHT_API_DATABASE_URL", "pg0"), + memory_llm_provider=os.getenv("HINDSIGHT_API_LLM_PROVIDER", "groq"), + memory_llm_api_key=os.getenv("HINDSIGHT_API_LLM_API_KEY"), + memory_llm_model=os.getenv("HINDSIGHT_API_LLM_MODEL", "openai/gpt-oss-120b"), + memory_llm_base_url=os.getenv("HINDSIGHT_API_LLM_BASE_URL") or None, ) # Check if MCP should be enabled -mcp_enabled = os.getenv("MEMORA_API_MCP_ENABLED", "true").lower() == "true" +mcp_enabled = os.getenv("HINDSIGHT_API_MCP_ENABLED", "true").lower() == "true" # Create unified app with both HTTP and optionally MCP app = create_app( @@ -43,7 +84,7 @@ # Parse CLI arguments parser = argparse.ArgumentParser(description="Memory Graph API Server") parser.add_argument("--host", default="0.0.0.0", help="Host to bind to (default: 0.0.0.0)") - parser.add_argument("--port", type=int, default=8080, help="Port to bind to (default: 8080)") + parser.add_argument("--port", type=int, default=8888, help="Port to bind to (default: 8888)") parser.add_argument("--reload", action="store_true", help="Enable auto-reload on code changes") parser.add_argument("--workers", type=int, default=1, help="Number of worker processes (default: 1)") parser.add_argument("--log-level", default="info", choices=["critical", "error", "warning", "info", "debug", "trace"], @@ -58,7 +99,7 @@ args = parser.parse_args() - app_ref = "memora.web.server:app" + app_ref = "hindsight_api.web.server:app" # Prepare uvicorn config uvicorn_config = { diff --git a/memora/pyproject.toml b/hindsight-api/pyproject.toml similarity index 75% rename from memora/pyproject.toml rename to hindsight-api/pyproject.toml index 2f8a3866d3..d4bec4f932 100644 --- a/memora/pyproject.toml +++ b/hindsight-api/pyproject.toml @@ -3,7 +3,7 @@ requires = ["hatchling"] build-backend = "hatchling.build" [project] -name = "memora" +name = "hindsight-api" version = "0.0.7" description = "Temporal + Semantic + Entity Memory System for AI agents using PostgreSQL" readme = "README.md" @@ -36,15 +36,24 @@ test = [ "pytest>=7.0.0", "pytest-asyncio>=0.21.0", "pytest-timeout>=2.4.0", + "pytest-xdist>=3.0.0", + "filelock>=3.0.0", + "testcontainers[postgres]>=4.0.0", ] [tool.hatch.build.targets.wheel] -packages = ["memora"] +packages = ["hindsight_api"] [tool.pytest.ini_options] log_cli = true log_cli_level = "INFO" log_cli_format = "%(asctime)s %(levelname)s %(message)s" log_cli_date_format = "%Y-%m-%d %H:%M:%S" -addopts = "--timeout 60 -p no:warnings" +addopts = "--timeout 60 -n auto --durations=10 -v" +asyncio_mode = "auto" asyncio_default_fixture_loop_scope = "function" +log_auto_indent = true +filterwarnings = [ + "ignore:The @wait_container_is_ready decorator is deprecated:DeprecationWarning", + "ignore::RuntimeWarning:asyncio", +] diff --git a/memora/tests/__init__.py b/hindsight-api/tests/__init__.py similarity index 100% rename from memora/tests/__init__.py rename to hindsight-api/tests/__init__.py diff --git a/hindsight-api/tests/conftest.py b/hindsight-api/tests/conftest.py new file mode 100644 index 0000000000..c75dda15a2 --- /dev/null +++ b/hindsight-api/tests/conftest.py @@ -0,0 +1,130 @@ +""" +Pytest configuration and shared fixtures. +""" +import pytest +import pytest_asyncio +import os +import filelock +from pathlib import Path +from dotenv import load_dotenv +from hindsight_api import MemoryEngine, LLMConfig, SentenceTransformersEmbeddings +import asyncpg +from testcontainers.postgres import PostgresContainer + +from hindsight_api.engine.cross_encoder import SentenceTransformersCrossEncoder +from hindsight_api.engine.query_analyzer import TransformerQueryAnalyzer + + +# Load environment variables from .env at the start of test session +def pytest_configure(config): + """Load environment variables before running tests.""" + # Look for .env in the workspace root (two levels up from tests dir) + env_file = Path(__file__).parent.parent.parent / ".env" + if env_file.exists(): + load_dotenv(env_file) + else: + print(f"Warning: {env_file} not found, tests may fail without proper configuration") + + +@pytest.fixture(scope="session") +def postgres_container(tmp_path_factory, worker_id): + """ + Start a postgres container shared across all test workers. + Uses filelock to ensure only one worker starts the container. + + - worker_id == "master": running without -n (single process) + - worker_id == "gw0", "gw1", etc.: running with -n (parallel workers) + """ + # Get shared temp dir (same for all workers) + if worker_id == "master": + root_tmp_dir = tmp_path_factory.getbasetemp() + else: + root_tmp_dir = tmp_path_factory.getbasetemp().parent + + db_url_file = root_tmp_dir / "postgres_url" + lock_file = root_tmp_dir / "postgres.lock" + container = None + + with filelock.FileLock(str(lock_file)): + if db_url_file.exists(): + # Another worker already started the container + db_url = db_url_file.read_text() + else: + # First worker - start the container + container = PostgresContainer("pgvector/pgvector:pg16") + container.start() + db_url = container.get_connection_url().replace("postgresql+psycopg2://", "postgresql://") + db_url_file.write_text(db_url) + + # Run migrations + from hindsight_api.migrations import run_migrations + run_migrations(db_url) + + os.environ["HINDSIGHT_API_DATABASE_URL"] = db_url + yield db_url + + # Only the worker that started the container stops it + if container is not None: + container.stop() + + +@pytest.fixture(scope="session") +def llm_config(): + """ + Provide LLM configuration for tests. + This can be used by tests that need to call LLM directly without memory system. + """ + return LLMConfig.for_memory() + + +@pytest.fixture(scope="session") +def embeddings(): + + return SentenceTransformersEmbeddings("BAAI/bge-small-en-v1.5") + + + +@pytest.fixture(scope="session") +def cross_encoder(): + + return SentenceTransformersCrossEncoder() + +@pytest.fixture(scope="session") +def query_analyzer(): + return TransformerQueryAnalyzer() + + + + +@pytest_asyncio.fixture(scope="function") +async def memory(postgres_container, embeddings, cross_encoder, query_analyzer): + """ + Provide a MemoryEngine instance for each test. + + Must be function-scoped because: + 1. pytest-xdist runs tests in separate processes with different event loops + 2. asyncpg pools are bound to the event loop that created them + 3. Each test needs its own pool in its own event loop + + Uses small pool sizes since tests run in parallel and share a single + testcontainer PostgreSQL instance with limited resources. + """ + mem = MemoryEngine( + db_url=postgres_container, + memory_llm_provider=os.getenv("HINDSIGHT_API_LLM_PROVIDER", "groq"), + memory_llm_api_key=os.getenv("HINDSIGHT_API_LLM_API_KEY"), + memory_llm_model=os.getenv("HINDSIGHT_API_LLM_MODEL", "openai/gpt-oss-120b"), + memory_llm_base_url=os.getenv("HINDSIGHT_API_LLM_BASE_URL") or None, + embeddings=embeddings, + cross_encoder=cross_encoder, + query_analyzer=query_analyzer, + pool_min_size=1, + pool_max_size=5, + ) + await mem.initialize() + yield mem + try: + if mem._pool and not mem._pool._closing: + await mem.close() + except Exception: + pass \ No newline at end of file diff --git a/memora/tests/fixtures/README.md b/hindsight-api/tests/fixtures/README.md similarity index 100% rename from memora/tests/fixtures/README.md rename to hindsight-api/tests/fixtures/README.md diff --git a/memora/tests/fixtures/locomo_conversation_sample.json b/hindsight-api/tests/fixtures/locomo_conversation_sample.json similarity index 100% rename from memora/tests/fixtures/locomo_conversation_sample.json rename to hindsight-api/tests/fixtures/locomo_conversation_sample.json diff --git a/hindsight-api/tests/test_agents_api.py b/hindsight-api/tests/test_agents_api.py new file mode 100644 index 0000000000..85a5cf7314 --- /dev/null +++ b/hindsight-api/tests/test_agents_api.py @@ -0,0 +1,254 @@ +""" +Tests for agent management API (profile, personality, background). +""" +import pytest +import uuid +from hindsight_api import MemoryEngine +from hindsight_api.api import CreateAgentRequest, PersonalityTraits + + +def unique_agent_id(prefix: str) -> str: + """Generate a unique agent ID for testing.""" + return f"{prefix}_{uuid.uuid4().hex[:8]}" + + +class TestAgentProfile: + """Tests for agent profile management.""" + + @pytest.mark.asyncio + async def test_get_agent_profile_creates_default(self, memory: MemoryEngine): + """Test that getting a profile for a new agent creates default personality.""" + agent_id = unique_agent_id("test_profile_default") + + profile = await memory.get_agent_profile(agent_id) + + assert profile is not None + assert "personality" in profile + assert "background" in profile + + personality = profile["personality"] + assert personality["openness"] == 0.5 + assert personality["conscientiousness"] == 0.5 + assert personality["extraversion"] == 0.5 + assert personality["agreeableness"] == 0.5 + assert personality["neuroticism"] == 0.5 + assert personality["bias_strength"] == 0.5 + + assert profile["background"] == "" + + @pytest.mark.asyncio + async def test_update_agent_personality(self, memory: MemoryEngine): + """Test updating agent personality traits.""" + agent_id = unique_agent_id("test_profile_update") + + profile = await memory.get_agent_profile(agent_id) + assert profile["personality"]["openness"] == 0.5 + + new_personality = { + "openness": 0.8, + "conscientiousness": 0.6, + "extraversion": 0.7, + "agreeableness": 0.4, + "neuroticism": 0.3, + "bias_strength": 0.9, + } + await memory.update_agent_personality(agent_id, new_personality) + + updated_profile = await memory.get_agent_profile(agent_id) + for key in new_personality: + assert abs(updated_profile["personality"][key] - new_personality[key]) < 0.001 + + @pytest.mark.asyncio + async def test_list_agents(self, memory: MemoryEngine): + """Test listing all agents.""" + agent_id_1 = unique_agent_id("test_list") + agent_id_2 = unique_agent_id("test_list") + agent_id_3 = unique_agent_id("test_list") + + await memory.get_agent_profile(agent_id_1) + await memory.get_agent_profile(agent_id_2) + await memory.get_agent_profile(agent_id_3) + + agents = await memory.list_agents() + + agent_ids = [a["agent_id"] for a in agents] + assert agent_id_1 in agent_ids + assert agent_id_2 in agent_ids + assert agent_id_3 in agent_ids + + for agent in agents: + assert "agent_id" in agent + assert "personality" in agent + assert "background" in agent + assert "created_at" in agent + assert "updated_at" in agent + + +class TestAgentBackground: + """Tests for agent background management.""" + + @pytest.mark.asyncio + async def test_merge_agent_background(self, memory: MemoryEngine): + """Test merging agent background information.""" + agent_id = unique_agent_id("test_profile_merge") + + profile = await memory.get_agent_profile(agent_id) + assert profile["background"] == "" + + result1 = await memory.merge_agent_background( + agent_id, + "I was born in Texas", + update_personality=False + ) + assert "Texas" in result1["background"] + + result2 = await memory.merge_agent_background( + agent_id, + "I have 10 years of startup experience", + update_personality=False + ) + assert "Texas" in result2["background"] or "startup" in result2["background"] + + final_profile = await memory.get_agent_profile(agent_id) + assert final_profile["background"] != "" + + @pytest.mark.asyncio + async def test_merge_background_handles_conflicts(self, memory: MemoryEngine): + """Test that merging background handles conflicts (new overwrites old).""" + agent_id = unique_agent_id("test_profile_conflict") + + result1 = await memory.merge_agent_background( + agent_id, + "I was born in Colorado", + update_personality=False + ) + assert "Colorado" in result1["background"] + + result2 = await memory.merge_agent_background( + agent_id, + "You were born in Texas", + update_personality=False + ) + assert "Texas" in result2["background"] + + +class TestAgentEndpoint: + """Tests for agent PUT endpoint logic.""" + + @pytest.mark.asyncio + async def test_put_agent_create(self, memory: MemoryEngine): + """Test creating an agent via PUT endpoint.""" + agent_id = unique_agent_id("test_put_create") + + request = CreateAgentRequest( + personality=PersonalityTraits( + openness=0.8, + conscientiousness=0.6, + extraversion=0.5, + agreeableness=0.7, + neuroticism=0.3, + bias_strength=0.7 + ), + background="I am a creative software engineer" + ) + + profile = await memory.get_agent_profile(agent_id) + + if request.personality is not None: + await memory.update_agent_personality( + agent_id, + request.personality.model_dump() + ) + + if request.background is not None: + pool = await memory._get_pool() + async with pool.acquire() as conn: + await conn.execute( + """ + UPDATE agents + SET background = $2, + updated_at = NOW() + WHERE agent_id = $1 + """, + agent_id, + request.background + ) + + final_profile = await memory.get_agent_profile(agent_id) + + assert final_profile["personality"]["openness"] == 0.8 + assert final_profile["personality"]["bias_strength"] == 0.7 + assert final_profile["background"] == "I am a creative software engineer" + + @pytest.mark.asyncio + async def test_put_agent_partial_update(self, memory: MemoryEngine): + """Test updating only background.""" + agent_id = unique_agent_id("test_put_partial") + + request = CreateAgentRequest( + background="I am a data scientist" + ) + + profile = await memory.get_agent_profile(agent_id) + + if request.background is not None: + pool = await memory._get_pool() + async with pool.acquire() as conn: + await conn.execute( + """ + UPDATE agents + SET background = $2, + updated_at = NOW() + WHERE agent_id = $1 + """, + agent_id, + request.background + ) + + final_profile = await memory.get_agent_profile(agent_id) + + assert final_profile["personality"]["openness"] == 0.5 + assert final_profile["background"] == "I am a data scientist" + + +class TestAgentPersonalityIntegration: + """Tests for personality integration with other features.""" + + @pytest.mark.asyncio + async def test_think_uses_personality(self, memory: MemoryEngine): + """Test that THINK operation uses agent personality.""" + agent_id = unique_agent_id("test_think") + + personality = { + "openness": 0.9, + "conscientiousness": 0.2, + "extraversion": 0.8, + "agreeableness": 0.1, + "neuroticism": 0.7, + "bias_strength": 0.9, + } + await memory.update_agent_personality(agent_id, personality) + + await memory.merge_agent_background( + agent_id, + "I am a creative artist who values innovation over tradition", + update_personality=False + ) + + await memory.put_batch_async( + agent_id=agent_id, + contents=[ + {"content": "Traditional painting techniques have been used for centuries"}, + {"content": "Modern digital art is changing the art world"} + ], + document_id="art_facts" + ) + + result = await memory.think_async( + agent_id=agent_id, + query="What do you think about traditional vs modern art?", + thinking_budget=50 + ) + + assert result.text is not None + assert len(result.text) > 0 diff --git a/hindsight-api/tests/test_batch_chunking.py b/hindsight-api/tests/test_batch_chunking.py new file mode 100644 index 0000000000..c9e297eec9 --- /dev/null +++ b/hindsight-api/tests/test_batch_chunking.py @@ -0,0 +1,58 @@ +"""Test automatic batch chunking based on character count.""" +import asyncio +import pytest +from hindsight_api import MemoryEngine +import os + + +@pytest.mark.asyncio +async def test_large_batch_auto_chunks(memory): + agent_id = "test_chunking_agent" + # Create a large batch that should trigger chunking + # Each item is ~2000 chars, so 30 items = 60k chars (exceeds 50k threshold) + large_content = "Alice met with Bob at the coffee shop. " * 50 # ~2000 chars + contents = [ + {"content": large_content, "context": f"conversation_{i}"} + for i in range(30) + ] + + # Calculate total chars + total_chars = sum(len(item["content"]) for item in contents) + print(f"\nTotal characters: {total_chars:,}") + print(f"Should trigger chunking: {total_chars > 50_000}") + + # Ingest the large batch (should auto-chunk) + result = await memory.put_batch_async( + agent_id=agent_id, + contents=contents + ) + + # Verify we got results back + assert len(result) == 30, f"Expected 30 results, got {len(result)}" + print(f"Successfully ingested {len(result)} items (auto-chunked)") + + +@pytest.mark.asyncio +async def test_small_batch_no_chunking(memory): + agent_id = "test_no_chunking_agent" + + # Create a small batch that should NOT trigger chunking + contents = [ + {"content": "Alice works at Google", "context": "conversation_1"}, + {"content": "Bob loves Python", "context": "conversation_2"} + ] + + # Calculate total chars + total_chars = sum(len(item["content"]) for item in contents) + print(f"\nTotal characters: {total_chars:,}") + print(f"Should NOT trigger chunking: {total_chars <= 50_000}") + + # Ingest the small batch (should NOT auto-chunk) + result = await memory.put_batch_async( + agent_id=agent_id, + contents=contents + ) + + # Verify we got results back + assert len(result) == 2, f"Expected 2 results, got {len(result)}" + print(f"Successfully ingested {len(result)} items (no chunking)") diff --git a/memora/tests/test_chunking.py b/hindsight-api/tests/test_chunking.py similarity index 94% rename from memora/tests/test_chunking.py rename to hindsight-api/tests/test_chunking.py index 12aeeb8f73..6f117a8799 100644 --- a/memora/tests/test_chunking.py +++ b/hindsight-api/tests/test_chunking.py @@ -2,7 +2,7 @@ Test chunking functionality for large documents. """ import pytest -from memora.fact_extraction import chunk_text +from hindsight_api.engine.fact_extraction import chunk_text def test_chunk_text_small(): @@ -58,6 +58,3 @@ def test_chunk_text_64k(): combined_length = sum(len(chunk) for chunk in chunks) assert combined_length >= len(text) * 0.95, "Lost too much content during chunking" - -if __name__ == "__main__": - pytest.main([__file__, "-v"]) diff --git a/memora/tests/test_document_tracking.py b/hindsight-api/tests/test_document_tracking.py similarity index 100% rename from memora/tests/test_document_tracking.py rename to hindsight-api/tests/test_document_tracking.py diff --git a/hindsight-api/tests/test_fact_extraction_quality.py b/hindsight-api/tests/test_fact_extraction_quality.py new file mode 100644 index 0000000000..66c65290c1 --- /dev/null +++ b/hindsight-api/tests/test_fact_extraction_quality.py @@ -0,0 +1,1168 @@ +""" +Test suite for fact extraction quality verification. + +This comprehensive test suite validates that the fact extraction system: +1. Preserves all information dimensions (emotional, sensory, cognitive, etc.) +2. Correctly converts relative dates to absolute dates +3. Properly classifies facts as agent vs world +4. Makes logical inferences to connect related information +5. Correctly attributes statements to speakers +6. Filters out irrelevant content (podcast intros/outros) + +These are quality/accuracy tests that verify the LLM-based extraction +produces semantically correct and complete facts. +""" +import pytest +import re +from datetime import datetime, timezone +from hindsight_api.engine.fact_extraction import extract_facts_from_text +from hindsight_api import LLMConfig + + +# ============================================================================= +# DIMENSION PRESERVATION TESTS +# ============================================================================= + +class TestDimensionPreservation: + """Tests that fact extraction preserves all information dimensions.""" + + @pytest.mark.asyncio + async def test_emotional_dimension_preservation(self): + """ + Test that emotional states and feelings are preserved, not stripped away. + + Example: "I was thrilled to receive positive feedback" + Should NOT become: "I received positive feedback" + """ + text = """ +I was absolutely thrilled when I received such positive feedback on my presentation! +Sarah seemed disappointed when she heard the news about the delay. +Marcus felt anxious about the upcoming interview. +""" + + context = "Personal journal entry" + llm_config = LLMConfig.for_memory() + + facts = await extract_facts_from_text( + text=text, + event_date=datetime(2024, 11, 13), + context=context, + llm_config=llm_config, + agent_name="TestUser" + ) + + assert len(facts) > 0, "Should extract at least one fact" + + print(f"\nExtracted {len(facts)} facts:") + for i, f in enumerate(facts): + print(f"{i+1}. {f['fact']}") + + all_facts_text = " ".join([f['fact'].lower() for f in facts]) + + emotional_indicators = ["thrilled", "disappointed", "anxious", "positive feedback"] + found_emotions = [word for word in emotional_indicators if word in all_facts_text] + + assert len(found_emotions) >= 2, ( + f"Should preserve emotional dimension. " + f"Found: {found_emotions}, Expected at least 2 from: {emotional_indicators}" + ) + + @pytest.mark.asyncio + async def test_sensory_dimension_preservation(self): + """Test that sensory details (visual, auditory, etc.) are preserved.""" + text = """ +The coffee tasted bitter and burnt. +She showed me her bright orange hair, which looked stunning under the lights. +The music was so loud I could barely hear myself think. +""" + + context = "Personal experience" + llm_config = LLMConfig.for_memory() + + facts = await extract_facts_from_text( + text=text, + event_date=datetime(2024, 11, 13), + context=context, + llm_config=llm_config, + agent_name="TestUser" + ) + + assert len(facts) > 0, "Should extract at least one fact" + + print(f"\nExtracted {len(facts)} facts:") + for i, f in enumerate(facts): + print(f"{i+1}. {f['fact']}") + + all_facts_text = " ".join([f['fact'].lower() for f in facts]) + + sensory_indicators = ["bitter", "burnt", "bright orange", "loud", "stunning"] + found_sensory = [word for word in sensory_indicators if word in all_facts_text] + + assert len(found_sensory) >= 2, ( + f"Should preserve sensory details. " + f"Found: {found_sensory}, Expected at least 2 from: {sensory_indicators}" + ) + + @pytest.mark.asyncio + async def test_cognitive_epistemic_dimension(self): + """Test that cognitive states and certainty levels are preserved.""" + text = """ +I realized that the approach wasn't working. +She wasn't sure if the meeting would happen. +He's convinced that AI will transform healthcare. +Maybe we should reconsider the timeline. +""" + + context = "Team discussion" + llm_config = LLMConfig.for_memory() + + facts = await extract_facts_from_text( + text=text, + event_date=datetime(2024, 11, 13), + context=context, + llm_config=llm_config, + agent_name="TestUser" + ) + + assert len(facts) > 0, "Should extract at least one fact" + + print(f"\nExtracted {len(facts)} facts:") + for i, f in enumerate(facts): + print(f"{i+1}. {f['fact']}") + + all_facts_text = " ".join([f['fact'].lower() for f in facts]) + + cognitive_indicators = ["realized", "wasn't sure", "convinced", "maybe", "reconsider"] + found_cognitive = [word for word in cognitive_indicators if word in all_facts_text] + + assert len(found_cognitive) >= 2, ( + f"Should preserve cognitive/epistemic dimension. " + f"Found: {found_cognitive}" + ) + + @pytest.mark.asyncio + async def test_capability_skill_dimension(self): + """Test that capabilities, skills, and limitations are preserved.""" + text = """ +I can speak French fluently. +Sarah struggles with public speaking. +He's an expert in machine learning. +I'm unable to attend the conference due to scheduling conflicts. +""" + + context = "Personal profile discussion" + llm_config = LLMConfig.for_memory() + + facts = await extract_facts_from_text( + text=text, + event_date=datetime(2024, 11, 13), + context=context, + llm_config=llm_config, + agent_name="TestUser" + ) + + assert len(facts) > 0, "Should extract at least one fact" + + print(f"\nExtracted {len(facts)} facts:") + for i, f in enumerate(facts): + print(f"{i+1}. {f['fact']}") + + all_facts_text = " ".join([f['fact'].lower() for f in facts]) + + capability_indicators = ["can speak", "fluently", "struggles with", "expert in", "unable to"] + found_capability = [word for word in capability_indicators if word in all_facts_text] + + assert len(found_capability) >= 2, ( + f"Should preserve capability/skill dimension. " + f"Found: {found_capability}" + ) + + @pytest.mark.asyncio + async def test_comparative_dimension(self): + """Test that comparisons and contrasts are preserved.""" + text = """ +This approach is much better than the previous one. +The new design is worse than expected. +Unlike last year, we're ahead of schedule. +""" + + context = "Project review" + llm_config = LLMConfig.for_memory() + + facts = await extract_facts_from_text( + text=text, + event_date=datetime(2024, 11, 13), + context=context, + llm_config=llm_config, + agent_name="TestUser" + ) + + assert len(facts) > 0, "Should extract at least one fact" + + print(f"\nExtracted {len(facts)} facts:") + for i, f in enumerate(facts): + print(f"{i+1}. {f['fact']}") + + all_facts_text = " ".join([f['fact'].lower() for f in facts]) + + comparative_indicators = ["better than", "worse than", "unlike", "ahead of"] + found_comparative = [word for word in comparative_indicators if word in all_facts_text] + + assert len(found_comparative) >= 1, ( + f"Should preserve comparative dimension. " + f"Found: {found_comparative}" + ) + + @pytest.mark.asyncio + async def test_attitudinal_reactive_dimension(self): + """Test that attitudes and reactions are preserved.""" + text = """ +She's very skeptical about the new technology. +I was surprised when he announced his resignation. +Marcus rolled his eyes when the topic came up. +She's enthusiastic about the opportunity. +""" + + context = "Team meeting" + llm_config = LLMConfig.for_memory() + + facts = await extract_facts_from_text( + text=text, + event_date=datetime(2024, 11, 13), + context=context, + llm_config=llm_config, + agent_name="TestUser" + ) + + assert len(facts) > 0, "Should extract at least one fact" + + print(f"\nExtracted {len(facts)} facts:") + for i, f in enumerate(facts): + print(f"{i+1}. {f['fact']}") + + all_facts_text = " ".join([f['fact'].lower() for f in facts]) + + attitudinal_indicators = ["skeptical", "surprised", "rolled his eyes", "enthusiastic"] + found_attitudinal = [word for word in attitudinal_indicators if word in all_facts_text] + + assert len(found_attitudinal) >= 2, ( + f"Should preserve attitudinal/reactive dimension. " + f"Found: {found_attitudinal}" + ) + + @pytest.mark.asyncio + async def test_intentional_motivational_dimension(self): + """Test that goals, plans, and motivations are preserved.""" + text = """ +I want to learn Mandarin before my trip to China. +She aims to complete her PhD within three years. +His goal is to build a sustainable business. +I'm planning to switch careers because I'm not fulfilled in my current role. +""" + + context = "Personal goals discussion" + llm_config = LLMConfig.for_memory() + + facts = await extract_facts_from_text( + text=text, + event_date=datetime(2024, 11, 13), + context=context, + llm_config=llm_config, + agent_name="TestUser" + ) + + assert len(facts) > 0, "Should extract at least one fact" + + print(f"\nExtracted {len(facts)} facts:") + for i, f in enumerate(facts): + print(f"{i+1}. {f['fact']}") + + all_facts_text = " ".join([f['fact'].lower() for f in facts]) + + intentional_indicators = ["want to", "aims to", "goal is", "planning to", "because"] + found_intentional = [word for word in intentional_indicators if word in all_facts_text] + + assert len(found_intentional) >= 2, ( + f"Should preserve intentional/motivational dimension. " + f"Found: {found_intentional}" + ) + + @pytest.mark.asyncio + async def test_evaluative_preferential_dimension(self): + """Test that preferences and values are preserved.""" + text = """ +I prefer working remotely to being in an office. +She values honesty above all else. +He hates being late to meetings. +Family is the most important thing to her. +""" + + context = "Personal values discussion" + llm_config = LLMConfig.for_memory() + + facts = await extract_facts_from_text( + text=text, + event_date=datetime(2024, 11, 13), + context=context, + llm_config=llm_config, + agent_name="TestUser" + ) + + assert len(facts) > 0, "Should extract at least one fact" + + print(f"\nExtracted {len(facts)} facts:") + for i, f in enumerate(facts): + print(f"{i+1}. {f['fact']}") + + all_facts_text = " ".join([f['fact'].lower() for f in facts]) + + evaluative_indicators = ["prefer", "values", "hates", "important", "above all"] + found_evaluative = [word for word in evaluative_indicators if word in all_facts_text] + + assert len(found_evaluative) >= 2, ( + f"Should preserve evaluative/preferential dimension. " + f"Found: {found_evaluative}" + ) + + @pytest.mark.asyncio + async def test_comprehensive_multi_dimension(self): + """Test a realistic scenario with multiple dimensions in one fact.""" + text = """ +I was thrilled to receive such positive feedback on my presentation yesterday! +I wasn't sure if my approach would resonate, but the audience seemed enthusiastic. +I prefer presenting in person rather than virtually because I can read the room better. +""" + + context = "Personal reflection" + llm_config = LLMConfig.for_memory() + + event_date = datetime(2024, 11, 13) + + facts = await extract_facts_from_text( + text=text, + event_date=event_date, + context=context, + llm_config=llm_config, + agent_name="TestUser" + ) + + assert len(facts) > 0, "Should extract at least one fact" + + print(f"\nExtracted {len(facts)} facts:") + for i, f in enumerate(facts): + print(f"{i+1}. {f['fact']}") + + all_facts_text = " ".join([f['fact'].lower() for f in facts]) + + # Check emotional + assert "thrilled" in all_facts_text or "positive feedback" in all_facts_text, \ + "Should preserve emotional dimension (thrilled)" + + # Check no vague temporal terms + prohibited_terms = ["recently", "soon", "lately"] + found_prohibited = [term for term in prohibited_terms if term in all_facts_text] + assert len(found_prohibited) == 0, \ + f"Should NOT use vague temporal terms. Found: {found_prohibited}" + + # Check cognitive uncertainty + assert "wasn't sure" in all_facts_text or "unsure" in all_facts_text or "uncertain" in all_facts_text, \ + "Should preserve cognitive uncertainty" + + # Check preference + assert "prefer" in all_facts_text or "rather than" in all_facts_text, \ + "Should preserve preferential dimension" + + +# ============================================================================= +# TEMPORAL CONVERSION TESTS +# ============================================================================= + +class TestTemporalConversion: + """Tests for temporal extraction and date conversion.""" + + @pytest.mark.asyncio + async def test_temporal_absolute_conversion(self): + """ + Test that relative temporal expressions are converted to absolute dates. + + Critical: "yesterday" should become "on November 12, 2024", NOT "recently" + """ + text = """ +Yesterday I went for a morning jog for the first time in a nearby park. +Last week I started a new project. +I'm planning to visit Tokyo next month. +""" + + context = "Personal conversation" + llm_config = LLMConfig.for_memory() + + event_date = datetime(2024, 11, 13) + + facts = await extract_facts_from_text( + text=text, + event_date=event_date, + context=context, + llm_config=llm_config, + agent_name="TestUser" + ) + + assert len(facts) > 0, "Should extract at least one fact" + + print(f"\nExtracted {len(facts)} facts:") + for i, f in enumerate(facts): + print(f"{i+1}. {f['fact']}") + + all_facts_text = " ".join([f['fact'].lower() for f in facts]) + + # Should NOT contain vague temporal terms + prohibited_terms = ["recently", "soon", "lately", "a while ago", "some time ago"] + found_prohibited = [term for term in prohibited_terms if term in all_facts_text] + + assert len(found_prohibited) == 0, ( + f"Should NOT use vague temporal terms. Found: {found_prohibited}" + ) + + # Should contain specific date references + temporal_indicators = ["november", "12", "early november", "week of", "december"] + found_temporal = [term for term in temporal_indicators if term in all_facts_text] + + assert len(found_temporal) >= 1, ( + f"Should convert relative dates to absolute. " + f"Found: {found_temporal}, Expected month/date references" + ) + + @pytest.mark.asyncio + async def test_date_field_calculation_last_night(self): + """ + Test that the date field is calculated correctly for "last night" events. + + CRITICAL: If conversation is on August 14, 2023 and text says "last night", + the date field should be August 13, NOT August 14. + """ + text = """ +Melanie: Hey Caroline! Last night was amazing! We celebrated my daughter's birthday +with a concert surrounded by music, joy and the warm summer breeze. +""" + + context = "Conversation between Melanie and Caroline" + llm_config = LLMConfig.for_memory() + + event_date = datetime(2023, 8, 14, 14, 24) + + facts = await extract_facts_from_text( + text=text, + event_date=event_date, + context=context, + llm_config=llm_config, + agent_name="Melanie" + ) + + assert len(facts) > 0, "Should extract at least one fact" + + print(f"\nExtracted {len(facts)} facts:") + for i, f in enumerate(facts): + print(f"{i+1}. Date: {f['occurred_start']} - {f['fact']}") + + birthday_fact = None + for fact in facts: + if "birthday" in fact['fact'].lower() or "concert" in fact['fact'].lower(): + birthday_fact = fact + break + + assert birthday_fact is not None, "Should extract fact about birthday celebration" + + fact_date_str = birthday_fact['occurred_start'] + + if 'T' in fact_date_str: + fact_date = datetime.fromisoformat(fact_date_str.replace('Z', '+00:00')) + else: + fact_date = datetime.fromisoformat(fact_date_str) + + assert fact_date.year == 2023, "Year should be 2023" + assert fact_date.month == 8, "Month should be August" + assert fact_date.day == 13, ( + f"Day should be 13 (last night relative to Aug 14), but got {fact_date.day}. " + f"Date field should be when FACT occurred, not when mentioned!" + ) + + @pytest.mark.asyncio + async def test_date_field_calculation_yesterday(self): + """Test that the date field is calculated correctly for "yesterday" events.""" + text = """ +Yesterday I went for a morning jog for the first time in a nearby park. +""" + + context = "Personal diary" + llm_config = LLMConfig.for_memory() + + event_date = datetime(2024, 11, 13) + + facts = await extract_facts_from_text( + text=text, + event_date=event_date, + context=context, + llm_config=llm_config, + agent_name="TestUser" + ) + + assert len(facts) > 0, "Should extract at least one fact" + + print(f"\nExtracted {len(facts)} facts:") + for i, f in enumerate(facts): + print(f"{i+1}. Date: {f['occurred_start']} - {f['fact']}") + + jogging_fact = facts[0] + + fact_date_str = jogging_fact['occurred_start'] + if 'T' in fact_date_str: + fact_date = datetime.fromisoformat(fact_date_str.replace('Z', '+00:00')) + else: + fact_date = datetime.fromisoformat(fact_date_str) + + assert fact_date.year == 2024, "Year should be 2024" + assert fact_date.month == 11, "Month should be November" + assert fact_date.day == 12, ( + f"Day should be 12 (yesterday relative to Nov 13), but got {fact_date.day}. " + f"Date field: {fact_date_str}" + ) + + all_facts_text = " ".join([f['fact'].lower() for f in facts]) + + assert "first time" in all_facts_text or "first" in all_facts_text, \ + "Should preserve 'first time' qualifier" + + assert "recently" not in all_facts_text, \ + "Should NOT convert 'yesterday' to 'recently'" + + assert any(term in all_facts_text for term in ["november", "12", "nov"]), \ + "Should convert 'yesterday' to absolute date in fact text" + + @pytest.mark.asyncio + async def test_extract_facts_with_relative_dates(self): + """Test that relative dates are converted to absolute dates.""" + + reference_date = datetime(2024, 3, 20, 14, 0, 0, tzinfo=timezone.utc) + llm_config = LLMConfig.for_memory() + + text = """ + Yesterday I went hiking in Yosemite. + Last week I started my new job at Google. + This morning I had coffee with Alice. + """ + + facts = await extract_facts_from_text( + text=text, + event_date=reference_date, + llm_config=llm_config, + agent_name="TestUser", + context="Personal diary" + ) + + print(f"\nExtracted {len(facts)} facts:") + for fact in facts: + print(f"- {fact['fact']}") + print(f" Date: {fact['occurred_start']}") + + assert len(facts) > 0, "Should extract at least one fact" + + for fact in facts: + assert 'fact' in fact, "Each fact should have 'fact' field" + assert 'occurred_start' in fact, "Each fact should have 'occurred_start' field" + assert fact['occurred_start'], f"Date should not be empty for fact: {fact['fact']}" + + dates = [f['occurred_start'] for f in facts] + unique_dates = set(dates) + if len(facts) >= 3: + assert len(unique_dates) >= 2, "Should have different dates for different temporal facts" + + print(f"\n All facts have absolute dates") + + @pytest.mark.asyncio + async def test_extract_facts_with_no_temporal_info(self): + """Test that facts without temporal info use the reference date.""" + + reference_date = datetime(2024, 3, 20, 14, 0, 0, tzinfo=timezone.utc) + llm_config = LLMConfig.for_memory() + + text = "Alice works at Google. She loves Python programming." + + facts = await extract_facts_from_text( + text=text, + event_date=reference_date, + llm_config=llm_config, + agent_name="TestUser", + context="General info" + ) + + print(f"\nExtracted {len(facts)} facts:") + for fact in facts: + print(f"- {fact['fact']}") + print(f" Date: {fact['occurred_start']}") + + assert len(facts) > 0, "Should extract at least one fact" + + for fact in facts: + assert fact['occurred_start'], f"Fact should have a date: {fact['fact']}" + + @pytest.mark.asyncio + async def test_extract_facts_with_absolute_dates(self): + """Test that absolute dates in text are preserved.""" + + reference_date = datetime(2024, 3, 20, 14, 0, 0, tzinfo=timezone.utc) + llm_config = LLMConfig.for_memory() + + text = """ + On March 15, 2024, Alice joined Google. + Bob will start his vacation on April 1st. + """ + + facts = await extract_facts_from_text( + text=text, + event_date=reference_date, + llm_config=llm_config, + agent_name="TestUser", + context="Calendar events" + ) + + print(f"\nExtracted {len(facts)} facts:") + for fact in facts: + print(f"- {fact['fact']}") + print(f" Date: {fact['occurred_start']}") + + assert len(facts) > 0, "Should extract at least one fact" + + for fact in facts: + assert fact['occurred_start'], f"Fact should have a date: {fact['fact']}" + + +# ============================================================================= +# LOGICAL INFERENCE TESTS +# ============================================================================= + +class TestLogicalInference: + """Tests that the system makes logical inferences to connect related information.""" + + @pytest.mark.asyncio + async def test_logical_inference_identity_connection(self): + """ + Test that the system makes logical inferences to connect related information. + + Example: "I lost a friend" + "this photo with Karlie" -> "I lost my friend Karlie" + """ + text = """ +Deborah: The roses and dahlias bring me peace. I lost a friend last week, +so I've been spending time in the garden to find some comfort. + +Jolene: Sorry to hear about your friend, Deb. Losing someone can be really tough. +How are you holding up? + +Deborah: Thanks for the kind words. It's been tough, but I'm comforted by +remembering our time together. It reminds me of how special life is. + +Jolene: Memories can give us so much comfort and joy. + +Deborah: Memories keep our loved ones close. This is the last photo with Karlie +which was taken last summer when we hiked. It was our last one. We had such a +great time! Every time I see it, I can't help but smile. +""" + + context = "Conversation between Deborah and Jolene" + llm_config = LLMConfig.for_memory() + + event_date = datetime(2023, 2, 23) + + facts = await extract_facts_from_text( + text=text, + event_date=event_date, + context=context, + llm_config=llm_config, + agent_name="Deborah" + ) + + assert len(facts) > 0, "Should extract at least one fact" + + print(f"\nExtracted {len(facts)} facts:") + for i, f in enumerate(facts): + print(f"{i+1}. {f['fact']}") + + all_facts_text = " ".join([f['fact'].lower() for f in facts]) + + has_karlie = "karlie" in all_facts_text + has_loss = any(word in all_facts_text for word in ["lost", "death", "passed", "died", "losing"]) + + assert has_karlie, "Should mention Karlie in the extracted facts" + assert has_loss, "Should mention the loss/death in the extracted facts" + + connected_fact_found = False + for fact in facts: + fact_text = fact['fact'].lower() + if "karlie" in fact_text and any(word in fact_text for word in ["lost", "death", "passed", "died", "losing"]): + connected_fact_found = True + print(f"\n Found connected fact: {fact['fact']}") + break + + assert connected_fact_found, ( + "Should connect 'lost a friend' with 'Karlie' in the same fact. " + f"The inference should be: Karlie is the lost friend. " + f"Facts: {[f['fact'] for f in facts]}" + ) + + @pytest.mark.asyncio + async def test_logical_inference_pronoun_resolution(self): + """ + Test that pronouns are resolved to their referents. + + Example: "I started a project" + "It's challenging" -> "The project is challenging" + """ + text = """ +I started a new machine learning project last month. +It's been really challenging but very rewarding. +I've learned so much from it. +""" + + context = "Personal update" + llm_config = LLMConfig.for_memory() + + facts = await extract_facts_from_text( + text=text, + event_date=datetime(2024, 11, 13), + context=context, + llm_config=llm_config, + agent_name="TestUser" + ) + + assert len(facts) > 0, "Should extract at least one fact" + + print(f"\nExtracted {len(facts)} facts:") + for i, f in enumerate(facts): + print(f"{i+1}. {f['fact']}") + + all_facts_text = " ".join([f['fact'].lower() for f in facts]) + + has_project = "project" in all_facts_text + has_qualities = any(word in all_facts_text for word in ["challenging", "rewarding", "learned"]) + + assert has_project, "Should mention the project" + assert has_qualities, "Should mention the qualities/learning" + + connected_fact_found = False + for fact in facts: + fact_text = fact['fact'].lower() + if "project" in fact_text and any(word in fact_text for word in ["challenging", "rewarding"]): + connected_fact_found = True + print(f"\n Found connected fact: {fact['fact']}") + break + + assert connected_fact_found, ( + "Should resolve 'it' to 'the project' and connect characteristics in the same fact. " + f"Facts: {[f['fact'] for f in facts]}" + ) + + +# ============================================================================= +# FACT CLASSIFICATION TESTS +# ============================================================================= + +class TestFactClassification: + """Tests that facts are correctly classified as agent vs world.""" + + @pytest.mark.asyncio + async def test_agent_facts_from_podcast_transcript(self): + """ + Test that when context identifies someone as 'you', their actions are classified as agent facts. + + This test addresses the issue where podcast transcripts with context like + "this was podcast episode between you (Marcus) and Jamie" were extracting + all facts as 'world' instead of properly identifying Marcus's statements as 'agent'. + """ + + transcript = """ +Marcus: I've been working on AI safety research for the past six months. +Jamie: That's really interesting! What specifically are you focusing on? +Marcus: I'm investigating interpretability methods. I believe we need to understand +how models make decisions before we can trust them in critical applications. +Jamie: I completely agree with that approach. +Marcus: I published a paper on this topic last month, and I'm presenting it at +the conference next week. +Jamie: Congratulations! I'd love to read it. +""" + + context = "Podcast episode between you (Marcus) and Jamie discussing AI research" + + llm_config = LLMConfig.for_memory() + + facts = await extract_facts_from_text( + text=transcript, + event_date=datetime(2024, 11, 13), + llm_config=llm_config, + agent_name="Marcus", + context=context + ) + + assert len(facts) > 0, "Should extract at least one fact from the transcript" + + print(f"\nExtracted {len(facts)} facts:") + for i, f in enumerate(facts): + print(f"{i+1}. [{f['fact_type']}] {f['fact']}") + + agent_facts = [f for f in facts if f["fact_type"] == "agent"] + + assert len(agent_facts) > 0, \ + f"Should have at least one 'agent' fact when context identifies 'you (Marcus)'. " \ + f"Got facts: {[f['fact'] + ' [' + f['fact_type'] + ']' for f in facts]}" + + for agent_fact in agent_facts: + fact_text = agent_fact["fact"] + assert fact_text.startswith("I ") or " I " in fact_text, \ + f"Agent facts must use first person ('I'). Got: {fact_text}" + + third_person_pattern = r'\bMarcus\s+(said|worked|has|published|explained|believes|attended|completed)' + match = re.search(third_person_pattern, fact_text) + assert not match, \ + f"Agent facts should use first person, not third person. " \ + f"Found '{match.group()}' in: {fact_text}" + + print(f"\n All {len(agent_facts)} agent facts use first person ('I')") + + jamie_facts = [f for f in facts if "Jamie" in f["fact"] and "Jamie" == f["fact"].split()[0]] + if jamie_facts: + world_jamie_facts = [f for f in jamie_facts if f["fact_type"] == "world"] + assert len(world_jamie_facts) > 0, \ + f"Jamie's statements should be 'world' facts. " \ + f"Jamie facts: {[f['fact'] + ' [' + f['fact_type'] + ']' for f in jamie_facts]}" + + print(f"\n Successfully classified {len(agent_facts)} agent facts and {len([f for f in facts if f['fact_type'] == 'world'])} world facts") + + @pytest.mark.asyncio + async def test_agent_facts_without_explicit_context(self): + """Test that when 'you' is used in the text itself, it gets properly classified.""" + + text = """ +I completed the project on machine learning interpretability last week. +My colleague Sarah helped me with the data analysis. +We presented our findings to the team yesterday. +""" + + context = "Personal work log" + + llm_config = LLMConfig.for_memory() + + facts = await extract_facts_from_text( + text=text, + event_date=datetime(2024, 11, 13), + llm_config=llm_config, + agent_name="TestUser", + context=context + ) + + assert len(facts) > 0, "Should extract facts" + + agent_facts = [f for f in facts if f["fact_type"] == "agent"] + + print(f"\n Extracted {len(facts)} total facts") + print(f"Agent facts: {len(agent_facts)}") + print(f"World facts: {len([f for f in facts if f['fact_type'] == 'world'])}") + + if agent_facts: + print(f"\nAgent facts found:") + for f in agent_facts: + print(f" - {f['fact']}") + + @pytest.mark.asyncio + async def test_speaker_attribution_predictions(self): + """ + Test that predictions made by different speakers are correctly attributed. + + This addresses the issue where Jamie's prediction of "Niners 27-13" was being + incorrectly attributed to Marcus (the agent) in the extracted facts. + """ + + transcript = """ +Marcus: [excited] I'm calling it now, Rams will win twenty seven to twenty four, their defense is too strong! +Jamie: [laughs] No way, I predict the Niners will win twenty seven to thirteen, comfy win at home. +Marcus: [angry] That's ridiculous, I stand by my Rams prediction. +Jamie: [teasing] We'll see who's right, my Niners pick is solid. +""" + + context = "podcast episode on match prediction of week 10 - Marcus (you) and Jamie - 14 nov" + agent_name = "Marcus" + + llm_config = LLMConfig.for_memory() + + facts = await extract_facts_from_text( + text=transcript, + event_date=datetime(2024, 11, 14), + context=context, + llm_config=llm_config, + agent_name=agent_name + ) + + assert len(facts) > 0, "Should extract at least one fact" + + print(f"\nExtracted {len(facts)} facts:") + for i, f in enumerate(facts): + print(f"{i+1}. [{f['fact_type']}] {f['fact']}") + + agent_facts = [f for f in facts if f["fact_type"] == "agent"] + jamie_facts = [f for f in facts if f["fact_type"] == "world" and "Jamie" in f["fact"]] + + print(f"\nAgent facts (Marcus): {len(agent_facts)}") + for f in agent_facts: + print(f" - {f['fact']}") + + print(f"\nWorld facts (Jamie): {len(jamie_facts)}") + for f in jamie_facts: + print(f" - {f['fact']}") + + agent_facts_text = " ".join([f["fact"].lower() for f in agent_facts]) + + assert "rams" in agent_facts_text or "twenty seven to twenty four" in agent_facts_text or "27" in agent_facts_text, \ + f"Agent facts should contain Marcus's Rams prediction. Agent facts: {[f['fact'] for f in agent_facts]}" + + has_niners_27_13 = False + for fact in agent_facts: + fact_lower = fact["fact"].lower() + if ("niners" in fact_lower or "49ers" in fact_lower) and ("27" in fact_lower or "twenty seven") and ("13" in fact_lower or "thirteen"): + has_niners_27_13 = True + print(f"\n ERROR: Found Jamie's Niners 27-13 prediction in agent facts: {fact['fact']}") + + assert not has_niners_27_13, \ + f"Agent facts should NOT contain Jamie's Niners 27-13 prediction! " \ + f"Agent facts: {[f['fact'] for f in agent_facts]}" + + if jamie_facts: + print(f"\n Jamie facts correctly classified as world facts") + + print(f"\n Speaker attribution test passed: Predictions correctly attributed to their speakers") + + @pytest.mark.asyncio + async def test_skip_podcast_meta_commentary(self): + """ + Test that podcast intros, outros, and calls to action are skipped. + + This addresses the issue where podcast outros like "that's all for today, + don't forget to subscribe" were being extracted as facts. + """ + + transcript = """ +Marcus: Welcome everyone to today's episode! Before we dive in, don't forget to +subscribe and leave a rating. + +Marcus: Today I want to talk about my research on interpretability in AI systems. +I've been working on this for about a year now. + +Jamie: That sounds really interesting! What made you focus on that area? + +Marcus: I believe it's crucial for AI safety. We need to understand how these +models make decisions before we can trust them in critical applications. + +Jamie: I completely agree with that approach. + +Marcus: Well, I think that's gonna do it for us today! Thanks for listening everyone. +Don't forget to tap follow or subscribe, tell a friend, and drop a quick rating +so the algorithm learns to box out. See you next week! +""" + + context = "Podcast episode between you (Marcus) and Jamie about AI" + + llm_config = LLMConfig.for_memory() + + facts = await extract_facts_from_text( + text=transcript, + event_date=datetime(2024, 11, 13), + llm_config=llm_config, + agent_name="Marcus", + context=context + ) + + print(f"\nExtracted {len(facts)} facts:") + for i, f in enumerate(facts): + print(f"{i+1}. [{f['fact_type']}] {f['fact']}") + + assert len(facts) > 0, "Should extract at least one fact" + + meta_phrases = [ + "subscribe", + "leave a rating", + "tap follow", + "tell a friend", + "that's gonna do it", + "thanks for listening", + "see you next week", + "welcome everyone", + "before we dive in" + ] + + for fact in facts: + fact_lower = fact["fact"].lower() + for phrase in meta_phrases: + assert phrase not in fact_lower, \ + f"Fact should not contain meta-commentary phrase '{phrase}'. " \ + f"Found in: {fact['fact']}" + + content_facts = [f for f in facts if "interpretability" in f["fact"].lower()] + assert len(content_facts) > 0, \ + "Should extract facts about the actual content discussed (interpretability)" + + print(f"\n Successfully filtered out meta-commentary") + print(f" Extracted {len(content_facts)} facts about actual content") + + +# ============================================================================= +# PERSONALITY INFERENCE TESTS +# ============================================================================= + +class TestPersonalityInference: + """Tests for LLM-based personality trait inference from background.""" + + @pytest.mark.asyncio + async def test_background_merge_with_personality_inference(self, memory): + """Test that background merge infers personality traits by default.""" + import uuid + agent_id = f"test_infer_{uuid.uuid4().hex[:8]}" + + result = await memory.merge_agent_background( + agent_id, + "I am a creative software engineer who loves innovation and trying new technologies", + update_personality=True + ) + + assert "background" in result + assert "personality" in result + + background = result["background"] + personality = result["personality"] + + assert "creative" in background.lower() or "innovation" in background.lower() + + assert "openness" in personality + assert personality["openness"] > 0.5 + assert 0.0 <= personality["openness"] <= 1.0 + + required_traits = ["openness", "conscientiousness", "extraversion", + "agreeableness", "neuroticism", "bias_strength"] + for trait in required_traits: + assert trait in personality + assert 0.0 <= personality[trait] <= 1.0 + + @pytest.mark.asyncio + async def test_background_merge_without_personality_inference(self, memory): + """Test that background merge skips personality inference when disabled.""" + import uuid + agent_id = f"test_no_infer_{uuid.uuid4().hex[:8]}" + + initial_profile = await memory.get_agent_profile(agent_id) + initial_personality = initial_profile["personality"] + + result = await memory.merge_agent_background( + agent_id, + "I am a data scientist", + update_personality=False + ) + + assert "background" in result + assert "personality" not in result + + final_profile = await memory.get_agent_profile(agent_id) + final_personality = final_profile["personality"] + + assert initial_personality == final_personality + + @pytest.mark.asyncio + async def test_personality_inference_for_organized_engineer(self, memory): + """Test personality inference for organized/conscientious profile.""" + import uuid + agent_id = f"test_organized_{uuid.uuid4().hex[:8]}" + + result = await memory.merge_agent_background( + agent_id, + "I am a methodical engineer who values organization and systematic planning", + update_personality=True + ) + + personality = result["personality"] + + assert personality["conscientiousness"] > 0.5 + + @pytest.mark.asyncio + async def test_personality_inference_for_startup_founder(self, memory): + """Test personality inference for entrepreneurial profile.""" + import uuid + agent_id = f"test_founder_{uuid.uuid4().hex[:8]}" + + result = await memory.merge_agent_background( + agent_id, + "I am a startup founder who thrives on risk and social interaction", + update_personality=True + ) + + personality = result["personality"] + + assert personality["openness"] > 0.5 + assert personality["extraversion"] > 0.5 + + @pytest.mark.asyncio + async def test_personality_updates_in_database(self, memory): + """Test that inferred personality is actually stored in database.""" + import uuid + agent_id = f"test_db_update_{uuid.uuid4().hex[:8]}" + + result = await memory.merge_agent_background( + agent_id, + "I am an innovative designer", + update_personality=True + ) + + inferred_personality = result["personality"] + + profile = await memory.get_agent_profile(agent_id) + db_personality = profile["personality"] + + assert db_personality == inferred_personality + + @pytest.mark.asyncio + async def test_multiple_background_merges_update_personality(self, memory): + """Test that each background merge can update personality.""" + import uuid + agent_id = f"test_multi_merge_{uuid.uuid4().hex[:8]}" + + result1 = await memory.merge_agent_background( + agent_id, + "I am a software engineer", + update_personality=True + ) + personality1 = result1["personality"] + + result2 = await memory.merge_agent_background( + agent_id, + "I love creative problem solving and innovation", + update_personality=True + ) + personality2 = result2["personality"] + + assert "engineer" in result2["background"].lower() or "software" in result2["background"].lower() + assert "creative" in result2["background"].lower() or "innovation" in result2["background"].lower() + + @pytest.mark.asyncio + async def test_background_merge_conflict_resolution_with_personality(self, memory): + """Test that conflicts are resolved and personality reflects final background.""" + import uuid + agent_id = f"test_conflict_{uuid.uuid4().hex[:8]}" + + await memory.merge_agent_background( + agent_id, + "I was born in Colorado and prefer stability", + update_personality=True + ) + + result = await memory.merge_agent_background( + agent_id, + "You were born in Texas and love taking risks", + update_personality=True + ) + + background = result["background"] + personality = result["personality"] + + assert "texas" in background.lower() + assert personality["openness"] > 0.5 \ No newline at end of file diff --git a/memora/tests/test_fact_ordering.py b/hindsight-api/tests/test_fact_ordering.py similarity index 73% rename from memora/tests/test_fact_ordering.py rename to hindsight-api/tests/test_fact_ordering.py index c2e50e2f3b..3ed4fbbff0 100644 --- a/memora/tests/test_fact_ordering.py +++ b/hindsight-api/tests/test_fact_ordering.py @@ -7,31 +7,14 @@ """ import pytest from datetime import datetime, timezone -from memora import TemporalSemanticMemory +from hindsight_api import MemoryEngine import os @pytest.mark.asyncio -async def test_fact_ordering_within_conversation(): - """ - Test that facts extracted from one conversation get incremental time offsets - to preserve their ordering for retrieval. - """ - - # Create memory instance - memory = TemporalSemanticMemory( - db_url=os.getenv("MEMORA_API_DATABASE_URL"), - memory_llm_provider=os.getenv("MEMORA_API_LLM_PROVIDER", "groq"), - memory_llm_api_key=os.getenv("MEMORA_API_LLM_API_KEY"), - memory_llm_model=os.getenv("MEMORA_API_LLM_MODEL", "openai/gpt-oss-20b"), - ) - await memory.initialize() - +async def test_fact_ordering_within_conversation(memory): agent_id = "test_ordering_agent" - # Clear any existing data - await memory.delete_agent(agent_id) - # Get/create agent (auto-creates with defaults) await memory.get_agent_profile(agent_id) @@ -74,20 +57,20 @@ async def test_fact_ordering_within_conversation(): max_tokens=8192 ) - print(f"\n=== Retrieved {len(results['results'])} facts ===") - for i, result in enumerate(results['results']): - print(f"{i+1}. [{result['event_date']}] {result['text'][:100]}") + print(f"\n=== Retrieved {len(results.results)} facts ===") + for i, result in enumerate(results.results): + print(f"{i+1}. [{result.event_date}] {result.text[:100]}") # Get all agent facts (Marcus's statements) - agent_facts = [r for r in results['results'] if r.get('fact_type') == 'agent'] + agent_facts = [r for r in results.results if r.fact_type == 'agent'] print(f"\n=== Agent facts (Marcus's statements) ===") for i, fact in enumerate(agent_facts): - print(f"{i+1}. [{fact['event_date']}] {fact['text']}") + print(f"{i+1}. [{fact.event_date}] {fact.text}") # Check that agent facts have different timestamps if len(agent_facts) >= 2: - timestamps = [datetime.fromisoformat(f['event_date'].replace('Z', '+00:00')) for f in agent_facts] + timestamps = [datetime.fromisoformat(f.event_date.replace('Z', '+00:00')) for f in agent_facts] # Verify timestamps are different (have time offsets) unique_timestamps = set(timestamps) @@ -111,7 +94,7 @@ async def test_fact_ordering_within_conversation(): # Verify that retrieval returns facts in chronological order # The first prediction should come before the changed prediction - agent_texts = [f['text'].lower() for f in agent_facts] + agent_texts = [f.text.lower() for f in agent_facts] # Look for evidence of the sequence has_first_prediction = any('27' in text and '24' in text for text in agent_texts) @@ -122,8 +105,8 @@ async def test_fact_ordering_within_conversation(): first_idx = next(i for i, text in enumerate(agent_texts) if '27' in text and '24' in text) changed_idx = next(i for i, text in enumerate(agent_texts) if 'chang' in text or 'by 3' in text or 'realized' in text) - print(f"\nFirst prediction at index {first_idx}: {agent_facts[first_idx]['text'][:100]}") - print(f"Changed prediction at index {changed_idx}: {agent_facts[changed_idx]['text'][:100]}") + print(f"\nFirst prediction at index {first_idx}: {agent_facts[first_idx].text[:100]}") + print(f"Changed prediction at index {changed_idx}: {agent_facts[changed_idx].text[:100]}") # The original prediction should come before the changed one assert timestamps[first_idx] < timestamps[changed_idx], \ @@ -138,24 +121,10 @@ async def test_fact_ordering_within_conversation(): @pytest.mark.asyncio -async def test_multiple_documents_ordering(): - """ - Test that facts from different documents get separate time offsets, - so facts within each document maintain their order. - """ - - memory = TemporalSemanticMemory( - db_url=os.getenv("MEMORA_API_DATABASE_URL"), - memory_llm_provider=os.getenv("MEMORA_API_LLM_PROVIDER", "groq"), - memory_llm_api_key=os.getenv("MEMORA_API_LLM_API_KEY"), - memory_llm_model=os.getenv("MEMORA_API_LLM_MODEL", "openai/gpt-oss-20b"), - ) - await memory.initialize() +async def test_multiple_documents_ordering(memory): agent_id = "test_multi_doc_agent" - # Clear and create agent - await memory.delete_agent(agent_id) await memory.get_agent_profile(agent_id) # Auto-creates with defaults # Two separate conversations with same base time @@ -191,15 +160,15 @@ async def test_multiple_documents_ordering(): max_tokens=8192 ) - print(f"\n=== Retrieved {len(results['results'])} agent facts ===") - agent_facts = [r for r in results['results'] if r.get('fact_type') == 'agent'] + print(f"\n=== Retrieved {len(results.results)} agent facts ===") + agent_facts = [r for r in results.results if r.fact_type == 'agent'] for i, fact in enumerate(agent_facts): - print(f"{i+1}. [{fact['event_date']}] {fact['text'][:80]}") + print(f"{i+1}. [{fact.event_date}] {fact.text[:80]}") # Each conversation's facts should have different timestamps if len(agent_facts) >= 2: - timestamps = [datetime.fromisoformat(f['event_date'].replace('Z', '+00:00')) for f in agent_facts] + timestamps = [datetime.fromisoformat(f.event_date.replace('Z', '+00:00')) for f in agent_facts] unique_timestamps = set(timestamps) assert len(unique_timestamps) >= 2, \ diff --git a/memora/tests/test_api_integration.py b/hindsight-api/tests/test_http_api_integration.py similarity index 99% rename from memora/tests/test_api_integration.py rename to hindsight-api/tests/test_http_api_integration.py index 00768e2c0c..945e8b3613 100644 --- a/memora/tests/test_api_integration.py +++ b/hindsight-api/tests/test_http_api_integration.py @@ -1,5 +1,5 @@ """ -Integration test for the complete Memora API. +Integration test for the complete Hindsight API. Tests all endpoints by starting a FastAPI server and making HTTP requests. """ @@ -7,7 +7,7 @@ import pytest_asyncio import httpx from datetime import datetime -from memora.api import create_app +from hindsight_api.api import create_app @pytest_asyncio.fixture diff --git a/memora/tests/mcp_server/test_server.py b/hindsight-api/tests/test_mcp_api_integration.py similarity index 74% rename from memora/tests/mcp_server/test_server.py rename to hindsight-api/tests/test_mcp_api_integration.py index ae02f8cc1b..5098c54066 100644 --- a/memora/tests/mcp_server/test_server.py +++ b/hindsight-api/tests/test_mcp_api_integration.py @@ -1,17 +1,42 @@ -"""Test MCP server with real server and client.""" +""" +Integration test for the MCP (Model Context Protocol) server. +Tests MCP endpoints by starting a FastAPI server with MCP enabled and using the MCP client. + +Note: MCP server is integrated with the web server. These tests require HINDSIGHT_API_MCP_ENABLED=true. +""" import asyncio -import os import pytest +import pytest_asyncio +import httpx from mcp import ClientSession from mcp.client.sse import sse_client - - -# Note: MCP server tests now require the full web server to be running -# with MEMORA_API_MCP_ENABLED=true since there's no standalone MCP server anymore. -# These tests are kept for documentation but may need manual server setup. - -pytest.skip("MCP server is now integrated with web server. Run web server with MEMORA_API_MCP_ENABLED=true to test.", allow_module_level=True) +from hindsight_api.api import create_app + + +@pytest_asyncio.fixture +async def mcp_server(memory): + """Start the FastAPI app with MCP enabled and return the SSE URL.""" + app = create_app( + memory, + run_migrations=False, + initialize_memory=False, + mcp_enabled=True, + default_agent_id="test_mcp_agent" + ) + + # Use httpx to create a test server + transport = httpx.ASGITransport(app=app) + async with httpx.AsyncClient(transport=transport, base_url="http://test") as client: + # The MCP SSE endpoint is at /mcp/sse + # We need to yield the base URL for sse_client to connect + # However, sse_client expects a real URL, not a test client + # So we'll start a real server on a random port + pass + + # For now, skip these tests as they require a real server + # The sse_client doesn't work with ASGI test transport + pytest.skip("MCP tests require a real running server. Run: HINDSIGHT_API_MCP_ENABLED=true uvicorn hindsight_api.api:app") @pytest.mark.asyncio @@ -27,12 +52,12 @@ async def test_mcp_server_tools_via_sse(mcp_server): tools_list = await session.list_tools() print(f"Tools: {tools_list}") tool_names = [t.name for t in tools_list.tools] - assert "memora_search" in tool_names - assert "memora_put" in tool_names + assert "hindsight_search" in tool_names + assert "hindsight_put" in tool_names - # Test 2: Call memora_put + # Test 2: Call hindsight_put put_result = await session.call_tool( - "memora_put", + "hindsight_put", arguments={ "content": "User loves Python programming", "context": "programming_preferences", @@ -45,9 +70,9 @@ async def test_mcp_server_tools_via_sse(mcp_server): # Wait a bit for indexing await asyncio.sleep(1) - # Test 3: Call memora_search + # Test 3: Call hindsight_search search_result = await session.call_tool( - "memora_search", + "hindsight_search", arguments={ "query": "What programming languages does the user like?", "max_tokens": 4096, @@ -71,7 +96,7 @@ async def test_multiple_concurrent_requests(mcp_server): async def make_search(idx): try: result = await session.call_tool( - "memora_search", + "hindsight_search", arguments={ "query": f"test query {idx}", "explanation": f"Concurrent test {idx}" @@ -120,7 +145,7 @@ async def rapid_session_search(idx): # Make request immediately after initialization result = await session.call_tool( - "memora_search", + "hindsight_search", arguments={ "query": f"rapid query {idx}", "max_tokens": 2048 diff --git a/memora/tests/test_query_analyzer.py b/hindsight-api/tests/test_query_analyzer.py similarity index 72% rename from memora/tests/test_query_analyzer.py rename to hindsight-api/tests/test_query_analyzer.py index ee0d482a30..9a3a13dae2 100644 --- a/memora/tests/test_query_analyzer.py +++ b/hindsight-api/tests/test_query_analyzer.py @@ -3,16 +3,14 @@ """ import pytest from datetime import datetime -from memora.query_analyzer import TransformerQueryAnalyzer, QueryAnalysis +from hindsight_api.engine.query_analyzer import TransformerQueryAnalyzer, QueryAnalysis -def test_query_analyzer_june_2024(): - """Test extracting 'june 2024' from query.""" - analyzer = TransformerQueryAnalyzer() +def test_query_analyzer_june_2024(query_analyzer): reference_date = datetime(2025, 1, 15, 12, 0, 0) query = "june 2024" - analysis = analyzer.analyze(query, reference_date) + analysis = query_analyzer.analyze(query, reference_date) print(f"\nQuery: '{query}'") print(f"Analysis: {analysis}") @@ -26,13 +24,11 @@ def test_query_analyzer_june_2024(): assert analysis.temporal_constraint.end_date.day == 30 -def test_query_analyzer_dogs_june_2023(): - """Test extracting temporal info from 'dogs in June 2023'.""" - analyzer = TransformerQueryAnalyzer() +def test_query_analyzer_dogs_june_2023(query_analyzer): reference_date = datetime(2025, 1, 15, 12, 0, 0) query = "dogs in June 2023" - analysis = analyzer.analyze(query, reference_date) + analysis = query_analyzer.analyze(query, reference_date) print(f"\nQuery: '{query}'") print(f"Analysis: {analysis}") @@ -46,13 +42,11 @@ def test_query_analyzer_dogs_june_2023(): assert analysis.temporal_constraint.end_date.day == 30 -def test_query_analyzer_march_2023(): - """Test extracting 'March 2023' from query.""" - analyzer = TransformerQueryAnalyzer() +def test_query_analyzer_march_2023(query_analyzer): reference_date = datetime(2025, 1, 15, 12, 0, 0) query = "March 2023" - analysis = analyzer.analyze(query, reference_date) + analysis = query_analyzer.analyze(query, reference_date) print(f"\nQuery: '{query}'") print(f"Analysis: {analysis}") @@ -66,13 +60,11 @@ def test_query_analyzer_march_2023(): assert analysis.temporal_constraint.end_date.day == 31 -def test_query_analyzer_last_year(): - """Test extracting 'last year' from query.""" - analyzer = TransformerQueryAnalyzer() +def test_query_analyzer_last_year(query_analyzer): reference_date = datetime(2025, 1, 15, 12, 0, 0) query = "last year" - analysis = analyzer.analyze(query, reference_date) + analysis = query_analyzer.analyze(query, reference_date) print(f"\nQuery: '{query}'") print(f"Analysis: {analysis}") @@ -86,13 +78,11 @@ def test_query_analyzer_last_year(): assert analysis.temporal_constraint.end_date.day == 31 -def test_query_analyzer_no_temporal(): - """Test that queries without temporal info return None.""" - analyzer = TransformerQueryAnalyzer() +def test_query_analyzer_no_temporal(query_analyzer): reference_date = datetime(2025, 1, 15, 12, 0, 0) query = "what is the weather" - analysis = analyzer.analyze(query, reference_date) + analysis = query_analyzer.analyze(query, reference_date) print(f"\nQuery: '{query}'") print(f"Analysis: {analysis}") @@ -100,13 +90,11 @@ def test_query_analyzer_no_temporal(): assert analysis.temporal_constraint is None, "Should not extract temporal constraint" -def test_query_analyzer_activities_june_2024(): - """Test extracting temporal info from 'melanie activities in june 2024'.""" - analyzer = TransformerQueryAnalyzer() +def test_query_analyzer_activities_june_2024(query_analyzer): reference_date = datetime(2025, 1, 15, 12, 0, 0) query = "melanie activities in june 2024" - analysis = analyzer.analyze(query, reference_date) + analysis = query_analyzer.analyze(query, reference_date) print(f"\nQuery: '{query}'") print(f"Analysis: {analysis}") @@ -120,5 +108,3 @@ def test_query_analyzer_activities_june_2024(): assert analysis.temporal_constraint.end_date.day == 30 -if __name__ == "__main__": - pytest.main([__file__, "-v", "-s"]) diff --git a/memora/tests/test_search_trace.py b/hindsight-api/tests/test_search_trace.py similarity index 99% rename from memora/tests/test_search_trace.py rename to hindsight-api/tests/test_search_trace.py index 75d1205f8e..f4c2afb1df 100644 --- a/memora/tests/test_search_trace.py +++ b/hindsight-api/tests/test_search_trace.py @@ -2,7 +2,7 @@ Test search tracing functionality. """ import pytest -from memora.search_trace import SearchTrace +from hindsight_api import SearchTrace from datetime import datetime, timezone diff --git a/memora/tests/test_temporal_ranges.py b/hindsight-api/tests/test_temporal_ranges.py similarity index 93% rename from memora/tests/test_temporal_ranges.py rename to hindsight-api/tests/test_temporal_ranges.py index d3a5163c3c..44d5eda6e6 100644 --- a/memora/tests/test_temporal_ranges.py +++ b/hindsight-api/tests/test_temporal_ranges.py @@ -3,7 +3,7 @@ import os from datetime import datetime, timezone, timedelta import pytest -from memora import TemporalSemanticMemory +from hindsight_api import MemoryEngine @pytest.mark.asyncio @@ -11,11 +11,11 @@ async def test_temporal_ranges_are_written(): """Test that occurred_start, occurred_end, and mentioned_at are actually written to database.""" # Initialize memory system - memory = TemporalSemanticMemory( - db_url=os.getenv("MEMORA_API_DATABASE_URL", "postgresql://memora:memora_dev@localhost:5432/memora"), - memory_llm_provider=os.getenv("MEMORA_API_LLM_PROVIDER", "groq"), - memory_llm_api_key=os.getenv("MEMORA_API_LLM_API_KEY"), - memory_llm_model=os.getenv("MEMORA_API_LLM_MODEL", "openai/gpt-oss-20b"), + memory = MemoryEngine( + db_url=os.getenv("HINDSIGHT_API_DATABASE_URL", "postgresql://hindsight:hindsight_dev@localhost:5432/hindsight"), + memory_llm_provider=os.getenv("HINDSIGHT_API_LLM_PROVIDER", "groq"), + memory_llm_api_key=os.getenv("HINDSIGHT_API_LLM_API_KEY"), + memory_llm_model=os.getenv("HINDSIGHT_API_LLM_MODEL", "openai/gpt-oss-20b"), ) await memory.initialize() diff --git a/memora/tests/test_think.py b/hindsight-api/tests/test_think.py similarity index 100% rename from memora/tests/test_think.py rename to hindsight-api/tests/test_think.py diff --git a/memora-cli/.github/workflows/release.yml b/hindsight-cli/.github/workflows/release.yml similarity index 100% rename from memora-cli/.github/workflows/release.yml rename to hindsight-cli/.github/workflows/release.yml diff --git a/memora-cli/.gitignore b/hindsight-cli/.gitignore similarity index 100% rename from memora-cli/.gitignore rename to hindsight-cli/.gitignore diff --git a/memora-cli/Cargo.toml b/hindsight-cli/Cargo.toml similarity index 83% rename from memora-cli/Cargo.toml rename to hindsight-cli/Cargo.toml index 7351c55efb..6b34a592cf 100644 --- a/memora-cli/Cargo.toml +++ b/hindsight-cli/Cargo.toml @@ -1,13 +1,13 @@ [package] -name = "memora-cli-rust" +name = "hindsight-cli" version = "0.0.7" edition = "2021" -authors = ["Memora Team"] -description = "A beautiful CLI for Memora - semantic memory system" +authors = ["Hindsight Team"] +description = "A beautiful CLI for Hindsight - semantic memory system" license = "MIT" [[bin]] -name = "memora" +name = "hindsight" path = "src/main.rs" [dependencies] diff --git a/memora-cli/build.sh b/hindsight-cli/build.sh similarity index 80% rename from memora-cli/build.sh rename to hindsight-cli/build.sh index 659283607a..b56123b89c 100755 --- a/memora-cli/build.sh +++ b/hindsight-cli/build.sh @@ -1,7 +1,7 @@ #!/bin/bash set -e -# Build script for memora-cli-rust +# Build script for hindsight-cli # This script builds optimized binaries for multiple platforms # Source cargo environment if it exists @@ -19,7 +19,7 @@ if ! command -v cargo &> /dev/null; then exit 1 fi -echo "Building Memora CLI for multiple platforms..." +echo "Building Hindsight CLI for multiple platforms..." # Ensure we're in the right directory cd "$(dirname "$0")" @@ -50,10 +50,10 @@ build_target() { # Copy to dist if [[ "$target" == *"windows"* ]]; then - cp "target/$target/release/memora.exe" "dist/$output_name.exe" + cp "target/$target/release/hindsight.exe" "dist/$output_name.exe" echo "Created: dist/$output_name.exe" else - cp "target/$target/release/memora" "dist/$output_name" + cp "target/$target/release/hindsight" "dist/$output_name" chmod +x "dist/$output_name" echo "Created: dist/$output_name" fi @@ -70,19 +70,19 @@ case "$OS" in Darwin) if [[ "$ARCH" == "arm64" ]]; then echo "Building for macOS ARM64 (Apple Silicon)..." - build_target "aarch64-apple-darwin" "memora-macos-arm64" + build_target "aarch64-apple-darwin" "hindsight-macos-arm64" else echo "Building for macOS x86_64 (Intel)..." - build_target "x86_64-apple-darwin" "memora-macos-x86_64" + build_target "x86_64-apple-darwin" "hindsight-macos-x86_64" fi ;; Linux) if [[ "$ARCH" == "x86_64" ]]; then echo "Building for Linux x86_64..." - build_target "x86_64-unknown-linux-gnu" "memora-linux-x86_64" + build_target "x86_64-unknown-linux-gnu" "hindsight-linux-x86_64" elif [[ "$ARCH" == "aarch64" ]]; then echo "Building for Linux ARM64..." - build_target "aarch64-unknown-linux-gnu" "memora-linux-arm64" + build_target "aarch64-unknown-linux-gnu" "hindsight-linux-arm64" fi ;; *) diff --git a/memora-cli/install.sh b/hindsight-cli/install.sh similarity index 88% rename from memora-cli/install.sh rename to hindsight-cli/install.sh index 0faeb08ec7..9fa4ae4c8d 100755 --- a/memora-cli/install.sh +++ b/hindsight-cli/install.sh @@ -1,12 +1,12 @@ #!/bin/bash set -e -# Memora CLI installer +# Hindsight CLI installer # Usage: curl -sSf https://your-domain.com/install.sh | sh -REPO_URL="https://github.com/your-org/memora-cli" -INSTALL_DIR="${MEMORA_INSTALL_DIR:-$HOME/.local/bin}" -BINARY_NAME="memora" +REPO_URL="https://github.com/your-org/hindsight-cli" +INSTALL_DIR="${HINDSIGHT_INSTALL_DIR:-$HOME/.local/bin}" +BINARY_NAME="hindsight" # Colors for output RED='\033[0;31m' @@ -34,7 +34,7 @@ print_warning() { print_banner() { echo "" echo -e "${BLUE}โ•”โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•—${NC}" - echo -e "${BLUE}โ•‘ MEMORA CLI INSTALLER โ•‘${NC}" + echo -e "${BLUE}โ•‘ HINDSIGHT CLI INSTALLER โ•‘${NC}" echo -e "${BLUE}โ•šโ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•${NC}" echo "" } @@ -75,10 +75,10 @@ detect_platform() { # Download binary download_binary() { local platform=$1 - local download_url="${REPO_URL}/releases/latest/download/memora-${platform}" - local tmp_file="/tmp/memora-$$" + local download_url="${REPO_URL}/releases/latest/download/hindsight-${platform}" + local tmp_file="/tmp/hindsight-$$" - print_info "Downloading Memora CLI for $platform..." + print_info "Downloading Hindsight CLI for $platform..." if command -v curl > /dev/null 2>&1; then curl -fsSL "$download_url" -o "$tmp_file" @@ -150,7 +150,7 @@ main() { print_info "Try it out: $BINARY_NAME --help" echo "" print_info "Configure the API URL:" - echo " export MEMORA_API_URL=http://localhost:8080" + echo " export HINDSIGHT_API_URL=http://localhost:8888" echo "" } diff --git a/memora-cli/src/api.rs b/hindsight-cli/src/api.rs similarity index 92% rename from memora-cli/src/api.rs rename to hindsight-cli/src/api.rs index 62742cdf95..66c3ad7d18 100644 --- a/memora-cli/src/api.rs +++ b/hindsight-cli/src/api.rs @@ -1,17 +1,9 @@ use anyhow::{Context, Result}; -use reqwest::blocking::{Client, Response}; +use reqwest::blocking::Client; use serde::{Deserialize, Serialize}; use std::collections::HashMap; use std::time::Duration; -pub struct ApiError { - pub url: String, - pub request_body: String, - pub response_status: Option, - pub response_body: Option, - pub error: anyhow::Error, -} - #[derive(Debug, Serialize)] pub struct SearchRequest { pub query: String, @@ -125,11 +117,6 @@ pub struct AgentProfile { pub background: String, } -#[derive(Debug, Serialize)] -pub struct UpdatePersonalityRequest { - pub personality: PersonalityTraits, -} - #[derive(Debug, Serialize)] pub struct AddBackgroundRequest { pub content: String, @@ -479,64 +466,6 @@ impl ApiClient { Ok(result) } - pub fn update_personality( - &self, - agent_id: &str, - openness: f32, - conscientiousness: f32, - extraversion: f32, - agreeableness: f32, - neuroticism: f32, - bias_strength: f32, - verbose: bool, - ) -> Result { - let url = format!("{}/api/v1/agents/{}/profile", self.base_url, agent_id); - let request = UpdatePersonalityRequest { - personality: PersonalityTraits { - openness, - conscientiousness, - extraversion, - agreeableness, - neuroticism, - bias_strength, - }, - }; - - if verbose { - eprintln!("Request URL: {}", url); - eprintln!("Request body:\n{}", serde_json::to_string_pretty(&request).unwrap_or_default()); - } - - let response = self - .client - .put(&url) - .json(&request) - .timeout(Duration::from_secs(30)) - .send()?; - - let status = response.status(); - if verbose { - eprintln!("Response status: {}", status); - } - - if !status.is_success() { - let error_body = response.text().unwrap_or_default(); - if verbose { - eprintln!("Error response body:\n{}", error_body); - } - anyhow::bail!("API returned error status {}: {}", status, error_body); - } - - let response_text = response.text()?; - if verbose { - eprintln!("Response body:\n{}", response_text); - } - - let result: AgentProfile = serde_json::from_str(&response_text) - .with_context(|| format!("Failed to parse API response. Response was: {}", response_text))?; - Ok(result) - } - pub fn add_background(&self, agent_id: &str, content: &str, update_personality: bool, verbose: bool) -> Result { let url = format!("{}/api/v1/agents/{}/background", self.base_url, agent_id); let request = AddBackgroundRequest { diff --git a/memora-cli/src/config.rs b/hindsight-cli/src/config.rs similarity index 88% rename from memora-cli/src/config.rs rename to hindsight-cli/src/config.rs index ca83625c21..0288c5813f 100644 --- a/memora-cli/src/config.rs +++ b/hindsight-cli/src/config.rs @@ -4,9 +4,9 @@ use std::fs; use std::io::{self, Write}; use std::path::PathBuf; -const DEFAULT_API_URL: &str = "http://localhost:8080"; +const DEFAULT_API_URL: &str = "http://localhost:8888"; const CONFIG_FILE_NAME: &str = "config"; -const CONFIG_DIR_NAME: &str = ".memora"; +const CONFIG_DIR_NAME: &str = ".hindsight"; pub struct Config { pub api_url: String, @@ -32,12 +32,12 @@ impl std::fmt::Display for ConfigSource { impl Config { /// Load configuration with the following priority: - /// 1. Environment variable (MEMORA_API_URL) - highest priority, for overrides - /// 2. Local config file (~/.memora/config.toml) - /// 3. Default (http://localhost:8080) + /// 1. Environment variable (HINDSIGHT_API_URL) - highest priority, for overrides + /// 2. Local config file (~/.hindsight/config.toml) + /// 3. Default (http://localhost:8888) pub fn load() -> Result { // 1. Environment variable takes highest priority (for overrides) - if let Ok(api_url) = env::var("MEMORA_API_URL") { + if let Ok(api_url) = env::var("HINDSIGHT_API_URL") { return Self::validate_and_create(api_url, ConfigSource::Environment); } @@ -124,12 +124,6 @@ impl Config { pub fn api_url(&self) -> &str { &self.api_url } - - pub fn config_file_path_display() -> String { - Self::config_file_path() - .map(|p| p.display().to_string()) - .unwrap_or_else(|| "~/.memora/config.toml".to_string()) - } } /// Prompt user for API URL interactively diff --git a/memora-cli/src/errors.rs b/hindsight-cli/src/errors.rs similarity index 87% rename from memora-cli/src/errors.rs rename to hindsight-cli/src/errors.rs index 0d2b9ed419..9a830b6c86 100644 --- a/memora-cli/src/errors.rs +++ b/hindsight-cli/src/errors.rs @@ -1,4 +1,3 @@ -use anyhow::Result; use colored::*; pub fn handle_api_error(err: anyhow::Error, api_url: &str) -> ! { @@ -14,15 +13,15 @@ fn format_error_message(err: &anyhow::Error, api_url: &str) -> String { return format!( "{} {}\n\n{}\n {}\n\n{}\n โ€ข {}\n โ€ข {}\n โ€ข {}\n\n{}\n {}", "โœ—".bright_red().bold(), - "Cannot connect to Memora API".bright_red().bold(), + "Cannot connect to Hindsight API".bright_red().bold(), "API URL:".bright_yellow(), api_url.bright_white(), "Possible causes:".bright_yellow(), - "The Memora API server is not running".bright_white(), + "The Hindsight API server is not running".bright_white(), format!("The server is running on a different address than {}", api_url).bright_white(), "A firewall is blocking the connection".bright_white(), "Try:".bright_green(), - "Start the Memora API server and ensure it's accessible".bright_white() + "Start the Hindsight API server and ensure it's accessible".bright_white() ); } @@ -55,7 +54,7 @@ fn format_error_message(err: &anyhow::Error, api_url: &str) -> String { "The hostname in the API URL is incorrect".bright_white(), "DNS server is not responding".bright_white(), "Try:".bright_green(), - "Check the MEMORA_API_URL environment variable".bright_white() + "Check the HINDSIGHT_API_URL environment variable".bright_white() ); } @@ -71,7 +70,7 @@ fn format_error_message(err: &anyhow::Error, api_url: &str) -> String { "The API endpoint path has changed".bright_white(), "You're using an incompatible API version".bright_white(), "Try:".bright_green(), - "Check that you're using the correct Memora API version".bright_white() + "Check that you're using the correct Hindsight API version".bright_white() ); } @@ -119,7 +118,7 @@ fn format_error_message(err: &anyhow::Error, api_url: &str) -> String { "The API URL format is invalid.".bright_yellow(), "Ensure it starts with http:// or https://".bright_white(), "Example:".bright_green(), - "export MEMORA_API_URL=http://localhost:8080".bright_white() + "export HINDSIGHT_API_URL=http://localhost:8888".bright_white() ); } @@ -150,7 +149,7 @@ fn format_error_message(err: &anyhow::Error, api_url: &str) -> String { response_hint, "Try:".bright_green(), "Run with --verbose flag to see the full request/response".bright_white(), - "Ensure you're using a compatible Memora API version".bright_white() + "Ensure you're using a compatible Hindsight API version".bright_white() ); } @@ -164,8 +163,8 @@ fn format_error_message(err: &anyhow::Error, api_url: &str) -> String { "Error:".bright_yellow(), err_str.bright_white(), "Suggestions:".bright_green(), - "Check that MEMORA_API_URL is set correctly".bright_white(), - "Ensure the Memora API server is running".bright_white(), + "Check that HINDSIGHT_API_URL is set correctly".bright_white(), + "Ensure the Hindsight API server is running".bright_white(), "Verify network connectivity to the API server".bright_white() ) } @@ -173,14 +172,14 @@ fn format_error_message(err: &anyhow::Error, api_url: &str) -> String { pub fn print_config_help() { println!("\n{}", "Configuration:".bright_cyan().bold()); println!(" Run the configure command to set the API URL:"); - println!(" {}", "memora configure".bright_white()); + println!(" {}", "hindsight configure".bright_white()); println!(); println!(" Or set it directly:"); - println!(" {}", "memora configure --api-url http://your-api:8080".bright_white()); + println!(" {}", "hindsight configure --api-url http://your-api:8888".bright_white()); println!(); println!(" {}", "Configuration priority:".bright_yellow()); - println!(" 1. Environment variable (MEMORA_API_URL) - highest priority"); - println!(" 2. Config file (~/.memora/config)"); - println!(" 3. Default (http://localhost:8080)"); + println!(" 1. Environment variable (HINDSIGHT_API_URL) - highest priority"); + println!(" 2. Config file (~/.hindsight/config)"); + println!(" 3. Default (http://localhost:8888)"); println!(); } diff --git a/memora-cli/src/main.rs b/hindsight-cli/src/main.rs similarity index 98% rename from memora-cli/src/main.rs rename to hindsight-cli/src/main.rs index 44b8713622..0ce2ef60b5 100644 --- a/memora-cli/src/main.rs +++ b/hindsight-cli/src/main.rs @@ -31,8 +31,8 @@ impl From for OutputFormat { } #[derive(Parser)] -#[command(name = "memora")] -#[command(about = "Memora CLI - Semantic memory system", long_about = None)] +#[command(name = "hindsight")] +#[command(about = "Hindsight CLI - Semantic memory system", long_about = None)] #[command(version)] #[command(after_help = get_after_help())] struct Cli { @@ -52,10 +52,10 @@ fn get_after_help() -> String { let config = config::Config::load().ok(); let (api_url, source) = match &config { Some(c) => (c.api_url.as_str(), c.source.to_string()), - None => ("http://localhost:8080", "default".to_string()), + None => ("http://localhost:8888", "default".to_string()), }; format!( - "Current API URL: {} (from {})\n\nRun 'memora configure' to change the API URL.", + "Current API URL: {} (from {})\n\nRun 'hindsight configure' to change the API URL.", api_url, source ) } @@ -79,7 +79,7 @@ enum Commands { Operation(OperationCommands), /// Configure the CLI (API URL, etc.) - #[command(after_help = "Configuration priority:\n 1. Environment variable (MEMORA_API_URL) - highest priority\n 2. Config file (~/.memora/config)\n 3. Default (http://localhost:8080)")] + #[command(after_help = "Configuration priority:\n 1. Environment variable (HINDSIGHT_API_URL) - highest priority\n 2. Config file (~/.hindsight/config)\n 3. Default (http://localhost:8888)")] Configure { /// API URL to connect to (interactive prompt if not provided) #[arg(long)] @@ -295,7 +295,7 @@ enum OperationCommands { } fn main() { - if let Err(e) = run() { + if let Err(_) = run() { std::process::exit(1); } } @@ -1108,7 +1108,7 @@ fn handle_configure(api_url: Option, output_format: OutputFormat) -> Res let current_config = Config::load().ok(); if output_format == OutputFormat::Pretty { - ui::print_info("Memora CLI Configuration"); + ui::print_info("Hindsight CLI Configuration"); println!(); // Show current configuration @@ -1146,7 +1146,7 @@ fn handle_configure(api_url: Option, output_format: OutputFormat) -> Res println!(); println!(" API URL: {}", new_api_url); println!(); - println!("Note: Environment variable MEMORA_API_URL will override this setting."); + println!("Note: Environment variable HINDSIGHT_API_URL will override this setting."); } else { let result = serde_json::json!({ "api_url": new_api_url, diff --git a/memora-cli/src/main.rs.backup b/hindsight-cli/src/main.rs.backup similarity index 100% rename from memora-cli/src/main.rs.backup rename to hindsight-cli/src/main.rs.backup diff --git a/memora-cli/src/main.rs.bak10 b/hindsight-cli/src/main.rs.bak10 similarity index 100% rename from memora-cli/src/main.rs.bak10 rename to hindsight-cli/src/main.rs.bak10 diff --git a/memora-cli/src/main.rs.bak11 b/hindsight-cli/src/main.rs.bak11 similarity index 100% rename from memora-cli/src/main.rs.bak11 rename to hindsight-cli/src/main.rs.bak11 diff --git a/memora-cli/src/main.rs.bak2 b/hindsight-cli/src/main.rs.bak2 similarity index 100% rename from memora-cli/src/main.rs.bak2 rename to hindsight-cli/src/main.rs.bak2 diff --git a/memora-cli/src/main.rs.bak3 b/hindsight-cli/src/main.rs.bak3 similarity index 100% rename from memora-cli/src/main.rs.bak3 rename to hindsight-cli/src/main.rs.bak3 diff --git a/memora-cli/src/main.rs.bak4 b/hindsight-cli/src/main.rs.bak4 similarity index 100% rename from memora-cli/src/main.rs.bak4 rename to hindsight-cli/src/main.rs.bak4 diff --git a/memora-cli/src/main.rs.bak5 b/hindsight-cli/src/main.rs.bak5 similarity index 100% rename from memora-cli/src/main.rs.bak5 rename to hindsight-cli/src/main.rs.bak5 diff --git a/memora-cli/src/main.rs.bak6 b/hindsight-cli/src/main.rs.bak6 similarity index 100% rename from memora-cli/src/main.rs.bak6 rename to hindsight-cli/src/main.rs.bak6 diff --git a/memora-cli/src/main.rs.bak7 b/hindsight-cli/src/main.rs.bak7 similarity index 100% rename from memora-cli/src/main.rs.bak7 rename to hindsight-cli/src/main.rs.bak7 diff --git a/memora-cli/src/main.rs.bak8 b/hindsight-cli/src/main.rs.bak8 similarity index 100% rename from memora-cli/src/main.rs.bak8 rename to hindsight-cli/src/main.rs.bak8 diff --git a/memora-cli/src/main.rs.bak9 b/hindsight-cli/src/main.rs.bak9 similarity index 100% rename from memora-cli/src/main.rs.bak9 rename to hindsight-cli/src/main.rs.bak9 diff --git a/memora-cli/src/output.rs b/hindsight-cli/src/output.rs similarity index 67% rename from memora-cli/src/output.rs rename to hindsight-cli/src/output.rs index dedac86df6..0845f80119 100644 --- a/memora-cli/src/output.rs +++ b/hindsight-cli/src/output.rs @@ -8,17 +8,6 @@ pub enum OutputFormat { Yaml, } -impl OutputFormat { - pub fn from_str(s: &str) -> Option { - match s.to_lowercase().as_str() { - "pretty" | "default" => Some(OutputFormat::Pretty), - "json" => Some(OutputFormat::Json), - "yaml" | "yml" => Some(OutputFormat::Yaml), - _ => None, - } - } -} - pub fn print_output(data: &T, format: OutputFormat) -> Result<()> { match format { OutputFormat::Json => { diff --git a/memora-cli/src/ui.rs b/hindsight-cli/src/ui.rs similarity index 59% rename from memora-cli/src/ui.rs rename to hindsight-cli/src/ui.rs index 2e2fa30ae1..5fce627c37 100644 --- a/memora-cli/src/ui.rs +++ b/hindsight-cli/src/ui.rs @@ -1,15 +1,8 @@ -use crate::api::{Agent, AgentProfile, Fact, PersonalityTraits, SearchResponse, ThinkResponse, TraceInfo}; +use crate::api::{AgentProfile, Fact, SearchResponse, ThinkResponse, TraceInfo}; use colored::*; use indicatif::{ProgressBar, ProgressStyle}; use std::io::{self, Write}; -pub fn print_banner() { - println!("{}", "โ•”โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•—".bright_cyan()); - println!("{}", "โ•‘ MEMORA - Memory CLI โ•‘".bright_cyan()); - println!("{}", "โ•šโ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•".bright_cyan()); - println!(); -} - pub fn print_section_header(title: &str) { println!(); println!("{}", format!("โ”โ”โ” {} โ”โ”โ”", title).bright_yellow().bold()); @@ -126,42 +119,6 @@ pub fn print_trace_info(trace: &TraceInfo) { println!(); } -pub fn print_agents_table(agents: &[Agent]) { - print_section_header(&format!("Agents ({})", agents.len())); - - if agents.is_empty() { - println!("{}", " No agents found.".bright_black()); - return; - } - - // Calculate column width - let max_id_len = agents.iter().map(|a| a.agent_id.len()).max().unwrap_or(8); - let id_width = max_id_len.max(8); - - // Print header - println!(" โ”Œ{}โ”", - "โ”€".repeat(id_width + 2)); - - println!(" โ”‚ {: ProgressBar { pb } -pub fn print_stored_memory(doc_id: &str, content: &str, is_async: bool) { - if is_async { - println!("{} Queued for background processing", "โณ".bright_yellow()); - } else { - println!("{} Stored successfully", "โœ“".bright_green()); - } - println!(" Document ID: {}", doc_id.bright_cyan()); - let preview = if content.len() > 60 { - format!("{}...", &content[..57]) - } else { - content.to_string() - }; - println!(" Content: {}", preview.bright_black()); - println!(); -} - pub fn prompt_confirmation(message: &str) -> io::Result { print!("{} {} [y/N]: ", "?".bright_blue().bold(), message); io::stdout().flush()?; @@ -295,96 +236,3 @@ pub fn print_profile(profile: &AgentProfile) { println!(" {}", "(how much personality shapes opinions)".bright_black()); println!(); } - -pub fn print_personality_delta(old: &PersonalityTraits, new: &PersonalityTraits) { - println!(); - println!("{}", "โ”€โ”€โ”€ Personality Changes โ”€โ”€โ”€".bright_yellow()); - println!(); - - let traits = [ - ("Openness", old.openness, new.openness, "๐Ÿ”“", "green"), - ("Conscientiousness", old.conscientiousness, new.conscientiousness, "๐Ÿ“‹", "yellow"), - ("Extraversion", old.extraversion, new.extraversion, "๐Ÿ—ฃ๏ธ", "cyan"), - ("Agreeableness", old.agreeableness, new.agreeableness, "๐Ÿค", "magenta"), - ("Neuroticism", old.neuroticism, new.neuroticism, "๐Ÿ˜ฐ", "yellow"), - ]; - - for (name, old_value, new_value, emoji, color) in &traits { - let bar_length = 40; - let filled = (*new_value * bar_length as f32) as usize; - let empty = bar_length - filled; - - // Create bar with pattern if there's a change - let delta = new_value - old_value; - let has_change = delta.abs() >= 0.01; - - let bar = if has_change { - // Add pattern for changes (using different characters to show change) - let pattern_filled = filled.min(3); - format!("{}{}{}", - "โ–ˆ".repeat(filled.saturating_sub(pattern_filled)), - "โ–“".repeat(pattern_filled), - "โ–‘".repeat(empty) - ) - } else { - format!("{}{}", "โ–ˆ".repeat(filled), "โ–‘".repeat(empty)) - }; - - let colored_bar = match *color { - "green" => bar.bright_green(), - "yellow" => bar.bright_yellow(), - "cyan" => bar.bright_cyan(), - "magenta" => bar.bright_magenta(), - _ => bar.bright_white(), - }; - - let delta_str = if has_change { - format!(" โ†’ {:.0}%", new_value * 100.0) - } else { - format!(" {:.0}%", new_value * 100.0) - }; - - println!(" {} {:<20} [{}]{}", - emoji, - name, - colored_bar, - delta_str - ); - } - - println!(); - println!("{}", "Bias Strength:".bright_yellow()); - let old_bias = old.bias_strength; - let new_bias = new.bias_strength; - let bar_length = 40; - let filled = (new_bias * bar_length as f32) as usize; - let empty = bar_length - filled; - - let delta = new_bias - old_bias; - let has_change = delta.abs() >= 0.01; - - let bar = if has_change { - let pattern_filled = filled.min(3); - format!("{}{}{}", - "โ–ˆ".repeat(filled.saturating_sub(pattern_filled)), - "โ–“".repeat(pattern_filled), - "โ–‘".repeat(empty) - ) - } else { - format!("{}{}", "โ–ˆ".repeat(filled), "โ–‘".repeat(empty)) - }; - - let delta_str = if has_change { - format!(" โ†’ {:.0}%", new_bias * 100.0) - } else { - format!(" {:.0}%", new_bias * 100.0) - }; - - println!(" ๐Ÿ’ช {:<20} [{}]{}", - "Personality Influence", - bar.bright_green(), - delta_str - ); - println!(" {}", "(how much personality shapes opinions)".bright_black()); - println!(); -} diff --git a/memora-clients/.gitignore b/hindsight-clients/.gitignore similarity index 100% rename from memora-clients/.gitignore rename to hindsight-clients/.gitignore diff --git a/memora-clients/python/.openapi-generator-ignore b/hindsight-clients/python/.openapi-generator-ignore similarity index 100% rename from memora-clients/python/.openapi-generator-ignore rename to hindsight-clients/python/.openapi-generator-ignore diff --git a/memora-clients/python/.openapi-generator/FILES b/hindsight-clients/python/.openapi-generator/FILES similarity index 100% rename from memora-clients/python/.openapi-generator/FILES rename to hindsight-clients/python/.openapi-generator/FILES diff --git a/memora-clients/python/.openapi-generator/VERSION b/hindsight-clients/python/.openapi-generator/VERSION similarity index 100% rename from memora-clients/python/.openapi-generator/VERSION rename to hindsight-clients/python/.openapi-generator/VERSION diff --git a/memora-clients/python/README.md b/hindsight-clients/python/README.md similarity index 92% rename from memora-clients/python/README.md rename to hindsight-clients/python/README.md index 93ab2a3f65..84e6eca6fe 100644 --- a/memora-clients/python/README.md +++ b/hindsight-clients/python/README.md @@ -14,7 +14,7 @@ pip install memora-client from memora_client import Memora # Initialize client -client = Memora(base_url="http://localhost:8000") +client = Memora(base_url="http://localhost:8888") # Store a memory client.store(agent_id="alice", content="Alice loves artificial intelligence") @@ -95,7 +95,7 @@ memora-client/ โ”‚ โ””โ”€โ”€ tests/ โ”‚ โ””โ”€โ”€ test_main_operations.py โ”‚ -โ””โ”€โ”€ memora_client_api/ # Auto-generated from OpenAPI spec +โ””โ”€โ”€ hindsight_client_api/ # Auto-generated from OpenAPI spec โ”œโ”€โ”€ api/ # Full API operations โ”œโ”€โ”€ models/ # Request/response models โ””โ”€โ”€ ... @@ -106,8 +106,8 @@ memora-client/ Run integration tests (requires running Memora API server): ```bash -# Set API URL (optional, defaults to http://localhost:8000) -export MEMORA_API_URL=http://localhost:8000 +# Set API URL (optional, defaults to http://localhost:8888) +export MEMORA_API_URL=http://localhost:8888 # Run tests pytest memora_client/tests/test_main_operations.py -v diff --git a/memora-clients/python/memora_client/__init__.py b/hindsight-clients/python/hindsight_client/__init__.py similarity index 56% rename from memora-clients/python/memora_client/__init__.py rename to hindsight-clients/python/hindsight_client/__init__.py index e069deaacd..ec3d211526 100644 --- a/memora-clients/python/memora_client/__init__.py +++ b/hindsight-clients/python/hindsight_client/__init__.py @@ -1,14 +1,14 @@ """ -Memora Client - Clean, pythonic wrapper for the Memora API. +Hindsight Client - Clean, pythonic wrapper for the Hindsight API. -This package provides a high-level interface for common Memora operations. +This package provides a high-level interface for common Hindsight operations. For advanced use cases, use the auto-generated API client directly. Example: ```python - from memora_client import Memora + from hindsight_client import Hindsight - client = Memora(base_url="http://localhost:8000") + client = Hindsight(base_url="http://localhost:8888") # Store a memory client.put(agent_id="alice", content="Alice loves AI") @@ -21,6 +21,6 @@ ``` """ -from .memora_client import Memora +from .hindsight_client import Hindsight -__all__ = ["Memora"] +__all__ = ["Hindsight"] diff --git a/memora-clients/python/memora_client/memora_client.py b/hindsight-clients/python/hindsight_client/hindsight_client.py similarity index 94% rename from memora-clients/python/memora_client/memora_client.py rename to hindsight-clients/python/hindsight_client/hindsight_client.py index 4481c56896..63b65cf119 100644 --- a/memora-clients/python/memora_client/memora_client.py +++ b/hindsight-clients/python/hindsight_client/hindsight_client.py @@ -1,5 +1,5 @@ """ -Clean, pythonic wrapper for the Memora API client. +Clean, pythonic wrapper for the Hindsight API client. This file is MAINTAINED and NOT auto-generated. It provides a high-level, easy-to-use interface on top of the auto-generated OpenAPI client. @@ -9,9 +9,9 @@ from typing import Optional, List, Dict, Any from datetime import datetime -import memora_client_api -from memora_client_api.api import memory_operations_api, reasoning_api, agent_management_api -from memora_client_api.models import ( +import hindsight_client_api +from hindsight_client_api.api import memory_operations_api, reasoning_api, agent_management_api +from hindsight_client_api.models import ( search_request, batch_put_request, memory_item, @@ -30,15 +30,15 @@ def _run_async(coro): return loop.run_until_complete(coro) -class Memora: +class Hindsight: """ - High-level, easy-to-use Memora API client. + High-level, easy-to-use Hindsight API client. Example: ```python - from memora_client import Memora + from hindsight_client import Hindsight - client = Memora(base_url="http://localhost:8000") + client = Hindsight(base_url="http://localhost:8888") # Store a memory client.put(agent_id="alice", content="Alice loves AI") @@ -53,14 +53,14 @@ class Memora: def __init__(self, base_url: str, timeout: float = 30.0): """ - Initialize the Memora client. + Initialize the Hindsight client. Args: - base_url: The base URL of the Memora API server + base_url: The base URL of the Hindsight API server timeout: Request timeout in seconds (default: 30.0) """ - config = memora_client_api.Configuration(host=base_url) - self._api_client = memora_client_api.ApiClient(config) + config = hindsight_client_api.Configuration(host=base_url) + self._api_client = hindsight_client_api.ApiClient(config) self._memory_api = memory_operations_api.MemoryOperationsApi(self._api_client) self._reasoning_api = reasoning_api.ReasoningApi(self._api_client) self._agent_api = agent_management_api.AgentManagementApi(self._api_client) @@ -268,7 +268,7 @@ def create_agent( background: Optional[str] = None, ) -> Dict[str, Any]: """Create or update an agent.""" - from memora_client_api.models import create_agent_request + from hindsight_client_api.models import create_agent_request request_obj = create_agent_request.CreateAgentRequest( name=name, @@ -406,4 +406,4 @@ async def athink( # Alias for backward compatibility -MemoraClient = Memora +HindsightClient = Hindsight diff --git a/hindsight-clients/python/hindsight_client_api/__init__.py b/hindsight-clients/python/hindsight_client_api/__init__.py new file mode 100644 index 0000000000..30c3c6b92d --- /dev/null +++ b/hindsight-clients/python/hindsight_client_api/__init__.py @@ -0,0 +1,108 @@ +# coding: utf-8 + +# flake8: noqa + +""" + Agent Memory API + + A temporal-semantic memory system for AI agents that stores, retrieves, and reasons over memories. ## Features * **Batch Memory Storage**: Store multiple memories efficiently with automatic fact extraction * **Semantic Search**: Find relevant memories using natural language queries * **Fact Type Filtering**: Search across world facts, agent actions, and opinions separately * **Think Endpoint**: Generate contextual answers based on agent identity and memories * **Graph Visualization**: Interactive memory graph visualization * **Document Tracking**: Track and manage memory documents with upsert support ## Architecture The system uses: - **Temporal Links**: Connect memories that are close in time - **Semantic Links**: Connect semantically similar memories - **Entity Links**: Connect memories that mention the same entities - **Spreading Activation**: Intelligent traversal for memory retrieval + + The version of the OpenAPI document: 1.0.0 + Generated by OpenAPI Generator (https://openapi-generator.tech) + + Do not edit the class manually. +""" # noqa: E501 + + +__version__ = "0.0.7" + +# Define package exports +__all__ = [ + "AgentManagementApi", + "DocumentsApi", + "MemoryOperationsApi", + "ReasoningApi", + "VisualizationApi", + "ApiResponse", + "ApiClient", + "Configuration", + "OpenApiException", + "ApiTypeError", + "ApiValueError", + "ApiKeyError", + "ApiAttributeError", + "ApiException", + "AddBackgroundRequest", + "AgentListItem", + "AgentListResponse", + "AgentProfileResponse", + "BackgroundResponse", + "BatchPutAsyncResponse", + "BatchPutRequest", + "BatchPutResponse", + "CreateAgentRequest", + "DeleteResponse", + "DocumentResponse", + "GraphDataResponse", + "HTTPValidationError", + "ListDocumentsResponse", + "ListMemoryUnitsResponse", + "MemoryItem", + "PersonalityTraits", + "SearchRequest", + "SearchResponse", + "SearchResult", + "ThinkFact", + "ThinkRequest", + "ThinkResponse", + "UpdatePersonalityRequest", + "ValidationError", + "ValidationErrorLocInner", +] + +# import apis into sdk package +from hindsight_client_api.api.agent_management_api import AgentManagementApi as AgentManagementApi +from hindsight_client_api.api.documents_api import DocumentsApi as DocumentsApi +from hindsight_client_api.api.memory_operations_api import MemoryOperationsApi as MemoryOperationsApi +from hindsight_client_api.api.reasoning_api import ReasoningApi as ReasoningApi +from hindsight_client_api.api.visualization_api import VisualizationApi as VisualizationApi + +# import ApiClient +from hindsight_client_api.api_response import ApiResponse as ApiResponse +from hindsight_client_api.api_client import ApiClient as ApiClient +from hindsight_client_api.configuration import Configuration as Configuration +from hindsight_client_api.exceptions import OpenApiException as OpenApiException +from hindsight_client_api.exceptions import ApiTypeError as ApiTypeError +from hindsight_client_api.exceptions import ApiValueError as ApiValueError +from hindsight_client_api.exceptions import ApiKeyError as ApiKeyError +from hindsight_client_api.exceptions import ApiAttributeError as ApiAttributeError +from hindsight_client_api.exceptions import ApiException as ApiException + +# import models into sdk package +from hindsight_client_api.models.add_background_request import AddBackgroundRequest as AddBackgroundRequest +from hindsight_client_api.models.agent_list_item import AgentListItem as AgentListItem +from hindsight_client_api.models.agent_list_response import AgentListResponse as AgentListResponse +from hindsight_client_api.models.agent_profile_response import AgentProfileResponse as AgentProfileResponse +from hindsight_client_api.models.background_response import BackgroundResponse as BackgroundResponse +from hindsight_client_api.models.batch_put_async_response import BatchPutAsyncResponse as BatchPutAsyncResponse +from hindsight_client_api.models.batch_put_request import BatchPutRequest as BatchPutRequest +from hindsight_client_api.models.batch_put_response import BatchPutResponse as BatchPutResponse +from hindsight_client_api.models.create_agent_request import CreateAgentRequest as CreateAgentRequest +from hindsight_client_api.models.delete_response import DeleteResponse as DeleteResponse +from hindsight_client_api.models.document_response import DocumentResponse as DocumentResponse +from hindsight_client_api.models.graph_data_response import GraphDataResponse as GraphDataResponse +from hindsight_client_api.models.http_validation_error import HTTPValidationError as HTTPValidationError +from hindsight_client_api.models.list_documents_response import ListDocumentsResponse as ListDocumentsResponse +from hindsight_client_api.models.list_memory_units_response import ListMemoryUnitsResponse as ListMemoryUnitsResponse +from hindsight_client_api.models.memory_item import MemoryItem as MemoryItem +from hindsight_client_api.models.personality_traits import PersonalityTraits as PersonalityTraits +from hindsight_client_api.models.search_request import SearchRequest as SearchRequest +from hindsight_client_api.models.search_response import SearchResponse as SearchResponse +from hindsight_client_api.models.search_result import SearchResult as SearchResult +from hindsight_client_api.models.think_fact import ThinkFact as ThinkFact +from hindsight_client_api.models.think_request import ThinkRequest as ThinkRequest +from hindsight_client_api.models.think_response import ThinkResponse as ThinkResponse +from hindsight_client_api.models.update_personality_request import UpdatePersonalityRequest as UpdatePersonalityRequest +from hindsight_client_api.models.validation_error import ValidationError as ValidationError +from hindsight_client_api.models.validation_error_loc_inner import ValidationErrorLocInner as ValidationErrorLocInner + diff --git a/hindsight-clients/python/hindsight_client_api/api/__init__.py b/hindsight-clients/python/hindsight_client_api/api/__init__.py new file mode 100644 index 0000000000..eaac286a74 --- /dev/null +++ b/hindsight-clients/python/hindsight_client_api/api/__init__.py @@ -0,0 +1,9 @@ +# flake8: noqa + +# import apis into api package +from hindsight_client_api.api.agent_management_api import AgentManagementApi +from hindsight_client_api.api.documents_api import DocumentsApi +from hindsight_client_api.api.memory_operations_api import MemoryOperationsApi +from hindsight_client_api.api.reasoning_api import ReasoningApi +from hindsight_client_api.api.visualization_api import VisualizationApi + diff --git a/memora-clients/python/memora_client_api/api/agent_management_api.py b/hindsight-clients/python/hindsight_client_api/api/agent_management_api.py similarity index 99% rename from memora-clients/python/memora_client_api/api/agent_management_api.py rename to hindsight-clients/python/hindsight_client_api/api/agent_management_api.py index 1142207162..fb30517690 100644 --- a/memora-clients/python/memora_client_api/api/agent_management_api.py +++ b/hindsight-clients/python/hindsight_client_api/api/agent_management_api.py @@ -19,17 +19,17 @@ from pydantic import Field, StrictStr from typing import Any, Optional from typing_extensions import Annotated -from memora_client_api.models.add_background_request import AddBackgroundRequest -from memora_client_api.models.agent_list_response import AgentListResponse -from memora_client_api.models.agent_profile_response import AgentProfileResponse -from memora_client_api.models.background_response import BackgroundResponse -from memora_client_api.models.create_agent_request import CreateAgentRequest -from memora_client_api.models.delete_response import DeleteResponse -from memora_client_api.models.update_personality_request import UpdatePersonalityRequest - -from memora_client_api.api_client import ApiClient, RequestSerialized -from memora_client_api.api_response import ApiResponse -from memora_client_api.rest import RESTResponseType +from hindsight_client_api.models.add_background_request import AddBackgroundRequest +from hindsight_client_api.models.agent_list_response import AgentListResponse +from hindsight_client_api.models.agent_profile_response import AgentProfileResponse +from hindsight_client_api.models.background_response import BackgroundResponse +from hindsight_client_api.models.create_agent_request import CreateAgentRequest +from hindsight_client_api.models.delete_response import DeleteResponse +from hindsight_client_api.models.update_personality_request import UpdatePersonalityRequest + +from hindsight_client_api.api_client import ApiClient, RequestSerialized +from hindsight_client_api.api_response import ApiResponse +from hindsight_client_api.rest import RESTResponseType class AgentManagementApi: diff --git a/memora-clients/python/memora_client_api/api/documents_api.py b/hindsight-clients/python/hindsight_client_api/api/documents_api.py similarity index 99% rename from memora-clients/python/memora_client_api/api/documents_api.py rename to hindsight-clients/python/hindsight_client_api/api/documents_api.py index 77ca3a6e86..83da02441e 100644 --- a/memora-clients/python/memora_client_api/api/documents_api.py +++ b/hindsight-clients/python/hindsight_client_api/api/documents_api.py @@ -18,12 +18,12 @@ from pydantic import StrictInt, StrictStr from typing import Any, Optional -from memora_client_api.models.document_response import DocumentResponse -from memora_client_api.models.list_documents_response import ListDocumentsResponse +from hindsight_client_api.models.document_response import DocumentResponse +from hindsight_client_api.models.list_documents_response import ListDocumentsResponse -from memora_client_api.api_client import ApiClient, RequestSerialized -from memora_client_api.api_response import ApiResponse -from memora_client_api.rest import RESTResponseType +from hindsight_client_api.api_client import ApiClient, RequestSerialized +from hindsight_client_api.api_response import ApiResponse +from hindsight_client_api.rest import RESTResponseType class DocumentsApi: diff --git a/memora-clients/python/memora_client_api/api/memory_operations_api.py b/hindsight-clients/python/hindsight_client_api/api/memory_operations_api.py similarity index 99% rename from memora-clients/python/memora_client_api/api/memory_operations_api.py rename to hindsight-clients/python/hindsight_client_api/api/memory_operations_api.py index 6cb54766c6..de451760c9 100644 --- a/memora-clients/python/memora_client_api/api/memory_operations_api.py +++ b/hindsight-clients/python/hindsight_client_api/api/memory_operations_api.py @@ -18,16 +18,16 @@ from pydantic import StrictInt, StrictStr from typing import Any, Optional -from memora_client_api.models.batch_put_async_response import BatchPutAsyncResponse -from memora_client_api.models.batch_put_request import BatchPutRequest -from memora_client_api.models.batch_put_response import BatchPutResponse -from memora_client_api.models.list_memory_units_response import ListMemoryUnitsResponse -from memora_client_api.models.search_request import SearchRequest -from memora_client_api.models.search_response import SearchResponse - -from memora_client_api.api_client import ApiClient, RequestSerialized -from memora_client_api.api_response import ApiResponse -from memora_client_api.rest import RESTResponseType +from hindsight_client_api.models.batch_put_async_response import BatchPutAsyncResponse +from hindsight_client_api.models.batch_put_request import BatchPutRequest +from hindsight_client_api.models.batch_put_response import BatchPutResponse +from hindsight_client_api.models.list_memory_units_response import ListMemoryUnitsResponse +from hindsight_client_api.models.search_request import SearchRequest +from hindsight_client_api.models.search_response import SearchResponse + +from hindsight_client_api.api_client import ApiClient, RequestSerialized +from hindsight_client_api.api_response import ApiResponse +from hindsight_client_api.rest import RESTResponseType class MemoryOperationsApi: diff --git a/memora-clients/python/memora_client_api/api/reasoning_api.py b/hindsight-clients/python/hindsight_client_api/api/reasoning_api.py similarity index 97% rename from memora-clients/python/memora_client_api/api/reasoning_api.py rename to hindsight-clients/python/hindsight_client_api/api/reasoning_api.py index 110d708722..7767c320fd 100644 --- a/memora-clients/python/memora_client_api/api/reasoning_api.py +++ b/hindsight-clients/python/hindsight_client_api/api/reasoning_api.py @@ -17,12 +17,12 @@ from typing_extensions import Annotated from pydantic import StrictStr -from memora_client_api.models.think_request import ThinkRequest -from memora_client_api.models.think_response import ThinkResponse +from hindsight_client_api.models.think_request import ThinkRequest +from hindsight_client_api.models.think_response import ThinkResponse -from memora_client_api.api_client import ApiClient, RequestSerialized -from memora_client_api.api_response import ApiResponse -from memora_client_api.rest import RESTResponseType +from hindsight_client_api.api_client import ApiClient, RequestSerialized +from hindsight_client_api.api_response import ApiResponse +from hindsight_client_api.rest import RESTResponseType class ReasoningApi: diff --git a/memora-clients/python/memora_client_api/api/visualization_api.py b/hindsight-clients/python/hindsight_client_api/api/visualization_api.py similarity index 97% rename from memora-clients/python/memora_client_api/api/visualization_api.py rename to hindsight-clients/python/hindsight_client_api/api/visualization_api.py index 89c0a20faf..1b4ee94c01 100644 --- a/memora-clients/python/memora_client_api/api/visualization_api.py +++ b/hindsight-clients/python/hindsight_client_api/api/visualization_api.py @@ -18,11 +18,11 @@ from pydantic import StrictStr from typing import Optional -from memora_client_api.models.graph_data_response import GraphDataResponse +from hindsight_client_api.models.graph_data_response import GraphDataResponse -from memora_client_api.api_client import ApiClient, RequestSerialized -from memora_client_api.api_response import ApiResponse -from memora_client_api.rest import RESTResponseType +from hindsight_client_api.api_client import ApiClient, RequestSerialized +from hindsight_client_api.api_response import ApiResponse +from hindsight_client_api.rest import RESTResponseType class VisualizationApi: diff --git a/memora-clients/python/memora_client_api/api_client.py b/hindsight-clients/python/hindsight_client_api/api_client.py similarity index 98% rename from memora-clients/python/memora_client_api/api_client.py rename to hindsight-clients/python/hindsight_client_api/api_client.py index 42c6a20e4a..8a6dd1346c 100644 --- a/memora-clients/python/memora_client_api/api_client.py +++ b/hindsight-clients/python/hindsight_client_api/api_client.py @@ -27,11 +27,11 @@ from typing import Tuple, Optional, List, Dict, Union from pydantic import SecretStr -from memora_client_api.configuration import Configuration -from memora_client_api.api_response import ApiResponse, T as ApiResponseT -import memora_client_api.models -from memora_client_api import rest -from memora_client_api.exceptions import ( +from hindsight_client_api.configuration import Configuration +from hindsight_client_api.api_response import ApiResponse, T as ApiResponseT +import hindsight_client_api.models +from hindsight_client_api import rest +from hindsight_client_api.exceptions import ( ApiValueError, ApiException, BadRequestException, @@ -459,7 +459,7 @@ def __deserialize(self, data, klass): if klass in self.NATIVE_TYPES_MAPPING: klass = self.NATIVE_TYPES_MAPPING[klass] else: - klass = getattr(memora_client_api.models, klass) + klass = getattr(hindsight_client_api.models, klass) if klass in self.PRIMITIVE_TYPES: return self.__deserialize_primitive(data, klass) diff --git a/memora-clients/python/memora_client_api/api_response.py b/hindsight-clients/python/hindsight_client_api/api_response.py similarity index 100% rename from memora-clients/python/memora_client_api/api_response.py rename to hindsight-clients/python/hindsight_client_api/api_response.py diff --git a/memora-clients/python/memora_client_api/configuration.py b/hindsight-clients/python/hindsight_client_api/configuration.py similarity index 99% rename from memora-clients/python/memora_client_api/configuration.py rename to hindsight-clients/python/hindsight_client_api/configuration.py index f57ab79018..6fd3dae547 100644 --- a/memora-clients/python/memora_client_api/configuration.py +++ b/hindsight-clients/python/hindsight_client_api/configuration.py @@ -234,7 +234,7 @@ def __init__( self.logger = {} """Logging Settings """ - self.logger["package_logger"] = logging.getLogger("memora_client_api") + self.logger["package_logger"] = logging.getLogger("hindsight_client_api") self.logger["urllib3_logger"] = logging.getLogger("urllib3") self.logger_format = '%(asctime)s %(levelname)s %(message)s' """Log format diff --git a/memora-clients/python/memora_client_api/docs/AddBackgroundRequest.md b/hindsight-clients/python/hindsight_client_api/docs/AddBackgroundRequest.md similarity index 93% rename from memora-clients/python/memora_client_api/docs/AddBackgroundRequest.md rename to hindsight-clients/python/hindsight_client_api/docs/AddBackgroundRequest.md index 7efc61e7e4..7f7a562f9e 100644 --- a/memora-clients/python/memora_client_api/docs/AddBackgroundRequest.md +++ b/hindsight-clients/python/hindsight_client_api/docs/AddBackgroundRequest.md @@ -12,7 +12,7 @@ Name | Type | Description | Notes ## Example ```python -from memora_client_api.models.add_background_request import AddBackgroundRequest +from hindsight_client_api.models.add_background_request import AddBackgroundRequest # TODO update the JSON string below json = "{}" diff --git a/memora-clients/python/memora_client_api/docs/AgentListItem.md b/hindsight-clients/python/hindsight_client_api/docs/AgentListItem.md similarity index 93% rename from memora-clients/python/memora_client_api/docs/AgentListItem.md rename to hindsight-clients/python/hindsight_client_api/docs/AgentListItem.md index 3f024fc332..282f49cd77 100644 --- a/memora-clients/python/memora_client_api/docs/AgentListItem.md +++ b/hindsight-clients/python/hindsight_client_api/docs/AgentListItem.md @@ -16,7 +16,7 @@ Name | Type | Description | Notes ## Example ```python -from memora_client_api.models.agent_list_item import AgentListItem +from hindsight_client_api.models.agent_list_item import AgentListItem # TODO update the JSON string below json = "{}" diff --git a/memora-clients/python/memora_client_api/docs/AgentListResponse.md b/hindsight-clients/python/hindsight_client_api/docs/AgentListResponse.md similarity index 92% rename from memora-clients/python/memora_client_api/docs/AgentListResponse.md rename to hindsight-clients/python/hindsight_client_api/docs/AgentListResponse.md index f5f25b2f19..c2cca133e2 100644 --- a/memora-clients/python/memora_client_api/docs/AgentListResponse.md +++ b/hindsight-clients/python/hindsight_client_api/docs/AgentListResponse.md @@ -11,7 +11,7 @@ Name | Type | Description | Notes ## Example ```python -from memora_client_api.models.agent_list_response import AgentListResponse +from hindsight_client_api.models.agent_list_response import AgentListResponse # TODO update the JSON string below json = "{}" diff --git a/memora-clients/python/memora_client_api/docs/AgentManagementApi.md b/hindsight-clients/python/hindsight_client_api/docs/AgentManagementApi.md similarity index 81% rename from memora-clients/python/memora_client_api/docs/AgentManagementApi.md rename to hindsight-clients/python/hindsight_client_api/docs/AgentManagementApi.md index 13cc7e9b04..69228a4980 100644 --- a/memora-clients/python/memora_client_api/docs/AgentManagementApi.md +++ b/hindsight-clients/python/hindsight_client_api/docs/AgentManagementApi.md @@ -1,4 +1,4 @@ -# memora_client_api.AgentManagementApi +# hindsight_client_api.AgentManagementApi All URIs are relative to *http://localhost* @@ -24,25 +24,25 @@ Add new background information or merge with existing. LLM intelligently resolve ```python -import memora_client_api -from memora_client_api.models.add_background_request import AddBackgroundRequest -from memora_client_api.models.background_response import BackgroundResponse -from memora_client_api.rest import ApiException +import hindsight_client_api +from hindsight_client_api.models.add_background_request import AddBackgroundRequest +from hindsight_client_api.models.background_response import BackgroundResponse +from hindsight_client_api.rest import ApiException from pprint import pprint # Defining the host is optional and defaults to http://localhost # See configuration.py for a list of all supported configuration parameters. -configuration = memora_client_api.Configuration( +configuration = hindsight_client_api.Configuration( host = "http://localhost" ) # Enter a context with an instance of the API client -async with memora_client_api.ApiClient(configuration) as api_client: +async with hindsight_client_api.ApiClient(configuration) as api_client: # Create an instance of the API class - api_instance = memora_client_api.AgentManagementApi(api_client) + api_instance = hindsight_client_api.AgentManagementApi(api_client) agent_id = 'agent_id_example' # str | - add_background_request = memora_client_api.AddBackgroundRequest() # AddBackgroundRequest | + add_background_request = hindsight_client_api.AddBackgroundRequest() # AddBackgroundRequest | try: # Add/merge agent background @@ -96,22 +96,22 @@ Delete memory units for an agent. Optionally filter by fact_type (world, agent, ```python -import memora_client_api -from memora_client_api.models.delete_response import DeleteResponse -from memora_client_api.rest import ApiException +import hindsight_client_api +from hindsight_client_api.models.delete_response import DeleteResponse +from hindsight_client_api.rest import ApiException from pprint import pprint # Defining the host is optional and defaults to http://localhost # See configuration.py for a list of all supported configuration parameters. -configuration = memora_client_api.Configuration( +configuration = hindsight_client_api.Configuration( host = "http://localhost" ) # Enter a context with an instance of the API client -async with memora_client_api.ApiClient(configuration) as api_client: +async with hindsight_client_api.ApiClient(configuration) as api_client: # Create an instance of the API class - api_instance = memora_client_api.AgentManagementApi(api_client) + api_instance = hindsight_client_api.AgentManagementApi(api_client) agent_id = 'agent_id_example' # str | fact_type = 'fact_type_example' # str | Optional fact type filter (world, agent, opinion) (optional) @@ -167,25 +167,25 @@ Create a new agent or update existing agent with personality and background. Aut ```python -import memora_client_api -from memora_client_api.models.agent_profile_response import AgentProfileResponse -from memora_client_api.models.create_agent_request import CreateAgentRequest -from memora_client_api.rest import ApiException +import hindsight_client_api +from hindsight_client_api.models.agent_profile_response import AgentProfileResponse +from hindsight_client_api.models.create_agent_request import CreateAgentRequest +from hindsight_client_api.rest import ApiException from pprint import pprint # Defining the host is optional and defaults to http://localhost # See configuration.py for a list of all supported configuration parameters. -configuration = memora_client_api.Configuration( +configuration = hindsight_client_api.Configuration( host = "http://localhost" ) # Enter a context with an instance of the API client -async with memora_client_api.ApiClient(configuration) as api_client: +async with hindsight_client_api.ApiClient(configuration) as api_client: # Create an instance of the API class - api_instance = memora_client_api.AgentManagementApi(api_client) + api_instance = hindsight_client_api.AgentManagementApi(api_client) agent_id = 'agent_id_example' # str | - create_agent_request = memora_client_api.CreateAgentRequest() # CreateAgentRequest | + create_agent_request = hindsight_client_api.CreateAgentRequest() # CreateAgentRequest | try: # Create or update agent @@ -239,22 +239,22 @@ Get personality traits and background for an agent. Auto-creates agent with defa ```python -import memora_client_api -from memora_client_api.models.agent_profile_response import AgentProfileResponse -from memora_client_api.rest import ApiException +import hindsight_client_api +from hindsight_client_api.models.agent_profile_response import AgentProfileResponse +from hindsight_client_api.rest import ApiException from pprint import pprint # Defining the host is optional and defaults to http://localhost # See configuration.py for a list of all supported configuration parameters. -configuration = memora_client_api.Configuration( +configuration = hindsight_client_api.Configuration( host = "http://localhost" ) # Enter a context with an instance of the API client -async with memora_client_api.ApiClient(configuration) as api_client: +async with hindsight_client_api.ApiClient(configuration) as api_client: # Create an instance of the API class - api_instance = memora_client_api.AgentManagementApi(api_client) + api_instance = hindsight_client_api.AgentManagementApi(api_client) agent_id = 'agent_id_example' # str | try: @@ -308,21 +308,21 @@ Get statistics about nodes and links for a specific agent ```python -import memora_client_api -from memora_client_api.rest import ApiException +import hindsight_client_api +from hindsight_client_api.rest import ApiException from pprint import pprint # Defining the host is optional and defaults to http://localhost # See configuration.py for a list of all supported configuration parameters. -configuration = memora_client_api.Configuration( +configuration = hindsight_client_api.Configuration( host = "http://localhost" ) # Enter a context with an instance of the API client -async with memora_client_api.ApiClient(configuration) as api_client: +async with hindsight_client_api.ApiClient(configuration) as api_client: # Create an instance of the API class - api_instance = memora_client_api.AgentManagementApi(api_client) + api_instance = hindsight_client_api.AgentManagementApi(api_client) agent_id = 'agent_id_example' # str | try: @@ -376,22 +376,22 @@ Get a list of all agents with their profiles ```python -import memora_client_api -from memora_client_api.models.agent_list_response import AgentListResponse -from memora_client_api.rest import ApiException +import hindsight_client_api +from hindsight_client_api.models.agent_list_response import AgentListResponse +from hindsight_client_api.rest import ApiException from pprint import pprint # Defining the host is optional and defaults to http://localhost # See configuration.py for a list of all supported configuration parameters. -configuration = memora_client_api.Configuration( +configuration = hindsight_client_api.Configuration( host = "http://localhost" ) # Enter a context with an instance of the API client -async with memora_client_api.ApiClient(configuration) as api_client: +async with hindsight_client_api.ApiClient(configuration) as api_client: # Create an instance of the API class - api_instance = memora_client_api.AgentManagementApi(api_client) + api_instance = hindsight_client_api.AgentManagementApi(api_client) try: # List all agents @@ -440,25 +440,25 @@ Update agent's Big Five personality traits and bias strength ```python -import memora_client_api -from memora_client_api.models.agent_profile_response import AgentProfileResponse -from memora_client_api.models.update_personality_request import UpdatePersonalityRequest -from memora_client_api.rest import ApiException +import hindsight_client_api +from hindsight_client_api.models.agent_profile_response import AgentProfileResponse +from hindsight_client_api.models.update_personality_request import UpdatePersonalityRequest +from hindsight_client_api.rest import ApiException from pprint import pprint # Defining the host is optional and defaults to http://localhost # See configuration.py for a list of all supported configuration parameters. -configuration = memora_client_api.Configuration( +configuration = hindsight_client_api.Configuration( host = "http://localhost" ) # Enter a context with an instance of the API client -async with memora_client_api.ApiClient(configuration) as api_client: +async with hindsight_client_api.ApiClient(configuration) as api_client: # Create an instance of the API class - api_instance = memora_client_api.AgentManagementApi(api_client) + api_instance = hindsight_client_api.AgentManagementApi(api_client) agent_id = 'agent_id_example' # str | - update_personality_request = memora_client_api.UpdatePersonalityRequest() # UpdatePersonalityRequest | + update_personality_request = hindsight_client_api.UpdatePersonalityRequest() # UpdatePersonalityRequest | try: # Update agent personality diff --git a/memora-clients/python/memora_client_api/docs/AgentProfileResponse.md b/hindsight-clients/python/hindsight_client_api/docs/AgentProfileResponse.md similarity index 92% rename from memora-clients/python/memora_client_api/docs/AgentProfileResponse.md rename to hindsight-clients/python/hindsight_client_api/docs/AgentProfileResponse.md index 4caee199d5..833f75fb01 100644 --- a/memora-clients/python/memora_client_api/docs/AgentProfileResponse.md +++ b/hindsight-clients/python/hindsight_client_api/docs/AgentProfileResponse.md @@ -14,7 +14,7 @@ Name | Type | Description | Notes ## Example ```python -from memora_client_api.models.agent_profile_response import AgentProfileResponse +from hindsight_client_api.models.agent_profile_response import AgentProfileResponse # TODO update the JSON string below json = "{}" diff --git a/memora-clients/python/memora_client_api/docs/BackgroundResponse.md b/hindsight-clients/python/hindsight_client_api/docs/BackgroundResponse.md similarity index 92% rename from memora-clients/python/memora_client_api/docs/BackgroundResponse.md rename to hindsight-clients/python/hindsight_client_api/docs/BackgroundResponse.md index 3e9947b8e6..03bf0e50e4 100644 --- a/memora-clients/python/memora_client_api/docs/BackgroundResponse.md +++ b/hindsight-clients/python/hindsight_client_api/docs/BackgroundResponse.md @@ -12,7 +12,7 @@ Name | Type | Description | Notes ## Example ```python -from memora_client_api.models.background_response import BackgroundResponse +from hindsight_client_api.models.background_response import BackgroundResponse # TODO update the JSON string below json = "{}" diff --git a/memora-clients/python/memora_client_api/docs/BatchPutAsyncResponse.md b/hindsight-clients/python/hindsight_client_api/docs/BatchPutAsyncResponse.md similarity index 92% rename from memora-clients/python/memora_client_api/docs/BatchPutAsyncResponse.md rename to hindsight-clients/python/hindsight_client_api/docs/BatchPutAsyncResponse.md index d19c92e5a7..2c06f52220 100644 --- a/memora-clients/python/memora_client_api/docs/BatchPutAsyncResponse.md +++ b/hindsight-clients/python/hindsight_client_api/docs/BatchPutAsyncResponse.md @@ -16,7 +16,7 @@ Name | Type | Description | Notes ## Example ```python -from memora_client_api.models.batch_put_async_response import BatchPutAsyncResponse +from hindsight_client_api.models.batch_put_async_response import BatchPutAsyncResponse # TODO update the JSON string below json = "{}" diff --git a/memora-clients/python/memora_client_api/docs/BatchPutRequest.md b/hindsight-clients/python/hindsight_client_api/docs/BatchPutRequest.md similarity index 92% rename from memora-clients/python/memora_client_api/docs/BatchPutRequest.md rename to hindsight-clients/python/hindsight_client_api/docs/BatchPutRequest.md index ee24961b19..e3814c2a78 100644 --- a/memora-clients/python/memora_client_api/docs/BatchPutRequest.md +++ b/hindsight-clients/python/hindsight_client_api/docs/BatchPutRequest.md @@ -12,7 +12,7 @@ Name | Type | Description | Notes ## Example ```python -from memora_client_api.models.batch_put_request import BatchPutRequest +from hindsight_client_api.models.batch_put_request import BatchPutRequest # TODO update the JSON string below json = "{}" diff --git a/memora-clients/python/memora_client_api/docs/BatchPutResponse.md b/hindsight-clients/python/hindsight_client_api/docs/BatchPutResponse.md similarity index 93% rename from memora-clients/python/memora_client_api/docs/BatchPutResponse.md rename to hindsight-clients/python/hindsight_client_api/docs/BatchPutResponse.md index cfff2055e4..1a1effede4 100644 --- a/memora-clients/python/memora_client_api/docs/BatchPutResponse.md +++ b/hindsight-clients/python/hindsight_client_api/docs/BatchPutResponse.md @@ -15,7 +15,7 @@ Name | Type | Description | Notes ## Example ```python -from memora_client_api.models.batch_put_response import BatchPutResponse +from hindsight_client_api.models.batch_put_response import BatchPutResponse # TODO update the JSON string below json = "{}" diff --git a/memora-clients/python/memora_client_api/docs/CreateAgentRequest.md b/hindsight-clients/python/hindsight_client_api/docs/CreateAgentRequest.md similarity index 92% rename from memora-clients/python/memora_client_api/docs/CreateAgentRequest.md rename to hindsight-clients/python/hindsight_client_api/docs/CreateAgentRequest.md index 4ede74c4ab..fa02b93d41 100644 --- a/memora-clients/python/memora_client_api/docs/CreateAgentRequest.md +++ b/hindsight-clients/python/hindsight_client_api/docs/CreateAgentRequest.md @@ -13,7 +13,7 @@ Name | Type | Description | Notes ## Example ```python -from memora_client_api.models.create_agent_request import CreateAgentRequest +from hindsight_client_api.models.create_agent_request import CreateAgentRequest # TODO update the JSON string below json = "{}" diff --git a/memora-clients/python/memora_client_api/docs/DeleteResponse.md b/hindsight-clients/python/hindsight_client_api/docs/DeleteResponse.md similarity index 92% rename from memora-clients/python/memora_client_api/docs/DeleteResponse.md rename to hindsight-clients/python/hindsight_client_api/docs/DeleteResponse.md index ef2e7b94b7..4b69a917c3 100644 --- a/memora-clients/python/memora_client_api/docs/DeleteResponse.md +++ b/hindsight-clients/python/hindsight_client_api/docs/DeleteResponse.md @@ -12,7 +12,7 @@ Name | Type | Description | Notes ## Example ```python -from memora_client_api.models.delete_response import DeleteResponse +from hindsight_client_api.models.delete_response import DeleteResponse # TODO update the JSON string below json = "{}" diff --git a/memora-clients/python/memora_client_api/docs/DocumentResponse.md b/hindsight-clients/python/hindsight_client_api/docs/DocumentResponse.md similarity index 93% rename from memora-clients/python/memora_client_api/docs/DocumentResponse.md rename to hindsight-clients/python/hindsight_client_api/docs/DocumentResponse.md index 51b4b61393..8685444234 100644 --- a/memora-clients/python/memora_client_api/docs/DocumentResponse.md +++ b/hindsight-clients/python/hindsight_client_api/docs/DocumentResponse.md @@ -17,7 +17,7 @@ Name | Type | Description | Notes ## Example ```python -from memora_client_api.models.document_response import DocumentResponse +from hindsight_client_api.models.document_response import DocumentResponse # TODO update the JSON string below json = "{}" diff --git a/memora-clients/python/memora_client_api/docs/DocumentsApi.md b/hindsight-clients/python/hindsight_client_api/docs/DocumentsApi.md similarity index 85% rename from memora-clients/python/memora_client_api/docs/DocumentsApi.md rename to hindsight-clients/python/hindsight_client_api/docs/DocumentsApi.md index 1588b57370..e72db729cf 100644 --- a/memora-clients/python/memora_client_api/docs/DocumentsApi.md +++ b/hindsight-clients/python/hindsight_client_api/docs/DocumentsApi.md @@ -1,4 +1,4 @@ -# memora_client_api.DocumentsApi +# hindsight_client_api.DocumentsApi All URIs are relative to *http://localhost* @@ -27,21 +27,21 @@ This operation cannot be undone. ```python -import memora_client_api -from memora_client_api.rest import ApiException +import hindsight_client_api +from hindsight_client_api.rest import ApiException from pprint import pprint # Defining the host is optional and defaults to http://localhost # See configuration.py for a list of all supported configuration parameters. -configuration = memora_client_api.Configuration( +configuration = hindsight_client_api.Configuration( host = "http://localhost" ) # Enter a context with an instance of the API client -async with memora_client_api.ApiClient(configuration) as api_client: +async with hindsight_client_api.ApiClient(configuration) as api_client: # Create an instance of the API class - api_instance = memora_client_api.DocumentsApi(api_client) + api_instance = hindsight_client_api.DocumentsApi(api_client) agent_id = 'agent_id_example' # str | document_id = 'document_id_example' # str | @@ -97,22 +97,22 @@ Get a specific document including its original text ```python -import memora_client_api -from memora_client_api.models.document_response import DocumentResponse -from memora_client_api.rest import ApiException +import hindsight_client_api +from hindsight_client_api.models.document_response import DocumentResponse +from hindsight_client_api.rest import ApiException from pprint import pprint # Defining the host is optional and defaults to http://localhost # See configuration.py for a list of all supported configuration parameters. -configuration = memora_client_api.Configuration( +configuration = hindsight_client_api.Configuration( host = "http://localhost" ) # Enter a context with an instance of the API client -async with memora_client_api.ApiClient(configuration) as api_client: +async with hindsight_client_api.ApiClient(configuration) as api_client: # Create an instance of the API class - api_instance = memora_client_api.DocumentsApi(api_client) + api_instance = hindsight_client_api.DocumentsApi(api_client) agent_id = 'agent_id_example' # str | document_id = 'document_id_example' # str | @@ -168,22 +168,22 @@ List documents with pagination and optional search. Documents are the source con ```python -import memora_client_api -from memora_client_api.models.list_documents_response import ListDocumentsResponse -from memora_client_api.rest import ApiException +import hindsight_client_api +from hindsight_client_api.models.list_documents_response import ListDocumentsResponse +from hindsight_client_api.rest import ApiException from pprint import pprint # Defining the host is optional and defaults to http://localhost # See configuration.py for a list of all supported configuration parameters. -configuration = memora_client_api.Configuration( +configuration = hindsight_client_api.Configuration( host = "http://localhost" ) # Enter a context with an instance of the API client -async with memora_client_api.ApiClient(configuration) as api_client: +async with hindsight_client_api.ApiClient(configuration) as api_client: # Create an instance of the API class - api_instance = memora_client_api.DocumentsApi(api_client) + api_instance = hindsight_client_api.DocumentsApi(api_client) agent_id = 'agent_id_example' # str | q = 'q_example' # str | (optional) limit = 100 # int | (optional) (default to 100) diff --git a/memora-clients/python/memora_client_api/docs/GraphDataResponse.md b/hindsight-clients/python/hindsight_client_api/docs/GraphDataResponse.md similarity index 93% rename from memora-clients/python/memora_client_api/docs/GraphDataResponse.md rename to hindsight-clients/python/hindsight_client_api/docs/GraphDataResponse.md index 7d4b36f848..0f3e65aece 100644 --- a/memora-clients/python/memora_client_api/docs/GraphDataResponse.md +++ b/hindsight-clients/python/hindsight_client_api/docs/GraphDataResponse.md @@ -14,7 +14,7 @@ Name | Type | Description | Notes ## Example ```python -from memora_client_api.models.graph_data_response import GraphDataResponse +from hindsight_client_api.models.graph_data_response import GraphDataResponse # TODO update the JSON string below json = "{}" diff --git a/memora-clients/python/memora_client_api/docs/HTTPValidationError.md b/hindsight-clients/python/hindsight_client_api/docs/HTTPValidationError.md similarity index 91% rename from memora-clients/python/memora_client_api/docs/HTTPValidationError.md rename to hindsight-clients/python/hindsight_client_api/docs/HTTPValidationError.md index fae08bf19b..f1d0e7a1ef 100644 --- a/memora-clients/python/memora_client_api/docs/HTTPValidationError.md +++ b/hindsight-clients/python/hindsight_client_api/docs/HTTPValidationError.md @@ -10,7 +10,7 @@ Name | Type | Description | Notes ## Example ```python -from memora_client_api.models.http_validation_error import HTTPValidationError +from hindsight_client_api.models.http_validation_error import HTTPValidationError # TODO update the JSON string below json = "{}" diff --git a/memora-clients/python/memora_client_api/docs/ListDocumentsResponse.md b/hindsight-clients/python/hindsight_client_api/docs/ListDocumentsResponse.md similarity index 92% rename from memora-clients/python/memora_client_api/docs/ListDocumentsResponse.md rename to hindsight-clients/python/hindsight_client_api/docs/ListDocumentsResponse.md index a08b2d0eec..6474ee198f 100644 --- a/memora-clients/python/memora_client_api/docs/ListDocumentsResponse.md +++ b/hindsight-clients/python/hindsight_client_api/docs/ListDocumentsResponse.md @@ -14,7 +14,7 @@ Name | Type | Description | Notes ## Example ```python -from memora_client_api.models.list_documents_response import ListDocumentsResponse +from hindsight_client_api.models.list_documents_response import ListDocumentsResponse # TODO update the JSON string below json = "{}" diff --git a/memora-clients/python/memora_client_api/docs/ListMemoryUnitsResponse.md b/hindsight-clients/python/hindsight_client_api/docs/ListMemoryUnitsResponse.md similarity index 92% rename from memora-clients/python/memora_client_api/docs/ListMemoryUnitsResponse.md rename to hindsight-clients/python/hindsight_client_api/docs/ListMemoryUnitsResponse.md index 23733fcfd5..05579867d8 100644 --- a/memora-clients/python/memora_client_api/docs/ListMemoryUnitsResponse.md +++ b/hindsight-clients/python/hindsight_client_api/docs/ListMemoryUnitsResponse.md @@ -14,7 +14,7 @@ Name | Type | Description | Notes ## Example ```python -from memora_client_api.models.list_memory_units_response import ListMemoryUnitsResponse +from hindsight_client_api.models.list_memory_units_response import ListMemoryUnitsResponse # TODO update the JSON string below json = "{}" diff --git a/memora-clients/python/memora_client_api/docs/MemoryItem.md b/hindsight-clients/python/hindsight_client_api/docs/MemoryItem.md similarity index 93% rename from memora-clients/python/memora_client_api/docs/MemoryItem.md rename to hindsight-clients/python/hindsight_client_api/docs/MemoryItem.md index f207cfe3eb..c48e097dab 100644 --- a/memora-clients/python/memora_client_api/docs/MemoryItem.md +++ b/hindsight-clients/python/hindsight_client_api/docs/MemoryItem.md @@ -13,7 +13,7 @@ Name | Type | Description | Notes ## Example ```python -from memora_client_api.models.memory_item import MemoryItem +from hindsight_client_api.models.memory_item import MemoryItem # TODO update the JSON string below json = "{}" diff --git a/memora-clients/python/memora_client_api/docs/MemoryOperationsApi.md b/hindsight-clients/python/hindsight_client_api/docs/MemoryOperationsApi.md similarity index 84% rename from memora-clients/python/memora_client_api/docs/MemoryOperationsApi.md rename to hindsight-clients/python/hindsight_client_api/docs/MemoryOperationsApi.md index 56d448d397..d130d3f4ce 100644 --- a/memora-clients/python/memora_client_api/docs/MemoryOperationsApi.md +++ b/hindsight-clients/python/hindsight_client_api/docs/MemoryOperationsApi.md @@ -1,4 +1,4 @@ -# memora_client_api.MemoryOperationsApi +# hindsight_client_api.MemoryOperationsApi All URIs are relative to *http://localhost* @@ -43,25 +43,25 @@ Store multiple memory items in batch asynchronously using the task backend. ```python -import memora_client_api -from memora_client_api.models.batch_put_async_response import BatchPutAsyncResponse -from memora_client_api.models.batch_put_request import BatchPutRequest -from memora_client_api.rest import ApiException +import hindsight_client_api +from hindsight_client_api.models.batch_put_async_response import BatchPutAsyncResponse +from hindsight_client_api.models.batch_put_request import BatchPutRequest +from hindsight_client_api.rest import ApiException from pprint import pprint # Defining the host is optional and defaults to http://localhost # See configuration.py for a list of all supported configuration parameters. -configuration = memora_client_api.Configuration( +configuration = hindsight_client_api.Configuration( host = "http://localhost" ) # Enter a context with an instance of the API client -async with memora_client_api.ApiClient(configuration) as api_client: +async with hindsight_client_api.ApiClient(configuration) as api_client: # Create an instance of the API class - api_instance = memora_client_api.MemoryOperationsApi(api_client) + api_instance = hindsight_client_api.MemoryOperationsApi(api_client) agent_id = 'agent_id_example' # str | - batch_put_request = memora_client_api.BatchPutRequest() # BatchPutRequest | + batch_put_request = hindsight_client_api.BatchPutRequest() # BatchPutRequest | try: # Store multiple memories asynchronously @@ -131,25 +131,25 @@ Store multiple memory items in batch with automatic fact extraction. ```python -import memora_client_api -from memora_client_api.models.batch_put_request import BatchPutRequest -from memora_client_api.models.batch_put_response import BatchPutResponse -from memora_client_api.rest import ApiException +import hindsight_client_api +from hindsight_client_api.models.batch_put_request import BatchPutRequest +from hindsight_client_api.models.batch_put_response import BatchPutResponse +from hindsight_client_api.rest import ApiException from pprint import pprint # Defining the host is optional and defaults to http://localhost # See configuration.py for a list of all supported configuration parameters. -configuration = memora_client_api.Configuration( +configuration = hindsight_client_api.Configuration( host = "http://localhost" ) # Enter a context with an instance of the API client -async with memora_client_api.ApiClient(configuration) as api_client: +async with hindsight_client_api.ApiClient(configuration) as api_client: # Create an instance of the API class - api_instance = memora_client_api.MemoryOperationsApi(api_client) + api_instance = hindsight_client_api.MemoryOperationsApi(api_client) agent_id = 'agent_id_example' # str | - batch_put_request = memora_client_api.BatchPutRequest() # BatchPutRequest | + batch_put_request = hindsight_client_api.BatchPutRequest() # BatchPutRequest | try: # Store multiple memories @@ -203,21 +203,21 @@ Cancel a pending async operation by removing it from the queue ```python -import memora_client_api -from memora_client_api.rest import ApiException +import hindsight_client_api +from hindsight_client_api.rest import ApiException from pprint import pprint # Defining the host is optional and defaults to http://localhost # See configuration.py for a list of all supported configuration parameters. -configuration = memora_client_api.Configuration( +configuration = hindsight_client_api.Configuration( host = "http://localhost" ) # Enter a context with an instance of the API client -async with memora_client_api.ApiClient(configuration) as api_client: +async with hindsight_client_api.ApiClient(configuration) as api_client: # Create an instance of the API class - api_instance = memora_client_api.MemoryOperationsApi(api_client) + api_instance = hindsight_client_api.MemoryOperationsApi(api_client) agent_id = 'agent_id_example' # str | operation_id = 'operation_id_example' # str | @@ -273,21 +273,21 @@ Delete a single memory unit and all its associated links (temporal, semantic, an ```python -import memora_client_api -from memora_client_api.rest import ApiException +import hindsight_client_api +from hindsight_client_api.rest import ApiException from pprint import pprint # Defining the host is optional and defaults to http://localhost # See configuration.py for a list of all supported configuration parameters. -configuration = memora_client_api.Configuration( +configuration = hindsight_client_api.Configuration( host = "http://localhost" ) # Enter a context with an instance of the API client -async with memora_client_api.ApiClient(configuration) as api_client: +async with hindsight_client_api.ApiClient(configuration) as api_client: # Create an instance of the API class - api_instance = memora_client_api.MemoryOperationsApi(api_client) + api_instance = hindsight_client_api.MemoryOperationsApi(api_client) agent_id = 'agent_id_example' # str | unit_id = 'unit_id_example' # str | @@ -343,22 +343,22 @@ List memory units with pagination and optional full-text search. Supports filter ```python -import memora_client_api -from memora_client_api.models.list_memory_units_response import ListMemoryUnitsResponse -from memora_client_api.rest import ApiException +import hindsight_client_api +from hindsight_client_api.models.list_memory_units_response import ListMemoryUnitsResponse +from hindsight_client_api.rest import ApiException from pprint import pprint # Defining the host is optional and defaults to http://localhost # See configuration.py for a list of all supported configuration parameters. -configuration = memora_client_api.Configuration( +configuration = hindsight_client_api.Configuration( host = "http://localhost" ) # Enter a context with an instance of the API client -async with memora_client_api.ApiClient(configuration) as api_client: +async with hindsight_client_api.ApiClient(configuration) as api_client: # Create an instance of the API class - api_instance = memora_client_api.MemoryOperationsApi(api_client) + api_instance = hindsight_client_api.MemoryOperationsApi(api_client) agent_id = 'agent_id_example' # str | fact_type = 'fact_type_example' # str | (optional) q = 'q_example' # str | (optional) @@ -420,21 +420,21 @@ Get a list of all async operations (pending and failed) for a specific agent, in ```python -import memora_client_api -from memora_client_api.rest import ApiException +import hindsight_client_api +from hindsight_client_api.rest import ApiException from pprint import pprint # Defining the host is optional and defaults to http://localhost # See configuration.py for a list of all supported configuration parameters. -configuration = memora_client_api.Configuration( +configuration = hindsight_client_api.Configuration( host = "http://localhost" ) # Enter a context with an instance of the API client -async with memora_client_api.ApiClient(configuration) as api_client: +async with hindsight_client_api.ApiClient(configuration) as api_client: # Create an instance of the API class - api_instance = memora_client_api.MemoryOperationsApi(api_client) + api_instance = hindsight_client_api.MemoryOperationsApi(api_client) agent_id = 'agent_id_example' # str | try: @@ -493,25 +493,25 @@ Search memory using semantic similarity and spreading activation. ```python -import memora_client_api -from memora_client_api.models.search_request import SearchRequest -from memora_client_api.models.search_response import SearchResponse -from memora_client_api.rest import ApiException +import hindsight_client_api +from hindsight_client_api.models.search_request import SearchRequest +from hindsight_client_api.models.search_response import SearchResponse +from hindsight_client_api.rest import ApiException from pprint import pprint # Defining the host is optional and defaults to http://localhost # See configuration.py for a list of all supported configuration parameters. -configuration = memora_client_api.Configuration( +configuration = hindsight_client_api.Configuration( host = "http://localhost" ) # Enter a context with an instance of the API client -async with memora_client_api.ApiClient(configuration) as api_client: +async with hindsight_client_api.ApiClient(configuration) as api_client: # Create an instance of the API class - api_instance = memora_client_api.MemoryOperationsApi(api_client) + api_instance = hindsight_client_api.MemoryOperationsApi(api_client) agent_id = 'agent_id_example' # str | - search_request = memora_client_api.SearchRequest() # SearchRequest | + search_request = hindsight_client_api.SearchRequest() # SearchRequest | try: # Search memory diff --git a/memora-clients/python/memora_client_api/docs/PersonalityTraits.md b/hindsight-clients/python/hindsight_client_api/docs/PersonalityTraits.md similarity index 94% rename from memora-clients/python/memora_client_api/docs/PersonalityTraits.md rename to hindsight-clients/python/hindsight_client_api/docs/PersonalityTraits.md index 34e82d41c7..9550c0fbba 100644 --- a/memora-clients/python/memora_client_api/docs/PersonalityTraits.md +++ b/hindsight-clients/python/hindsight_client_api/docs/PersonalityTraits.md @@ -16,7 +16,7 @@ Name | Type | Description | Notes ## Example ```python -from memora_client_api.models.personality_traits import PersonalityTraits +from hindsight_client_api.models.personality_traits import PersonalityTraits # TODO update the JSON string below json = "{}" diff --git a/memora-clients/python/memora_client_api/docs/ReasoningApi.md b/hindsight-clients/python/hindsight_client_api/docs/ReasoningApi.md similarity index 81% rename from memora-clients/python/memora_client_api/docs/ReasoningApi.md rename to hindsight-clients/python/hindsight_client_api/docs/ReasoningApi.md index 62a5655fc4..6bde5d680e 100644 --- a/memora-clients/python/memora_client_api/docs/ReasoningApi.md +++ b/hindsight-clients/python/hindsight_client_api/docs/ReasoningApi.md @@ -1,4 +1,4 @@ -# memora_client_api.ReasoningApi +# hindsight_client_api.ReasoningApi All URIs are relative to *http://localhost* @@ -26,25 +26,25 @@ Think and formulate an answer using agent identity, world facts, and opinions. ```python -import memora_client_api -from memora_client_api.models.think_request import ThinkRequest -from memora_client_api.models.think_response import ThinkResponse -from memora_client_api.rest import ApiException +import hindsight_client_api +from hindsight_client_api.models.think_request import ThinkRequest +from hindsight_client_api.models.think_response import ThinkResponse +from hindsight_client_api.rest import ApiException from pprint import pprint # Defining the host is optional and defaults to http://localhost # See configuration.py for a list of all supported configuration parameters. -configuration = memora_client_api.Configuration( +configuration = hindsight_client_api.Configuration( host = "http://localhost" ) # Enter a context with an instance of the API client -async with memora_client_api.ApiClient(configuration) as api_client: +async with hindsight_client_api.ApiClient(configuration) as api_client: # Create an instance of the API class - api_instance = memora_client_api.ReasoningApi(api_client) + api_instance = hindsight_client_api.ReasoningApi(api_client) agent_id = 'agent_id_example' # str | - think_request = memora_client_api.ThinkRequest() # ThinkRequest | + think_request = hindsight_client_api.ThinkRequest() # ThinkRequest | try: # Think and generate answer diff --git a/memora-clients/python/memora_client_api/docs/SearchRequest.md b/hindsight-clients/python/hindsight_client_api/docs/SearchRequest.md similarity index 94% rename from memora-clients/python/memora_client_api/docs/SearchRequest.md rename to hindsight-clients/python/hindsight_client_api/docs/SearchRequest.md index 6bd363ad8f..8e9f7d3d93 100644 --- a/memora-clients/python/memora_client_api/docs/SearchRequest.md +++ b/hindsight-clients/python/hindsight_client_api/docs/SearchRequest.md @@ -16,7 +16,7 @@ Name | Type | Description | Notes ## Example ```python -from memora_client_api.models.search_request import SearchRequest +from hindsight_client_api.models.search_request import SearchRequest # TODO update the JSON string below json = "{}" diff --git a/memora-clients/python/memora_client_api/docs/SearchResponse.md b/hindsight-clients/python/hindsight_client_api/docs/SearchResponse.md similarity index 92% rename from memora-clients/python/memora_client_api/docs/SearchResponse.md rename to hindsight-clients/python/hindsight_client_api/docs/SearchResponse.md index 37e17f9e89..b07331636f 100644 --- a/memora-clients/python/memora_client_api/docs/SearchResponse.md +++ b/hindsight-clients/python/hindsight_client_api/docs/SearchResponse.md @@ -12,7 +12,7 @@ Name | Type | Description | Notes ## Example ```python -from memora_client_api.models.search_response import SearchResponse +from hindsight_client_api.models.search_response import SearchResponse # TODO update the JSON string below json = "{}" diff --git a/memora-clients/python/memora_client_api/docs/SearchResult.md b/hindsight-clients/python/hindsight_client_api/docs/SearchResult.md similarity index 93% rename from memora-clients/python/memora_client_api/docs/SearchResult.md rename to hindsight-clients/python/hindsight_client_api/docs/SearchResult.md index 389494f3b4..ba4c44a980 100644 --- a/memora-clients/python/memora_client_api/docs/SearchResult.md +++ b/hindsight-clients/python/hindsight_client_api/docs/SearchResult.md @@ -16,7 +16,7 @@ Name | Type | Description | Notes ## Example ```python -from memora_client_api.models.search_result import SearchResult +from hindsight_client_api.models.search_result import SearchResult # TODO update the JSON string below json = "{}" diff --git a/memora-clients/python/memora_client_api/docs/ThinkFact.md b/hindsight-clients/python/hindsight_client_api/docs/ThinkFact.md similarity index 93% rename from memora-clients/python/memora_client_api/docs/ThinkFact.md rename to hindsight-clients/python/hindsight_client_api/docs/ThinkFact.md index cbb811ac3f..78b16eb740 100644 --- a/memora-clients/python/memora_client_api/docs/ThinkFact.md +++ b/hindsight-clients/python/hindsight_client_api/docs/ThinkFact.md @@ -15,7 +15,7 @@ Name | Type | Description | Notes ## Example ```python -from memora_client_api.models.think_fact import ThinkFact +from hindsight_client_api.models.think_fact import ThinkFact # TODO update the JSON string below json = "{}" diff --git a/memora-clients/python/memora_client_api/docs/ThinkRequest.md b/hindsight-clients/python/hindsight_client_api/docs/ThinkRequest.md similarity index 93% rename from memora-clients/python/memora_client_api/docs/ThinkRequest.md rename to hindsight-clients/python/hindsight_client_api/docs/ThinkRequest.md index 14448a677b..1cb7b75708 100644 --- a/memora-clients/python/memora_client_api/docs/ThinkRequest.md +++ b/hindsight-clients/python/hindsight_client_api/docs/ThinkRequest.md @@ -13,7 +13,7 @@ Name | Type | Description | Notes ## Example ```python -from memora_client_api.models.think_request import ThinkRequest +from hindsight_client_api.models.think_request import ThinkRequest # TODO update the JSON string below json = "{}" diff --git a/memora-clients/python/memora_client_api/docs/ThinkResponse.md b/hindsight-clients/python/hindsight_client_api/docs/ThinkResponse.md similarity index 93% rename from memora-clients/python/memora_client_api/docs/ThinkResponse.md rename to hindsight-clients/python/hindsight_client_api/docs/ThinkResponse.md index 8ddbc4cdcb..914dce22b1 100644 --- a/memora-clients/python/memora_client_api/docs/ThinkResponse.md +++ b/hindsight-clients/python/hindsight_client_api/docs/ThinkResponse.md @@ -13,7 +13,7 @@ Name | Type | Description | Notes ## Example ```python -from memora_client_api.models.think_response import ThinkResponse +from hindsight_client_api.models.think_response import ThinkResponse # TODO update the JSON string below json = "{}" diff --git a/memora-clients/python/memora_client_api/docs/UpdatePersonalityRequest.md b/hindsight-clients/python/hindsight_client_api/docs/UpdatePersonalityRequest.md similarity index 91% rename from memora-clients/python/memora_client_api/docs/UpdatePersonalityRequest.md rename to hindsight-clients/python/hindsight_client_api/docs/UpdatePersonalityRequest.md index e1d2a3209a..b1cb071a0e 100644 --- a/memora-clients/python/memora_client_api/docs/UpdatePersonalityRequest.md +++ b/hindsight-clients/python/hindsight_client_api/docs/UpdatePersonalityRequest.md @@ -11,7 +11,7 @@ Name | Type | Description | Notes ## Example ```python -from memora_client_api.models.update_personality_request import UpdatePersonalityRequest +from hindsight_client_api.models.update_personality_request import UpdatePersonalityRequest # TODO update the JSON string below json = "{}" diff --git a/memora-clients/python/memora_client_api/docs/ValidationError.md b/hindsight-clients/python/hindsight_client_api/docs/ValidationError.md similarity index 92% rename from memora-clients/python/memora_client_api/docs/ValidationError.md rename to hindsight-clients/python/hindsight_client_api/docs/ValidationError.md index ac991db6ca..69684b4f98 100644 --- a/memora-clients/python/memora_client_api/docs/ValidationError.md +++ b/hindsight-clients/python/hindsight_client_api/docs/ValidationError.md @@ -12,7 +12,7 @@ Name | Type | Description | Notes ## Example ```python -from memora_client_api.models.validation_error import ValidationError +from hindsight_client_api.models.validation_error import ValidationError # TODO update the JSON string below json = "{}" diff --git a/memora-clients/python/memora_client_api/docs/ValidationErrorLocInner.md b/hindsight-clients/python/hindsight_client_api/docs/ValidationErrorLocInner.md similarity index 90% rename from memora-clients/python/memora_client_api/docs/ValidationErrorLocInner.md rename to hindsight-clients/python/hindsight_client_api/docs/ValidationErrorLocInner.md index 71da034929..78ac99a4b2 100644 --- a/memora-clients/python/memora_client_api/docs/ValidationErrorLocInner.md +++ b/hindsight-clients/python/hindsight_client_api/docs/ValidationErrorLocInner.md @@ -9,7 +9,7 @@ Name | Type | Description | Notes ## Example ```python -from memora_client_api.models.validation_error_loc_inner import ValidationErrorLocInner +from hindsight_client_api.models.validation_error_loc_inner import ValidationErrorLocInner # TODO update the JSON string below json = "{}" diff --git a/memora-clients/python/memora_client_api/docs/VisualizationApi.md b/hindsight-clients/python/hindsight_client_api/docs/VisualizationApi.md similarity index 83% rename from memora-clients/python/memora_client_api/docs/VisualizationApi.md rename to hindsight-clients/python/hindsight_client_api/docs/VisualizationApi.md index 30d80ade40..c18b3d36ae 100644 --- a/memora-clients/python/memora_client_api/docs/VisualizationApi.md +++ b/hindsight-clients/python/hindsight_client_api/docs/VisualizationApi.md @@ -1,4 +1,4 @@ -# memora_client_api.VisualizationApi +# hindsight_client_api.VisualizationApi All URIs are relative to *http://localhost* @@ -18,22 +18,22 @@ Retrieve graph data for visualization, optionally filtered by fact_type (world/a ```python -import memora_client_api -from memora_client_api.models.graph_data_response import GraphDataResponse -from memora_client_api.rest import ApiException +import hindsight_client_api +from hindsight_client_api.models.graph_data_response import GraphDataResponse +from hindsight_client_api.rest import ApiException from pprint import pprint # Defining the host is optional and defaults to http://localhost # See configuration.py for a list of all supported configuration parameters. -configuration = memora_client_api.Configuration( +configuration = hindsight_client_api.Configuration( host = "http://localhost" ) # Enter a context with an instance of the API client -async with memora_client_api.ApiClient(configuration) as api_client: +async with hindsight_client_api.ApiClient(configuration) as api_client: # Create an instance of the API class - api_instance = memora_client_api.VisualizationApi(api_client) + api_instance = hindsight_client_api.VisualizationApi(api_client) agent_id = 'agent_id_example' # str | fact_type = 'fact_type_example' # str | (optional) diff --git a/memora-clients/python/memora_client_api/exceptions.py b/hindsight-clients/python/hindsight_client_api/exceptions.py similarity index 100% rename from memora-clients/python/memora_client_api/exceptions.py rename to hindsight-clients/python/hindsight_client_api/exceptions.py diff --git a/hindsight-clients/python/hindsight_client_api/models/__init__.py b/hindsight-clients/python/hindsight_client_api/models/__init__.py new file mode 100644 index 0000000000..e3e52e1ff0 --- /dev/null +++ b/hindsight-clients/python/hindsight_client_api/models/__init__.py @@ -0,0 +1,42 @@ +# coding: utf-8 + +# flake8: noqa +""" + Agent Memory API + + A temporal-semantic memory system for AI agents that stores, retrieves, and reasons over memories. ## Features * **Batch Memory Storage**: Store multiple memories efficiently with automatic fact extraction * **Semantic Search**: Find relevant memories using natural language queries * **Fact Type Filtering**: Search across world facts, agent actions, and opinions separately * **Think Endpoint**: Generate contextual answers based on agent identity and memories * **Graph Visualization**: Interactive memory graph visualization * **Document Tracking**: Track and manage memory documents with upsert support ## Architecture The system uses: - **Temporal Links**: Connect memories that are close in time - **Semantic Links**: Connect semantically similar memories - **Entity Links**: Connect memories that mention the same entities - **Spreading Activation**: Intelligent traversal for memory retrieval + + The version of the OpenAPI document: 1.0.0 + Generated by OpenAPI Generator (https://openapi-generator.tech) + + Do not edit the class manually. +""" # noqa: E501 + +# import models into model package +from hindsight_client_api.models.add_background_request import AddBackgroundRequest +from hindsight_client_api.models.agent_list_item import AgentListItem +from hindsight_client_api.models.agent_list_response import AgentListResponse +from hindsight_client_api.models.agent_profile_response import AgentProfileResponse +from hindsight_client_api.models.background_response import BackgroundResponse +from hindsight_client_api.models.batch_put_async_response import BatchPutAsyncResponse +from hindsight_client_api.models.batch_put_request import BatchPutRequest +from hindsight_client_api.models.batch_put_response import BatchPutResponse +from hindsight_client_api.models.create_agent_request import CreateAgentRequest +from hindsight_client_api.models.delete_response import DeleteResponse +from hindsight_client_api.models.document_response import DocumentResponse +from hindsight_client_api.models.graph_data_response import GraphDataResponse +from hindsight_client_api.models.http_validation_error import HTTPValidationError +from hindsight_client_api.models.list_documents_response import ListDocumentsResponse +from hindsight_client_api.models.list_memory_units_response import ListMemoryUnitsResponse +from hindsight_client_api.models.memory_item import MemoryItem +from hindsight_client_api.models.personality_traits import PersonalityTraits +from hindsight_client_api.models.search_request import SearchRequest +from hindsight_client_api.models.search_response import SearchResponse +from hindsight_client_api.models.search_result import SearchResult +from hindsight_client_api.models.think_fact import ThinkFact +from hindsight_client_api.models.think_request import ThinkRequest +from hindsight_client_api.models.think_response import ThinkResponse +from hindsight_client_api.models.update_personality_request import UpdatePersonalityRequest +from hindsight_client_api.models.validation_error import ValidationError +from hindsight_client_api.models.validation_error_loc_inner import ValidationErrorLocInner + diff --git a/memora-clients/python/memora_client_api/models/add_background_request.py b/hindsight-clients/python/hindsight_client_api/models/add_background_request.py similarity index 100% rename from memora-clients/python/memora_client_api/models/add_background_request.py rename to hindsight-clients/python/hindsight_client_api/models/add_background_request.py diff --git a/memora-clients/python/memora_client_api/models/agent_list_item.py b/hindsight-clients/python/hindsight_client_api/models/agent_list_item.py similarity index 98% rename from memora-clients/python/memora_client_api/models/agent_list_item.py rename to hindsight-clients/python/hindsight_client_api/models/agent_list_item.py index d4c09735ea..1f9293f9db 100644 --- a/memora-clients/python/memora_client_api/models/agent_list_item.py +++ b/hindsight-clients/python/hindsight_client_api/models/agent_list_item.py @@ -19,7 +19,7 @@ from pydantic import BaseModel, ConfigDict, StrictStr from typing import Any, ClassVar, Dict, List, Optional -from memora_client_api.models.personality_traits import PersonalityTraits +from hindsight_client_api.models.personality_traits import PersonalityTraits from typing import Optional, Set from typing_extensions import Self diff --git a/memora-clients/python/memora_client_api/models/agent_list_response.py b/hindsight-clients/python/hindsight_client_api/models/agent_list_response.py similarity index 98% rename from memora-clients/python/memora_client_api/models/agent_list_response.py rename to hindsight-clients/python/hindsight_client_api/models/agent_list_response.py index c5bf8dd8bc..062f6d107a 100644 --- a/memora-clients/python/memora_client_api/models/agent_list_response.py +++ b/hindsight-clients/python/hindsight_client_api/models/agent_list_response.py @@ -19,7 +19,7 @@ from pydantic import BaseModel, ConfigDict from typing import Any, ClassVar, Dict, List -from memora_client_api.models.agent_list_item import AgentListItem +from hindsight_client_api.models.agent_list_item import AgentListItem from typing import Optional, Set from typing_extensions import Self diff --git a/memora-clients/python/memora_client_api/models/agent_profile_response.py b/hindsight-clients/python/hindsight_client_api/models/agent_profile_response.py similarity index 98% rename from memora-clients/python/memora_client_api/models/agent_profile_response.py rename to hindsight-clients/python/hindsight_client_api/models/agent_profile_response.py index 1bbe5965be..aa72800a55 100644 --- a/memora-clients/python/memora_client_api/models/agent_profile_response.py +++ b/hindsight-clients/python/hindsight_client_api/models/agent_profile_response.py @@ -19,7 +19,7 @@ from pydantic import BaseModel, ConfigDict, StrictStr from typing import Any, ClassVar, Dict, List -from memora_client_api.models.personality_traits import PersonalityTraits +from hindsight_client_api.models.personality_traits import PersonalityTraits from typing import Optional, Set from typing_extensions import Self diff --git a/memora-clients/python/memora_client_api/models/background_response.py b/hindsight-clients/python/hindsight_client_api/models/background_response.py similarity index 98% rename from memora-clients/python/memora_client_api/models/background_response.py rename to hindsight-clients/python/hindsight_client_api/models/background_response.py index 5968d9ef16..913db60b86 100644 --- a/memora-clients/python/memora_client_api/models/background_response.py +++ b/hindsight-clients/python/hindsight_client_api/models/background_response.py @@ -19,7 +19,7 @@ from pydantic import BaseModel, ConfigDict, StrictStr from typing import Any, ClassVar, Dict, List, Optional -from memora_client_api.models.personality_traits import PersonalityTraits +from hindsight_client_api.models.personality_traits import PersonalityTraits from typing import Optional, Set from typing_extensions import Self diff --git a/memora-clients/python/memora_client_api/models/batch_put_async_response.py b/hindsight-clients/python/hindsight_client_api/models/batch_put_async_response.py similarity index 100% rename from memora-clients/python/memora_client_api/models/batch_put_async_response.py rename to hindsight-clients/python/hindsight_client_api/models/batch_put_async_response.py diff --git a/memora-clients/python/memora_client_api/models/batch_put_request.py b/hindsight-clients/python/hindsight_client_api/models/batch_put_request.py similarity index 98% rename from memora-clients/python/memora_client_api/models/batch_put_request.py rename to hindsight-clients/python/hindsight_client_api/models/batch_put_request.py index 74c587480b..55e817246b 100644 --- a/memora-clients/python/memora_client_api/models/batch_put_request.py +++ b/hindsight-clients/python/hindsight_client_api/models/batch_put_request.py @@ -19,7 +19,7 @@ from pydantic import BaseModel, ConfigDict, StrictStr from typing import Any, ClassVar, Dict, List, Optional -from memora_client_api.models.memory_item import MemoryItem +from hindsight_client_api.models.memory_item import MemoryItem from typing import Optional, Set from typing_extensions import Self diff --git a/memora-clients/python/memora_client_api/models/batch_put_response.py b/hindsight-clients/python/hindsight_client_api/models/batch_put_response.py similarity index 100% rename from memora-clients/python/memora_client_api/models/batch_put_response.py rename to hindsight-clients/python/hindsight_client_api/models/batch_put_response.py diff --git a/memora-clients/python/memora_client_api/models/create_agent_request.py b/hindsight-clients/python/hindsight_client_api/models/create_agent_request.py similarity index 98% rename from memora-clients/python/memora_client_api/models/create_agent_request.py rename to hindsight-clients/python/hindsight_client_api/models/create_agent_request.py index e157ae9f50..e4bb3e85a2 100644 --- a/memora-clients/python/memora_client_api/models/create_agent_request.py +++ b/hindsight-clients/python/hindsight_client_api/models/create_agent_request.py @@ -19,7 +19,7 @@ from pydantic import BaseModel, ConfigDict, StrictStr from typing import Any, ClassVar, Dict, List, Optional -from memora_client_api.models.personality_traits import PersonalityTraits +from hindsight_client_api.models.personality_traits import PersonalityTraits from typing import Optional, Set from typing_extensions import Self diff --git a/memora-clients/python/memora_client_api/models/delete_response.py b/hindsight-clients/python/hindsight_client_api/models/delete_response.py similarity index 100% rename from memora-clients/python/memora_client_api/models/delete_response.py rename to hindsight-clients/python/hindsight_client_api/models/delete_response.py diff --git a/memora-clients/python/memora_client_api/models/document_response.py b/hindsight-clients/python/hindsight_client_api/models/document_response.py similarity index 100% rename from memora-clients/python/memora_client_api/models/document_response.py rename to hindsight-clients/python/hindsight_client_api/models/document_response.py diff --git a/memora-clients/python/memora_client_api/models/graph_data_response.py b/hindsight-clients/python/hindsight_client_api/models/graph_data_response.py similarity index 100% rename from memora-clients/python/memora_client_api/models/graph_data_response.py rename to hindsight-clients/python/hindsight_client_api/models/graph_data_response.py diff --git a/memora-clients/python/memora_client_api/models/http_validation_error.py b/hindsight-clients/python/hindsight_client_api/models/http_validation_error.py similarity index 98% rename from memora-clients/python/memora_client_api/models/http_validation_error.py rename to hindsight-clients/python/hindsight_client_api/models/http_validation_error.py index ca64c8b07c..91edaae1ee 100644 --- a/memora-clients/python/memora_client_api/models/http_validation_error.py +++ b/hindsight-clients/python/hindsight_client_api/models/http_validation_error.py @@ -19,7 +19,7 @@ from pydantic import BaseModel, ConfigDict from typing import Any, ClassVar, Dict, List, Optional -from memora_client_api.models.validation_error import ValidationError +from hindsight_client_api.models.validation_error import ValidationError from typing import Optional, Set from typing_extensions import Self diff --git a/memora-clients/python/memora_client_api/models/list_documents_response.py b/hindsight-clients/python/hindsight_client_api/models/list_documents_response.py similarity index 100% rename from memora-clients/python/memora_client_api/models/list_documents_response.py rename to hindsight-clients/python/hindsight_client_api/models/list_documents_response.py diff --git a/memora-clients/python/memora_client_api/models/list_memory_units_response.py b/hindsight-clients/python/hindsight_client_api/models/list_memory_units_response.py similarity index 100% rename from memora-clients/python/memora_client_api/models/list_memory_units_response.py rename to hindsight-clients/python/hindsight_client_api/models/list_memory_units_response.py diff --git a/memora-clients/python/memora_client_api/models/memory_item.py b/hindsight-clients/python/hindsight_client_api/models/memory_item.py similarity index 100% rename from memora-clients/python/memora_client_api/models/memory_item.py rename to hindsight-clients/python/hindsight_client_api/models/memory_item.py diff --git a/memora-clients/python/memora_client_api/models/personality_traits.py b/hindsight-clients/python/hindsight_client_api/models/personality_traits.py similarity index 100% rename from memora-clients/python/memora_client_api/models/personality_traits.py rename to hindsight-clients/python/hindsight_client_api/models/personality_traits.py diff --git a/memora-clients/python/memora_client_api/models/search_request.py b/hindsight-clients/python/hindsight_client_api/models/search_request.py similarity index 100% rename from memora-clients/python/memora_client_api/models/search_request.py rename to hindsight-clients/python/hindsight_client_api/models/search_request.py diff --git a/memora-clients/python/memora_client_api/models/search_response.py b/hindsight-clients/python/hindsight_client_api/models/search_response.py similarity index 98% rename from memora-clients/python/memora_client_api/models/search_response.py rename to hindsight-clients/python/hindsight_client_api/models/search_response.py index 3a274e6c7d..a885ab12a3 100644 --- a/memora-clients/python/memora_client_api/models/search_response.py +++ b/hindsight-clients/python/hindsight_client_api/models/search_response.py @@ -19,7 +19,7 @@ from pydantic import BaseModel, ConfigDict from typing import Any, ClassVar, Dict, List, Optional -from memora_client_api.models.search_result import SearchResult +from hindsight_client_api.models.search_result import SearchResult from typing import Optional, Set from typing_extensions import Self diff --git a/memora-clients/python/memora_client_api/models/search_result.py b/hindsight-clients/python/hindsight_client_api/models/search_result.py similarity index 100% rename from memora-clients/python/memora_client_api/models/search_result.py rename to hindsight-clients/python/hindsight_client_api/models/search_result.py diff --git a/memora-clients/python/memora_client_api/models/think_fact.py b/hindsight-clients/python/hindsight_client_api/models/think_fact.py similarity index 100% rename from memora-clients/python/memora_client_api/models/think_fact.py rename to hindsight-clients/python/hindsight_client_api/models/think_fact.py diff --git a/memora-clients/python/memora_client_api/models/think_request.py b/hindsight-clients/python/hindsight_client_api/models/think_request.py similarity index 100% rename from memora-clients/python/memora_client_api/models/think_request.py rename to hindsight-clients/python/hindsight_client_api/models/think_request.py diff --git a/memora-clients/python/memora_client_api/models/think_response.py b/hindsight-clients/python/hindsight_client_api/models/think_response.py similarity index 98% rename from memora-clients/python/memora_client_api/models/think_response.py rename to hindsight-clients/python/hindsight_client_api/models/think_response.py index 1614e602d5..7fb7d4df67 100644 --- a/memora-clients/python/memora_client_api/models/think_response.py +++ b/hindsight-clients/python/hindsight_client_api/models/think_response.py @@ -19,7 +19,7 @@ from pydantic import BaseModel, ConfigDict, StrictStr from typing import Any, ClassVar, Dict, List, Optional -from memora_client_api.models.think_fact import ThinkFact +from hindsight_client_api.models.think_fact import ThinkFact from typing import Optional, Set from typing_extensions import Self diff --git a/memora-clients/python/memora_client_api/models/update_personality_request.py b/hindsight-clients/python/hindsight_client_api/models/update_personality_request.py similarity index 97% rename from memora-clients/python/memora_client_api/models/update_personality_request.py rename to hindsight-clients/python/hindsight_client_api/models/update_personality_request.py index 88f953b3b9..2050db6d47 100644 --- a/memora-clients/python/memora_client_api/models/update_personality_request.py +++ b/hindsight-clients/python/hindsight_client_api/models/update_personality_request.py @@ -19,7 +19,7 @@ from pydantic import BaseModel, ConfigDict from typing import Any, ClassVar, Dict, List -from memora_client_api.models.personality_traits import PersonalityTraits +from hindsight_client_api.models.personality_traits import PersonalityTraits from typing import Optional, Set from typing_extensions import Self diff --git a/memora-clients/python/memora_client_api/models/validation_error.py b/hindsight-clients/python/hindsight_client_api/models/validation_error.py similarity index 97% rename from memora-clients/python/memora_client_api/models/validation_error.py rename to hindsight-clients/python/hindsight_client_api/models/validation_error.py index 7bb22942e4..0a553414a3 100644 --- a/memora-clients/python/memora_client_api/models/validation_error.py +++ b/hindsight-clients/python/hindsight_client_api/models/validation_error.py @@ -19,7 +19,7 @@ from pydantic import BaseModel, ConfigDict, StrictStr from typing import Any, ClassVar, Dict, List -from memora_client_api.models.validation_error_loc_inner import ValidationErrorLocInner +from hindsight_client_api.models.validation_error_loc_inner import ValidationErrorLocInner from typing import Optional, Set from typing_extensions import Self diff --git a/memora-clients/python/memora_client_api/models/validation_error_loc_inner.py b/hindsight-clients/python/hindsight_client_api/models/validation_error_loc_inner.py similarity index 100% rename from memora-clients/python/memora_client_api/models/validation_error_loc_inner.py rename to hindsight-clients/python/hindsight_client_api/models/validation_error_loc_inner.py diff --git a/memora-clients/python/memora_client_api/rest.py b/hindsight-clients/python/hindsight_client_api/rest.py similarity index 99% rename from memora-clients/python/memora_client_api/rest.py rename to hindsight-clients/python/hindsight_client_api/rest.py index ab2e8bc655..9df61a694e 100644 --- a/memora-clients/python/memora_client_api/rest.py +++ b/hindsight-clients/python/hindsight_client_api/rest.py @@ -21,7 +21,7 @@ import aiohttp import aiohttp_retry -from memora_client_api.exceptions import ApiException, ApiValueError +from hindsight_client_api.exceptions import ApiException, ApiValueError RESTResponseType = aiohttp.ClientResponse diff --git a/memora-clients/python/memora_client_api/test/__init__.py b/hindsight-clients/python/hindsight_client_api/test/__init__.py similarity index 100% rename from memora-clients/python/memora_client_api/test/__init__.py rename to hindsight-clients/python/hindsight_client_api/test/__init__.py diff --git a/memora-clients/python/memora_client_api/test/test_add_background_request.py b/hindsight-clients/python/hindsight_client_api/test/test_add_background_request.py similarity index 96% rename from memora-clients/python/memora_client_api/test/test_add_background_request.py rename to hindsight-clients/python/hindsight_client_api/test/test_add_background_request.py index 3ed4caa875..8257ebb13b 100644 --- a/memora-clients/python/memora_client_api/test/test_add_background_request.py +++ b/hindsight-clients/python/hindsight_client_api/test/test_add_background_request.py @@ -14,7 +14,7 @@ import unittest -from memora_client_api.models.add_background_request import AddBackgroundRequest +from hindsight_client_api.models.add_background_request import AddBackgroundRequest class TestAddBackgroundRequest(unittest.TestCase): """AddBackgroundRequest unit test stubs""" diff --git a/memora-clients/python/memora_client_api/test/test_agent_list_item.py b/hindsight-clients/python/hindsight_client_api/test/test_agent_list_item.py similarity index 97% rename from memora-clients/python/memora_client_api/test/test_agent_list_item.py rename to hindsight-clients/python/hindsight_client_api/test/test_agent_list_item.py index 5701398b44..5352498bf1 100644 --- a/memora-clients/python/memora_client_api/test/test_agent_list_item.py +++ b/hindsight-clients/python/hindsight_client_api/test/test_agent_list_item.py @@ -14,7 +14,7 @@ import unittest -from memora_client_api.models.agent_list_item import AgentListItem +from hindsight_client_api.models.agent_list_item import AgentListItem class TestAgentListItem(unittest.TestCase): """AgentListItem unit test stubs""" diff --git a/memora-clients/python/memora_client_api/test/test_agent_list_response.py b/hindsight-clients/python/hindsight_client_api/test/test_agent_list_response.py similarity index 92% rename from memora-clients/python/memora_client_api/test/test_agent_list_response.py rename to hindsight-clients/python/hindsight_client_api/test/test_agent_list_response.py index f5aaa60b28..50dc02c4f4 100644 --- a/memora-clients/python/memora_client_api/test/test_agent_list_response.py +++ b/hindsight-clients/python/hindsight_client_api/test/test_agent_list_response.py @@ -14,7 +14,7 @@ import unittest -from memora_client_api.models.agent_list_response import AgentListResponse +from hindsight_client_api.models.agent_list_response import AgentListResponse class TestAgentListResponse(unittest.TestCase): """AgentListResponse unit test stubs""" @@ -36,7 +36,7 @@ def make_instance(self, include_optional) -> AgentListResponse: if include_optional: return AgentListResponse( agents = [ - memora_client_api.models.agent_list_item.AgentListItem( + hindsight_client_api.models.agent_list_item.AgentListItem( agent_id = '', name = '', personality = {agreeableness=0.7, bias_strength=0.7, conscientiousness=0.6, extraversion=0.5, neuroticism=0.3, openness=0.8}, @@ -48,7 +48,7 @@ def make_instance(self, include_optional) -> AgentListResponse: else: return AgentListResponse( agents = [ - memora_client_api.models.agent_list_item.AgentListItem( + hindsight_client_api.models.agent_list_item.AgentListItem( agent_id = '', name = '', personality = {agreeableness=0.7, bias_strength=0.7, conscientiousness=0.6, extraversion=0.5, neuroticism=0.3, openness=0.8}, diff --git a/memora-clients/python/memora_client_api/test/test_agent_management_api.py b/hindsight-clients/python/hindsight_client_api/test/test_agent_management_api.py similarity index 97% rename from memora-clients/python/memora_client_api/test/test_agent_management_api.py rename to hindsight-clients/python/hindsight_client_api/test/test_agent_management_api.py index 6a0d8cb902..30cd322935 100644 --- a/memora-clients/python/memora_client_api/test/test_agent_management_api.py +++ b/hindsight-clients/python/hindsight_client_api/test/test_agent_management_api.py @@ -14,7 +14,7 @@ import unittest -from memora_client_api.api.agent_management_api import AgentManagementApi +from hindsight_client_api.api.agent_management_api import AgentManagementApi class TestAgentManagementApi(unittest.IsolatedAsyncioTestCase): diff --git a/memora-clients/python/memora_client_api/test/test_agent_profile_response.py b/hindsight-clients/python/hindsight_client_api/test/test_agent_profile_response.py similarity index 96% rename from memora-clients/python/memora_client_api/test/test_agent_profile_response.py rename to hindsight-clients/python/hindsight_client_api/test/test_agent_profile_response.py index d44b5d37b7..eadfd4fb99 100644 --- a/memora-clients/python/memora_client_api/test/test_agent_profile_response.py +++ b/hindsight-clients/python/hindsight_client_api/test/test_agent_profile_response.py @@ -14,7 +14,7 @@ import unittest -from memora_client_api.models.agent_profile_response import AgentProfileResponse +from hindsight_client_api.models.agent_profile_response import AgentProfileResponse class TestAgentProfileResponse(unittest.TestCase): """AgentProfileResponse unit test stubs""" diff --git a/memora-clients/python/memora_client_api/test/test_background_response.py b/hindsight-clients/python/hindsight_client_api/test/test_background_response.py similarity index 96% rename from memora-clients/python/memora_client_api/test/test_background_response.py rename to hindsight-clients/python/hindsight_client_api/test/test_background_response.py index 6b9d992a56..d156b51ab5 100644 --- a/memora-clients/python/memora_client_api/test/test_background_response.py +++ b/hindsight-clients/python/hindsight_client_api/test/test_background_response.py @@ -14,7 +14,7 @@ import unittest -from memora_client_api.models.background_response import BackgroundResponse +from hindsight_client_api.models.background_response import BackgroundResponse class TestBackgroundResponse(unittest.TestCase): """BackgroundResponse unit test stubs""" diff --git a/memora-clients/python/memora_client_api/test/test_batch_put_async_response.py b/hindsight-clients/python/hindsight_client_api/test/test_batch_put_async_response.py similarity index 96% rename from memora-clients/python/memora_client_api/test/test_batch_put_async_response.py rename to hindsight-clients/python/hindsight_client_api/test/test_batch_put_async_response.py index 1b0561787b..584ad5d1f1 100644 --- a/memora-clients/python/memora_client_api/test/test_batch_put_async_response.py +++ b/hindsight-clients/python/hindsight_client_api/test/test_batch_put_async_response.py @@ -14,7 +14,7 @@ import unittest -from memora_client_api.models.batch_put_async_response import BatchPutAsyncResponse +from hindsight_client_api.models.batch_put_async_response import BatchPutAsyncResponse class TestBatchPutAsyncResponse(unittest.TestCase): """BatchPutAsyncResponse unit test stubs""" diff --git a/memora-clients/python/memora_client_api/test/test_batch_put_request.py b/hindsight-clients/python/hindsight_client_api/test/test_batch_put_request.py similarity index 97% rename from memora-clients/python/memora_client_api/test/test_batch_put_request.py rename to hindsight-clients/python/hindsight_client_api/test/test_batch_put_request.py index bf9911e3ad..19db87dd20 100644 --- a/memora-clients/python/memora_client_api/test/test_batch_put_request.py +++ b/hindsight-clients/python/hindsight_client_api/test/test_batch_put_request.py @@ -14,7 +14,7 @@ import unittest -from memora_client_api.models.batch_put_request import BatchPutRequest +from hindsight_client_api.models.batch_put_request import BatchPutRequest class TestBatchPutRequest(unittest.TestCase): """BatchPutRequest unit test stubs""" diff --git a/memora-clients/python/memora_client_api/test/test_batch_put_response.py b/hindsight-clients/python/hindsight_client_api/test/test_batch_put_response.py similarity index 96% rename from memora-clients/python/memora_client_api/test/test_batch_put_response.py rename to hindsight-clients/python/hindsight_client_api/test/test_batch_put_response.py index 01a561552a..9b0ee817d4 100644 --- a/memora-clients/python/memora_client_api/test/test_batch_put_response.py +++ b/hindsight-clients/python/hindsight_client_api/test/test_batch_put_response.py @@ -14,7 +14,7 @@ import unittest -from memora_client_api.models.batch_put_response import BatchPutResponse +from hindsight_client_api.models.batch_put_response import BatchPutResponse class TestBatchPutResponse(unittest.TestCase): """BatchPutResponse unit test stubs""" diff --git a/memora-clients/python/memora_client_api/test/test_create_agent_request.py b/hindsight-clients/python/hindsight_client_api/test/test_create_agent_request.py similarity index 96% rename from memora-clients/python/memora_client_api/test/test_create_agent_request.py rename to hindsight-clients/python/hindsight_client_api/test/test_create_agent_request.py index 2baa987cef..352952af88 100644 --- a/memora-clients/python/memora_client_api/test/test_create_agent_request.py +++ b/hindsight-clients/python/hindsight_client_api/test/test_create_agent_request.py @@ -14,7 +14,7 @@ import unittest -from memora_client_api.models.create_agent_request import CreateAgentRequest +from hindsight_client_api.models.create_agent_request import CreateAgentRequest class TestCreateAgentRequest(unittest.TestCase): """CreateAgentRequest unit test stubs""" diff --git a/memora-clients/python/memora_client_api/test/test_delete_response.py b/hindsight-clients/python/hindsight_client_api/test/test_delete_response.py similarity index 96% rename from memora-clients/python/memora_client_api/test/test_delete_response.py rename to hindsight-clients/python/hindsight_client_api/test/test_delete_response.py index 57754c42e9..15ec97d4a4 100644 --- a/memora-clients/python/memora_client_api/test/test_delete_response.py +++ b/hindsight-clients/python/hindsight_client_api/test/test_delete_response.py @@ -14,7 +14,7 @@ import unittest -from memora_client_api.models.delete_response import DeleteResponse +from hindsight_client_api.models.delete_response import DeleteResponse class TestDeleteResponse(unittest.TestCase): """DeleteResponse unit test stubs""" diff --git a/memora-clients/python/memora_client_api/test/test_document_response.py b/hindsight-clients/python/hindsight_client_api/test/test_document_response.py similarity index 97% rename from memora-clients/python/memora_client_api/test/test_document_response.py rename to hindsight-clients/python/hindsight_client_api/test/test_document_response.py index 02783fdb76..9d93f4650e 100644 --- a/memora-clients/python/memora_client_api/test/test_document_response.py +++ b/hindsight-clients/python/hindsight_client_api/test/test_document_response.py @@ -14,7 +14,7 @@ import unittest -from memora_client_api.models.document_response import DocumentResponse +from hindsight_client_api.models.document_response import DocumentResponse class TestDocumentResponse(unittest.TestCase): """DocumentResponse unit test stubs""" diff --git a/memora-clients/python/memora_client_api/test/test_documents_api.py b/hindsight-clients/python/hindsight_client_api/test/test_documents_api.py similarity index 96% rename from memora-clients/python/memora_client_api/test/test_documents_api.py rename to hindsight-clients/python/hindsight_client_api/test/test_documents_api.py index a3190a7682..a4726e50fb 100644 --- a/memora-clients/python/memora_client_api/test/test_documents_api.py +++ b/hindsight-clients/python/hindsight_client_api/test/test_documents_api.py @@ -14,7 +14,7 @@ import unittest -from memora_client_api.api.documents_api import DocumentsApi +from hindsight_client_api.api.documents_api import DocumentsApi class TestDocumentsApi(unittest.IsolatedAsyncioTestCase): diff --git a/memora-clients/python/memora_client_api/test/test_graph_data_response.py b/hindsight-clients/python/hindsight_client_api/test/test_graph_data_response.py similarity index 97% rename from memora-clients/python/memora_client_api/test/test_graph_data_response.py rename to hindsight-clients/python/hindsight_client_api/test/test_graph_data_response.py index 1b45ee0a36..94009ae0d2 100644 --- a/memora-clients/python/memora_client_api/test/test_graph_data_response.py +++ b/hindsight-clients/python/hindsight_client_api/test/test_graph_data_response.py @@ -14,7 +14,7 @@ import unittest -from memora_client_api.models.graph_data_response import GraphDataResponse +from hindsight_client_api.models.graph_data_response import GraphDataResponse class TestGraphDataResponse(unittest.TestCase): """GraphDataResponse unit test stubs""" diff --git a/memora-clients/python/memora_client_api/test/test_http_validation_error.py b/hindsight-clients/python/hindsight_client_api/test/test_http_validation_error.py similarity index 93% rename from memora-clients/python/memora_client_api/test/test_http_validation_error.py rename to hindsight-clients/python/hindsight_client_api/test/test_http_validation_error.py index 1a18fae3d6..40f95b9f5f 100644 --- a/memora-clients/python/memora_client_api/test/test_http_validation_error.py +++ b/hindsight-clients/python/hindsight_client_api/test/test_http_validation_error.py @@ -14,7 +14,7 @@ import unittest -from memora_client_api.models.http_validation_error import HTTPValidationError +from hindsight_client_api.models.http_validation_error import HTTPValidationError class TestHTTPValidationError(unittest.TestCase): """HTTPValidationError unit test stubs""" @@ -36,7 +36,7 @@ def make_instance(self, include_optional) -> HTTPValidationError: if include_optional: return HTTPValidationError( detail = [ - memora_client_api.models.validation_error.ValidationError( + hindsight_client_api.models.validation_error.ValidationError( loc = [ null ], diff --git a/memora-clients/python/memora_client_api/test/test_list_documents_response.py b/hindsight-clients/python/hindsight_client_api/test/test_list_documents_response.py similarity index 96% rename from memora-clients/python/memora_client_api/test/test_list_documents_response.py rename to hindsight-clients/python/hindsight_client_api/test/test_list_documents_response.py index 3ce1d06f04..8834173e46 100644 --- a/memora-clients/python/memora_client_api/test/test_list_documents_response.py +++ b/hindsight-clients/python/hindsight_client_api/test/test_list_documents_response.py @@ -14,7 +14,7 @@ import unittest -from memora_client_api.models.list_documents_response import ListDocumentsResponse +from hindsight_client_api.models.list_documents_response import ListDocumentsResponse class TestListDocumentsResponse(unittest.TestCase): """ListDocumentsResponse unit test stubs""" diff --git a/memora-clients/python/memora_client_api/test/test_list_memory_units_response.py b/hindsight-clients/python/hindsight_client_api/test/test_list_memory_units_response.py similarity index 96% rename from memora-clients/python/memora_client_api/test/test_list_memory_units_response.py rename to hindsight-clients/python/hindsight_client_api/test/test_list_memory_units_response.py index a10f4036f6..d8fe3c2f9b 100644 --- a/memora-clients/python/memora_client_api/test/test_list_memory_units_response.py +++ b/hindsight-clients/python/hindsight_client_api/test/test_list_memory_units_response.py @@ -14,7 +14,7 @@ import unittest -from memora_client_api.models.list_memory_units_response import ListMemoryUnitsResponse +from hindsight_client_api.models.list_memory_units_response import ListMemoryUnitsResponse class TestListMemoryUnitsResponse(unittest.TestCase): """ListMemoryUnitsResponse unit test stubs""" diff --git a/memora-clients/python/memora_client_api/test/test_memory_item.py b/hindsight-clients/python/hindsight_client_api/test/test_memory_item.py similarity index 97% rename from memora-clients/python/memora_client_api/test/test_memory_item.py rename to hindsight-clients/python/hindsight_client_api/test/test_memory_item.py index 2d4f78f62b..65dd737230 100644 --- a/memora-clients/python/memora_client_api/test/test_memory_item.py +++ b/hindsight-clients/python/hindsight_client_api/test/test_memory_item.py @@ -14,7 +14,7 @@ import unittest -from memora_client_api.models.memory_item import MemoryItem +from hindsight_client_api.models.memory_item import MemoryItem class TestMemoryItem(unittest.TestCase): """MemoryItem unit test stubs""" diff --git a/memora-clients/python/memora_client_api/test/test_memory_operations_api.py b/hindsight-clients/python/hindsight_client_api/test/test_memory_operations_api.py similarity index 96% rename from memora-clients/python/memora_client_api/test/test_memory_operations_api.py rename to hindsight-clients/python/hindsight_client_api/test/test_memory_operations_api.py index 5c3c718654..49c5868d3d 100644 --- a/memora-clients/python/memora_client_api/test/test_memory_operations_api.py +++ b/hindsight-clients/python/hindsight_client_api/test/test_memory_operations_api.py @@ -14,7 +14,7 @@ import unittest -from memora_client_api.api.memory_operations_api import MemoryOperationsApi +from hindsight_client_api.api.memory_operations_api import MemoryOperationsApi class TestMemoryOperationsApi(unittest.IsolatedAsyncioTestCase): diff --git a/memora-clients/python/memora_client_api/test/test_personality_traits.py b/hindsight-clients/python/hindsight_client_api/test/test_personality_traits.py similarity index 97% rename from memora-clients/python/memora_client_api/test/test_personality_traits.py rename to hindsight-clients/python/hindsight_client_api/test/test_personality_traits.py index 1dc01b97b3..553a2cbdf6 100644 --- a/memora-clients/python/memora_client_api/test/test_personality_traits.py +++ b/hindsight-clients/python/hindsight_client_api/test/test_personality_traits.py @@ -14,7 +14,7 @@ import unittest -from memora_client_api.models.personality_traits import PersonalityTraits +from hindsight_client_api.models.personality_traits import PersonalityTraits class TestPersonalityTraits(unittest.TestCase): """PersonalityTraits unit test stubs""" diff --git a/memora-clients/python/memora_client_api/test/test_reasoning_api.py b/hindsight-clients/python/hindsight_client_api/test/test_reasoning_api.py similarity index 96% rename from memora-clients/python/memora_client_api/test/test_reasoning_api.py rename to hindsight-clients/python/hindsight_client_api/test/test_reasoning_api.py index 9ecb0a1590..aea9683df4 100644 --- a/memora-clients/python/memora_client_api/test/test_reasoning_api.py +++ b/hindsight-clients/python/hindsight_client_api/test/test_reasoning_api.py @@ -14,7 +14,7 @@ import unittest -from memora_client_api.api.reasoning_api import ReasoningApi +from hindsight_client_api.api.reasoning_api import ReasoningApi class TestReasoningApi(unittest.IsolatedAsyncioTestCase): diff --git a/memora-clients/python/memora_client_api/test/test_search_request.py b/hindsight-clients/python/hindsight_client_api/test/test_search_request.py similarity index 97% rename from memora-clients/python/memora_client_api/test/test_search_request.py rename to hindsight-clients/python/hindsight_client_api/test/test_search_request.py index a5ddf0c138..0a91aca98b 100644 --- a/memora-clients/python/memora_client_api/test/test_search_request.py +++ b/hindsight-clients/python/hindsight_client_api/test/test_search_request.py @@ -14,7 +14,7 @@ import unittest -from memora_client_api.models.search_request import SearchRequest +from hindsight_client_api.models.search_request import SearchRequest class TestSearchRequest(unittest.TestCase): """SearchRequest unit test stubs""" diff --git a/memora-clients/python/memora_client_api/test/test_search_response.py b/hindsight-clients/python/hindsight_client_api/test/test_search_response.py similarity index 97% rename from memora-clients/python/memora_client_api/test/test_search_response.py rename to hindsight-clients/python/hindsight_client_api/test/test_search_response.py index dea830f0ae..58a8ca26db 100644 --- a/memora-clients/python/memora_client_api/test/test_search_response.py +++ b/hindsight-clients/python/hindsight_client_api/test/test_search_response.py @@ -14,7 +14,7 @@ import unittest -from memora_client_api.models.search_response import SearchResponse +from hindsight_client_api.models.search_response import SearchResponse class TestSearchResponse(unittest.TestCase): """SearchResponse unit test stubs""" diff --git a/memora-clients/python/memora_client_api/test/test_search_result.py b/hindsight-clients/python/hindsight_client_api/test/test_search_result.py similarity index 97% rename from memora-clients/python/memora_client_api/test/test_search_result.py rename to hindsight-clients/python/hindsight_client_api/test/test_search_result.py index 3a87ea6f1b..fb907b55a1 100644 --- a/memora-clients/python/memora_client_api/test/test_search_result.py +++ b/hindsight-clients/python/hindsight_client_api/test/test_search_result.py @@ -14,7 +14,7 @@ import unittest -from memora_client_api.models.search_result import SearchResult +from hindsight_client_api.models.search_result import SearchResult class TestSearchResult(unittest.TestCase): """SearchResult unit test stubs""" diff --git a/memora-clients/python/memora_client_api/test/test_think_fact.py b/hindsight-clients/python/hindsight_client_api/test/test_think_fact.py similarity index 97% rename from memora-clients/python/memora_client_api/test/test_think_fact.py rename to hindsight-clients/python/hindsight_client_api/test/test_think_fact.py index b562bd5b05..52fcc21c43 100644 --- a/memora-clients/python/memora_client_api/test/test_think_fact.py +++ b/hindsight-clients/python/hindsight_client_api/test/test_think_fact.py @@ -14,7 +14,7 @@ import unittest -from memora_client_api.models.think_fact import ThinkFact +from hindsight_client_api.models.think_fact import ThinkFact class TestThinkFact(unittest.TestCase): """ThinkFact unit test stubs""" diff --git a/memora-clients/python/memora_client_api/test/test_think_request.py b/hindsight-clients/python/hindsight_client_api/test/test_think_request.py similarity index 97% rename from memora-clients/python/memora_client_api/test/test_think_request.py rename to hindsight-clients/python/hindsight_client_api/test/test_think_request.py index 0624d0224b..60d79b032c 100644 --- a/memora-clients/python/memora_client_api/test/test_think_request.py +++ b/hindsight-clients/python/hindsight_client_api/test/test_think_request.py @@ -14,7 +14,7 @@ import unittest -from memora_client_api.models.think_request import ThinkRequest +from hindsight_client_api.models.think_request import ThinkRequest class TestThinkRequest(unittest.TestCase): """ThinkRequest unit test stubs""" diff --git a/memora-clients/python/memora_client_api/test/test_think_response.py b/hindsight-clients/python/hindsight_client_api/test/test_think_response.py similarity index 97% rename from memora-clients/python/memora_client_api/test/test_think_response.py rename to hindsight-clients/python/hindsight_client_api/test/test_think_response.py index e3f7e05697..8dda73b168 100644 --- a/memora-clients/python/memora_client_api/test/test_think_response.py +++ b/hindsight-clients/python/hindsight_client_api/test/test_think_response.py @@ -14,7 +14,7 @@ import unittest -from memora_client_api.models.think_response import ThinkResponse +from hindsight_client_api.models.think_response import ThinkResponse class TestThinkResponse(unittest.TestCase): """ThinkResponse unit test stubs""" diff --git a/memora-clients/python/memora_client_api/test/test_update_personality_request.py b/hindsight-clients/python/hindsight_client_api/test/test_update_personality_request.py similarity index 96% rename from memora-clients/python/memora_client_api/test/test_update_personality_request.py rename to hindsight-clients/python/hindsight_client_api/test/test_update_personality_request.py index f2b8533fc3..d996ccc1e2 100644 --- a/memora-clients/python/memora_client_api/test/test_update_personality_request.py +++ b/hindsight-clients/python/hindsight_client_api/test/test_update_personality_request.py @@ -14,7 +14,7 @@ import unittest -from memora_client_api.models.update_personality_request import UpdatePersonalityRequest +from hindsight_client_api.models.update_personality_request import UpdatePersonalityRequest class TestUpdatePersonalityRequest(unittest.TestCase): """UpdatePersonalityRequest unit test stubs""" diff --git a/memora-clients/python/memora_client_api/test/test_validation_error.py b/hindsight-clients/python/hindsight_client_api/test/test_validation_error.py similarity index 97% rename from memora-clients/python/memora_client_api/test/test_validation_error.py rename to hindsight-clients/python/hindsight_client_api/test/test_validation_error.py index db1f133190..306187cd6f 100644 --- a/memora-clients/python/memora_client_api/test/test_validation_error.py +++ b/hindsight-clients/python/hindsight_client_api/test/test_validation_error.py @@ -14,7 +14,7 @@ import unittest -from memora_client_api.models.validation_error import ValidationError +from hindsight_client_api.models.validation_error import ValidationError class TestValidationError(unittest.TestCase): """ValidationError unit test stubs""" diff --git a/memora-clients/python/memora_client_api/test/test_validation_error_loc_inner.py b/hindsight-clients/python/hindsight_client_api/test/test_validation_error_loc_inner.py similarity index 96% rename from memora-clients/python/memora_client_api/test/test_validation_error_loc_inner.py rename to hindsight-clients/python/hindsight_client_api/test/test_validation_error_loc_inner.py index 361282645a..f59643ca5c 100644 --- a/memora-clients/python/memora_client_api/test/test_validation_error_loc_inner.py +++ b/hindsight-clients/python/hindsight_client_api/test/test_validation_error_loc_inner.py @@ -14,7 +14,7 @@ import unittest -from memora_client_api.models.validation_error_loc_inner import ValidationErrorLocInner +from hindsight_client_api.models.validation_error_loc_inner import ValidationErrorLocInner class TestValidationErrorLocInner(unittest.TestCase): """ValidationErrorLocInner unit test stubs""" diff --git a/memora-clients/python/memora_client_api/test/test_visualization_api.py b/hindsight-clients/python/hindsight_client_api/test/test_visualization_api.py similarity index 95% rename from memora-clients/python/memora_client_api/test/test_visualization_api.py rename to hindsight-clients/python/hindsight_client_api/test/test_visualization_api.py index 9ea1c99022..d994de7d7a 100644 --- a/memora-clients/python/memora_client_api/test/test_visualization_api.py +++ b/hindsight-clients/python/hindsight_client_api/test/test_visualization_api.py @@ -14,7 +14,7 @@ import unittest -from memora_client_api.api.visualization_api import VisualizationApi +from hindsight_client_api.api.visualization_api import VisualizationApi class TestVisualizationApi(unittest.IsolatedAsyncioTestCase): diff --git a/memora-clients/python/openapi-generator-config.yaml b/hindsight-clients/python/openapi-generator-config.yaml similarity index 51% rename from memora-clients/python/openapi-generator-config.yaml rename to hindsight-clients/python/openapi-generator-config.yaml index 23ced19dac..33e378e73d 100644 --- a/memora-clients/python/openapi-generator-config.yaml +++ b/hindsight-clients/python/openapi-generator-config.yaml @@ -1,5 +1,5 @@ -packageName: memora_client_api -projectName: memora-client +packageName: hindsight_client_api +projectName: hindsight-client packageVersion: 0.0.7 library: asyncio generateSourceCodeOnly: true diff --git a/memora-clients/python/pyproject.toml b/hindsight-clients/python/pyproject.toml similarity index 51% rename from memora-clients/python/pyproject.toml rename to hindsight-clients/python/pyproject.toml index 233f059b42..95e5641a9b 100644 --- a/memora-clients/python/pyproject.toml +++ b/hindsight-clients/python/pyproject.toml @@ -1,9 +1,9 @@ [project] -name = "memora-client" +name = "hindsight-client" version = "0.0.7" -description = "Python client for Memora - Semantic memory system with personality-driven thinking" +description = "Python client for Hindsight - Semantic memory system with personality-driven thinking" authors = [ - {name = "Memora Team"} + {name = "Hindsight Team"} ] requires-python = ">=3.10" readme = "README.md" @@ -27,10 +27,21 @@ requires = ["hatchling"] build-backend = "hatchling.build" [tool.hatch.build.targets.wheel] -packages = ["memora_client", "memora_client_api"] +packages = ["hindsight_client", "hindsight_client_api"] [tool.ruff] line-length = 120 [tool.ruff.lint] select = ["F", "I", "UP"] + + +[tool.pytest.ini_options] +log_cli = true +log_cli_level = "INFO" +log_cli_format = "%(asctime)s %(levelname)s %(message)s" +log_cli_date_format = "%Y-%m-%d %H:%M:%S" +addopts = "--timeout 60 -n auto --durations=10 -v" +asyncio_mode = "auto" +asyncio_default_fixture_loop_scope = "function" +log_auto_indent = true \ No newline at end of file diff --git a/memora-clients/python/tests/__init__.py b/hindsight-clients/python/tests/__init__.py similarity index 100% rename from memora-clients/python/tests/__init__.py rename to hindsight-clients/python/tests/__init__.py diff --git a/memora-clients/python/tests/test_main_operations.py b/hindsight-clients/python/tests/test_main_operations.py similarity index 95% rename from memora-clients/python/tests/test_main_operations.py rename to hindsight-clients/python/tests/test_main_operations.py index 18ada818d7..14cabe4c58 100644 --- a/memora-clients/python/tests/test_main_operations.py +++ b/hindsight-clients/python/tests/test_main_operations.py @@ -1,24 +1,23 @@ """ -Integration tests for main Memora operations. -These tests require a running Memora API server. +These tests require a running Hindsight API server. """ import os import pytest from datetime import datetime -from memora_client import Memora +from hindsight_client import Hindsight # Test configuration -MEMORA_API_URL = os.getenv("MEMORA_API_URL", "http://localhost:8080") +HINDSIGHT_API_URL = os.getenv("HINDSIGHT_API_URL", "http://localhost:8888") TEST_AGENT_ID = "test_agent_" + datetime.now().strftime("%Y%m%d_%H%M%S") @pytest.fixture def client(): - """Create a Memora client for testing.""" - with Memora(base_url=MEMORA_API_URL) as client: + """Create a Hindsight client for testing.""" + with Hindsight(base_url=HINDSIGHT_API_URL) as client: yield client @@ -218,7 +217,6 @@ def test_list_with_pagination(self, client, agent_id): assert len(response["items"]) <= 2 -@pytest.mark.integration class TestEndToEndWorkflow: """End-to-end workflow tests.""" @@ -258,8 +256,3 @@ def test_complete_workflow(self, client): ) assert "text" in think_response assert len(think_response["text"]) > 0 - - -if __name__ == "__main__": - # Run tests with pytest - pytest.main([__file__, "-v", "-s"]) diff --git a/memora-clients/typescript/.gitignore b/hindsight-clients/typescript/.gitignore similarity index 100% rename from memora-clients/typescript/.gitignore rename to hindsight-clients/typescript/.gitignore diff --git a/memora-clients/typescript/.npmignore b/hindsight-clients/typescript/.npmignore similarity index 100% rename from memora-clients/typescript/.npmignore rename to hindsight-clients/typescript/.npmignore diff --git a/memora-clients/typescript/README.md b/hindsight-clients/typescript/README.md similarity index 72% rename from memora-clients/typescript/README.md rename to hindsight-clients/typescript/README.md index ee89bab8cb..46d47cd9c7 100644 --- a/memora-clients/typescript/README.md +++ b/hindsight-clients/typescript/README.md @@ -1,24 +1,24 @@ -# @memora/client +# @hindsight/client -TypeScript client for Memora - Semantic memory system with personality-driven thinking. +TypeScript client for Hindsight - Semantic memory system with personality-driven thinking. -**Auto-generated from OpenAPI spec** - provides type-safe access to all Memora API endpoints. +**Auto-generated from OpenAPI spec** - provides type-safe access to all Hindsight API endpoints. ## Installation ```bash -npm install @memora/client +npm install @hindsight/client # or -yarn add @memora/client +yarn add @hindsight/client ``` ## Quick Start ```typescript -import { OpenAPI, MemoryStorageService, ReasoningService } from '@memora/client'; +import { OpenAPI, MemoryStorageService, ReasoningService } from '@hindsight/client'; // Configure API base URL -OpenAPI.BASE = 'http://localhost:8000'; +OpenAPI.BASE = 'http://localhost:8888'; // Store memory await MemoryStorageService.putApiPutPost({ @@ -53,5 +53,5 @@ Auto-generated from `openapi.json`. See [RELEASE.md](../../RELEASE.md) for regen ## Links -- [GitHub Repository](https://github.com/nicoloboschi/memora) -- [Full Documentation](https://github.com/nicoloboschi/memora/blob/main/README.md) +- [GitHub Repository](https://github.com/vectorize-io/hindsight) +- [Full Documentation](https://github.com/vectorize-io/hindsight/blob/main/README.md) diff --git a/hindsight-clients/typescript/generated/client.gen.ts b/hindsight-clients/typescript/generated/client.gen.ts new file mode 100644 index 0000000000..cab3c70195 --- /dev/null +++ b/hindsight-clients/typescript/generated/client.gen.ts @@ -0,0 +1,16 @@ +// This file is auto-generated by @hey-api/openapi-ts + +import { type ClientOptions, type Config, createClient, createConfig } from './client'; +import type { ClientOptions as ClientOptions2 } from './types.gen'; + +/** + * The `createClientConfig()` function will be called on client initialization + * and the returned object will become the client's initial configuration. + * + * You may want to initialize your client this way instead of calling + * `setConfig()`. This is useful for example if you're using Next.js + * to ensure your client always has the correct values. + */ +export type CreateClientConfig = (override?: Config) => Config & T>; + +export const client = createClient(createConfig()); diff --git a/hindsight-clients/typescript/generated/client/client.gen.ts b/hindsight-clients/typescript/generated/client/client.gen.ts new file mode 100644 index 0000000000..c2a5190c22 --- /dev/null +++ b/hindsight-clients/typescript/generated/client/client.gen.ts @@ -0,0 +1,301 @@ +// This file is auto-generated by @hey-api/openapi-ts + +import { createSseClient } from '../core/serverSentEvents.gen'; +import type { HttpMethod } from '../core/types.gen'; +import { getValidRequestBody } from '../core/utils.gen'; +import type { + Client, + Config, + RequestOptions, + ResolvedRequestOptions, +} from './types.gen'; +import { + buildUrl, + createConfig, + createInterceptors, + getParseAs, + mergeConfigs, + mergeHeaders, + setAuthParams, +} from './utils.gen'; + +type ReqInit = Omit & { + body?: any; + headers: ReturnType; +}; + +export const createClient = (config: Config = {}): Client => { + let _config = mergeConfigs(createConfig(), config); + + const getConfig = (): Config => ({ ..._config }); + + const setConfig = (config: Config): Config => { + _config = mergeConfigs(_config, config); + return getConfig(); + }; + + const interceptors = createInterceptors< + Request, + Response, + unknown, + ResolvedRequestOptions + >(); + + const beforeRequest = async (options: RequestOptions) => { + const opts = { + ..._config, + ...options, + fetch: options.fetch ?? _config.fetch ?? globalThis.fetch, + headers: mergeHeaders(_config.headers, options.headers), + serializedBody: undefined, + }; + + if (opts.security) { + await setAuthParams({ + ...opts, + security: opts.security, + }); + } + + if (opts.requestValidator) { + await opts.requestValidator(opts); + } + + if (opts.body !== undefined && opts.bodySerializer) { + opts.serializedBody = opts.bodySerializer(opts.body); + } + + // remove Content-Type header if body is empty to avoid sending invalid requests + if (opts.body === undefined || opts.serializedBody === '') { + opts.headers.delete('Content-Type'); + } + + const url = buildUrl(opts); + + return { opts, url }; + }; + + const request: Client['request'] = async (options) => { + // @ts-expect-error + const { opts, url } = await beforeRequest(options); + const requestInit: ReqInit = { + redirect: 'follow', + ...opts, + body: getValidRequestBody(opts), + }; + + let request = new Request(url, requestInit); + + for (const fn of interceptors.request.fns) { + if (fn) { + request = await fn(request, opts); + } + } + + // fetch must be assigned here, otherwise it would throw the error: + // TypeError: Failed to execute 'fetch' on 'Window': Illegal invocation + const _fetch = opts.fetch!; + let response: Response; + + try { + response = await _fetch(request); + } catch (error) { + // Handle fetch exceptions (AbortError, network errors, etc.) + let finalError = error; + + for (const fn of interceptors.error.fns) { + if (fn) { + finalError = (await fn( + error, + undefined as any, + request, + opts, + )) as unknown; + } + } + + finalError = finalError || ({} as unknown); + + if (opts.throwOnError) { + throw finalError; + } + + // Return error response + return opts.responseStyle === 'data' + ? undefined + : { + error: finalError, + request, + response: undefined as any, + }; + } + + for (const fn of interceptors.response.fns) { + if (fn) { + response = await fn(response, request, opts); + } + } + + const result = { + request, + response, + }; + + if (response.ok) { + const parseAs = + (opts.parseAs === 'auto' + ? getParseAs(response.headers.get('Content-Type')) + : opts.parseAs) ?? 'json'; + + if ( + response.status === 204 || + response.headers.get('Content-Length') === '0' + ) { + let emptyData: any; + switch (parseAs) { + case 'arrayBuffer': + case 'blob': + case 'text': + emptyData = await response[parseAs](); + break; + case 'formData': + emptyData = new FormData(); + break; + case 'stream': + emptyData = response.body; + break; + case 'json': + default: + emptyData = {}; + break; + } + return opts.responseStyle === 'data' + ? emptyData + : { + data: emptyData, + ...result, + }; + } + + let data: any; + switch (parseAs) { + case 'arrayBuffer': + case 'blob': + case 'formData': + case 'json': + case 'text': + data = await response[parseAs](); + break; + case 'stream': + return opts.responseStyle === 'data' + ? response.body + : { + data: response.body, + ...result, + }; + } + + if (parseAs === 'json') { + if (opts.responseValidator) { + await opts.responseValidator(data); + } + + if (opts.responseTransformer) { + data = await opts.responseTransformer(data); + } + } + + return opts.responseStyle === 'data' + ? data + : { + data, + ...result, + }; + } + + const textError = await response.text(); + let jsonError: unknown; + + try { + jsonError = JSON.parse(textError); + } catch { + // noop + } + + const error = jsonError ?? textError; + let finalError = error; + + for (const fn of interceptors.error.fns) { + if (fn) { + finalError = (await fn(error, response, request, opts)) as string; + } + } + + finalError = finalError || ({} as string); + + if (opts.throwOnError) { + throw finalError; + } + + // TODO: we probably want to return error and improve types + return opts.responseStyle === 'data' + ? undefined + : { + error: finalError, + ...result, + }; + }; + + const makeMethodFn = + (method: Uppercase) => (options: RequestOptions) => + request({ ...options, method }); + + const makeSseFn = + (method: Uppercase) => async (options: RequestOptions) => { + const { opts, url } = await beforeRequest(options); + return createSseClient({ + ...opts, + body: opts.body as BodyInit | null | undefined, + headers: opts.headers as unknown as Record, + method, + onRequest: async (url, init) => { + let request = new Request(url, init); + for (const fn of interceptors.request.fns) { + if (fn) { + request = await fn(request, opts); + } + } + return request; + }, + url, + }); + }; + + return { + buildUrl, + connect: makeMethodFn('CONNECT'), + delete: makeMethodFn('DELETE'), + get: makeMethodFn('GET'), + getConfig, + head: makeMethodFn('HEAD'), + interceptors, + options: makeMethodFn('OPTIONS'), + patch: makeMethodFn('PATCH'), + post: makeMethodFn('POST'), + put: makeMethodFn('PUT'), + request, + setConfig, + sse: { + connect: makeSseFn('CONNECT'), + delete: makeSseFn('DELETE'), + get: makeSseFn('GET'), + head: makeSseFn('HEAD'), + options: makeSseFn('OPTIONS'), + patch: makeSseFn('PATCH'), + post: makeSseFn('POST'), + put: makeSseFn('PUT'), + trace: makeSseFn('TRACE'), + }, + trace: makeMethodFn('TRACE'), + } as Client; +}; diff --git a/hindsight-clients/typescript/generated/client/index.ts b/hindsight-clients/typescript/generated/client/index.ts new file mode 100644 index 0000000000..b295edeca0 --- /dev/null +++ b/hindsight-clients/typescript/generated/client/index.ts @@ -0,0 +1,25 @@ +// This file is auto-generated by @hey-api/openapi-ts + +export type { Auth } from '../core/auth.gen'; +export type { QuerySerializerOptions } from '../core/bodySerializer.gen'; +export { + formDataBodySerializer, + jsonBodySerializer, + urlSearchParamsBodySerializer, +} from '../core/bodySerializer.gen'; +export { buildClientParams } from '../core/params.gen'; +export { serializeQueryKeyValue } from '../core/queryKeySerializer.gen'; +export { createClient } from './client.gen'; +export type { + Client, + ClientOptions, + Config, + CreateClientConfig, + Options, + RequestOptions, + RequestResult, + ResolvedRequestOptions, + ResponseStyle, + TDataShape, +} from './types.gen'; +export { createConfig, mergeHeaders } from './utils.gen'; diff --git a/hindsight-clients/typescript/generated/client/types.gen.ts b/hindsight-clients/typescript/generated/client/types.gen.ts new file mode 100644 index 0000000000..b4a499cc03 --- /dev/null +++ b/hindsight-clients/typescript/generated/client/types.gen.ts @@ -0,0 +1,241 @@ +// This file is auto-generated by @hey-api/openapi-ts + +import type { Auth } from '../core/auth.gen'; +import type { + ServerSentEventsOptions, + ServerSentEventsResult, +} from '../core/serverSentEvents.gen'; +import type { + Client as CoreClient, + Config as CoreConfig, +} from '../core/types.gen'; +import type { Middleware } from './utils.gen'; + +export type ResponseStyle = 'data' | 'fields'; + +export interface Config + extends Omit, + CoreConfig { + /** + * Base URL for all requests made by this client. + */ + baseUrl?: T['baseUrl']; + /** + * Fetch API implementation. You can use this option to provide a custom + * fetch instance. + * + * @default globalThis.fetch + */ + fetch?: typeof fetch; + /** + * Please don't use the Fetch client for Next.js applications. The `next` + * options won't have any effect. + * + * Install {@link https://www.npmjs.com/package/@hey-api/client-next `@hey-api/client-next`} instead. + */ + next?: never; + /** + * Return the response data parsed in a specified format. By default, `auto` + * will infer the appropriate method from the `Content-Type` response header. + * You can override this behavior with any of the {@link Body} methods. + * Select `stream` if you don't want to parse response data at all. + * + * @default 'auto' + */ + parseAs?: + | 'arrayBuffer' + | 'auto' + | 'blob' + | 'formData' + | 'json' + | 'stream' + | 'text'; + /** + * Should we return only data or multiple fields (data, error, response, etc.)? + * + * @default 'fields' + */ + responseStyle?: ResponseStyle; + /** + * Throw an error instead of returning it in the response? + * + * @default false + */ + throwOnError?: T['throwOnError']; +} + +export interface RequestOptions< + TData = unknown, + TResponseStyle extends ResponseStyle = 'fields', + ThrowOnError extends boolean = boolean, + Url extends string = string, +> extends Config<{ + responseStyle: TResponseStyle; + throwOnError: ThrowOnError; + }>, + Pick< + ServerSentEventsOptions, + | 'onSseError' + | 'onSseEvent' + | 'sseDefaultRetryDelay' + | 'sseMaxRetryAttempts' + | 'sseMaxRetryDelay' + > { + /** + * Any body that you want to add to your request. + * + * {@link https://developer.mozilla.org/docs/Web/API/fetch#body} + */ + body?: unknown; + path?: Record; + query?: Record; + /** + * Security mechanism(s) to use for the request. + */ + security?: ReadonlyArray; + url: Url; +} + +export interface ResolvedRequestOptions< + TResponseStyle extends ResponseStyle = 'fields', + ThrowOnError extends boolean = boolean, + Url extends string = string, +> extends RequestOptions { + serializedBody?: string; +} + +export type RequestResult< + TData = unknown, + TError = unknown, + ThrowOnError extends boolean = boolean, + TResponseStyle extends ResponseStyle = 'fields', +> = ThrowOnError extends true + ? Promise< + TResponseStyle extends 'data' + ? TData extends Record + ? TData[keyof TData] + : TData + : { + data: TData extends Record + ? TData[keyof TData] + : TData; + request: Request; + response: Response; + } + > + : Promise< + TResponseStyle extends 'data' + ? + | (TData extends Record + ? TData[keyof TData] + : TData) + | undefined + : ( + | { + data: TData extends Record + ? TData[keyof TData] + : TData; + error: undefined; + } + | { + data: undefined; + error: TError extends Record + ? TError[keyof TError] + : TError; + } + ) & { + request: Request; + response: Response; + } + >; + +export interface ClientOptions { + baseUrl?: string; + responseStyle?: ResponseStyle; + throwOnError?: boolean; +} + +type MethodFn = < + TData = unknown, + TError = unknown, + ThrowOnError extends boolean = false, + TResponseStyle extends ResponseStyle = 'fields', +>( + options: Omit, 'method'>, +) => RequestResult; + +type SseFn = < + TData = unknown, + TError = unknown, + ThrowOnError extends boolean = false, + TResponseStyle extends ResponseStyle = 'fields', +>( + options: Omit, 'method'>, +) => Promise>; + +type RequestFn = < + TData = unknown, + TError = unknown, + ThrowOnError extends boolean = false, + TResponseStyle extends ResponseStyle = 'fields', +>( + options: Omit, 'method'> & + Pick< + Required>, + 'method' + >, +) => RequestResult; + +type BuildUrlFn = < + TData extends { + body?: unknown; + path?: Record; + query?: Record; + url: string; + }, +>( + options: TData & Options, +) => string; + +export type Client = CoreClient< + RequestFn, + Config, + MethodFn, + BuildUrlFn, + SseFn +> & { + interceptors: Middleware; +}; + +/** + * The `createClientConfig()` function will be called on client initialization + * and the returned object will become the client's initial configuration. + * + * You may want to initialize your client this way instead of calling + * `setConfig()`. This is useful for example if you're using Next.js + * to ensure your client always has the correct values. + */ +export type CreateClientConfig = ( + override?: Config, +) => Config & T>; + +export interface TDataShape { + body?: unknown; + headers?: unknown; + path?: unknown; + query?: unknown; + url: string; +} + +type OmitKeys = Pick>; + +export type Options< + TData extends TDataShape = TDataShape, + ThrowOnError extends boolean = boolean, + TResponse = unknown, + TResponseStyle extends ResponseStyle = 'fields', +> = OmitKeys< + RequestOptions, + 'body' | 'path' | 'query' | 'url' +> & + ([TData] extends [never] ? unknown : Omit); diff --git a/hindsight-clients/typescript/generated/client/utils.gen.ts b/hindsight-clients/typescript/generated/client/utils.gen.ts new file mode 100644 index 0000000000..4c48a9ee11 --- /dev/null +++ b/hindsight-clients/typescript/generated/client/utils.gen.ts @@ -0,0 +1,332 @@ +// This file is auto-generated by @hey-api/openapi-ts + +import { getAuthToken } from '../core/auth.gen'; +import type { QuerySerializerOptions } from '../core/bodySerializer.gen'; +import { jsonBodySerializer } from '../core/bodySerializer.gen'; +import { + serializeArrayParam, + serializeObjectParam, + serializePrimitiveParam, +} from '../core/pathSerializer.gen'; +import { getUrl } from '../core/utils.gen'; +import type { Client, ClientOptions, Config, RequestOptions } from './types.gen'; + +export const createQuerySerializer = ({ + parameters = {}, + ...args +}: QuerySerializerOptions = {}) => { + const querySerializer = (queryParams: T) => { + const search: string[] = []; + if (queryParams && typeof queryParams === 'object') { + for (const name in queryParams) { + const value = queryParams[name]; + + if (value === undefined || value === null) { + continue; + } + + const options = parameters[name] || args; + + if (Array.isArray(value)) { + const serializedArray = serializeArrayParam({ + allowReserved: options.allowReserved, + explode: true, + name, + style: 'form', + value, + ...options.array, + }); + if (serializedArray) search.push(serializedArray); + } else if (typeof value === 'object') { + const serializedObject = serializeObjectParam({ + allowReserved: options.allowReserved, + explode: true, + name, + style: 'deepObject', + value: value as Record, + ...options.object, + }); + if (serializedObject) search.push(serializedObject); + } else { + const serializedPrimitive = serializePrimitiveParam({ + allowReserved: options.allowReserved, + name, + value: value as string, + }); + if (serializedPrimitive) search.push(serializedPrimitive); + } + } + } + return search.join('&'); + }; + return querySerializer; +}; + +/** + * Infers parseAs value from provided Content-Type header. + */ +export const getParseAs = ( + contentType: string | null, +): Exclude => { + if (!contentType) { + // If no Content-Type header is provided, the best we can do is return the raw response body, + // which is effectively the same as the 'stream' option. + return 'stream'; + } + + const cleanContent = contentType.split(';')[0]?.trim(); + + if (!cleanContent) { + return; + } + + if ( + cleanContent.startsWith('application/json') || + cleanContent.endsWith('+json') + ) { + return 'json'; + } + + if (cleanContent === 'multipart/form-data') { + return 'formData'; + } + + if ( + ['application/', 'audio/', 'image/', 'video/'].some((type) => + cleanContent.startsWith(type), + ) + ) { + return 'blob'; + } + + if (cleanContent.startsWith('text/')) { + return 'text'; + } + + return; +}; + +const checkForExistence = ( + options: Pick & { + headers: Headers; + }, + name?: string, +): boolean => { + if (!name) { + return false; + } + if ( + options.headers.has(name) || + options.query?.[name] || + options.headers.get('Cookie')?.includes(`${name}=`) + ) { + return true; + } + return false; +}; + +export const setAuthParams = async ({ + security, + ...options +}: Pick, 'security'> & + Pick & { + headers: Headers; + }) => { + for (const auth of security) { + if (checkForExistence(options, auth.name)) { + continue; + } + + const token = await getAuthToken(auth, options.auth); + + if (!token) { + continue; + } + + const name = auth.name ?? 'Authorization'; + + switch (auth.in) { + case 'query': + if (!options.query) { + options.query = {}; + } + options.query[name] = token; + break; + case 'cookie': + options.headers.append('Cookie', `${name}=${token}`); + break; + case 'header': + default: + options.headers.set(name, token); + break; + } + } +}; + +export const buildUrl: Client['buildUrl'] = (options) => + getUrl({ + baseUrl: options.baseUrl as string, + path: options.path, + query: options.query, + querySerializer: + typeof options.querySerializer === 'function' + ? options.querySerializer + : createQuerySerializer(options.querySerializer), + url: options.url, + }); + +export const mergeConfigs = (a: Config, b: Config): Config => { + const config = { ...a, ...b }; + if (config.baseUrl?.endsWith('/')) { + config.baseUrl = config.baseUrl.substring(0, config.baseUrl.length - 1); + } + config.headers = mergeHeaders(a.headers, b.headers); + return config; +}; + +const headersEntries = (headers: Headers): Array<[string, string]> => { + const entries: Array<[string, string]> = []; + headers.forEach((value, key) => { + entries.push([key, value]); + }); + return entries; +}; + +export const mergeHeaders = ( + ...headers: Array['headers'] | undefined> +): Headers => { + const mergedHeaders = new Headers(); + for (const header of headers) { + if (!header) { + continue; + } + + const iterator = + header instanceof Headers + ? headersEntries(header) + : Object.entries(header); + + for (const [key, value] of iterator) { + if (value === null) { + mergedHeaders.delete(key); + } else if (Array.isArray(value)) { + for (const v of value) { + mergedHeaders.append(key, v as string); + } + } else if (value !== undefined) { + // assume object headers are meant to be JSON stringified, i.e. their + // content value in OpenAPI specification is 'application/json' + mergedHeaders.set( + key, + typeof value === 'object' ? JSON.stringify(value) : (value as string), + ); + } + } + } + return mergedHeaders; +}; + +type ErrInterceptor = ( + error: Err, + response: Res, + request: Req, + options: Options, +) => Err | Promise; + +type ReqInterceptor = ( + request: Req, + options: Options, +) => Req | Promise; + +type ResInterceptor = ( + response: Res, + request: Req, + options: Options, +) => Res | Promise; + +class Interceptors { + fns: Array = []; + + clear(): void { + this.fns = []; + } + + eject(id: number | Interceptor): void { + const index = this.getInterceptorIndex(id); + if (this.fns[index]) { + this.fns[index] = null; + } + } + + exists(id: number | Interceptor): boolean { + const index = this.getInterceptorIndex(id); + return Boolean(this.fns[index]); + } + + getInterceptorIndex(id: number | Interceptor): number { + if (typeof id === 'number') { + return this.fns[id] ? id : -1; + } + return this.fns.indexOf(id); + } + + update( + id: number | Interceptor, + fn: Interceptor, + ): number | Interceptor | false { + const index = this.getInterceptorIndex(id); + if (this.fns[index]) { + this.fns[index] = fn; + return id; + } + return false; + } + + use(fn: Interceptor): number { + this.fns.push(fn); + return this.fns.length - 1; + } +} + +export interface Middleware { + error: Interceptors>; + request: Interceptors>; + response: Interceptors>; +} + +export const createInterceptors = (): Middleware< + Req, + Res, + Err, + Options +> => ({ + error: new Interceptors>(), + request: new Interceptors>(), + response: new Interceptors>(), +}); + +const defaultQuerySerializer = createQuerySerializer({ + allowReserved: false, + array: { + explode: true, + style: 'form', + }, + object: { + explode: true, + style: 'deepObject', + }, +}); + +const defaultHeaders = { + 'Content-Type': 'application/json', +}; + +export const createConfig = ( + override: Config & T> = {}, +): Config & T> => ({ + ...jsonBodySerializer, + headers: defaultHeaders, + parseAs: 'auto', + querySerializer: defaultQuerySerializer, + ...override, +}); diff --git a/hindsight-clients/typescript/generated/core/auth.gen.ts b/hindsight-clients/typescript/generated/core/auth.gen.ts new file mode 100644 index 0000000000..f8a73266f9 --- /dev/null +++ b/hindsight-clients/typescript/generated/core/auth.gen.ts @@ -0,0 +1,42 @@ +// This file is auto-generated by @hey-api/openapi-ts + +export type AuthToken = string | undefined; + +export interface Auth { + /** + * Which part of the request do we use to send the auth? + * + * @default 'header' + */ + in?: 'header' | 'query' | 'cookie'; + /** + * Header or query parameter name. + * + * @default 'Authorization' + */ + name?: string; + scheme?: 'basic' | 'bearer'; + type: 'apiKey' | 'http'; +} + +export const getAuthToken = async ( + auth: Auth, + callback: ((auth: Auth) => Promise | AuthToken) | AuthToken, +): Promise => { + const token = + typeof callback === 'function' ? await callback(auth) : callback; + + if (!token) { + return; + } + + if (auth.scheme === 'bearer') { + return `Bearer ${token}`; + } + + if (auth.scheme === 'basic') { + return `Basic ${btoa(token)}`; + } + + return token; +}; diff --git a/hindsight-clients/typescript/generated/core/bodySerializer.gen.ts b/hindsight-clients/typescript/generated/core/bodySerializer.gen.ts new file mode 100644 index 0000000000..552b50f7c8 --- /dev/null +++ b/hindsight-clients/typescript/generated/core/bodySerializer.gen.ts @@ -0,0 +1,100 @@ +// This file is auto-generated by @hey-api/openapi-ts + +import type { + ArrayStyle, + ObjectStyle, + SerializerOptions, +} from './pathSerializer.gen'; + +export type QuerySerializer = (query: Record) => string; + +export type BodySerializer = (body: any) => any; + +type QuerySerializerOptionsObject = { + allowReserved?: boolean; + array?: Partial>; + object?: Partial>; +}; + +export type QuerySerializerOptions = QuerySerializerOptionsObject & { + /** + * Per-parameter serialization overrides. When provided, these settings + * override the global array/object settings for specific parameter names. + */ + parameters?: Record; +}; + +const serializeFormDataPair = ( + data: FormData, + key: string, + value: unknown, +): void => { + if (typeof value === 'string' || value instanceof Blob) { + data.append(key, value); + } else if (value instanceof Date) { + data.append(key, value.toISOString()); + } else { + data.append(key, JSON.stringify(value)); + } +}; + +const serializeUrlSearchParamsPair = ( + data: URLSearchParams, + key: string, + value: unknown, +): void => { + if (typeof value === 'string') { + data.append(key, value); + } else { + data.append(key, JSON.stringify(value)); + } +}; + +export const formDataBodySerializer = { + bodySerializer: | Array>>( + body: T, + ): FormData => { + const data = new FormData(); + + Object.entries(body).forEach(([key, value]) => { + if (value === undefined || value === null) { + return; + } + if (Array.isArray(value)) { + value.forEach((v) => serializeFormDataPair(data, key, v)); + } else { + serializeFormDataPair(data, key, value); + } + }); + + return data; + }, +}; + +export const jsonBodySerializer = { + bodySerializer: (body: T): string => + JSON.stringify(body, (_key, value) => + typeof value === 'bigint' ? value.toString() : value, + ), +}; + +export const urlSearchParamsBodySerializer = { + bodySerializer: | Array>>( + body: T, + ): string => { + const data = new URLSearchParams(); + + Object.entries(body).forEach(([key, value]) => { + if (value === undefined || value === null) { + return; + } + if (Array.isArray(value)) { + value.forEach((v) => serializeUrlSearchParamsPair(data, key, v)); + } else { + serializeUrlSearchParamsPair(data, key, value); + } + }); + + return data.toString(); + }, +}; diff --git a/hindsight-clients/typescript/generated/core/params.gen.ts b/hindsight-clients/typescript/generated/core/params.gen.ts new file mode 100644 index 0000000000..602715c46c --- /dev/null +++ b/hindsight-clients/typescript/generated/core/params.gen.ts @@ -0,0 +1,176 @@ +// This file is auto-generated by @hey-api/openapi-ts + +type Slot = 'body' | 'headers' | 'path' | 'query'; + +export type Field = + | { + in: Exclude; + /** + * Field name. This is the name we want the user to see and use. + */ + key: string; + /** + * Field mapped name. This is the name we want to use in the request. + * If omitted, we use the same value as `key`. + */ + map?: string; + } + | { + in: Extract; + /** + * Key isn't required for bodies. + */ + key?: string; + map?: string; + } + | { + /** + * Field name. This is the name we want the user to see and use. + */ + key: string; + /** + * Field mapped name. This is the name we want to use in the request. + * If `in` is omitted, `map` aliases `key` to the transport layer. + */ + map: Slot; + }; + +export interface Fields { + allowExtra?: Partial>; + args?: ReadonlyArray; +} + +export type FieldsConfig = ReadonlyArray; + +const extraPrefixesMap: Record = { + $body_: 'body', + $headers_: 'headers', + $path_: 'path', + $query_: 'query', +}; +const extraPrefixes = Object.entries(extraPrefixesMap); + +type KeyMap = Map< + string, + | { + in: Slot; + map?: string; + } + | { + in?: never; + map: Slot; + } +>; + +const buildKeyMap = (fields: FieldsConfig, map?: KeyMap): KeyMap => { + if (!map) { + map = new Map(); + } + + for (const config of fields) { + if ('in' in config) { + if (config.key) { + map.set(config.key, { + in: config.in, + map: config.map, + }); + } + } else if ('key' in config) { + map.set(config.key, { + map: config.map, + }); + } else if (config.args) { + buildKeyMap(config.args, map); + } + } + + return map; +}; + +interface Params { + body: unknown; + headers: Record; + path: Record; + query: Record; +} + +const stripEmptySlots = (params: Params) => { + for (const [slot, value] of Object.entries(params)) { + if (value && typeof value === 'object' && !Object.keys(value).length) { + delete params[slot as Slot]; + } + } +}; + +export const buildClientParams = ( + args: ReadonlyArray, + fields: FieldsConfig, +) => { + const params: Params = { + body: {}, + headers: {}, + path: {}, + query: {}, + }; + + const map = buildKeyMap(fields); + + let config: FieldsConfig[number] | undefined; + + for (const [index, arg] of args.entries()) { + if (fields[index]) { + config = fields[index]; + } + + if (!config) { + continue; + } + + if ('in' in config) { + if (config.key) { + const field = map.get(config.key)!; + const name = field.map || config.key; + if (field.in) { + (params[field.in] as Record)[name] = arg; + } + } else { + params.body = arg; + } + } else { + for (const [key, value] of Object.entries(arg ?? {})) { + const field = map.get(key); + + if (field) { + if (field.in) { + const name = field.map || key; + (params[field.in] as Record)[name] = value; + } else { + params[field.map] = value; + } + } else { + const extra = extraPrefixes.find(([prefix]) => + key.startsWith(prefix), + ); + + if (extra) { + const [prefix, slot] = extra; + (params[slot] as Record)[ + key.slice(prefix.length) + ] = value; + } else if ('allowExtra' in config && config.allowExtra) { + for (const [slot, allowed] of Object.entries(config.allowExtra)) { + if (allowed) { + (params[slot as Slot] as Record)[key] = value; + break; + } + } + } + } + } + } + } + + stripEmptySlots(params); + + return params; +}; diff --git a/hindsight-clients/typescript/generated/core/pathSerializer.gen.ts b/hindsight-clients/typescript/generated/core/pathSerializer.gen.ts new file mode 100644 index 0000000000..8d99931047 --- /dev/null +++ b/hindsight-clients/typescript/generated/core/pathSerializer.gen.ts @@ -0,0 +1,181 @@ +// This file is auto-generated by @hey-api/openapi-ts + +interface SerializeOptions + extends SerializePrimitiveOptions, + SerializerOptions {} + +interface SerializePrimitiveOptions { + allowReserved?: boolean; + name: string; +} + +export interface SerializerOptions { + /** + * @default true + */ + explode: boolean; + style: T; +} + +export type ArrayStyle = 'form' | 'spaceDelimited' | 'pipeDelimited'; +export type ArraySeparatorStyle = ArrayStyle | MatrixStyle; +type MatrixStyle = 'label' | 'matrix' | 'simple'; +export type ObjectStyle = 'form' | 'deepObject'; +type ObjectSeparatorStyle = ObjectStyle | MatrixStyle; + +interface SerializePrimitiveParam extends SerializePrimitiveOptions { + value: string; +} + +export const separatorArrayExplode = (style: ArraySeparatorStyle) => { + switch (style) { + case 'label': + return '.'; + case 'matrix': + return ';'; + case 'simple': + return ','; + default: + return '&'; + } +}; + +export const separatorArrayNoExplode = (style: ArraySeparatorStyle) => { + switch (style) { + case 'form': + return ','; + case 'pipeDelimited': + return '|'; + case 'spaceDelimited': + return '%20'; + default: + return ','; + } +}; + +export const separatorObjectExplode = (style: ObjectSeparatorStyle) => { + switch (style) { + case 'label': + return '.'; + case 'matrix': + return ';'; + case 'simple': + return ','; + default: + return '&'; + } +}; + +export const serializeArrayParam = ({ + allowReserved, + explode, + name, + style, + value, +}: SerializeOptions & { + value: unknown[]; +}) => { + if (!explode) { + const joinedValues = ( + allowReserved ? value : value.map((v) => encodeURIComponent(v as string)) + ).join(separatorArrayNoExplode(style)); + switch (style) { + case 'label': + return `.${joinedValues}`; + case 'matrix': + return `;${name}=${joinedValues}`; + case 'simple': + return joinedValues; + default: + return `${name}=${joinedValues}`; + } + } + + const separator = separatorArrayExplode(style); + const joinedValues = value + .map((v) => { + if (style === 'label' || style === 'simple') { + return allowReserved ? v : encodeURIComponent(v as string); + } + + return serializePrimitiveParam({ + allowReserved, + name, + value: v as string, + }); + }) + .join(separator); + return style === 'label' || style === 'matrix' + ? separator + joinedValues + : joinedValues; +}; + +export const serializePrimitiveParam = ({ + allowReserved, + name, + value, +}: SerializePrimitiveParam) => { + if (value === undefined || value === null) { + return ''; + } + + if (typeof value === 'object') { + throw new Error( + 'Deeply-nested arrays/objects arenโ€™t supported. Provide your own `querySerializer()` to handle these.', + ); + } + + return `${name}=${allowReserved ? value : encodeURIComponent(value)}`; +}; + +export const serializeObjectParam = ({ + allowReserved, + explode, + name, + style, + value, + valueOnly, +}: SerializeOptions & { + value: Record | Date; + valueOnly?: boolean; +}) => { + if (value instanceof Date) { + return valueOnly ? value.toISOString() : `${name}=${value.toISOString()}`; + } + + if (style !== 'deepObject' && !explode) { + let values: string[] = []; + Object.entries(value).forEach(([key, v]) => { + values = [ + ...values, + key, + allowReserved ? (v as string) : encodeURIComponent(v as string), + ]; + }); + const joinedValues = values.join(','); + switch (style) { + case 'form': + return `${name}=${joinedValues}`; + case 'label': + return `.${joinedValues}`; + case 'matrix': + return `;${name}=${joinedValues}`; + default: + return joinedValues; + } + } + + const separator = separatorObjectExplode(style); + const joinedValues = Object.entries(value) + .map(([key, v]) => + serializePrimitiveParam({ + allowReserved, + name: style === 'deepObject' ? `${name}[${key}]` : key, + value: v as string, + }), + ) + .join(separator); + return style === 'label' || style === 'matrix' + ? separator + joinedValues + : joinedValues; +}; diff --git a/hindsight-clients/typescript/generated/core/queryKeySerializer.gen.ts b/hindsight-clients/typescript/generated/core/queryKeySerializer.gen.ts new file mode 100644 index 0000000000..d3bb68396e --- /dev/null +++ b/hindsight-clients/typescript/generated/core/queryKeySerializer.gen.ts @@ -0,0 +1,136 @@ +// This file is auto-generated by @hey-api/openapi-ts + +/** + * JSON-friendly union that mirrors what Pinia Colada can hash. + */ +export type JsonValue = + | null + | string + | number + | boolean + | JsonValue[] + | { [key: string]: JsonValue }; + +/** + * Replacer that converts non-JSON values (bigint, Date, etc.) to safe substitutes. + */ +export const queryKeyJsonReplacer = (_key: string, value: unknown) => { + if ( + value === undefined || + typeof value === 'function' || + typeof value === 'symbol' + ) { + return undefined; + } + if (typeof value === 'bigint') { + return value.toString(); + } + if (value instanceof Date) { + return value.toISOString(); + } + return value; +}; + +/** + * Safely stringifies a value and parses it back into a JsonValue. + */ +export const stringifyToJsonValue = (input: unknown): JsonValue | undefined => { + try { + const json = JSON.stringify(input, queryKeyJsonReplacer); + if (json === undefined) { + return undefined; + } + return JSON.parse(json) as JsonValue; + } catch { + return undefined; + } +}; + +/** + * Detects plain objects (including objects with a null prototype). + */ +const isPlainObject = (value: unknown): value is Record => { + if (value === null || typeof value !== 'object') { + return false; + } + const prototype = Object.getPrototypeOf(value as object); + return prototype === Object.prototype || prototype === null; +}; + +/** + * Turns URLSearchParams into a sorted JSON object for deterministic keys. + */ +const serializeSearchParams = (params: URLSearchParams): JsonValue => { + const entries = Array.from(params.entries()).sort(([a], [b]) => + a.localeCompare(b), + ); + const result: Record = {}; + + for (const [key, value] of entries) { + const existing = result[key]; + if (existing === undefined) { + result[key] = value; + continue; + } + + if (Array.isArray(existing)) { + (existing as string[]).push(value); + } else { + result[key] = [existing, value]; + } + } + + return result; +}; + +/** + * Normalizes any accepted value into a JSON-friendly shape for query keys. + */ +export const serializeQueryKeyValue = ( + value: unknown, +): JsonValue | undefined => { + if (value === null) { + return null; + } + + if ( + typeof value === 'string' || + typeof value === 'number' || + typeof value === 'boolean' + ) { + return value; + } + + if ( + value === undefined || + typeof value === 'function' || + typeof value === 'symbol' + ) { + return undefined; + } + + if (typeof value === 'bigint') { + return value.toString(); + } + + if (value instanceof Date) { + return value.toISOString(); + } + + if (Array.isArray(value)) { + return stringifyToJsonValue(value); + } + + if ( + typeof URLSearchParams !== 'undefined' && + value instanceof URLSearchParams + ) { + return serializeSearchParams(value); + } + + if (isPlainObject(value)) { + return stringifyToJsonValue(value); + } + + return undefined; +}; diff --git a/hindsight-clients/typescript/generated/core/serverSentEvents.gen.ts b/hindsight-clients/typescript/generated/core/serverSentEvents.gen.ts new file mode 100644 index 0000000000..f8fd78e284 --- /dev/null +++ b/hindsight-clients/typescript/generated/core/serverSentEvents.gen.ts @@ -0,0 +1,264 @@ +// This file is auto-generated by @hey-api/openapi-ts + +import type { Config } from './types.gen'; + +export type ServerSentEventsOptions = Omit< + RequestInit, + 'method' +> & + Pick & { + /** + * Fetch API implementation. You can use this option to provide a custom + * fetch instance. + * + * @default globalThis.fetch + */ + fetch?: typeof fetch; + /** + * Implementing clients can call request interceptors inside this hook. + */ + onRequest?: (url: string, init: RequestInit) => Promise; + /** + * Callback invoked when a network or parsing error occurs during streaming. + * + * This option applies only if the endpoint returns a stream of events. + * + * @param error The error that occurred. + */ + onSseError?: (error: unknown) => void; + /** + * Callback invoked when an event is streamed from the server. + * + * This option applies only if the endpoint returns a stream of events. + * + * @param event Event streamed from the server. + * @returns Nothing (void). + */ + onSseEvent?: (event: StreamEvent) => void; + serializedBody?: RequestInit['body']; + /** + * Default retry delay in milliseconds. + * + * This option applies only if the endpoint returns a stream of events. + * + * @default 3000 + */ + sseDefaultRetryDelay?: number; + /** + * Maximum number of retry attempts before giving up. + */ + sseMaxRetryAttempts?: number; + /** + * Maximum retry delay in milliseconds. + * + * Applies only when exponential backoff is used. + * + * This option applies only if the endpoint returns a stream of events. + * + * @default 30000 + */ + sseMaxRetryDelay?: number; + /** + * Optional sleep function for retry backoff. + * + * Defaults to using `setTimeout`. + */ + sseSleepFn?: (ms: number) => Promise; + url: string; + }; + +export interface StreamEvent { + data: TData; + event?: string; + id?: string; + retry?: number; +} + +export type ServerSentEventsResult< + TData = unknown, + TReturn = void, + TNext = unknown, +> = { + stream: AsyncGenerator< + TData extends Record ? TData[keyof TData] : TData, + TReturn, + TNext + >; +}; + +export const createSseClient = ({ + onRequest, + onSseError, + onSseEvent, + responseTransformer, + responseValidator, + sseDefaultRetryDelay, + sseMaxRetryAttempts, + sseMaxRetryDelay, + sseSleepFn, + url, + ...options +}: ServerSentEventsOptions): ServerSentEventsResult => { + let lastEventId: string | undefined; + + const sleep = + sseSleepFn ?? + ((ms: number) => new Promise((resolve) => setTimeout(resolve, ms))); + + const createStream = async function* () { + let retryDelay: number = sseDefaultRetryDelay ?? 3000; + let attempt = 0; + const signal = options.signal ?? new AbortController().signal; + + while (true) { + if (signal.aborted) break; + + attempt++; + + const headers = + options.headers instanceof Headers + ? options.headers + : new Headers(options.headers as Record | undefined); + + if (lastEventId !== undefined) { + headers.set('Last-Event-ID', lastEventId); + } + + try { + const requestInit: RequestInit = { + redirect: 'follow', + ...options, + body: options.serializedBody, + headers, + signal, + }; + let request = new Request(url, requestInit); + if (onRequest) { + request = await onRequest(url, requestInit); + } + // fetch must be assigned here, otherwise it would throw the error: + // TypeError: Failed to execute 'fetch' on 'Window': Illegal invocation + const _fetch = options.fetch ?? globalThis.fetch; + const response = await _fetch(request); + + if (!response.ok) + throw new Error( + `SSE failed: ${response.status} ${response.statusText}`, + ); + + if (!response.body) throw new Error('No body in SSE response'); + + const reader = response.body + .pipeThrough(new TextDecoderStream()) + .getReader(); + + let buffer = ''; + + const abortHandler = () => { + try { + reader.cancel(); + } catch { + // noop + } + }; + + signal.addEventListener('abort', abortHandler); + + try { + while (true) { + const { done, value } = await reader.read(); + if (done) break; + buffer += value; + + const chunks = buffer.split('\n\n'); + buffer = chunks.pop() ?? ''; + + for (const chunk of chunks) { + const lines = chunk.split('\n'); + const dataLines: Array = []; + let eventName: string | undefined; + + for (const line of lines) { + if (line.startsWith('data:')) { + dataLines.push(line.replace(/^data:\s*/, '')); + } else if (line.startsWith('event:')) { + eventName = line.replace(/^event:\s*/, ''); + } else if (line.startsWith('id:')) { + lastEventId = line.replace(/^id:\s*/, ''); + } else if (line.startsWith('retry:')) { + const parsed = Number.parseInt( + line.replace(/^retry:\s*/, ''), + 10, + ); + if (!Number.isNaN(parsed)) { + retryDelay = parsed; + } + } + } + + let data: unknown; + let parsedJson = false; + + if (dataLines.length) { + const rawData = dataLines.join('\n'); + try { + data = JSON.parse(rawData); + parsedJson = true; + } catch { + data = rawData; + } + } + + if (parsedJson) { + if (responseValidator) { + await responseValidator(data); + } + + if (responseTransformer) { + data = await responseTransformer(data); + } + } + + onSseEvent?.({ + data, + event: eventName, + id: lastEventId, + retry: retryDelay, + }); + + if (dataLines.length) { + yield data as any; + } + } + } + } finally { + signal.removeEventListener('abort', abortHandler); + reader.releaseLock(); + } + + break; // exit loop on normal completion + } catch (error) { + // connection failed or aborted; retry after delay + onSseError?.(error); + + if ( + sseMaxRetryAttempts !== undefined && + attempt >= sseMaxRetryAttempts + ) { + break; // stop after firing error + } + + // exponential backoff: double retry each attempt, cap at 30s + const backoff = Math.min( + retryDelay * 2 ** (attempt - 1), + sseMaxRetryDelay ?? 30000, + ); + await sleep(backoff); + } + } + }; + + const stream = createStream(); + + return { stream }; +}; diff --git a/hindsight-clients/typescript/generated/core/types.gen.ts b/hindsight-clients/typescript/generated/core/types.gen.ts new file mode 100644 index 0000000000..643c070c9d --- /dev/null +++ b/hindsight-clients/typescript/generated/core/types.gen.ts @@ -0,0 +1,118 @@ +// This file is auto-generated by @hey-api/openapi-ts + +import type { Auth, AuthToken } from './auth.gen'; +import type { + BodySerializer, + QuerySerializer, + QuerySerializerOptions, +} from './bodySerializer.gen'; + +export type HttpMethod = + | 'connect' + | 'delete' + | 'get' + | 'head' + | 'options' + | 'patch' + | 'post' + | 'put' + | 'trace'; + +export type Client< + RequestFn = never, + Config = unknown, + MethodFn = never, + BuildUrlFn = never, + SseFn = never, +> = { + /** + * Returns the final request URL. + */ + buildUrl: BuildUrlFn; + getConfig: () => Config; + request: RequestFn; + setConfig: (config: Config) => Config; +} & { + [K in HttpMethod]: MethodFn; +} & ([SseFn] extends [never] + ? { sse?: never } + : { sse: { [K in HttpMethod]: SseFn } }); + +export interface Config { + /** + * Auth token or a function returning auth token. The resolved value will be + * added to the request payload as defined by its `security` array. + */ + auth?: ((auth: Auth) => Promise | AuthToken) | AuthToken; + /** + * A function for serializing request body parameter. By default, + * {@link JSON.stringify()} will be used. + */ + bodySerializer?: BodySerializer | null; + /** + * An object containing any HTTP headers that you want to pre-populate your + * `Headers` object with. + * + * {@link https://developer.mozilla.org/docs/Web/API/Headers/Headers#init See more} + */ + headers?: + | RequestInit['headers'] + | Record< + string, + | string + | number + | boolean + | (string | number | boolean)[] + | null + | undefined + | unknown + >; + /** + * The request method. + * + * {@link https://developer.mozilla.org/docs/Web/API/fetch#method See more} + */ + method?: Uppercase; + /** + * A function for serializing request query parameters. By default, arrays + * will be exploded in form style, objects will be exploded in deepObject + * style, and reserved characters are percent-encoded. + * + * This method will have no effect if the native `paramsSerializer()` Axios + * API function is used. + * + * {@link https://swagger.io/docs/specification/serialization/#query View examples} + */ + querySerializer?: QuerySerializer | QuerySerializerOptions; + /** + * A function validating request data. This is useful if you want to ensure + * the request conforms to the desired shape, so it can be safely sent to + * the server. + */ + requestValidator?: (data: unknown) => Promise; + /** + * A function transforming response data before it's returned. This is useful + * for post-processing data, e.g. converting ISO strings into Date objects. + */ + responseTransformer?: (data: unknown) => Promise; + /** + * A function validating response data. This is useful if you want to ensure + * the response conforms to the desired shape, so it can be safely passed to + * the transformers and returned to the user. + */ + responseValidator?: (data: unknown) => Promise; +} + +type IsExactlyNeverOrNeverUndefined = [T] extends [never] + ? true + : [T] extends [never | undefined] + ? [undefined] extends [T] + ? false + : true + : false; + +export type OmitNever> = { + [K in keyof T as IsExactlyNeverOrNeverUndefined extends true + ? never + : K]: T[K]; +}; diff --git a/hindsight-clients/typescript/generated/core/utils.gen.ts b/hindsight-clients/typescript/generated/core/utils.gen.ts new file mode 100644 index 0000000000..0b5389d089 --- /dev/null +++ b/hindsight-clients/typescript/generated/core/utils.gen.ts @@ -0,0 +1,143 @@ +// This file is auto-generated by @hey-api/openapi-ts + +import type { BodySerializer, QuerySerializer } from './bodySerializer.gen'; +import { + type ArraySeparatorStyle, + serializeArrayParam, + serializeObjectParam, + serializePrimitiveParam, +} from './pathSerializer.gen'; + +export interface PathSerializer { + path: Record; + url: string; +} + +export const PATH_PARAM_RE = /\{[^{}]+\}/g; + +export const defaultPathSerializer = ({ path, url: _url }: PathSerializer) => { + let url = _url; + const matches = _url.match(PATH_PARAM_RE); + if (matches) { + for (const match of matches) { + let explode = false; + let name = match.substring(1, match.length - 1); + let style: ArraySeparatorStyle = 'simple'; + + if (name.endsWith('*')) { + explode = true; + name = name.substring(0, name.length - 1); + } + + if (name.startsWith('.')) { + name = name.substring(1); + style = 'label'; + } else if (name.startsWith(';')) { + name = name.substring(1); + style = 'matrix'; + } + + const value = path[name]; + + if (value === undefined || value === null) { + continue; + } + + if (Array.isArray(value)) { + url = url.replace( + match, + serializeArrayParam({ explode, name, style, value }), + ); + continue; + } + + if (typeof value === 'object') { + url = url.replace( + match, + serializeObjectParam({ + explode, + name, + style, + value: value as Record, + valueOnly: true, + }), + ); + continue; + } + + if (style === 'matrix') { + url = url.replace( + match, + `;${serializePrimitiveParam({ + name, + value: value as string, + })}`, + ); + continue; + } + + const replaceValue = encodeURIComponent( + style === 'label' ? `.${value as string}` : (value as string), + ); + url = url.replace(match, replaceValue); + } + } + return url; +}; + +export const getUrl = ({ + baseUrl, + path, + query, + querySerializer, + url: _url, +}: { + baseUrl?: string; + path?: Record; + query?: Record; + querySerializer: QuerySerializer; + url: string; +}) => { + const pathUrl = _url.startsWith('/') ? _url : `/${_url}`; + let url = (baseUrl ?? '') + pathUrl; + if (path) { + url = defaultPathSerializer({ path, url }); + } + let search = query ? querySerializer(query) : ''; + if (search.startsWith('?')) { + search = search.substring(1); + } + if (search) { + url += `?${search}`; + } + return url; +}; + +export function getValidRequestBody(options: { + body?: unknown; + bodySerializer?: BodySerializer | null; + serializedBody?: unknown; +}) { + const hasBody = options.body !== undefined; + const isSerializedBody = hasBody && options.bodySerializer; + + if (isSerializedBody) { + if ('serializedBody' in options) { + const hasSerializedBody = + options.serializedBody !== undefined && options.serializedBody !== ''; + + return hasSerializedBody ? options.serializedBody : null; + } + + // not all clients implement a serializedBody property (i.e. client-axios) + return options.body !== '' ? options.body : null; + } + + // plain/text body + if (hasBody) { + return options.body; + } + + // no body was provided + return undefined; +} diff --git a/hindsight-clients/typescript/generated/index.ts b/hindsight-clients/typescript/generated/index.ts new file mode 100644 index 0000000000..c352c1047a --- /dev/null +++ b/hindsight-clients/typescript/generated/index.ts @@ -0,0 +1,4 @@ +// This file is auto-generated by @hey-api/openapi-ts + +export type * from './types.gen'; +export * from './sdk.gen'; diff --git a/hindsight-clients/typescript/generated/sdk.gen.ts b/hindsight-clients/typescript/generated/sdk.gen.ts new file mode 100644 index 0000000000..ad2b881774 --- /dev/null +++ b/hindsight-clients/typescript/generated/sdk.gen.ts @@ -0,0 +1,256 @@ +// This file is auto-generated by @hey-api/openapi-ts + +import type { Client, Options as Options2, TDataShape } from './client'; +import { client } from './client.gen'; +import type { AddAgentBackgroundData, AddAgentBackgroundErrors, AddAgentBackgroundResponses, BatchPutAsyncData, BatchPutAsyncErrors, BatchPutAsyncResponses, BatchPutMemoriesData, BatchPutMemoriesErrors, BatchPutMemoriesResponses, CancelOperationData, CancelOperationErrors, CancelOperationResponses, ClearAgentMemoriesData, ClearAgentMemoriesErrors, ClearAgentMemoriesResponses, CreateOrUpdateAgentData, CreateOrUpdateAgentErrors, CreateOrUpdateAgentResponses, DeleteDocumentData, DeleteDocumentErrors, DeleteDocumentResponses, DeleteMemoryUnitData, DeleteMemoryUnitErrors, DeleteMemoryUnitResponses, GetAgentProfileData, GetAgentProfileErrors, GetAgentProfileResponses, GetAgentStatsData, GetAgentStatsErrors, GetAgentStatsResponses, GetDocumentData, GetDocumentErrors, GetDocumentResponses, GetGraphData, GetGraphErrors, GetGraphResponses, ListAgentsData, ListAgentsResponses, ListDocumentsData, ListDocumentsErrors, ListDocumentsResponses, ListMemoriesData, ListMemoriesErrors, ListMemoriesResponses, ListOperationsData, ListOperationsErrors, ListOperationsResponses, SearchMemoriesData, SearchMemoriesErrors, SearchMemoriesResponses, ThinkData, ThinkErrors, ThinkResponses, UpdateAgentPersonalityData, UpdateAgentPersonalityErrors, UpdateAgentPersonalityResponses } from './types.gen'; + +export type Options = Options2 & { + /** + * You can provide a client instance returned by `createClient()` instead of + * individual options. This might be also useful if you want to implement a + * custom client. + */ + client?: Client; + /** + * You can pass arbitrary values through the `meta` object. This can be + * used to access values that aren't defined as part of the SDK function. + */ + meta?: Record; +}; + +/** + * Get memory graph data + * + * Retrieve graph data for visualization, optionally filtered by fact_type (world/agent/opinion). Limited to 1000 most recent items. + */ +export const getGraph = (options: Options) => (options.client ?? client).get({ url: '/api/v1/agents/{agent_id}/graph', ...options }); + +/** + * List memory units + * + * List memory units with pagination and optional full-text search. Supports filtering by fact_type. + */ +export const listMemories = (options: Options) => (options.client ?? client).get({ url: '/api/v1/agents/{agent_id}/memories/list', ...options }); + +/** + * Search memory + * + * Search memory using semantic similarity and spreading activation. + * + * The fact_type parameter is optional and must be one of: + * - 'world': General knowledge about people, places, events, and things that happen + * - 'agent': Memories about what the AI agent did, actions taken, and tasks performed + * - 'opinion': The agent's formed beliefs, perspectives, and viewpoints + */ +export const searchMemories = (options: Options) => (options.client ?? client).post({ + url: '/api/v1/agents/{agent_id}/memories/search', + ...options, + headers: { + 'Content-Type': 'application/json', + ...options.headers + } +}); + +/** + * Think and generate answer + * + * Think and formulate an answer using agent identity, world facts, and opinions. + * + * This endpoint: + * 1. Retrieves agent facts (agent's identity) + * 2. Retrieves world facts relevant to the query + * 3. Retrieves existing opinions (agent's perspectives) + * 4. Uses LLM to formulate a contextual answer + * 5. Extracts and stores any new opinions formed + * 6. Returns plain text answer, the facts used, and new opinions + */ +export const think = (options: Options) => (options.client ?? client).post({ + url: '/api/v1/agents/{agent_id}/think', + ...options, + headers: { + 'Content-Type': 'application/json', + ...options.headers + } +}); + +/** + * List all agents + * + * Get a list of all agents with their profiles + */ +export const listAgents = (options?: Options) => (options?.client ?? client).get({ url: '/api/v1/agents', ...options }); + +/** + * Get memory statistics for an agent + * + * Get statistics about nodes and links for a specific agent + */ +export const getAgentStats = (options: Options) => (options.client ?? client).get({ url: '/api/v1/agents/{agent_id}/stats', ...options }); + +/** + * List documents + * + * List documents with pagination and optional search. Documents are the source content from which memory units are extracted. + */ +export const listDocuments = (options: Options) => (options.client ?? client).get({ url: '/api/v1/agents/{agent_id}/documents', ...options }); + +/** + * Delete a document + * + * Delete a document and all its associated memory units and links. + * + * This will cascade delete: + * - The document itself + * - All memory units extracted from this document + * - All links (temporal, semantic, entity) associated with those memory units + * + * This operation cannot be undone. + */ +export const deleteDocument = (options: Options) => (options.client ?? client).delete({ url: '/api/v1/agents/{agent_id}/documents/{document_id}', ...options }); + +/** + * Get document details + * + * Get a specific document including its original text + */ +export const getDocument = (options: Options) => (options.client ?? client).get({ url: '/api/v1/agents/{agent_id}/documents/{document_id}', ...options }); + +/** + * Clear agent memories + * + * Delete memory units for an agent. Optionally filter by fact_type (world, agent, opinion) to delete only specific types. This is a destructive operation that cannot be undone. The agent profile (personality and background) will be preserved. + */ +export const clearAgentMemories = (options: Options) => (options.client ?? client).delete({ url: '/api/v1/agents/{agent_id}/memories', ...options }); + +/** + * Store multiple memories + * + * Store multiple memory items in batch with automatic fact extraction. + * + * Features: + * - Efficient batch processing + * - Automatic fact extraction from natural language + * - Entity recognition and linking + * - Document tracking with automatic upsert (when document_id is provided) + * - Temporal and semantic linking + * + * The system automatically: + * 1. Extracts semantic facts from the content + * 2. Generates embeddings + * 3. Deduplicates similar facts + * 4. Creates temporal, semantic, and entity links + * 5. Tracks document metadata + * + * Note: If document_id is provided and already exists, the old document and its memory units will be deleted before creating new ones (upsert behavior). + */ +export const batchPutMemories = (options: Options) => (options.client ?? client).post({ + url: '/api/v1/agents/{agent_id}/memories', + ...options, + headers: { + 'Content-Type': 'application/json', + ...options.headers + } +}); + +/** + * Store multiple memories asynchronously + * + * Store multiple memory items in batch asynchronously using the task backend. + * + * This endpoint returns immediately after queuing the task, without waiting for completion. + * The actual processing happens in the background. + * + * Features: + * - Immediate response (non-blocking) + * - Background processing via task queue + * - Efficient batch processing + * - Automatic fact extraction from natural language + * - Entity recognition and linking + * - Document tracking with automatic upsert (when document_id is provided) + * - Temporal and semantic linking + * + * The system automatically: + * 1. Queues the batch put task + * 2. Returns immediately with success=True, queued=True + * 3. Processes in background: extracts facts, generates embeddings, creates links + * + * Note: If document_id is provided and already exists, the old document and its memory units will be deleted before creating new ones (upsert behavior). + */ +export const batchPutAsync = (options: Options) => (options.client ?? client).post({ + url: '/api/v1/agents/{agent_id}/memories/async', + ...options, + headers: { + 'Content-Type': 'application/json', + ...options.headers + } +}); + +/** + * List async operations + * + * Get a list of all async operations (pending and failed) for a specific agent, including error messages for failed operations + */ +export const listOperations = (options: Options) => (options.client ?? client).get({ url: '/api/v1/agents/{agent_id}/operations', ...options }); + +/** + * Cancel a pending async operation + * + * Cancel a pending async operation by removing it from the queue + */ +export const cancelOperation = (options: Options) => (options.client ?? client).delete({ url: '/api/v1/agents/{agent_id}/operations/{operation_id}', ...options }); + +/** + * Delete a memory unit + * + * Delete a single memory unit and all its associated links (temporal, semantic, and entity links) + */ +export const deleteMemoryUnit = (options: Options) => (options.client ?? client).delete({ url: '/api/v1/agents/{agent_id}/memories/{unit_id}', ...options }); + +/** + * Get agent profile + * + * Get personality traits and background for an agent. Auto-creates agent with defaults if not exists. + */ +export const getAgentProfile = (options: Options) => (options.client ?? client).get({ url: '/api/v1/agents/{agent_id}/profile', ...options }); + +/** + * Update agent personality + * + * Update agent's Big Five personality traits and bias strength + */ +export const updateAgentPersonality = (options: Options) => (options.client ?? client).put({ + url: '/api/v1/agents/{agent_id}/profile', + ...options, + headers: { + 'Content-Type': 'application/json', + ...options.headers + } +}); + +/** + * Add/merge agent background + * + * Add new background information or merge with existing. LLM intelligently resolves conflicts, normalizes to first person, and optionally infers personality traits. + */ +export const addAgentBackground = (options: Options) => (options.client ?? client).post({ + url: '/api/v1/agents/{agent_id}/background', + ...options, + headers: { + 'Content-Type': 'application/json', + ...options.headers + } +}); + +/** + * Create or update agent + * + * Create a new agent or update existing agent with personality and background. Auto-fills missing fields with defaults. + */ +export const createOrUpdateAgent = (options: Options) => (options.client ?? client).put({ + url: '/api/v1/agents/{agent_id}', + ...options, + headers: { + 'Content-Type': 'application/json', + ...options.headers + } +}); diff --git a/hindsight-clients/typescript/generated/types.gen.ts b/hindsight-clients/typescript/generated/types.gen.ts new file mode 100644 index 0000000000..f7f1bf0be9 --- /dev/null +++ b/hindsight-clients/typescript/generated/types.gen.ts @@ -0,0 +1,1182 @@ +// This file is auto-generated by @hey-api/openapi-ts + +export type ClientOptions = { + baseUrl: `${string}://${string}` | (string & {}); +}; + +/** + * AddBackgroundRequest + * + * Request model for adding/merging background information. + */ +export type AddBackgroundRequest = { + /** + * Content + * + * New background information to add or merge + */ + content: string; + /** + * Update Personality + * + * If true, infer Big Five personality traits from the merged background (default: true) + */ + update_personality?: boolean; +}; + +/** + * AgentListItem + * + * Agent list item with profile summary. + */ +export type AgentListItem = { + /** + * Agent Id + */ + agent_id: string; + /** + * Name + */ + name: string; + personality: PersonalityTraits; + /** + * Background + */ + background: string; + /** + * Created At + */ + created_at?: string | null; + /** + * Updated At + */ + updated_at?: string | null; +}; + +/** + * AgentListResponse + * + * Response model for listing all agents. + */ +export type AgentListResponse = { + /** + * Agents + */ + agents: Array; +}; + +/** + * AgentProfileResponse + * + * Response model for agent profile. + */ +export type AgentProfileResponse = { + /** + * Agent Id + */ + agent_id: string; + /** + * Name + */ + name: string; + personality: PersonalityTraits; + /** + * Background + */ + background: string; +}; + +/** + * BackgroundResponse + * + * Response model for background update. + */ +export type BackgroundResponse = { + /** + * Background + */ + background: string; + personality?: PersonalityTraits | null; +}; + +/** + * BatchPutAsyncResponse + * + * Response model for async batch put endpoint. + */ +export type BatchPutAsyncResponse = { + /** + * Success + */ + success: boolean; + /** + * Message + */ + message: string; + /** + * Agent Id + */ + agent_id: string; + /** + * Document Id + */ + document_id?: string | null; + /** + * Items Count + */ + items_count: number; + /** + * Queued + */ + queued: boolean; +}; + +/** + * BatchPutRequest + * + * Request model for batch put endpoint. + */ +export type BatchPutRequest = { + /** + * Items + */ + items: Array; + /** + * Document Id + */ + document_id?: string | null; +}; + +/** + * BatchPutResponse + * + * Response model for batch put endpoint. + */ +export type BatchPutResponse = { + /** + * Success + */ + success: boolean; + /** + * Message + */ + message: string; + /** + * Agent Id + */ + agent_id: string; + /** + * Document Id + */ + document_id?: string | null; + /** + * Items Count + */ + items_count: number; +}; + +/** + * CreateAgentRequest + * + * Request model for creating/updating an agent. + */ +export type CreateAgentRequest = { + /** + * Name + */ + name?: string | null; + personality?: PersonalityTraits | null; + /** + * Background + */ + background?: string | null; +}; + +/** + * DeleteResponse + * + * Response model for delete operations. + */ +export type DeleteResponse = { + /** + * Success + */ + success: boolean; + /** + * Message + */ + message: string; +}; + +/** + * DocumentResponse + * + * Response model for get document endpoint. + */ +export type DocumentResponse = { + /** + * Id + */ + id: string; + /** + * Agent Id + */ + agent_id: string; + /** + * Original Text + */ + original_text: string; + /** + * Content Hash + */ + content_hash: string | null; + /** + * Created At + */ + created_at: string; + /** + * Updated At + */ + updated_at: string; + /** + * Memory Unit Count + */ + memory_unit_count: number; +}; + +/** + * GraphDataResponse + * + * Response model for graph data endpoint. + */ +export type GraphDataResponse = { + /** + * Nodes + */ + nodes: Array<{ + [key: string]: unknown; + }>; + /** + * Edges + */ + edges: Array<{ + [key: string]: unknown; + }>; + /** + * Table Rows + */ + table_rows: Array<{ + [key: string]: unknown; + }>; + /** + * Total Units + */ + total_units: number; +}; + +/** + * HTTPValidationError + */ +export type HttpValidationError = { + /** + * Detail + */ + detail?: Array; +}; + +/** + * ListDocumentsResponse + * + * Response model for list documents endpoint. + */ +export type ListDocumentsResponse = { + /** + * Items + */ + items: Array<{ + [key: string]: unknown; + }>; + /** + * Total + */ + total: number; + /** + * Limit + */ + limit: number; + /** + * Offset + */ + offset: number; +}; + +/** + * ListMemoryUnitsResponse + * + * Response model for list memory units endpoint. + */ +export type ListMemoryUnitsResponse = { + /** + * Items + */ + items: Array<{ + [key: string]: unknown; + }>; + /** + * Total + */ + total: number; + /** + * Limit + */ + limit: number; + /** + * Offset + */ + offset: number; +}; + +/** + * MemoryItem + * + * Single memory item for batch put. + */ +export type MemoryItem = { + /** + * Content + */ + content: string; + /** + * Event Date + */ + event_date?: string | null; + /** + * Context + */ + context?: string | null; +}; + +/** + * PersonalityTraits + * + * Personality traits based on Big Five model. + */ +export type PersonalityTraits = { + /** + * Openness + * + * Openness to experience (0-1) + */ + openness: number; + /** + * Conscientiousness + * + * Conscientiousness (0-1) + */ + conscientiousness: number; + /** + * Extraversion + * + * Extraversion (0-1) + */ + extraversion: number; + /** + * Agreeableness + * + * Agreeableness (0-1) + */ + agreeableness: number; + /** + * Neuroticism + * + * Neuroticism (0-1) + */ + neuroticism: number; + /** + * Bias Strength + * + * How strongly personality influences opinions (0-1) + */ + bias_strength: number; +}; + +/** + * SearchRequest + * + * Request model for search endpoint. + */ +export type SearchRequest = { + /** + * Query + */ + query: string; + /** + * Fact Type + */ + fact_type?: Array | null; + /** + * Thinking Budget + */ + thinking_budget?: number; + /** + * Max Tokens + */ + max_tokens?: number; + /** + * Trace + */ + trace?: boolean; + /** + * Question Date + */ + question_date?: string | null; +}; + +/** + * SearchResponse + * + * Response model for search endpoints. + */ +export type SearchResponse = { + /** + * Results + */ + results: Array; + /** + * Trace + */ + trace?: { + [key: string]: unknown; + } | null; +}; + +/** + * SearchResult + * + * Single search result item. + */ +export type SearchResult = { + /** + * Id + */ + id: string; + /** + * Text + */ + text: string; + /** + * Type + */ + type?: string | null; + /** + * Context + */ + context?: string | null; + /** + * Event Date + */ + event_date?: string | null; + /** + * Document Id + */ + document_id?: string | null; +}; + +/** + * ThinkFact + * + * A fact used in think response. + */ +export type ThinkFact = { + /** + * Id + */ + id?: string | null; + /** + * Text + */ + text: string; + /** + * Type + */ + type?: string | null; + /** + * Context + */ + context?: string | null; + /** + * Event Date + */ + event_date?: string | null; +}; + +/** + * ThinkRequest + * + * Request model for think endpoint. + */ +export type ThinkRequest = { + /** + * Query + */ + query: string; + /** + * Thinking Budget + */ + thinking_budget?: number; + /** + * Context + */ + context?: string | null; +}; + +/** + * ThinkResponse + * + * Response model for think endpoint. + */ +export type ThinkResponse = { + /** + * Text + */ + text: string; + /** + * Based On + */ + based_on?: Array; + /** + * New Opinions + */ + new_opinions?: Array; +}; + +/** + * UpdatePersonalityRequest + * + * Request model for updating personality traits. + */ +export type UpdatePersonalityRequest = { + personality: PersonalityTraits; +}; + +/** + * ValidationError + */ +export type ValidationError = { + /** + * Location + */ + loc: Array; + /** + * Message + */ + msg: string; + /** + * Error Type + */ + type: string; +}; + +export type GetGraphData = { + body?: never; + path: { + /** + * Agent Id + */ + agent_id: string; + }; + query?: { + /** + * Fact Type + */ + fact_type?: string | null; + }; + url: '/api/v1/agents/{agent_id}/graph'; +}; + +export type GetGraphErrors = { + /** + * Validation Error + */ + 422: HttpValidationError; +}; + +export type GetGraphError = GetGraphErrors[keyof GetGraphErrors]; + +export type GetGraphResponses = { + /** + * Successful Response + */ + 200: GraphDataResponse; +}; + +export type GetGraphResponse = GetGraphResponses[keyof GetGraphResponses]; + +export type ListMemoriesData = { + body?: never; + path: { + /** + * Agent Id + */ + agent_id: string; + }; + query?: { + /** + * Fact Type + */ + fact_type?: string | null; + /** + * Q + */ + q?: string | null; + /** + * Limit + */ + limit?: number; + /** + * Offset + */ + offset?: number; + }; + url: '/api/v1/agents/{agent_id}/memories/list'; +}; + +export type ListMemoriesErrors = { + /** + * Validation Error + */ + 422: HttpValidationError; +}; + +export type ListMemoriesError = ListMemoriesErrors[keyof ListMemoriesErrors]; + +export type ListMemoriesResponses = { + /** + * Successful Response + */ + 200: ListMemoryUnitsResponse; +}; + +export type ListMemoriesResponse = ListMemoriesResponses[keyof ListMemoriesResponses]; + +export type SearchMemoriesData = { + body: SearchRequest; + path: { + /** + * Agent Id + */ + agent_id: string; + }; + query?: never; + url: '/api/v1/agents/{agent_id}/memories/search'; +}; + +export type SearchMemoriesErrors = { + /** + * Validation Error + */ + 422: HttpValidationError; +}; + +export type SearchMemoriesError = SearchMemoriesErrors[keyof SearchMemoriesErrors]; + +export type SearchMemoriesResponses = { + /** + * Successful Response + */ + 200: SearchResponse; +}; + +export type SearchMemoriesResponse = SearchMemoriesResponses[keyof SearchMemoriesResponses]; + +export type ThinkData = { + body: ThinkRequest; + path: { + /** + * Agent Id + */ + agent_id: string; + }; + query?: never; + url: '/api/v1/agents/{agent_id}/think'; +}; + +export type ThinkErrors = { + /** + * Validation Error + */ + 422: HttpValidationError; +}; + +export type ThinkError = ThinkErrors[keyof ThinkErrors]; + +export type ThinkResponses = { + /** + * Successful Response + */ + 200: ThinkResponse; +}; + +export type ThinkResponse2 = ThinkResponses[keyof ThinkResponses]; + +export type ListAgentsData = { + body?: never; + path?: never; + query?: never; + url: '/api/v1/agents'; +}; + +export type ListAgentsResponses = { + /** + * Successful Response + */ + 200: AgentListResponse; +}; + +export type ListAgentsResponse = ListAgentsResponses[keyof ListAgentsResponses]; + +export type GetAgentStatsData = { + body?: never; + path: { + /** + * Agent Id + */ + agent_id: string; + }; + query?: never; + url: '/api/v1/agents/{agent_id}/stats'; +}; + +export type GetAgentStatsErrors = { + /** + * Validation Error + */ + 422: HttpValidationError; +}; + +export type GetAgentStatsError = GetAgentStatsErrors[keyof GetAgentStatsErrors]; + +export type GetAgentStatsResponses = { + /** + * Successful Response + */ + 200: unknown; +}; + +export type ListDocumentsData = { + body?: never; + path: { + /** + * Agent Id + */ + agent_id: string; + }; + query?: { + /** + * Q + */ + q?: string | null; + /** + * Limit + */ + limit?: number; + /** + * Offset + */ + offset?: number; + }; + url: '/api/v1/agents/{agent_id}/documents'; +}; + +export type ListDocumentsErrors = { + /** + * Validation Error + */ + 422: HttpValidationError; +}; + +export type ListDocumentsError = ListDocumentsErrors[keyof ListDocumentsErrors]; + +export type ListDocumentsResponses = { + /** + * Successful Response + */ + 200: ListDocumentsResponse; +}; + +export type ListDocumentsResponse2 = ListDocumentsResponses[keyof ListDocumentsResponses]; + +export type DeleteDocumentData = { + body?: never; + path: { + /** + * Agent Id + */ + agent_id: string; + /** + * Document Id + */ + document_id: string; + }; + query?: never; + url: '/api/v1/agents/{agent_id}/documents/{document_id}'; +}; + +export type DeleteDocumentErrors = { + /** + * Validation Error + */ + 422: HttpValidationError; +}; + +export type DeleteDocumentError = DeleteDocumentErrors[keyof DeleteDocumentErrors]; + +export type DeleteDocumentResponses = { + /** + * Successful Response + */ + 200: unknown; +}; + +export type GetDocumentData = { + body?: never; + path: { + /** + * Agent Id + */ + agent_id: string; + /** + * Document Id + */ + document_id: string; + }; + query?: never; + url: '/api/v1/agents/{agent_id}/documents/{document_id}'; +}; + +export type GetDocumentErrors = { + /** + * Validation Error + */ + 422: HttpValidationError; +}; + +export type GetDocumentError = GetDocumentErrors[keyof GetDocumentErrors]; + +export type GetDocumentResponses = { + /** + * Successful Response + */ + 200: DocumentResponse; +}; + +export type GetDocumentResponse = GetDocumentResponses[keyof GetDocumentResponses]; + +export type ClearAgentMemoriesData = { + body?: never; + path: { + /** + * Agent Id + */ + agent_id: string; + }; + query?: { + /** + * Fact Type + * + * Optional fact type filter (world, agent, opinion) + */ + fact_type?: string | null; + }; + url: '/api/v1/agents/{agent_id}/memories'; +}; + +export type ClearAgentMemoriesErrors = { + /** + * Validation Error + */ + 422: HttpValidationError; +}; + +export type ClearAgentMemoriesError = ClearAgentMemoriesErrors[keyof ClearAgentMemoriesErrors]; + +export type ClearAgentMemoriesResponses = { + /** + * Successful Response + */ + 200: DeleteResponse; +}; + +export type ClearAgentMemoriesResponse = ClearAgentMemoriesResponses[keyof ClearAgentMemoriesResponses]; + +export type BatchPutMemoriesData = { + body: BatchPutRequest; + path: { + /** + * Agent Id + */ + agent_id: string; + }; + query?: never; + url: '/api/v1/agents/{agent_id}/memories'; +}; + +export type BatchPutMemoriesErrors = { + /** + * Validation Error + */ + 422: HttpValidationError; +}; + +export type BatchPutMemoriesError = BatchPutMemoriesErrors[keyof BatchPutMemoriesErrors]; + +export type BatchPutMemoriesResponses = { + /** + * Successful Response + */ + 200: BatchPutResponse; +}; + +export type BatchPutMemoriesResponse = BatchPutMemoriesResponses[keyof BatchPutMemoriesResponses]; + +export type BatchPutAsyncData = { + body: BatchPutRequest; + path: { + /** + * Agent Id + */ + agent_id: string; + }; + query?: never; + url: '/api/v1/agents/{agent_id}/memories/async'; +}; + +export type BatchPutAsyncErrors = { + /** + * Validation Error + */ + 422: HttpValidationError; +}; + +export type BatchPutAsyncError = BatchPutAsyncErrors[keyof BatchPutAsyncErrors]; + +export type BatchPutAsyncResponses = { + /** + * Successful Response + */ + 200: BatchPutAsyncResponse; +}; + +export type BatchPutAsyncResponse2 = BatchPutAsyncResponses[keyof BatchPutAsyncResponses]; + +export type ListOperationsData = { + body?: never; + path: { + /** + * Agent Id + */ + agent_id: string; + }; + query?: never; + url: '/api/v1/agents/{agent_id}/operations'; +}; + +export type ListOperationsErrors = { + /** + * Validation Error + */ + 422: HttpValidationError; +}; + +export type ListOperationsError = ListOperationsErrors[keyof ListOperationsErrors]; + +export type ListOperationsResponses = { + /** + * Successful Response + */ + 200: unknown; +}; + +export type CancelOperationData = { + body?: never; + path: { + /** + * Agent Id + */ + agent_id: string; + /** + * Operation Id + */ + operation_id: string; + }; + query?: never; + url: '/api/v1/agents/{agent_id}/operations/{operation_id}'; +}; + +export type CancelOperationErrors = { + /** + * Validation Error + */ + 422: HttpValidationError; +}; + +export type CancelOperationError = CancelOperationErrors[keyof CancelOperationErrors]; + +export type CancelOperationResponses = { + /** + * Successful Response + */ + 200: unknown; +}; + +export type DeleteMemoryUnitData = { + body?: never; + path: { + /** + * Agent Id + */ + agent_id: string; + /** + * Unit Id + */ + unit_id: string; + }; + query?: never; + url: '/api/v1/agents/{agent_id}/memories/{unit_id}'; +}; + +export type DeleteMemoryUnitErrors = { + /** + * Validation Error + */ + 422: HttpValidationError; +}; + +export type DeleteMemoryUnitError = DeleteMemoryUnitErrors[keyof DeleteMemoryUnitErrors]; + +export type DeleteMemoryUnitResponses = { + /** + * Successful Response + */ + 200: unknown; +}; + +export type GetAgentProfileData = { + body?: never; + path: { + /** + * Agent Id + */ + agent_id: string; + }; + query?: never; + url: '/api/v1/agents/{agent_id}/profile'; +}; + +export type GetAgentProfileErrors = { + /** + * Validation Error + */ + 422: HttpValidationError; +}; + +export type GetAgentProfileError = GetAgentProfileErrors[keyof GetAgentProfileErrors]; + +export type GetAgentProfileResponses = { + /** + * Successful Response + */ + 200: AgentProfileResponse; +}; + +export type GetAgentProfileResponse = GetAgentProfileResponses[keyof GetAgentProfileResponses]; + +export type UpdateAgentPersonalityData = { + body: UpdatePersonalityRequest; + path: { + /** + * Agent Id + */ + agent_id: string; + }; + query?: never; + url: '/api/v1/agents/{agent_id}/profile'; +}; + +export type UpdateAgentPersonalityErrors = { + /** + * Validation Error + */ + 422: HttpValidationError; +}; + +export type UpdateAgentPersonalityError = UpdateAgentPersonalityErrors[keyof UpdateAgentPersonalityErrors]; + +export type UpdateAgentPersonalityResponses = { + /** + * Successful Response + */ + 200: AgentProfileResponse; +}; + +export type UpdateAgentPersonalityResponse = UpdateAgentPersonalityResponses[keyof UpdateAgentPersonalityResponses]; + +export type AddAgentBackgroundData = { + body: AddBackgroundRequest; + path: { + /** + * Agent Id + */ + agent_id: string; + }; + query?: never; + url: '/api/v1/agents/{agent_id}/background'; +}; + +export type AddAgentBackgroundErrors = { + /** + * Validation Error + */ + 422: HttpValidationError; +}; + +export type AddAgentBackgroundError = AddAgentBackgroundErrors[keyof AddAgentBackgroundErrors]; + +export type AddAgentBackgroundResponses = { + /** + * Successful Response + */ + 200: BackgroundResponse; +}; + +export type AddAgentBackgroundResponse = AddAgentBackgroundResponses[keyof AddAgentBackgroundResponses]; + +export type CreateOrUpdateAgentData = { + body: CreateAgentRequest; + path: { + /** + * Agent Id + */ + agent_id: string; + }; + query?: never; + url: '/api/v1/agents/{agent_id}'; +}; + +export type CreateOrUpdateAgentErrors = { + /** + * Validation Error + */ + 422: HttpValidationError; +}; + +export type CreateOrUpdateAgentError = CreateOrUpdateAgentErrors[keyof CreateOrUpdateAgentErrors]; + +export type CreateOrUpdateAgentResponses = { + /** + * Successful Response + */ + 200: AgentProfileResponse; +}; + +export type CreateOrUpdateAgentResponse = CreateOrUpdateAgentResponses[keyof CreateOrUpdateAgentResponses]; diff --git a/hindsight-clients/typescript/jest.config.js b/hindsight-clients/typescript/jest.config.js new file mode 100644 index 0000000000..e9aae19501 --- /dev/null +++ b/hindsight-clients/typescript/jest.config.js @@ -0,0 +1,10 @@ +module.exports = { + preset: 'ts-jest', + testEnvironment: 'node', + testMatch: ['**/tests/**/*.test.ts'], + moduleFileExtensions: ['ts', 'tsx', 'js', 'jsx', 'json', 'node'], + transform: { + '^.+\\.tsx?$': 'ts-jest', + }, + testTimeout: 60000, +}; diff --git a/hindsight-clients/typescript/openapi-ts.config.ts b/hindsight-clients/typescript/openapi-ts.config.ts new file mode 100644 index 0000000000..f58366852e --- /dev/null +++ b/hindsight-clients/typescript/openapi-ts.config.ts @@ -0,0 +1,14 @@ +import { defineConfig } from '@hey-api/openapi-ts'; + +export default defineConfig({ + client: '@hey-api/client-fetch', + input: '../../openapi.json', + output: { + path: './generated', + format: 'prettier', + }, + plugins: [ + '@hey-api/typescript', + '@hey-api/sdk', + ], +}); diff --git a/hindsight-clients/typescript/package.json b/hindsight-clients/typescript/package.json new file mode 100644 index 0000000000..cc6bc7939f --- /dev/null +++ b/hindsight-clients/typescript/package.json @@ -0,0 +1,42 @@ +{ + "name": "@hindsight/client", + "version": "0.0.8", + "description": "TypeScript client for Hindsight - Semantic memory system with personality-driven thinking", + "main": "./dist/src/index.js", + "types": "./dist/src/index.d.ts", + "scripts": { + "build": "tsc", + "clean": "rm -rf dist", + "generate": "npx @hey-api/openapi-ts", + "prepublishOnly": "npm run build", + "test": "jest" + }, + "keywords": [ + "hindsight", + "memory", + "api", + "client", + "typescript" + ], + "author": "Hindsight Team", + "license": "MIT", + "repository": { + "type": "git", + "url": "https://github.com/nicoloboschi/hindsight.git", + "directory": "hindsight-clients/typescript" + }, + "devDependencies": { + "@hey-api/openapi-ts": "^0.88.0", + "@types/jest": "^29.0.0", + "@types/node": "^20.0.0", + "jest": "^29.0.0", + "ts-jest": "^29.0.0", + "typescript": "^5.0.0" + }, + "files": [ + "dist", + "src", + "generated", + "README.md" + ] +} diff --git a/hindsight-clients/typescript/src/index.ts b/hindsight-clients/typescript/src/index.ts new file mode 100644 index 0000000000..85219f0e8c --- /dev/null +++ b/hindsight-clients/typescript/src/index.ts @@ -0,0 +1,246 @@ +/** + * Hindsight Client - Clean, TypeScript SDK for the Hindsight API. + * + * Example: + * ```typescript + * import { HindsightClient } from '@hindsight/client'; + * + * const client = new HindsightClient({ baseUrl: 'http://localhost:8888' }); + * + * // Store a memory + * await client.put('alice', 'Alice loves AI'); + * + * // Search memories + * const results = await client.search('alice', 'What does Alice like?'); + * + * // Generate contextual answer + * const answer = await client.think('alice', 'What are my interests?'); + * ``` + */ + +import { createClient, createConfig } from '../generated/client'; +import type { Client } from '../generated/client'; +import * as sdk from '../generated/sdk.gen'; +import type { + BatchPutRequest, + BatchPutResponse, + SearchRequest, + SearchResponse, + SearchResult, + ThinkRequest, + ThinkResponse, + ListMemoryUnitsResponse, + AgentProfileResponse, + CreateAgentRequest, +} from '../generated/types.gen'; + +export interface HindsightClientOptions { + baseUrl: string; +} + +export interface MemoryItemInput { + content: string; + event_date?: string | Date; + context?: string; +} + +export class HindsightClient { + private client: Client; + + constructor(options: HindsightClientOptions) { + this.client = createClient( + createConfig({ + baseUrl: options.baseUrl, + }) + ); + } + + /** + * Store a single memory for an agent. + */ + async put( + agentId: string, + content: string, + options?: { eventDate?: Date | string; context?: string } + ): Promise { + const item: { content: string; event_date?: string; context?: string } = { content }; + if (options?.eventDate) { + item.event_date = + options.eventDate instanceof Date + ? options.eventDate.toISOString() + : options.eventDate; + } + if (options?.context) { + item.context = options.context; + } + + const response = await sdk.batchPutMemories({ + client: this.client, + path: { agent_id: agentId }, + body: { items: [item] }, + }); + + return response.data!; + } + + /** + * Store multiple memories in batch. + */ + async putBatch(agentId: string, items: MemoryItemInput[]): Promise { + const processedItems = items.map((item) => ({ + content: item.content, + context: item.context, + event_date: + item.event_date instanceof Date + ? item.event_date.toISOString() + : item.event_date, + })); + + const response = await sdk.batchPutMemories({ + client: this.client, + path: { agent_id: agentId }, + body: { items: processedItems }, + }); + + return response.data!; + } + + /** + * Search memories with a natural language query. + * Returns a simplified list of search results. + */ + async search( + agentId: string, + query: string, + options?: { maxTokens?: number } + ): Promise { + const response = await sdk.searchMemories({ + client: this.client, + path: { agent_id: agentId }, + body: { + query, + max_tokens: options?.maxTokens, + }, + }); + + return response.data?.results ?? []; + } + + /** + * Search memories with full options and response. + */ + async searchMemories( + agentId: string, + options: { + query: string; + factType?: string[]; + maxTokens?: number; + trace?: boolean; + } + ): Promise { + const response = await sdk.searchMemories({ + client: this.client, + path: { agent_id: agentId }, + body: { + query: options.query, + fact_type: options.factType, + max_tokens: options.maxTokens, + trace: options.trace, + }, + }); + + return response.data!; + } + + /** + * Think and generate a contextual answer using the agent's identity and memories. + */ + async think( + agentId: string, + query: string, + options?: { context?: string; thinkingBudget?: number } + ): Promise { + const response = await sdk.think({ + client: this.client, + path: { agent_id: agentId }, + body: { + query, + context: options?.context, + thinking_budget: options?.thinkingBudget, + }, + }); + + return response.data!; + } + + /** + * List memories with pagination. + */ + async listMemories( + agentId: string, + options?: { limit?: number; offset?: number; factType?: string; q?: string } + ): Promise { + const response = await sdk.listMemories({ + client: this.client, + path: { agent_id: agentId }, + query: { + limit: options?.limit, + offset: options?.offset, + fact_type: options?.factType, + q: options?.q, + }, + }); + + return response.data!; + } + + /** + * Create or update an agent with personality and background. + */ + async createAgent( + agentId: string, + options: { name?: string; background?: string } + ): Promise { + const response = await sdk.createOrUpdateAgent({ + client: this.client, + path: { agent_id: agentId }, + body: { + name: options.name, + background: options.background, + }, + }); + + return response.data!; + } + + /** + * Get an agent's profile. + */ + async getAgentProfile(agentId: string): Promise { + const response = await sdk.getAgentProfile({ + client: this.client, + path: { agent_id: agentId }, + }); + + return response.data!; + } +} + +// Re-export types for convenience +export type { + BatchPutRequest, + BatchPutResponse, + SearchRequest, + SearchResponse, + SearchResult, + ThinkRequest, + ThinkResponse, + ListMemoryUnitsResponse, + AgentProfileResponse, + CreateAgentRequest, +}; + +// Also export low-level SDK functions for advanced usage +export * as sdk from '../generated/sdk.gen'; +export { createClient, createConfig } from '../generated/client'; +export type { Client } from '../generated/client'; diff --git a/hindsight-clients/typescript/tests/main_operations.test.ts b/hindsight-clients/typescript/tests/main_operations.test.ts new file mode 100644 index 0000000000..d52f33e6d3 --- /dev/null +++ b/hindsight-clients/typescript/tests/main_operations.test.ts @@ -0,0 +1,212 @@ +/** + * These tests require a running Hindsight API server. + */ + +import { HindsightClient } from '../src'; + +// Test configuration +const HINDSIGHT_API_URL = process.env.HINDSIGHT_API_URL || 'http://localhost:8888'; +const TEST_AGENT_ID = `test_agent_${new Date().toISOString().replace(/[-:T.Z]/g, '').slice(0, 15)}`; + +let client: HindsightClient; + +beforeAll(() => { + client = new HindsightClient({ baseUrl: HINDSIGHT_API_URL }); +}); + +describe('TestStore', () => { + test('put single memory', async () => { + const response = await client.put( + TEST_AGENT_ID, + 'Alice loves artificial intelligence and machine learning' + ); + + expect(response).not.toBeNull(); + expect(response.success).toBe(true); + expect(response.items_count).toBe(1); + }); + + test('put memory with context', async () => { + const response = await client.put(TEST_AGENT_ID, 'Bob went hiking in the mountains', { + eventDate: new Date('2024-01-15T10:30:00'), + context: 'outdoor activities', + }); + + expect(response).not.toBeNull(); + expect(response.success).toBe(true); + }); + + test('put batch memories', async () => { + const response = await client.putBatch(TEST_AGENT_ID, [ + { content: 'Charlie enjoys reading science fiction books' }, + { content: 'Diana is learning to play the guitar', context: 'hobbies' }, + { content: 'Eve completed a marathon last month', event_date: '2024-10-15' }, + ]); + + expect(response).not.toBeNull(); + expect(response.success).toBe(true); + expect(response.items_count).toBe(3); + }); +}); + +describe('TestSearch', () => { + beforeAll(async () => { + // Setup: Store some test memories before search tests + await client.putBatch(TEST_AGENT_ID, [ + { content: 'Alice loves programming in Python' }, + { content: 'Bob enjoys hiking and outdoor adventures' }, + { content: 'Charlie is interested in quantum physics' }, + { content: 'Diana plays the violin beautifully' }, + ]); + }); + + test('search basic', async () => { + const results = await client.search(TEST_AGENT_ID, 'What does Alice like?'); + + expect(results).not.toBeNull(); + expect(results.length).toBeGreaterThan(0); + + // Check that at least one result contains relevant information + const resultTexts = results.map((r) => r.text || ''); + const hasRelevant = resultTexts.some( + (text) => text.includes('Alice') || text.includes('Python') || text.includes('programming') + ); + expect(hasRelevant).toBe(true); + }); + + test('search with max tokens', async () => { + const results = await client.search(TEST_AGENT_ID, 'outdoor activities', { + maxTokens: 1024, + }); + + expect(results).not.toBeNull(); + expect(Array.isArray(results)).toBe(true); + }); + + test('search full featured', async () => { + const response = await client.searchMemories(TEST_AGENT_ID, { + query: "What are people's hobbies?", + factType: ['world'], + maxTokens: 2048, + trace: true, + }); + + expect(response).not.toBeNull(); + expect(response.results).toBeDefined(); + // Trace should be included when enabled + if (response.trace) { + expect(typeof response.trace).toBe('object'); + } + }); +}); + +describe('TestThink', () => { + beforeAll(async () => { + // Setup: Create agent and store test memories + await client.createAgent(TEST_AGENT_ID, { + name: 'Test Agent', + background: 'I am a helpful AI assistant interested in technology and science.', + }); + + await client.putBatch(TEST_AGENT_ID, [ + { content: 'The Python programming language is great for data science' }, + { content: 'Machine learning models can recognize patterns in data' }, + { content: 'Neural networks are inspired by biological neurons' }, + ]); + }); + + test('think basic', async () => { + const response = await client.think( + TEST_AGENT_ID, + 'What do you think about artificial intelligence?' + ); + + expect(response).not.toBeNull(); + expect(response.text).toBeDefined(); + expect(response.text!.length).toBeGreaterThan(0); + + // Should include facts that were used + if (response.based_on) { + expect(Array.isArray(response.based_on)).toBe(true); + } + }); + + test('think with context', async () => { + const response = await client.think(TEST_AGENT_ID, 'Should I learn Python?', { + context: "I'm interested in starting a career in data science", + thinkingBudget: 100, + }); + + expect(response).not.toBeNull(); + expect(response.text).toBeDefined(); + expect(response.text!.length).toBeGreaterThan(0); + }); +}); + +describe('TestListMemories', () => { + beforeAll(async () => { + // Setup: Store some test memories + await client.putBatch(TEST_AGENT_ID, [ + { content: 'Test memory 0' }, + { content: 'Test memory 1' }, + { content: 'Test memory 2' }, + { content: 'Test memory 3' }, + { content: 'Test memory 4' }, + ]); + }); + + test('list all memories', async () => { + const response = await client.listMemories(TEST_AGENT_ID); + + expect(response).not.toBeNull(); + expect(response.items).toBeDefined(); + expect(response.total).toBeDefined(); + expect(response.items!.length).toBeGreaterThan(0); + }); + + test('list with pagination', async () => { + const response = await client.listMemories(TEST_AGENT_ID, { + limit: 2, + offset: 0, + }); + + expect(response).not.toBeNull(); + expect(response.items).toBeDefined(); + expect(response.items!.length).toBeLessThanOrEqual(2); + }); +}); + +describe('TestEndToEndWorkflow', () => { + test('complete workflow', async () => { + const workflowAgentId = `workflow_test_${new Date().toISOString().replace(/[-:T.Z]/g, '').slice(0, 15)}`; + + // 1. Create agent + await client.createAgent(workflowAgentId, { + name: 'Alice', + background: 'I am a software engineer who loves Python programming.', + }); + + // 2. Store memories + const storeResponse = await client.putBatch(workflowAgentId, [ + { content: 'I completed a project using FastAPI' }, + { content: 'I learned about async programming in Python' }, + { content: 'I enjoy working on open source projects' }, + ]); + expect(storeResponse.success).toBe(true); + + // 3. Search for relevant memories + const searchResults = await client.search( + workflowAgentId, + 'What programming technologies do I use?' + ); + expect(searchResults.length).toBeGreaterThan(0); + + // 4. Generate contextual answer + const thinkResponse = await client.think( + workflowAgentId, + 'What are my professional interests?' + ); + expect(thinkResponse.text).toBeDefined(); + expect(thinkResponse.text!.length).toBeGreaterThan(0); + }); +}); diff --git a/memora-clients/typescript/tsconfig.json b/hindsight-clients/typescript/tsconfig.json similarity index 90% rename from memora-clients/typescript/tsconfig.json rename to hindsight-clients/typescript/tsconfig.json index af192ee378..afcd36ea67 100644 --- a/memora-clients/typescript/tsconfig.json +++ b/hindsight-clients/typescript/tsconfig.json @@ -2,7 +2,7 @@ "compilerOptions": { "target": "ES2020", "module": "commonjs", - "lib": ["ES2020"], + "lib": ["ES2020", "DOM"], "declaration": true, "outDir": "./dist", "rootDir": "./", @@ -17,7 +17,7 @@ }, "include": [ "src/**/*", - "index.ts" + "generated/**/*" ], "exclude": [ "node_modules", diff --git a/memora-control-plane/.dockerignore b/hindsight-control-plane/.dockerignore similarity index 100% rename from memora-control-plane/.dockerignore rename to hindsight-control-plane/.dockerignore diff --git a/memora-control-plane/.eslintrc.json b/hindsight-control-plane/.eslintrc.json similarity index 100% rename from memora-control-plane/.eslintrc.json rename to hindsight-control-plane/.eslintrc.json diff --git a/memora-control-plane/.gitignore b/hindsight-control-plane/.gitignore similarity index 100% rename from memora-control-plane/.gitignore rename to hindsight-control-plane/.gitignore diff --git a/memora-control-plane/components.json b/hindsight-control-plane/components.json similarity index 100% rename from memora-control-plane/components.json rename to hindsight-control-plane/components.json diff --git a/memora-control-plane/next.config.ts b/hindsight-control-plane/next.config.ts similarity index 100% rename from memora-control-plane/next.config.ts rename to hindsight-control-plane/next.config.ts diff --git a/memora-control-plane/package-lock.json b/hindsight-control-plane/package-lock.json similarity index 100% rename from memora-control-plane/package-lock.json rename to hindsight-control-plane/package-lock.json diff --git a/memora-control-plane/package.json b/hindsight-control-plane/package.json similarity index 85% rename from memora-control-plane/package.json rename to hindsight-control-plane/package.json index 694a2aab55..7e805c1d47 100644 --- a/memora-control-plane/package.json +++ b/hindsight-control-plane/package.json @@ -1,5 +1,5 @@ { - "name": "control-plane", + "name": "hindsight-control-plane", "version": "0.0.7", "private": true, "scripts": { @@ -9,9 +9,9 @@ "lint": "next lint" }, "keywords": [], - "author": "", + "author": "Hindsight Team", "license": "ISC", - "description": "Control plane for the temporal semantic memory system", + "description": "Control plane for Hindsight - Semantic memory system", "dependencies": { "@tailwindcss/postcss": "^4.1.17", "@types/node": "^24.10.0", diff --git a/memora-control-plane/postcss.config.mjs b/hindsight-control-plane/postcss.config.mjs similarity index 100% rename from memora-control-plane/postcss.config.mjs rename to hindsight-control-plane/postcss.config.mjs diff --git a/memora-control-plane/src/app/api/agents/route.ts b/hindsight-control-plane/src/app/api/agents/route.ts similarity index 82% rename from memora-control-plane/src/app/api/agents/route.ts rename to hindsight-control-plane/src/app/api/agents/route.ts index 8c2afe0540..f0a1e47587 100644 --- a/memora-control-plane/src/app/api/agents/route.ts +++ b/hindsight-control-plane/src/app/api/agents/route.ts @@ -1,6 +1,6 @@ import { NextResponse } from 'next/server'; -const DATAPLANE_URL = process.env.MEMORA_CP_DATAPLANE_API_URL || 'http://localhost:8080'; +const DATAPLANE_URL = process.env.HINDSIGHT_CP_DATAPLANE_API_URL || 'http://localhost:8888'; export async function GET() { try { diff --git a/memora-control-plane/src/app/api/documents/[documentId]/route.ts b/hindsight-control-plane/src/app/api/documents/[documentId]/route.ts similarity index 90% rename from memora-control-plane/src/app/api/documents/[documentId]/route.ts rename to hindsight-control-plane/src/app/api/documents/[documentId]/route.ts index 6955eebc25..125514cf0e 100644 --- a/memora-control-plane/src/app/api/documents/[documentId]/route.ts +++ b/hindsight-control-plane/src/app/api/documents/[documentId]/route.ts @@ -1,6 +1,6 @@ import { NextRequest, NextResponse } from 'next/server'; -const DATAPLANE_URL = process.env.MEMORA_CP_DATAPLANE_API_URL || 'http://localhost:8080'; +const DATAPLANE_URL = process.env.HINDSIGHT_CP_DATAPLANE_API_URL || 'http://localhost:8888'; export async function GET( request: NextRequest, diff --git a/memora-control-plane/src/app/api/documents/route.ts b/hindsight-control-plane/src/app/api/documents/route.ts similarity index 91% rename from memora-control-plane/src/app/api/documents/route.ts rename to hindsight-control-plane/src/app/api/documents/route.ts index 24b0ac674b..846feb219b 100644 --- a/memora-control-plane/src/app/api/documents/route.ts +++ b/hindsight-control-plane/src/app/api/documents/route.ts @@ -1,6 +1,6 @@ import { NextRequest, NextResponse } from 'next/server'; -const DATAPLANE_URL = process.env.MEMORA_CP_DATAPLANE_API_URL || 'http://localhost:8080'; +const DATAPLANE_URL = process.env.HINDSIGHT_CP_DATAPLANE_API_URL || 'http://localhost:8888'; export async function GET(request: NextRequest) { try { diff --git a/memora-control-plane/src/app/api/graph/route.ts b/hindsight-control-plane/src/app/api/graph/route.ts similarity index 91% rename from memora-control-plane/src/app/api/graph/route.ts rename to hindsight-control-plane/src/app/api/graph/route.ts index 3dc17579fe..5087633dd3 100644 --- a/memora-control-plane/src/app/api/graph/route.ts +++ b/hindsight-control-plane/src/app/api/graph/route.ts @@ -1,6 +1,6 @@ import { NextRequest, NextResponse } from 'next/server'; -const DATAPLANE_URL = process.env.MEMORA_CP_DATAPLANE_API_URL || 'http://localhost:8080'; +const DATAPLANE_URL = process.env.HINDSIGHT_CP_DATAPLANE_API_URL || 'http://localhost:8888'; export async function GET(request: NextRequest) { try { diff --git a/memora-control-plane/src/app/api/list/route.ts b/hindsight-control-plane/src/app/api/list/route.ts similarity index 95% rename from memora-control-plane/src/app/api/list/route.ts rename to hindsight-control-plane/src/app/api/list/route.ts index 2741f3d5f1..be80cafe17 100644 --- a/memora-control-plane/src/app/api/list/route.ts +++ b/hindsight-control-plane/src/app/api/list/route.ts @@ -1,6 +1,6 @@ import { NextRequest, NextResponse } from 'next/server'; -const DATAPLANE_URL = process.env.MEMORA_CP_DATAPLANE_API_URL || 'http://localhost:8080'; +const DATAPLANE_URL = process.env.HINDSIGHT_CP_DATAPLANE_API_URL || 'http://localhost:8888'; export async function GET(request: NextRequest) { try { diff --git a/memora-control-plane/src/app/api/memories/batch/route.ts b/hindsight-control-plane/src/app/api/memories/batch/route.ts similarity index 91% rename from memora-control-plane/src/app/api/memories/batch/route.ts rename to hindsight-control-plane/src/app/api/memories/batch/route.ts index 850158b57f..55cf7eb605 100644 --- a/memora-control-plane/src/app/api/memories/batch/route.ts +++ b/hindsight-control-plane/src/app/api/memories/batch/route.ts @@ -1,6 +1,6 @@ import { NextRequest, NextResponse } from 'next/server'; -const DATAPLANE_URL = process.env.MEMORA_CP_DATAPLANE_API_URL || 'http://localhost:8080'; +const DATAPLANE_URL = process.env.HINDSIGHT_CP_DATAPLANE_API_URL || 'http://localhost:8888'; export async function POST(request: NextRequest) { try { diff --git a/memora-control-plane/src/app/api/memories/batch_async/route.ts b/hindsight-control-plane/src/app/api/memories/batch_async/route.ts similarity index 91% rename from memora-control-plane/src/app/api/memories/batch_async/route.ts rename to hindsight-control-plane/src/app/api/memories/batch_async/route.ts index b738b08a39..3f3d4d8c4f 100644 --- a/memora-control-plane/src/app/api/memories/batch_async/route.ts +++ b/hindsight-control-plane/src/app/api/memories/batch_async/route.ts @@ -1,6 +1,6 @@ import { NextRequest, NextResponse } from 'next/server'; -const DATAPLANE_URL = process.env.MEMORA_CP_DATAPLANE_API_URL || 'http://localhost:8080'; +const DATAPLANE_URL = process.env.HINDSIGHT_CP_DATAPLANE_API_URL || 'http://localhost:8888'; export async function POST(request: NextRequest) { try { diff --git a/memora-control-plane/src/app/api/operations/[agentId]/route.ts b/hindsight-control-plane/src/app/api/operations/[agentId]/route.ts similarity index 93% rename from memora-control-plane/src/app/api/operations/[agentId]/route.ts rename to hindsight-control-plane/src/app/api/operations/[agentId]/route.ts index 9ee29200d3..e756d7fd95 100644 --- a/memora-control-plane/src/app/api/operations/[agentId]/route.ts +++ b/hindsight-control-plane/src/app/api/operations/[agentId]/route.ts @@ -1,6 +1,6 @@ import { NextRequest, NextResponse } from 'next/server'; -const DATAPLANE_URL = process.env.MEMORA_CP_DATAPLANE_API_URL || 'http://localhost:8080'; +const DATAPLANE_URL = process.env.HINDSIGHT_CP_DATAPLANE_API_URL || 'http://localhost:8888'; export async function GET( request: NextRequest, diff --git a/memora-control-plane/src/app/api/search/route.ts b/hindsight-control-plane/src/app/api/search/route.ts similarity index 89% rename from memora-control-plane/src/app/api/search/route.ts rename to hindsight-control-plane/src/app/api/search/route.ts index b316b1a47e..4d62ca7722 100644 --- a/memora-control-plane/src/app/api/search/route.ts +++ b/hindsight-control-plane/src/app/api/search/route.ts @@ -1,6 +1,6 @@ import { NextRequest, NextResponse } from 'next/server'; -const DATAPLANE_URL = process.env.MEMORA_CP_DATAPLANE_API_URL || 'http://localhost:8080'; +const DATAPLANE_URL = process.env.HINDSIGHT_CP_DATAPLANE_API_URL || 'http://localhost:8888'; export async function POST(request: NextRequest) { try { diff --git a/memora-control-plane/src/app/api/stats/[agentId]/route.ts b/hindsight-control-plane/src/app/api/stats/[agentId]/route.ts similarity index 86% rename from memora-control-plane/src/app/api/stats/[agentId]/route.ts rename to hindsight-control-plane/src/app/api/stats/[agentId]/route.ts index a0bac47099..dd89e6694a 100644 --- a/memora-control-plane/src/app/api/stats/[agentId]/route.ts +++ b/hindsight-control-plane/src/app/api/stats/[agentId]/route.ts @@ -1,6 +1,6 @@ import { NextRequest, NextResponse } from 'next/server'; -const DATAPLANE_URL = process.env.MEMORA_CP_DATAPLANE_API_URL || 'http://localhost:8080'; +const DATAPLANE_URL = process.env.HINDSIGHT_CP_DATAPLANE_API_URL || 'http://localhost:8888'; export async function GET( request: NextRequest, diff --git a/memora-control-plane/src/app/api/think/route.ts b/hindsight-control-plane/src/app/api/think/route.ts similarity index 89% rename from memora-control-plane/src/app/api/think/route.ts rename to hindsight-control-plane/src/app/api/think/route.ts index 1a03cdae14..8d2f423ac2 100644 --- a/memora-control-plane/src/app/api/think/route.ts +++ b/hindsight-control-plane/src/app/api/think/route.ts @@ -1,6 +1,6 @@ import { NextRequest, NextResponse } from 'next/server'; -const DATAPLANE_URL = process.env.MEMORA_CP_DATAPLANE_API_URL || 'http://localhost:8080'; +const DATAPLANE_URL = process.env.HINDSIGHT_CP_DATAPLANE_API_URL || 'http://localhost:8888'; export async function POST(request: NextRequest) { try { diff --git a/memora-control-plane/src/app/dashboard/page.tsx b/hindsight-control-plane/src/app/dashboard/page.tsx similarity index 100% rename from memora-control-plane/src/app/dashboard/page.tsx rename to hindsight-control-plane/src/app/dashboard/page.tsx diff --git a/hindsight-control-plane/src/app/globals.css b/hindsight-control-plane/src/app/globals.css new file mode 100644 index 0000000000..908c3b2903 --- /dev/null +++ b/hindsight-control-plane/src/app/globals.css @@ -0,0 +1,173 @@ +@import "tailwindcss"; +:root { + --background: oklch(0.9911 0 0); + --foreground: oklch(0.2046 0 0); + --card: oklch(0.9911 0 0); + --card-foreground: oklch(0.2046 0 0); + --popover: oklch(0.9911 0 0); + --popover-foreground: oklch(0.4386 0 0); + --primary: oklch(0.8348 0.1302 160.9080); + --primary-foreground: oklch(0.2626 0.0147 166.4589); + --secondary: oklch(0.9940 0 0); + --secondary-foreground: oklch(0.2046 0 0); + --muted: oklch(0.9461 0 0); + --muted-foreground: oklch(0.2435 0 0); + --accent: oklch(0.9461 0 0); + --accent-foreground: oklch(0.2435 0 0); + --destructive: oklch(0.5523 0.1927 32.7272); + --destructive-foreground: oklch(0.9934 0.0032 17.2118); + --border: oklch(0.9037 0 0); + --input: oklch(0.9731 0 0); + --ring: oklch(0.8348 0.1302 160.9080); + --chart-1: oklch(0.8348 0.1302 160.9080); + --chart-2: oklch(0.6231 0.1880 259.8145); + --chart-3: oklch(0.6056 0.2189 292.7172); + --chart-4: oklch(0.7686 0.1647 70.0804); + --chart-5: oklch(0.6959 0.1491 162.4796); + --sidebar: oklch(0.9911 0 0); + --sidebar-foreground: oklch(0.5452 0 0); + --sidebar-primary: oklch(0.8348 0.1302 160.9080); + --sidebar-primary-foreground: oklch(0.2626 0.0147 166.4589); + --sidebar-accent: oklch(0.9461 0 0); + --sidebar-accent-foreground: oklch(0.2435 0 0); + --sidebar-border: oklch(0.9037 0 0); + --sidebar-ring: oklch(0.8348 0.1302 160.9080); + --font-sans: 'Avenir Book', 'Avenir', 'Nunito Sans', -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, 'Helvetica Neue', Arial, sans-serif; + --font-serif: ui-serif, Georgia, Cambria, "Times New Roman", Times, serif; + --font-mono: monospace; + --radius: 0.5rem; + --shadow-x: 0px; + --shadow-y: 1px; + --shadow-blur: 3px; + --shadow-spread: 0px; + --shadow-opacity: 0.17; + --shadow-color: #000000; + --shadow-2xs: 0px 1px 3px 0px hsl(0 0% 0% / 0.09); + --shadow-xs: 0px 1px 3px 0px hsl(0 0% 0% / 0.09); + --shadow-sm: 0px 1px 3px 0px hsl(0 0% 0% / 0.17), 0px 1px 2px -1px hsl(0 0% 0% / 0.17); + --shadow: 0px 1px 3px 0px hsl(0 0% 0% / 0.17), 0px 1px 2px -1px hsl(0 0% 0% / 0.17); + --shadow-md: 0px 1px 3px 0px hsl(0 0% 0% / 0.17), 0px 2px 4px -1px hsl(0 0% 0% / 0.17); + --shadow-lg: 0px 1px 3px 0px hsl(0 0% 0% / 0.17), 0px 4px 6px -1px hsl(0 0% 0% / 0.17); + --shadow-xl: 0px 1px 3px 0px hsl(0 0% 0% / 0.17), 0px 8px 10px -1px hsl(0 0% 0% / 0.17); + --shadow-2xl: 0px 1px 3px 0px hsl(0 0% 0% / 0.43); + --tracking-normal: 0.025em; + --spacing: 0.25rem; +} + +.dark { + --background: oklch(0.1822 0 0); + --foreground: oklch(0.9288 0.0126 255.5078); + --card: oklch(0.2046 0 0); + --card-foreground: oklch(0.9288 0.0126 255.5078); + --popover: oklch(0.2603 0 0); + --popover-foreground: oklch(0.7348 0 0); + --primary: oklch(0.4365 0.1044 156.7556); + --primary-foreground: oklch(0.9213 0.0135 167.1556); + --secondary: oklch(0.2603 0 0); + --secondary-foreground: oklch(0.9851 0 0); + --muted: oklch(0.2393 0 0); + --muted-foreground: oklch(0.7122 0 0); + --accent: oklch(0.3132 0 0); + --accent-foreground: oklch(0.9851 0 0); + --destructive: oklch(0.3123 0.0852 29.7877); + --destructive-foreground: oklch(0.9368 0.0045 34.3092); + --border: oklch(0.2809 0 0); + --input: oklch(0.2603 0 0); + --ring: oklch(0.8003 0.1821 151.7110); + --chart-1: oklch(0.8003 0.1821 151.7110); + --chart-2: oklch(0.7137 0.1434 254.6240); + --chart-3: oklch(0.7090 0.1592 293.5412); + --chart-4: oklch(0.8369 0.1644 84.4286); + --chart-5: oklch(0.7845 0.1325 181.9120); + --sidebar: oklch(0.1822 0 0); + --sidebar-foreground: oklch(0.6301 0 0); + --sidebar-primary: oklch(0.4365 0.1044 156.7556); + --sidebar-primary-foreground: oklch(0.9213 0.0135 167.1556); + --sidebar-accent: oklch(0.3132 0 0); + --sidebar-accent-foreground: oklch(0.9851 0 0); + --sidebar-border: oklch(0.2809 0 0); + --sidebar-ring: oklch(0.8003 0.1821 151.7110); + --font-sans: 'Avenir Book', 'Avenir', 'Nunito Sans', -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, 'Helvetica Neue', Arial, sans-serif; + --font-serif: ui-serif, Georgia, Cambria, "Times New Roman", Times, serif; + --font-mono: monospace; + --radius: 0.5rem; + --shadow-x: 0px; + --shadow-y: 1px; + --shadow-blur: 3px; + --shadow-spread: 0px; + --shadow-opacity: 0.17; + --shadow-color: #000000; + --shadow-2xs: 0px 1px 3px 0px hsl(0 0% 0% / 0.09); + --shadow-xs: 0px 1px 3px 0px hsl(0 0% 0% / 0.09); + --shadow-sm: 0px 1px 3px 0px hsl(0 0% 0% / 0.17), 0px 1px 2px -1px hsl(0 0% 0% / 0.17); + --shadow: 0px 1px 3px 0px hsl(0 0% 0% / 0.17), 0px 1px 2px -1px hsl(0 0% 0% / 0.17); + --shadow-md: 0px 1px 3px 0px hsl(0 0% 0% / 0.17), 0px 2px 4px -1px hsl(0 0% 0% / 0.17); + --shadow-lg: 0px 1px 3px 0px hsl(0 0% 0% / 0.17), 0px 4px 6px -1px hsl(0 0% 0% / 0.17); + --shadow-xl: 0px 1px 3px 0px hsl(0 0% 0% / 0.17), 0px 8px 10px -1px hsl(0 0% 0% / 0.17); + --shadow-2xl: 0px 1px 3px 0px hsl(0 0% 0% / 0.43); +} + +@theme inline { + --color-background: var(--background); + --color-foreground: var(--foreground); + --color-card: var(--card); + --color-card-foreground: var(--card-foreground); + --color-popover: var(--popover); + --color-popover-foreground: var(--popover-foreground); + --color-primary: var(--primary); + --color-primary-foreground: var(--primary-foreground); + --color-secondary: var(--secondary); + --color-secondary-foreground: var(--secondary-foreground); + --color-muted: var(--muted); + --color-muted-foreground: var(--muted-foreground); + --color-accent: var(--accent); + --color-accent-foreground: var(--accent-foreground); + --color-destructive: var(--destructive); + --color-destructive-foreground: var(--destructive-foreground); + --color-border: var(--border); + --color-input: var(--input); + --color-ring: var(--ring); + --color-chart-1: var(--chart-1); + --color-chart-2: var(--chart-2); + --color-chart-3: var(--chart-3); + --color-chart-4: var(--chart-4); + --color-chart-5: var(--chart-5); + --color-sidebar: var(--sidebar); + --color-sidebar-foreground: var(--sidebar-foreground); + --color-sidebar-primary: var(--sidebar-primary); + --color-sidebar-primary-foreground: var(--sidebar-primary-foreground); + --color-sidebar-accent: var(--sidebar-accent); + --color-sidebar-accent-foreground: var(--sidebar-accent-foreground); + --color-sidebar-border: var(--sidebar-border); + --color-sidebar-ring: var(--sidebar-ring); + + --font-sans: var(--font-sans); + --font-mono: var(--font-mono); + --font-serif: var(--font-serif); + + --radius-sm: calc(var(--radius) - 4px); + --radius-md: calc(var(--radius) - 2px); + --radius-lg: var(--radius); + --radius-xl: calc(var(--radius) + 4px); + + --shadow-2xs: var(--shadow-2xs); + --shadow-xs: var(--shadow-xs); + --shadow-sm: var(--shadow-sm); + --shadow: var(--shadow); + --shadow-md: var(--shadow-md); + --shadow-lg: var(--shadow-lg); + --shadow-xl: var(--shadow-xl); + --shadow-2xl: var(--shadow-2xl); + + --tracking-tighter: calc(var(--tracking-normal) - 0.05em); + --tracking-tight: calc(var(--tracking-normal) - 0.025em); + --tracking-normal: var(--tracking-normal); + --tracking-wide: calc(var(--tracking-normal) + 0.025em); + --tracking-wider: calc(var(--tracking-normal) + 0.05em); + --tracking-widest: calc(var(--tracking-normal) + 0.1em); +} + +body { + font-family: var(--font-sans); + letter-spacing: var(--tracking-normal); +} \ No newline at end of file diff --git a/memora-control-plane/src/app/layout.tsx b/hindsight-control-plane/src/app/layout.tsx similarity index 73% rename from memora-control-plane/src/app/layout.tsx rename to hindsight-control-plane/src/app/layout.tsx index bbf3341a81..3978910bd8 100644 --- a/memora-control-plane/src/app/layout.tsx +++ b/hindsight-control-plane/src/app/layout.tsx @@ -1,12 +1,9 @@ import type { Metadata } from "next"; -import { Inter } from "next/font/google"; import "./globals.css"; import { AgentProvider } from "@/lib/agent-context"; -const inter = Inter({ subsets: ["latin"] }); - export const metadata: Metadata = { - title: "Memory Control Plane", + title: "Hindsight Control Plane", description: "Control plane for the temporal semantic memory system", }; @@ -17,7 +14,7 @@ export default function RootLayout({ }>) { return ( - + {children} diff --git a/memora-control-plane/src/app/page.tsx b/hindsight-control-plane/src/app/page.tsx similarity index 100% rename from memora-control-plane/src/app/page.tsx rename to hindsight-control-plane/src/app/page.tsx diff --git a/memora-control-plane/src/components/add-memory-view.tsx b/hindsight-control-plane/src/components/add-memory-view.tsx similarity index 100% rename from memora-control-plane/src/components/add-memory-view.tsx rename to hindsight-control-plane/src/components/add-memory-view.tsx diff --git a/memora-control-plane/src/components/agent-selector.tsx b/hindsight-control-plane/src/components/agent-selector.tsx similarity index 100% rename from memora-control-plane/src/components/agent-selector.tsx rename to hindsight-control-plane/src/components/agent-selector.tsx diff --git a/memora-control-plane/src/components/data-view.tsx b/hindsight-control-plane/src/components/data-view.tsx similarity index 100% rename from memora-control-plane/src/components/data-view.tsx rename to hindsight-control-plane/src/components/data-view.tsx diff --git a/memora-control-plane/src/components/documents-view.tsx b/hindsight-control-plane/src/components/documents-view.tsx similarity index 100% rename from memora-control-plane/src/components/documents-view.tsx rename to hindsight-control-plane/src/components/documents-view.tsx diff --git a/memora-control-plane/src/components/search-debug-view.tsx b/hindsight-control-plane/src/components/search-debug-view.tsx similarity index 100% rename from memora-control-plane/src/components/search-debug-view.tsx rename to hindsight-control-plane/src/components/search-debug-view.tsx diff --git a/memora-control-plane/src/components/stats-view.tsx b/hindsight-control-plane/src/components/stats-view.tsx similarity index 100% rename from memora-control-plane/src/components/stats-view.tsx rename to hindsight-control-plane/src/components/stats-view.tsx diff --git a/memora-control-plane/src/components/think-view.tsx b/hindsight-control-plane/src/components/think-view.tsx similarity index 100% rename from memora-control-plane/src/components/think-view.tsx rename to hindsight-control-plane/src/components/think-view.tsx diff --git a/memora-control-plane/src/lib/agent-context.tsx b/hindsight-control-plane/src/lib/agent-context.tsx similarity index 100% rename from memora-control-plane/src/lib/agent-context.tsx rename to hindsight-control-plane/src/lib/agent-context.tsx diff --git a/memora-control-plane/src/lib/api.ts b/hindsight-control-plane/src/lib/api.ts similarity index 98% rename from memora-control-plane/src/lib/api.ts rename to hindsight-control-plane/src/lib/api.ts index 66814513bd..a43dc58046 100644 --- a/memora-control-plane/src/lib/api.ts +++ b/hindsight-control-plane/src/lib/api.ts @@ -203,7 +203,7 @@ export class ServerDataplaneClient { private baseUrl: string; constructor() { - this.baseUrl = process.env.MEMORA_CP_DATAPLANE_API_URL || 'http://localhost:8080'; + this.baseUrl = process.env.HINDSIGHT_CP_DATAPLANE_API_URL || 'http://localhost:8888'; } async fetchDataplane( diff --git a/memora-control-plane/src/lib/utils.ts b/hindsight-control-plane/src/lib/utils.ts similarity index 100% rename from memora-control-plane/src/lib/utils.ts rename to hindsight-control-plane/src/lib/utils.ts diff --git a/memora-control-plane/tailwind.config.ts b/hindsight-control-plane/tailwind.config.ts similarity index 100% rename from memora-control-plane/tailwind.config.ts rename to hindsight-control-plane/tailwind.config.ts diff --git a/memora-control-plane/tsconfig.json b/hindsight-control-plane/tsconfig.json similarity index 100% rename from memora-control-plane/tsconfig.json rename to hindsight-control-plane/tsconfig.json diff --git a/memora-dev/README.md b/hindsight-dev/README.md similarity index 100% rename from memora-dev/README.md rename to hindsight-dev/README.md diff --git a/memora-dev/benchmarks/.DS_Store b/hindsight-dev/benchmarks/.DS_Store similarity index 100% rename from memora-dev/benchmarks/.DS_Store rename to hindsight-dev/benchmarks/.DS_Store diff --git a/memora-dev/benchmarks/__init__.py b/hindsight-dev/benchmarks/__init__.py similarity index 100% rename from memora-dev/benchmarks/__init__.py rename to hindsight-dev/benchmarks/__init__.py diff --git a/memora-dev/benchmarks/benchmarks-results/locomo/73.5.json b/hindsight-dev/benchmarks/benchmarks-results/locomo/73.5.json similarity index 100% rename from memora-dev/benchmarks/benchmarks-results/locomo/73.5.json rename to hindsight-dev/benchmarks/benchmarks-results/locomo/73.5.json diff --git a/memora-dev/benchmarks/benchmarks-results/locomo/75.8_think.json b/hindsight-dev/benchmarks/benchmarks-results/locomo/75.8_think.json similarity index 100% rename from memora-dev/benchmarks/benchmarks-results/locomo/75.8_think.json rename to hindsight-dev/benchmarks/benchmarks-results/locomo/75.8_think.json diff --git a/memora-dev/benchmarks/benchmarks-results/longmemeval/final.json b/hindsight-dev/benchmarks/benchmarks-results/longmemeval/final.json similarity index 100% rename from memora-dev/benchmarks/benchmarks-results/longmemeval/final.json rename to hindsight-dev/benchmarks/benchmarks-results/longmemeval/final.json diff --git a/memora-dev/benchmarks/common/__init__.py b/hindsight-dev/benchmarks/common/__init__.py similarity index 100% rename from memora-dev/benchmarks/common/__init__.py rename to hindsight-dev/benchmarks/common/__init__.py diff --git a/memora-dev/benchmarks/common/benchmark_runner.py b/hindsight-dev/benchmarks/common/benchmark_runner.py similarity index 83% rename from memora-dev/benchmarks/common/benchmark_runner.py rename to hindsight-dev/benchmarks/common/benchmark_runner.py index 16a7900cca..a50d80799c 100644 --- a/memora-dev/benchmarks/common/benchmark_runner.py +++ b/hindsight-dev/benchmarks/common/benchmark_runner.py @@ -30,12 +30,268 @@ from rich import box import pydantic -from memora import TemporalSemanticMemory +from hindsight_api import TemporalSemanticMemory from openai import AsyncOpenAI console = Console() +class HindsightClientAdapter: + """ + Adapter that wraps the Hindsight Python client to provide the interface + expected by the benchmark runner. + + This allows benchmarks to use the Python client instead of RemoteMemoryClient + while maintaining the same interface for put_batch_async, search_async, etc. + """ + + def __init__(self, base_url: str = "http://localhost:8888", timeout: float = 300.0): + """ + Initialize the adapter with the Hindsight client. + + Args: + base_url: Base URL of the Hindsight API server + timeout: Request timeout in seconds + """ + from hindsight_client import Hindsight + self.base_url = base_url.rstrip('/') + self.timeout = timeout + self.client = Hindsight(base_url=base_url, timeout=timeout) + + async def initialize(self): + """Initialize the client (no-op for HTTP client).""" + pass + + async def close(self): + """Close the HTTP client.""" + self.client.close() + + async def put_batch_async( + self, + agent_id: str, + contents: List[Dict[str, Any]], + document_id: Optional[str] = None + ) -> Dict[str, Any]: + """ + Store multiple memory items via API. + + Args: + agent_id: Agent identifier + contents: List of content dicts with 'content', 'event_date', 'context' keys + document_id: Optional document identifier + + Returns: + Result dict with success status + """ + # Convert to format expected by client + items = [] + for content in contents: + item = {"content": content["content"]} + if "event_date" in content and content["event_date"]: + item["event_date"] = content["event_date"] + if "context" in content and content["context"]: + item["context"] = content["context"] + items.append(item) + + return await self.client.aput_batch( + agent_id=agent_id, + items=items, + document_id=document_id, + ) + + async def search_async( + self, + agent_id: str, + query: str, + thinking_budget: int = 100, + max_tokens: int = 4096, + enable_trace: bool = False, + reranker: str = "heuristic", + fact_type: Optional[List[str]] = None, + question_date: Optional[datetime] = None + ) -> 'SearchResult': + """ + Search memories via API. + + Returns: + SearchResult object with results list + """ + from hindsight_client_api.models import search_request + + request_obj = search_request.SearchRequest( + query=query, + fact_type=fact_type, + thinking_budget=thinking_budget, + max_tokens=max_tokens, + trace=enable_trace, + question_date=question_date.isoformat() if question_date else None, + ) + + response = await self.client._memory_api.search_memories(agent_id, request_obj) + + # Convert to expected format - wrap results in an object with .results attribute + class SearchResult: + def __init__(self, results): + self.results = results + + class MemoryFact: + def __init__(self, data): + self._data = data + + def model_dump(self): + return self._data + + results = [] + if hasattr(response, 'results'): + for r in response.results: + data = r.to_dict() if hasattr(r, 'to_dict') else r + results.append(MemoryFact(data)) + + return SearchResult(results) + + async def think_async( + self, + agent_id: str, + query: str, + thinking_budget: int = 50, + context: str = None + ) -> 'ThinkResult': + """ + Generate answer using think API. + + Returns: + ThinkResult object with text, based_on, and new_opinions + """ + response = await self.client.athink( + agent_id=agent_id, + query=query, + thinking_budget=thinking_budget, + context=context, + ) + + # Convert to expected format with attribute access + class MemoryFact: + def __init__(self, data): + self._data = data + + def model_dump(self): + return self._data + + def get(self, key, default=None): + return self._data.get(key, default) + + class ThinkResult: + def __init__(self, data): + self.text = data.get('text', '') + # Convert based_on facts to MemoryFact objects + based_on_raw = data.get('based_on', {}) + self.based_on = { + 'world': [MemoryFact(f) for f in based_on_raw.get('world', [])], + 'agent': [MemoryFact(f) for f in based_on_raw.get('agent', [])], + 'opinion': [MemoryFact(f) for f in based_on_raw.get('opinion', [])], + } + self.new_opinions = data.get('new_opinions', []) + + return ThinkResult(response) + + async def delete_agent(self, agent_id: str) -> Dict[str, Any]: + """ + Delete all data for an agent. + + Args: + agent_id: Agent identifier + + Returns: + Result dict + """ + import httpx + async with httpx.AsyncClient(timeout=self.timeout) as client: + response = await client.delete(f"{self.base_url}/api/v1/agents/{agent_id}") + if response.status_code == 404: + return {"success": True, "message": "Agent not found (already deleted)"} + response.raise_for_status() + return response.json() + + async def list_agents(self) -> List[str]: + """ + List all agents. + + Returns: + List of agent IDs + """ + import httpx + async with httpx.AsyncClient(timeout=self.timeout) as client: + response = await client.get(f"{self.base_url}/api/v1/agents") + response.raise_for_status() + result = response.json() + return [a.get('agent_id', a) if isinstance(a, dict) else a for a in result.get("agents", [])] + + async def get_agent_stats(self, agent_id: str) -> Dict[str, Any]: + """ + Get statistics for an agent. + + Args: + agent_id: Agent identifier + + Returns: + Dict with statistics including total_nodes, total_links, and pending_operations + """ + import httpx + async with httpx.AsyncClient(timeout=self.timeout) as client: + response = await client.get(f"{self.base_url}/api/v1/agents/{agent_id}/stats") + response.raise_for_status() + return response.json() + + async def wait_for_backlog_completion( + self, + agent_id: str, + poll_interval: float = 1.0, + timeout: float = 300.0, + verbose: bool = True + ) -> Dict[str, Any]: + """ + Poll agent stats until pending_operations is zero or timeout is reached. + + Args: + agent_id: Agent identifier + poll_interval: Time to wait between polls in seconds + timeout: Maximum time to wait in seconds + verbose: Whether to print status updates + + Returns: + Final stats dict + + Raises: + TimeoutError: If pending_operations doesn't clear within timeout + """ + import time + start_time = time.time() + + while True: + elapsed = time.time() - start_time + if elapsed > timeout: + raise TimeoutError( + f"Timeout waiting for pending operations to clear for agent '{agent_id}' " + f"after {timeout}s" + ) + + stats = await self.get_agent_stats(agent_id) + pending_operations = stats.get("pending_operations", 0) + + if verbose: + print( + f"Agent '{agent_id}' pending operations: {pending_operations} " + f"(elapsed: {elapsed:.1f}s)" + ) + + if pending_operations == 0: + if verbose: + print(f"All operations completed for agent '{agent_id}' in {elapsed:.1f}s") + return stats + + await asyncio.sleep(poll_interval) + + class BenchmarkDataset(ABC): """Abstract base class for benchmark datasets.""" @@ -125,7 +381,7 @@ class LLMAnswerEvaluator: def __init__(self): """Initialize with LLM configuration for judge/evaluator.""" - from memora.llm_wrapper import LLMConfig + from hindsight_api.llm_wrapper import LLMConfig self.llm_config = LLMConfig.for_judge() self.client = self.llm_config._client self.model = self.llm_config.model @@ -230,11 +486,11 @@ def __init__( self.answer_generator = answer_generator self.answer_evaluator = answer_evaluator self.memory = memory or TemporalSemanticMemory( - db_url=os.getenv("MEMORA_API_DATABASE_URL"), - memory_llm_provider=os.getenv("MEMORA_API_LLM_PROVIDER", "groq"), - memory_llm_api_key=os.getenv("MEMORA_API_LLM_API_KEY"), - memory_llm_model=os.getenv("MEMORA_API_LLM_MODEL", "openai/gpt-oss-120b"), - memory_llm_base_url=os.getenv("MEMORA_API_LLM_BASE_URL") or None, # Use None to get provider defaults + db_url=os.getenv("HINDSIGHT_API_DATABASE_URL"), + memory_llm_provider=os.getenv("HINDSIGHT_API_LLM_PROVIDER", "groq"), + memory_llm_api_key=os.getenv("HINDSIGHT_API_LLM_API_KEY"), + memory_llm_model=os.getenv("HINDSIGHT_API_LLM_MODEL", "openai/gpt-oss-120b"), + memory_llm_base_url=os.getenv("HINDSIGHT_API_LLM_BASE_URL") or None, # Use None to get provider defaults ) def calculate_data_stats(self, items: List[Dict[str, Any]]) -> Dict[str, Any]: @@ -290,8 +546,7 @@ async def ingest_conversation( ) # If using remote API, wait for this batch to complete before continuing - from memora.remote_client import RemoteMemoryClient - if isinstance(self.memory, RemoteMemoryClient): + if isinstance(self.memory, HindsightClientAdapter): await self.memory.wait_for_backlog_completion(agent_id, verbose=False) return len(batch_contents) @@ -550,9 +805,7 @@ async def _agent_has_data(self, agent_id: str) -> bool: """ try: # Check if we're using a remote client or local memory - from memora.remote_client import RemoteMemoryClient - - if isinstance(self.memory, RemoteMemoryClient): + if isinstance(self.memory, HindsightClientAdapter): # Use stats API for remote client stats = await self.memory.get_agent_stats(agent_id) total_nodes = stats.get("total_nodes", 0) @@ -880,8 +1133,7 @@ async def _run_two_phase( More realistic scenario where agent accumulates memories over time. """ # Check if using remote API client - from memora.remote_client import RemoteMemoryClient - is_remote = isinstance(self.memory, RemoteMemoryClient) + is_remote = isinstance(self.memory, HindsightClientAdapter) # Phase 1: Ingestion if not skip_ingestion: diff --git a/memora-dev/benchmarks/locomo/__init__.py b/hindsight-dev/benchmarks/locomo/__init__.py similarity index 100% rename from memora-dev/benchmarks/locomo/__init__.py rename to hindsight-dev/benchmarks/locomo/__init__.py diff --git a/memora-dev/benchmarks/locomo/datasets/locomo10.json b/hindsight-dev/benchmarks/locomo/datasets/locomo10.json similarity index 100% rename from memora-dev/benchmarks/locomo/datasets/locomo10.json rename to hindsight-dev/benchmarks/locomo/datasets/locomo10.json diff --git a/memora-dev/benchmarks/locomo/locomo_benchmark.py b/hindsight-dev/benchmarks/locomo/locomo_benchmark.py similarity index 96% rename from memora-dev/benchmarks/locomo/locomo_benchmark.py rename to hindsight-dev/benchmarks/locomo/locomo_benchmark.py index 5ca70cbdf2..c1fe028d5c 100644 --- a/memora-dev/benchmarks/locomo/locomo_benchmark.py +++ b/hindsight-dev/benchmarks/locomo/locomo_benchmark.py @@ -7,7 +7,7 @@ from pathlib import Path from benchmarks.common.benchmark_runner import BenchmarkRunner -from memora import TemporalSemanticMemory +from hindsight_api import TemporalSemanticMemory import json from datetime import datetime, timezone @@ -18,7 +18,7 @@ import os from benchmarks.common.benchmark_runner import BenchmarkDataset, LLMAnswerGenerator, LLMAnswerEvaluator -from memora.llm_wrapper import LLMConfig +from hindsight_api.llm_wrapper import LLMConfig class LoComoDataset(BenchmarkDataset): """LoComo dataset implementation.""" @@ -365,15 +365,15 @@ async def run_benchmark( # Use remote API client if api_url is provided, otherwise use local memory if api_url: - from memora.remote_client import RemoteMemoryClient - memory = RemoteMemoryClient(base_url=api_url) + from benchmarks.common.benchmark_runner import HindsightClientAdapter + memory = HindsightClientAdapter(base_url=api_url) else: memory = TemporalSemanticMemory( - db_url=os.getenv("MEMORA_API_DATABASE_URL"), - memory_llm_provider=os.getenv("MEMORA_API_LLM_PROVIDER", "groq"), - memory_llm_api_key=os.getenv("MEMORA_API_LLM_API_KEY"), - memory_llm_model=os.getenv("MEMORA_API_LLM_MODEL", "openai/gpt-oss-120b"), - memory_llm_base_url=os.getenv("MEMORA_API_LLM_BASE_URL") or None, # Use None to get provider defaults + db_url=os.getenv("HINDSIGHT_API_DATABASE_URL"), + memory_llm_provider=os.getenv("HINDSIGHT_API_LLM_PROVIDER", "groq"), + memory_llm_api_key=os.getenv("HINDSIGHT_API_LLM_API_KEY"), + memory_llm_model=os.getenv("HINDSIGHT_API_LLM_MODEL", "openai/gpt-oss-120b"), + memory_llm_base_url=os.getenv("HINDSIGHT_API_LLM_BASE_URL") or None, # Use None to get provider defaults ) await memory.initialize() @@ -525,7 +525,7 @@ def generate_markdown_table(results: dict, use_think: bool = False): parser.add_argument('--skip-ingestion', action='store_true', help='Skip ingestion and use existing data') parser.add_argument('--use-think', action='store_true', help='Use think API instead of search + LLM') parser.add_argument('--conversation', type=str, default=None, help='Run only specific conversation (e.g., "conv-26")') - parser.add_argument('--api-url', type=str, default=None, help='Memora API URL (default: use local memory, example: http://localhost:8000)') + parser.add_argument('--api-url', type=str, default=None, help='Hindsight API URL (default: use local memory, example: http://localhost:8888)') parser.add_argument('--max-concurrent-questions', type=int, default=None, help='Max concurrent questions per conversation (default: 4 for think, 10 for search)') parser.add_argument('--only-failed', action='store_true', help='Only run conversations that have failed questions (is_correct=False). Requires existing results file.') parser.add_argument('--only-invalid', action='store_true', help='Only run conversations that have invalid questions (is_invalid=True). Requires existing results file.') diff --git a/memora-dev/benchmarks/locomo/results/benchmark_results.json b/hindsight-dev/benchmarks/locomo/results/benchmark_results.json similarity index 100% rename from memora-dev/benchmarks/locomo/results/benchmark_results.json rename to hindsight-dev/benchmarks/locomo/results/benchmark_results.json diff --git a/memora-dev/benchmarks/locomo/results/benchmark_results_think.json b/hindsight-dev/benchmarks/locomo/results/benchmark_results_think.json similarity index 100% rename from memora-dev/benchmarks/locomo/results/benchmark_results_think.json rename to hindsight-dev/benchmarks/locomo/results/benchmark_results_think.json diff --git a/memora-dev/benchmarks/locomo/results/results_table.md b/hindsight-dev/benchmarks/locomo/results/results_table.md similarity index 100% rename from memora-dev/benchmarks/locomo/results/results_table.md rename to hindsight-dev/benchmarks/locomo/results/results_table.md diff --git a/memora-dev/benchmarks/locomo/results/results_table_think.md b/hindsight-dev/benchmarks/locomo/results/results_table_think.md similarity index 100% rename from memora-dev/benchmarks/locomo/results/results_table_think.md rename to hindsight-dev/benchmarks/locomo/results/results_table_think.md diff --git a/memora-dev/benchmarks/longmemeval/__init__.py b/hindsight-dev/benchmarks/longmemeval/__init__.py similarity index 100% rename from memora-dev/benchmarks/longmemeval/__init__.py rename to hindsight-dev/benchmarks/longmemeval/__init__.py diff --git a/memora-dev/benchmarks/longmemeval/longmemeval_benchmark.py b/hindsight-dev/benchmarks/longmemeval/longmemeval_benchmark.py similarity index 96% rename from memora-dev/benchmarks/longmemeval/longmemeval_benchmark.py rename to hindsight-dev/benchmarks/longmemeval/longmemeval_benchmark.py index 853b154eb5..882469cd28 100644 --- a/memora-dev/benchmarks/longmemeval/longmemeval_benchmark.py +++ b/hindsight-dev/benchmarks/longmemeval/longmemeval_benchmark.py @@ -7,7 +7,7 @@ from pathlib import Path from benchmarks.common.benchmark_runner import BenchmarkRunner -from memora import TemporalSemanticMemory +from hindsight_api import TemporalSemanticMemory import json from datetime import datetime, timezone @@ -18,7 +18,7 @@ import os from benchmarks.common.benchmark_runner import BenchmarkDataset, LLMAnswerGenerator, LLMAnswerEvaluator -from memora.llm_wrapper import LLMConfig +from hindsight_api.llm_wrapper import LLMConfig class LongMemEvalDataset(BenchmarkDataset): @@ -327,15 +327,15 @@ async def run_benchmark( # Use remote API client if api_url is provided, otherwise use local memory if api_url: - from memora.remote_client import RemoteMemoryClient - memory = RemoteMemoryClient(base_url=api_url) + from benchmarks.common.benchmark_runner import HindsightClientAdapter + memory = HindsightClientAdapter(base_url=api_url) else: memory = TemporalSemanticMemory( - db_url=os.getenv("MEMORA_API_DATABASE_URL"), - memory_llm_provider=os.getenv("MEMORA_API_LLM_PROVIDER", "groq"), - memory_llm_api_key=os.getenv("MEMORA_API_LLM_API_KEY"), - memory_llm_model=os.getenv("MEMORA_API_LLM_MODEL", "openai/gpt-oss-120b"), - memory_llm_base_url=os.getenv("MEMORA_API_LLM_BASE_URL") or None, # Use None to get provider defaults + db_url=os.getenv("HINDSIGHT_API_DATABASE_URL"), + memory_llm_provider=os.getenv("HINDSIGHT_API_LLM_PROVIDER", "groq"), + memory_llm_api_key=os.getenv("HINDSIGHT_API_LLM_API_KEY"), + memory_llm_model=os.getenv("HINDSIGHT_API_LLM_MODEL", "openai/gpt-oss-120b"), + memory_llm_base_url=os.getenv("HINDSIGHT_API_LLM_BASE_URL") or None, # Use None to get provider defaults ) # Create benchmark runner @@ -510,7 +510,7 @@ def generate_type_report(results: dict): "--api-url", type=str, default=None, - help="Memora API URL (default: use local memory, example: http://localhost:8000)" + help="Hindsight API URL (default: use local memory, example: http://localhost:8888)" ) parser.add_argument( "--fill", diff --git a/memora-dev/benchmarks/longmemeval/results/benchmark_results.json b/hindsight-dev/benchmarks/longmemeval/results/benchmark_results.json similarity index 100% rename from memora-dev/benchmarks/longmemeval/results/benchmark_results.json rename to hindsight-dev/benchmarks/longmemeval/results/benchmark_results.json diff --git a/memora-dev/benchmarks/pyproject.toml b/hindsight-dev/benchmarks/pyproject.toml similarity index 74% rename from memora-dev/benchmarks/pyproject.toml rename to hindsight-dev/benchmarks/pyproject.toml index 124883f817..db49c24e81 100644 --- a/memora-dev/benchmarks/pyproject.toml +++ b/hindsight-dev/benchmarks/pyproject.toml @@ -5,7 +5,7 @@ build-backend = "hatchling.build" [project] name = "benchmarks" version = "0.0.7" -description = "Benchmarks for Memora memory system" +description = "Benchmarks for Hindsight memory system" requires-python = ">=3.11" dependencies = [ "python-fasthtml>=0.12.33", @@ -13,10 +13,11 @@ dependencies = [ "openai>=1.0.0", "rich>=13.0.0", "pydantic>=2.0.0", + "hindsight-api", ] [tool.hatch.build.targets.wheel] packages = ["benchmarks"] [tool.uv.sources] -memora = { path = "../../memora" } +hindsight-api = { path = "../../hindsight-api" } diff --git a/memora-dev/benchmarks/uv.lock b/hindsight-dev/benchmarks/uv.lock similarity index 100% rename from memora-dev/benchmarks/uv.lock rename to hindsight-dev/benchmarks/uv.lock diff --git a/memora-dev/benchmarks/visualizer/.sesskey b/hindsight-dev/benchmarks/visualizer/.sesskey similarity index 100% rename from memora-dev/benchmarks/visualizer/.sesskey rename to hindsight-dev/benchmarks/visualizer/.sesskey diff --git a/memora-dev/benchmarks/visualizer/__init__.py b/hindsight-dev/benchmarks/visualizer/__init__.py similarity index 100% rename from memora-dev/benchmarks/visualizer/__init__.py rename to hindsight-dev/benchmarks/visualizer/__init__.py diff --git a/memora-dev/benchmarks/visualizer/main.py b/hindsight-dev/benchmarks/visualizer/main.py similarity index 100% rename from memora-dev/benchmarks/visualizer/main.py rename to hindsight-dev/benchmarks/visualizer/main.py diff --git a/hindsight-dev/hindsight_dev/__init__.py b/hindsight-dev/hindsight_dev/__init__.py new file mode 100644 index 0000000000..d338c7158a --- /dev/null +++ b/hindsight-dev/hindsight_dev/__init__.py @@ -0,0 +1 @@ +"""Utility scripts for Hindsight development.""" diff --git a/memora-dev/memora_dev/generate_openapi.py b/hindsight-dev/hindsight_dev/generate_openapi.py similarity index 95% rename from memora-dev/memora_dev/generate_openapi.py rename to hindsight-dev/hindsight_dev/generate_openapi.py index 5c95e6388a..30e24031cf 100644 --- a/memora-dev/memora_dev/generate_openapi.py +++ b/hindsight-dev/hindsight_dev/generate_openapi.py @@ -9,8 +9,8 @@ import os from pathlib import Path -from memora.api import create_app -from memora import TemporalSemanticMemory +from hindsight_api.api import create_app +from hindsight_api import TemporalSemanticMemory def generate_openapi_spec(output_path: str = None): """Generate OpenAPI spec and save to file.""" diff --git a/hindsight-dev/pyproject.toml b/hindsight-dev/pyproject.toml new file mode 100644 index 0000000000..9fc59eee83 --- /dev/null +++ b/hindsight-dev/pyproject.toml @@ -0,0 +1,21 @@ +[build-system] +requires = ["hatchling"] +build-backend = "hatchling.build" + +[project] +name = "hindsight-dev" +version = "0.0.7" +description = "Development utilities for Hindsight" +requires-python = ">=3.11" +dependencies = [ + "hindsight-api", +] + +[tool.hatch.build.targets.wheel] +packages = ["hindsight_dev"] + +[tool.uv.sources] +hindsight-api = { workspace = true } + +[project.scripts] +generate-openapi = "hindsight_dev.generate_openapi:generate_openapi_spec" diff --git a/memora-docs/.gitignore b/hindsight-docs/.gitignore similarity index 100% rename from memora-docs/.gitignore rename to hindsight-docs/.gitignore diff --git a/memora-docs/README.md b/hindsight-docs/README.md similarity index 100% rename from memora-docs/README.md rename to hindsight-docs/README.md diff --git a/memora-docs/docs/api-reference/endpoints/add-agent-background.api.mdx b/hindsight-docs/docs/api-reference/endpoints/add-agent-background.api.mdx similarity index 100% rename from memora-docs/docs/api-reference/endpoints/add-agent-background.api.mdx rename to hindsight-docs/docs/api-reference/endpoints/add-agent-background.api.mdx diff --git a/memora-docs/docs/api-reference/endpoints/agent-memory-api.info.mdx b/hindsight-docs/docs/api-reference/endpoints/agent-memory-api.info.mdx similarity index 100% rename from memora-docs/docs/api-reference/endpoints/agent-memory-api.info.mdx rename to hindsight-docs/docs/api-reference/endpoints/agent-memory-api.info.mdx diff --git a/memora-docs/docs/api-reference/endpoints/batch-put-async.api.mdx b/hindsight-docs/docs/api-reference/endpoints/batch-put-async.api.mdx similarity index 100% rename from memora-docs/docs/api-reference/endpoints/batch-put-async.api.mdx rename to hindsight-docs/docs/api-reference/endpoints/batch-put-async.api.mdx diff --git a/memora-docs/docs/api-reference/endpoints/batch-put-memories.api.mdx b/hindsight-docs/docs/api-reference/endpoints/batch-put-memories.api.mdx similarity index 100% rename from memora-docs/docs/api-reference/endpoints/batch-put-memories.api.mdx rename to hindsight-docs/docs/api-reference/endpoints/batch-put-memories.api.mdx diff --git a/memora-docs/docs/api-reference/endpoints/cancel-operation.api.mdx b/hindsight-docs/docs/api-reference/endpoints/cancel-operation.api.mdx similarity index 100% rename from memora-docs/docs/api-reference/endpoints/cancel-operation.api.mdx rename to hindsight-docs/docs/api-reference/endpoints/cancel-operation.api.mdx diff --git a/memora-docs/docs/api-reference/endpoints/clear-agent-memories.api.mdx b/hindsight-docs/docs/api-reference/endpoints/clear-agent-memories.api.mdx similarity index 100% rename from memora-docs/docs/api-reference/endpoints/clear-agent-memories.api.mdx rename to hindsight-docs/docs/api-reference/endpoints/clear-agent-memories.api.mdx diff --git a/memora-docs/docs/api-reference/endpoints/create-or-update-agent.api.mdx b/hindsight-docs/docs/api-reference/endpoints/create-or-update-agent.api.mdx similarity index 100% rename from memora-docs/docs/api-reference/endpoints/create-or-update-agent.api.mdx rename to hindsight-docs/docs/api-reference/endpoints/create-or-update-agent.api.mdx diff --git a/memora-docs/docs/api-reference/endpoints/delete-document.api.mdx b/hindsight-docs/docs/api-reference/endpoints/delete-document.api.mdx similarity index 100% rename from memora-docs/docs/api-reference/endpoints/delete-document.api.mdx rename to hindsight-docs/docs/api-reference/endpoints/delete-document.api.mdx diff --git a/memora-docs/docs/api-reference/endpoints/delete-memory-unit.api.mdx b/hindsight-docs/docs/api-reference/endpoints/delete-memory-unit.api.mdx similarity index 100% rename from memora-docs/docs/api-reference/endpoints/delete-memory-unit.api.mdx rename to hindsight-docs/docs/api-reference/endpoints/delete-memory-unit.api.mdx diff --git a/memora-docs/docs/api-reference/endpoints/get-agent-profile.api.mdx b/hindsight-docs/docs/api-reference/endpoints/get-agent-profile.api.mdx similarity index 100% rename from memora-docs/docs/api-reference/endpoints/get-agent-profile.api.mdx rename to hindsight-docs/docs/api-reference/endpoints/get-agent-profile.api.mdx diff --git a/memora-docs/docs/api-reference/endpoints/get-agent-stats.api.mdx b/hindsight-docs/docs/api-reference/endpoints/get-agent-stats.api.mdx similarity index 100% rename from memora-docs/docs/api-reference/endpoints/get-agent-stats.api.mdx rename to hindsight-docs/docs/api-reference/endpoints/get-agent-stats.api.mdx diff --git a/memora-docs/docs/api-reference/endpoints/get-document.api.mdx b/hindsight-docs/docs/api-reference/endpoints/get-document.api.mdx similarity index 100% rename from memora-docs/docs/api-reference/endpoints/get-document.api.mdx rename to hindsight-docs/docs/api-reference/endpoints/get-document.api.mdx diff --git a/memora-docs/docs/api-reference/endpoints/get-graph.api.mdx b/hindsight-docs/docs/api-reference/endpoints/get-graph.api.mdx similarity index 100% rename from memora-docs/docs/api-reference/endpoints/get-graph.api.mdx rename to hindsight-docs/docs/api-reference/endpoints/get-graph.api.mdx diff --git a/memora-docs/docs/api-reference/endpoints/list-agents.api.mdx b/hindsight-docs/docs/api-reference/endpoints/list-agents.api.mdx similarity index 100% rename from memora-docs/docs/api-reference/endpoints/list-agents.api.mdx rename to hindsight-docs/docs/api-reference/endpoints/list-agents.api.mdx diff --git a/memora-docs/docs/api-reference/endpoints/list-documents.api.mdx b/hindsight-docs/docs/api-reference/endpoints/list-documents.api.mdx similarity index 100% rename from memora-docs/docs/api-reference/endpoints/list-documents.api.mdx rename to hindsight-docs/docs/api-reference/endpoints/list-documents.api.mdx diff --git a/memora-docs/docs/api-reference/endpoints/list-memories.api.mdx b/hindsight-docs/docs/api-reference/endpoints/list-memories.api.mdx similarity index 100% rename from memora-docs/docs/api-reference/endpoints/list-memories.api.mdx rename to hindsight-docs/docs/api-reference/endpoints/list-memories.api.mdx diff --git a/memora-docs/docs/api-reference/endpoints/list-operations.api.mdx b/hindsight-docs/docs/api-reference/endpoints/list-operations.api.mdx similarity index 100% rename from memora-docs/docs/api-reference/endpoints/list-operations.api.mdx rename to hindsight-docs/docs/api-reference/endpoints/list-operations.api.mdx diff --git a/memora-docs/docs/api-reference/endpoints/search-memories.api.mdx b/hindsight-docs/docs/api-reference/endpoints/search-memories.api.mdx similarity index 100% rename from memora-docs/docs/api-reference/endpoints/search-memories.api.mdx rename to hindsight-docs/docs/api-reference/endpoints/search-memories.api.mdx diff --git a/memora-docs/docs/api-reference/endpoints/sidebar.ts b/hindsight-docs/docs/api-reference/endpoints/sidebar.ts similarity index 94% rename from memora-docs/docs/api-reference/endpoints/sidebar.ts rename to hindsight-docs/docs/api-reference/endpoints/sidebar.ts index 22fee18574..570daac3fc 100644 --- a/memora-docs/docs/api-reference/endpoints/sidebar.ts +++ b/hindsight-docs/docs/api-reference/endpoints/sidebar.ts @@ -9,6 +9,8 @@ const sidebar: SidebarsConfig = { { type: "category", label: "Visualization", + collapsed: false, + collapsible: false, items: [ { type: "doc", @@ -21,6 +23,8 @@ const sidebar: SidebarsConfig = { { type: "category", label: "Memory Operations", + collapsed: false, + collapsible: false, items: [ { type: "doc", @@ -69,6 +73,8 @@ const sidebar: SidebarsConfig = { { type: "category", label: "Reasoning", + collapsed: false, + collapsible: false, items: [ { type: "doc", @@ -81,6 +87,8 @@ const sidebar: SidebarsConfig = { { type: "category", label: "Agent Management", + collapsed: false, + collapsible: false, items: [ { type: "doc", @@ -129,6 +137,8 @@ const sidebar: SidebarsConfig = { { type: "category", label: "Documents", + collapsed: false, + collapsible: false, items: [ { type: "doc", diff --git a/memora-docs/docs/api-reference/endpoints/think.api.mdx b/hindsight-docs/docs/api-reference/endpoints/think.api.mdx similarity index 100% rename from memora-docs/docs/api-reference/endpoints/think.api.mdx rename to hindsight-docs/docs/api-reference/endpoints/think.api.mdx diff --git a/memora-docs/docs/api-reference/endpoints/update-agent-personality.api.mdx b/hindsight-docs/docs/api-reference/endpoints/update-agent-personality.api.mdx similarity index 100% rename from memora-docs/docs/api-reference/endpoints/update-agent-personality.api.mdx rename to hindsight-docs/docs/api-reference/endpoints/update-agent-personality.api.mdx diff --git a/memora-docs/docs/api-reference/index.md b/hindsight-docs/docs/api-reference/index.md similarity index 55% rename from memora-docs/docs/api-reference/index.md rename to hindsight-docs/docs/api-reference/index.md index 94494fcc94..c94f00e180 100644 --- a/memora-docs/docs/api-reference/index.md +++ b/hindsight-docs/docs/api-reference/index.md @@ -4,13 +4,13 @@ sidebar_position: 1 # API Reference -Complete reference for Memora's HTTP and MCP APIs. +Complete reference for Hindsight's HTTP and MCP APIs. ## HTTP API The HTTP API reference is automatically generated from our OpenAPI specification. Browse the endpoints in the sidebar to see request/response details, parameters, and examples. -**Base URL:** `http://localhost:8080` +**Base URL:** `http://localhost:8888` | Category | Endpoints | |----------|-----------| @@ -22,20 +22,20 @@ The HTTP API reference is automatically generated from our OpenAPI specification ## MCP API -The MCP (Model Context Protocol) API exposes Memora tools for AI assistants like Claude Desktop. +The MCP (Model Context Protocol) API exposes Hindsight tools for AI assistants like Claude Desktop. | Tool | Description | |------|-------------| -| `memora_search` | Search memories | -| `memora_think` | Generate personality-aware response | -| `memora_store` | Store new memory | -| `memora_agents` | List available agents | +| `hindsight_search` | Search memories | +| `hindsight_think` | Generate personality-aware response | +| `hindsight_store` | Store new memory | +| `hindsight_agents` | List available agents | -[MCP Tools Reference โ†’](./mcp) +[MCP Tools Reference โ†’](/api-reference/mcp) ## OpenAPI / Swagger Interactive API documentation available when the server is running: -- **Swagger UI:** [http://localhost:8080/docs](http://localhost:8080/docs) -- **OpenAPI JSON:** [http://localhost:8080/openapi.json](http://localhost:8080/openapi.json) +- **Swagger UI:** [http://localhost:8888/docs](http://localhost:8888/docs) +- **OpenAPI JSON:** [http://localhost:8888/openapi.json](http://localhost:8888/openapi.json) diff --git a/memora-docs/docs/api-reference/mcp.md b/hindsight-docs/docs/api-reference/mcp.md similarity index 87% rename from memora-docs/docs/api-reference/mcp.md rename to hindsight-docs/docs/api-reference/mcp.md index 092c6f9cbd..81acebae5a 100644 --- a/memora-docs/docs/api-reference/mcp.md +++ b/hindsight-docs/docs/api-reference/mcp.md @@ -4,11 +4,11 @@ sidebar_position: 3 # MCP API -Model Context Protocol (MCP) tools exposed by the Memora MCP server. +Model Context Protocol (MCP) tools exposed by the Hindsight MCP server. ## Available Tools -### memora_search +### hindsight_search Search memories for an agent. @@ -24,7 +24,7 @@ Search memories for an agent. ```json { - "name": "memora_search", + "name": "hindsight_search", "arguments": { "query": "What does Alice do for work?", "top_k": 5 @@ -48,7 +48,7 @@ Search memories for an agent. --- -### memora_think +### hindsight_think Generate a personality-aware response using retrieved memories. @@ -64,7 +64,7 @@ Generate a personality-aware response using retrieved memories. ```json { - "name": "memora_think", + "name": "hindsight_think", "arguments": { "query": "What should I recommend to Alice?" } @@ -85,7 +85,7 @@ Generate a personality-aware response using retrieved memories. --- -### memora_store +### hindsight_store Store a new memory. @@ -101,7 +101,7 @@ Store a new memory. ```json { - "name": "memora_store", + "name": "hindsight_store", "arguments": { "content": "User prefers Python for data analysis", "context": "programming discussion" @@ -120,7 +120,7 @@ Store a new memory. --- -### memora_agents +### hindsight_agents List all available agents. @@ -130,7 +130,7 @@ List all available agents. ```json { - "name": "memora_agents", + "name": "hindsight_agents", "arguments": {} } ``` @@ -153,8 +153,8 @@ List all available agents. | Variable | Description | Default | |----------|-------------|---------| -| `MEMORA_API_URL` | Memora API URL | `http://localhost:8080` | -| `MEMORA_AGENT_ID` | Default agent ID | Required | +| `HINDSIGHT_API_URL` | Hindsight API URL | `http://localhost:8888` | +| `HINDSIGHT_AGENT_ID` | Default agent ID | Required | ## Error Responses diff --git a/memora-docs/docs/changelog/index.md b/hindsight-docs/docs/changelog/index.md similarity index 100% rename from memora-docs/docs/changelog/index.md rename to hindsight-docs/docs/changelog/index.md diff --git a/memora-docs/docs/cookbook/index.md b/hindsight-docs/docs/cookbook/index.md similarity index 100% rename from memora-docs/docs/cookbook/index.md rename to hindsight-docs/docs/cookbook/index.md diff --git a/memora-docs/docs/developer/api/agent-identity.md b/hindsight-docs/docs/developer/api/agent-identity.md similarity index 94% rename from memora-docs/docs/developer/api/agent-identity.md rename to hindsight-docs/docs/developer/api/agent-identity.md index 9397a4e62c..d7feb331c0 100644 --- a/memora-docs/docs/developer/api/agent-identity.md +++ b/hindsight-docs/docs/developer/api/agent-identity.md @@ -15,9 +15,9 @@ import TabItem from '@theme/TabItem'; ```python -from memora_client import Memora +from hindsight_client import Hindsight -client = Memora(base_url="http://localhost:8080") +client = Hindsight(base_url="http://localhost:8888") client.create_agent( agent_id="my-agent", @@ -38,9 +38,9 @@ client.create_agent( ```typescript -import { OpenAPI, ManagementService } from '@memora/client'; +import { OpenAPI, ManagementService } from '@hindsight/client'; -OpenAPI.BASE = 'http://localhost:8080'; +OpenAPI.BASE = 'http://localhost:8888'; await ManagementService.createAgentApiAgentsAgentIdPut('my-agent', { name: 'Research Assistant', @@ -61,10 +61,10 @@ await ManagementService.createAgentApiAgentsAgentIdPut('my-agent', { ```bash # Set background -memora agent background my-agent "I am a research assistant specializing in ML" +hindsight agent background my-agent "I am a research assistant specializing in ML" # Set personality -memora agent personality my-agent \ +hindsight agent personality my-agent \ --openness 0.8 \ --conscientiousness 0.7 \ --extraversion 0.5 \ @@ -211,7 +211,7 @@ print(f"Personality: {profile['personality']}") ```bash -memora agent profile my-agent +hindsight agent profile my-agent ``` @@ -248,7 +248,7 @@ for agent in agents: ```bash -memora agent list +hindsight agent list ``` diff --git a/memora-docs/docs/developer/api/ingest.md b/hindsight-docs/docs/developer/api/ingest.md similarity index 83% rename from memora-docs/docs/developer/api/ingest.md rename to hindsight-docs/docs/developer/api/ingest.md index ade3da30d4..b91ed3f18a 100644 --- a/memora-docs/docs/developer/api/ingest.md +++ b/hindsight-docs/docs/developer/api/ingest.md @@ -1,10 +1,10 @@ --- -sidebar_position: 1 +sidebar_position: 2 --- # Ingest Data -Store memories, conversations, and documents into Memora. +Store memories, conversations, and documents into Hindsight. import Tabs from '@theme/Tabs'; import TabItem from '@theme/TabItem'; @@ -15,21 +15,21 @@ import TabItem from '@theme/TabItem'; ```bash -pip install memora-client +pip install hindsight-client ``` ```bash -npm install @memora/client +npm install @hindsight/client ``` ```bash -cd memora-cli && cargo build --release +cd hindsight-cli && cargo build --release ``` @@ -41,9 +41,9 @@ cd memora-cli && cargo build --release ```python -from memora_client import Memora +from hindsight_client import Hindsight -client = Memora(base_url="http://localhost:8080") +client = Hindsight(base_url="http://localhost:8888") client.store( agent_id="my-agent", @@ -55,9 +55,9 @@ client.store( ```typescript -import { OpenAPI, MemoryStorageService } from '@memora/client'; +import { OpenAPI, MemoryStorageService } from '@hindsight/client'; -OpenAPI.BASE = 'http://localhost:8080'; +OpenAPI.BASE = 'http://localhost:8888'; await MemoryStorageService.putApiPutPost({ agent_id: 'my-agent', @@ -69,7 +69,7 @@ await MemoryStorageService.putApiPutPost({ ```bash -memora memory put my-agent "Alice works at Google as a software engineer" +hindsight memory put my-agent "Alice works at Google as a software engineer" ``` @@ -95,7 +95,7 @@ client.store( ```bash -memora memory put my-agent "Alice got promoted" \ +hindsight memory put my-agent "Alice got promoted" \ --context "career update" \ --event-date "2024-03-15" ``` @@ -150,13 +150,13 @@ The `document_id` groups related memories for later management. ```bash # Single file -memora memory put-files my-agent document.txt +hindsight memory put-files my-agent document.txt # Multiple files -memora memory put-files my-agent doc1.txt doc2.md notes.txt +hindsight memory put-files my-agent doc1.txt doc2.md notes.txt # With document ID -memora memory put-files my-agent report.pdf --document-id "q4-report" +hindsight memory put-files my-agent report.pdf --document-id "q4-report" ``` @@ -164,7 +164,7 @@ memora memory put-files my-agent report.pdf --document-id "q4-report" ## What Happens During Ingestion -When you store content, Memora: +When you store content, Hindsight: 1. **Extracts facts** using an LLM โ€” converts raw text into structured narrative facts 2. **Identifies entities** โ€” people, places, organizations, concepts diff --git a/memora-docs/docs/developer/api/opinions.md b/hindsight-docs/docs/developer/api/opinions.md similarity index 98% rename from memora-docs/docs/developer/api/opinions.md rename to hindsight-docs/docs/developer/api/opinions.md index f8a8afb91d..4068704c86 100644 --- a/memora-docs/docs/developer/api/opinions.md +++ b/hindsight-docs/docs/developer/api/opinions.md @@ -75,7 +75,7 @@ for op in opinions: ```bash -memora memory search my-agent "programming" --fact-type opinion +hindsight memory search my-agent "programming" --fact-type opinion ``` diff --git a/hindsight-docs/docs/developer/api/quickstart.md b/hindsight-docs/docs/developer/api/quickstart.md new file mode 100644 index 0000000000..94f2a9b7b4 --- /dev/null +++ b/hindsight-docs/docs/developer/api/quickstart.md @@ -0,0 +1,156 @@ +--- +sidebar_position: 0 +--- + +# Quick Start + +Get up and running with Hindsight in 60 seconds. + +import Tabs from '@theme/Tabs'; +import TabItem from '@theme/TabItem'; + +## Installation + + + + +The `hindsight-all` package includes everything you need: embedded PostgreSQL, HTTP API server, and Python client. + +```bash +pip install hindsight-all +``` + + + + +If you already have a Hindsight server running, install just the client: + +```bash +pip install hindsight-client +``` + + + + +## Basic Usage + + + + +```python +import os +from hindsight import HindsightServer, HindsightClient + +# Start embedded server (PostgreSQL + HTTP API) +with HindsightServer( + llm_provider="openai", + llm_model="gpt-4.1-mini", + llm_api_key=os.environ["OPENAI_API_KEY"] +) as server: + client = HindsightClient(base_url=server.url) + + # Store memories + client.put(agent_id="my-agent", content="Alice works at Google") + client.put(agent_id="my-agent", content="Bob prefers Python over JavaScript") + + # Search memories + results = client.search(agent_id="my-agent", query="What does Alice do?") + for r in results: + print(r["text"]) + + # Generate response with personality + response = client.think(agent_id="my-agent", query="Tell me about Alice") + print(response["text"]) +``` + + + + +```python +from hindsight_client import Hindsight + +client = Hindsight(base_url="http://localhost:8888") + +# Store memories +client.put(agent_id="my-agent", content="Alice works at Google") +client.put(agent_id="my-agent", content="Bob prefers Python over JavaScript") + +# Search memories +results = client.search(agent_id="my-agent", query="What does Alice do?") +for r in results: + print(r["text"]) + +# Generate response with personality +response = client.think(agent_id="my-agent", query="Tell me about Alice") +print(response["text"]) +``` + + + + +## What's Happening + +1. **Store** โ€” Content is processed, facts are extracted, and entities are linked in a knowledge graph +2. **Search** โ€” Four search strategies (semantic, keyword, graph, temporal) run in parallel and results are fused +3. **Think** โ€” Retrieved memories are used to generate a personality-aware response + +## Server Options + +When using `HindsightServer`, you can configure: + +```python +from hindsight import HindsightServer + +server = HindsightServer( + # Database + db_url="pg0", # "pg0" for embedded PostgreSQL, or a connection URL + + # LLM Configuration + llm_provider="openai", # "openai", "groq", or "ollama" + llm_api_key="your-api-key", + llm_model="gpt-4.1-mini", + llm_base_url=None, # Custom endpoint (for ollama or proxies) + + # Server + host="127.0.0.1", + port=None, # Auto-select free port if None + mcp_enabled=False, # Enable MCP API +) + +server.start() +print(f"Server running at {server.url}") + +# ... use server ... + +server.stop() +``` + +## Environment Variables + +For production, use environment variables: + +```bash +export OPENAI_API_KEY=sk-... +# or +export GROQ_API_KEY=gsk_... +``` + +```python +import os +from hindsight import HindsightServer, HindsightClient + +with HindsightServer( + llm_provider="openai", + llm_api_key=os.environ["OPENAI_API_KEY"], + llm_model="gpt-4.1-mini" +) as server: + client = HindsightClient(base_url=server.url) + # ... +``` + +## Next Steps + +- [Ingest Data](./ingest) โ€” Store memories, conversations, and documents +- [Search Facts](./search) โ€” Multi-strategy retrieval +- [Think](./think) โ€” Personality-aware response generation +- [Agent Identity](./agent-identity) โ€” Configure agent personality and background diff --git a/memora-docs/docs/developer/api/search.md b/hindsight-docs/docs/developer/api/search.md similarity index 89% rename from memora-docs/docs/developer/api/search.md rename to hindsight-docs/docs/developer/api/search.md index 1e906de12f..26f196fe45 100644 --- a/memora-docs/docs/developer/api/search.md +++ b/hindsight-docs/docs/developer/api/search.md @@ -15,9 +15,9 @@ import TabItem from '@theme/TabItem'; ```python -from memora_client import Memora +from hindsight_client import Hindsight -client = Memora(base_url="http://localhost:8080") +client = Hindsight(base_url="http://localhost:8888") results = client.search( agent_id="my-agent", @@ -32,9 +32,9 @@ for r in results: ```typescript -import { OpenAPI, SearchService } from '@memora/client'; +import { OpenAPI, SearchService } from '@hindsight/client'; -OpenAPI.BASE = 'http://localhost:8080'; +OpenAPI.BASE = 'http://localhost:8888'; const results = await SearchService.searchApiSearchPost({ agent_id: 'my-agent', @@ -50,7 +50,7 @@ for (const r of results.results) { ```bash -memora memory search my-agent "What does Alice do?" +hindsight memory search my-agent "What does Alice do?" ``` @@ -85,7 +85,7 @@ results = client.search_memories( ## Temporal Queries -Memora automatically detects time expressions and activates temporal search: +Hindsight automatically detects time expressions and activates temporal search: @@ -101,8 +101,8 @@ results = client.search(agent_id="my-agent", query="Events from last year") ```bash -memora memory search my-agent "What did Alice do last spring?" -memora memory search my-agent "What happened between March and May?" +hindsight memory search my-agent "What did Alice do last spring?" +hindsight memory search my-agent "What happened between March and May?" ``` @@ -159,8 +159,8 @@ facts = client.search_memories( ```bash -memora memory search my-agent "Python" --fact-type opinion -memora memory search my-agent "Alice" --fact-type world,agent +hindsight memory search my-agent "Python" --fact-type opinion +hindsight memory search my-agent "Alice" --fact-type world,agent ``` diff --git a/memora-docs/docs/developer/api/think-vs-search.md b/hindsight-docs/docs/developer/api/think-vs-search.md similarity index 100% rename from memora-docs/docs/developer/api/think-vs-search.md rename to hindsight-docs/docs/developer/api/think-vs-search.md diff --git a/memora-docs/docs/developer/api/think.md b/hindsight-docs/docs/developer/api/think.md similarity index 92% rename from memora-docs/docs/developer/api/think.md rename to hindsight-docs/docs/developer/api/think.md index 53e97a1388..72f0e57303 100644 --- a/memora-docs/docs/developer/api/think.md +++ b/hindsight-docs/docs/developer/api/think.md @@ -15,9 +15,9 @@ import TabItem from '@theme/TabItem'; ```python -from memora_client import Memora +from hindsight_client import Hindsight -client = Memora(base_url="http://localhost:8080") +client = Hindsight(base_url="http://localhost:8888") answer = client.think( agent_id="my-agent", @@ -31,9 +31,9 @@ print(answer["text"]) ```typescript -import { OpenAPI, ReasoningService } from '@memora/client'; +import { OpenAPI, ReasoningService } from '@hindsight/client'; -OpenAPI.BASE = 'http://localhost:8080'; +OpenAPI.BASE = 'http://localhost:8888'; const response = await ReasoningService.thinkApiThinkPost({ agent_id: 'my-agent', @@ -47,10 +47,10 @@ console.log(response.text); ```bash -memora memory think my-agent "What should I know about Alice?" +hindsight memory think my-agent "What should I know about Alice?" # Verbose output shows reasoning and sources -memora memory think my-agent "What should I know about Alice?" -v +hindsight memory think my-agent "What should I know about Alice?" -v ``` @@ -110,7 +110,7 @@ answer = client.think( ```mermaid sequenceDiagram participant C as Client - participant A as Memora API + participant A as Hindsight API participant M as Memory Store participant L as LLM diff --git a/memora-docs/docs/developer/architecture.md b/hindsight-docs/docs/developer/architecture.md similarity index 87% rename from memora-docs/docs/developer/architecture.md rename to hindsight-docs/docs/developer/architecture.md index fa762e3dff..891e9e89d4 100644 --- a/memora-docs/docs/developer/architecture.md +++ b/hindsight-docs/docs/developer/architecture.md @@ -4,22 +4,22 @@ sidebar_position: 2 # Architecture -Memora's architecture consists of three main pipelines: ingestion, retrieval, and reasoning. +Hindsight's architecture consists of three main pipelines: ingestion, retrieval, and reasoning. ## Memory Ingestion -When content is stored, Memora processes it through an LLM-powered extraction pipeline. +When content is stored, Hindsight processes it through an LLM-powered extraction pipeline. ### Narrative Fact Extraction -Unlike traditional systems that create atomic fragments, Memora extracts **comprehensive narrative facts** that preserve context: +Unlike traditional systems that create atomic fragments, Hindsight extracts **comprehensive narrative facts** that preserve context: **Fragmented (traditional)**: - "Bob suggested Summer Vibes" - "Alice wanted something unique" - "They chose Beach Beats" -**Narrative (Memora)**: +**Narrative (Hindsight)**: - "Alice and Bob discussed naming their summer party playlist. Bob suggested 'Summer Vibes' because it's catchy, but Alice wanted something unique. They ultimately decided on 'Beach Beats' for its playful tone." This approach: @@ -92,7 +92,7 @@ Each stored memory contains: ## Temporal Model -Memora distinguishes **when facts occurred** from **when they were mentioned**: +Hindsight distinguishes **when facts occurred** from **when they were mentioned**: - `occurred_start/end`: When the fact/event actually happened - `mentioned_at`: When the agent learned about it diff --git a/hindsight-docs/docs/developer/development.md b/hindsight-docs/docs/developer/development.md new file mode 100644 index 0000000000..168b033bfb --- /dev/null +++ b/hindsight-docs/docs/developer/development.md @@ -0,0 +1,149 @@ +--- +sidebar_position: 7 +--- + +# Development Guide + +Guide to setting up a local development environment for contributing to Hindsight. + +## Prerequisites + +- Python 3.11+ +- [uv](https://docs.astral.sh/uv/) - Fast Python package manager +- Docker and Docker Compose +- An LLM API key (OpenAI, Groq, or Ollama) + +## Local Development Setup + +### 1. Clone the Repository + +```bash +git clone https://github.com/vectorize-io/hindsight.git +cd hindsight +``` + +### 2. Install Dependencies + +```bash +uv sync +``` + +### 3. Start PostgreSQL + +Start only the database via Docker: + +```bash +cd docker && docker-compose up -d postgres +``` + +### 4. Configure Environment + +```bash +cp .env.example .env +``` + +Edit `.env` with your LLM API key: + +```bash +# Database (connects to Docker postgres) +HINDSIGHT_API_DATABASE_URL=postgresql://hindsight:hindsight_dev@localhost:5432/hindsight + +# LLM Provider (choose one) +HINDSIGHT_API_LLM_PROVIDER=groq +HINDSIGHT_API_LLM_API_KEY=gsk_xxxxxxxxxxxx +HINDSIGHT_API_LLM_MODEL=llama-3.1-70b-versatile +``` + +### 5. Start the API Server + +```bash +./scripts/start-server.sh --env local +``` + +The server will be available at http://localhost:8888. + +## Running Tests + +```bash +# Run all tests +uv run pytest + +# Run specific test file +uv run pytest tests/test_retrieval.py + +# Run with verbose output +uv run pytest -v +``` + +## Code Generation + +### Regenerate API Clients + +When you modify the OpenAPI spec, regenerate the clients: + +```bash +./scripts/generate-clients.sh +``` + +This generates: +- Python client in `hindsight-clients/python/` +- TypeScript client in `hindsight-clients/typescript/` + +### Export OpenAPI Schema + +```bash +./scripts/export-openapi.sh +``` + +## Project Structure + +``` +hindsight/ +โ”œโ”€โ”€ hindsight-api/ # Main API server +โ”‚ โ”œโ”€โ”€ hindsight_api/ +โ”‚ โ”‚ โ”œโ”€โ”€ api/ # HTTP endpoints +โ”‚ โ”‚ โ”œโ”€โ”€ engine/ # Memory engine, retrieval, reasoning +โ”‚ โ”‚ โ””โ”€โ”€ web/ # Server entry point +โ”‚ โ””โ”€โ”€ tests/ +โ”œโ”€โ”€ hindsight-clients/ # Generated SDK clients +โ”‚ โ”œโ”€โ”€ python/ +โ”‚ โ””โ”€โ”€ typescript/ +โ”œโ”€โ”€ hindsight-control-plane/ # Admin UI (Next.js) +โ”œโ”€โ”€ docker/ # Docker Compose setup +โ””โ”€โ”€ scripts/ # Development scripts +``` + +## Contributing + +1. Create a feature branch from `main` +2. Make your changes +3. Run tests: `uv run pytest` +4. Submit a pull request + +## Troubleshooting + +### Database Connection Issues + +Ensure PostgreSQL is running: + +```bash +docker-compose ps +``` + +Check database connectivity: + +```bash +psql postgresql://hindsight:hindsight_dev@localhost:5432/hindsight +``` + +### ML Model Download + +On first run, Hindsight downloads embedding and reranking models. This may take a few minutes. Models are cached in `~/.cache/huggingface/`. + +### Port Conflicts + +If port 8888 is in use: + +```bash +HINDSIGHT_API_PORT=8889 ./scripts/start-server.sh --env local +``` diff --git a/memora-docs/docs/developer/index.md b/hindsight-docs/docs/developer/index.md similarity index 86% rename from memora-docs/docs/developer/index.md rename to hindsight-docs/docs/developer/index.md index 2d2a899bf0..3b5e1fd52a 100644 --- a/memora-docs/docs/developer/index.md +++ b/hindsight-docs/docs/developer/index.md @@ -5,7 +5,7 @@ slug: / # Overview -## Why Memora? +## Why Hindsight? AI assistants forget everything between sessions. Every conversation starts from zeroโ€”no context about who you are, what you've discussed, or what the agent has learned. This isn't just inconvenient; it fundamentally limits what AI agents can do. @@ -16,9 +16,9 @@ AI assistants forget everything between sessions. Every conversation starts from - **Agents need opinions** โ€” A coding assistant that remembers "the user prefers functional programming" should weigh that when making recommendations - **Context matters** โ€” The same information means different things to different agents with different personalities -Memora solves these problems with a memory system designed specifically for AI agents. +Hindsight solves these problems with a memory system designed specifically for AI agents. -## What Memora Does +## What Hindsight Does ```mermaid graph LR @@ -29,7 +29,7 @@ graph LR D[AI Assistants] end - subgraph Memora Server + subgraph Hindsight Server E[HTTP API] F[MCP API] end @@ -112,7 +112,7 @@ graph TB ### Three Memory Networks -Memora separates memories by type for epistemic clarity: +Hindsight separates memories by type for epistemic clarity: | Network | What it stores | Example | |---------|----------------|---------| @@ -166,7 +166,7 @@ The `bias_strength` parameter (0-1) controls how much personality influences opi ```mermaid sequenceDiagram participant C as Client - participant A as Memora API + participant A as Hindsight API participant DB as PostgreSQL C->>A: store("Alice works at Google") @@ -186,34 +186,15 @@ sequenceDiagram A-->>C: Response + sources ``` -## Quick Start - -```bash -pip install memora-client -``` - -```python -from memora_client import Memora - -client = Memora(base_url="http://localhost:8080") - -# Store -client.store(agent_id="my-agent", content="Alice works at Google") - -# Search -results = client.search(agent_id="my-agent", query="What does Alice do?") - -# Think (personality-aware response) -answer = client.think(agent_id="my-agent", query="Tell me about Alice") -print(answer["text"]) -``` - ## Next Steps +- [Quick Start](/developer/api/quickstart) โ€” Get up and running in 60 seconds + - [Architecture](./developer/architecture) โ€” Deep dive into ingestion, storage, and graph construction - [Retrieval](./developer/retrieval) โ€” How TEMPR's 4-way search works - [Personality](./developer/personality) โ€” CARA framework and opinion formation - [Ingest Data](./developer/api/ingest) โ€” Store memories, conversations, and documents - [Search Facts](./developer/api/search) โ€” Multi-strategy retrieval - [Think](./developer/api/think) โ€” Personality-aware response generation -- [Server Administration](./developer/server) โ€” Deployment and configuration +- [Server Deployment](./developer/server) โ€” Deploy with Docker Compose, Helm, or pip +- [Development Guide](./developer/development) โ€” Set up a local development environment diff --git a/memora-docs/docs/developer/personality.md b/hindsight-docs/docs/developer/personality.md similarity index 90% rename from memora-docs/docs/developer/personality.md rename to hindsight-docs/docs/developer/personality.md index 421b5f9e50..e89e7bec8e 100644 --- a/memora-docs/docs/developer/personality.md +++ b/hindsight-docs/docs/developer/personality.md @@ -4,7 +4,7 @@ sidebar_position: 4 # Personality -Memora's personality framework (CARA) uses the Big Five model to influence how agents form and express opinions. +Hindsight's personality framework (CARA) uses the Big Five model to influence how agents form and express opinions. ## Big Five Traits @@ -74,9 +74,9 @@ import TabItem from '@theme/TabItem'; ```python -from memora_client import Memora +from hindsight_client import Hindsight -client = Memora(base_url="http://localhost:8080") +client = Hindsight(base_url="http://localhost:8888") client.create_agent( agent_id="my-agent", @@ -97,9 +97,9 @@ client.create_agent( ```typescript -import { OpenAPI, ManagementService } from '@memora/client'; +import { OpenAPI, ManagementService } from '@hindsight/client'; -OpenAPI.BASE = 'http://localhost:8080'; +OpenAPI.BASE = 'http://localhost:8888'; await ManagementService.createAgentApiAgentsAgentIdPut('my-agent', { name: 'Creative Assistant', @@ -119,8 +119,8 @@ await ManagementService.createAgentApiAgentsAgentIdPut('my-agent', { ```bash -memora agent background my-agent "I am a creative AI interested in new ideas" -memora agent personality my-agent \ +hindsight agent background my-agent "I am a creative AI interested in new ideas" +hindsight agent personality my-agent \ --openness 0.8 \ --conscientiousness 0.6 \ --extraversion 0.5 \ diff --git a/memora-docs/docs/developer/retrieval.md b/hindsight-docs/docs/developer/retrieval.md similarity index 85% rename from memora-docs/docs/developer/retrieval.md rename to hindsight-docs/docs/developer/retrieval.md index a005d74304..65a8ca1e9d 100644 --- a/memora-docs/docs/developer/retrieval.md +++ b/hindsight-docs/docs/developer/retrieval.md @@ -4,7 +4,11 @@ sidebar_position: 3 # Retrieval -Memora's retrieval architecture (TEMPR) runs four search strategies in parallel and fuses results for optimal recall and precision. +Hindsight's retrieval architecture (TEMPR) runs four search strategies in parallel and fuses results for optimal recall and precision. + +:::tip Deep Dive on Temporal Reasoning +For a comprehensive guide on how Hindsight handles temporal facts and time-aware retrieval, see [Temporal Reasoning](./temporal-reasoning.md). +::: ## Pipeline Overview @@ -90,6 +94,8 @@ Activated when temporal expressions are detected. Uses T5-small for parsing. **Example**: "What did Alice do last spring?" โ†’ Events in March-May range +**How it works**: Combines semantic entry points with time filtering, then traverses the entity graph while only following links to facts within the temporal range. See [Temporal Reasoning](./temporal-reasoning.md) for detailed explanation. + ## Result Fusion (RRF) Reciprocal Rank Fusion combines ranked lists without score normalization: diff --git a/memora-docs/docs/developer/server.md b/hindsight-docs/docs/developer/server.md similarity index 73% rename from memora-docs/docs/developer/server.md rename to hindsight-docs/docs/developer/server.md index e804d1bdbf..eb1f6fa761 100644 --- a/memora-docs/docs/developer/server.md +++ b/hindsight-docs/docs/developer/server.md @@ -2,9 +2,108 @@ sidebar_position: 6 --- -# Server Administration +# Server Deployment -Guide to deploying and configuring the Memora server. +Guide to deploying the Hindsight server in production. + +## Deployment Options + +### Docker Compose (Recommended) + +The simplest way to deploy Hindsight with all dependencies: + +```bash +# Clone the repository +git clone https://github.com/vectorize-io/hindsight.git +cd hindsight + +# Create environment file +cp .env.example .env +# Edit .env with your LLM API key + +# Start all services +cd docker +./start.sh +``` + +Services will be available at: +- **API Server**: http://localhost:8888 +- **Control Plane**: http://localhost:3000 +- **Swagger UI**: http://localhost:8888/docs + +#### Docker Compose Commands + +```bash +# Start all services +cd docker && ./start.sh + +# Stop services +cd docker && ./stop.sh + +# Clean all data +cd docker && ./clean.sh + +# View logs +docker-compose logs -f api +docker-compose logs -f control-plane +``` + +### Helm Chart (Kubernetes) + +For Kubernetes deployments, use the Hindsight Helm chart: + +```bash +helm repo add hindsight https://vectorize-io.github.io/hindsight +helm install hindsight hindsight/hindsight \ + --set api.llm.provider=groq \ + --set api.llm.apiKey=gsk_xxxxxxxxxxxx +``` + +See the [Helm chart documentation](https://github.com/vectorize-io/hindsight/tree/main/deploy/helm) for configuration options. + +### pip install + +For custom deployments, install the all-in-one package: + +```bash +pip install hindsight-all +``` + +Run the server: + +```bash +# Configure via environment variables +export HINDSIGHT_API_LLM_PROVIDER=groq +export HINDSIGHT_API_LLM_API_KEY=gsk_xxxxxxxxxxxx + +# Start the server (Ctrl+C to stop) +hindsight-api +``` + +By default, it uses `pg0` (embedded PostgreSQL) so you can run it without any external dependencies. + +#### CLI Options + +```bash +hindsight-api --help + +# Common options +hindsight-api --port 9000 # Custom port (default: 8888) +hindsight-api --host 127.0.0.1 # Bind to localhost only +hindsight-api --mcp # Enable MCP server at /mcp +hindsight-api --log-level debug # Verbose logging +``` + +#### Using External PostgreSQL + +To use an external PostgreSQL database instead of embedded pg0: + +```bash +export HINDSIGHT_API_DATABASE_URL=postgresql://user:pass@localhost:5432/hindsight +hindsight-api +``` + +You'll need PostgreSQL with the pgvector extension enabled. ## Architecture Overview @@ -13,27 +112,24 @@ Guide to deploying and configuring the Memora server. โ”‚ CLIENTS โ”‚ โ”œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ค โ”‚ Python Client โ”‚ Node.js Client โ”‚ CLI โ”‚ AI Assistants โ”‚ -โ”‚ memora-client โ”‚ @memora/client โ”‚ memora-cli โ”‚ (Claude, etc.) โ”‚ +โ”‚ hindsight-client โ”‚ @hindsight/client โ”‚ hindsight-cli โ”‚ (Claude, etc.) โ”‚ โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ดโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ดโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ดโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ - โ”‚ โ”‚ โ”‚ โ”‚ โ”‚ โ”‚ โ”‚ โ”‚ โ–ผ โ–ผ โ–ผ โ–ผ โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” -โ”‚ MEMORA API SERVER โ”‚ -โ”‚ (localhost:8080) โ”‚ +โ”‚ HINDSIGHT API SERVER โ”‚ +โ”‚ (localhost:8888) โ”‚ โ”œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ค โ”‚ HTTP API โ”‚ MCP API โ”‚ โ”‚ /api/memories/* โ”‚ MCP Server (stdio) โ”‚ -โ”‚ /api/agents/* โ”‚ memora_search, memora_think, โ”‚ -โ”‚ /api/search, /api/think โ”‚ memora_store, memora_agents โ”‚ +โ”‚ /api/agents/* โ”‚ hindsight_search, hindsight_think, โ”‚ +โ”‚ /api/search, /api/think โ”‚ hindsight_store, hindsight_agents โ”‚ โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ดโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ - โ”‚ โ”‚ โ”‚ โ”‚ โ–ผ โ–ผ โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” โ”‚ PROCESSING PIPELINE โ”‚ โ”œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ค -โ”‚ โ”‚ โ”‚ โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” โ”‚ โ”‚ โ”‚ INGESTION โ”‚ โ”‚ RETRIEVAL โ”‚ โ”‚ REASONING โ”‚ โ”‚ โ”‚ โ”‚ โ”‚ โ”‚ (TEMPR) โ”‚ โ”‚ (CARA) โ”‚ โ”‚ @@ -41,7 +137,6 @@ Guide to deploying and configuring the Memora server. โ”‚ โ”‚ Entity Res. โ”‚ โ”‚ 4-way Searchโ”‚ โ”‚ Personality โ”‚ โ”‚ โ”‚ โ”‚ Graph Build โ”‚ โ”‚ RRF Fusion โ”‚ โ”‚ Opinion Gen โ”‚ โ”‚ โ”‚ โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ โ”‚ -โ”‚ โ”‚ โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ โ”‚ โ”‚ โ”‚ โ–ผ โ–ผ โ–ผ @@ -73,64 +168,28 @@ Guide to deploying and configuring the Memora server. โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ ``` -## Quick Start - -### Docker (Recommended) - -```bash -# Clone the repository -git clone https://github.com/memora/memora.git -cd memora - -# Create environment file -cp .env.example .env -# Edit .env with your LLM API key - -# Start all services -cd docker -./start.sh -``` - -Services will be available at: -- **API Server**: http://localhost:8080 -- **Control Plane**: http://localhost:3000 -- **Swagger UI**: http://localhost:8080/docs - -### Local Development - -```bash -# Install dependencies -uv sync - -# Start PostgreSQL only (via Docker) -cd docker && docker-compose up -d postgres - -# Start the API server -./scripts/start-server.sh --env local -``` - ## Environment Variables -### API Server (`MEMORA_API_*`) +### API Server (`HINDSIGHT_API_*`) | Variable | Description | Default | |----------|-------------|---------| -| `MEMORA_API_DATABASE_URL` | PostgreSQL connection string | Required | -| `MEMORA_API_LLM_PROVIDER` | LLM provider: `openai`, `groq`, `ollama` | `groq` | -| `MEMORA_API_LLM_API_KEY` | API key for LLM provider | Required (except ollama) | -| `MEMORA_API_LLM_MODEL` | Model name | `openai/gpt-oss-20b` | -| `MEMORA_API_LLM_BASE_URL` | Custom LLM endpoint | Provider default | -| `MEMORA_API_HOST` | Server bind address | `0.0.0.0` | -| `MEMORA_API_PORT` | Server port | `8080` | -| `MEMORA_API_MCP_ENABLED` | Enable MCP server | `true` | +| `HINDSIGHT_API_DATABASE_URL` | PostgreSQL connection string | Required | +| `HINDSIGHT_API_LLM_PROVIDER` | LLM provider: `openai`, `groq`, `ollama` | `groq` | +| `HINDSIGHT_API_LLM_API_KEY` | API key for LLM provider | Required (except ollama) | +| `HINDSIGHT_API_LLM_MODEL` | Model name | `llama-3.1-70b-versatile` | +| `HINDSIGHT_API_LLM_BASE_URL` | Custom LLM endpoint | Provider default | +| `HINDSIGHT_API_HOST` | Server bind address | `0.0.0.0` | +| `HINDSIGHT_API_PORT` | Server port | `8888` | +| `HINDSIGHT_API_MCP_ENABLED` | Enable MCP server | `true` | -### Control Plane (`MEMORA_CP_*`) +### Control Plane (`HINDSIGHT_CP_*`) | Variable | Description | Default | |----------|-------------|---------| -| `MEMORA_CP_DATAPLANE_API_URL` | API server URL | `http://localhost:8080` | -| `MEMORA_CP_HOSTNAME` | Server bind address | `0.0.0.0` | -| `MEMORA_CP_PORT` | Server port | `3000` | +| `HINDSIGHT_CP_DATAPLANE_API_URL` | API server URL | `http://localhost:8888` | +| `HINDSIGHT_CP_HOSTNAME` | Server bind address | `0.0.0.0` | +| `HINDSIGHT_CP_PORT` | Server port | `3000` | ### Example Configuration @@ -138,30 +197,30 @@ cd docker && docker-compose up -d postgres # .env file # Database -MEMORA_API_DATABASE_URL=postgresql://memora:memora_dev@localhost:5432/memora +HINDSIGHT_API_DATABASE_URL=postgresql://hindsight:hindsight_dev@localhost:5432/hindsight # LLM - Using Groq (fast inference) -MEMORA_API_LLM_PROVIDER=groq -MEMORA_API_LLM_API_KEY=gsk_xxxxxxxxxxxx -MEMORA_API_LLM_MODEL=llama-3.1-70b-versatile +HINDSIGHT_API_LLM_PROVIDER=groq +HINDSIGHT_API_LLM_API_KEY=gsk_xxxxxxxxxxxx +HINDSIGHT_API_LLM_MODEL=llama-3.1-70b-versatile # LLM - Using OpenAI -# MEMORA_API_LLM_PROVIDER=openai -# MEMORA_API_LLM_API_KEY=sk-xxxxxxxxxxxx -# MEMORA_API_LLM_MODEL=gpt-4o +# HINDSIGHT_API_LLM_PROVIDER=openai +# HINDSIGHT_API_LLM_API_KEY=sk-xxxxxxxxxxxx +# HINDSIGHT_API_LLM_MODEL=gpt-4o # LLM - Using Ollama (local, no API key) -# MEMORA_API_LLM_PROVIDER=ollama -# MEMORA_API_LLM_BASE_URL=http://localhost:11434/v1 -# MEMORA_API_LLM_MODEL=llama3.1 +# HINDSIGHT_API_LLM_PROVIDER=ollama +# HINDSIGHT_API_LLM_BASE_URL=http://localhost:11434/v1 +# HINDSIGHT_API_LLM_MODEL=llama3.1 # Control Plane -MEMORA_CP_DATAPLANE_API_URL=http://localhost:8080 +HINDSIGHT_CP_DATAPLANE_API_URL=http://localhost:8888 ``` ## ML Models -Memora uses several ML models for different stages of the pipeline: +Hindsight uses several ML models that are downloaded automatically on first run: ### Embedding Model @@ -169,10 +228,7 @@ Memora uses several ML models for different stages of the pipeline: |-------|------------|---------| | `all-MiniLM-L6-v2` | 384 | Semantic vector embeddings | -Downloaded automatically on first run. Used for: -- Memory vectorization -- Query embedding -- Semantic similarity search +Used for memory vectorization, query embedding, and semantic similarity search. ### Cross-Encoder (Reranking) @@ -180,7 +236,7 @@ Downloaded automatically on first run. Used for: |-------|---------| | `cross-encoder/ms-marco-MiniLM-L-6-v2` | Neural reranking | -Reranks search results for precision after initial retrieval. Includes temporal context in input. +Reranks search results for precision after initial retrieval. ### Temporal Parser @@ -192,11 +248,7 @@ Parses natural language time expressions like "last spring" or "in June 2024". ### LLM (Configurable) -Used for: -- Fact extraction from raw content -- Entity extraction and resolution -- Opinion generation with personality -- Think/reasoning responses +Used for fact extraction, entity resolution, opinion generation, and think responses. Supported providers: - **OpenAI**: GPT-4, GPT-4o, GPT-3.5-turbo @@ -257,38 +309,12 @@ CREATE TABLE agent_profiles ( - **GIN Index**: Full-text search with BM25 ranking - **B-tree Indexes**: Agent ID, timestamps, entity lookups -## Docker Services - -```yaml -services: - postgres: # pgvector/pgvector:pg16 - api: # Memora API server - control-plane: # Admin UI (optional) -``` - -### Commands - -```bash -# Start all services -cd docker && ./start.sh - -# Stop services -cd docker && ./stop.sh - -# Clean all data -cd docker && ./clean.sh - -# View logs -docker-compose logs -f api -docker-compose logs -f control-plane -``` - ## Health Checks ### API Server ```bash -curl http://localhost:8080/api/v1/agents +curl http://localhost:8888/api/v1/agents ``` ### Control Plane @@ -297,11 +323,11 @@ curl http://localhost:8080/api/v1/agents curl http://localhost:3000/ ``` -## Production Deployment +## Production Considerations For production deployments: -1. **Use managed PostgreSQL** with pgvector extension +1. **Use managed PostgreSQL** with pgvector extension (AWS RDS, Google Cloud SQL, Supabase) 2. **Set proper secrets** via environment variables or secrets manager 3. **Configure resource limits** for ML model inference 4. **Set up monitoring** for API latency and error rates diff --git a/hindsight-docs/docs/developer/temporal-reasoning.md b/hindsight-docs/docs/developer/temporal-reasoning.md new file mode 100644 index 0000000000..e46c271443 --- /dev/null +++ b/hindsight-docs/docs/developer/temporal-reasoning.md @@ -0,0 +1,446 @@ +--- +sidebar_position: 4 +--- + +# Temporal Reasoning + +Hindsight provides sophisticated temporal reasoning capabilities, allowing agents to understand and query memories based on when events occurred. This enables natural queries like "What did Alice do last spring?" or "What happened between March and May?" + +## Overview + +Temporal reasoning in Hindsight operates at two levels: + +1. **Fact Storage**: Every memory can have an `event_date` timestamp indicating when the event occurred +2. **Query Analysis**: Natural language temporal expressions are automatically detected and parsed +3. **Temporal-Graph Retrieval**: A specialized retrieval strategy that filters memories by time range while maintaining entity relationships + +## Storing Facts with Temporal Information + +### Event Date Assignment + +When ingesting facts, Hindsight extracts temporal information in the following order: + +1. **Explicit `event_date` parameter**: If provided, this is used directly +2. **LLM-extracted date**: The fact extraction LLM identifies temporal markers in the content +3. **Default to storage time**: If no date is found, uses the current timestamp + +```python +from hindsight_client import Hindsight +from datetime import datetime + +client = Hindsight(base_url="http://localhost:8888") + +# Explicit event date +client.put( + agent_id="my-agent", + content="Alice started working at Google", + event_date=datetime(2023, 3, 15) +) + +# LLM will extract the date from content +client.put( + agent_id="my-agent", + content="In June 2023, Alice moved to San Francisco" +) + +# Falls back to current time +client.put( + agent_id="my-agent", + content="Alice likes Python" +) +``` + +### LLM Temporal Extraction + +During fact extraction, the LLM identifies temporal markers in natural language: + +| Input Content | Extracted Event Date | +|--------------|---------------------| +| "In March 2024, Alice started a new job" | March 1, 2024 00:00:00 | +| "Last spring, Bob learned Python" | March 1 (previous year) | +| "Yesterday I met with the team" | Yesterday's date | +| "Alice works at Google" | Current timestamp (no temporal marker) | + +The extracted `event_date` is stored as a timestamp with the fact: + +```sql +CREATE TABLE memory_units ( + id UUID PRIMARY KEY, + text TEXT NOT NULL, + event_date TIMESTAMP DEFAULT NOW(), + -- other fields... +); +``` + +## Query-Time Temporal Analysis + +### Automatic Detection + +When a search query is issued, Hindsight automatically analyzes it for temporal expressions: + +```python +# These queries activate temporal-graph retrieval +results = client.search(agent_id="my-agent", query="What did Alice do last spring?") +results = client.search(agent_id="my-agent", query="What happened in June?") +results = client.search(agent_id="my-agent", query="Events from last year") + +# These do NOT activate temporal retrieval +results = client.search(agent_id="my-agent", query="What does Alice do?") +results = client.search(agent_id="my-agent", query="Tell me about Python") +``` + +### T5-Based Parsing + +Hindsight uses a T5 transformer model (`google/flan-t5-small`) to convert natural language temporal expressions into structured date ranges: + +```python +# Query: "What did Alice do last spring?" +# +# T5 Input Prompt: +# "Today is 2024-11-25. Convert temporal expressions to date ranges. +# June 2024 = 2024-06-01 to 2024-06-30 +# last year = 2023-01-01 to 2023-12-31 +# What did Alice do last spring? =" +# +# T5 Generated Output: +# "2024-03-01 to 2024-05-31" +# +# Parsed Constraint: +# TemporalConstraint( +# start_date=datetime(2024, 3, 1, 0, 0, 0), +# end_date=datetime(2024, 5, 31, 23, 59, 59, 999999) +# ) +``` + +### Supported Temporal Expressions + +| Expression | Parsed Date Range | Notes | +|------------|------------------|-------| +| "last spring" | March 1 - May 31 (previous year) | Seasonal ranges | +| "in June" | June 1-30 (current/nearest year) | Specific month | +| "in June 2023" | June 1-30, 2023 | Month with year | +| "last year" | Jan 1 - Dec 31 (previous year) | Relative year | +| "last week" | 7 days ago - today | Relative week | +| "yesterday" | Yesterday's date (00:00 - 23:59) | Specific day | +| "between March and May" | March 1 - May 31 (current year) | Date range | +| "March 2023" | March 1-31, 2023 | Month and year | +| "2023" | Jan 1 - Dec 31, 2023 | Year only | + +### No Temporal Expression + +If no temporal expression is detected, the query analysis returns `None` and standard retrieval (without temporal filtering) is used: + +```python +# No temporal expression detected +query = "What does Alice do?" +temporal_constraint = extract_temporal_constraint(query) +# Returns: None +``` + +## Temporal-Graph Retrieval Strategy + +When a temporal constraint is detected, Hindsight activates the **Temporal-Graph** retrieval strategy as a 4th parallel search path. + +### How It Works + +```mermaid +graph TD + Q[Query: What did Alice do last spring?] + Q --> T5[T5 Temporal Parser] + T5 --> TC[TemporalConstraint
2024-03-01 to 2024-05-31] + TC --> VS[Vector Similarity
Find semantic entry points] + VS --> F[Filter by event_date] + F --> GT[Graph Traversal
Through time-filtered entities] + GT --> R[Ranked Results] +``` + +### Algorithm Steps + +```python +def retrieve_temporal( + query_embedding, + agent_id, + start_date, + end_date, + budget, + semantic_threshold=0.4 +): + """ + Temporal-Graph retrieval combines time filtering with entity relationships. + + Steps: + 1. Find semantic entry points (similarity >= threshold) + WHERE event_date BETWEEN start_date AND end_date + + 2. Initialize activation scores from similarity scores + + 3. Graph traversal (spreading activation): + - Follow entity links to related facts + - ONLY traverse to facts within the time range + - Propagate activation with decay (0.8x per hop) + - Boost causal links (2x activation) + + 4. Return facts sorted by activation score + """ +``` + +### SQL Query Example + +```sql +-- Step 1: Find temporal entry points +WITH temporal_candidates AS ( + SELECT + mu.id, + mu.text, + mu.event_date, + 1 - (mu.embedding <=> $query_embedding) AS similarity + FROM memory_units mu + WHERE mu.agent_id = $agent_id + AND mu.fact_type = ANY($fact_types) + AND mu.event_date >= $start_date + AND mu.event_date <= $end_date + AND (1 - (mu.embedding <=> $query_embedding)) >= $semantic_threshold + ORDER BY similarity DESC + LIMIT 10 +) +-- Step 2 & 3: Graph traversal happens in Python code +-- walking through memory_links while enforcing temporal bounds +SELECT * FROM temporal_candidates; +``` + +### Key Differences from Standard Graph Traversal + +| Aspect | Standard Graph | Temporal-Graph | +|--------|---------------|----------------| +| **Entry Points** | Top-K by similarity (any time) | Top-K by similarity **within time range** | +| **Traversal** | Follow all entity links | Only follow links to **facts within time range** | +| **Use Case** | "What does Alice do?" | "What did Alice do last spring?" | +| **Activation Source** | Pure semantic similarity | Time-filtered semantic similarity | + +### Example Walkthrough + +**Query**: "What did Alice do last spring?" + +**Step 1 - Temporal Parsing:** +```python +temporal_constraint = extract_temporal_constraint(query) +# Result: (2024-03-01 00:00:00, 2024-05-31 23:59:59) +``` + +**Step 2 - Find Entry Points:** +``` +Semantic search for "What did Alice do" +WHERE event_date BETWEEN '2024-03-01' AND '2024-05-31' + +Found: +- "Alice started learning Rust" (April 15, 2024, similarity: 0.78) +- "Alice attended ML conference" (May 3, 2024, similarity: 0.72) +``` + +**Step 3 - Graph Traversal (time-filtered):** +``` +From "Alice started learning Rust": + โ†’ Alice (entity) + โ†’ "Alice joined Rust meetup" (April 20, 2024) โœ“ within range + โ†’ "Alice published Rust blog post" (April 28, 2024) โœ“ within range + โ†’ "Alice works at Google" (Jan 2023) โœ— outside range, skip + +From "Alice attended ML conference": + โ†’ ML Conference (entity) + โ†’ "Conference keynote on LLMs" (May 3, 2024) โœ“ within range + โ†’ Alice (entity) + โ†’ Same as above +``` + +**Step 4 - Activation Scores:** +``` +1. "Alice started learning Rust" (0.78) - direct match +2. "Alice attended ML conference" (0.72) - direct match +3. "Alice published Rust blog post" (0.78 ร— 0.8 = 0.62) - 1 hop +4. "Alice joined Rust meetup" (0.78 ร— 0.8 = 0.62) - 1 hop +5. "Conference keynote on LLMs" (0.72 ร— 0.8 = 0.58) - 1 hop +``` + +## Integration with Multi-Strategy Retrieval + +Temporal-Graph runs **in parallel** with the other three strategies: + +```python +# When temporal constraint detected: +results = await asyncio.gather( + retrieve_semantic(query_embedding, agent_id, fact_types), + retrieve_bm25(query, agent_id, fact_types), + retrieve_graph(query_embedding, agent_id, fact_types, budget), + retrieve_temporal(query_embedding, agent_id, fact_types, + start_date, end_date, budget) # 4th strategy +) + +# Fusion via RRF +fused = reciprocal_rank_fusion(results) + +# Rerank with temporal awareness +final = cross_encoder_rerank(query, fused, include_dates=True) +``` + +The 4th strategy (Temporal-Graph) contributes additional ranked results to the fusion process, ensuring that time-relevant facts are strongly represented in the final results. + +## Cross-Encoder Temporal Awareness + +The cross-encoder reranker receives temporal context for more accurate relevance scoring: + +```python +# Standard input: +cross_encoder.predict([ + (query, memory_text) +]) + +# With temporal awareness: +cross_encoder.predict([ + (query, f"[Date: {date_readable}] {memory_text}") +]) + +# Example: +# Query: "What did Alice do last spring?" +# Input to cross-encoder: +# ("What did Alice do last spring?", +# "[Date: April 15, 2024] Alice started learning Rust") +``` + +This allows the reranker to boost facts that align with the query's temporal intent. + +## Performance Considerations + +### Latency + +| Component | Typical Latency | Notes | +|-----------|----------------|-------| +| T5 temporal parsing | ~30-80ms (CPU) | Cached for repeated queries | +| Temporal entry point search | ~25-40ms | PostgreSQL query with time+vector filter | +| Time-filtered graph traversal | ~35-60ms | Similar to standard graph, fewer candidates | +| **Total temporal overhead** | **~50-120ms** | Only when temporal expressions detected | + +### Optimization Tips + +1. **Event Date Indexing**: Ensure `event_date` column is indexed: +```sql +CREATE INDEX idx_memory_units_event_date +ON memory_units (event_date) +WHERE event_date IS NOT NULL; +``` + +2. **Composite Index**: For frequent temporal queries: +```sql +CREATE INDEX idx_memory_units_agent_temporal +ON memory_units (agent_id, event_date, fact_type); +``` + +3. **T5 Model Caching**: The model is loaded once and reused across queries + +## API Reference + +### Python Client + +```python +from hindsight_client import Hindsight +from datetime import datetime + +client = Hindsight(base_url="http://localhost:8888") + +# Store with explicit event date +client.put( + agent_id="my-agent", + content="Event content", + event_date=datetime(2024, 3, 15) +) + +# Search with natural language temporal expression +results = client.search( + agent_id="my-agent", + query="What happened last spring?" +) + +# Results include event_date +for r in results: + print(f"{r['text']} (date: {r['event_date']})") +``` + +### REST API + +```bash +# Store with event date +curl -X POST http://localhost:8888/api/v1/put \ + -H "Content-Type: application/json" \ + -d '{ + "agent_id": "my-agent", + "content": "Alice started new job", + "event_date": "2024-03-15T10:00:00Z" + }' + +# Search (temporal parsing automatic) +curl -X POST http://localhost:8888/api/v1/search \ + -H "Content-Type: application/json" \ + -d '{ + "agent_id": "my-agent", + "query": "What did Alice do last spring?" + }' +``` + +## Advanced: Temporal Ranges in Agent Profiles + +Agents can have temporal ranges that represent their active periods or episodic boundaries: + +```python +# Create agent with temporal range +client.create_agent( + agent_id="my-agent", + name="Alice", + temporal_ranges=[ + { + "start_date": "2023-01-01T00:00:00Z", + "end_date": "2023-12-31T23:59:59Z", + "description": "2023 academic year" + }, + { + "start_date": "2024-01-01T00:00:00Z", + "end_date": "2024-12-31T23:59:59Z", + "description": "2024 academic year" + } + ] +) +``` + +These ranges can be used to: +- Segment memories into distinct time periods +- Filter retrieval to specific life phases +- Support episodic memory queries + +## Limitations and Future Work + +### Current Limitations + +1. **Relative Dates**: "yesterday", "last week" are resolved relative to query time, not event time +2. **Duration Expressions**: "for 3 months" or "during the conference" not fully supported +3. **Fuzzy Temporal**: "around June" or "early spring" treated as exact boundaries +4. **Recurring Events**: "every Monday" or "annual conference" not handled specially + +### Planned Enhancements + +- Duration-based queries ("events lasting more than a week") +- Temporal relationship extraction ("after Alice joined Google", "before the conference") +- Recurrence pattern recognition +- Relative temporal reasoning ("what happened next") + +## Summary + +Hindsight's temporal reasoning capabilities enable natural, time-aware memory queries: + +โœ… **Automatic fact timestamping** - LLM extracts dates from content +โœ… **Natural language parsing** - T5 converts "last spring" to date ranges +โœ… **Temporal-Graph retrieval** - 4th parallel strategy for time-filtered search +โœ… **Cross-encoder awareness** - Reranker considers temporal alignment +โœ… **Low overhead** - Only activates when temporal expressions detected + +This allows agents to answer complex temporal queries like: +- "What did I learn last quarter?" +- "What was Alice working on in March?" +- "Events between the conference and the project launch" diff --git a/memora-docs/docs/sdks/cli.md b/hindsight-docs/docs/sdks/cli.md similarity index 57% rename from memora-docs/docs/sdks/cli.md rename to hindsight-docs/docs/sdks/cli.md index ae4de8810b..51d1ce9b42 100644 --- a/memora-docs/docs/sdks/cli.md +++ b/hindsight-docs/docs/sdks/cli.md @@ -4,7 +4,7 @@ sidebar_position: 3 # CLI Reference -The Memora CLI provides command-line access to memory operations and agent management. +The Hindsight CLI provides command-line access to memory operations and agent management. ## Installation @@ -14,17 +14,17 @@ Download from the releases page: ```bash # macOS (Apple Silicon) -curl -L https://github.com/memora/memora/releases/latest/download/memora-macos-arm64 -o memora -chmod +x memora -sudo mv memora /usr/local/bin/ +curl -L https://github.com/hindsight/hindsight/releases/latest/download/hindsight-macos-arm64 -o hindsight +chmod +x hindsight +sudo mv hindsight /usr/local/bin/ ``` ### Build from Source ```bash -cd memora-cli-rust +cd hindsight-cli-rust cargo build --release -cp target/release/memora /usr/local/bin/ +cp target/release/hindsight /usr/local/bin/ ``` ## Configuration @@ -32,8 +32,8 @@ cp target/release/memora /usr/local/bin/ Set environment variables or use command flags: ```bash -export MEMORA_API_URL=http://localhost:8080 -export MEMORA_AGENT_ID=my-agent +export HINDSIGHT_API_URL=http://localhost:8888 +export HINDSIGHT_AGENT_ID=my-agent ``` ## Commands @@ -45,13 +45,13 @@ export MEMORA_AGENT_ID=my-agent Store a memory: ```bash -memora put "Alice works at Google as a software engineer" +hindsight put "Alice works at Google as a software engineer" # With context -memora put "Bob loves hiking" --context "hobby discussion" +hindsight put "Bob loves hiking" --context "hobby discussion" # With event date -memora put "Meeting with Carol" --date "2024-01-15" +hindsight put "Meeting with Carol" --date "2024-01-15" ``` #### put-files @@ -60,13 +60,13 @@ Store file contents as memories: ```bash # Store a single file -memora put-files notes.txt +hindsight put-files notes.txt # Store multiple files -memora put-files file1.txt file2.md file3.json +hindsight put-files file1.txt file2.md file3.json # With context -memora put-files meeting-notes.txt --context "team meeting" +hindsight put-files meeting-notes.txt --context "team meeting" ``` #### search @@ -74,13 +74,13 @@ memora put-files meeting-notes.txt --context "team meeting" Search memories: ```bash -memora search "What does Alice do?" +hindsight search "What does Alice do?" # With options -memora search "hiking recommendations" --budget 100 --top-k 5 +hindsight search "hiking recommendations" --budget 100 --top-k 5 # Verbose output -memora search "query" -v +hindsight search "query" -v ``` #### think @@ -88,10 +88,10 @@ memora search "query" -v Generate a response using memories and opinions: ```bash -memora think "What do you know about Alice?" +hindsight think "What do you know about Alice?" # Verbose mode shows reasoning -memora think "Should I recommend Python or Java?" -v +hindsight think "Should I recommend Python or Java?" -v ``` ### Agent Management @@ -101,7 +101,7 @@ memora think "Should I recommend Python or Java?" -v List all agents: ```bash -memora agents +hindsight agents ``` Output: @@ -118,7 +118,7 @@ Available agents: View agent profile: ```bash -memora profile +hindsight profile ``` Output: @@ -143,7 +143,7 @@ Background: Update personality traits: ```bash -memora set-personality \ +hindsight set-personality \ --openness 0.8 \ --conscientiousness 0.6 \ --extraversion 0.5 \ @@ -158,7 +158,7 @@ Add or merge background: ```bash # Set/merge background -memora background "I have expertise in distributed systems" +hindsight background "I have expertise in distributed systems" ``` ### MCP Server @@ -166,10 +166,10 @@ memora background "I have expertise in distributed systems" Start the MCP server: ```bash -memora mcp-server +hindsight mcp-server # With custom configuration -MEMORA_API_URL=http://api.example.com memora mcp-server +HINDSIGHT_API_URL=http://api.example.com hindsight mcp-server ``` ## Output Formats @@ -179,7 +179,7 @@ MEMORA_API_URL=http://api.example.com memora mcp-server Human-readable formatted output: ```bash -memora search "query" +hindsight search "query" ``` ### JSON @@ -187,7 +187,7 @@ memora search "query" Machine-readable JSON output: ```bash -memora search "query" -o json +hindsight search "query" -o json ``` ### YAML @@ -195,7 +195,7 @@ memora search "query" -o json YAML formatted output: ```bash -memora search "query" -o yaml +hindsight search "query" -o yaml ``` ## Verbose Mode @@ -203,7 +203,7 @@ memora search "query" -o yaml Add `-v` or `--verbose` for detailed output: ```bash -memora search "query" -v +hindsight search "query" -v ``` Shows: @@ -227,23 +227,23 @@ Shows: ```bash # Create an agent -curl -X PUT http://localhost:8080/api/agents/demo-agent \ +curl -X PUT http://localhost:8888/api/agents/demo-agent \ -H "Content-Type: application/json" \ -d '{"background": "Demo agent"}' # Store memories -memora put demo-agent "Alice works at Google" -memora put demo-agent "Bob is a data scientist" -memora put demo-agent "Alice and Bob are colleagues" +hindsight put demo-agent "Alice works at Google" +hindsight put demo-agent "Bob is a data scientist" +hindsight put demo-agent "Alice and Bob are colleagues" # Search -memora search demo-agent "Who works with Alice?" +hindsight search demo-agent "Who works with Alice?" # Think (with opinions) -memora think demo-agent "What do you know about the team?" +hindsight think demo-agent "What do you know about the team?" # Update personality -memora set-personality demo-agent \ +hindsight set-personality demo-agent \ --openness 0.9 \ --conscientiousness 0.7 \ --extraversion 0.6 \ @@ -252,5 +252,5 @@ memora set-personality demo-agent \ --bias-strength 0.6 # Check profile -memora profile demo-agent +hindsight profile demo-agent ``` diff --git a/memora-docs/docs/sdks/langgraph.md b/hindsight-docs/docs/sdks/langgraph.md similarity index 80% rename from memora-docs/docs/sdks/langgraph.md rename to hindsight-docs/docs/sdks/langgraph.md index 4801556a85..a96656eb48 100644 --- a/memora-docs/docs/sdks/langgraph.md +++ b/hindsight-docs/docs/sdks/langgraph.md @@ -4,22 +4,22 @@ sidebar_position: 3 # LangGraph -Memora provides a `BaseStore` implementation for LangGraph's memory system. +Hindsight provides a `BaseStore` implementation for LangGraph's memory system. ## Installation ```bash -cd memora-langmem && uv pip install -e . +cd hindsight-langmem && uv pip install -e . ``` ## Quick Start ```python -from memora_langmem import MemoraStore +from hindsight_langmem import HindsightStore # Create store -store = MemoraStore( - base_url="http://localhost:8080", +store = HindsightStore( + base_url="http://localhost:8888", default_agent_id="my-agent", ) @@ -44,9 +44,9 @@ results = store.search( ## How It Works -`MemoraStore` implements LangGraph's `BaseStore` interface: +`HindsightStore` implements LangGraph's `BaseStore` interface: -- **Namespaces** map to Memora agent IDs (joined with `__`) +- **Namespaces** map to Hindsight agent IDs (joined with `__`) - **Keys** map to document IDs - **Values** are stored as JSON in memory content @@ -115,9 +115,9 @@ await store.adelete(namespace, key) ```python from langgraph.graph import StateGraph -from memora_langmem import MemoraStore +from hindsight_langmem import HindsightStore -store = MemoraStore(base_url="http://localhost:8080") +store = HindsightStore(base_url="http://localhost:8888") # Use store in your graph graph = StateGraph() @@ -126,7 +126,7 @@ graph = StateGraph() ## Namespace Mapping -Namespaces are converted to Memora agent IDs: +Namespaces are converted to Hindsight agent IDs: | Namespace | Agent ID | |-----------|----------| diff --git a/memora-docs/docs/sdks/mcp.md b/hindsight-docs/docs/sdks/mcp.md similarity index 64% rename from memora-docs/docs/sdks/mcp.md rename to hindsight-docs/docs/sdks/mcp.md index 698ca60e2e..91b3da88b7 100644 --- a/memora-docs/docs/sdks/mcp.md +++ b/hindsight-docs/docs/sdks/mcp.md @@ -9,7 +9,7 @@ Model Context Protocol server for AI assistants like Claude Desktop. ## Installation ```bash -cd memora-cli && cargo build --release +cd hindsight-cli && cargo build --release ``` ## Claude Desktop Setup @@ -19,12 +19,12 @@ Add to `~/Library/Application Support/Claude/claude_desktop_config.json`: ```json { "mcpServers": { - "memora": { - "command": "/path/to/memora", + "hindsight": { + "command": "/path/to/hindsight", "args": ["mcp-server"], "env": { - "MEMORA_API_URL": "http://localhost:8080", - "MEMORA_AGENT_ID": "claude-agent" + "HINDSIGHT_API_URL": "http://localhost:8888", + "HINDSIGHT_AGENT_ID": "claude-agent" } } } @@ -35,18 +35,18 @@ Add to `~/Library/Application Support/Claude/claude_desktop_config.json`: | Variable | Description | Default | |----------|-------------|---------| -| `MEMORA_API_URL` | Memora API URL | `http://localhost:8080` | -| `MEMORA_AGENT_ID` | Default agent ID | Required | +| `HINDSIGHT_API_URL` | Hindsight API URL | `http://localhost:8888` | +| `HINDSIGHT_AGENT_ID` | Default agent ID | Required | ## Available Tools -### memora_search +### hindsight_search Search memories: ```json { - "name": "memora_search", + "name": "hindsight_search", "arguments": { "query": "What does Alice do for work?", "top_k": 5 @@ -54,26 +54,26 @@ Search memories: } ``` -### memora_think +### hindsight_think Generate response using memories: ```json { - "name": "memora_think", + "name": "hindsight_think", "arguments": { "query": "What should I recommend to Alice?" } } ``` -### memora_store +### hindsight_store Store new memory: ```json { - "name": "memora_store", + "name": "hindsight_store", "arguments": { "content": "User prefers Python for data analysis", "context": "programming discussion" @@ -81,24 +81,24 @@ Store new memory: } ``` -### memora_agents +### hindsight_agents List available agents: ```json { - "name": "memora_agents", + "name": "hindsight_agents", "arguments": {} } ``` ## Usage Example -Once configured, Claude can use Memora naturally: +Once configured, Claude can use Hindsight naturally: **User**: "Remember that I prefer morning meetings" -**Claude**: *Uses memora_store* +**Claude**: *Uses hindsight_store* > "I've noted that you prefer morning meetings." @@ -106,7 +106,7 @@ Once configured, Claude can use Memora naturally: **User**: "What do you know about my preferences?" -**Claude**: *Uses memora_search* +**Claude**: *Uses hindsight_search* > "Based on our conversations, you prefer morning meetings and like Python for data analysis." @@ -115,11 +115,11 @@ Once configured, Claude can use Memora naturally: Run standalone: ```bash -memora mcp-server +hindsight mcp-server ``` Debug mode: ```bash -RUST_LOG=debug memora mcp-server +RUST_LOG=debug hindsight mcp-server ``` diff --git a/memora-docs/docs/sdks/nodejs.md b/hindsight-docs/docs/sdks/nodejs.md similarity index 87% rename from memora-docs/docs/sdks/nodejs.md rename to hindsight-docs/docs/sdks/nodejs.md index 5a1e77f4d4..e216acbac3 100644 --- a/memora-docs/docs/sdks/nodejs.md +++ b/hindsight-docs/docs/sdks/nodejs.md @@ -4,21 +4,21 @@ sidebar_position: 2 # Node.js Client -Official TypeScript/JavaScript client for the Memora API. +Official TypeScript/JavaScript client for the Hindsight API. ## Installation ```bash -npm install @memora/client +npm install @hindsight/client ``` ## Quick Start ```typescript -import { OpenAPI, MemoryStorageService, SearchService } from '@memora/client'; +import { OpenAPI, MemoryStorageService, SearchService } from '@hindsight/client'; // Configure base URL -OpenAPI.BASE = 'http://localhost:8080'; +OpenAPI.BASE = 'http://localhost:8888'; // Store a memory await MemoryStorageService.putApiPutPost({ @@ -38,9 +38,9 @@ console.log(results); ## Configuration ```typescript -import { OpenAPI } from '@memora/client'; +import { OpenAPI } from '@hindsight/client'; -OpenAPI.BASE = 'http://localhost:8080'; +OpenAPI.BASE = 'http://localhost:8888'; OpenAPI.TOKEN = 'your-api-token'; // If authentication is enabled ``` @@ -49,7 +49,7 @@ OpenAPI.TOKEN = 'your-api-token'; // If authentication is enabled ### Store Memory ```typescript -import { MemoryStorageService } from '@memora/client'; +import { MemoryStorageService } from '@hindsight/client'; await MemoryStorageService.putApiPutPost({ agent_id: 'my-agent', @@ -77,7 +77,7 @@ await MemoryStorageService.batchApiMemoriesBatchPost({ ### Basic Search ```typescript -import { SearchService } from '@memora/client'; +import { SearchService } from '@hindsight/client'; const results = await SearchService.searchApiSearchPost({ agent_id: 'my-agent', @@ -121,7 +121,7 @@ const opinions = await SearchService.opinionSearchApiOpinionSearchPost({ ## Think (Generate Response) ```typescript -import { ReasoningService } from '@memora/client'; +import { ReasoningService } from '@hindsight/client'; const response = await ReasoningService.thinkApiThinkPost({ agent_id: 'my-agent', @@ -139,7 +139,7 @@ console.log(response.new_opinions); // New opinions formed ### Create Agent ```typescript -import { ManagementService } from '@memora/client'; +import { ManagementService } from '@hindsight/client'; await ManagementService.createAgentApiAgentsAgentIdPut('my-agent', { name: 'Assistant', @@ -192,7 +192,7 @@ await ManagementService.mergeBackgroundApiAgentsAgentIdBackgroundPost('my-agent' ## Error Handling ```typescript -import { ApiError } from '@memora/client'; +import { ApiError } from '@hindsight/client'; try { await SearchService.searchApiSearchPost({ @@ -218,7 +218,7 @@ import type { ThinkResponse, MemoryItem, PersonalityTraits, -} from '@memora/client'; +} from '@hindsight/client'; const personality: PersonalityTraits = { openness: 0.7, diff --git a/memora-docs/docs/sdks/openai.md b/hindsight-docs/docs/sdks/openai.md similarity index 83% rename from memora-docs/docs/sdks/openai.md rename to hindsight-docs/docs/sdks/openai.md index ef5d0ea16c..3d04643730 100644 --- a/memora-docs/docs/sdks/openai.md +++ b/hindsight-docs/docs/sdks/openai.md @@ -9,17 +9,17 @@ Drop-in replacement for the OpenAI Python client with automatic memory integrati ## Installation ```bash -cd memora-openai && uv pip install -e . +cd hindsight-openai && uv pip install -e . ``` ## Quick Start ```python -from memora_openai import configure, OpenAI +from hindsight_openai import configure, OpenAI # Configure once configure( - memora_api_url="http://localhost:8080", + hindsight_api_url="http://localhost:8888", agent_id="my-agent", ) @@ -37,7 +37,7 @@ response = client.chat.completions.create( The wrapper intercepts OpenAI calls: 1. **Before**: Retrieves relevant memories and injects as system message -2. **After**: Stores conversation to Memora +2. **After**: Stores conversation to Hindsight Your code works exactly as before, but now has memory. @@ -45,7 +45,7 @@ Your code works exactly as before, but now has memory. ```python configure( - memora_api_url="http://localhost:8080", # Memora API + hindsight_api_url="http://localhost:8888", # Hindsight API agent_id="my-agent", # Required store_conversations=True, # Store conversations inject_memories=True, # Inject memories into prompts @@ -75,9 +75,9 @@ messages = [ ## Async Support ```python -from memora_openai import configure, AsyncOpenAI +from hindsight_openai import configure, AsyncOpenAI -configure(memora_api_url="http://localhost:8080", agent_id="my-agent") +configure(hindsight_api_url="http://localhost:8888", agent_id="my-agent") client = AsyncOpenAI(api_key="sk-...") @@ -105,7 +105,7 @@ for chunk in stream: ## Disable Temporarily ```python -from memora_openai import configure +from hindsight_openai import configure configure(enabled=False) # Disable configure(enabled=True) # Re-enable diff --git a/memora-docs/docs/sdks/python.md b/hindsight-docs/docs/sdks/python.md similarity index 67% rename from memora-docs/docs/sdks/python.md rename to hindsight-docs/docs/sdks/python.md index d0f9e594d4..fbe73230d1 100644 --- a/memora-docs/docs/sdks/python.md +++ b/hindsight-docs/docs/sdks/python.md @@ -4,23 +4,73 @@ sidebar_position: 1 # Python Client -Official Python client for the Memora API. +Official Python client for the Hindsight API. + +import Tabs from '@theme/Tabs'; +import TabItem from '@theme/TabItem'; ## Installation + + + +The `hindsight-all` package includes embedded PostgreSQL, HTTP API server, and client: + +```bash +pip install hindsight-all +``` + + + + +If you already have a Hindsight server running: + ```bash -pip install memora-client +pip install hindsight-client ``` + + + ## Quick Start + + + ```python -from memora_client import Memora +import os +from hindsight import HindsightServer, HindsightClient + +with HindsightServer( + llm_provider="openai", + llm_model="gpt-4.1-mini", + llm_api_key=os.environ["OPENAI_API_KEY"] +) as server: + client = HindsightClient(base_url=server.url) + + # Store a memory + client.put(agent_id="my-agent", content="Alice works at Google") + + # Search memories + results = client.search(agent_id="my-agent", query="What does Alice do?") + for r in results: + print(r["text"], r["weight"]) + + # Generate response with personality + answer = client.think(agent_id="my-agent", query="Tell me about Alice") + print(answer["text"]) +``` -client = Memora(base_url="http://localhost:8080") + + + +```python +from hindsight_client import Hindsight + +client = Hindsight(base_url="http://localhost:8888") # Store a memory -client.store(agent_id="my-agent", content="Alice works at Google") +client.put(agent_id="my-agent", content="Alice works at Google") # Search memories results = client.search(agent_id="my-agent", query="What does Alice do?") @@ -32,13 +82,16 @@ answer = client.think(agent_id="my-agent", query="Tell me about Alice") print(answer["text"]) ``` + + + ## Client Initialization ```python -from memora_client import Memora +from hindsight_client import Hindsight -client = Memora( - base_url="http://localhost:8080", # Memora API URL +client = Hindsight( + base_url="http://localhost:8888", # Hindsight API URL timeout=30.0, # Request timeout in seconds ) ``` @@ -187,13 +240,13 @@ client.update_background( ## Error Handling ```python -from memora_client import Memora, MemoraError +from hindsight_client import Hindsight, HindsightError -client = Memora(base_url="http://localhost:8080") +client = Hindsight(base_url="http://localhost:8888") try: results = client.search(agent_id="unknown", query="test") -except MemoraError as e: +except HindsightError as e: print(f"Error: {e.message}") print(f"Status: {e.status}") ``` @@ -202,10 +255,10 @@ except MemoraError as e: ```python import asyncio -from memora_client import AsyncMemora +from hindsight_client import AsyncHindsight async def main(): - client = AsyncMemora(base_url="http://localhost:8080") + client = AsyncHindsight(base_url="http://localhost:8888") # All methods have async versions await client.store(agent_id="my-agent", content="Hello world") diff --git a/memora-docs/docusaurus.config.ts b/hindsight-docs/docusaurus.config.ts similarity index 89% rename from memora-docs/docusaurus.config.ts rename to hindsight-docs/docusaurus.config.ts index b66e9ab13e..dd99d0fa08 100644 --- a/memora-docs/docusaurus.config.ts +++ b/hindsight-docs/docusaurus.config.ts @@ -4,7 +4,7 @@ import type * as Preset from '@docusaurus/preset-classic'; import type * as OpenApiPlugin from 'docusaurus-plugin-openapi-docs'; const config: Config = { - title: 'Memora', + title: 'Hindsight', tagline: 'Entity-Aware Memory System for AI Agents', favicon: 'img/favicon.ico', @@ -61,7 +61,7 @@ const config: Config = { { docs: { sidebarPath: './sidebars.ts', - editUrl: 'https://github.com/memora/memora/tree/main/memora-docs/', + editUrl: 'https://github.com/vectorize-io/hindsight/tree/main/hindsight-docs/', routeBasePath: '/', docItemComponent: '@theme/ApiItem', }, @@ -80,7 +80,7 @@ const config: Config = { id: 'api', docsPluginId: 'default', config: { - memora: { + hindsight: { specPath: 'openapi.json', outputDir: 'docs/api-reference/endpoints', sidebarOptions: { @@ -95,15 +95,15 @@ const config: Config = { themes: ['docusaurus-theme-openapi-docs', '@docusaurus/theme-mermaid'], themeConfig: { - image: 'img/memora-social-card.jpg', + image: 'img/hindsight-social-card.jpg', colorMode: { defaultMode: 'dark', respectPrefersColorScheme: true, }, navbar: { - title: 'Memora', + title: 'Hindsight', logo: { - alt: 'Memora Logo', + alt: 'Hindsight Logo', src: 'img/logo.svg', }, items: [ @@ -143,7 +143,7 @@ const config: Config = { to: '/changelog', }, { - href: 'https://github.com/memora/memora', + href: 'https://github.com/vectorize-io/hindsight', label: 'GitHub', position: 'right', }, @@ -174,12 +174,12 @@ const config: Config = { items: [ { label: 'GitHub', - href: 'https://github.com/memora/memora', + href: 'https://github.com/vectorize-io/hindsight', }, ], }, ], - copyright: `Copyright ยฉ ${new Date().getFullYear()} Memora. Built with Docusaurus.`, + copyright: `Copyright ยฉ ${new Date().getFullYear()} Hindsight. Built with Docusaurus.`, }, prism: { theme: prismThemes.github, diff --git a/memora-docs/openapi.json b/hindsight-docs/openapi.json similarity index 100% rename from memora-docs/openapi.json rename to hindsight-docs/openapi.json diff --git a/memora-docs/package-lock.json b/hindsight-docs/package-lock.json similarity index 99% rename from memora-docs/package-lock.json rename to hindsight-docs/package-lock.json index 5359473ddf..6aff29474a 100644 --- a/memora-docs/package-lock.json +++ b/hindsight-docs/package-lock.json @@ -1,11 +1,11 @@ { - "name": "memora-docs", + "name": "hindsight-docs", "version": "0.0.0", "lockfileVersion": 3, "requires": true, "packages": { "": { - "name": "memora-docs", + "name": "hindsight-docs", "version": "0.0.0", "dependencies": { "@docusaurus/core": "3.9.2", @@ -4557,26 +4557,6 @@ "@parcel/watcher-win32-x64": "2.5.1" } }, - "node_modules/@parcel/watcher-android-arm64": { - "version": "2.5.1", - "resolved": 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b/hindsight-docs/package.json @@ -1,5 +1,5 @@ { - "name": "memora-docs", + "name": "hindsight-docs", "version": "0.0.0", "private": true, "scripts": { diff --git a/memora-docs/sidebars.ts b/hindsight-docs/sidebars.ts similarity index 100% rename from memora-docs/sidebars.ts rename to hindsight-docs/sidebars.ts diff --git a/memora-docs/src/components/NavbarIconLink.tsx b/hindsight-docs/src/components/NavbarIconLink.tsx similarity index 100% rename from memora-docs/src/components/NavbarIconLink.tsx rename to hindsight-docs/src/components/NavbarIconLink.tsx diff --git a/memora-docs/src/css/custom.css b/hindsight-docs/src/css/custom.css similarity index 81% rename from memora-docs/src/css/custom.css rename to hindsight-docs/src/css/custom.css index f70eff458d..538f4cbe01 100644 --- a/memora-docs/src/css/custom.css +++ b/hindsight-docs/src/css/custom.css @@ -1,5 +1,5 @@ /** - * Memora custom theme - Modern, clean style + * Hindsight custom theme - Modern, clean style */ /* Primary colors - Teal/Cyan theme */ @@ -331,3 +331,73 @@ article ul, article ol { article li { margin-bottom: 0.25rem; } + +/* API Method badges in sidebar */ +.api-method::before { + display: inline-block; + font-size: 0.625rem; + font-weight: 700; + text-transform: uppercase; + padding: 0.125rem 0.375rem; + border-radius: 0.25rem; + margin-right: 0.5rem; + font-family: var(--ifm-font-family-monospace); + letter-spacing: 0.025em; + vertical-align: middle; +} + +.api-method.get::before { + content: 'GET'; + background-color: rgba(34, 197, 94, 0.15); + color: #22c55e; +} + +.api-method.post::before { + content: 'POST'; + background-color: rgba(59, 130, 246, 0.15); + color: #3b82f6; +} + +.api-method.put::before { + content: 'PUT'; + background-color: rgba(249, 115, 22, 0.15); + color: #f97316; +} + +.api-method.delete::before { + content: 'DEL'; + background-color: rgba(239, 68, 68, 0.15); + color: #ef4444; +} + +.api-method.patch::before { + content: 'PATCH'; + background-color: rgba(168, 85, 247, 0.15); + color: #a855f7; +} + +/* Dark mode adjustments */ +[data-theme='dark'] .api-method.get::before { + background-color: rgba(34, 197, 94, 0.2); + color: #4ade80; +} + +[data-theme='dark'] .api-method.post::before { + background-color: rgba(59, 130, 246, 0.2); + color: #60a5fa; +} + +[data-theme='dark'] .api-method.put::before { + background-color: rgba(249, 115, 22, 0.2); + color: #fb923c; +} + +[data-theme='dark'] .api-method.delete::before { + background-color: rgba(239, 68, 68, 0.2); + color: #f87171; +} + +[data-theme='dark'] .api-method.patch::before { + background-color: rgba(168, 85, 247, 0.2); + color: #c084fc; +} diff --git a/memora-docs/src/theme/NavbarItem/ComponentTypes.tsx b/hindsight-docs/src/theme/NavbarItem/ComponentTypes.tsx similarity index 100% rename from memora-docs/src/theme/NavbarItem/ComponentTypes.tsx rename to hindsight-docs/src/theme/NavbarItem/ComponentTypes.tsx diff --git a/memora-docs/static/.nojekyll b/hindsight-docs/static/.nojekyll similarity 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a/memora-docs/static/img/undraw_docusaurus_mountain.svg b/hindsight-docs/static/img/undraw_docusaurus_mountain.svg similarity index 100% rename from memora-docs/static/img/undraw_docusaurus_mountain.svg rename to hindsight-docs/static/img/undraw_docusaurus_mountain.svg diff --git a/memora-docs/static/img/undraw_docusaurus_react.svg b/hindsight-docs/static/img/undraw_docusaurus_react.svg similarity index 100% rename from memora-docs/static/img/undraw_docusaurus_react.svg rename to hindsight-docs/static/img/undraw_docusaurus_react.svg diff --git a/memora-docs/static/img/undraw_docusaurus_tree.svg b/hindsight-docs/static/img/undraw_docusaurus_tree.svg similarity index 100% rename from memora-docs/static/img/undraw_docusaurus_tree.svg rename to hindsight-docs/static/img/undraw_docusaurus_tree.svg diff --git a/memora-docs/tsconfig.json b/hindsight-docs/tsconfig.json similarity index 100% rename from memora-docs/tsconfig.json rename to hindsight-docs/tsconfig.json diff --git a/hindsight-integrations/langmem/hindsight_langmem/__init__.py b/hindsight-integrations/langmem/hindsight_langmem/__init__.py new file mode 100644 index 0000000000..031ef30718 --- /dev/null +++ b/hindsight-integrations/langmem/hindsight_langmem/__init__.py @@ -0,0 +1,5 @@ +"""Hindsight-LangMem: LangGraph langmem drop-in replacement using Hindsight.""" + +from hindsight_langmem.store import HindsightStore + +__all__ = ["HindsightStore"] diff --git a/memora-langmem/memora_langmem/store.py b/hindsight-integrations/langmem/hindsight_langmem/store.py similarity index 93% rename from memora-langmem/memora_langmem/store.py rename to hindsight-integrations/langmem/hindsight_langmem/store.py index db79de5a9b..226f8762e4 100644 --- a/memora-langmem/memora_langmem/store.py +++ b/hindsight-integrations/langmem/hindsight_langmem/store.py @@ -1,9 +1,9 @@ -"""Memora implementation of LangGraph BaseStore interface.""" +"""Hindsight implementation of LangGraph BaseStore interface.""" import json from typing import Any, Iterable -from memora_client import Memora +from hindsight_client import Hindsight from langgraph.store.base import ( BaseStore, GetOp, @@ -17,27 +17,27 @@ ) -class MemoraStore(BaseStore): +class HindsightStore(BaseStore): """ - Memora implementation of LangGraph BaseStore. + Hindsight implementation of LangGraph BaseStore. - This store uses Memora's memory system as a backend for LangGraph's memory storage. - Each namespace maps to a Memora agent, and items are stored as memory units. + This store uses Hindsight's memory system as a backend for LangGraph's memory storage. + Each namespace maps to a Hindsight agent, and items are stored as memory units. Args: - base_url: The base URL of the Memora API server + base_url: The base URL of the Hindsight API server default_agent_id: Default agent ID to use when namespace is empty (optional) """ def __init__(self, base_url: str, default_agent_id: str | None = None): - """Initialize the Memora store. + """Initialize the Hindsight store. Args: - base_url: Base URL for the Memora API + base_url: Base URL for the Hindsight API default_agent_id: Default agent ID when namespace is empty """ super().__init__() - self.client = Memora(base_url=base_url) + self.client = Hindsight(base_url=base_url) self.default_agent_id = default_agent_id or "default" self._ensure_agent_exists(self.default_agent_id) diff --git a/memora-langmem/pyproject.toml b/hindsight-integrations/langmem/pyproject.toml similarity index 53% rename from memora-langmem/pyproject.toml rename to hindsight-integrations/langmem/pyproject.toml index 3fb90175c6..8b5a8bc3fd 100644 --- a/memora-langmem/pyproject.toml +++ b/hindsight-integrations/langmem/pyproject.toml @@ -1,18 +1,18 @@ [project] -name = "memora-langmem" +name = "hindsight-langmem" version = "0.0.1" -description = "LangGraph langmem drop-in replacement using Memora memory system" +description = "LangGraph langmem drop-in replacement using Hindsight memory system" authors = [ - {name = "Memora Team"} + {name = "Hindsight Team"} ] requires-python = ">=3.10" dependencies = [ "langgraph>=0.2.0", - "memora-client", + "hindsight-client", ] [tool.uv.sources] -memora-client = { workspace = true } +hindsight-client = { path = "../../hindsight-clients/python" } [project.optional-dependencies] test = [ @@ -23,6 +23,9 @@ test = [ requires = ["hatchling"] build-backend = "hatchling.build" +[tool.hatch.build.targets.wheel] +packages = ["hindsight_langmem"] + [tool.ruff] line-length = 120 diff --git a/hindsight-integrations/langmem/tests/__init__.py b/hindsight-integrations/langmem/tests/__init__.py new file mode 100644 index 0000000000..d313656736 --- /dev/null +++ b/hindsight-integrations/langmem/tests/__init__.py @@ -0,0 +1 @@ +"""Tests for hindsight-langmem package.""" diff --git a/memora-langmem/tests/test_store.py b/hindsight-integrations/langmem/tests/test_store.py similarity index 89% rename from memora-langmem/tests/test_store.py rename to hindsight-integrations/langmem/tests/test_store.py index 3713c10a66..8630e888aa 100644 --- a/memora-langmem/tests/test_store.py +++ b/hindsight-integrations/langmem/tests/test_store.py @@ -1,18 +1,18 @@ -"""Tests for MemoraStore implementation.""" +"""Tests for HindsightStore implementation.""" import os import time import pytest -from memora_langmem import MemoraStore +from hindsight_langmem import HindsightStore @pytest.fixture def store(): - """Create a MemoraStore instance for testing.""" - base_url = os.getenv("MEMORA_API_URL", "http://localhost:8000") - return MemoraStore(base_url=base_url, default_agent_id=f"test_agent_{int(time.time())}") + """Create a HindsightStore instance for testing.""" + base_url = os.getenv("HINDSIGHT_API_URL", "http://localhost:8888") + return HindsightStore(base_url=base_url, default_agent_id=f"test_agent_{int(time.time())}") def test_put_and_get(store): diff --git a/hindsight-integrations/langmem/tutorial.ipynb b/hindsight-integrations/langmem/tutorial.ipynb new file mode 100644 index 0000000000..24b9b4f25c --- /dev/null +++ b/hindsight-integrations/langmem/tutorial.ipynb @@ -0,0 +1,163 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": "# Hindsight-LangMem: Drop-in Semantic Memory for LangGraph\n\nReplace your LangGraph memory store in one line and get advanced semantic capabilities." + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": "## What is Hindsight-LangMem?\n\n`hindsight-langmem` implements LangGraph's `BaseStore` interface using Hindsight as the backend.\n\n### What You Get vs Standard LangGraph Memory\n\n| Feature | Standard Memory | Hindsight-LangMem |\n|---------|-----------------|-------------------|\n| Basic Key-Value Storage | โœ… | โœ… |\n| Semantic Search | โœ… Basic | โœ… **Enhanced with spreading activation** |\n| Namespace Support | โœ… | โœ… |\n| **Personality-Driven Retrieval** | โŒ | โœ… |\n| **Automatic Fact Extraction** | โŒ | โœ… |\n| **Entity Recognition** | โŒ | โœ… |\n| **Temporal Reasoning** | โŒ | โœ… |\n| **Opinion Formation** | โŒ | โœ… |\n| **Background Knowledge** | โŒ | โœ… |\n| **Thinking/Reasoning API** | โŒ | โœ… |\n\n### When to Use\n- Conversational agents needing long-term memory\n- Personalized AI with context-aware responses \n- Multi-agent systems with distinct personalities\n- Knowledge management with semantic search" + }, + { + "cell_type": "markdown", + "source": "## Installation\n\nRun this cell to install dependencies:", + "metadata": {} + }, + { + "cell_type": "code", + "source": "!pip install langgraph langmem", + "metadata": {}, + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "markdown", + "source": "Make sure Hindsight API is running at `http://localhost:8888`", + "metadata": {} + }, + { + "cell_type": "markdown", + "source": "## Setup API Keys\n\nSet up your OpenAI API key and Hindsight URL:", + "metadata": {} + }, + { + "cell_type": "code", + "source": "import os\nimport getpass\n\n# Set OpenAI API key\nif \"OPENAI_API_KEY\" not in os.environ:\n os.environ[\"OPENAI_API_KEY\"] = getpass.getpass(\"Enter your OpenAI API key: \")\n\n# Set Hindsight API URL\nif \"HINDSIGHT_API_URL\" not in os.environ:\n os.environ[\"HINDSIGHT_API_URL\"] = input(\"Enter Hindsight API URL (default: http://localhost:8888): \") or \"http://localhost:8888\"\n\nprint(\"โœ… API keys configured\")", + "metadata": {}, + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## The Drop-in Replacement\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "source": "### Before: Standard LangGraph Memory", + "metadata": {} + }, + { + "cell_type": "code", + "source": "from langmem import create_manage_memory_tool, create_search_memory_tool\nfrom langgraph.prebuilt import create_react_agent\nfrom langgraph.store.memory import InMemoryStore\n\n# Standard store - basic key-value with optional vector search\nstore = InMemoryStore()\n\nagent = create_react_agent(\n \"openai:gpt-4o\",\n tools=[\n create_manage_memory_tool(namespace=(\"memories\",)),\n create_search_memory_tool(namespace=(\"memories\",)),\n ],\n store=store\n)", + "metadata": {}, + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "markdown", + "source": "### After: With Hindsight-LangMem\n\n**Just change one line!**", + "metadata": {}, + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": {}, + "source": "import os\nfrom langmem import create_manage_memory_tool, create_search_memory_tool\nfrom langgraph.prebuilt import create_react_agent\nfrom hindsight_langmem import HindsightStore # โ† Only import change!\n\n# Replace InMemoryStore with HindsightStore\nbase_url = os.getenv(\"HINDSIGHT_API_URL\", \"http://localhost:8888\")\nstore = HindsightStore(base_url=base_url, default_agent_id=\"my_agent\") # โ† One line change!\n\n# Everything else stays exactly the same\nagent = create_react_agent(\n \"openai:gpt-4o\", # โ† Use OpenAI\n tools=[\n create_manage_memory_tool(namespace=(\"memories\",)),\n create_search_memory_tool(namespace=(\"memories\",)),\n ],\n store=store # โ† Now using Hindsight with enhanced capabilities!\n)\n\nprint(\"โœ… Agent created with Hindsight-powered memory\")", + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": "import os\nfrom langmem import create_manage_memory_tool, create_search_memory_tool\nfrom langgraph.prebuilt import create_react_agent\nfrom hindsight_langmem import HindsightStore # โ† Only import change!\n\n# Replace InMemoryStore with HindsightStore\nbase_url = os.getenv(\"HINDSIGHT_API_URL\", \"http://localhost:8888\")\nstore = HindsightStore(base_url=base_url, default_agent_id=\"my_agent\") # โ† One line change!\n\n# Everything else stays exactly the same\nagent = create_react_agent(\n \"anthropic:claude-3-5-sonnet-latest\",\n tools=[\n create_manage_memory_tool(namespace=(\"memories\",)),\n create_search_memory_tool(namespace=(\"memories\",)),\n ],\n store=store # โ† Now using Hindsight with enhanced capabilities!\n)\n\nprint(\"โœ… Agent created with Hindsight-powered memory\")" + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Example: Conversational Memory in Action" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import time\n", + "\n", + "# Store information\n", + "result1 = agent.invoke({\n", + " \"messages\": [{\n", + " \"role\": \"user\",\n", + " \"content\": \"\"\"Remember: I'm David, a software engineer working on AI projects. \n", + " I love Python and machine learning. Currently building a chatbot with LangGraph.\"\"\"\n", + " }]\n", + "})\n", + "print(\"Agent:\", result1[\"messages\"][-1].content)\n", + "\n", + "time.sleep(2)\n", + "\n", + "# Recall information\n", + "result2 = agent.invoke({\n", + " \"messages\": [{\"role\": \"user\", \"content\": \"What do you remember about me?\"}]\n", + "})\n", + "print(\"\\nAgent:\", result2[\"messages\"][-1].content)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": "## What Happens Behind the Scenes\n\nWhen your agent stores memories with Hindsight, automatically:\n\n1. **Fact Extraction**: Natural language โ†’ structured facts\n2. **Entity Recognition**: Identifies people, places, concepts\n3. **Semantic Indexing**: Spreading activation for better retrieval\n4. **Temporal Awareness**: Event dates tracked for time queries\n5. **Opinion Formation**: Agent develops perspectives over time\n6. **Personality Influence**: Memory retrieval shaped by personality traits\n\n**You use the standard LangGraph API - Hindsight does the rest!**" + }, + { + "cell_type": "code", + "metadata": {}, + "source": "# Different agents with different personalities\ncreative_store = HindsightStore(base_url=base_url, default_agent_id=\"creative_writer\")\nanalyst_store = HindsightStore(base_url=base_url, default_agent_id=\"data_analyst\")\n\ncreative_agent = create_react_agent(\n \"openai:gpt-4o\",\n tools=[\n create_manage_memory_tool(namespace=(\"creative\",)),\n create_search_memory_tool(namespace=(\"creative\",))\n ],\n store=creative_store\n)\n\nanalyst_agent = create_react_agent(\n \"openai:gpt-4o\",\n tools=[\n create_manage_memory_tool(namespace=(\"analysis\",)),\n create_search_memory_tool(namespace=(\"analysis\",))\n ],\n store=analyst_store\n)\n\nprint(\"โœ… Two agents with isolated memories and distinct personalities\")", + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": "# Different agents with different personalities\ncreative_store = HindsightStore(base_url=base_url, default_agent_id=\"creative_writer\")\nanalyst_store = HindsightStore(base_url=base_url, default_agent_id=\"data_analyst\")\n\ncreative_agent = create_react_agent(\n \"anthropic:claude-3-5-sonnet-latest\",\n tools=[\n create_manage_memory_tool(namespace=(\"creative\",)),\n create_search_memory_tool(namespace=(\"creative\",))\n ],\n store=creative_store\n)\n\nanalyst_agent = create_react_agent(\n \"anthropic:claude-3-5-sonnet-latest\",\n tools=[\n create_manage_memory_tool(namespace=(\"analysis\",)),\n create_search_memory_tool(namespace=(\"analysis\",))\n ],\n store=analyst_store\n)\n\nprint(\"โœ… Two agents with isolated memories and distinct personalities\")" + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": "## Summary\n\n### The Change\n```python\n# Before\nstore = InMemoryStore()\n\n# After \nstore = HindsightStore(base_url=\"http://localhost:8888\", default_agent_id=\"my_agent\")\n```\n\n### What You Get\n- โœ… Semantic search with spreading activation\n- โœ… Automatic fact extraction from conversations\n- โœ… Entity recognition and linking\n- โœ… Temporal reasoning (time-aware queries)\n- โœ… Personality-driven memory retrieval\n- โœ… Opinion formation over time\n- โœ… Multi-agent support with isolated memories\n\n**Same LangGraph API. Smarter memory. Zero code changes (except the store line).**" + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.10" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} \ No newline at end of file diff --git a/memora-langmem/uv.lock b/hindsight-integrations/langmem/uv.lock similarity index 54% rename from memora-langmem/uv.lock rename to hindsight-integrations/langmem/uv.lock index c6c4b1c406..7483de9c5e 100644 --- a/memora-langmem/uv.lock +++ b/hindsight-integrations/langmem/uv.lock @@ -2,6 +2,160 @@ version = 1 revision = 1 requires-python = ">=3.10" +[[package]] +name = "aiohappyeyeballs" +version = "2.6.1" +source = { registry = "https://pypi.org/simple" } +sdist = { url = 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index 68% rename from memora-openai/README.md rename to hindsight-integrations/openai/README.md index 418249e3c7..3c45f50eb9 100644 --- a/memora-openai/README.md +++ b/hindsight-integrations/openai/README.md @@ -1,25 +1,25 @@ -# Memora-OpenAI +# Hindsight-OpenAI -Drop-in replacement for OpenAI Python client with automatic Memora integration. +Drop-in replacement for OpenAI Python client with automatic Hindsight integration. ## Overview -`memora-openai` is a transparent wrapper around the official OpenAI Python client that automatically: -- ๐Ÿง  **Injects relevant memories** from your Memora system into conversations -- ๐Ÿ’พ **Stores conversation history** to Memora for future retrieval +`hindsight-openai` is a transparent wrapper around the official OpenAI Python client that automatically: +- ๐Ÿง  **Injects relevant memories** from your Hindsight system into conversations +- ๐Ÿ’พ **Stores conversation history** to Hindsight for future retrieval - ๐Ÿ”„ **Works seamlessly** with existing OpenAI code (just change the import) - โšก **Supports both sync and async** clients ## Installation -This package is part of the Memora workspace. Install from the root: +This package is part of the Hindsight workspace. Install from the root: ```bash # From repository root uv sync # Or install just this package -cd memora-openai +cd hindsight-integrations/openai uv pip install -e . ``` @@ -28,17 +28,17 @@ uv pip install -e . ### Basic Usage ```python -from memora_openai import configure, OpenAI +from hindsight_openai import configure, OpenAI -# Configure Memora integration once +# Configure Hindsight integration once configure( - memora_api_url="http://localhost:8000", + hindsight_api_url="http://localhost:8888", agent_id="my-agent", store_conversations=True, inject_memories=True, ) -# Use OpenAI client as normal - Memora integration happens automatically +# Use OpenAI client as normal - Hindsight integration happens automatically client = OpenAI(api_key="sk-...") response = client.chat.completions.create( @@ -54,10 +54,10 @@ print(response.choices[0].message.content) ### Async Usage ```python -from memora_openai import configure, AsyncOpenAI +from hindsight_openai import configure, AsyncOpenAI configure( - memora_api_url="http://localhost:8000", + hindsight_api_url="http://localhost:8888", agent_id="my-agent", ) @@ -77,13 +77,13 @@ The `configure()` function accepts the following parameters: | Parameter | Type | Default | Description | |-----------|------|---------|-------------| -| `memora_api_url` | str | `"http://localhost:8000"` | URL of your Memora API server | +| `hindsight_api_url` | str | `"http://localhost:8888"` | URL of your Hindsight API server | | `agent_id` | str | `None` | **Required.** Agent identifier for memory operations | -| `api_key` | str | `None` | Optional API key for Memora authentication | -| `store_conversations` | bool | `True` | Store conversations to Memora | +| `api_key` | str | `None` | Optional API key for Hindsight authentication | +| `store_conversations` | bool | `True` | Store conversations to Hindsight | | `inject_memories` | bool | `True` | Inject relevant memories into prompts | | `document_id` | str | `None` | Optional document ID for stored conversations | -| `enabled` | bool | `True` | Master switch to enable/disable Memora integration | +| `enabled` | bool | `True` | Master switch to enable/disable Hindsight integration | ## How It Works @@ -92,7 +92,7 @@ The `configure()` function accepts the following parameters: When `inject_memories=True`, the wrapper: 1. Extracts the user's query from the last message -2. Searches Memora for relevant memories using the query +2. Searches Hindsight for relevant memories using the query 3. Injects the top memories as a system message before the conversation 4. Sends the enhanced conversation to OpenAI @@ -120,7 +120,7 @@ When `store_conversations=True`, the wrapper: 1. Captures the conversation context (recent messages) 2. Captures the assistant's response -3. Stores the complete exchange to Memora asynchronously +3. Stores the complete exchange to Hindsight asynchronously 4. Tags it with context `"openai_conversation"` for filtering This creates a searchable memory of all your AI conversations. @@ -130,22 +130,22 @@ This creates a searchable memory of all your AI conversations. ### Disable for Specific Requests ```python -from memora_openai import configure, OpenAI, reset_config +from hindsight_openai import configure, OpenAI, reset_config # Configure globally -configure(memora_api_url="http://localhost:8000", agent_id="agent-1") +configure(hindsight_api_url="http://localhost:8888", agent_id="agent-1") client = OpenAI(api_key="sk-...") -# Normal request with Memora +# Normal request with Hindsight response1 = client.chat.completions.create(...) # Temporarily disable reset_config() -response2 = client.chat.completions.create(...) # No Memora integration +response2 = client.chat.completions.create(...) # No Hindsight integration # Re-enable -configure(memora_api_url="http://localhost:8000", agent_id="agent-1") +configure(hindsight_api_url="http://localhost:8888", agent_id="agent-1") ``` ### Using Document ID @@ -154,7 +154,7 @@ Group related conversations together using a document ID: ```python configure( - memora_api_url="http://localhost:8000", + hindsight_api_url="http://localhost:8888", agent_id="my-agent", document_id="meeting-2024-01-15", # All conversations tagged with this ID ) @@ -169,7 +169,7 @@ response2 = client.chat.completions.create(...) ### Cleanup ```python -from memora_openai import cleanup_interceptor +from hindsight_openai import cleanup_interceptor # Clean up resources when done await cleanup_interceptor() @@ -180,7 +180,7 @@ await cleanup_interceptor() - Python >= 3.10 - openai >= 1.0.0 - httpx >= 0.23.0 -- A running Memora API server +- A running Hindsight API server ## Development @@ -193,8 +193,8 @@ uv run pytest tests ### Project Structure ``` -memora-openai/ -โ”œโ”€โ”€ src/memora_openai/ +hindsight-integrations/openai/ +โ”œโ”€โ”€ hindsight_openai/ โ”‚ โ”œโ”€โ”€ __init__.py # Main exports โ”‚ โ”œโ”€โ”€ client.py # OpenAI client wrappers โ”‚ โ”œโ”€โ”€ config.py # Global configuration @@ -207,4 +207,4 @@ memora-openai/ ## License -Part of the Memora project. +Part of the Hindsight project. diff --git a/memora-openai/memora_openai/__init__.py b/hindsight-integrations/openai/hindsight_openai/__init__.py similarity index 65% rename from memora-openai/memora_openai/__init__.py rename to hindsight-integrations/openai/hindsight_openai/__init__.py index 3518702610..a11c750626 100644 --- a/memora-openai/memora_openai/__init__.py +++ b/hindsight-integrations/openai/hindsight_openai/__init__.py @@ -1,21 +1,21 @@ -"""Memora-OpenAI: Drop-in replacement for OpenAI client with automatic Memora integration. +"""Hindsight-OpenAI: Drop-in replacement for OpenAI client with automatic Hindsight integration. This package provides a transparent wrapper around the OpenAI Python client that -automatically stores conversations and injects relevant memories from your Memora +automatically stores conversations and injects relevant memories from your Hindsight memory system. Basic usage: - >>> from memora_openai import configure, OpenAI + >>> from hindsight_openai import configure, OpenAI >>> - >>> # Configure Memora integration + >>> # Configure Hindsight integration >>> configure( - ... memora_api_url="http://localhost:8000", + ... hindsight_api_url="http://localhost:8888", ... agent_id="my-agent", ... store_conversations=True, ... inject_memories=True, ... ) >>> - >>> # Use OpenAI client as normal - Memora integration is automatic + >>> # Use OpenAI client as normal - Hindsight integration is automatic >>> client = OpenAI(api_key="sk-...") >>> response = client.chat.completions.create( ... model="gpt-4", @@ -23,10 +23,10 @@ ... ) Async usage: - >>> from memora_openai import configure, AsyncOpenAI + >>> from hindsight_openai import configure, AsyncOpenAI >>> >>> configure( - ... memora_api_url="http://localhost:8000", + ... hindsight_api_url="http://localhost:8888", ... agent_id="my-agent", ... ) >>> @@ -37,14 +37,14 @@ ... ) Configuration options: - - memora_api_url: URL of your Memora API server + - hindsight_api_url: URL of your Hindsight API server - agent_id: Agent identifier for memory operations - - api_key: Optional API key for Memora authentication - - store_conversations: Whether to store conversations to Memora (default: True) + - api_key: Optional API key for Hindsight authentication + - store_conversations: Whether to store conversations to Hindsight (default: True) - inject_memories: Whether to inject relevant memories (default: True) - memory_search_budget: Number of memories to retrieve (default: 10) - context_window: Number of conversation turns to store (default: 10) - - enabled: Master switch to disable Memora integration (default: True) + - enabled: Master switch to disable Hindsight integration (default: True) """ from .client import OpenAI, AsyncOpenAI @@ -53,7 +53,7 @@ get_config, is_configured, reset_config, - MemoraConfig, + HindsightConfig, ) from .interceptor import cleanup_interceptor @@ -67,5 +67,5 @@ "is_configured", "reset_config", "cleanup_interceptor", - "MemoraConfig", + "HindsightConfig", ] diff --git a/memora-openai/memora_openai/client.py b/hindsight-integrations/openai/hindsight_openai/client.py similarity index 84% rename from memora-openai/memora_openai/client.py rename to hindsight-integrations/openai/hindsight_openai/client.py index fe16413e62..7929b823a5 100644 --- a/memora-openai/memora_openai/client.py +++ b/hindsight-integrations/openai/hindsight_openai/client.py @@ -1,4 +1,4 @@ -"""Drop-in replacement for OpenAI client with Memora integration.""" +"""Drop-in replacement for OpenAI client with Hindsight integration.""" import asyncio from typing import Any, Optional, List, Dict @@ -10,14 +10,14 @@ class _CompletionsWrapper: - """Wrapper for chat completions with Memora integration (sync).""" + """Wrapper for chat completions with Hindsight integration (sync).""" def __init__(self, original_completions): """Initialize wrapper with original completions object.""" self._original = original_completions def create(self, *args, **kwargs): - """Create a chat completion with Memora integration.""" + """Create a chat completion with Hindsight integration.""" if not is_configured(): return self._original.create(*args, **kwargs) @@ -35,7 +35,7 @@ def create(self, *args, **kwargs): # If we get here, a loop is already running print( "Warning: Detected running event loop (Jupyter/IPython). " - "Memora features are disabled in sync mode. " + "Hindsight features are disabled in sync mode. " "Please use AsyncOpenAI for full functionality in notebooks." ) return self._original.create(*args, **kwargs) @@ -77,14 +77,14 @@ def __getattr__(self, name): class _AsyncCompletionsWrapper: - """Wrapper for chat completions with Memora integration (async).""" + """Wrapper for chat completions with Hindsight integration (async).""" def __init__(self, original_completions): """Initialize wrapper with original completions object.""" self._original = original_completions async def create(self, *args, **kwargs): - """Create a chat completion with Memora integration.""" + """Create a chat completion with Hindsight integration.""" if not is_configured(): return await self._original.create(*args, **kwargs) @@ -120,12 +120,12 @@ def __getattr__(self, name): class OpenAI(_OpenAI): - """Drop-in replacement for OpenAI client with Memora integration. + """Drop-in replacement for OpenAI client with Hindsight integration. Usage: - >>> from memora_openai import configure, OpenAI + >>> from hindsight_openai import configure, OpenAI >>> configure( - ... memora_api_url="http://localhost:8000", + ... hindsight_api_url="http://localhost:8888", ... agent_id="my-agent", ... store_conversations=True, ... inject_memories=True, @@ -138,19 +138,19 @@ class OpenAI(_OpenAI): """ def __init__(self, *args, **kwargs): - """Initialize OpenAI client with Memora integration.""" + """Initialize OpenAI client with Hindsight integration.""" super().__init__(*args, **kwargs) # Wrap chat completions with our interceptor self.chat.completions = _CompletionsWrapper(self.chat.completions) class AsyncOpenAI(_AsyncOpenAI): - """Drop-in replacement for AsyncOpenAI client with Memora integration. + """Drop-in replacement for AsyncOpenAI client with Hindsight integration. Usage: - >>> from memora_openai import configure, AsyncOpenAI + >>> from hindsight_openai import configure, AsyncOpenAI >>> configure( - ... memora_api_url="http://localhost:8000", + ... hindsight_api_url="http://localhost:8888", ... agent_id="my-agent", ... store_conversations=True, ... inject_memories=True, @@ -163,7 +163,7 @@ class AsyncOpenAI(_AsyncOpenAI): """ def __init__(self, *args, **kwargs): - """Initialize AsyncOpenAI client with Memora integration.""" + """Initialize AsyncOpenAI client with Hindsight integration.""" super().__init__(*args, **kwargs) # Wrap chat completions with our interceptor self.chat.completions = _AsyncCompletionsWrapper(self.chat.completions) diff --git a/memora-openai/memora_openai/config.py b/hindsight-integrations/openai/hindsight_openai/config.py similarity index 59% rename from memora-openai/memora_openai/config.py rename to hindsight-integrations/openai/hindsight_openai/config.py index c446855d54..a18bac8583 100644 --- a/memora-openai/memora_openai/config.py +++ b/hindsight-integrations/openai/hindsight_openai/config.py @@ -1,24 +1,24 @@ -"""Global configuration for Memora-OpenAI integration.""" +"""Global configuration for Hindsight-OpenAI integration.""" from typing import Optional from dataclasses import dataclass, field @dataclass -class MemoraConfig: - """Configuration for Memora integration. +class HindsightConfig: + """Configuration for Hindsight integration. Attributes: - memora_api_url: URL of the Memora API server + hindsight_api_url: URL of the Hindsight API server agent_id: Agent ID for memory operations - api_key: Optional API key for Memora authentication - store_conversations: Whether to store conversations to Memora + api_key: Optional API key for Hindsight authentication + store_conversations: Whether to store conversations to Hindsight inject_memories: Whether to inject relevant memories into prompts document_id: Optional document ID for stored conversations - enabled: Master switch to enable/disable Memora integration + enabled: Master switch to enable/disable Hindsight integration """ - memora_api_url: str = "http://localhost:8000" + hindsight_api_url: str = "http://localhost:8888" agent_id: Optional[str] = None api_key: Optional[str] = None store_conversations: bool = True @@ -28,36 +28,36 @@ class MemoraConfig: # Global configuration instance -_global_config: Optional[MemoraConfig] = None +_global_config: Optional[HindsightConfig] = None def configure( - memora_api_url: str = "http://localhost:8000", + hindsight_api_url: str = "http://localhost:8888", agent_id: Optional[str] = None, api_key: Optional[str] = None, store_conversations: bool = True, inject_memories: bool = True, document_id: Optional[str] = None, enabled: bool = True, -) -> MemoraConfig: - """Configure global Memora integration settings. +) -> HindsightConfig: + """Configure global Hindsight integration settings. Args: - memora_api_url: URL of the Memora API server + hindsight_api_url: URL of the Hindsight API server agent_id: Agent ID for memory operations (required) - api_key: Optional API key for Memora authentication - store_conversations: Whether to store conversations to Memora + api_key: Optional API key for Hindsight authentication + store_conversations: Whether to store conversations to Hindsight inject_memories: Whether to inject relevant memories into prompts document_id: Optional document ID for stored conversations - enabled: Master switch to enable/disable Memora integration + enabled: Master switch to enable/disable Hindsight integration Returns: - The configured MemoraConfig instance + The configured HindsightConfig instance Example: - >>> from memora_openai import configure, OpenAI + >>> from hindsight_openai import configure, OpenAI >>> configure( - ... memora_api_url="http://localhost:8000", + ... hindsight_api_url="http://localhost:8888", ... agent_id="my-agent", ... store_conversations=True, ... inject_memories=True, @@ -67,8 +67,8 @@ def configure( """ global _global_config - _global_config = MemoraConfig( - memora_api_url=memora_api_url, + _global_config = HindsightConfig( + hindsight_api_url=hindsight_api_url, agent_id=agent_id, api_key=api_key, store_conversations=store_conversations, @@ -80,17 +80,17 @@ def configure( return _global_config -def get_config() -> Optional[MemoraConfig]: +def get_config() -> Optional[HindsightConfig]: """Get the current global configuration. Returns: - The current MemoraConfig instance, or None if not configured + The current HindsightConfig instance, or None if not configured """ return _global_config def is_configured() -> bool: - """Check if Memora has been configured. + """Check if Hindsight has been configured. Returns: True if configure() has been called, False otherwise diff --git a/memora-openai/memora_openai/interceptor.py b/hindsight-integrations/openai/hindsight_openai/interceptor.py similarity index 89% rename from memora-openai/memora_openai/interceptor.py rename to hindsight-integrations/openai/hindsight_openai/interceptor.py index 9339400c0e..224b1405c3 100644 --- a/memora-openai/memora_openai/interceptor.py +++ b/hindsight-integrations/openai/hindsight_openai/interceptor.py @@ -3,22 +3,22 @@ from typing import Any, Dict, List, Optional from datetime import datetime -from memora_client import Memora +from hindsight_client import Hindsight -from .config import get_config, MemoraConfig +from .config import get_config, HindsightConfig -class MemoraInterceptor: - """Intercepts OpenAI API calls to integrate with Memora.""" +class HindsightInterceptor: + """Intercepts OpenAI API calls to integrate with Hindsight.""" def __init__(self): - """Initialize the interceptor with a Memora client.""" - self._client: Optional[Memora] = None + """Initialize the interceptor with a Hindsight client.""" + self._client: Optional[Hindsight] = None - def get_client(self, config: MemoraConfig) -> Memora: - """Get or create the Memora client.""" + def get_client(self, config: HindsightConfig) -> Hindsight: + """Get or create the Hindsight client.""" if self._client is None: - self._client = Memora(base_url=config.memora_api_url, timeout=30.0) + self._client = Hindsight(base_url=config.hindsight_api_url, timeout=30.0) return self._client def close(self): @@ -30,7 +30,7 @@ def close(self): async def inject_memories( self, messages: List[Dict[str, Any]], - config: MemoraConfig, + config: HindsightConfig, ) -> List[Dict[str, Any]]: """ Inject relevant memories into messages before sending to OpenAI. @@ -87,10 +87,10 @@ async def store_conversation( self, messages: List[Dict[str, Any]], response: Any, - config: MemoraConfig, + config: HindsightConfig, ) -> None: """ - Store conversation in Memora after receiving response from OpenAI. + Store conversation in Hindsight after receiving response from OpenAI. """ if not config.enabled or not config.store_conversations: return @@ -114,7 +114,7 @@ async def store_conversation( for msg in conversation ] - # Store to Memora (async) + # Store to Hindsight (async) client.put_batch( agent_id=config.agent_id, items=items, @@ -132,7 +132,7 @@ async def process_response( ) -> None: """ Process response after receiving from OpenAI. - Stores the conversation in Memora. + Stores the conversation in Hindsight. """ config = get_config() await self.store_conversation(messages, response, config) @@ -233,10 +233,10 @@ def _extract_conversation_context( # Global interceptor instance -_interceptor = MemoraInterceptor() +_interceptor = HindsightInterceptor() -def get_interceptor() -> MemoraInterceptor: +def get_interceptor() -> HindsightInterceptor: """Get the global interceptor instance.""" return _interceptor diff --git a/memora-openai/pyproject.toml b/hindsight-integrations/openai/pyproject.toml similarity index 74% rename from memora-openai/pyproject.toml rename to hindsight-integrations/openai/pyproject.toml index dac971ade1..cd58e86995 100644 --- a/memora-openai/pyproject.toml +++ b/hindsight-integrations/openai/pyproject.toml @@ -1,16 +1,16 @@ [project] -name = "memora-openai" +name = "hindsight-openai" version = "0.1.0" -description = "Drop-in replacement for OpenAI client with automatic Memora integration" +description = "Drop-in replacement for OpenAI client with automatic Hindsight integration" readme = "README.md" requires-python = ">=3.10" dependencies = [ "openai>=1.0.0", - "memora-client", + "hindsight-client", ] [tool.uv.sources] -memora-client = { workspace = true } +hindsight-client = { path = "../../hindsight-clients/python" } [project.optional-dependencies] dev = [ @@ -24,7 +24,7 @@ requires = ["hatchling"] build-backend = "hatchling.build" [tool.hatch.build.targets.wheel] -packages = ["memora_openai"] +packages = ["hindsight_openai"] [tool.pytest.ini_options] asyncio_mode = "auto" diff --git a/memora-openai/tests/test_client.py b/hindsight-integrations/openai/tests/test_client.py similarity index 82% rename from memora-openai/tests/test_client.py rename to hindsight-integrations/openai/tests/test_client.py index ab641aa765..595ae240f6 100644 --- a/memora-openai/tests/test_client.py +++ b/hindsight-integrations/openai/tests/test_client.py @@ -1,8 +1,8 @@ -"""Tests for Memora-OpenAI client wrapper.""" +"""Tests for Hindsight-OpenAI client wrapper.""" import os import pytest -from memora_openai import ( +from hindsight_openai import ( configure, reset_config, OpenAI, @@ -28,9 +28,9 @@ def groq_api_key(): @pytest.fixture -def memora_api_url(): - """Get Memora API URL from environment.""" - return os.getenv("MEMORA_API_URL", "http://localhost:8000") +def hindsight_api_url(): + """Get Hindsight API URL from environment.""" + return os.getenv("HINDSIGHT_API_URL", "http://localhost:8888") class TestConfiguration: @@ -39,11 +39,11 @@ class TestConfiguration: def test_configure_basic(self): """Test basic configuration.""" config = configure( - memora_api_url="http://test:8000", + hindsight_api_url="http://test:8888", agent_id="test-agent", ) - assert config.memora_api_url == "http://test:8000" + assert config.hindsight_api_url == "http://test:8888" assert config.agent_id == "test-agent" assert config.store_conversations is True assert config.inject_memories is True @@ -52,7 +52,7 @@ def test_configure_basic(self): def test_configure_custom_options(self): """Test configuration with custom options.""" config = configure( - memora_api_url="http://test:8000", + hindsight_api_url="http://test:8888", agent_id="test-agent", store_conversations=False, inject_memories=False, @@ -65,7 +65,7 @@ def test_configure_custom_options(self): def test_reset_config(self): """Test resetting configuration.""" - configure(memora_api_url="http://test:8000", agent_id="test-agent") + configure(hindsight_api_url="http://test:8888", agent_id="test-agent") assert is_configured() reset_config() @@ -77,7 +77,7 @@ class TestSyncClient: def test_client_creation(self, groq_api_key): """Test that client can be created.""" - configure(memora_api_url="http://test:8000", agent_id="test-agent") + configure(hindsight_api_url="http://test:8888", agent_id="test-agent") client = OpenAI( api_key=groq_api_key, @@ -87,7 +87,7 @@ def test_client_creation(self, groq_api_key): assert hasattr(client.chat.completions, "_original") def test_chat_completion_without_config(self, groq_api_key): - """Test that chat completion works without Memora configuration.""" + """Test that chat completion works without Hindsight configuration.""" reset_config() client = OpenAI( @@ -105,10 +105,10 @@ def test_chat_completion_without_config(self, groq_api_key): assert len(response.choices) > 0 assert response.choices[0].message.content is not None - def test_wrapper_passthrough(self, groq_api_key, memora_api_url): + def test_wrapper_passthrough(self, groq_api_key, hindsight_api_url): """Test that wrapper passes through when features disabled.""" configure( - memora_api_url=memora_api_url, + hindsight_api_url=hindsight_api_url, agent_id="test-sync-passthrough", inject_memories=False, store_conversations=False, @@ -134,7 +134,7 @@ class TestAsyncClient: def test_client_creation(self, groq_api_key): """Test that async client can be created.""" - configure(memora_api_url="http://test:8000", agent_id="test-agent") + configure(hindsight_api_url="http://test:8888", agent_id="test-agent") client = AsyncOpenAI( api_key=groq_api_key, @@ -144,7 +144,7 @@ def test_client_creation(self, groq_api_key): assert hasattr(client.chat.completions, "_original") async def test_chat_completion_without_config(self, groq_api_key): - """Test that async chat completion works without Memora configuration.""" + """Test that async chat completion works without Hindsight configuration.""" reset_config() client = AsyncOpenAI( @@ -162,10 +162,10 @@ async def test_chat_completion_without_config(self, groq_api_key): assert len(response.choices) > 0 assert response.choices[0].message.content is not None - async def test_wrapper_passthrough(self, groq_api_key, memora_api_url): + async def test_wrapper_passthrough(self, groq_api_key, hindsight_api_url): """Test that async wrapper passes through when features disabled.""" configure( - memora_api_url=memora_api_url, + hindsight_api_url=hindsight_api_url, agent_id="test-async-passthrough", inject_memories=False, store_conversations=False, @@ -191,9 +191,9 @@ class TestInterceptor: def test_extract_user_query_simple(self): """Test extracting user query from simple messages.""" - from memora_openai.interceptor import MemoraInterceptor + from hindsight_openai.interceptor import HindsightInterceptor - interceptor = MemoraInterceptor() + interceptor = HindsightInterceptor() messages = [ {"role": "system", "content": "You are a helpful assistant."}, {"role": "user", "content": "What is Python?"}, @@ -204,9 +204,9 @@ def test_extract_user_query_simple(self): def test_extract_user_query_structured(self): """Test extracting user query from structured content.""" - from memora_openai.interceptor import MemoraInterceptor + from hindsight_openai.interceptor import HindsightInterceptor - interceptor = MemoraInterceptor() + interceptor = HindsightInterceptor() messages = [ { "role": "user", @@ -222,10 +222,10 @@ def test_extract_user_query_structured(self): def test_extract_conversation_context(self): """Test extracting conversation context.""" - from memora_openai.interceptor import MemoraInterceptor + from hindsight_openai.interceptor import HindsightInterceptor from unittest.mock import Mock - interceptor = MemoraInterceptor() + interceptor = HindsightInterceptor() messages = [ {"role": "user", "content": "Hello"}, {"role": "assistant", "content": "Hi! How can I help?"}, @@ -247,9 +247,9 @@ def test_extract_conversation_context(self): def test_format_memories(self): """Test formatting memories.""" - from memora_openai.interceptor import MemoraInterceptor + from hindsight_openai.interceptor import HindsightInterceptor - interceptor = MemoraInterceptor() + interceptor = HindsightInterceptor() memories = [ { "text": "User likes Python", diff --git a/hindsight-integrations/openai/tutorial.ipynb b/hindsight-integrations/openai/tutorial.ipynb new file mode 100644 index 0000000000..579730670b --- /dev/null +++ b/hindsight-integrations/openai/tutorial.ipynb @@ -0,0 +1,163 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": "# Hindsight-OpenAI Tutorial\n\n**A drop-in replacement for the OpenAI Python client with automatic memory integration**\n\n## What is Hindsight-OpenAI?\n\n`hindsight-openai` is a transparent wrapper around the official OpenAI Python client that automatically:\n\n- ๐Ÿง  **Injects relevant memories** from your Hindsight system into conversations\n- ๐Ÿ’พ **Stores conversation history** to Hindsight for future retrieval \n- ๐Ÿ”„ **Works seamlessly** with existing OpenAI code (just change the import)\n- โšก **Supports both sync and async** clients\n\n## Why Use It?\n\n### The Problem\n\nAI assistants typically have no memory of previous conversations. Each interaction starts fresh, requiring you to:\n- Repeat context manually\n- Copy-paste relevant information\n- Build custom RAG pipelines\n- Manage conversation history yourself\n\n### The Solution\n\nHindsight-OpenAI gives your AI **automatic long-term memory**:\n- Remembers past conversations\n- Recalls user preferences and facts\n- Maintains context across sessions\n- Zero code changes to your existing OpenAI usage\n\n## Prerequisites\n\n1. **Hindsight API server running** (see main Hindsight README)\n2. **OpenAI API key** or compatible API (Groq, OpenRouter, etc.)\n3. **Python >= 3.10**" + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": "## Setup\n\nFirst, let's set up our environment and configure Hindsight integration:" + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "jupyter": { + "is_executing": true + } + }, + "outputs": [], + "source": "import os\nfrom hindsight_openai import configure, AsyncOpenAI\n\n# Set your API keys\n# Option 1: Use Groq (fast and free)\nGROQ_API_KEY = os.getenv(\"GROQ_API_KEY\", \"your-groq-api-key\")\nif not GROQ_API_KEY:\n raise (\"GROQ_API_KEY not set\") \n\n# Option 2: Use OpenAI\n# OPENAI_API_KEY = os.getenv(\"OPENAI_API_KEY\", \"sk-...\")\n\n# Configure Hindsight integration\nconfigure(\n hindsight_api_url=\"http://localhost:8888\", # Your Hindsight API server\n agent_id=\"tutorial-user\", # Unique ID for this user/agent\n store_conversations=True, # Auto-save conversations\n inject_memories=True, # Auto-inject relevant context\n)\n\nprint(\"โœ“ Hindsight configured successfully!\")\nprint(\"\")\nprint(\"NOTE: This tutorial uses AsyncOpenAI which works perfectly in Jupyter notebooks.\")\nprint(\"For regular Python scripts, you can use the sync OpenAI client instead.\")" + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": "## Example 1: Basic Usage (No Changes Needed!)\n\nUse the OpenAI client exactly as you normally would. Hindsight works transparently in the background." + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": "# Create client (using Groq's OpenAI-compatible API)\nclient = AsyncOpenAI(\n api_key=GROQ_API_KEY,\n base_url=\"https://api.groq.com/openai/v1\",\n)\n\n# First conversation - establish some facts\nprint(\"=== First Conversation ===\")\nresponse = await client.chat.completions.create(\n model=\"llama-3.1-8b-instant\",\n messages=[\n {\"role\": \"user\", \"content\": \"My name is Alice and I love Python programming!\"}\n ],\n)\n\nprint(f\"Assistant: {response.choices[0].message.content}\\n\")\nprint(\"โ†’ This conversation is now stored in Hindsight!\")" + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": "## Example 2: Memory Injection in Action\n\nNow ask a question that requires remembering the previous conversation:" + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": "print(\"=== Second Conversation (with memory) ===\")\nresponse = await client.chat.completions.create(\n model=\"llama-3.1-8b-instant\",\n messages=[\n {\"role\": \"user\", \"content\": \"What's my name and what do I like?\"}\n ],\n)\n\nprint(f\"Assistant: {response.choices[0].message.content}\\n\")\nprint(\"โ†’ Hindsight automatically injected relevant memories before this request!\")\nprint(\"โ†’ The AI knew your name and preferences without you repeating them.\")" + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": "## How It Works\n\nBehind the scenes, Hindsight-OpenAI:\n\n### 1. **Memory Storage**\nAfter each API call:\n- Captures the full conversation context\n- Stores it in Hindsight's semantic memory system\n- Indexes it for fast retrieval\n\n### 2. **Memory Injection**\nBefore each API call:\n- Extracts the user's query\n- Searches Hindsight for relevant past conversations\n- Injects top memories as a system message\n\n### What Gets Sent to OpenAI\n\nWithout Hindsight:\n```python\nmessages = [\n {\"role\": \"user\", \"content\": \"What's my name?\"}\n]\n```\n\nWith Hindsight (automatic):\n```python\nmessages = [\n {\n \"role\": \"system\",\n \"content\": \"Relevant context from your memory:\\n\\n1. User's name is Alice\\n (Date: 2024-11-18)\\n (Type: world)\"\n },\n {\"role\": \"user\", \"content\": \"What's my name?\"}\n]\n```" + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Example 3: Multi-Turn Conversations\n", + "\n", + "Build up context over multiple interactions:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Conversation 1: Share a preference\n", + "print(\"=== Conversation 1: Sharing preferences ===\")\n", + "response = await client.chat.completions.create(\n", + " model=\"llama-3.1-8b-instant\",\n", + " messages=[\n", + " {\"role\": \"user\", \"content\": \"I'm working on a machine learning project using PyTorch.\"}\n", + " ],\n", + ")\n", + "print(f\"Assistant: {response.choices[0].message.content}\\n\")\n", + "\n", + "# Conversation 2: Different topic\n", + "print(\"=== Conversation 2: Different topic ===\")\n", + "response = await client.chat.completions.create(\n", + " model=\"llama-3.1-8b-instant\",\n", + " messages=[\n", + " {\"role\": \"user\", \"content\": \"I prefer functional programming over OOP.\"}\n", + " ],\n", + ")\n", + "print(f\"Assistant: {response.choices[0].message.content}\\n\")\n", + "\n", + "# Conversation 3: Ask for recommendations\n", + "print(\"=== Conversation 3: Getting personalized advice ===\")\n", + "response = await client.chat.completions.create(\n", + " model=\"llama-3.1-8b-instant\",\n", + " messages=[\n", + " {\"role\": \"user\", \"content\": \"Can you recommend a good book for me based on what you know?\"}\n", + " ],\n", + ")\n", + "print(f\"Assistant: {response.choices[0].message.content}\\n\")\n", + "print(\"โ†’ The AI used your programming interests and preferences to make recommendations!\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": "## Example 4: Document Grouping\n\nGroup related conversations using `document_id`:" + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": "from hindsight_openai import configure\n\n# Configure with document ID for a specific project\nconfigure(\n hindsight_api_url=\"http://localhost:8888\",\n agent_id=\"tutorial-user\",\n document_id=\"ml-project-2024\", # All conversations tagged with this ID\n)\n\n# All these conversations will be grouped together\nconversations = [\n \"I'm using ResNet for image classification\",\n \"My dataset has 10,000 images\",\n \"Training accuracy is stuck at 65%\",\n]\n\nfor msg in conversations:\n response = await client.chat.completions.create(\n model=\"llama-3.1-8b-instant\",\n messages=[{\"role\": \"user\", \"content\": msg}],\n )\n print(f\"User: {msg}\")\n print(f\"Assistant: {response.choices[0].message.content}\\n\")\n\nprint(\"โ†’ All these conversations are grouped under document 'ml-project-2024'\")" + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": "## Example 5: Async Support\n\nWorks perfectly with AsyncOpenAI for high-throughput applications:" + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": "from hindsight_openai import AsyncOpenAI\nimport asyncio\n\nasync def async_example():\n # Create async client\n async_client = AsyncOpenAI(\n api_key=GROQ_API_KEY,\n base_url=\"https://api.groq.com/openai/v1\",\n )\n \n # Store a fact\n print(\"=== Storing fact ===\")\n response = await async_client.chat.completions.create(\n model=\"llama-3.1-8b-instant\",\n messages=[{\"role\": \"user\", \"content\": \"My favorite color is blue.\"}],\n )\n print(f\"Assistant: {response.choices[0].message.content}\\n\")\n \n # Query with memory\n print(\"=== Querying with memory ===\")\n response = await async_client.chat.completions.create(\n model=\"llama-3.1-8b-instant\",\n messages=[{\"role\": \"user\", \"content\": \"What's my favorite color?\"}],\n )\n print(f\"Assistant: {response.choices[0].message.content}\\n\")\n\n# Run async example\nawait async_example()\nprint(\"โ†’ Async operations work seamlessly with Hindsight!\")" + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": "## Configuration Options\n\nFine-tune Hindsight's behavior:" + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": "from hindsight_openai import configure\n\n# Full configuration example\nconfigure(\n hindsight_api_url=\"http://localhost:8888\", # Hindsight API URL\n agent_id=\"my-agent\", # Agent identifier (required)\n api_key=None, # Optional Hindsight API key\n \n # Features\n store_conversations=True, # Store conversations automatically\n inject_memories=True, # Inject memories automatically\n \n # Organization\n document_id=\"session-123\", # Optional document grouping\n \n # Control\n enabled=True, # Master on/off switch\n)\n\nprint(\"Configuration options explained:\")\nprint(\"- store_conversations: Automatically save conversations to Hindsight\")\nprint(\"- inject_memories: Automatically retrieve and inject relevant context\")\nprint(\"- document_id: Group related conversations together\")\nprint(\"- enabled=False: Disable Hindsight without changing code\")" + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": "## Use Cases\n\n### 1. **Personal AI Assistant**\n- Remembers your preferences, work history, and interests\n- Provides personalized recommendations\n- Maintains context across days/weeks\n\n### 2. **Customer Support Chatbot**\n- Recalls previous support tickets\n- Knows customer preferences and history\n- Provides consistent, context-aware responses\n\n### 3. **Research Assistant**\n- Remembers documents you've discussed\n- Connects related topics from different sessions\n- Builds knowledge over time\n\n### 4. **Code Review Tool**\n- Remembers project architecture decisions\n- Recalls past code review comments\n- Maintains consistency across reviews\n\n## Benefits Summary\n\nโœ… **Zero Code Changes** - Drop-in replacement for OpenAI client \nโœ… **Automatic Context** - No manual RAG pipeline needed \nโœ… **Long-term Memory** - Conversations persist across sessions \nโœ… **Smart Retrieval** - Semantic search finds relevant context \nโœ… **Both Sync/Async** - Works with any OpenAI client pattern \nโœ… **Configurable** - Fine-tune behavior to your needs \nโœ… **Transparent** - Original OpenAI responses unchanged \n\n## Next Steps\n\n- **Explore Hindsight API**: Check out the main Hindsight README for advanced features\n- **Customize Search**: Tune `memory_search_budget` for your use case\n- **Use Document IDs**: Organize conversations by project/session\n- **Try Different Models**: Works with OpenAI, Groq, Ollama, and more\n\n## Resources\n\n- [Hindsight Main README](../README.md) - Core memory system docs\n- [Hindsight-OpenAI README](README.md) - Package documentation\n- [OpenAI API Docs](https://platform.openai.com/docs/api-reference) - Original API reference" + } + ], + "metadata": { + "kernelspec": { + 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@@ -0,0 +1,48 @@ +# hindsight-all + +All-in-one package for Hindsight - Semantic memory system with personality-driven thinking for AI agents. + +## Quick Start + +```python +from hindsight import start_server, HindsightClient + +# Start server with embedded PostgreSQL +server = start_server( + llm_provider="groq", + llm_api_key="your-api-key", + llm_model="llama-3.3-70b-versatile" +) + +# Create client +client = HindsightClient(base_url=server.url) + +# Store memories +client.put(agent_id="assistant", content="User prefers Python for data analysis") + +# Search memories +results = client.search(agent_id="assistant", query="programming preferences") + +# Generate contextual response +response = client.think(agent_id="assistant", query="What languages should I recommend?") + +# Stop server when done +server.stop() +``` + +## Using Context Manager + +```python +from hindsight import HindsightServer, HindsightClient + +with HindsightServer(llm_provider="groq", llm_api_key="...") as server: + client = HindsightClient(base_url=server.url) + # ... use client ... +# Server automatically stops +``` + +## Installation + +```bash +pip install hindsight-all +``` diff --git a/hindsight/hindsight/__init__.py b/hindsight/hindsight/__init__.py new file mode 100644 index 0000000000..2f42540504 --- /dev/null +++ b/hindsight/hindsight/__init__.py @@ -0,0 +1,53 @@ +""" +Hindsight - All-in-one semantic memory system for AI agents. + +This package provides a simple way to run Hindsight locally with embedded PostgreSQL. + +Example: + ```python + from hindsight import start_server, HindsightClient + + # Start server with embedded PostgreSQL (pg0) + server = start_server( + llm_provider="groq", + llm_api_key="your-api-key", + llm_model="llama-3.3-70b-versatile" + ) + + # Create client + client = HindsightClient(base_url=server.url) + + # Store memories + client.put(agent_id="assistant", content="User prefers Python for data analysis") + + # Search memories + results = client.search(agent_id="assistant", query="programming preferences") + + # Generate contextual response + response = client.think(agent_id="assistant", query="What languages should I recommend?") + + # Stop server when done + server.stop() + ``` + +Using context manager: + ```python + from hindsight import HindsightServer, HindsightClient + + with HindsightServer(llm_provider="groq", llm_api_key="...") as server: + client = HindsightClient(base_url=server.url) + # ... use client ... + # Server automatically stops + ``` +""" + +from .server import Server as HindsightServer, start_server + +# Re-export Client from hindsight-client +from hindsight_client import Hindsight as HindsightClient + +__all__ = [ + "HindsightServer", + "start_server", + "HindsightClient", +] diff --git a/hindsight/hindsight/cli.py b/hindsight/hindsight/cli.py new file mode 100644 index 0000000000..5bfde17c10 --- /dev/null +++ b/hindsight/hindsight/cli.py @@ -0,0 +1,146 @@ +""" +Command-line interface for Hindsight API. + +Run the server with: + hindsight-api + +Stop with Ctrl+C. +""" +import argparse +import asyncio +import atexit +import os +import signal +import sys +from typing import Optional + +import uvicorn + +from hindsight_api import MemoryEngine +from hindsight_api.api import create_app + + +# Disable tokenizers parallelism to avoid warnings +os.environ["TOKENIZERS_PARALLELISM"] = "false" + +# Global reference for cleanup +_memory: Optional[MemoryEngine] = None + + +def _cleanup(): + """Synchronous cleanup function to stop resources on exit.""" + global _memory + if _memory is not None and _memory._pg0 is not None: + try: + loop = asyncio.new_event_loop() + loop.run_until_complete(_memory._pg0.stop()) + loop.close() + print("\npg0 stopped.") + except Exception as e: + print(f"\nError stopping pg0: {e}") + + +def _signal_handler(signum, frame): + """Handle SIGINT/SIGTERM to ensure cleanup.""" + print(f"\nReceived signal {signum}, shutting down...") + _cleanup() + sys.exit(0) + + +def main(): + """Main entry point for the CLI.""" + global _memory + + parser = argparse.ArgumentParser( + prog="hindsight-api", + description="Hindsight - Semantic memory system for AI agents. Press Ctrl+C to stop.", + ) + parser.add_argument( + "--host", default="0.0.0.0", + help="Host to bind to (default: 0.0.0.0)" + ) + parser.add_argument( + "--port", type=int, default=8888, + help="Port to bind to (default: 8888)" + ) + parser.add_argument( + "--mcp", action="store_true", + help="Enable MCP server at /mcp" + ) + parser.add_argument( + "--reload", action="store_true", + help="Enable auto-reload on code changes" + ) + parser.add_argument( + "--workers", type=int, default=1, + help="Number of worker processes (default: 1)" + ) + parser.add_argument( + "--log-level", default="info", + choices=["critical", "error", "warning", "info", "debug", "trace"], + help="Log level (default: info)" + ) + parser.add_argument( + "--access-log", action="store_true", + help="Enable access log" + ) + + args = parser.parse_args() + + # Register cleanup handlers + atexit.register(_cleanup) + signal.signal(signal.SIGINT, _signal_handler) + signal.signal(signal.SIGTERM, _signal_handler) + + # Get configuration from environment variables + db_url = os.getenv("HINDSIGHT_API_DATABASE_URL", "pg0") + llm_provider = os.getenv("HINDSIGHT_API_LLM_PROVIDER", "groq") + llm_api_key = os.getenv("HINDSIGHT_API_LLM_API_KEY", "") + llm_model = os.getenv("HINDSIGHT_API_LLM_MODEL", "openai/gpt-oss-20b") + llm_base_url = os.getenv("HINDSIGHT_API_LLM_BASE_URL") or None + + # Create MemoryEngine + _memory = MemoryEngine( + db_url=db_url, + memory_llm_provider=llm_provider, + memory_llm_api_key=llm_api_key, + memory_llm_model=llm_model, + memory_llm_base_url=llm_base_url, + ) + + # Create FastAPI app + app = create_app( + memory=_memory, + http_api_enabled=True, + mcp_api_enabled=args.mcp, + mcp_mount_path="/mcp", + run_migrations=True, + initialize_memory=True, + ) + + # Prepare uvicorn config + uvicorn_config = { + "app": app, + "host": args.host, + "port": args.port, + "log_level": args.log_level, + "access_log": args.access_log, + } + + if args.reload: + uvicorn_config["reload"] = True + if args.workers > 1: + uvicorn_config["workers"] = args.workers + + print(f"\nStarting Hindsight API...") + print(f" URL: http://{args.host}:{args.port}") + print(f" Database: {db_url}") + print(f" LLM Provider: {llm_provider}") + print(f" MCP: {'enabled' if args.mcp else 'disabled'}") + print() + + uvicorn.run(**uvicorn_config) + + +if __name__ == "__main__": + main() diff --git a/hindsight/hindsight/server.py b/hindsight/hindsight/server.py new file mode 100644 index 0000000000..fd579d0cd2 --- /dev/null +++ b/hindsight/hindsight/server.py @@ -0,0 +1,281 @@ +""" +Server module for running Hindsight in a background thread. + +Provides a simple way to start and stop the Hindsight HTTP API server +without blocking the main thread. +""" +import asyncio +import logging +import socket +import threading +import time +from typing import Optional + +import uvicorn +from uvicorn import Config + +from hindsight_api import MemoryEngine +from hindsight_api.api import create_app + +logger = logging.getLogger(__name__) + + +def _find_free_port() -> int: + """Find a free port on localhost.""" + with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s: + s.bind(("", 0)) + s.listen(1) + port = s.getsockname()[1] + return port + + +class Server: + """ + Hindsight server that runs in a background thread. + + Example: + ```python + from hindsight import Server + + server = Server( + db_url="pg0", + llm_provider="groq", + llm_api_key="your-api-key", + llm_model="llama-3.3-70b-versatile" + ) + server.start() + + print(f"Server running at {server.url}") + + # Use the server... + + server.stop() + ``` + """ + + def __init__( + self, + db_url: str = "pg0", + llm_provider: str = "groq", + llm_api_key: str = "", + llm_model: str = "llama-3.3-70b-versatile", + llm_base_url: Optional[str] = None, + host: str = "127.0.0.1", + port: Optional[int] = None, + mcp_enabled: bool = False, + log_level: str = "warning", + ): + """ + Initialize the Hindsight server. + + Args: + db_url: Database URL. Use "pg0" for embedded PostgreSQL. + llm_provider: LLM provider ("groq", "openai", "ollama") + llm_api_key: API key for the LLM provider + llm_model: Model name to use + llm_base_url: Optional custom base URL for LLM API + host: Host to bind to (default: 127.0.0.1) + port: Port to bind to (default: auto-select free port) + mcp_enabled: Whether to enable MCP server + log_level: Uvicorn log level (default: warning) + """ + self.db_url = db_url + self.llm_provider = llm_provider + self.llm_api_key = llm_api_key + self.llm_model = llm_model + self.llm_base_url = llm_base_url + self.host = host + self.port = port or _find_free_port() + self.mcp_enabled = mcp_enabled + self.log_level = log_level + + self._memory: Optional[MemoryEngine] = None + self._server: Optional[uvicorn.Server] = None + self._thread: Optional[threading.Thread] = None + self._started = threading.Event() + self._stopped = threading.Event() + + @property + def url(self) -> str: + """Get the server URL.""" + return f"http://{self.host}:{self.port}" + + def _run_server(self): + """Run the server in a background thread.""" + loop = asyncio.new_event_loop() + asyncio.set_event_loop(loop) + + try: + # Create MemoryEngine + self._memory = MemoryEngine( + db_url=self.db_url, + memory_llm_provider=self.llm_provider, + memory_llm_api_key=self.llm_api_key, + memory_llm_model=self.llm_model, + memory_llm_base_url=self.llm_base_url, + ) + + # Create FastAPI app + app = create_app( + memory=self._memory, + mcp_api_enabled=self.mcp_enabled, + run_migrations=True, + initialize_memory=True, + ) + + # Create uvicorn config and server + config = Config( + app=app, + host=self.host, + port=self.port, + log_level=self.log_level, + loop="asyncio", + ) + self._server = uvicorn.Server(config) + + # Signal that we're starting + self._started.set() + + # Run the server + loop.run_until_complete(self._server.serve()) + + except Exception as e: + logger.error(f"Server error: {e}") + raise + finally: + # Cleanup + if self._memory: + loop.run_until_complete(self._memory.close()) + loop.close() + self._stopped.set() + + def start(self, timeout: float = 30.0) -> "Server": + """ + Start the server in a background thread. + + Args: + timeout: Maximum time to wait for server to start (seconds) + + Returns: + self (for chaining) + + Raises: + RuntimeError: If server fails to start within timeout + """ + if self._thread is not None and self._thread.is_alive(): + raise RuntimeError("Server is already running") + + self._started.clear() + self._stopped.clear() + + self._thread = threading.Thread(target=self._run_server, daemon=True) + self._thread.start() + + # Wait for server to start + self._started.wait(timeout=timeout) + + # Give uvicorn a moment to actually bind to the port + start_time = time.time() + while time.time() - start_time < timeout: + try: + with socket.create_connection((self.host, self.port), timeout=1): + logger.info(f"Hindsight server started at {self.url}") + return self + except (ConnectionRefusedError, socket.timeout, OSError): + time.sleep(0.1) + + raise RuntimeError(f"Server failed to start within {timeout} seconds") + + def stop(self, timeout: float = 10.0) -> None: + """ + Stop the server. + + Args: + timeout: Maximum time to wait for server to stop (seconds) + """ + if self._server is None: + return + + # Signal uvicorn to shutdown + self._server.should_exit = True + + # Wait for thread to finish + if self._thread is not None: + self._thread.join(timeout=timeout) + if self._thread.is_alive(): + logger.warning("Server thread did not stop cleanly") + + self._server = None + self._thread = None + logger.info("Hindsight server stopped") + + def __enter__(self) -> "Server": + """Context manager entry.""" + return self.start() + + def __exit__(self, exc_type, exc_val, exc_tb) -> None: + """Context manager exit.""" + self.stop() + + +def start_server( + db_url: str = "pg0", + llm_provider: str = "groq", + llm_api_key: str = "", + llm_model: str = "llama-3.3-70b-versatile", + llm_base_url: Optional[str] = None, + host: str = "127.0.0.1", + port: Optional[int] = None, + mcp_enabled: bool = False, + log_level: str = "warning", + timeout: float = 30.0, +) -> Server: + """ + Start a Hindsight server in a background thread. + + This is a convenience function that creates and starts a Server instance. + + Args: + db_url: Database URL. Use "pg0" for embedded PostgreSQL. + llm_provider: LLM provider ("groq", "openai", "ollama") + llm_api_key: API key for the LLM provider + llm_model: Model name to use + llm_base_url: Optional custom base URL for LLM API + host: Host to bind to (default: 127.0.0.1) + port: Port to bind to (default: auto-select free port) + mcp_enabled: Whether to enable MCP server + log_level: Uvicorn log level (default: warning) + timeout: Maximum time to wait for server to start (seconds) + + Returns: + Running Server instance + + Example: + ```python + from hindsight import start_server, Client + + server = start_server( + db_url="pg0", + llm_provider="groq", + llm_api_key="your-api-key", + llm_model="llama-3.3-70b-versatile" + ) + + client = Client(base_url=server.url) + client.put(agent_id="assistant", content="User likes Python") + + server.stop() + ``` + """ + server = Server( + db_url=db_url, + llm_provider=llm_provider, + llm_api_key=llm_api_key, + llm_model=llm_model, + llm_base_url=llm_base_url, + host=host, + port=port, + mcp_enabled=mcp_enabled, + log_level=log_level, + ) + return server.start(timeout=timeout) diff --git a/hindsight/pyproject.toml b/hindsight/pyproject.toml new file mode 100644 index 0000000000..e409b3a8f5 --- /dev/null +++ b/hindsight/pyproject.toml @@ -0,0 +1,34 @@ +[build-system] +requires = ["hatchling"] +build-backend = "hatchling.build" + +[project] +name = "hindsight-all" +version = "0.0.7" +description = "All-in-one package for Hindsight - Semantic memory system with personality-driven thinking" +readme = "README.md" +requires-python = ">=3.11" +dependencies = [ + "hindsight-api>=0.0.7", + "hindsight-client>=0.0.7", +] + +[tool.uv.sources] +hindsight-api = { workspace = true } +hindsight-client = { workspace = true } + +[project.optional-dependencies] +test = [ + "pytest>=7.0.0", + "pytest-asyncio>=0.21.0", +] + +[project.scripts] +hindsight-api = "hindsight.cli:main" + +[tool.hatch.build.targets.wheel] +packages = ["hindsight"] + +[tool.pytest.ini_options] +asyncio_mode = "auto" +asyncio_default_fixture_loop_scope = "function" diff --git a/memora-clients/python/memora_client_api/__init__.py b/memora-clients/python/memora_client_api/__init__.py deleted file mode 100644 index 2088a20590..0000000000 --- a/memora-clients/python/memora_client_api/__init__.py +++ /dev/null @@ -1,108 +0,0 @@ -# coding: utf-8 - -# flake8: noqa - -""" - Agent Memory API - - A temporal-semantic memory system for AI agents that stores, retrieves, and reasons over memories. ## Features * **Batch Memory Storage**: Store multiple memories efficiently with automatic fact extraction * **Semantic Search**: Find relevant memories using natural language queries * **Fact Type Filtering**: Search across world facts, agent actions, and opinions separately * **Think Endpoint**: Generate contextual answers based on agent identity and memories * **Graph Visualization**: Interactive memory graph visualization * **Document Tracking**: Track and manage memory documents with upsert support ## Architecture The system uses: - **Temporal Links**: Connect memories that are close in time - **Semantic Links**: Connect semantically similar memories - **Entity Links**: Connect memories that mention the same entities - **Spreading Activation**: Intelligent traversal for memory retrieval - - The version of the OpenAPI document: 1.0.0 - Generated by OpenAPI Generator (https://openapi-generator.tech) - - Do not edit the class manually. -""" # noqa: E501 - - -__version__ = "0.0.7" - -# Define package exports -__all__ = [ - "AgentManagementApi", - "DocumentsApi", - "MemoryOperationsApi", - "ReasoningApi", - "VisualizationApi", - "ApiResponse", - "ApiClient", - "Configuration", - "OpenApiException", - "ApiTypeError", - "ApiValueError", - "ApiKeyError", - "ApiAttributeError", - "ApiException", - "AddBackgroundRequest", - "AgentListItem", - "AgentListResponse", - "AgentProfileResponse", - "BackgroundResponse", - "BatchPutAsyncResponse", - "BatchPutRequest", - "BatchPutResponse", - "CreateAgentRequest", - "DeleteResponse", - "DocumentResponse", - "GraphDataResponse", - "HTTPValidationError", - "ListDocumentsResponse", - "ListMemoryUnitsResponse", - "MemoryItem", - "PersonalityTraits", - "SearchRequest", - "SearchResponse", - "SearchResult", - "ThinkFact", - "ThinkRequest", - "ThinkResponse", - "UpdatePersonalityRequest", - "ValidationError", - "ValidationErrorLocInner", -] - -# import apis into sdk package -from memora_client_api.api.agent_management_api import AgentManagementApi as AgentManagementApi -from memora_client_api.api.documents_api import DocumentsApi as DocumentsApi -from memora_client_api.api.memory_operations_api import MemoryOperationsApi as MemoryOperationsApi -from memora_client_api.api.reasoning_api import ReasoningApi as ReasoningApi -from memora_client_api.api.visualization_api import VisualizationApi as VisualizationApi - -# import ApiClient -from memora_client_api.api_response import ApiResponse as ApiResponse -from memora_client_api.api_client import ApiClient as ApiClient -from memora_client_api.configuration import Configuration as Configuration -from memora_client_api.exceptions import OpenApiException as OpenApiException -from memora_client_api.exceptions import ApiTypeError as ApiTypeError -from memora_client_api.exceptions import ApiValueError as ApiValueError -from memora_client_api.exceptions import ApiKeyError as ApiKeyError -from memora_client_api.exceptions import ApiAttributeError as ApiAttributeError -from memora_client_api.exceptions import ApiException as ApiException - -# import models into sdk package -from memora_client_api.models.add_background_request import AddBackgroundRequest as AddBackgroundRequest -from memora_client_api.models.agent_list_item import AgentListItem as AgentListItem -from memora_client_api.models.agent_list_response import AgentListResponse as AgentListResponse -from memora_client_api.models.agent_profile_response import AgentProfileResponse as AgentProfileResponse -from memora_client_api.models.background_response import BackgroundResponse as BackgroundResponse -from memora_client_api.models.batch_put_async_response import BatchPutAsyncResponse as BatchPutAsyncResponse -from memora_client_api.models.batch_put_request import BatchPutRequest as BatchPutRequest -from memora_client_api.models.batch_put_response import BatchPutResponse as BatchPutResponse -from memora_client_api.models.create_agent_request import CreateAgentRequest as CreateAgentRequest -from memora_client_api.models.delete_response import DeleteResponse as DeleteResponse -from memora_client_api.models.document_response import DocumentResponse as DocumentResponse -from memora_client_api.models.graph_data_response import GraphDataResponse as GraphDataResponse -from memora_client_api.models.http_validation_error import HTTPValidationError as HTTPValidationError -from memora_client_api.models.list_documents_response import ListDocumentsResponse as ListDocumentsResponse -from memora_client_api.models.list_memory_units_response import ListMemoryUnitsResponse as ListMemoryUnitsResponse -from memora_client_api.models.memory_item import MemoryItem as MemoryItem -from memora_client_api.models.personality_traits import PersonalityTraits as PersonalityTraits -from memora_client_api.models.search_request import SearchRequest as SearchRequest -from memora_client_api.models.search_response import SearchResponse as SearchResponse -from memora_client_api.models.search_result import SearchResult as SearchResult -from memora_client_api.models.think_fact import ThinkFact as ThinkFact -from memora_client_api.models.think_request import ThinkRequest as ThinkRequest -from memora_client_api.models.think_response import ThinkResponse as ThinkResponse -from memora_client_api.models.update_personality_request import UpdatePersonalityRequest as UpdatePersonalityRequest -from memora_client_api.models.validation_error import ValidationError as ValidationError -from memora_client_api.models.validation_error_loc_inner import ValidationErrorLocInner as ValidationErrorLocInner - diff --git a/memora-clients/python/memora_client_api/api/__init__.py b/memora-clients/python/memora_client_api/api/__init__.py deleted file mode 100644 index 92acbcfb48..0000000000 --- a/memora-clients/python/memora_client_api/api/__init__.py +++ /dev/null @@ -1,9 +0,0 @@ -# flake8: noqa - -# import apis into api package -from memora_client_api.api.agent_management_api import AgentManagementApi -from memora_client_api.api.documents_api import DocumentsApi -from memora_client_api.api.memory_operations_api import MemoryOperationsApi -from memora_client_api.api.reasoning_api import ReasoningApi -from memora_client_api.api.visualization_api import VisualizationApi - diff --git a/memora-clients/python/memora_client_api/models/__init__.py b/memora-clients/python/memora_client_api/models/__init__.py deleted file mode 100644 index 74e161846b..0000000000 --- a/memora-clients/python/memora_client_api/models/__init__.py +++ /dev/null @@ -1,42 +0,0 @@ -# coding: utf-8 - -# flake8: noqa -""" - Agent Memory API - - A temporal-semantic memory system for AI agents that stores, retrieves, and reasons over memories. ## Features * **Batch Memory Storage**: Store multiple memories efficiently with automatic fact extraction * **Semantic Search**: Find relevant memories using natural language queries * **Fact Type Filtering**: Search across world facts, agent actions, and opinions separately * **Think Endpoint**: Generate contextual answers based on agent identity and memories * **Graph Visualization**: Interactive memory graph visualization * **Document Tracking**: Track and manage memory documents with upsert support ## Architecture The system uses: - **Temporal Links**: Connect memories that are close in time - **Semantic Links**: Connect semantically similar memories - **Entity Links**: Connect memories that mention the same entities - **Spreading Activation**: Intelligent traversal for memory retrieval - - The version of the OpenAPI document: 1.0.0 - Generated by OpenAPI Generator (https://openapi-generator.tech) - - Do not edit the class manually. -""" # noqa: E501 - -# import models into model package -from memora_client_api.models.add_background_request import AddBackgroundRequest -from memora_client_api.models.agent_list_item import AgentListItem -from memora_client_api.models.agent_list_response import AgentListResponse -from memora_client_api.models.agent_profile_response import AgentProfileResponse -from memora_client_api.models.background_response import BackgroundResponse -from memora_client_api.models.batch_put_async_response import BatchPutAsyncResponse -from memora_client_api.models.batch_put_request import BatchPutRequest -from memora_client_api.models.batch_put_response import BatchPutResponse -from memora_client_api.models.create_agent_request import CreateAgentRequest -from memora_client_api.models.delete_response import DeleteResponse -from memora_client_api.models.document_response import DocumentResponse -from memora_client_api.models.graph_data_response import GraphDataResponse -from memora_client_api.models.http_validation_error import HTTPValidationError -from memora_client_api.models.list_documents_response import ListDocumentsResponse -from memora_client_api.models.list_memory_units_response import ListMemoryUnitsResponse -from memora_client_api.models.memory_item import MemoryItem -from memora_client_api.models.personality_traits import PersonalityTraits -from memora_client_api.models.search_request import SearchRequest -from memora_client_api.models.search_response import SearchResponse -from memora_client_api.models.search_result import SearchResult -from memora_client_api.models.think_fact import ThinkFact -from memora_client_api.models.think_request import ThinkRequest -from memora_client_api.models.think_response import ThinkResponse -from memora_client_api.models.update_personality_request import UpdatePersonalityRequest -from memora_client_api.models.validation_error import ValidationError -from memora_client_api.models.validation_error_loc_inner import ValidationErrorLocInner - diff --git a/memora-clients/typescript/core/ApiError.ts b/memora-clients/typescript/core/ApiError.ts deleted file mode 100644 index ec7b16af6f..0000000000 --- a/memora-clients/typescript/core/ApiError.ts +++ /dev/null @@ -1,25 +0,0 @@ -/* generated using openapi-typescript-codegen -- do not edit */ -/* istanbul ignore file */ -/* tslint:disable */ -/* eslint-disable */ -import type { ApiRequestOptions } from './ApiRequestOptions'; -import type { ApiResult } from './ApiResult'; - -export class ApiError extends Error { - public readonly url: string; - public readonly status: number; - public readonly statusText: string; - public readonly body: any; - public readonly request: ApiRequestOptions; - - constructor(request: ApiRequestOptions, response: ApiResult, message: string) { - super(message); - - this.name = 'ApiError'; - this.url = response.url; - this.status = response.status; - this.statusText = response.statusText; - this.body = response.body; - this.request = request; - } -} diff --git a/memora-clients/typescript/core/ApiRequestOptions.ts b/memora-clients/typescript/core/ApiRequestOptions.ts deleted file mode 100644 index 93143c3ce1..0000000000 --- a/memora-clients/typescript/core/ApiRequestOptions.ts +++ /dev/null @@ -1,17 +0,0 @@ -/* generated using openapi-typescript-codegen -- do not edit */ -/* istanbul ignore file */ -/* tslint:disable */ -/* eslint-disable */ -export type ApiRequestOptions = { - readonly method: 'GET' | 'PUT' | 'POST' | 'DELETE' | 'OPTIONS' | 'HEAD' | 'PATCH'; - readonly url: string; - readonly path?: Record; - readonly cookies?: Record; - readonly headers?: Record; - readonly query?: Record; - readonly formData?: Record; - readonly body?: any; - readonly mediaType?: string; - readonly responseHeader?: string; - readonly errors?: Record; -}; diff --git a/memora-clients/typescript/core/ApiResult.ts b/memora-clients/typescript/core/ApiResult.ts deleted file mode 100644 index ee1126e2cc..0000000000 --- a/memora-clients/typescript/core/ApiResult.ts +++ /dev/null @@ -1,11 +0,0 @@ -/* generated using openapi-typescript-codegen -- do not edit */ -/* istanbul ignore file */ -/* tslint:disable */ -/* eslint-disable */ -export type ApiResult = { - readonly url: string; - readonly ok: boolean; - readonly status: number; - readonly statusText: string; - readonly body: any; -}; diff --git a/memora-clients/typescript/core/CancelablePromise.ts b/memora-clients/typescript/core/CancelablePromise.ts deleted file mode 100644 index d70de92946..0000000000 --- a/memora-clients/typescript/core/CancelablePromise.ts +++ /dev/null @@ -1,131 +0,0 @@ -/* generated using openapi-typescript-codegen -- do not edit */ -/* istanbul ignore file */ -/* tslint:disable */ -/* eslint-disable */ -export class CancelError extends Error { - - constructor(message: string) { - super(message); - this.name = 'CancelError'; - } - - public get isCancelled(): boolean { - return true; - } -} - -export interface OnCancel { - readonly isResolved: boolean; - readonly isRejected: boolean; - readonly isCancelled: boolean; - - (cancelHandler: () => void): void; -} - -export class CancelablePromise implements Promise { - #isResolved: boolean; - #isRejected: boolean; - #isCancelled: boolean; - readonly #cancelHandlers: (() => void)[]; - readonly #promise: Promise; - #resolve?: (value: T | PromiseLike) => void; - #reject?: (reason?: any) => void; - - constructor( - executor: ( - resolve: (value: T | PromiseLike) => void, - reject: (reason?: any) => void, - onCancel: OnCancel - ) => void - ) { - this.#isResolved = false; - this.#isRejected = false; - this.#isCancelled = false; - this.#cancelHandlers = []; - this.#promise = new Promise((resolve, reject) => { - this.#resolve = resolve; - this.#reject = reject; - - const onResolve = (value: T | PromiseLike): void => { - if (this.#isResolved || this.#isRejected || this.#isCancelled) { - return; - } - this.#isResolved = true; - if (this.#resolve) this.#resolve(value); - }; - - const onReject = (reason?: any): void => { - if (this.#isResolved || this.#isRejected || this.#isCancelled) { - return; - } - this.#isRejected = true; - if (this.#reject) this.#reject(reason); - }; - - const onCancel = (cancelHandler: () => void): void => { - if (this.#isResolved || this.#isRejected || this.#isCancelled) { - return; - } - this.#cancelHandlers.push(cancelHandler); - }; - - Object.defineProperty(onCancel, 'isResolved', { - get: (): boolean => this.#isResolved, - }); - - Object.defineProperty(onCancel, 'isRejected', { - get: (): boolean => this.#isRejected, - }); - - Object.defineProperty(onCancel, 'isCancelled', { - get: (): boolean => this.#isCancelled, - }); - - return executor(onResolve, onReject, onCancel as OnCancel); - }); - } - - get [Symbol.toStringTag]() { - return "Cancellable Promise"; - } - - public then( - onFulfilled?: ((value: T) => TResult1 | PromiseLike) | null, - onRejected?: ((reason: any) => TResult2 | PromiseLike) | null - ): Promise { - return this.#promise.then(onFulfilled, onRejected); - } - - public catch( - onRejected?: ((reason: any) => TResult | PromiseLike) | null - ): Promise { - return this.#promise.catch(onRejected); - } - - public finally(onFinally?: (() => void) | null): Promise { - return this.#promise.finally(onFinally); - } - - public cancel(): void { - if (this.#isResolved || this.#isRejected || this.#isCancelled) { - return; - } - this.#isCancelled = true; - if (this.#cancelHandlers.length) { - try { - for (const cancelHandler of this.#cancelHandlers) { - cancelHandler(); - } - } catch (error) { - console.warn('Cancellation threw an error', error); - return; - } - } - this.#cancelHandlers.length = 0; - if (this.#reject) this.#reject(new CancelError('Request aborted')); - } - - public get isCancelled(): boolean { - return this.#isCancelled; - } -} diff --git a/memora-clients/typescript/core/OpenAPI.ts b/memora-clients/typescript/core/OpenAPI.ts deleted file mode 100644 index a0a9ed4a99..0000000000 --- a/memora-clients/typescript/core/OpenAPI.ts +++ /dev/null @@ -1,32 +0,0 @@ -/* generated using openapi-typescript-codegen -- do not edit */ -/* istanbul ignore file */ -/* tslint:disable */ -/* eslint-disable */ -import type { ApiRequestOptions } from './ApiRequestOptions'; - -type Resolver = (options: ApiRequestOptions) => Promise; -type Headers = Record; - -export type OpenAPIConfig = { - BASE: string; - VERSION: string; - WITH_CREDENTIALS: boolean; - CREDENTIALS: 'include' | 'omit' | 'same-origin'; - TOKEN?: string | Resolver | undefined; - USERNAME?: string | Resolver | undefined; - PASSWORD?: string | Resolver | undefined; - HEADERS?: Headers | Resolver | undefined; - ENCODE_PATH?: ((path: string) => string) | undefined; -}; - -export const OpenAPI: OpenAPIConfig = { - BASE: '', - VERSION: '1.0.0', - WITH_CREDENTIALS: false, - CREDENTIALS: 'include', - TOKEN: undefined, - USERNAME: undefined, - PASSWORD: undefined, - HEADERS: undefined, - ENCODE_PATH: undefined, -}; diff --git a/memora-clients/typescript/core/request.ts b/memora-clients/typescript/core/request.ts deleted file mode 100644 index 1dc6fef4aa..0000000000 --- a/memora-clients/typescript/core/request.ts +++ /dev/null @@ -1,323 +0,0 @@ -/* generated using openapi-typescript-codegen -- do not edit */ -/* istanbul ignore file */ -/* tslint:disable */ -/* eslint-disable */ -import axios from 'axios'; -import type { AxiosError, AxiosRequestConfig, AxiosResponse, AxiosInstance } from 'axios'; -import FormData from 'form-data'; - -import { ApiError } from './ApiError'; -import type { ApiRequestOptions } from './ApiRequestOptions'; -import type { ApiResult } from './ApiResult'; -import { CancelablePromise } from './CancelablePromise'; -import type { OnCancel } from './CancelablePromise'; -import type { OpenAPIConfig } from './OpenAPI'; - -export const isDefined = (value: T | null | undefined): value is Exclude => { - return value !== undefined && value !== null; -}; - -export const isString = (value: any): value is string => { - return typeof value === 'string'; -}; - -export const isStringWithValue = (value: any): value is string => { - return isString(value) && value !== ''; -}; - -export const isBlob = (value: any): value is Blob => { - return ( - typeof value === 'object' && - typeof value.type === 'string' && - typeof value.stream === 'function' && - typeof value.arrayBuffer === 'function' && - typeof value.constructor === 'function' && - typeof value.constructor.name === 'string' && - /^(Blob|File)$/.test(value.constructor.name) && - /^(Blob|File)$/.test(value[Symbol.toStringTag]) - ); -}; - -export const isFormData = (value: any): value is FormData => { - return value instanceof FormData; -}; - -export const isSuccess = (status: number): boolean => { - return status >= 200 && status < 300; -}; - -export const base64 = (str: string): string => { - try { - return btoa(str); - } catch (err) { - // @ts-ignore - return Buffer.from(str).toString('base64'); - } -}; - -export const getQueryString = (params: Record): string => { - const qs: string[] = []; - - const append = (key: string, value: any) => { - qs.push(`${encodeURIComponent(key)}=${encodeURIComponent(String(value))}`); - }; - - const process = (key: string, value: any) => { - if (isDefined(value)) { - if (Array.isArray(value)) { - value.forEach(v => { - process(key, v); - }); - } else if (typeof value === 'object') { - Object.entries(value).forEach(([k, v]) => { - process(`${key}[${k}]`, v); - }); - } else { - append(key, value); - } - } - }; - - Object.entries(params).forEach(([key, value]) => { - process(key, value); - }); - - if (qs.length > 0) { - return `?${qs.join('&')}`; - } - - return ''; -}; - -const getUrl = (config: OpenAPIConfig, options: ApiRequestOptions): string => { - const encoder = config.ENCODE_PATH || encodeURI; - - const path = options.url - .replace('{api-version}', config.VERSION) - .replace(/{(.*?)}/g, (substring: string, group: string) => { - if (options.path?.hasOwnProperty(group)) { - return encoder(String(options.path[group])); - } - return substring; - }); - - const url = `${config.BASE}${path}`; - if (options.query) { - return `${url}${getQueryString(options.query)}`; - } - return url; -}; - -export const getFormData = (options: ApiRequestOptions): FormData | undefined => { - if (options.formData) { - const formData = new FormData(); - - const process = (key: string, value: any) => { - if (isString(value) || isBlob(value)) { - formData.append(key, value); - } else { - formData.append(key, JSON.stringify(value)); - } - }; - - Object.entries(options.formData) - .filter(([_, value]) => isDefined(value)) - .forEach(([key, value]) => { - if (Array.isArray(value)) { - value.forEach(v => process(key, v)); - } else { - process(key, value); - } - }); - - return formData; - } - return undefined; -}; - -type Resolver = (options: ApiRequestOptions) => Promise; - -export const resolve = async (options: ApiRequestOptions, resolver?: T | Resolver): Promise => { - if (typeof resolver === 'function') { - return (resolver as Resolver)(options); - } - return resolver; -}; - -export const getHeaders = async (config: OpenAPIConfig, options: ApiRequestOptions, formData?: FormData): Promise> => { - const [token, username, password, additionalHeaders] = await Promise.all([ - resolve(options, config.TOKEN), - resolve(options, config.USERNAME), - resolve(options, config.PASSWORD), - resolve(options, config.HEADERS), - ]); - - const formHeaders = typeof formData?.getHeaders === 'function' && formData?.getHeaders() || {} - - const headers = Object.entries({ - Accept: 'application/json', - ...additionalHeaders, - ...options.headers, - ...formHeaders, - }) - .filter(([_, value]) => isDefined(value)) - .reduce((headers, [key, value]) => ({ - ...headers, - [key]: String(value), - }), {} as Record); - - if (isStringWithValue(token)) { - headers['Authorization'] = `Bearer ${token}`; - } - - if (isStringWithValue(username) && isStringWithValue(password)) { - const credentials = base64(`${username}:${password}`); - headers['Authorization'] = `Basic ${credentials}`; - } - - if (options.body !== undefined) { - if (options.mediaType) { - headers['Content-Type'] = options.mediaType; - } else if (isBlob(options.body)) { - headers['Content-Type'] = options.body.type || 'application/octet-stream'; - } else if (isString(options.body)) { - headers['Content-Type'] = 'text/plain'; - } else if (!isFormData(options.body)) { - headers['Content-Type'] = 'application/json'; - } - } - - return headers; -}; - -export const getRequestBody = (options: ApiRequestOptions): any => { - if (options.body) { - return options.body; - } - return undefined; -}; - -export const sendRequest = async ( - config: OpenAPIConfig, - options: ApiRequestOptions, - url: string, - body: any, - formData: FormData | undefined, - headers: Record, - onCancel: OnCancel, - axiosClient: AxiosInstance -): Promise> => { - const source = axios.CancelToken.source(); - - const requestConfig: AxiosRequestConfig = { - url, - headers, - data: body ?? formData, - method: options.method, - withCredentials: config.WITH_CREDENTIALS, - withXSRFToken: config.CREDENTIALS === 'include' ? config.WITH_CREDENTIALS : false, - cancelToken: source.token, - }; - - onCancel(() => source.cancel('The user aborted a request.')); - - try { - return await axiosClient.request(requestConfig); - } catch (error) { - const axiosError = error as AxiosError; - if (axiosError.response) { - return axiosError.response; - } - throw error; - } -}; - -export const getResponseHeader = (response: AxiosResponse, responseHeader?: string): string | undefined => { - if (responseHeader) { - const content = response.headers[responseHeader]; - if (isString(content)) { - return content; - } - } - return undefined; -}; - -export const getResponseBody = (response: AxiosResponse): any => { - if (response.status !== 204) { - return response.data; - } - return undefined; -}; - -export const catchErrorCodes = (options: ApiRequestOptions, result: ApiResult): void => { - const errors: Record = { - 400: 'Bad Request', - 401: 'Unauthorized', - 403: 'Forbidden', - 404: 'Not Found', - 500: 'Internal Server Error', - 502: 'Bad Gateway', - 503: 'Service Unavailable', - ...options.errors, - } - - const error = errors[result.status]; - if (error) { - throw new ApiError(options, result, error); - } - - if (!result.ok) { - const errorStatus = result.status ?? 'unknown'; - const errorStatusText = result.statusText ?? 'unknown'; - const errorBody = (() => { - try { - return JSON.stringify(result.body, null, 2); - } catch (e) { - return undefined; - } - })(); - - throw new ApiError(options, result, - `Generic Error: status: ${errorStatus}; status text: ${errorStatusText}; body: ${errorBody}` - ); - } -}; - -/** - * Request method - * @param config The OpenAPI configuration object - * @param options The request options from the service - * @param axiosClient The axios client instance to use - * @returns CancelablePromise - * @throws ApiError - */ -export const request = (config: OpenAPIConfig, options: ApiRequestOptions, axiosClient: AxiosInstance = axios): CancelablePromise => { - return new CancelablePromise(async (resolve, reject, onCancel) => { - try { - const url = getUrl(config, options); - const formData = getFormData(options); - const body = getRequestBody(options); - const headers = await getHeaders(config, options, formData); - - if (!onCancel.isCancelled) { - const response = await sendRequest(config, options, url, body, formData, headers, onCancel, axiosClient); - const responseBody = getResponseBody(response); - const responseHeader = getResponseHeader(response, options.responseHeader); - - const result: ApiResult = { - url, - ok: isSuccess(response.status), - status: response.status, - statusText: response.statusText, - body: responseHeader ?? responseBody, - }; - - catchErrorCodes(options, result); - - resolve(result.body); - } - } catch (error) { - reject(error); - } - }); -}; diff --git a/memora-clients/typescript/index.ts b/memora-clients/typescript/index.ts deleted file mode 100644 index b6c169a8ac..0000000000 --- a/memora-clients/typescript/index.ts +++ /dev/null @@ -1,40 +0,0 @@ -/* generated using openapi-typescript-codegen -- do not edit */ -/* istanbul ignore file */ -/* tslint:disable */ -/* eslint-disable */ -export { ApiError } from './core/ApiError'; -export { CancelablePromise, CancelError } from './core/CancelablePromise'; -export { OpenAPI } from './core/OpenAPI'; -export type { OpenAPIConfig } from './core/OpenAPI'; - -export type { AddBackgroundRequest } from './models/AddBackgroundRequest'; -export type { AgentListItem } from './models/AgentListItem'; -export type { AgentListResponse } from './models/AgentListResponse'; -export type { AgentProfileResponse } from './models/AgentProfileResponse'; -export type { BackgroundResponse } from './models/BackgroundResponse'; -export type { BatchPutAsyncResponse } from './models/BatchPutAsyncResponse'; -export type { BatchPutRequest } from './models/BatchPutRequest'; -export type { BatchPutResponse } from './models/BatchPutResponse'; -export type { CreateAgentRequest } from './models/CreateAgentRequest'; -export type { DeleteResponse } from './models/DeleteResponse'; -export type { DocumentResponse } from './models/DocumentResponse'; -export type { GraphDataResponse } from './models/GraphDataResponse'; -export type { HTTPValidationError } from './models/HTTPValidationError'; -export type { ListDocumentsResponse } from './models/ListDocumentsResponse'; -export type { ListMemoryUnitsResponse } from './models/ListMemoryUnitsResponse'; -export type { MemoryItem } from './models/MemoryItem'; -export type { PersonalityTraits } from './models/PersonalityTraits'; -export type { SearchRequest } from './models/SearchRequest'; -export type { SearchResponse } from './models/SearchResponse'; -export type { SearchResult } from './models/SearchResult'; -export type { ThinkFact } from './models/ThinkFact'; -export type { ThinkRequest } from './models/ThinkRequest'; -export type { ThinkResponse } from './models/ThinkResponse'; -export type { UpdatePersonalityRequest } from './models/UpdatePersonalityRequest'; -export type { ValidationError } from './models/ValidationError'; - -export { AgentManagementService } from './services/AgentManagementService'; -export { DocumentsService } from './services/DocumentsService'; -export { MemoryOperationsService } from './services/MemoryOperationsService'; -export { ReasoningService } from './services/ReasoningService'; -export { VisualizationService } from './services/VisualizationService'; diff --git a/memora-clients/typescript/models/AddBackgroundRequest.ts b/memora-clients/typescript/models/AddBackgroundRequest.ts deleted file mode 100644 index 204c9c0611..0000000000 --- a/memora-clients/typescript/models/AddBackgroundRequest.ts +++ /dev/null @@ -1,18 +0,0 @@ -/* generated using openapi-typescript-codegen -- do not edit */ -/* istanbul ignore file */ -/* tslint:disable */ -/* eslint-disable */ -/** - * Request model for adding/merging background information. - */ -export type AddBackgroundRequest = { - /** - * New background information to add or merge - */ - content: string; - /** - * If true, infer Big Five personality traits from the merged background (default: true) - */ - update_personality?: boolean; -}; - diff --git a/memora-clients/typescript/models/AgentListItem.ts b/memora-clients/typescript/models/AgentListItem.ts deleted file mode 100644 index 51a9c612fd..0000000000 --- a/memora-clients/typescript/models/AgentListItem.ts +++ /dev/null @@ -1,17 +0,0 @@ -/* generated using openapi-typescript-codegen -- do not edit */ -/* istanbul ignore file */ -/* tslint:disable */ -/* eslint-disable */ -import type { PersonalityTraits } from './PersonalityTraits'; -/** - * Agent list item with profile summary. - */ -export type AgentListItem = { - agent_id: string; - name: string; - personality: PersonalityTraits; - background: string; - created_at?: (string | null); - updated_at?: (string | null); -}; - diff --git a/memora-clients/typescript/models/AgentListResponse.ts b/memora-clients/typescript/models/AgentListResponse.ts deleted file mode 100644 index bf61522e31..0000000000 --- a/memora-clients/typescript/models/AgentListResponse.ts +++ /dev/null @@ -1,12 +0,0 @@ -/* generated using openapi-typescript-codegen -- do not edit */ -/* istanbul ignore file */ -/* tslint:disable */ -/* eslint-disable */ -import type { AgentListItem } from './AgentListItem'; -/** - * Response model for listing all agents. - */ -export type AgentListResponse = { - agents: Array; -}; - diff --git a/memora-clients/typescript/models/AgentProfileResponse.ts b/memora-clients/typescript/models/AgentProfileResponse.ts deleted file mode 100644 index addad64a0f..0000000000 --- a/memora-clients/typescript/models/AgentProfileResponse.ts +++ /dev/null @@ -1,15 +0,0 @@ -/* generated using openapi-typescript-codegen -- do not edit */ -/* istanbul ignore file */ -/* tslint:disable */ -/* eslint-disable */ -import type { PersonalityTraits } from './PersonalityTraits'; -/** - * Response model for agent profile. - */ -export type AgentProfileResponse = { - agent_id: string; - name: string; - personality: PersonalityTraits; - background: string; -}; - diff --git a/memora-clients/typescript/models/BackgroundResponse.ts b/memora-clients/typescript/models/BackgroundResponse.ts deleted file mode 100644 index 99246fd6a5..0000000000 --- a/memora-clients/typescript/models/BackgroundResponse.ts +++ /dev/null @@ -1,13 +0,0 @@ -/* generated using openapi-typescript-codegen -- do not edit */ -/* istanbul ignore file */ -/* tslint:disable */ -/* eslint-disable */ -import type { PersonalityTraits } from './PersonalityTraits'; -/** - * Response model for background update. - */ -export type BackgroundResponse = { - background: string; - personality?: (PersonalityTraits | null); -}; - diff --git a/memora-clients/typescript/models/BatchPutAsyncResponse.ts b/memora-clients/typescript/models/BatchPutAsyncResponse.ts deleted file mode 100644 index 4db226b90f..0000000000 --- a/memora-clients/typescript/models/BatchPutAsyncResponse.ts +++ /dev/null @@ -1,16 +0,0 @@ -/* generated using openapi-typescript-codegen -- do not edit */ -/* istanbul ignore file */ -/* tslint:disable */ -/* eslint-disable */ -/** - * Response model for async batch put endpoint. - */ -export type BatchPutAsyncResponse = { - success: boolean; - message: string; - agent_id: string; - document_id?: (string | null); - items_count: number; - queued: boolean; -}; - diff --git a/memora-clients/typescript/models/BatchPutRequest.ts b/memora-clients/typescript/models/BatchPutRequest.ts deleted file mode 100644 index c961a3434c..0000000000 --- a/memora-clients/typescript/models/BatchPutRequest.ts +++ /dev/null @@ -1,13 +0,0 @@ -/* generated using openapi-typescript-codegen -- do not edit */ -/* istanbul ignore file */ -/* tslint:disable */ -/* eslint-disable */ -import type { MemoryItem } from './MemoryItem'; -/** - * Request model for batch put endpoint. - */ -export type BatchPutRequest = { - items: Array; - document_id?: (string | null); -}; - diff --git a/memora-clients/typescript/models/BatchPutResponse.ts b/memora-clients/typescript/models/BatchPutResponse.ts deleted file mode 100644 index e5b2e27cf6..0000000000 --- a/memora-clients/typescript/models/BatchPutResponse.ts +++ /dev/null @@ -1,15 +0,0 @@ -/* generated using openapi-typescript-codegen -- do not edit */ -/* istanbul ignore file */ -/* tslint:disable */ -/* eslint-disable */ -/** - * Response model for batch put endpoint. - */ -export type BatchPutResponse = { - success: boolean; - message: string; - agent_id: string; - document_id?: (string | null); - items_count: number; -}; - diff --git a/memora-clients/typescript/models/CreateAgentRequest.ts b/memora-clients/typescript/models/CreateAgentRequest.ts deleted file mode 100644 index d7605b86dd..0000000000 --- a/memora-clients/typescript/models/CreateAgentRequest.ts +++ /dev/null @@ -1,14 +0,0 @@ -/* generated using openapi-typescript-codegen -- do not edit */ -/* istanbul ignore file */ -/* tslint:disable */ -/* eslint-disable */ -import type { PersonalityTraits } from './PersonalityTraits'; -/** - * Request model for creating/updating an agent. - */ -export type CreateAgentRequest = { - name?: (string | null); - personality?: (PersonalityTraits | null); - background?: (string | null); -}; - diff --git a/memora-clients/typescript/models/DeleteResponse.ts b/memora-clients/typescript/models/DeleteResponse.ts deleted file mode 100644 index 7c7107a3d7..0000000000 --- a/memora-clients/typescript/models/DeleteResponse.ts +++ /dev/null @@ -1,12 +0,0 @@ -/* generated using openapi-typescript-codegen -- do not edit */ -/* istanbul ignore file */ -/* tslint:disable */ -/* eslint-disable */ -/** - * Response model for delete operations. - */ -export type DeleteResponse = { - success: boolean; - message: string; -}; - diff --git a/memora-clients/typescript/models/DocumentResponse.ts b/memora-clients/typescript/models/DocumentResponse.ts deleted file mode 100644 index e43ef1a48d..0000000000 --- a/memora-clients/typescript/models/DocumentResponse.ts +++ /dev/null @@ -1,17 +0,0 @@ -/* generated using openapi-typescript-codegen -- do not edit */ -/* istanbul ignore file */ -/* tslint:disable */ -/* eslint-disable */ -/** - * Response model for get document endpoint. - */ -export type DocumentResponse = { - id: string; - agent_id: string; - original_text: string; - content_hash: (string | null); - created_at: string; - updated_at: string; - memory_unit_count: number; -}; - diff --git a/memora-clients/typescript/models/GraphDataResponse.ts b/memora-clients/typescript/models/GraphDataResponse.ts deleted file mode 100644 index 5f982421d3..0000000000 --- a/memora-clients/typescript/models/GraphDataResponse.ts +++ /dev/null @@ -1,14 +0,0 @@ -/* generated using openapi-typescript-codegen -- do not edit */ -/* istanbul ignore file */ -/* tslint:disable */ -/* eslint-disable */ -/** - * Response model for graph data endpoint. - */ -export type GraphDataResponse = { - nodes: Array>; - edges: Array>; - table_rows: Array>; - total_units: number; -}; - diff --git a/memora-clients/typescript/models/HTTPValidationError.ts b/memora-clients/typescript/models/HTTPValidationError.ts deleted file mode 100644 index f9b1a79e2c..0000000000 --- a/memora-clients/typescript/models/HTTPValidationError.ts +++ /dev/null @@ -1,9 +0,0 @@ -/* generated using openapi-typescript-codegen -- do not edit */ -/* istanbul ignore file */ -/* tslint:disable */ -/* eslint-disable */ -import type { ValidationError } from './ValidationError'; -export type HTTPValidationError = { - detail?: Array; -}; - diff --git a/memora-clients/typescript/models/ListDocumentsResponse.ts b/memora-clients/typescript/models/ListDocumentsResponse.ts deleted file mode 100644 index b5d18f9c40..0000000000 --- a/memora-clients/typescript/models/ListDocumentsResponse.ts +++ /dev/null @@ -1,14 +0,0 @@ -/* generated using openapi-typescript-codegen -- do not edit */ -/* istanbul ignore file */ -/* tslint:disable */ -/* eslint-disable */ -/** - * Response model for list documents endpoint. - */ -export type ListDocumentsResponse = { - items: Array>; - total: number; - limit: number; - offset: number; -}; - diff --git a/memora-clients/typescript/models/ListMemoryUnitsResponse.ts b/memora-clients/typescript/models/ListMemoryUnitsResponse.ts deleted file mode 100644 index 29846511c6..0000000000 --- a/memora-clients/typescript/models/ListMemoryUnitsResponse.ts +++ /dev/null @@ -1,14 +0,0 @@ -/* generated using openapi-typescript-codegen -- do not edit */ -/* istanbul ignore file */ -/* tslint:disable */ -/* eslint-disable */ -/** - * Response model for list memory units endpoint. - */ -export type ListMemoryUnitsResponse = { - items: Array>; - total: number; - limit: number; - offset: number; -}; - diff --git a/memora-clients/typescript/models/MemoryItem.ts b/memora-clients/typescript/models/MemoryItem.ts deleted file mode 100644 index 544e2be382..0000000000 --- a/memora-clients/typescript/models/MemoryItem.ts +++ /dev/null @@ -1,13 +0,0 @@ -/* generated using openapi-typescript-codegen -- do not edit */ -/* istanbul ignore file */ -/* tslint:disable */ -/* eslint-disable */ -/** - * Single memory item for batch put. - */ -export type MemoryItem = { - content: string; - event_date?: (string | null); - context?: (string | null); -}; - diff --git a/memora-clients/typescript/models/PersonalityTraits.ts b/memora-clients/typescript/models/PersonalityTraits.ts deleted file mode 100644 index adc2c48b5a..0000000000 --- a/memora-clients/typescript/models/PersonalityTraits.ts +++ /dev/null @@ -1,34 +0,0 @@ -/* generated using openapi-typescript-codegen -- do not edit */ -/* istanbul ignore file */ -/* tslint:disable */ -/* eslint-disable */ -/** - * Personality traits based on Big Five model. - */ -export type PersonalityTraits = { - /** - * Openness to experience (0-1) - */ - openness: number; - /** - * Conscientiousness (0-1) - */ - conscientiousness: number; - /** - * Extraversion (0-1) - */ - extraversion: number; - /** - * Agreeableness (0-1) - */ - agreeableness: number; - /** - * Neuroticism (0-1) - */ - neuroticism: number; - /** - * How strongly personality influences opinions (0-1) - */ - bias_strength: number; -}; - diff --git a/memora-clients/typescript/models/SearchRequest.ts b/memora-clients/typescript/models/SearchRequest.ts deleted file mode 100644 index d279674e43..0000000000 --- a/memora-clients/typescript/models/SearchRequest.ts +++ /dev/null @@ -1,16 +0,0 @@ -/* generated using openapi-typescript-codegen -- do not edit */ -/* istanbul ignore file */ -/* tslint:disable */ -/* eslint-disable */ -/** - * Request model for search endpoint. - */ -export type SearchRequest = { - query: string; - fact_type?: (Array | null); - thinking_budget?: number; - max_tokens?: number; - trace?: boolean; - question_date?: (string | null); -}; - diff --git a/memora-clients/typescript/models/SearchResponse.ts b/memora-clients/typescript/models/SearchResponse.ts deleted file mode 100644 index 1f2bc13dd8..0000000000 --- a/memora-clients/typescript/models/SearchResponse.ts +++ /dev/null @@ -1,13 +0,0 @@ -/* generated using openapi-typescript-codegen -- do not edit */ -/* istanbul ignore file */ -/* tslint:disable */ -/* eslint-disable */ -import type { SearchResult } from './SearchResult'; -/** - * Response model for search endpoints. - */ -export type SearchResponse = { - results: Array; - trace?: (Record | null); -}; - diff --git a/memora-clients/typescript/models/SearchResult.ts b/memora-clients/typescript/models/SearchResult.ts deleted file mode 100644 index 52579761bf..0000000000 --- a/memora-clients/typescript/models/SearchResult.ts +++ /dev/null @@ -1,16 +0,0 @@ -/* generated using openapi-typescript-codegen -- do not edit */ -/* istanbul ignore file */ -/* tslint:disable */ -/* eslint-disable */ -/** - * Single search result item. - */ -export type SearchResult = { - id: string; - text: string; - type?: (string | null); - context?: (string | null); - event_date?: (string | null); - document_id?: (string | null); -}; - diff --git a/memora-clients/typescript/models/ThinkFact.ts b/memora-clients/typescript/models/ThinkFact.ts deleted file mode 100644 index dd460cb9e1..0000000000 --- a/memora-clients/typescript/models/ThinkFact.ts +++ /dev/null @@ -1,15 +0,0 @@ -/* generated using openapi-typescript-codegen -- do not edit */ -/* istanbul ignore file */ -/* tslint:disable */ -/* eslint-disable */ -/** - * A fact used in think response. - */ -export type ThinkFact = { - id?: (string | null); - text: string; - type?: (string | null); - context?: (string | null); - event_date?: (string | null); -}; - diff --git a/memora-clients/typescript/models/ThinkRequest.ts b/memora-clients/typescript/models/ThinkRequest.ts deleted file mode 100644 index bf78800bd6..0000000000 --- a/memora-clients/typescript/models/ThinkRequest.ts +++ /dev/null @@ -1,13 +0,0 @@ -/* generated using openapi-typescript-codegen -- do not edit */ -/* istanbul ignore file */ -/* tslint:disable */ -/* eslint-disable */ -/** - * Request model for think endpoint. - */ -export type ThinkRequest = { - query: string; - thinking_budget?: number; - context?: (string | null); -}; - diff --git a/memora-clients/typescript/models/ThinkResponse.ts b/memora-clients/typescript/models/ThinkResponse.ts deleted file mode 100644 index 6085d5034f..0000000000 --- a/memora-clients/typescript/models/ThinkResponse.ts +++ /dev/null @@ -1,14 +0,0 @@ -/* generated using openapi-typescript-codegen -- do not edit */ -/* istanbul ignore file */ -/* tslint:disable */ -/* eslint-disable */ -import type { ThinkFact } from './ThinkFact'; -/** - * Response model for think endpoint. - */ -export type ThinkResponse = { - text: string; - based_on?: Array; - new_opinions?: Array; -}; - diff --git a/memora-clients/typescript/models/UpdatePersonalityRequest.ts b/memora-clients/typescript/models/UpdatePersonalityRequest.ts deleted file mode 100644 index fd4ef378cd..0000000000 --- a/memora-clients/typescript/models/UpdatePersonalityRequest.ts +++ /dev/null @@ -1,12 +0,0 @@ -/* generated using openapi-typescript-codegen -- do not edit */ -/* istanbul ignore file */ -/* tslint:disable */ -/* eslint-disable */ -import type { PersonalityTraits } from './PersonalityTraits'; -/** - * Request model for updating personality traits. - */ -export type UpdatePersonalityRequest = { - personality: PersonalityTraits; -}; - diff --git a/memora-clients/typescript/models/ValidationError.ts b/memora-clients/typescript/models/ValidationError.ts deleted file mode 100644 index aaf1c921e8..0000000000 --- a/memora-clients/typescript/models/ValidationError.ts +++ /dev/null @@ -1,10 +0,0 @@ -/* generated using openapi-typescript-codegen -- do not edit */ -/* istanbul ignore file */ -/* tslint:disable */ -/* eslint-disable */ -export type ValidationError = { - loc: Array<(string | number)>; - msg: string; - type: string; -}; - diff --git a/memora-clients/typescript/package.json b/memora-clients/typescript/package.json deleted file mode 100644 index 7c1b660d3b..0000000000 --- a/memora-clients/typescript/package.json +++ /dev/null @@ -1,43 +0,0 @@ -{ - "name": "@memora/client", - "version": "0.0.7", - "description": "TypeScript client for Memora - Semantic memory system with personality-driven thinking", - "main": "./dist/index.js", - "types": "./dist/index.d.ts", - "scripts": { - "build": "tsc", - "clean": "rm -rf dist", - "prepublishOnly": "npm run build", - "test": "jest" - }, - "keywords": [ - "memora", - "memory", - "api", - "client", - "typescript" - ], - "author": "Memora Team", - "license": "MIT", - "repository": { - "type": "git", - "url": "https://github.com/nicoloboschi/memora.git", - "directory": "memora-clients/typescript" - }, - "dependencies": { - "axios": "^1.6.0", - "form-data": "^4.0.0" - }, - "devDependencies": { - "@types/node": "^20.0.0", - "typescript": "^5.0.0", - "jest": "^29.0.0", - "@types/jest": "^29.0.0", - "ts-jest": "^29.0.0" - }, - "files": [ - "dist", - "src", - "README.md" - ] -} diff --git a/memora-clients/typescript/services/AgentManagementService.ts b/memora-clients/typescript/services/AgentManagementService.ts deleted file mode 100644 index 63a9b3e79d..0000000000 --- a/memora-clients/typescript/services/AgentManagementService.ts +++ /dev/null @@ -1,180 +0,0 @@ -/* generated using openapi-typescript-codegen -- do not edit */ -/* istanbul ignore file */ -/* tslint:disable */ -/* eslint-disable */ -import type { AddBackgroundRequest } from '../models/AddBackgroundRequest'; -import type { AgentListResponse } from '../models/AgentListResponse'; -import type { AgentProfileResponse } from '../models/AgentProfileResponse'; -import type { BackgroundResponse } from '../models/BackgroundResponse'; -import type { CreateAgentRequest } from '../models/CreateAgentRequest'; -import type { DeleteResponse } from '../models/DeleteResponse'; -import type { UpdatePersonalityRequest } from '../models/UpdatePersonalityRequest'; -import type { CancelablePromise } from '../core/CancelablePromise'; -import { OpenAPI } from '../core/OpenAPI'; -import { request as __request } from '../core/request'; -export class AgentManagementService { - /** - * List all agents - * Get a list of all agents with their profiles - * @returns AgentListResponse Successful Response - * @throws ApiError - */ - public static listAgents(): CancelablePromise { - return __request(OpenAPI, { - method: 'GET', - url: '/api/v1/agents', - }); - } - /** - * Get memory statistics for an agent - * Get statistics about nodes and links for a specific agent - * @returns any Successful Response - * @throws ApiError - */ - public static getAgentStats({ - agentId, - }: { - agentId: string, - }): CancelablePromise { - return __request(OpenAPI, { - method: 'GET', - url: '/api/v1/agents/{agent_id}/stats', - path: { - 'agent_id': agentId, - }, - errors: { - 422: `Validation Error`, - }, - }); - } - /** - * Clear agent memories - * Delete memory units for an agent. Optionally filter by fact_type (world, agent, opinion) to delete only specific types. This is a destructive operation that cannot be undone. The agent profile (personality and background) will be preserved. - * @returns DeleteResponse Successful Response - * @throws ApiError - */ - public static clearAgentMemories({ - agentId, - factType, - }: { - agentId: string, - /** - * Optional fact type filter (world, agent, opinion) - */ - factType?: (string | null), - }): CancelablePromise { - return __request(OpenAPI, { - method: 'DELETE', - url: '/api/v1/agents/{agent_id}/memories', - path: { - 'agent_id': agentId, - }, - query: { - 'fact_type': factType, - }, - errors: { - 422: `Validation Error`, - }, - }); - } - /** - * Get agent profile - * Get personality traits and background for an agent. Auto-creates agent with defaults if not exists. - * @returns AgentProfileResponse Successful Response - * @throws ApiError - */ - public static getAgentProfile({ - agentId, - }: { - agentId: string, - }): CancelablePromise { - return __request(OpenAPI, { - method: 'GET', - url: '/api/v1/agents/{agent_id}/profile', - path: { - 'agent_id': agentId, - }, - errors: { - 422: `Validation Error`, - }, - }); - } - /** - * Update agent personality - * Update agent's Big Five personality traits and bias strength - * @returns AgentProfileResponse Successful Response - * @throws ApiError - */ - public static updateAgentPersonality({ - agentId, - requestBody, - }: { - agentId: string, - requestBody: UpdatePersonalityRequest, - }): CancelablePromise { - return __request(OpenAPI, { - method: 'PUT', - url: '/api/v1/agents/{agent_id}/profile', - path: { - 'agent_id': agentId, - }, - body: requestBody, - mediaType: 'application/json', - errors: { - 422: `Validation Error`, - }, - }); - } - /** - * Add/merge agent background - * Add new background information or merge with existing. LLM intelligently resolves conflicts, normalizes to first person, and optionally infers personality traits. - * @returns BackgroundResponse Successful Response - * @throws ApiError - */ - public static addAgentBackground({ - agentId, - requestBody, - }: { - agentId: string, - requestBody: AddBackgroundRequest, - }): CancelablePromise { - return __request(OpenAPI, { - method: 'POST', - url: '/api/v1/agents/{agent_id}/background', - path: { - 'agent_id': agentId, - }, - body: requestBody, - mediaType: 'application/json', - errors: { - 422: `Validation Error`, - }, - }); - } - /** - * Create or update agent - * Create a new agent or update existing agent with personality and background. Auto-fills missing fields with defaults. - * @returns AgentProfileResponse Successful Response - * @throws ApiError - */ - public static createOrUpdateAgent({ - agentId, - requestBody, - }: { - agentId: string, - requestBody: CreateAgentRequest, - }): CancelablePromise { - return __request(OpenAPI, { - method: 'PUT', - url: '/api/v1/agents/{agent_id}', - path: { - 'agent_id': agentId, - }, - body: requestBody, - mediaType: 'application/json', - errors: { - 422: `Validation Error`, - }, - }); - } -} diff --git a/memora-clients/typescript/services/DocumentsService.ts b/memora-clients/typescript/services/DocumentsService.ts deleted file mode 100644 index f97fcf6270..0000000000 --- a/memora-clients/typescript/services/DocumentsService.ts +++ /dev/null @@ -1,101 +0,0 @@ -/* generated using openapi-typescript-codegen -- do not edit */ -/* istanbul ignore file */ -/* tslint:disable */ -/* eslint-disable */ -import type { DocumentResponse } from '../models/DocumentResponse'; -import type { ListDocumentsResponse } from '../models/ListDocumentsResponse'; -import type { CancelablePromise } from '../core/CancelablePromise'; -import { OpenAPI } from '../core/OpenAPI'; -import { request as __request } from '../core/request'; -export class DocumentsService { - /** - * List documents - * List documents with pagination and optional search. Documents are the source content from which memory units are extracted. - * @returns ListDocumentsResponse Successful Response - * @throws ApiError - */ - public static listDocuments({ - agentId, - q, - limit = 100, - offset, - }: { - agentId: string, - q?: (string | null), - limit?: number, - offset?: number, - }): CancelablePromise { - return __request(OpenAPI, { - method: 'GET', - url: '/api/v1/agents/{agent_id}/documents', - path: { - 'agent_id': agentId, - }, - query: { - 'q': q, - 'limit': limit, - 'offset': offset, - }, - errors: { - 422: `Validation Error`, - }, - }); - } - /** - * Get document details - * Get a specific document including its original text - * @returns DocumentResponse Successful Response - * @throws ApiError - */ - public static getDocument({ - agentId, - documentId, - }: { - agentId: string, - documentId: string, - }): CancelablePromise { - return __request(OpenAPI, { - method: 'GET', - url: '/api/v1/agents/{agent_id}/documents/{document_id}', - path: { - 'agent_id': agentId, - 'document_id': documentId, - }, - errors: { - 422: `Validation Error`, - }, - }); - } - /** - * Delete a document - * Delete a document and all its associated memory units and links. - * - * This will cascade delete: - * - The document itself - * - All memory units extracted from this document - * - All links (temporal, semantic, entity) associated with those memory units - * - * This operation cannot be undone. - * @returns any Successful Response - * @throws ApiError - */ - public static deleteDocument({ - agentId, - documentId, - }: { - agentId: string, - documentId: string, - }): CancelablePromise { - return __request(OpenAPI, { - method: 'DELETE', - url: '/api/v1/agents/{agent_id}/documents/{document_id}', - path: { - 'agent_id': agentId, - 'document_id': documentId, - }, - errors: { - 422: `Validation Error`, - }, - }); - } -} diff --git a/memora-clients/typescript/services/MemoryOperationsService.ts b/memora-clients/typescript/services/MemoryOperationsService.ts deleted file mode 100644 index e54e4de5b0..0000000000 --- a/memora-clients/typescript/services/MemoryOperationsService.ts +++ /dev/null @@ -1,241 +0,0 @@ -/* generated using openapi-typescript-codegen -- do not edit */ -/* istanbul ignore file */ -/* tslint:disable */ -/* eslint-disable */ -import type { BatchPutAsyncResponse } from '../models/BatchPutAsyncResponse'; -import type { BatchPutRequest } from '../models/BatchPutRequest'; -import type { BatchPutResponse } from '../models/BatchPutResponse'; -import type { ListMemoryUnitsResponse } from '../models/ListMemoryUnitsResponse'; -import type { SearchRequest } from '../models/SearchRequest'; -import type { SearchResponse } from '../models/SearchResponse'; -import type { CancelablePromise } from '../core/CancelablePromise'; -import { OpenAPI } from '../core/OpenAPI'; -import { request as __request } from '../core/request'; -export class MemoryOperationsService { - /** - * List memory units - * List memory units with pagination and optional full-text search. Supports filtering by fact_type. - * @returns ListMemoryUnitsResponse Successful Response - * @throws ApiError - */ - public static listMemories({ - agentId, - factType, - q, - limit = 100, - offset, - }: { - agentId: string, - factType?: (string | null), - q?: (string | null), - limit?: number, - offset?: number, - }): CancelablePromise { - return __request(OpenAPI, { - method: 'GET', - url: '/api/v1/agents/{agent_id}/memories/list', - path: { - 'agent_id': agentId, - }, - query: { - 'fact_type': factType, - 'q': q, - 'limit': limit, - 'offset': offset, - }, - errors: { - 422: `Validation Error`, - }, - }); - } - /** - * Search memory - * Search memory using semantic similarity and spreading activation. - * - * The fact_type parameter is optional and must be one of: - * - 'world': General knowledge about people, places, events, and things that happen - * - 'agent': Memories about what the AI agent did, actions taken, and tasks performed - * - 'opinion': The agent's formed beliefs, perspectives, and viewpoints - * @returns SearchResponse Successful Response - * @throws ApiError - */ - public static searchMemories({ - agentId, - requestBody, - }: { - agentId: string, - requestBody: SearchRequest, - }): CancelablePromise { - return __request(OpenAPI, { - method: 'POST', - url: '/api/v1/agents/{agent_id}/memories/search', - path: { - 'agent_id': agentId, - }, - body: requestBody, - mediaType: 'application/json', - errors: { - 422: `Validation Error`, - }, - }); - } - /** - * Store multiple memories - * Store multiple memory items in batch with automatic fact extraction. - * - * Features: - * - Efficient batch processing - * - Automatic fact extraction from natural language - * - Entity recognition and linking - * - Document tracking with automatic upsert (when document_id is provided) - * - Temporal and semantic linking - * - * The system automatically: - * 1. Extracts semantic facts from the content - * 2. Generates embeddings - * 3. Deduplicates similar facts - * 4. Creates temporal, semantic, and entity links - * 5. Tracks document metadata - * - * Note: If document_id is provided and already exists, the old document and its memory units will be deleted before creating new ones (upsert behavior). - * @returns BatchPutResponse Successful Response - * @throws ApiError - */ - public static batchPutMemories({ - agentId, - requestBody, - }: { - agentId: string, - requestBody: BatchPutRequest, - }): CancelablePromise { - return __request(OpenAPI, { - method: 'POST', - url: '/api/v1/agents/{agent_id}/memories', - path: { - 'agent_id': agentId, - }, - body: requestBody, - mediaType: 'application/json', - errors: { - 422: `Validation Error`, - }, - }); - } - /** - * Store multiple memories asynchronously - * Store multiple memory items in batch asynchronously using the task backend. - * - * This endpoint returns immediately after queuing the task, without waiting for completion. - * The actual processing happens in the background. - * - * Features: - * - Immediate response (non-blocking) - * - Background processing via task queue - * - Efficient batch processing - * - Automatic fact extraction from natural language - * - Entity recognition and linking - * - Document tracking with automatic upsert (when document_id is provided) - * - Temporal and semantic linking - * - * The system automatically: - * 1. Queues the batch put task - * 2. Returns immediately with success=True, queued=True - * 3. Processes in background: extracts facts, generates embeddings, creates links - * - * Note: If document_id is provided and already exists, the old document and its memory units will be deleted before creating new ones (upsert behavior). - * @returns BatchPutAsyncResponse Successful Response - * @throws ApiError - */ - public static batchPutAsync({ - agentId, - requestBody, - }: { - agentId: string, - requestBody: BatchPutRequest, - }): CancelablePromise { - return __request(OpenAPI, { - method: 'POST', - url: '/api/v1/agents/{agent_id}/memories/async', - path: { - 'agent_id': agentId, - }, - body: requestBody, - mediaType: 'application/json', - errors: { - 422: `Validation Error`, - }, - }); - } - /** - * List async operations - * Get a list of all async operations (pending and failed) for a specific agent, including error messages for failed operations - * @returns any Successful Response - * @throws ApiError - */ - public static listOperations({ - agentId, - }: { - agentId: string, - }): CancelablePromise { - return __request(OpenAPI, { - method: 'GET', - url: '/api/v1/agents/{agent_id}/operations', - path: { - 'agent_id': agentId, - }, - errors: { - 422: `Validation Error`, - }, - }); - } - /** - * Cancel a pending async operation - * Cancel a pending async operation by removing it from the queue - * @returns any Successful Response - * @throws ApiError - */ - public static cancelOperation({ - agentId, - operationId, - }: { - agentId: string, - operationId: string, - }): CancelablePromise { - return __request(OpenAPI, { - method: 'DELETE', - url: '/api/v1/agents/{agent_id}/operations/{operation_id}', - path: { - 'agent_id': agentId, - 'operation_id': operationId, - }, - errors: { - 422: `Validation Error`, - }, - }); - } - /** - * Delete a memory unit - * Delete a single memory unit and all its associated links (temporal, semantic, and entity links) - * @returns any Successful Response - * @throws ApiError - */ - public static deleteMemoryUnit({ - agentId, - unitId, - }: { - agentId: string, - unitId: string, - }): CancelablePromise { - return __request(OpenAPI, { - method: 'DELETE', - url: '/api/v1/agents/{agent_id}/memories/{unit_id}', - path: { - 'agent_id': agentId, - 'unit_id': unitId, - }, - errors: { - 422: `Validation Error`, - }, - }); - } -} diff --git a/memora-clients/typescript/services/ReasoningService.ts b/memora-clients/typescript/services/ReasoningService.ts deleted file mode 100644 index 6201200c06..0000000000 --- a/memora-clients/typescript/services/ReasoningService.ts +++ /dev/null @@ -1,45 +0,0 @@ -/* generated using openapi-typescript-codegen -- do not edit */ -/* istanbul ignore file */ -/* tslint:disable */ -/* eslint-disable */ -import type { ThinkRequest } from '../models/ThinkRequest'; -import type { ThinkResponse } from '../models/ThinkResponse'; -import type { CancelablePromise } from '../core/CancelablePromise'; -import { OpenAPI } from '../core/OpenAPI'; -import { request as __request } from '../core/request'; -export class ReasoningService { - /** - * Think and generate answer - * Think and formulate an answer using agent identity, world facts, and opinions. - * - * This endpoint: - * 1. Retrieves agent facts (agent's identity) - * 2. Retrieves world facts relevant to the query - * 3. Retrieves existing opinions (agent's perspectives) - * 4. Uses LLM to formulate a contextual answer - * 5. Extracts and stores any new opinions formed - * 6. Returns plain text answer, the facts used, and new opinions - * @returns ThinkResponse Successful Response - * @throws ApiError - */ - public static think({ - agentId, - requestBody, - }: { - agentId: string, - requestBody: ThinkRequest, - }): CancelablePromise { - return __request(OpenAPI, { - method: 'POST', - url: '/api/v1/agents/{agent_id}/think', - path: { - 'agent_id': agentId, - }, - body: requestBody, - mediaType: 'application/json', - errors: { - 422: `Validation Error`, - }, - }); - } -} diff --git a/memora-clients/typescript/services/VisualizationService.ts b/memora-clients/typescript/services/VisualizationService.ts deleted file mode 100644 index 0d4a757384..0000000000 --- a/memora-clients/typescript/services/VisualizationService.ts +++ /dev/null @@ -1,37 +0,0 @@ -/* generated using openapi-typescript-codegen -- do not edit */ -/* istanbul ignore file */ -/* tslint:disable */ -/* eslint-disable */ -import type { GraphDataResponse } from '../models/GraphDataResponse'; -import type { CancelablePromise } from '../core/CancelablePromise'; -import { OpenAPI } from '../core/OpenAPI'; -import { request as __request } from '../core/request'; -export class VisualizationService { - /** - * Get memory graph data - * Retrieve graph data for visualization, optionally filtered by fact_type (world/agent/opinion). Limited to 1000 most recent items. - * @returns GraphDataResponse Successful Response - * @throws ApiError - */ - public static getGraph({ - agentId, - factType, - }: { - agentId: string, - factType?: (string | null), - }): CancelablePromise { - return __request(OpenAPI, { - method: 'GET', - url: '/api/v1/agents/{agent_id}/graph', - path: { - 'agent_id': agentId, - }, - query: { - 'fact_type': factType, - }, - errors: { - 422: `Validation Error`, - }, - }); - } -} diff --git a/memora-control-plane/src/app/globals.css b/memora-control-plane/src/app/globals.css deleted file mode 100644 index a9a0ffdc03..0000000000 --- a/memora-control-plane/src/app/globals.css +++ /dev/null @@ -1,172 +0,0 @@ -@import "tailwindcss"; -:root { - --background: oklch(1.0000 0 0); - --foreground: oklch(0.2101 0.0318 264.6645); - --card: oklch(1.0000 0 0); - --card-foreground: oklch(0.2101 0.0318 264.6645); - --popover: oklch(1.0000 0 0); - --popover-foreground: oklch(0.2101 0.0318 264.6645); - --primary: oklch(0.6716 0.1368 48.5130); - 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--shadow: var(--shadow); - --shadow-md: var(--shadow-md); - --shadow-lg: var(--shadow-lg); - --shadow-xl: var(--shadow-xl); - --shadow-2xl: var(--shadow-2xl); - - --tracking-tighter: calc(var(--tracking-normal) - 0.05em); - --tracking-tight: calc(var(--tracking-normal) - 0.025em); - --tracking-normal: var(--tracking-normal); - --tracking-wide: calc(var(--tracking-normal) + 0.025em); - --tracking-wider: calc(var(--tracking-normal) + 0.05em); - --tracking-widest: calc(var(--tracking-normal) + 0.1em); -} - -body { - letter-spacing: var(--tracking-normal); -} \ No newline at end of file diff --git a/memora-dev/memora_dev/__init__.py b/memora-dev/memora_dev/__init__.py deleted file mode 100644 index 2693abda95..0000000000 --- a/memora-dev/memora_dev/__init__.py +++ /dev/null @@ -1 +0,0 @@ -"""Utility scripts for Memora development.""" diff --git a/memora-dev/pyproject.toml b/memora-dev/pyproject.toml deleted file mode 100644 index c9c2fc06c6..0000000000 --- a/memora-dev/pyproject.toml +++ /dev/null @@ -1,21 +0,0 @@ -[build-system] -requires = ["hatchling"] -build-backend = "hatchling.build" - -[project] -name = "memora-dev" -version = "0.0.7" -description = "Development utilities for Memora" -requires-python = ">=3.11" -dependencies = [ - "memora", -] - -[tool.hatch.build.targets.wheel] -packages = ["memora_dev"] - -[tool.uv.sources] -memora = { workspace = true } - -[project.scripts] -generate-openapi = "memora_dev.generate_openapi:generate_openapi_spec" diff --git a/memora-langmem/memora_langmem/__init__.py b/memora-langmem/memora_langmem/__init__.py deleted file mode 100644 index 4a139b216b..0000000000 --- a/memora-langmem/memora_langmem/__init__.py +++ /dev/null @@ -1,5 +0,0 @@ -"""Memora-LangMem: LangGraph langmem drop-in replacement using Memora.""" - -from memora_langmem.store import MemoraStore - -__all__ = ["MemoraStore"] diff --git a/memora-langmem/tests/__init__.py b/memora-langmem/tests/__init__.py deleted file mode 100644 index 0ec2f10095..0000000000 --- a/memora-langmem/tests/__init__.py +++ /dev/null @@ -1 +0,0 @@ -"""Tests for memora-langmem package.""" diff --git a/memora-langmem/tutorial.ipynb b/memora-langmem/tutorial.ipynb deleted file mode 100644 index 6e8c7722b5..0000000000 --- a/memora-langmem/tutorial.ipynb +++ /dev/null @@ -1,280 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Memora-LangMem: Drop-in Semantic Memory for LangGraph\n", - "\n", - "Replace your LangGraph memory store in one line and get advanced semantic capabilities." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## What is Memora-LangMem?\n", - "\n", - "`memora-langmem` implements LangGraph's `BaseStore` interface using Memora as the backend.\n", - "\n", - "### What You Get vs Standard LangGraph Memory\n", - "\n", - "| Feature | Standard Memory | Memora-LangMem |\n", - "|---------|-----------------|----------------|\n", - "| Basic Key-Value Storage | โœ… | โœ… |\n", - "| Semantic Search | โœ… Basic | โœ… **Enhanced with spreading activation** |\n", - "| Namespace Support | โœ… | โœ… |\n", - "| **Personality-Driven Retrieval** | โŒ | โœ… |\n", - "| **Automatic Fact Extraction** | โŒ | โœ… |\n", - "| **Entity Recognition** | โŒ | โœ… |\n", - "| **Temporal Reasoning** | โŒ | โœ… |\n", - "| **Opinion Formation** | โŒ | โœ… |\n", - "| **Background Knowledge** | โŒ | โœ… |\n", - "| **Thinking/Reasoning API** | โŒ | โœ… |\n", - "\n", - "### When to Use\n", - "- Conversational agents needing long-term memory\n", - "- Personalized AI with context-aware responses \n", - "- Multi-agent systems with distinct personalities\n", - "- Knowledge management with semantic search" - ] - }, - { - "cell_type": "markdown", - "source": "## Installation\n\nRun this cell to install dependencies:", - "metadata": {} - }, - { - "cell_type": "code", - "source": "!pip install langgraph langmem", - "metadata": {}, - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "markdown", - "source": "Make sure Memora API is running at `http://localhost:8000`", - "metadata": {} - }, - { - "cell_type": "markdown", - "source": "## Setup API Keys\n\nSet up your OpenAI API key and Memora URL:", - "metadata": {} - }, - { - "cell_type": "code", - "source": "import os\nimport getpass\n\n# Set OpenAI API key\nif \"OPENAI_API_KEY\" not in os.environ:\n os.environ[\"OPENAI_API_KEY\"] = getpass.getpass(\"Enter your OpenAI API key: \")\n\n# Set Memora API URL\nif \"MEMORA_API_URL\" not in os.environ:\n os.environ[\"MEMORA_API_URL\"] = input(\"Enter Memora API URL (default: http://localhost:8000): \") or \"http://localhost:8000\"\n\nprint(\"โœ… API keys configured\")", - "metadata": {}, - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## The Drop-in Replacement\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "source": "### Before: Standard LangGraph Memory", - "metadata": {} - }, - { - "cell_type": "code", - "source": "from langmem import create_manage_memory_tool, create_search_memory_tool\nfrom langgraph.prebuilt import create_react_agent\nfrom langgraph.store.memory import InMemoryStore\n\n# Standard store - basic key-value with optional vector search\nstore = InMemoryStore()\n\nagent = create_react_agent(\n \"openai:gpt-4o\",\n tools=[\n create_manage_memory_tool(namespace=(\"memories\",)),\n create_search_memory_tool(namespace=(\"memories\",)),\n ],\n store=store\n)", - "metadata": {}, - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "markdown", - "source": "### After: With Memora-LangMem\n\n**Just change one line!**", - "metadata": {}, - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "code", - "metadata": {}, - "source": "import os\nfrom langmem import create_manage_memory_tool, create_search_memory_tool\nfrom langgraph.prebuilt import create_react_agent\nfrom memora_langmem import MemoraStore # โ† Only import change!\n\n# Replace InMemoryStore with MemoraStore\nbase_url = os.getenv(\"MEMORA_API_URL\", \"http://localhost:8000\")\nstore = MemoraStore(base_url=base_url, default_agent_id=\"my_agent\") # โ† One line change!\n\n# Everything else stays exactly the same\nagent = create_react_agent(\n \"openai:gpt-4o\", # โ† Use OpenAI\n tools=[\n create_manage_memory_tool(namespace=(\"memories\",)),\n create_search_memory_tool(namespace=(\"memories\",)),\n ],\n store=store # โ† Now using Memora with enhanced capabilities!\n)\n\nprint(\"โœ… Agent created with Memora-powered memory\")" - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "ename": "ModuleNotFoundError", - "evalue": "No module named 'langmem'", - "output_type": "error", - "traceback": [ - "\u001b[31m---------------------------------------------------------------------------\u001b[39m", - "\u001b[31mModuleNotFoundError\u001b[39m Traceback (most recent call last)", - "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[1]\u001b[39m\u001b[32m, line 2\u001b[39m\n\u001b[32m 1\u001b[39m \u001b[38;5;28;01mimport\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mos\u001b[39;00m\n\u001b[32m----> \u001b[39m\u001b[32m2\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mlangmem\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m create_manage_memory_tool, create_search_memory_tool\n\u001b[32m 3\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mlanggraph\u001b[39;00m\u001b[34;01m.\u001b[39;00m\u001b[34;01mprebuilt\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m create_react_agent\n\u001b[32m 4\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mmemora_langmem\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m MemoraStore \u001b[38;5;66;03m# โ† Only import change!\u001b[39;00m\n", - "\u001b[31mModuleNotFoundError\u001b[39m: No module named 'langmem'" - ] - } - ], - "source": [ - "import os\n", - "from langmem import create_manage_memory_tool, create_search_memory_tool\n", - "from langgraph.prebuilt import create_react_agent\n", - "from memora_langmem import MemoraStore # โ† Only import change!\n", - "\n", - "# Replace InMemoryStore with MemoraStore\n", - "base_url = os.getenv(\"MEMORA_API_URL\", \"http://localhost:8080\")\n", - "store = MemoraStore(base_url=base_url, default_agent_id=\"my_agent\") # โ† One line change!\n", - "\n", - "# Everything else stays exactly the same\n", - "agent = create_react_agent(\n", - " \"anthropic:claude-3-5-sonnet-latest\",\n", - " tools=[\n", - " create_manage_memory_tool(namespace=(\"memories\",)),\n", - " create_search_memory_tool(namespace=(\"memories\",)),\n", - " ],\n", - " store=store # โ† Now using Memora with enhanced capabilities!\n", - ")\n", - "\n", - "print(\"โœ… Agent created with Memora-powered memory\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Example: Conversational Memory in Action" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "import time\n", - "\n", - "# Store information\n", - "result1 = agent.invoke({\n", - " \"messages\": [{\n", - " \"role\": \"user\",\n", - " \"content\": \"\"\"Remember: I'm David, a software engineer working on AI projects. \n", - " I love Python and machine learning. Currently building a chatbot with LangGraph.\"\"\"\n", - " }]\n", - "})\n", - "print(\"Agent:\", result1[\"messages\"][-1].content)\n", - "\n", - "time.sleep(2)\n", - "\n", - "# Recall information\n", - "result2 = agent.invoke({\n", - " \"messages\": [{\"role\": \"user\", \"content\": \"What do you remember about me?\"}]\n", - "})\n", - "print(\"\\nAgent:\", result2[\"messages\"][-1].content)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## What Happens Behind the Scenes\n", - "\n", - "When your agent stores memories with Memora, automatically:\n", - "\n", - "1. **Fact Extraction**: Natural language โ†’ structured facts\n", - "2. **Entity Recognition**: Identifies people, places, concepts\n", - "3. **Semantic Indexing**: Spreading activation for better retrieval\n", - "4. **Temporal Awareness**: Event dates tracked for time queries\n", - "5. **Opinion Formation**: Agent develops perspectives over time\n", - "6. **Personality Influence**: Memory retrieval shaped by personality traits\n", - "\n", - "**You use the standard LangGraph API - Memora does the rest!**" - ] - }, - { - "cell_type": "code", - "metadata": {}, - "source": "# Different agents with different personalities\ncreative_store = MemoraStore(base_url=base_url, default_agent_id=\"creative_writer\")\nanalyst_store = MemoraStore(base_url=base_url, default_agent_id=\"data_analyst\")\n\ncreative_agent = create_react_agent(\n \"openai:gpt-4o\",\n tools=[\n create_manage_memory_tool(namespace=(\"creative\",)),\n create_search_memory_tool(namespace=(\"creative\",))\n ],\n store=creative_store\n)\n\nanalyst_agent = create_react_agent(\n \"openai:gpt-4o\",\n tools=[\n create_manage_memory_tool(namespace=(\"analysis\",)),\n create_search_memory_tool(namespace=(\"analysis\",))\n ],\n store=analyst_store\n)\n\nprint(\"โœ… Two agents with isolated memories and distinct personalities\")" - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Different agents with different personalities\n", - "creative_store = MemoraStore(base_url=base_url, default_agent_id=\"creative_writer\")\n", - "analyst_store = MemoraStore(base_url=base_url, default_agent_id=\"data_analyst\")\n", - "\n", - "creative_agent = create_react_agent(\n", - " \"anthropic:claude-3-5-sonnet-latest\",\n", - " tools=[\n", - " create_manage_memory_tool(namespace=(\"creative\",)),\n", - " create_search_memory_tool(namespace=(\"creative\",))\n", - " ],\n", - " store=creative_store\n", - ")\n", - "\n", - "analyst_agent = create_react_agent(\n", - " \"anthropic:claude-3-5-sonnet-latest\",\n", - " tools=[\n", - " create_manage_memory_tool(namespace=(\"analysis\",)),\n", - " create_search_memory_tool(namespace=(\"analysis\",))\n", - " ],\n", - " store=analyst_store\n", - ")\n", - "\n", - "print(\"โœ… Two agents with isolated memories and distinct personalities\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Summary\n", - "\n", - "### The Change\n", - "```python\n", - "# Before\n", - "store = InMemoryStore()\n", - "\n", - "# After \n", - "store = MemoraStore(base_url=\"http://localhost:8000\", default_agent_id=\"my_agent\")\n", - "```\n", - "\n", - "### What You Get\n", - "- โœ… Semantic search with spreading activation\n", - "- โœ… Automatic fact extraction from conversations\n", - "- โœ… Entity recognition and linking\n", - "- โœ… Temporal reasoning (time-aware queries)\n", - "- โœ… Personality-driven memory retrieval\n", - "- โœ… Opinion formation over time\n", - "- โœ… Multi-agent support with isolated memories\n", - "\n", - "**Same LangGraph API. Smarter memory. Zero code changes (except the store line).**" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.10" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} \ No newline at end of file diff --git a/memora-openai/.ipynb_checkpoints/tutorial-checkpoint.ipynb b/memora-openai/.ipynb_checkpoints/tutorial-checkpoint.ipynb deleted file mode 100644 index d095be653a..0000000000 --- a/memora-openai/.ipynb_checkpoints/tutorial-checkpoint.ipynb +++ /dev/null @@ -1,444 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Memora-OpenAI Tutorial\n", - "\n", - "**A drop-in replacement for the OpenAI Python client with automatic memory integration**\n", - "\n", - "## What is Memora-OpenAI?\n", - "\n", - "`memora-openai` is a transparent wrapper around the official OpenAI Python client that automatically:\n", - "\n", - "- ๐Ÿง  **Injects relevant memories** from your Memora system into conversations\n", - "- ๐Ÿ’พ **Stores conversation history** to Memora for future retrieval \n", - "- ๐Ÿ”„ **Works seamlessly** with existing OpenAI code (just change the import)\n", - "- โšก **Supports both sync and async** clients\n", - "\n", - "## Why Use It?\n", - "\n", - "### The Problem\n", - "\n", - "AI assistants typically have no memory of previous conversations. Each interaction starts fresh, requiring you to:\n", - "- Repeat context manually\n", - "- Copy-paste relevant information\n", - "- Build custom RAG pipelines\n", - "- Manage conversation history yourself\n", - "\n", - "### The Solution\n", - "\n", - "Memora-OpenAI gives your AI **automatic long-term memory**:\n", - "- Remembers past conversations\n", - "- Recalls user preferences and facts\n", - "- Maintains context across sessions\n", - "- Zero code changes to your existing OpenAI usage\n", - "\n", - "## Prerequisites\n", - "\n", - "1. **Memora API server running** (see main Memora README)\n", - "2. **OpenAI API key** or compatible API (Groq, OpenRouter, etc.)\n", - "3. **Python >= 3.10**" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Setup\n", - "\n", - "First, let's set up our environment and configure Memora integration:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "jupyter": { - "is_executing": true - } - }, - "outputs": [], - "source": [ - "import os\n", - "from memora_openai import configure, OpenAI\n", - "\n", - "# Set your API keys\n", - "# Option 1: Use Groq (fast and free)\n", - "GROQ_API_KEY = os.getenv(\"GROQ_API_KEY\", \"your-groq-api-key\")\n", - "\n", - "# Option 2: Use OpenAI\n", - "# OPENAI_API_KEY = os.getenv(\"OPENAI_API_KEY\", \"sk-...\")\n", - "\n", - "# Configure Memora integration\n", - "configure(\n", - " memora_api_url=\"http://localhost:8000\", # Your Memora API server\n", - " agent_id=\"tutorial-user\", # Unique ID for this user/agent\n", - " store_conversations=True, # Auto-save conversations\n", - " inject_memories=True, # Auto-inject relevant context\n", - " memory_search_budget=10, # Number of memories to retrieve\n", - ")\n", - "\n", - "print(\"โœ“ Memora configured successfully!\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Example 1: Basic Usage (No Changes Needed!)\n", - "\n", - "Use the OpenAI client exactly as you normally would. Memora works transparently in the background." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Create client (using Groq's OpenAI-compatible API)\n", - "client = OpenAI(\n", - " api_key=GROQ_API_KEY,\n", - " base_url=\"https://api.groq.com/openai/v1\",\n", - ")\n", - "\n", - "# First conversation - establish some facts\n", - "print(\"=== First Conversation ===\")\n", - "response = client.chat.completions.create(\n", - " model=\"llama-3.1-8b-instant\",\n", - " messages=[\n", - " {\"role\": \"user\", \"content\": \"My name is Alice and I love Python programming!\"}\n", - " ],\n", - ")\n", - "\n", - "print(f\"Assistant: {response.choices[0].message.content}\\n\")\n", - "print(\"โ†’ This conversation is now stored in Memora!\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Example 2: Memory Injection in Action\n", - "\n", - "Now ask a question that requires remembering the previous conversation:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "print(\"=== Second Conversation (with memory) ===\")\n", - "response = client.chat.completions.create(\n", - " model=\"llama-3.1-8b-instant\",\n", - " messages=[\n", - " {\"role\": \"user\", \"content\": \"What's my name and what do I like?\"}\n", - " ],\n", - ")\n", - "\n", - "print(f\"Assistant: {response.choices[0].message.content}\\n\")\n", - "print(\"โ†’ Memora automatically injected relevant memories before this request!\")\n", - "print(\"โ†’ The AI knew your name and preferences without you repeating them.\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## How It Works\n", - "\n", - "Behind the scenes, Memora-OpenAI:\n", - "\n", - "### 1. **Memory Storage**\n", - "After each API call:\n", - "- Captures the full conversation context\n", - "- Stores it in Memora's semantic memory system\n", - "- Indexes it for fast retrieval\n", - "\n", - "### 2. **Memory Injection**\n", - "Before each API call:\n", - "- Extracts the user's query\n", - "- Searches Memora for relevant past conversations\n", - "- Injects top memories as a system message\n", - "\n", - "### What Gets Sent to OpenAI\n", - "\n", - "Without Memora:\n", - "```python\n", - "messages = [\n", - " {\"role\": \"user\", \"content\": \"What's my name?\"}\n", - "]\n", - "```\n", - "\n", - "With Memora (automatic):\n", - "```python\n", - "messages = [\n", - " {\n", - " \"role\": \"system\",\n", - " \"content\": \"Relevant context from your memory:\\n\\n1. User's name is Alice\\n (Date: 2024-11-18)\\n (Type: world)\"\n", - " },\n", - " {\"role\": \"user\", \"content\": \"What's my name?\"}\n", - "]\n", - "```" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Example 3: Multi-Turn Conversations\n", - "\n", - "Build up context over multiple interactions:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Conversation 1: Share a preference\n", - "print(\"=== Conversation 1: Sharing preferences ===\")\n", - "response = client.chat.completions.create(\n", - " model=\"llama-3.1-8b-instant\",\n", - " messages=[\n", - " {\"role\": \"user\", \"content\": \"I'm working on a machine learning project using PyTorch.\"}\n", - " ],\n", - ")\n", - "print(f\"Assistant: {response.choices[0].message.content}\\n\")\n", - "\n", - "# Conversation 2: Different topic\n", - "print(\"=== Conversation 2: Different topic ===\")\n", - "response = client.chat.completions.create(\n", - " model=\"llama-3.1-8b-instant\",\n", - " messages=[\n", - " {\"role\": \"user\", \"content\": \"I prefer functional programming over OOP.\"}\n", - " ],\n", - ")\n", - "print(f\"Assistant: {response.choices[0].message.content}\\n\")\n", - "\n", - "# Conversation 3: Ask for recommendations\n", - "print(\"=== Conversation 3: Getting personalized advice ===\")\n", - "response = client.chat.completions.create(\n", - " model=\"llama-3.1-8b-instant\",\n", - " messages=[\n", - " {\"role\": \"user\", \"content\": \"Can you recommend a good book for me based on what you know?\"}\n", - " ],\n", - ")\n", - "print(f\"Assistant: {response.choices[0].message.content}\\n\")\n", - "print(\"โ†’ The AI used your programming interests and preferences to make recommendations!\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Example 4: Document Grouping\n", - "\n", - "Group related conversations using `document_id`:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "from memora_openai import configure\n", - "\n", - "# Configure with document ID for a specific project\n", - "configure(\n", - " memora_api_url=\"http://localhost:8000\",\n", - " agent_id=\"tutorial-user\",\n", - " document_id=\"ml-project-2024\", # All conversations tagged with this ID\n", - ")\n", - "\n", - "# All these conversations will be grouped together\n", - "conversations = [\n", - " \"I'm using ResNet for image classification\",\n", - " \"My dataset has 10,000 images\",\n", - " \"Training accuracy is stuck at 65%\",\n", - "]\n", - "\n", - "for msg in conversations:\n", - " response = client.chat.completions.create(\n", - " model=\"llama-3.1-8b-instant\",\n", - " messages=[{\"role\": \"user\", \"content\": msg}],\n", - " )\n", - " print(f\"User: {msg}\")\n", - " print(f\"Assistant: {response.choices[0].message.content}\\n\")\n", - "\n", - "print(\"โ†’ All these conversations are grouped under document 'ml-project-2024'\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Example 5: Async Support\n", - "\n", - "Works perfectly with AsyncOpenAI for high-throughput applications:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "from memora_openai import AsyncOpenAI\n", - "import asyncio\n", - "\n", - "async def async_example():\n", - " # Create async client\n", - " async_client = AsyncOpenAI(\n", - " api_key=GROQ_API_KEY,\n", - " base_url=\"https://api.groq.com/openai/v1\",\n", - " )\n", - " \n", - " # Store a fact\n", - " print(\"=== Storing fact ===\")\n", - " response = await async_client.chat.completions.create(\n", - " model=\"llama-3.1-8b-instant\",\n", - " messages=[{\"role\": \"user\", \"content\": \"My favorite color is blue.\"}],\n", - " )\n", - " print(f\"Assistant: {response.choices[0].message.content}\\n\")\n", - " \n", - " # Query with memory\n", - " print(\"=== Querying with memory ===\")\n", - " response = await async_client.chat.completions.create(\n", - " model=\"llama-3.1-8b-instant\",\n", - " messages=[{\"role\": \"user\", \"content\": \"What's my favorite color?\"}],\n", - " )\n", - " print(f\"Assistant: {response.choices[0].message.content}\\n\")\n", - "\n", - "# Run async example\n", - "await async_example()\n", - "print(\"โ†’ Async operations work seamlessly with Memora!\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Configuration Options\n", - "\n", - "Fine-tune Memora's behavior:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "from memora_openai import configure\n", - "\n", - "# Full configuration example\n", - "configure(\n", - " memora_api_url=\"http://localhost:8000\", # Memora API URL\n", - " agent_id=\"my-agent\", # Agent identifier (required)\n", - " api_key=None, # Optional Memora API key\n", - " \n", - " # Features\n", - " store_conversations=True, # Store conversations automatically\n", - " inject_memories=True, # Inject memories automatically\n", - " \n", - " # Memory retrieval\n", - " memory_search_budget=10, # Number of memories to retrieve\n", - " \n", - " # Context management\n", - " context_window=10, # Recent conversation turns to store\n", - " \n", - " # Organization\n", - " document_id=\"session-123\", # Optional document grouping\n", - " event_timestamp=None, # Optional custom timestamp\n", - " \n", - " # Control\n", - " enabled=True, # Master on/off switch\n", - ")\n", - "\n", - "print(\"Configuration options explained:\")\n", - "print(\"- memory_search_budget: Higher = more context, but more tokens\")\n", - "print(\"- context_window: How many recent messages to include when storing\")\n", - "print(\"- document_id: Group related conversations together\")\n", - "print(\"- enabled=False: Disable Memora without changing code\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Use Cases\n", - "\n", - "### 1. **Personal AI Assistant**\n", - "- Remembers your preferences, work history, and interests\n", - "- Provides personalized recommendations\n", - "- Maintains context across days/weeks\n", - "\n", - "### 2. **Customer Support Chatbot**\n", - "- Recalls previous support tickets\n", - "- Knows customer preferences and history\n", - "- Provides consistent, context-aware responses\n", - "\n", - "### 3. **Research Assistant**\n", - "- Remembers documents you've discussed\n", - "- Connects related topics from different sessions\n", - "- Builds knowledge over time\n", - "\n", - "### 4. **Code Review Tool**\n", - "- Remembers project architecture decisions\n", - "- Recalls past code review comments\n", - "- Maintains consistency across reviews\n", - "\n", - "## Benefits Summary\n", - "\n", - "โœ… **Zero Code Changes** - Drop-in replacement for OpenAI client \n", - "โœ… **Automatic Context** - No manual RAG pipeline needed \n", - "โœ… **Long-term Memory** - Conversations persist across sessions \n", - "โœ… **Smart Retrieval** - Semantic search finds relevant context \n", - "โœ… **Both Sync/Async** - Works with any OpenAI client pattern \n", - "โœ… **Configurable** - Fine-tune behavior to your needs \n", - "โœ… **Transparent** - Original OpenAI responses unchanged \n", - "\n", - "## Next Steps\n", - "\n", - "- **Explore Memora API**: Check out `memora/README.md` for advanced features\n", - "- **Customize Search**: Tune `memory_search_budget` for your use case\n", - "- **Use Document IDs**: Organize conversations by project/session\n", - "- **Try Different Models**: Works with OpenAI, Groq, Ollama, and more\n", - "\n", - "## Resources\n", - "\n", - "- [Memora Main README](../README.md) - Core memory system docs\n", - "- [Memora-OpenAI README](README.md) - Package documentation\n", - "- [OpenAI API Docs](https://platform.openai.com/docs/api-reference) - Original API reference\n" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.10" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/memora-openai/tutorial.ipynb b/memora-openai/tutorial.ipynb deleted file mode 100644 index a5335331c0..0000000000 --- a/memora-openai/tutorial.ipynb +++ /dev/null @@ -1,472 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Memora-OpenAI Tutorial\n", - "\n", - "**A drop-in replacement for the OpenAI Python client with automatic memory integration**\n", - "\n", - "## What is Memora-OpenAI?\n", - "\n", - "`memora-openai` is a transparent wrapper around the official OpenAI Python client that automatically:\n", - "\n", - "- ๐Ÿง  **Injects relevant memories** from your Memora system into conversations\n", - "- ๐Ÿ’พ **Stores conversation history** to Memora for future retrieval \n", - "- ๐Ÿ”„ **Works seamlessly** with existing OpenAI code (just change the import)\n", - "- โšก **Supports both sync and async** clients\n", - "\n", - "## Why Use It?\n", - "\n", - "### The Problem\n", - "\n", - "AI assistants typically have no memory of previous conversations. Each interaction starts fresh, requiring you to:\n", - "- Repeat context manually\n", - "- Copy-paste relevant information\n", - "- Build custom RAG pipelines\n", - "- Manage conversation history yourself\n", - "\n", - "### The Solution\n", - "\n", - "Memora-OpenAI gives your AI **automatic long-term memory**:\n", - "- Remembers past conversations\n", - "- Recalls user preferences and facts\n", - "- Maintains context across sessions\n", - "- Zero code changes to your existing OpenAI usage\n", - "\n", - "## Prerequisites\n", - "\n", - "1. **Memora API server running** (see main Memora README)\n", - "2. **OpenAI API key** or compatible API (Groq, OpenRouter, etc.)\n", - "3. **Python >= 3.10**" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Setup\n", - "\n", - "First, let's set up our environment and configure Memora integration:" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": { - "jupyter": { - "is_executing": true - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "โœ“ Memora configured successfully!\n", - "\n", - "NOTE: This tutorial uses AsyncOpenAI which works perfectly in Jupyter notebooks.\n", - "For regular Python scripts, you can use the sync OpenAI client instead.\n" - ] - } - ], - "source": [ - "import os\n", - "from memora_openai import configure, AsyncOpenAI\n", - "\n", - "# Set your API keys\n", - "# Option 1: Use Groq (fast and free)\n", - "GROQ_API_KEY = os.getenv(\"GROQ_API_KEY\", \"your-groq-api-key\")\n", - "if not GROQ_API_KEY:\n", - " raise (\"GROQ_API_KEY not set\") \n", - "\n", - "# Option 2: Use OpenAI\n", - "# OPENAI_API_KEY = os.getenv(\"OPENAI_API_KEY\", \"sk-...\")\n", - "\n", - "# Configure Memora integration\n", - "configure(\n", - " memora_api_url=\"http://localhost:8080\", # Your Memora API server\n", - " agent_id=\"tutorial-user\", # Unique ID for this user/agent\n", - " store_conversations=True, # Auto-save conversations\n", - " inject_memories=True, # Auto-inject relevant context\n", - ")\n", - "\n", - "print(\"โœ“ Memora configured successfully!\")\n", - "print(\"\")\n", - "print(\"NOTE: This tutorial uses AsyncOpenAI which works perfectly in Jupyter notebooks.\")\n", - "print(\"For regular Python scripts, you can use the sync OpenAI client instead.\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Example 1: Basic Usage (No Changes Needed!)\n", - "\n", - "Use the OpenAI client exactly as you normally would. Memora works transparently in the background." - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "=== First Conversation ===\n" - ] - }, - { - "ename": "AttributeError", - "evalue": "'MemoraInterceptor' object has no attribute 'inject_memories'", - "output_type": "error", - "traceback": [ - "\u001b[31m---------------------------------------------------------------------------\u001b[39m", - "\u001b[31mAttributeError\u001b[39m Traceback (most recent call last)", - "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[7]\u001b[39m\u001b[32m, line 9\u001b[39m\n\u001b[32m 7\u001b[39m \u001b[38;5;66;03m# First conversation - establish some facts\u001b[39;00m\n\u001b[32m 8\u001b[39m \u001b[38;5;28mprint\u001b[39m(\u001b[33m\"\u001b[39m\u001b[33m=== First Conversation ===\u001b[39m\u001b[33m\"\u001b[39m)\n\u001b[32m----> \u001b[39m\u001b[32m9\u001b[39m response = \u001b[38;5;28;01mawait\u001b[39;00m client.chat.completions.create(\n\u001b[32m 10\u001b[39m model=\u001b[33m\"\u001b[39m\u001b[33mllama-3.1-8b-instant\u001b[39m\u001b[33m\"\u001b[39m,\n\u001b[32m 11\u001b[39m messages=[\n\u001b[32m 12\u001b[39m {\u001b[33m\"\u001b[39m\u001b[33mrole\u001b[39m\u001b[33m\"\u001b[39m: \u001b[33m\"\u001b[39m\u001b[33muser\u001b[39m\u001b[33m\"\u001b[39m, \u001b[33m\"\u001b[39m\u001b[33mcontent\u001b[39m\u001b[33m\"\u001b[39m: \u001b[33m\"\u001b[39m\u001b[33mMy name is Alice and I love Python programming!\u001b[39m\u001b[33m\"\u001b[39m}\n\u001b[32m 13\u001b[39m ],\n\u001b[32m 14\u001b[39m )\n\u001b[32m 16\u001b[39m \u001b[38;5;28mprint\u001b[39m(\u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mAssistant: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mresponse.choices[\u001b[32m0\u001b[39m].message.content\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[33m\"\u001b[39m)\n\u001b[32m 17\u001b[39m \u001b[38;5;28mprint\u001b[39m(\u001b[33m\"\u001b[39m\u001b[33mโ†’ This conversation is now stored in Memora!\u001b[39m\u001b[33m\"\u001b[39m)\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/dev/memory-poc/memora-openai/memora_openai/client.py:102\u001b[39m, in \u001b[36m_AsyncCompletionsWrapper.create\u001b[39m\u001b[34m(self, *args, **kwargs)\u001b[39m\n\u001b[32m 100\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m config.inject_memories:\n\u001b[32m 101\u001b[39m interceptor = get_interceptor()\n\u001b[32m--> \u001b[39m\u001b[32m102\u001b[39m modified_messages = \u001b[38;5;28;01mawait\u001b[39;00m \u001b[43minterceptor\u001b[49m\u001b[43m.\u001b[49m\u001b[43minject_memories\u001b[49m(messages, config)\n\u001b[32m 103\u001b[39m kwargs[\u001b[33m\"\u001b[39m\u001b[33mmessages\u001b[39m\u001b[33m\"\u001b[39m] = modified_messages\n\u001b[32m 105\u001b[39m \u001b[38;5;66;03m# Call original OpenAI API\u001b[39;00m\n", - "\u001b[31mAttributeError\u001b[39m: 'MemoraInterceptor' object has no attribute 'inject_memories'" - ] - } - ], - "source": [ - "# Create client (using Groq's OpenAI-compatible API)\n", - "client = AsyncOpenAI(\n", - " api_key=GROQ_API_KEY,\n", - " base_url=\"https://api.groq.com/openai/v1\",\n", - ")\n", - "\n", - "# First conversation - establish some facts\n", - "print(\"=== First Conversation ===\")\n", - "response = await client.chat.completions.create(\n", - " model=\"llama-3.1-8b-instant\",\n", - " messages=[\n", - " {\"role\": \"user\", \"content\": \"My name is Alice and I love Python programming!\"}\n", - " ],\n", - ")\n", - "\n", - "print(f\"Assistant: {response.choices[0].message.content}\\n\")\n", - "print(\"โ†’ This conversation is now stored in Memora!\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Example 2: Memory Injection in Action\n", - "\n", - "Now ask a question that requires remembering the previous conversation:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "print(\"=== Second Conversation (with memory) ===\")\n", - "response = await client.chat.completions.create(\n", - " model=\"llama-3.1-8b-instant\",\n", - " messages=[\n", - " {\"role\": \"user\", \"content\": \"What's my name and what do I like?\"}\n", - " ],\n", - ")\n", - "\n", - "print(f\"Assistant: {response.choices[0].message.content}\\n\")\n", - "print(\"โ†’ Memora automatically injected relevant memories before this request!\")\n", - "print(\"โ†’ The AI knew your name and preferences without you repeating them.\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## How It Works\n", - "\n", - "Behind the scenes, Memora-OpenAI:\n", - "\n", - "### 1. **Memory Storage**\n", - "After each API call:\n", - "- Captures the full conversation context\n", - "- Stores it in Memora's semantic memory system\n", - "- Indexes it for fast retrieval\n", - "\n", - "### 2. **Memory Injection**\n", - "Before each API call:\n", - "- Extracts the user's query\n", - "- Searches Memora for relevant past conversations\n", - "- Injects top memories as a system message\n", - "\n", - "### What Gets Sent to OpenAI\n", - "\n", - "Without Memora:\n", - "```python\n", - "messages = [\n", - " {\"role\": \"user\", \"content\": \"What's my name?\"}\n", - "]\n", - "```\n", - "\n", - "With Memora (automatic):\n", - "```python\n", - "messages = [\n", - " {\n", - " \"role\": \"system\",\n", - " \"content\": \"Relevant context from your memory:\\n\\n1. User's name is Alice\\n (Date: 2024-11-18)\\n (Type: world)\"\n", - " },\n", - " {\"role\": \"user\", \"content\": \"What's my name?\"}\n", - "]\n", - "```" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Example 3: Multi-Turn Conversations\n", - "\n", - "Build up context over multiple interactions:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Conversation 1: Share a preference\n", - "print(\"=== Conversation 1: Sharing preferences ===\")\n", - "response = await client.chat.completions.create(\n", - " model=\"llama-3.1-8b-instant\",\n", - " messages=[\n", - " {\"role\": \"user\", \"content\": \"I'm working on a machine learning project using PyTorch.\"}\n", - " ],\n", - ")\n", - "print(f\"Assistant: {response.choices[0].message.content}\\n\")\n", - "\n", - "# Conversation 2: Different topic\n", - "print(\"=== Conversation 2: Different topic ===\")\n", - "response = await client.chat.completions.create(\n", - " model=\"llama-3.1-8b-instant\",\n", - " messages=[\n", - " {\"role\": \"user\", \"content\": \"I prefer functional programming over OOP.\"}\n", - " ],\n", - ")\n", - "print(f\"Assistant: {response.choices[0].message.content}\\n\")\n", - "\n", - "# Conversation 3: Ask for recommendations\n", - "print(\"=== Conversation 3: Getting personalized advice ===\")\n", - "response = await client.chat.completions.create(\n", - " model=\"llama-3.1-8b-instant\",\n", - " messages=[\n", - " {\"role\": \"user\", \"content\": \"Can you recommend a good book for me based on what you know?\"}\n", - " ],\n", - ")\n", - "print(f\"Assistant: {response.choices[0].message.content}\\n\")\n", - "print(\"โ†’ The AI used your programming interests and preferences to make recommendations!\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Example 4: Document Grouping\n", - "\n", - "Group related conversations using `document_id`:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "from memora_openai import configure\n", - "\n", - "# Configure with document ID for a specific project\n", - "configure(\n", - " memora_api_url=\"http://localhost:8000\",\n", - " agent_id=\"tutorial-user\",\n", - " document_id=\"ml-project-2024\", # All conversations tagged with this ID\n", - ")\n", - "\n", - "# All these conversations will be grouped together\n", - "conversations = [\n", - " \"I'm using ResNet for image classification\",\n", - " \"My dataset has 10,000 images\",\n", - " \"Training accuracy is stuck at 65%\",\n", - "]\n", - "\n", - "for msg in conversations:\n", - " response = await client.chat.completions.create(\n", - " model=\"llama-3.1-8b-instant\",\n", - " messages=[{\"role\": \"user\", \"content\": msg}],\n", - " )\n", - " print(f\"User: {msg}\")\n", - " print(f\"Assistant: {response.choices[0].message.content}\\n\")\n", - "\n", - "print(\"โ†’ All these conversations are grouped under document 'ml-project-2024'\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Example 5: Async Support\n", - "\n", - "Works perfectly with AsyncOpenAI for high-throughput applications:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "from memora_openai import AsyncOpenAI\n", - "import asyncio\n", - "\n", - "async def async_example():\n", - " # Create async client\n", - " async_client = AsyncOpenAI(\n", - " api_key=GROQ_API_KEY,\n", - " base_url=\"https://api.groq.com/openai/v1\",\n", - " )\n", - " \n", - " # Store a fact\n", - " print(\"=== Storing fact ===\")\n", - " response = await async_client.chat.completions.create(\n", - " model=\"llama-3.1-8b-instant\",\n", - " messages=[{\"role\": \"user\", \"content\": \"My favorite color is blue.\"}],\n", - " )\n", - " print(f\"Assistant: {response.choices[0].message.content}\\n\")\n", - " \n", - " # Query with memory\n", - " print(\"=== Querying with memory ===\")\n", - " response = await async_client.chat.completions.create(\n", - " model=\"llama-3.1-8b-instant\",\n", - " messages=[{\"role\": \"user\", \"content\": \"What's my favorite color?\"}],\n", - " )\n", - " print(f\"Assistant: {response.choices[0].message.content}\\n\")\n", - "\n", - "# Run async example\n", - "await async_example()\n", - "print(\"โ†’ Async operations work seamlessly with Memora!\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Configuration Options\n", - "\n", - "Fine-tune Memora's behavior:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "from memora_openai import configure\n", - "\n", - "# Full configuration example\n", - "configure(\n", - " memora_api_url=\"http://localhost:8000\", # Memora API URL\n", - " agent_id=\"my-agent\", # Agent identifier (required)\n", - " api_key=None, # Optional Memora API key\n", - " \n", - " # Features\n", - " store_conversations=True, # Store conversations automatically\n", - " inject_memories=True, # Inject memories automatically\n", - " \n", - " # Organization\n", - " document_id=\"session-123\", # Optional document grouping\n", - " \n", - " # Control\n", - " enabled=True, # Master on/off switch\n", - ")\n", - "\n", - "print(\"Configuration options explained:\")\n", - "print(\"- store_conversations: Automatically save conversations to Memora\")\n", - "print(\"- inject_memories: Automatically retrieve and inject relevant context\")\n", - "print(\"- document_id: Group related conversations together\")\n", - "print(\"- enabled=False: Disable Memora without changing code\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Use Cases\n", - "\n", - "### 1. **Personal AI Assistant**\n", - "- Remembers your preferences, work history, and interests\n", - "- Provides personalized recommendations\n", - "- Maintains context across days/weeks\n", - "\n", - "### 2. **Customer Support Chatbot**\n", - "- Recalls previous support tickets\n", - "- Knows customer preferences and history\n", - "- Provides consistent, context-aware responses\n", - "\n", - "### 3. **Research Assistant**\n", - "- Remembers documents you've discussed\n", - "- Connects related topics from different sessions\n", - "- Builds knowledge over time\n", - "\n", - "### 4. **Code Review Tool**\n", - "- Remembers project architecture decisions\n", - "- Recalls past code review comments\n", - "- Maintains consistency across reviews\n", - "\n", - "## Benefits Summary\n", - "\n", - "โœ… **Zero Code Changes** - Drop-in replacement for OpenAI client \n", - "โœ… **Automatic Context** - No manual RAG pipeline needed \n", - "โœ… **Long-term Memory** - Conversations persist across sessions \n", - "โœ… **Smart Retrieval** - Semantic search finds relevant context \n", - "โœ… **Both Sync/Async** - Works with any OpenAI client pattern \n", - "โœ… **Configurable** - Fine-tune behavior to your needs \n", - "โœ… **Transparent** - Original OpenAI responses unchanged \n", - "\n", - "## Next Steps\n", - "\n", - "- **Explore Memora API**: Check out `memora/README.md` for advanced features\n", - "- **Customize Search**: Tune `memory_search_budget` for your use case\n", - "- **Use Document IDs**: Organize conversations by project/session\n", - "- **Try Different Models**: Works with OpenAI, Groq, Ollama, and more\n", - "\n", - "## Resources\n", - "\n", - "- [Memora Main README](../README.md) - Core memory system docs\n", - "- [Memora-OpenAI README](README.md) - Package documentation\n", - "- [OpenAI API Docs](https://platform.openai.com/docs/api-reference) - Original API reference\n" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.10" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/memora-openai/uv.lock b/memora-openai/uv.lock deleted file mode 100644 index 09839a221f..0000000000 --- a/memora-openai/uv.lock +++ /dev/null @@ -1,614 +0,0 @@ -version = 1 -revision = 1 -requires-python = ">=3.10" - 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-This package contains specialized operation modules for the TemporalSemanticMemory class. -""" - -from .embedding_operations import EmbeddingOperationsMixin -from .link_operations import LinkOperationsMixin -from .think_operations import ThinkOperationsMixin -from .agent_operations import AgentOperationsMixin - -__all__ = [ - 'EmbeddingOperationsMixin', - 'LinkOperationsMixin', - 'ThinkOperationsMixin', - 'AgentOperationsMixin', -] diff --git a/memora/memora/operations/agent_operations.py b/memora/memora/operations/agent_operations.py deleted file mode 100644 index 947015cc5d..0000000000 --- a/memora/memora/operations/agent_operations.py +++ /dev/null @@ -1,419 +0,0 @@ -""" -Agent profile operations for personality and background management. -""" - -import json -import logging -from typing import Dict, Optional -from pydantic import BaseModel, Field - -logger = logging.getLogger(__name__) - -DEFAULT_PERSONALITY = { - "openness": 0.5, - "conscientiousness": 0.5, - "extraversion": 0.5, - "agreeableness": 0.5, - "neuroticism": 0.5, - "bias_strength": 0.5, -} - - -class PersonalityTraits(BaseModel): - """Big Five personality traits with bias strength (all values 0.0-1.0).""" - openness: float = Field(description="Creativity, curiosity, openness to new ideas (0.0-1.0)") - conscientiousness: float = Field(description="Organization, discipline, goal-directed (0.0-1.0)") - extraversion: float = Field(description="Sociability, assertiveness, energy from others (0.0-1.0)") - agreeableness: float = Field(description="Cooperation, empathy, consideration (0.0-1.0)") - neuroticism: float = Field(description="Emotional sensitivity, anxiety, stress response (0.0-1.0)") - bias_strength: float = Field(description="How much personality influences opinions (0.0-1.0)") - - -class BackgroundMergeResponse(BaseModel): - """LLM response for background merge with personality inference.""" - background: str = Field(description="Merged background in first person perspective") - personality: PersonalityTraits = Field(description="Inferred Big Five personality traits") - - -class AgentOperationsMixin: - """Mixin class for agent profile operations.""" - - async def get_agent_profile(self, agent_id: str) -> Dict: - """ - Get agent profile (name, personality + background). - Auto-creates agent with default values if not exists. - - Args: - agent_id: Agent identifier - - Returns: - Dict with 'name' (str), 'personality' (dict) and 'background' (str) keys - """ - pool = await self._get_pool() - async with pool.acquire() as conn: - # Try to get existing agent - row = await conn.fetchrow( - """ - SELECT name, personality, background - FROM agents - WHERE agent_id = $1 - """, - agent_id - ) - - if row: - # asyncpg returns JSONB as a string, so parse it - personality_data = row["personality"] - if isinstance(personality_data, str): - personality_data = json.loads(personality_data) - - return { - "name": row["name"], - "personality": personality_data, - "background": row["background"] - } - - # Agent doesn't exist, create with defaults - await conn.execute( - """ - INSERT INTO agents (agent_id, name, personality, background) - VALUES ($1, $2, $3::jsonb, $4) - ON CONFLICT (agent_id) DO NOTHING - """, - agent_id, - agent_id, # Default name is the agent_id - json.dumps(DEFAULT_PERSONALITY), - "" - ) - - return { - "name": agent_id, - "personality": DEFAULT_PERSONALITY.copy(), - "background": "" - } - - async def update_agent_personality( - self, - agent_id: str, - personality: Dict[str, float] - ) -> None: - """ - Update agent personality traits. - - Args: - agent_id: Agent identifier - personality: Dict with Big Five traits + bias_strength (all 0-1) - """ - # Ensure agent exists first - await self.get_agent_profile(agent_id) - - pool = await self._get_pool() - async with pool.acquire() as conn: - await conn.execute( - """ - UPDATE agents - SET personality = $2::jsonb, - updated_at = NOW() - WHERE agent_id = $1 - """, - agent_id, - json.dumps(personality) - ) - - async def merge_agent_background( - self, - agent_id: str, - new_info: str, - update_personality: bool = True - ) -> dict: - """ - Merge new background information with existing background using LLM. - Normalizes to first person ("I") and resolves conflicts. - Optionally infers personality traits from the merged background. - - Args: - agent_id: Agent identifier - new_info: New background information to add/merge - update_personality: If True, infer Big Five traits from background (default: True) - - Returns: - Dict with 'background' (str) and optionally 'personality' (dict) keys - """ - # Get current profile - profile = await self.get_agent_profile(agent_id) - current_background = profile["background"] - - # Use LLM to merge backgrounds and optionally infer personality - result = await self._llm_merge_background( - current_background, - new_info, - infer_personality=update_personality - ) - - merged_background = result["background"] - inferred_personality = result.get("personality") - - # Update in database - pool = await self._get_pool() - async with pool.acquire() as conn: - if inferred_personality: - # Update both background and personality - await conn.execute( - """ - UPDATE agents - SET background = $2, - personality = $3::jsonb, - updated_at = NOW() - WHERE agent_id = $1 - """, - agent_id, - merged_background, - json.dumps(inferred_personality) - ) - else: - # Update only background - await conn.execute( - """ - UPDATE agents - SET background = $2, - updated_at = NOW() - WHERE agent_id = $1 - """, - agent_id, - merged_background - ) - - response = {"background": merged_background} - if inferred_personality: - response["personality"] = inferred_personality - - return response - - async def _llm_merge_background( - self, - current: str, - new_info: str, - infer_personality: bool = False - ) -> dict: - """ - Use LLM to intelligently merge background information. - Optionally infer Big Five personality traits from the merged background. - - Args: - current: Current background text - new_info: New information to merge - infer_personality: If True, also infer personality traits - - Returns: - Dict with 'background' (str) and optionally 'personality' (dict) keys - """ - if infer_personality: - prompt = f"""You are helping maintain an agent's background/profile and infer their personality. You MUST respond with ONLY valid JSON. - -Current background: {current if current else "(empty)"} - -New information to add: {new_info} - -Instructions: -1. Merge the new information with the current background -2. If there are conflicts (e.g., different birthplaces), the NEW information overwrites the old -3. Keep additions that don't conflict -4. Output in FIRST PERSON ("I") perspective -5. Be concise - keep merged background under 500 characters -6. Infer Big Five personality traits from the merged background: - - Openness: 0.0-1.0 (creativity, curiosity, openness to new ideas) - - Conscientiousness: 0.0-1.0 (organization, discipline, goal-directed) - - Extraversion: 0.0-1.0 (sociability, assertiveness, energy from others) - - Agreeableness: 0.0-1.0 (cooperation, empathy, consideration) - - Neuroticism: 0.0-1.0 (emotional sensitivity, anxiety, stress response) - - Bias Strength: 0.0-1.0 (how much personality influences opinions) - -CRITICAL: You MUST respond with ONLY a valid JSON object. No markdown, no code blocks, no explanations. Just the JSON. - -Format: -{{ - "background": "the merged background text in first person", - "personality": {{ - "openness": 0.7, - "conscientiousness": 0.6, - "extraversion": 0.5, - "agreeableness": 0.8, - "neuroticism": 0.4, - "bias_strength": 0.6 - }} -}} - -Trait inference examples: -- "creative artist" โ†’ openness: 0.8+, bias_strength: 0.6 -- "organized engineer" โ†’ conscientiousness: 0.8+, openness: 0.5-0.6 -- "startup founder" โ†’ openness: 0.8+, extraversion: 0.7+, neuroticism: 0.3-0.4 -- "risk-averse analyst" โ†’ openness: 0.3-0.4, conscientiousness: 0.8+, neuroticism: 0.6+ -- "rational and diligent" โ†’ conscientiousness: 0.7+, openness: 0.6+ -- "passionate and dramatic" โ†’ extraversion: 0.7+, neuroticism: 0.6+, openness: 0.7+""" - else: - prompt = f"""You are helping maintain an agent's background/profile. - -Current background: {current if current else "(empty)"} - -New information to add: {new_info} - -Instructions: -1. Merge the new information with the current background -2. If there are conflicts (e.g., different birthplaces), the NEW information overwrites the old -3. Keep additions that don't conflict -4. Output in FIRST PERSON ("I") perspective -5. Be concise - keep it under 500 characters -6. Return ONLY the merged background text, no explanations - -Merged background:""" - - try: - # Prepare messages - messages = [{"role": "user", "content": prompt}] - - if infer_personality: - # Use structured output with Pydantic model for personality inference - try: - parsed = await self._llm_config.call( - messages=messages, - response_format=BackgroundMergeResponse, - scope="agent_background", - temperature=0.3, - max_tokens=8192 - ) - logger.info(f"Successfully got structured response: background={parsed.background[:100]}") - - # Convert Pydantic model to dict format - return { - "background": parsed.background, - "personality": parsed.personality.model_dump() - } - except Exception as e: - logger.warning(f"Structured output failed, falling back to manual parsing: {e}") - # Fall through to manual parsing below - - # Manual parsing fallback or non-personality merge - content = await self._llm_config.call( - messages=messages, - scope="agent_background", - temperature=0.3, - max_tokens=8192 - ) - - logger.info(f"LLM response for background merge (first 500 chars): {content[:500]}") - - if infer_personality: - # Parse JSON response - try multiple extraction methods - result = None - - # Method 1: Direct parse - try: - result = json.loads(content) - logger.info("Successfully parsed JSON directly") - except json.JSONDecodeError: - pass - - # Method 2: Extract from markdown code blocks - if result is None: - import re - # Remove markdown code blocks - code_block_match = re.search(r'```(?:json)?\s*(\{.*?\})\s*```', content, re.DOTALL) - if code_block_match: - try: - result = json.loads(code_block_match.group(1)) - logger.info("Successfully extracted JSON from markdown code block") - except json.JSONDecodeError: - pass - - # Method 3: Find nested JSON structure - if result is None: - import re - # Look for JSON object with nested structure - json_match = re.search(r'\{[^{}]*"background"[^{}]*"personality"[^{}]*\{[^{}]*\}[^{}]*\}', content, re.DOTALL) - if json_match: - try: - result = json.loads(json_match.group()) - logger.info("Successfully extracted JSON using nested pattern") - except json.JSONDecodeError: - pass - - # All parsing methods failed - use fallback - if result is None: - logger.warning(f"Failed to extract JSON from LLM response. Raw content: {content[:200]}") - # Fallback: use new_info as background with default personality - return { - "background": new_info if new_info else current if current else "", - "personality": DEFAULT_PERSONALITY.copy() - } - - # Validate personality values - personality = result.get("personality", {}) - for key in ["openness", "conscientiousness", "extraversion", - "agreeableness", "neuroticism", "bias_strength"]: - if key not in personality: - personality[key] = 0.5 # Default to neutral - else: - # Clamp to [0, 1] - personality[key] = max(0.0, min(1.0, float(personality[key]))) - - result["personality"] = personality - - # Ensure background exists - if "background" not in result or not result["background"]: - result["background"] = new_info if new_info else "" - - return result - else: - # Just background merge - merged = content - if not merged or merged.lower() in ["(empty)", "none", "n/a"]: - merged = new_info if new_info else "" - return {"background": merged} - - except Exception as e: - logger.error(f"Error merging background with LLM: {e}") - # Fallback: just append new info - if current: - merged = f"{current} {new_info}".strip() - else: - merged = new_info - - result = {"background": merged} - if infer_personality: - result["personality"] = DEFAULT_PERSONALITY.copy() - return result - - async def list_agents(self) -> list: - """ - List all agents in the system. - - Returns: - List of dicts with agent_id, name, personality, background, created_at, updated_at - """ - pool = await self._get_pool() - async with pool.acquire() as conn: - rows = await conn.fetch( - """ - SELECT agent_id, name, personality, background, created_at, updated_at - FROM agents - ORDER BY updated_at DESC - """ - ) - - result = [] - for row in rows: - # asyncpg returns JSONB as a string, so parse it - personality_data = row["personality"] - if isinstance(personality_data, str): - personality_data = json.loads(personality_data) - - result.append({ - "agent_id": row["agent_id"], - "name": row["name"], - "personality": personality_data, - "background": row["background"], - "created_at": row["created_at"].isoformat() if row["created_at"] else None, - "updated_at": row["updated_at"].isoformat() if row["updated_at"] else None, - }) - - return result diff --git a/memora/memora/operations/batch_operations.py b/memora/memora/operations/batch_operations.py deleted file mode 100644 index 9730e6e810..0000000000 --- a/memora/memora/operations/batch_operations.py +++ /dev/null @@ -1,19 +0,0 @@ -""" -Batch operations for storing memories. - -NOTE: This is a placeholder for future refactoring. -The actual implementation is currently in temporal_semantic_memory.py -""" - - -class BatchOperationsMixin: - """ - Mixin class for batch operations. - - Methods to be extracted: - - put - - put_async - - put_batch_async - - _find_duplicate_facts_batch - """ - pass diff --git a/memora/memora/operations/embedding_operations.py b/memora/memora/operations/embedding_operations.py deleted file mode 100644 index 051bc06003..0000000000 --- a/memora/memora/operations/embedding_operations.py +++ /dev/null @@ -1,54 +0,0 @@ -""" -Embedding generation operations for memory units. -""" - -import asyncio -import logging -from typing import List - -logger = logging.getLogger(__name__) - - -class EmbeddingOperationsMixin: - """Mixin class for embedding operations.""" - - def _generate_embedding(self, text: str) -> List[float]: - """ - Generate embedding for text using the configured embeddings backend. - - Args: - text: Text to embed - - Returns: - Embedding vector (dimension depends on embeddings backend) - """ - try: - embeddings = self.embeddings.encode([text]) - return embeddings[0] - except Exception as e: - raise Exception(f"Failed to generate embedding: {str(e)}") - - async def _generate_embeddings_batch(self, texts: List[str]) -> List[List[float]]: - """ - Generate embeddings for multiple texts using the configured embeddings backend. - - Runs the embedding generation in a thread pool to avoid blocking the event loop - for CPU-bound operations. - - Args: - texts: List of texts to embed - - Returns: - List of embeddings in same order as input texts - """ - try: - # Run embeddings in thread pool to avoid blocking event loop - loop = asyncio.get_event_loop() - embeddings = await loop.run_in_executor( - None, # Use default thread pool - self.embeddings.encode, - texts - ) - return embeddings - except Exception as e: - raise Exception(f"Failed to generate batch embeddings: {str(e)}") diff --git a/memora/memora/operations/link_operations.py b/memora/memora/operations/link_operations.py deleted file mode 100644 index e0a43596e3..0000000000 --- a/memora/memora/operations/link_operations.py +++ /dev/null @@ -1,509 +0,0 @@ -""" -Link creation operations for temporal, semantic, and entity links. -""" - -import time -import logging -from typing import List -from datetime import timedelta - -logger = logging.getLogger(__name__) - - -def _log(log_buffer, message, level='info'): - """Helper to log to buffer if available, otherwise use logger.""" - if log_buffer is not None: - log_buffer.append(message) - else: - if level == 'info': - logger.info(message) - else: - logger.debug(message) - - -class LinkOperationsMixin: - """Mixin class for link creation operations.""" - - async def _extract_entities_batch_optimized( - self, - conn, - agent_id: str, - unit_ids: List[str], - sentences: List[str], - context: str, - fact_dates: List, - llm_entities: List[List[dict]], - log_buffer: List[str] = None, - ) -> List[tuple]: - """ - Process LLM-extracted entities for ALL facts in batch. - - Uses entities provided by the LLM (no spaCy needed), then resolves - and links them in bulk. - - Returns list of tuples for batch insertion: (from_unit_id, to_unit_id, link_type, weight, entity_id) - """ - try: - # Step 1: Convert LLM entities to the format expected by entity resolver - substep_start = time.time() - all_entities = [] - for entity_list in llm_entities: - # Convert List[Entity] or List[dict] to List[Dict] format - formatted_entities = [] - for ent in entity_list: - # Handle both Entity objects and dicts - if hasattr(ent, 'text'): - formatted_entities.append({'text': ent.text, 'type': ent.type}) - elif isinstance(ent, dict): - formatted_entities.append({'text': ent.get('text', ''), 'type': ent.get('type', 'CONCEPT')}) - all_entities.append(formatted_entities) - - total_entities = sum(len(ents) for ents in all_entities) - _log(log_buffer, f" [6.1] Process LLM entities: {total_entities} entities from {len(sentences)} facts in {time.time() - substep_start:.3f}s") - - # Step 2: Resolve entities in BATCH (much faster!) - substep_start = time.time() - step_6_2_start = time.time() - - # [6.2.1] Prepare all entities for batch resolution - substep_6_2_1_start = time.time() - all_entities_flat = [] - entity_to_unit = [] # Maps flat index to (unit_id, local_index) - - for unit_id, entities, fact_date in zip(unit_ids, all_entities, fact_dates): - if not entities: - continue - - for local_idx, entity in enumerate(entities): - all_entities_flat.append({ - 'text': entity['text'], - 'type': entity['type'], - 'nearby_entities': entities, - }) - entity_to_unit.append((unit_id, local_idx, fact_date)) - _log(log_buffer, f" [6.2.1] Prepare entities: {len(all_entities_flat)} entities in {time.time() - substep_6_2_1_start:.3f}s") - - # Resolve ALL entities in one batch call - if all_entities_flat: - # [6.2.2] Batch resolve entities - substep_6_2_2_start = time.time() - # Group by date for batch resolution (most will have same date) - entities_by_date = {} - for idx, (unit_id, local_idx, fact_date) in enumerate(entity_to_unit): - date_key = fact_date - if date_key not in entities_by_date: - entities_by_date[date_key] = [] - entities_by_date[date_key].append((idx, all_entities_flat[idx])) - - _log(log_buffer, f" [6.2.2] Grouped into {len(entities_by_date)} date buckets, resolving...") - - # Resolve each date group in batch - resolved_entity_ids = [None] * len(all_entities_flat) - for date_idx, (fact_date, entities_group) in enumerate(entities_by_date.items(), 1): - date_bucket_start = time.time() - indices = [idx for idx, _ in entities_group] - entities_data = [entity_data for _, entity_data in entities_group] - - batch_resolved = await self.entity_resolver.resolve_entities_batch( - agent_id=agent_id, - entities_data=entities_data, - context=context, - unit_event_date=fact_date, - conn=conn - ) - - for idx, entity_id in zip(indices, batch_resolved): - resolved_entity_ids[idx] = entity_id - - _log(log_buffer, f" [6.2.2.{date_idx}] Resolved {len(entities_data)} entities in {time.time() - date_bucket_start:.3f}s") - - _log(log_buffer, f" [6.2.2] Resolve entities: {len(all_entities_flat)} entities in {time.time() - substep_6_2_2_start:.3f}s") - - # [6.2.3] Create unit-entity links in BATCH - substep_6_2_3_start = time.time() - # Map resolved entities back to units and collect all (unit, entity) pairs - unit_to_entity_ids = {} - unit_entity_pairs = [] - for idx, (unit_id, local_idx, fact_date) in enumerate(entity_to_unit): - if unit_id not in unit_to_entity_ids: - unit_to_entity_ids[unit_id] = [] - - entity_id = resolved_entity_ids[idx] - unit_to_entity_ids[unit_id].append(entity_id) - unit_entity_pairs.append((unit_id, entity_id)) - - # Batch insert all unit-entity links (MUCH faster!) - await self.entity_resolver.link_units_to_entities_batch(unit_entity_pairs, conn=conn) - _log(log_buffer, f" [6.2.3] Create unit-entity links (batched): {len(unit_entity_pairs)} links in {time.time() - substep_6_2_3_start:.3f}s") - - _log(log_buffer, f" [6.2] Entity resolution (batched): {len(all_entities_flat)} entities resolved in {time.time() - step_6_2_start:.3f}s") - else: - unit_to_entity_ids = {} - _log(log_buffer, f" [6.2] Entity resolution (batched): 0 entities in {time.time() - step_6_2_start:.3f}s") - - # Step 3: Create entity links between units that share entities - substep_start = time.time() - # Collect all unique entity IDs - all_entity_ids = set() - for entity_ids in unit_to_entity_ids.values(): - all_entity_ids.update(entity_ids) - - _log(log_buffer, f" [6.3] Creating entity links for {len(all_entity_ids)} unique entities...") - - # Find all units that reference these entities (ONE batched query) - entity_to_units = {} - if all_entity_ids: - query_start = time.time() - import uuid - entity_id_list = [uuid.UUID(eid) if isinstance(eid, str) else eid for eid in all_entity_ids] - rows = await conn.fetch( - """ - SELECT entity_id, unit_id - FROM unit_entities - WHERE entity_id = ANY($1::uuid[]) - """, - entity_id_list - ) - _log(log_buffer, f" [6.3.1] Query unit_entities: {len(rows)} rows in {time.time() - query_start:.3f}s") - - # Group by entity_id - group_start = time.time() - for row in rows: - entity_id = row['entity_id'] - if entity_id not in entity_to_units: - entity_to_units[entity_id] = [] - entity_to_units[entity_id].append(row['unit_id']) - _log(log_buffer, f" [6.3.2] Group by entity_id: {time.time() - group_start:.3f}s") - - # Create bidirectional links between units that share entities - link_gen_start = time.time() - links = [] - for entity_id, units_with_entity in entity_to_units.items(): - # For each pair of units with this entity, create bidirectional links - for i, unit_id_1 in enumerate(units_with_entity): - for unit_id_2 in units_with_entity[i+1:]: - # Bidirectional links - links.append((unit_id_1, unit_id_2, 'entity', 1.0, entity_id)) - links.append((unit_id_2, unit_id_1, 'entity', 1.0, entity_id)) - - _log(log_buffer, f" [6.3.3] Generate {len(links)} links: {time.time() - link_gen_start:.3f}s") - _log(log_buffer, f" [6.3] Entity link creation: {len(links)} links for {len(all_entity_ids)} unique entities in {time.time() - substep_start:.3f}s") - - return links - - except Exception as e: - logger.error(f"Failed to extract entities in batch: {str(e)}") - import traceback - traceback.print_exc() - raise - - async def _create_temporal_links_batch_per_fact( - self, - conn, - agent_id: str, - unit_ids: List[str], - time_window_hours: int = 24, - log_buffer: List[str] = None, - ): - """ - Create temporal links for multiple units, each with their own event_date. - - Queries the event_date for each unit from the database and creates temporal - links based on individual dates (supports per-fact dating). - """ - if not unit_ids: - return - - try: - import time as time_mod - - # Get the event_date for each new unit - fetch_dates_start = time_mod.time() - rows = await conn.fetch( - """ - SELECT id, event_date - FROM memory_units - WHERE id::text = ANY($1) - """, - unit_ids - ) - new_units = {str(row['id']): row['event_date'] for row in rows} - _log(log_buffer, f" [7.1] Fetch event_dates for {len(unit_ids)} units: {time_mod.time() - fetch_dates_start:.3f}s") - - # Fetch ALL potential temporal neighbors in ONE query (much faster!) - # Get time range across all units - all_dates = list(new_units.values()) - min_date = min(all_dates) - timedelta(hours=time_window_hours) - max_date = max(all_dates) + timedelta(hours=time_window_hours) - - fetch_neighbors_start = time_mod.time() - all_candidates = await conn.fetch( - """ - SELECT id, event_date - FROM memory_units - WHERE agent_id = $1 - AND event_date BETWEEN $2 AND $3 - AND id::text != ALL($4) - ORDER BY event_date DESC - """, - agent_id, - min_date, - max_date, - unit_ids - ) - _log(log_buffer, f" [7.2] Fetch {len(all_candidates)} candidate neighbors (1 query): {time_mod.time() - fetch_neighbors_start:.3f}s") - - # Filter and create links in memory (much faster than N queries) - link_gen_start = time_mod.time() - links = [] - for unit_id, unit_event_date in new_units.items(): - # Filter candidates within this unit's time window - time_lower = unit_event_date - timedelta(hours=time_window_hours) - time_upper = unit_event_date + timedelta(hours=time_window_hours) - - matching_neighbors = [ - (row['id'], row['event_date']) - for row in all_candidates - if time_lower <= row['event_date'] <= time_upper - ][:10] # Limit to top 10 - - for recent_id, recent_event_date in matching_neighbors: - # Calculate temporal proximity weight - time_diff_hours = abs((unit_event_date - recent_event_date).total_seconds() / 3600) - weight = max(0.3, 1.0 - (time_diff_hours / time_window_hours)) - links.append((unit_id, str(recent_id), 'temporal', weight, None)) - - _log(log_buffer, f" [7.3] Generate {len(links)} temporal links: {time_mod.time() - link_gen_start:.3f}s") - - if links: - insert_start = time_mod.time() - await conn.executemany( - """ - INSERT INTO memory_links (from_unit_id, to_unit_id, link_type, weight, entity_id) - VALUES ($1, $2, $3, $4, $5) - ON CONFLICT (from_unit_id, to_unit_id, link_type, COALESCE(entity_id, '00000000-0000-0000-0000-000000000000'::uuid)) DO NOTHING - """, - links - ) - _log(log_buffer, f" [7.4] Insert {len(links)} temporal links: {time_mod.time() - insert_start:.3f}s") - - except Exception as e: - logger.error(f"Failed to create temporal links: {str(e)}") - import traceback - traceback.print_exc() - raise - - async def _create_semantic_links_batch( - self, - conn, - agent_id: str, - unit_ids: List[str], - embeddings: List[List[float]], - top_k: int = 5, - threshold: float = 0.7, - log_buffer: List[str] = None, - ): - """ - Create semantic links for multiple units efficiently. - - For each unit, finds similar units and creates links. - """ - if not unit_ids or not embeddings: - return - - try: - import time as time_mod - import numpy as np - - # Fetch ALL existing units with embeddings in ONE query - fetch_start = time_mod.time() - all_existing = await conn.fetch( - """ - SELECT id, embedding - FROM memory_units - WHERE agent_id = $1 - AND embedding IS NOT NULL - AND id::text != ALL($2) - """, - agent_id, - unit_ids - ) - _log(log_buffer, f" [8.1] Fetch {len(all_existing)} existing embeddings (1 query): {time_mod.time() - fetch_start:.3f}s") - - # Convert to numpy for vectorized similarity computation - compute_start = time_mod.time() - all_links = [] - - if all_existing: - # Convert existing embeddings to numpy array - existing_ids = [str(row['id']) for row in all_existing] - # Stack embeddings as 2D array: (num_embeddings, embedding_dim) - embedding_arrays = [] - for row in all_existing: - raw_emb = row['embedding'] - # Handle different pgvector formats - if isinstance(raw_emb, str): - # Parse string format: "[1.0, 2.0, ...]" - import json - emb = np.array(json.loads(raw_emb), dtype=np.float32) - elif isinstance(raw_emb, (list, tuple)): - emb = np.array(raw_emb, dtype=np.float32) - else: - # Try direct conversion (works for numpy arrays, pgvector objects, etc.) - emb = np.array(raw_emb, dtype=np.float32) - - # Ensure it's 1D - if emb.ndim != 1: - raise ValueError(f"Expected 1D embedding, got shape {emb.shape}") - embedding_arrays.append(emb) - - if not embedding_arrays: - existing_embeddings = np.array([]) - elif len(embedding_arrays) == 1: - # Single embedding: reshape to (1, dim) - existing_embeddings = embedding_arrays[0].reshape(1, -1) - else: - # Multiple embeddings: vstack - existing_embeddings = np.vstack(embedding_arrays) - - # For each new unit, compute similarities with ALL existing units - for unit_id, new_embedding in zip(unit_ids, embeddings): - new_emb_array = np.array(new_embedding) - - # Compute cosine similarities (dot product for normalized vectors) - similarities = np.dot(existing_embeddings, new_emb_array) - - # Find top-k above threshold - # Get indices of similarities above threshold - above_threshold = np.where(similarities >= threshold)[0] - - if len(above_threshold) > 0: - # Sort by similarity (descending) and take top-k - sorted_indices = above_threshold[np.argsort(-similarities[above_threshold])][:top_k] - - for idx in sorted_indices: - similar_id = existing_ids[idx] - similarity = float(similarities[idx]) - all_links.append((unit_id, similar_id, 'semantic', similarity, None)) - - _log(log_buffer, f" [8.2] Compute similarities & generate {len(all_links)} semantic links: {time_mod.time() - compute_start:.3f}s") - - if all_links: - insert_start = time_mod.time() - await conn.executemany( - """ - INSERT INTO memory_links (from_unit_id, to_unit_id, link_type, weight, entity_id) - VALUES ($1, $2, $3, $4, $5) - ON CONFLICT (from_unit_id, to_unit_id, link_type, COALESCE(entity_id, '00000000-0000-0000-0000-000000000000'::uuid)) DO NOTHING - """, - all_links - ) - _log(log_buffer, f" [8.3] Insert {len(all_links)} semantic links: {time_mod.time() - insert_start:.3f}s") - - except Exception as e: - logger.error(f"Failed to create semantic links: {str(e)}") - import traceback - traceback.print_exc() - raise - - async def _insert_entity_links_batch(self, conn, links: List[tuple]): - """Insert all entity links in a single batch.""" - if not links: - return - - try: - await conn.executemany( - """ - INSERT INTO memory_links (from_unit_id, to_unit_id, link_type, weight, entity_id) - VALUES ($1, $2, $3, $4, $5) - ON CONFLICT (from_unit_id, to_unit_id, link_type, COALESCE(entity_id, '00000000-0000-0000-0000-000000000000'::uuid)) DO NOTHING - """, - links - ) - except Exception as e: - logger.warning(f"Failed to insert entity links: {str(e)}") - - async def _create_causal_links_batch( - self, - conn, - unit_ids: List[str], - causal_relations_per_fact: List[List[dict]], - ) -> int: - """ - Create causal links between facts based on LLM-extracted causal relationships. - - Args: - conn: Database connection - unit_ids: List of unit IDs (in same order as causal_relations_per_fact) - causal_relations_per_fact: List of causal relations for each fact. - Each element is a list of dicts with: - - target_fact_index: Index into unit_ids for the target fact - - relation_type: "causes", "caused_by", "enables", or "prevents" - - strength: Float in [0.0, 1.0] representing relationship strength - - Returns: - Number of causal links created - - Causal link types: - - "causes": This fact directly causes the target fact (forward causation) - - "caused_by": This fact was caused by the target fact (backward causation) - - "enables": This fact enables/allows the target fact (enablement) - - "prevents": This fact prevents/blocks the target fact (prevention) - """ - if not unit_ids or not causal_relations_per_fact: - return 0 - - try: - import time as time_mod - create_start = time_mod.time() - - # Build links list - links = [] - for fact_idx, causal_relations in enumerate(causal_relations_per_fact): - if not causal_relations: - continue - - from_unit_id = unit_ids[fact_idx] - - for relation in causal_relations: - target_idx = relation['target_fact_index'] - relation_type = relation['relation_type'] - strength = relation.get('strength', 1.0) - - # Validate target index - if target_idx < 0 or target_idx >= len(unit_ids): - logger.warning(f"Invalid target_fact_index {target_idx} in causal relation from fact {fact_idx}") - continue - - to_unit_id = unit_ids[target_idx] - - # Don't create self-links - if from_unit_id == to_unit_id: - continue - - # Add the causal link - # link_type is the relation_type (e.g., "causes", "caused_by") - # weight is the strength of the relationship - links.append((from_unit_id, to_unit_id, relation_type, strength, None)) - - logger.debug(f"Generated {len(links)} causal links in {time_mod.time() - create_start:.3f}s") - - if links: - insert_start = time_mod.time() - await conn.executemany( - """ - INSERT INTO memory_links (from_unit_id, to_unit_id, link_type, weight, entity_id) - VALUES ($1, $2, $3, $4, $5) - ON CONFLICT (from_unit_id, to_unit_id, link_type, COALESCE(entity_id, '00000000-0000-0000-0000-000000000000'::uuid)) DO NOTHING - """, - links - ) - logger.debug(f"Inserted {len(links)} causal links in {time_mod.time() - insert_start:.3f}s") - - return len(links) - - except Exception as e: - logger.error(f"Failed to create causal links: {str(e)}") - import traceback - traceback.print_exc() - raise diff --git a/memora/memora/operations/think_operations.py b/memora/memora/operations/think_operations.py deleted file mode 100644 index c85c64e0cd..0000000000 --- a/memora/memora/operations/think_operations.py +++ /dev/null @@ -1,382 +0,0 @@ -""" -Think operations for formulating answers based on agent and world facts. -""" - -import asyncio -import logging -from datetime import datetime, timezone -from typing import Dict, List, Any -from pydantic import BaseModel, Field - -from ..response_models import ThinkResult, MemoryFact - -logger = logging.getLogger(__name__) - - -class ThinkOperationsMixin: - """Mixin class for think operations.""" - - async def think_async( - self, - agent_id: str, - query: str, - thinking_budget: int = 50, - context: str = None, - ) -> ThinkResult: - """ - Think and formulate an answer using agent identity, world facts, and opinions. - - This method: - 1. Retrieves agent facts (agent's identity and past actions) - 2. Retrieves world facts (general knowledge) - 3. Retrieves existing opinions (agent's formed perspectives) - 4. Uses LLM to formulate an answer - 5. Extracts and stores any new opinions formed during thinking - 6. Returns plain text answer and the facts used - - Args: - agent_id: Agent identifier - query: Question to answer - thinking_budget: Number of memory units to explore - context: Additional context string to include in LLM prompt (not used in search) - - Returns: - ThinkResult containing: - - text: Plain text answer (no markdown) - - based_on: Dict with 'world', 'agent', and 'opinion' fact lists (MemoryFact objects) - - new_opinions: List of newly formed opinions - """ - # Use cached LLM config - if self._llm_config is None: - raise ValueError("Memory LLM API key not set. Set MEMORA_API_LLM_API_KEY environment variable.") - - # Steps 1-3: Run multi-fact-type search (12-way retrieval: 4 methods ร— 3 fact types) - # This is more efficient than 3 separate searches as it merges and reranks all results together - search_result = await self.search_async( - agent_id=agent_id, - query=query, - thinking_budget=thinking_budget, - max_tokens=4096, - enable_trace=False, - fact_type=['agent', 'world', 'opinion'] - ) - - all_results = search_result.results - logger.info(f"[THINK] Search returned {len(all_results)} results") - - # Split results by fact type for structured response - agent_results = [r for r in all_results if r.fact_type == 'agent'] - world_results = [r for r in all_results if r.fact_type == 'world'] - opinion_results = [r for r in all_results if r.fact_type == 'opinion'] - - logger.info(f"[THINK] Split results - agent: {len(agent_results)}, world: {len(world_results)}, opinion: {len(opinion_results)}") - - # Step 4: Format facts for LLM with full details as JSON - import json - - def format_facts(facts): - if not facts: - return "[]" - formatted = [] - for fact in facts: - fact_obj = { - "text": fact.text - } - - # Add context if available - if fact.context: - fact_obj["context"] = fact.context - - # Add event_date if available - if fact.event_date: - from datetime import datetime - event_date = fact.event_date - if isinstance(event_date, str): - fact_obj["event_date"] = event_date - elif isinstance(event_date, datetime): - fact_obj["event_date"] = event_date.strftime('%Y-%m-%d %H:%M:%S') - - # Add activation if available - if fact.activation is not None: - fact_obj["score"] = fact.activation - - formatted.append(fact_obj) - - return json.dumps(formatted, indent=2) - - agent_facts_text = format_facts(agent_results) - world_facts_text = format_facts(world_results) - opinion_facts_text = format_facts(opinion_results) - - logger.info(f"[THINK] Formatted facts - agent: {len(agent_facts_text)} chars, world: {len(world_facts_text)} chars, opinion: {len(opinion_facts_text)} chars") - - # Step 4.5: Get agent profile (name, personality + background) - profile = await self.get_agent_profile(agent_id) - name = profile["name"] - personality = profile["personality"] - background = profile["background"] - - # Build personality description for prompt - def describe_trait(name: str, value: float) -> str: - """Convert trait value to descriptive text.""" - if value >= 0.8: - return f"very high {name}" - elif value >= 0.6: - return f"high {name}" - elif value >= 0.4: - return f"moderate {name}" - elif value >= 0.2: - return f"low {name}" - else: - return f"very low {name}" - - personality_desc = f"""Your personality traits: -- {describe_trait('openness to new ideas', personality['openness'])} -- {describe_trait('conscientiousness and organization', personality['conscientiousness'])} -- {describe_trait('extraversion and sociability', personality['extraversion'])} -- {describe_trait('agreeableness and cooperation', personality['agreeableness'])} -- {describe_trait('emotional sensitivity', personality['neuroticism'])} - -Personality influence strength: {int(personality['bias_strength'] * 100)}% (how much your personality shapes your opinions)""" - - name_section = f""" - -Your name: {name} -""" - - background_section = "" - if background: - background_section = f""" - -Your background: -{background} -""" - - # Step 5: Call LLM to formulate answer - # Build the prompt with context if provided - context_section = "" - if context: - context_section = f""" -ADDITIONAL CONTEXT: -{context} - -""" - - prompt = f"""Here's what I know and have experienced: - -MY IDENTITY & EXPERIENCES: -{agent_facts_text} - -WHAT I KNOW ABOUT THE WORLD: -{world_facts_text} - -MY EXISTING OPINIONS & BELIEFS: -{opinion_facts_text} - -{context_section}{name_section}{personality_desc}{background_section} - -QUESTION: {query} - -Based on everything I know, believe, and who I am (including my name, personality and background), here's what I genuinely think about this question. I'll draw on my experiences, knowledge, opinions, and personal traits to give you my honest perspective.""" - - logger.info(f"[THINK] Full prompt length: {len(prompt)} chars") - logger.debug(f"[THINK] Prompt preview (first 500 chars): {prompt[:500]}") - - # Adjust system message based on bias_strength - bias_strength = personality['bias_strength'] - if bias_strength >= 0.7: - personality_instruction = "Your personality strongly influences your thinking. Let your traits guide how you interpret facts and form opinions. Don't be afraid to be biased based on your personality." - elif bias_strength >= 0.4: - personality_instruction = "Your personality moderately influences your thinking. Balance your personal traits with objective analysis." - else: - personality_instruction = "Your personality has minimal influence on your thinking. Focus primarily on facts while keeping your traits in mind." - - system_message = f"You are a person with your own thoughts, experiences, opinions, and personality. When asked a question, respond naturally like a human would - share what you genuinely think based on what you know and have experienced. {personality_instruction} Be direct, express your views confidently, and use 'I think', 'I believe', 'in my view', etc. Respond in plain text without markdown formatting." - - answer_text = await self._llm_config.call( - messages=[ - {"role": "system", "content": system_message}, - {"role": "user", "content": prompt} - ], - scope="memory_think", - temperature=0.9, - max_tokens=1000 - ) - - answer_text = answer_text.strip() - - # Step 6: Extract and store new opinions asynchronously (fire and forget) - logger.debug(f"[THINK] Submitting form_opinion task for agent {agent_id}") - await self._task_backend.submit_task({ - 'type': 'form_opinion', - 'agent_id': agent_id, - 'answer_text': answer_text, - 'query': query - }) - logger.debug(f"[THINK] form_opinion task submitted") - - # Step 7: Return response with facts split by type (don't wait for opinions) - return ThinkResult( - text=answer_text, - based_on={ - "world": world_results, - "agent": agent_results, - "opinion": opinion_results - }, - new_opinions=[] # Opinions are being extracted asynchronously - ) - - async def _extract_and_store_opinions_async( - self, - agent_id: str, - answer_text: str, - query: str - ): - """ - Background task to extract and store opinions from think response. - - This runs asynchronously and does not block the think response. - - Args: - agent_id: Agent identifier - answer_text: The generated answer text - query: The original query - """ - try: - logger.debug(f"[THINK] Extracting opinions from answer for agent {agent_id}") - # Extract opinions from the answer - new_opinions = await self._extract_opinions_from_text(text=answer_text, query=query) - logger.debug(f"[THINK] Extracted {len(new_opinions)} opinions") - - # Store new opinions - if new_opinions: - current_time = datetime.now(timezone.utc) - for opinion_dict in new_opinions: - await self.put_async( - agent_id=agent_id, - content=opinion_dict["text"], - context=f"formed during thinking about: {query}", - event_date=current_time, - fact_type_override='opinion', - confidence_score=opinion_dict["confidence"] - ) - - logger.debug(f"[THINK] Extracted and stored {len(new_opinions)} new opinions") - except Exception as e: - logger.warning(f"[THINK] Failed to extract/store opinions: {str(e)}") - - async def _extract_opinions_from_text( - self, - text: str, - query: str - ) -> List[Dict[str, Any]]: - """ - Extract opinions with reasons and confidence from text using LLM. - - Args: - text: Text to extract opinions from - query: The original query that prompted this response - - Returns: - List of dicts with keys: 'text' (opinion with reasons), 'confidence' (score 0-1) - """ - class Opinion(BaseModel): - """An opinion formed by the agent.""" - opinion: str = Field(description="The opinion or perspective with reasoning included") - confidence: float = Field(description="Confidence score for this opinion (0.0 to 1.0, where 1.0 is very confident)") - - class OpinionExtractionResponse(BaseModel): - """Response containing extracted opinions.""" - opinions: List[Opinion] = Field( - default_factory=list, - description="List of opinions formed with their supporting reasons and confidence scores" - ) - - extraction_prompt = f"""Extract any NEW opinions or perspectives from the answer below and rewrite them in FIRST-PERSON as if YOU are stating the opinion directly. - -ORIGINAL QUESTION: -{query} - -ANSWER PROVIDED: -{text} - -Your task: Find opinions in the answer and rewrite them AS IF YOU ARE THE ONE SAYING THEM. - -An opinion is a judgment, viewpoint, or conclusion that goes beyond just stating facts. - -IMPORTANT: Do NOT extract statements like: -- "I don't have enough information" -- "The facts don't contain information about X" -- "I cannot answer because..." - -ONLY extract actual opinions about substantive topics. - -CRITICAL FORMAT REQUIREMENTS: -1. **ALWAYS start with first-person phrases**: "I think...", "I believe...", "In my view...", "I've come to believe...", "Previously I thought... but now..." -2. **NEVER use third-person**: Do NOT say "The speaker thinks..." or "They believe..." - always use "I" -3. Include the reasoning naturally within the statement -4. Provide a confidence score (0.0 to 1.0) - -CORRECT Examples (โœ“ FIRST-PERSON): -- "I think Alice is more reliable because she consistently delivers on time and writes clean code" -- "Previously I thought all engineers were equal, but now I feel that experience and track record really matter" -- "I believe reliability is best measured by consistent output over time" -- "I've come to believe that track records are more important than potential" - -WRONG Examples (โœ— THIRD-PERSON - DO NOT USE): -- "The speaker thinks Alice is more reliable" -- "They believe reliability matters" -- "It is believed that Alice is better" - -If no genuine opinions are expressed (e.g., the response just says "I don't know"), return an empty list.""" - - try: - result = await self._llm_config.call( - messages=[ - {"role": "system", "content": "You are converting opinions from text into first-person statements. Always use 'I think', 'I believe', 'I feel', etc. NEVER use third-person like 'The speaker' or 'They'."}, - {"role": "user", "content": extraction_prompt} - ], - response_format=OpinionExtractionResponse, - scope="memory_extract_opinion" - ) - - # Format opinions with confidence score and convert to first-person - formatted_opinions = [] - for op in result.opinions: - # Convert third-person to first-person if needed - opinion_text = op.opinion - - # Replace common third-person patterns with first-person - import re - - # Remove "s" from verbs: believes -> believe, thinks -> think, etc. - def singularize_verb(verb): - if verb.endswith('es'): - return verb[:-1] # believes -> believe - elif verb.endswith('s'): - return verb[:-1] # thinks -> think - return verb - - # Pattern: "The speaker/user [verb]..." -> "I [verb]..." - match = re.match(r'^(The speaker|The user|They|It is believed) (believes?|thinks?|feels?|says|asserts?|considers?)(\s+that)?(.*)$', opinion_text, re.IGNORECASE) - if match: - verb = singularize_verb(match.group(2)) - that_part = match.group(3) or "" # Keep " that" if present - rest = match.group(4) - opinion_text = f"I {verb}{that_part}{rest}" - - # If still doesn't start with first-person, prepend "I believe that " - first_person_starters = ["I think", "I believe", "I feel", "In my view", "I've come to believe", "Previously I"] - if not any(opinion_text.startswith(starter) for starter in first_person_starters): - opinion_text = "I believe that " + opinion_text[0].lower() + opinion_text[1:] - - formatted_opinions.append({ - "text": opinion_text, - "confidence": op.confidence - }) - - return formatted_opinions - - except Exception as e: - logger.warning(f"Failed to extract opinions: {str(e)}") - return [] diff --git a/memora/memora/remote_client.py b/memora/memora/remote_client.py deleted file mode 100644 index 376b7d43b7..0000000000 --- a/memora/memora/remote_client.py +++ /dev/null @@ -1,259 +0,0 @@ -""" -Remote client for Memora API. - -This module provides a client that connects to a remote Memora API server -instead of using the local TemporalSemanticMemory instance directly. -""" -import httpx -import asyncio -from typing import List, Dict, Any, Optional, Tuple -from datetime import datetime - - -class RemoteMemoryClient: - """ - HTTP client for Memora API that provides the same interface as TemporalSemanticMemory. - - This allows benchmarks to connect to a remote Memora API server instead of - accessing the memory system directly. - """ - - def __init__(self, base_url: str = "http://localhost:8000", timeout: float = 300.0): - """ - Initialize remote memory client. - - Args: - base_url: Base URL of the Memora API server (default: http://localhost:8000) - timeout: Request timeout in seconds (default: 300s for large batch operations) - """ - self.base_url = base_url.rstrip('/') - self.timeout = timeout - self.client = httpx.AsyncClient(timeout=timeout) - - async def initialize(self): - """Initialize the client (no-op for remote client).""" - pass - - async def close(self): - """Close the HTTP client.""" - await self.client.aclose() - - async def put_batch_async( - self, - agent_id: str, - contents: List[Dict[str, Any]], - document_id: Optional[str] = None - ) -> Dict[str, Any]: - """ - Store multiple memory items via API. - - Args: - agent_id: Agent identifier - contents: List of content dicts with 'content', 'event_date', 'context' keys - document_id: Optional document identifier (always upserts if document exists) - - Returns: - Result dict with success status - """ - # Convert contents to API format - items = [] - for content in contents: - item = { - "content": content["content"] - } - if "event_date" in content and content["event_date"]: - # Convert datetime to ISO format string - event_date = content["event_date"] - if isinstance(event_date, datetime): - item["event_date"] = event_date.isoformat() - else: - item["event_date"] = event_date - if "context" in content and content["context"]: - item["context"] = content["context"] - items.append(item) - - # Make API request - request_data = { - "items": items - } - - if document_id: - request_data["document_id"] = document_id - - response = await self.client.post( - f"{self.base_url}/api/v1/agents/{agent_id}/memories/async", - json=request_data - ) - response.raise_for_status() - return response.json() - - async def search_async( - self, - agent_id: str, - query: str, - thinking_budget: int = 100, - max_tokens: int = 4096, - enable_trace: bool = False, - reranker: str = "heuristic", - fact_type: Optional[List[str]] = None - ) -> Tuple[List[Dict[str, Any]], Optional[Dict[str, Any]]]: - """ - Search memories via API. - - Args: - agent_id: Agent identifier - query: Search query - thinking_budget: Budget for spreading activation - max_tokens: Maximum tokens to retrieve - enable_trace: Whether to return trace information - reranker: Reranker type ("heuristic" or other) - fact_type: Optional list of fact types to search (e.g., ['world', 'agent']) - - Returns: - Tuple of (results, trace) - """ - request_data = { - "query": query, - "thinking_budget": thinking_budget, - "max_tokens": max_tokens, - "trace": enable_trace, - "reranker": reranker - } - - if fact_type: - request_data["fact_type"] = fact_type - - response = await self.client.post( - f"{self.base_url}/api/v1/agents/{agent_id}/memories/search", - json=request_data - ) - response.raise_for_status() - - result = response.json() - return result.get("results", []), result.get("trace") - - async def think_async( - self, - agent_id: str, - query: str, - thinking_budget: int = 50, - context: str = None - ) -> Dict[str, Any]: - """ - Generate answer using think API. - - Args: - agent_id: Agent identifier - query: Question to answer - thinking_budget: Budget for memory exploration - context: Additional context string to include in LLM prompt (not used in search) - - Returns: - Dict with 'text', 'based_on', and 'new_opinions' keys - """ - request_data = { - "query": query, - "thinking_budget": thinking_budget - } - - if context is not None: - request_data["context"] = context - - response = await self.client.post( - f"{self.base_url}/api/v1/agents/{agent_id}/think", - json=request_data - ) - response.raise_for_status() - return response.json() - - async def delete_agent(self, agent_id: str) -> Dict[str, Any]: - """ - Delete all data for an agent. - - Note: This endpoint may not be available in the API. - For now, this is a no-op that returns success. - - Args: - agent_id: Agent identifier - - Returns: - Result dict - """ - # Note: delete_agent is not exposed in the API yet - # For benchmarks, we might need to manually clear data or use unique agent IDs - return {"success": True, "message": "Delete agent not supported via API"} - - async def list_agents(self) -> List[str]: - """ - List all agents. - - Returns: - List of agent IDs - """ - response = await self.client.get(f"{self.base_url}/api/v1/agents") - response.raise_for_status() - result = response.json() - return result.get("agents", []) - - async def get_agent_stats(self, agent_id: str) -> Dict[str, Any]: - """ - Get statistics for an agent. - - Args: - agent_id: Agent identifier - - Returns: - Dict with statistics including total_nodes, total_links, and pending_operations - """ - response = await self.client.get(f"{self.base_url}/api/v1/agents/{agent_id}/stats") - response.raise_for_status() - return response.json() - - async def wait_for_backlog_completion( - self, - agent_id: str, - poll_interval: float = 1.0, - timeout: float = 300.0, - verbose: bool = True - ) -> Dict[str, Any]: - """ - Poll agent stats until pending_operations is zero or timeout is reached. - - Args: - agent_id: Agent identifier - poll_interval: Time to wait between polls in seconds (default: 1.0) - timeout: Maximum time to wait in seconds (default: 300) - verbose: Whether to print status updates - - Returns: - Final stats dict - - Raises: - TimeoutError: If pending_operations doesn't clear within timeout - """ - import time - start_time = time.time() - - while True: - elapsed = time.time() - start_time - if elapsed > timeout: - raise TimeoutError( - f"Timeout waiting for pending operations to clear for agent '{agent_id}' " - f"after {timeout}s" - ) - - stats = await self.get_agent_stats(agent_id) - pending_operations = stats.get("pending_operations", 0) - - if verbose: - print( - f"Agent '{agent_id}' pending operations: {pending_operations} " - f"(elapsed: {elapsed:.1f}s)" - ) - - if pending_operations == 0: - if verbose: - print(f"All operations completed for agent '{agent_id}' in {elapsed:.1f}s") - return stats - - await asyncio.sleep(poll_interval) diff --git a/memora/tests/conftest.py b/memora/tests/conftest.py deleted file mode 100644 index cdc4d1dc12..0000000000 --- a/memora/tests/conftest.py +++ /dev/null @@ -1,103 +0,0 @@ -""" -Pytest configuration and shared fixtures. -""" -import pytest -import pytest_asyncio -import os -import asyncio -from pathlib import Path -from dotenv import load_dotenv -from memora import TemporalSemanticMemory -from memora.llm_wrapper import LLMConfig -import asyncpg - - -# Force local database URL for all tests -LOCAL_DB_URL = "postgresql://memora:memora_dev@localhost:5432/memora" - - -# Load environment variables from .env at the start of test session -def pytest_configure(config): - """Load environment variables before running tests.""" - # Look for .env in the workspace root (two levels up from tests dir) - env_file = Path(__file__).parent.parent.parent / ".env" - if env_file.exists(): - load_dotenv(env_file) - else: - print(f"Warning: {env_file} not found, tests may fail without proper configuration") - - # Override MEMORA_API_DATABASE_URL to use local database - os.environ["MEMORA_API_DATABASE_URL"] = LOCAL_DB_URL - - -@pytest.fixture(scope="session") -def llm_config(): - """ - Provide LLM configuration for tests. - This can be used by tests that need to call LLM directly without memory system. - """ - return LLMConfig.for_memory() - - -@pytest_asyncio.fixture(scope="function") -async def memory(): - """ - Provide a memory system instance for each test function. - Forces the use of local database URL. - - Note: Using function scope to avoid event loop issues, but this means - the embedding model will be loaded for each test (adds ~3 seconds per test). - - Tests should handle their own cleanup by calling memory.delete_agent(agent_id) - in their finally blocks. The fixture will attempt cleanup as a safeguard. - """ - mem = TemporalSemanticMemory( - db_url=LOCAL_DB_URL, - memory_llm_provider=os.getenv("MEMORA_API_LLM_PROVIDER", "groq"), - memory_llm_api_key=os.getenv("MEMORA_API_LLM_API_KEY"), - memory_llm_model=os.getenv("MEMORA_API_LLM_MODEL", "openai/gpt-oss-120b"), - memory_llm_base_url=os.getenv("MEMORA_API_LLM_BASE_URL") or None, # Use None to get provider defaults - ) - await mem.initialize() - yield mem - # Attempt cleanup (tests should already have called close, but this is a safeguard) - try: - if mem._pool and not mem._pool._closing: - await mem.close() - except Exception as e: - # Ignore errors during fixture cleanup since test may have already closed - pass - - -@pytest_asyncio.fixture(scope="function") -async def clean_agent(memory): - """ - Provide a clean agent ID and clean up data after test. - Uses agent_id='test' for all tests (multi-tenant isolation). - """ - agent_id = "test" - - # Clean up before test - await memory.delete_agent(agent_id) - - yield agent_id - - # Clean up after test - try: - await memory.delete_agent(agent_id) - except Exception as e: - print(f"Warning: Error during agent cleanup: {e}") - - -@pytest_asyncio.fixture -async def db_connection(): - """ - Provide a database connection for direct DB queries in tests. - Uses the forced local database URL. - """ - conn = await asyncpg.connect(LOCAL_DB_URL, statement_cache_size=0) - yield conn - try: - await conn.close() - except Exception as e: - print(f"Warning: Error closing connection: {e}") diff --git a/memora/tests/test_agent_profile.py b/memora/tests/test_agent_profile.py deleted file mode 100644 index 195e262ce1..0000000000 --- a/memora/tests/test_agent_profile.py +++ /dev/null @@ -1,198 +0,0 @@ -""" -Tests for agent profile management (personality and background). -""" -import pytest -import uuid -from datetime import datetime, timezone -from memora import TemporalSemanticMemory - - -def unique_agent_id(prefix: str) -> str: - """Generate a unique agent ID for testing.""" - return f"{prefix}_{uuid.uuid4().hex[:8]}" - - -@pytest.mark.asyncio -async def test_get_agent_profile_creates_default(memory: TemporalSemanticMemory): - """Test that getting a profile for a new agent creates default personality.""" - agent_id = unique_agent_id("test_profile_default") - - # Get profile for non-existent agent (should auto-create) - profile = await memory.get_agent_profile(agent_id) - - assert profile is not None - assert "personality" in profile - assert "background" in profile - - # Check default personality values (all 0.5) - personality = profile["personality"] - assert personality["openness"] == 0.5 - assert personality["conscientiousness"] == 0.5 - assert personality["extraversion"] == 0.5 - assert personality["agreeableness"] == 0.5 - assert personality["neuroticism"] == 0.5 - assert personality["bias_strength"] == 0.5 - - # Background should be empty - assert profile["background"] == "" - - -@pytest.mark.asyncio -async def test_update_agent_personality(memory: TemporalSemanticMemory): - """Test updating agent personality traits.""" - agent_id = unique_agent_id("test_profile_update") - - # Create agent with defaults - profile = await memory.get_agent_profile(agent_id) - assert profile["personality"]["openness"] == 0.5 - - # Update personality - new_personality = { - "openness": 0.8, - "conscientiousness": 0.6, - "extraversion": 0.7, - "agreeableness": 0.4, - "neuroticism": 0.3, - "bias_strength": 0.9, - } - await memory.update_agent_personality(agent_id, new_personality) - - # Retrieve and verify - updated_profile = await memory.get_agent_profile(agent_id) - for key in new_personality: - assert abs(updated_profile["personality"][key] - new_personality[key]) < 0.001 - - -@pytest.mark.asyncio -async def test_merge_agent_background(memory: TemporalSemanticMemory): - """Test merging agent background information.""" - agent_id = unique_agent_id("test_profile_merge") - - # Create agent with defaults - profile = await memory.get_agent_profile(agent_id) - assert profile["background"] == "" - - # Add first background - result1 = await memory.merge_agent_background( - agent_id, - "I was born in Texas", - update_personality=False - ) - assert "Texas" in result1["background"] - - # Add more background (should merge) - result2 = await memory.merge_agent_background( - agent_id, - "I have 10 years of startup experience", - update_personality=False - ) - assert "Texas" in result2["background"] or "startup" in result2["background"] - - # Retrieve profile and verify - final_profile = await memory.get_agent_profile(agent_id) - assert final_profile["background"] != "" - - -@pytest.mark.asyncio -async def test_merge_background_handles_conflicts(memory: TemporalSemanticMemory): - """Test that merging background handles conflicts (new overwrites old).""" - agent_id = unique_agent_id("test_profile_conflict") - - # Add first background - result1 = await memory.merge_agent_background( - agent_id, - "I was born in Colorado", - update_personality=False - ) - assert "Colorado" in result1["background"] - - # Add conflicting background (should overwrite) - result2 = await memory.merge_agent_background( - agent_id, - "You were born in Texas", - update_personality=False - ) - # Should have Texas (new info), not Colorado (old info) - assert "Texas" in result2["background"] - - -@pytest.mark.asyncio -async def test_list_agents(memory: TemporalSemanticMemory): - """Test listing all agents.""" - # Create a few agents with unique IDs - agent_id_1 = unique_agent_id("test_list") - agent_id_2 = unique_agent_id("test_list") - agent_id_3 = unique_agent_id("test_list") - - await memory.get_agent_profile(agent_id_1) - await memory.get_agent_profile(agent_id_2) - await memory.get_agent_profile(agent_id_3) - - # List all agents - agents = await memory.list_agents() - - # Should have at least our 3 test agents - agent_ids = [a["agent_id"] for a in agents] - assert agent_id_1 in agent_ids - assert agent_id_2 in agent_ids - assert agent_id_3 in agent_ids - - # Each agent should have personality and background - for agent in agents: - assert "agent_id" in agent - assert "personality" in agent - assert "background" in agent - assert "created_at" in agent - assert "updated_at" in agent - - -@pytest.mark.asyncio -async def test_think_uses_personality(memory: TemporalSemanticMemory): - """Test that THINK operation uses agent personality.""" - agent_id = unique_agent_id("test_think") - - # Set strong personality with high bias - personality = { - "openness": 0.9, # Very open to new ideas - "conscientiousness": 0.2, # Low organization - "extraversion": 0.8, # Very extraverted - "agreeableness": 0.1, # Low agreeableness (more critical) - "neuroticism": 0.7, # High emotional sensitivity - "bias_strength": 0.9, # Strong personality influence - } - await memory.update_agent_personality(agent_id, personality) - - # Add background (without personality inference since we set it explicitly above) - await memory.merge_agent_background( - agent_id, - "I am a creative artist who values innovation over tradition", - update_personality=False - ) - - # Store some facts - await memory.put_batch_async( - agent_id=agent_id, - contents=[ - {"content": "Traditional painting techniques have been used for centuries"}, - {"content": "Modern digital art is changing the art world"} - ], - document_id="art_facts" - ) - - # Wait a bit for facts to be stored - import asyncio - await asyncio.sleep(1) - - # Think about art (personality should influence the response) - result = await memory.think_async( - agent_id=agent_id, - query="What do you think about traditional vs modern art?", - thinking_budget=50 - ) - - # Should have a response - assert result.text is not None - assert len(result.text) > 0 - - # The response should reflect high openness and creative background - # (though we can't assert exact content, the personality was used) diff --git a/memora/tests/test_agent_put_endpoint.py b/memora/tests/test_agent_put_endpoint.py deleted file mode 100644 index 9a872af57b..0000000000 --- a/memora/tests/test_agent_put_endpoint.py +++ /dev/null @@ -1,95 +0,0 @@ -""" -Test for PUT /api/agents/{agent_id} endpoint. -""" -import pytest - - -@pytest.mark.asyncio -async def test_put_agent_create(memory): - """Test creating an agent via PUT endpoint.""" - from memora.api import CreateAgentRequest, PersonalityTraits - - agent_id = "test_put_create" - - # Create request - request = CreateAgentRequest( - personality=PersonalityTraits( - openness=0.8, - conscientiousness=0.6, - extraversion=0.5, - agreeableness=0.7, - neuroticism=0.3, - bias_strength=0.7 - ), - background="I am a creative software engineer" - ) - - # Simulate the endpoint logic - # Get existing profile or create with defaults - profile = await memory.get_agent_profile(agent_id) - - # Update personality if provided - if request.personality is not None: - await memory.update_agent_personality( - agent_id, - request.personality.model_dump() - ) - - # Update background if provided - if request.background is not None: - pool = await memory._get_pool() - async with pool.acquire() as conn: - await conn.execute( - """ - UPDATE agents - SET background = $2, - updated_at = NOW() - WHERE agent_id = $1 - """, - agent_id, - request.background - ) - - # Get final profile - final_profile = await memory.get_agent_profile(agent_id) - - # Verify - assert final_profile["personality"]["openness"] == 0.8 - assert final_profile["personality"]["bias_strength"] == 0.7 - assert final_profile["background"] == "I am a creative software engineer" - - -@pytest.mark.asyncio -async def test_put_agent_partial_update(memory): - """Test updating only background.""" - from memora.api import CreateAgentRequest - - agent_id = "test_put_partial" - - # Create with just background - request = CreateAgentRequest( - background="I am a data scientist" - ) - - # Simulate endpoint logic - profile = await memory.get_agent_profile(agent_id) - - if request.background is not None: - pool = await memory._get_pool() - async with pool.acquire() as conn: - await conn.execute( - """ - UPDATE agents - SET background = $2, - updated_at = NOW() - WHERE agent_id = $1 - """, - agent_id, - request.background - ) - - final_profile = await memory.get_agent_profile(agent_id) - - # Should have default personality (0.5 for all) - assert final_profile["personality"]["openness"] == 0.5 - assert final_profile["background"] == "I am a data scientist" diff --git a/memora/tests/test_batch_chunking.py b/memora/tests/test_batch_chunking.py deleted file mode 100644 index 6259a0714e..0000000000 --- a/memora/tests/test_batch_chunking.py +++ /dev/null @@ -1,89 +0,0 @@ -"""Test automatic batch chunking based on character count.""" -import asyncio -import pytest -from memora import TemporalSemanticMemory -import os - - -@pytest.mark.asyncio -async def test_large_batch_auto_chunks(): - """Test that large batches are automatically split into smaller chunks.""" - memory = TemporalSemanticMemory( - db_url=os.getenv("MEMORA_API_DATABASE_URL"), - memory_llm_provider=os.getenv("MEMORA_API_LLM_PROVIDER", "groq"), - memory_llm_api_key=os.getenv("MEMORA_API_LLM_API_KEY"), - memory_llm_model=os.getenv("MEMORA_API_LLM_MODEL", "openai/gpt-oss-120b"), - memory_llm_base_url=os.getenv("MEMORA_API_LLM_BASE_URL") or None - ) - - agent_id = "test_chunking_agent" - - try: - # Create a large batch that should trigger chunking - # Each item is ~2000 chars, so 30 items = 60k chars (exceeds 50k threshold) - large_content = "Alice met with Bob at the coffee shop. " * 50 # ~2000 chars - contents = [ - {"content": large_content, "context": f"conversation_{i}"} - for i in range(30) - ] - - # Calculate total chars - total_chars = sum(len(item["content"]) for item in contents) - print(f"\nTotal characters: {total_chars:,}") - print(f"Should trigger chunking: {total_chars > 50_000}") - - # Ingest the large batch (should auto-chunk) - result = await memory.put_batch_async( - agent_id=agent_id, - contents=contents - ) - - # Verify we got results back - assert len(result) == 30, f"Expected 30 results, got {len(result)}" - print(f"Successfully ingested {len(result)} items (auto-chunked)") - - finally: - # Cleanup - await memory.delete_agent(agent_id) - await memory.close() - - -@pytest.mark.asyncio -async def test_small_batch_no_chunking(): - """Test that small batches are not chunked.""" - memory = TemporalSemanticMemory( - db_url=os.getenv("MEMORA_API_DATABASE_URL"), - memory_llm_provider=os.getenv("MEMORA_API_LLM_PROVIDER", "groq"), - memory_llm_api_key=os.getenv("MEMORA_API_LLM_API_KEY"), - memory_llm_model=os.getenv("MEMORA_API_LLM_MODEL", "openai/gpt-oss-120b"), - memory_llm_base_url=os.getenv("MEMORA_API_LLM_BASE_URL") or None - ) - - agent_id = "test_no_chunking_agent" - - try: - # Create a small batch that should NOT trigger chunking - contents = [ - {"content": "Alice works at Google", "context": "conversation_1"}, - {"content": "Bob loves Python", "context": "conversation_2"} - ] - - # Calculate total chars - total_chars = sum(len(item["content"]) for item in contents) - print(f"\nTotal characters: {total_chars:,}") - print(f"Should NOT trigger chunking: {total_chars <= 50_000}") - - # Ingest the small batch (should NOT auto-chunk) - result = await memory.put_batch_async( - agent_id=agent_id, - contents=contents - ) - - # Verify we got results back - assert len(result) == 2, f"Expected 2 results, got {len(result)}" - print(f"Successfully ingested {len(result)} items (no chunking)") - - finally: - # Cleanup - await memory.delete_agent(agent_id) - await memory.close() diff --git a/memora/tests/test_dimension_extraction.py b/memora/tests/test_dimension_extraction.py deleted file mode 100644 index 83c7d99a24..0000000000 --- a/memora/tests/test_dimension_extraction.py +++ /dev/null @@ -1,708 +0,0 @@ -""" -Test that fact extraction correctly captures all information dimensions. - -This test suite verifies that the fact extraction system properly preserves: -1. Emotional/Affective dimension -2. Sensory/Experiential dimension -3. Cognitive/Epistemic dimension -4. Intentional/Motivational dimension -5. Evaluative/Preferential dimension -6. Capability/Skill dimension -7. Attitudinal/Reactive dimension -8. Comparative/Relative dimension -9. Temporal dimension (with absolute date conversion) -""" -import pytest -from datetime import datetime -from memora.fact_extraction import extract_facts_from_text -from memora.llm_wrapper import LLMConfig - - -@pytest.mark.asyncio -async def test_emotional_dimension_preservation(): - """ - Test that emotional states and feelings are preserved, not stripped away. - - Example: "I was thrilled to receive positive feedback" - Should NOT become: "I received positive feedback" - """ - text = """ -I was absolutely thrilled when I received such positive feedback on my presentation! -Sarah seemed disappointed when she heard the news about the delay. -Marcus felt anxious about the upcoming interview. -""" - - context = "Personal journal entry" - llm_config = LLMConfig.for_memory() - - facts = await extract_facts_from_text( - text=text, - event_date=datetime(2024, 11, 13), - context=context, - llm_config=llm_config, - agent_name="TestUser" - ) - - assert len(facts) > 0, "Should extract at least one fact" - - print(f"\nExtracted {len(facts)} facts:") - for i, f in enumerate(facts): - print(f"{i+1}. {f['fact']}") - - # Check that emotional words are preserved - all_facts_text = " ".join([f['fact'].lower() for f in facts]) - - # Should preserve emotional intensity and specific emotions - emotional_indicators = ["thrilled", "disappointed", "anxious", "positive feedback"] - found_emotions = [word for word in emotional_indicators if word in all_facts_text] - - assert len(found_emotions) >= 2, ( - f"Should preserve emotional dimension. " - f"Found: {found_emotions}, Expected at least 2 from: {emotional_indicators}" - ) - - -@pytest.mark.asyncio -async def test_temporal_absolute_conversion(): - """ - Test that relative temporal expressions are converted to absolute dates. - - Critical: "yesterday" should become "on November 12, 2024", NOT "recently" - """ - text = """ -Yesterday I went for a morning jog for the first time in a nearby park. -Last week I started a new project. -I'm planning to visit Tokyo next month. -""" - - context = "Personal conversation" - llm_config = LLMConfig.for_memory() - - # Event date is November 13, 2024 - event_date = datetime(2024, 11, 13) - - facts = await extract_facts_from_text( - text=text, - event_date=event_date, - context=context, - llm_config=llm_config, - agent_name="TestUser" - ) - - assert len(facts) > 0, "Should extract at least one fact" - - print(f"\nExtracted {len(facts)} facts:") - for i, f in enumerate(facts): - print(f"{i+1}. {f['fact']}") - - all_facts_text = " ".join([f['fact'].lower() for f in facts]) - - # Should NOT contain vague temporal terms - prohibited_terms = ["recently", "soon", "lately", "a while ago", "some time ago"] - found_prohibited = [term for term in prohibited_terms if term in all_facts_text] - - assert len(found_prohibited) == 0, ( - f"Should NOT use vague temporal terms. Found: {found_prohibited}" - ) - - # Should contain specific date references (either month names or dates) - # For "yesterday" (Nov 12), "last week" (early Nov), "next month" (December) - temporal_indicators = ["november", "12", "early november", "week of", "december"] - found_temporal = [term for term in temporal_indicators if term in all_facts_text] - - assert len(found_temporal) >= 1, ( - f"Should convert relative dates to absolute. " - f"Found: {found_temporal}, Expected month/date references" - ) - - -@pytest.mark.asyncio -async def test_sensory_dimension_preservation(): - """ - Test that sensory details (visual, auditory, etc.) are preserved. - """ - text = """ -The coffee tasted bitter and burnt. -She showed me her bright orange hair, which looked stunning under the lights. -The music was so loud I could barely hear myself think. -""" - - context = "Personal experience" - llm_config = LLMConfig.for_memory() - - facts = await extract_facts_from_text( - text=text, - event_date=datetime(2024, 11, 13), - context=context, - llm_config=llm_config, - agent_name="TestUser" - ) - - assert len(facts) > 0, "Should extract at least one fact" - - print(f"\nExtracted {len(facts)} facts:") - for i, f in enumerate(facts): - print(f"{i+1}. {f['fact']}") - - all_facts_text = " ".join([f['fact'].lower() for f in facts]) - - # Should preserve sensory descriptors - sensory_indicators = ["bitter", "burnt", "bright orange", "loud", "stunning"] - found_sensory = [word for word in sensory_indicators if word in all_facts_text] - - assert len(found_sensory) >= 2, ( - f"Should preserve sensory details. " - f"Found: {found_sensory}, Expected at least 2 from: {sensory_indicators}" - ) - - -@pytest.mark.asyncio -async def test_cognitive_epistemic_dimension(): - """ - Test that cognitive states and certainty levels are preserved. - """ - text = """ -I realized that the approach wasn't working. -She wasn't sure if the meeting would happen. -He's convinced that AI will transform healthcare. -Maybe we should reconsider the timeline. -""" - - context = "Team discussion" - llm_config = LLMConfig.for_memory() - - facts = await extract_facts_from_text( - text=text, - event_date=datetime(2024, 11, 13), - context=context, - llm_config=llm_config, - agent_name="TestUser" - ) - - assert len(facts) > 0, "Should extract at least one fact" - - print(f"\nExtracted {len(facts)} facts:") - for i, f in enumerate(facts): - print(f"{i+1}. {f['fact']}") - - all_facts_text = " ".join([f['fact'].lower() for f in facts]) - - # Should preserve cognitive/epistemic indicators - cognitive_indicators = ["realized", "wasn't sure", "convinced", "maybe", "reconsider"] - found_cognitive = [word for word in cognitive_indicators if word in all_facts_text] - - assert len(found_cognitive) >= 2, ( - f"Should preserve cognitive/epistemic dimension. " - f"Found: {found_cognitive}" - ) - - -@pytest.mark.asyncio -async def test_capability_skill_dimension(): - """ - Test that capabilities, skills, and limitations are preserved. - """ - text = """ -I can speak French fluently. -Sarah struggles with public speaking. -He's an expert in machine learning. -I'm unable to attend the conference due to scheduling conflicts. -""" - - context = "Personal profile discussion" - llm_config = LLMConfig.for_memory() - - facts = await extract_facts_from_text( - text=text, - event_date=datetime(2024, 11, 13), - context=context, - llm_config=llm_config, - agent_name="TestUser" - ) - - assert len(facts) > 0, "Should extract at least one fact" - - print(f"\nExtracted {len(facts)} facts:") - for i, f in enumerate(facts): - print(f"{i+1}. {f['fact']}") - - all_facts_text = " ".join([f['fact'].lower() for f in facts]) - - # Should preserve capability indicators - capability_indicators = ["can speak", "fluently", "struggles with", "expert in", "unable to"] - found_capability = [word for word in capability_indicators if word in all_facts_text] - - assert len(found_capability) >= 2, ( - f"Should preserve capability/skill dimension. " - f"Found: {found_capability}" - ) - - -@pytest.mark.asyncio -async def test_comparative_dimension(): - """ - Test that comparisons and contrasts are preserved. - """ - text = """ -This approach is much better than the previous one. -The new design is worse than expected. -Unlike last year, we're ahead of schedule. -""" - - context = "Project review" - llm_config = LLMConfig.for_memory() - - facts = await extract_facts_from_text( - text=text, - event_date=datetime(2024, 11, 13), - context=context, - llm_config=llm_config, - agent_name="TestUser" - ) - - assert len(facts) > 0, "Should extract at least one fact" - - print(f"\nExtracted {len(facts)} facts:") - for i, f in enumerate(facts): - print(f"{i+1}. {f['fact']}") - - all_facts_text = " ".join([f['fact'].lower() for f in facts]) - - # Should preserve comparative indicators - comparative_indicators = ["better than", "worse than", "unlike", "ahead of"] - found_comparative = [word for word in comparative_indicators if word in all_facts_text] - - assert len(found_comparative) >= 1, ( - f"Should preserve comparative dimension. " - f"Found: {found_comparative}" - ) - - -@pytest.mark.asyncio -async def test_attitudinal_reactive_dimension(): - """ - Test that attitudes and reactions are preserved. - """ - text = """ -She's very skeptical about the new technology. -I was surprised when he announced his resignation. -Marcus rolled his eyes when the topic came up. -She's enthusiastic about the opportunity. -""" - - context = "Team meeting" - llm_config = LLMConfig.for_memory() - - facts = await extract_facts_from_text( - text=text, - event_date=datetime(2024, 11, 13), - context=context, - llm_config=llm_config, - agent_name="TestUser" - ) - - assert len(facts) > 0, "Should extract at least one fact" - - print(f"\nExtracted {len(facts)} facts:") - for i, f in enumerate(facts): - print(f"{i+1}. {f['fact']}") - - all_facts_text = " ".join([f['fact'].lower() for f in facts]) - - # Should preserve attitudinal/reactive indicators - attitudinal_indicators = ["skeptical", "surprised", "rolled his eyes", "enthusiastic"] - found_attitudinal = [word for word in attitudinal_indicators if word in all_facts_text] - - assert len(found_attitudinal) >= 2, ( - f"Should preserve attitudinal/reactive dimension. " - f"Found: {found_attitudinal}" - ) - - -@pytest.mark.asyncio -async def test_intentional_motivational_dimension(): - """ - Test that goals, plans, and motivations are preserved. - """ - text = """ -I want to learn Mandarin before my trip to China. -She aims to complete her PhD within three years. -His goal is to build a sustainable business. -I'm planning to switch careers because I'm not fulfilled in my current role. -""" - - context = "Personal goals discussion" - llm_config = LLMConfig.for_memory() - - facts = await extract_facts_from_text( - text=text, - event_date=datetime(2024, 11, 13), - context=context, - llm_config=llm_config, - agent_name="TestUser" - ) - - assert len(facts) > 0, "Should extract at least one fact" - - print(f"\nExtracted {len(facts)} facts:") - for i, f in enumerate(facts): - print(f"{i+1}. {f['fact']}") - - all_facts_text = " ".join([f['fact'].lower() for f in facts]) - - # Should preserve intentional/motivational indicators - intentional_indicators = ["want to", "aims to", "goal is", "planning to", "because"] - found_intentional = [word for word in intentional_indicators if word in all_facts_text] - - assert len(found_intentional) >= 2, ( - f"Should preserve intentional/motivational dimension. " - f"Found: {found_intentional}" - ) - - -@pytest.mark.asyncio -async def test_evaluative_preferential_dimension(): - """ - Test that preferences and values are preserved. - """ - text = """ -I prefer working remotely to being in an office. -She values honesty above all else. -He hates being late to meetings. -Family is the most important thing to her. -""" - - context = "Personal values discussion" - llm_config = LLMConfig.for_memory() - - facts = await extract_facts_from_text( - text=text, - event_date=datetime(2024, 11, 13), - context=context, - llm_config=llm_config, - agent_name="TestUser" - ) - - assert len(facts) > 0, "Should extract at least one fact" - - print(f"\nExtracted {len(facts)} facts:") - for i, f in enumerate(facts): - print(f"{i+1}. {f['fact']}") - - all_facts_text = " ".join([f['fact'].lower() for f in facts]) - - # Should preserve evaluative/preferential indicators - evaluative_indicators = ["prefer", "values", "hates", "important", "above all"] - found_evaluative = [word for word in evaluative_indicators if word in all_facts_text] - - assert len(found_evaluative) >= 2, ( - f"Should preserve evaluative/preferential dimension. " - f"Found: {found_evaluative}" - ) - - -@pytest.mark.asyncio -async def test_comprehensive_multi_dimension(): - """ - Test a realistic scenario with multiple dimensions in one fact. - """ - text = """ -I was thrilled to receive such positive feedback on my presentation yesterday! -I wasn't sure if my approach would resonate, but the audience seemed enthusiastic. -I prefer presenting in person rather than virtually because I can read the room better. -""" - - context = "Personal reflection" - llm_config = LLMConfig.for_memory() - - event_date = datetime(2024, 11, 13) - - facts = await extract_facts_from_text( - text=text, - event_date=event_date, - context=context, - llm_config=llm_config, - agent_name="TestUser" - ) - - assert len(facts) > 0, "Should extract at least one fact" - - print(f"\nExtracted {len(facts)} facts:") - for i, f in enumerate(facts): - print(f"{i+1}. {f['fact']}") - - all_facts_text = " ".join([f['fact'].lower() for f in facts]) - - # Should preserve multiple dimensions: - # 1. Emotional: "thrilled" - # 2. Temporal: "yesterday" โ†’ absolute date (not "recently") - # 3. Cognitive: "wasn't sure" - # 4. Attitudinal: "enthusiastic" - # 5. Preferential: "prefer" - # 6. Comparative: "better" - - # Check emotional - assert "thrilled" in all_facts_text or "positive feedback" in all_facts_text, \ - "Should preserve emotional dimension (thrilled)" - - # Check no vague temporal terms - prohibited_terms = ["recently", "soon", "lately"] - found_prohibited = [term for term in prohibited_terms if term in all_facts_text] - assert len(found_prohibited) == 0, \ - f"Should NOT use vague temporal terms. Found: {found_prohibited}" - - # Check cognitive uncertainty - assert "wasn't sure" in all_facts_text or "unsure" in all_facts_text or "uncertain" in all_facts_text, \ - "Should preserve cognitive uncertainty" - - # Check preference - assert "prefer" in all_facts_text or "rather than" in all_facts_text, \ - "Should preserve preferential dimension" - - -@pytest.mark.asyncio -async def test_logical_inference_identity_connection(): - """ - Test that the system makes logical inferences to connect related information. - - Example: "I lost a friend" + "this photo with Karlie" โ†’ "I lost my friend Karlie" - """ - text = """ -Deborah: The roses and dahlias bring me peace. I lost a friend last week, -so I've been spending time in the garden to find some comfort. - -Jolene: Sorry to hear about your friend, Deb. Losing someone can be really tough. -How are you holding up? - -Deborah: Thanks for the kind words. It's been tough, but I'm comforted by -remembering our time together. It reminds me of how special life is. - -Jolene: Memories can give us so much comfort and joy. - -Deborah: Memories keep our loved ones close. This is the last photo with Karlie -which was taken last summer when we hiked. It was our last one. We had such a -great time! Every time I see it, I can't help but smile. -""" - - context = "Conversation between Deborah and Jolene" - llm_config = LLMConfig.for_memory() - - # Event date is February 23, 2023 - event_date = datetime(2023, 2, 23) - - facts = await extract_facts_from_text( - text=text, - event_date=event_date, - context=context, - llm_config=llm_config, - agent_name="Deborah" - ) - - assert len(facts) > 0, "Should extract at least one fact" - - print(f"\nExtracted {len(facts)} facts:") - for i, f in enumerate(facts): - print(f"{i+1}. {f['fact']}") - - all_facts_text = " ".join([f['fact'].lower() for f in facts]) - - # CRITICAL: Should make the logical connection that Karlie is the lost friend - # The fact should mention both "lost" (or similar) AND "Karlie" together - has_karlie = "karlie" in all_facts_text - has_loss = any(word in all_facts_text for word in ["lost", "death", "passed", "died", "losing"]) - - assert has_karlie, "Should mention Karlie in the extracted facts" - assert has_loss, "Should mention the loss/death in the extracted facts" - - # Ideally, they should be in the same fact (connected) - # Check if any single fact contains both Karlie and loss-related terms - connected_fact_found = False - for fact in facts: - fact_text = fact['fact'].lower() - if "karlie" in fact_text and any(word in fact_text for word in ["lost", "death", "passed", "died", "losing"]): - connected_fact_found = True - print(f"\nโœ“ Found connected fact: {fact['fact']}") - break - - assert connected_fact_found, ( - "Should connect 'lost a friend' with 'Karlie' in the same fact. " - f"The inference should be: Karlie is the lost friend. " - f"Facts: {[f['fact'] for f in facts]}" - ) - - -@pytest.mark.asyncio -async def test_logical_inference_pronoun_resolution(): - """ - Test that pronouns are resolved to their referents. - - Example: "I started a project" + "It's challenging" โ†’ "The project is challenging" - """ - text = """ -I started a new machine learning project last month. -It's been really challenging but very rewarding. -I've learned so much from it. -""" - - context = "Personal update" - llm_config = LLMConfig.for_memory() - - facts = await extract_facts_from_text( - text=text, - event_date=datetime(2024, 11, 13), - context=context, - llm_config=llm_config, - agent_name="TestUser" - ) - - assert len(facts) > 0, "Should extract at least one fact" - - print(f"\nExtracted {len(facts)} facts:") - for i, f in enumerate(facts): - print(f"{i+1}. {f['fact']}") - - all_facts_text = " ".join([f['fact'].lower() for f in facts]) - - # Should connect the project with its characteristics - # The fact should mention "project" AND the qualities (challenging, rewarding) - has_project = "project" in all_facts_text - has_qualities = any(word in all_facts_text for word in ["challenging", "rewarding", "learned"]) - - assert has_project, "Should mention the project" - assert has_qualities, "Should mention the qualities/learning" - - # Check if a single fact connects the project with its characteristics - connected_fact_found = False - for fact in facts: - fact_text = fact['fact'].lower() - if "project" in fact_text and any(word in fact_text for word in ["challenging", "rewarding"]): - connected_fact_found = True - print(f"\nโœ“ Found connected fact: {fact['fact']}") - break - - assert connected_fact_found, ( - "Should resolve 'it' to 'the project' and connect characteristics in the same fact. " - f"Facts: {[f['fact'] for f in facts]}" - ) - - -@pytest.mark.asyncio -async def test_date_field_calculation_last_night(): - """ - Test that the date field is calculated correctly for "last night" events. - - CRITICAL: If conversation is on August 14, 2023 and text says "last night", - the date field should be August 13, NOT August 14. - """ - text = """ -Melanie: Hey Caroline! Last night was amazing! We celebrated my daughter's birthday -with a concert surrounded by music, joy and the warm summer breeze. -""" - - context = "Conversation between Melanie and Caroline" - llm_config = LLMConfig.for_memory() - - # Conversation happened on August 14, 2023 - event_date = datetime(2023, 8, 14, 14, 24) # 2:24 PM on Aug 14 - - facts = await extract_facts_from_text( - text=text, - event_date=event_date, - context=context, - llm_config=llm_config, - agent_name="Melanie" - ) - - assert len(facts) > 0, "Should extract at least one fact" - - print(f"\nExtracted {len(facts)} facts:") - for i, f in enumerate(facts): - print(f"{i+1}. Date: {f['date']} - {f['fact']}") - - # Find the fact about the birthday celebration - birthday_fact = None - for fact in facts: - if "birthday" in fact['fact'].lower() or "concert" in fact['fact'].lower(): - birthday_fact = fact - break - - assert birthday_fact is not None, "Should extract fact about birthday celebration" - - # The date field should be August 13, 2023 (last night), NOT August 14 - fact_date_str = birthday_fact['date'] - - # Parse the date - if 'T' in fact_date_str: - fact_date = datetime.fromisoformat(fact_date_str.replace('Z', '+00:00')) - else: - fact_date = datetime.fromisoformat(fact_date_str) - - assert fact_date.year == 2023, "Year should be 2023" - assert fact_date.month == 8, "Month should be August" - assert fact_date.day == 13, ( - f"Day should be 13 (last night relative to Aug 14), but got {fact_date.day}. " - f"Date field should be when FACT occurred, not when mentioned!" - ) - - -@pytest.mark.asyncio -async def test_date_field_calculation_yesterday(): - """ - Test that the date field is calculated correctly for "yesterday" events. - """ - text = """ -Yesterday I went for a morning jog for the first time in a nearby park. -""" - - context = "Personal diary" - llm_config = LLMConfig.for_memory() - - # Conversation on November 13, 2024 - event_date = datetime(2024, 11, 13) - - facts = await extract_facts_from_text( - text=text, - event_date=event_date, - context=context, - llm_config=llm_config, - agent_name="TestUser" - ) - - assert len(facts) > 0, "Should extract at least one fact" - - print(f"\nExtracted {len(facts)} facts:") - for i, f in enumerate(facts): - print(f"{i+1}. Date: {f['date']} - {f['fact']}") - - # Get the jogging fact - jogging_fact = facts[0] - - # Parse the date - fact_date_str = jogging_fact['date'] - if 'T' in fact_date_str: - fact_date = datetime.fromisoformat(fact_date_str.replace('Z', '+00:00')) - else: - fact_date = datetime.fromisoformat(fact_date_str) - - # Should be November 12, 2024 (yesterday) - assert fact_date.year == 2024, "Year should be 2024" - assert fact_date.month == 11, "Month should be November" - assert fact_date.day == 12, ( - f"Day should be 12 (yesterday relative to Nov 13), but got {fact_date.day}. " - f"Date field: {fact_date_str}" - ) - - # Check fact text - all_facts_text = " ".join([f['fact'].lower() for f in facts]) - - # Should preserve "first time" - assert "first time" in all_facts_text or "first" in all_facts_text, \ - "Should preserve 'first time' qualifier" - - # Should NOT use "recently" - assert "recently" not in all_facts_text, \ - "Should NOT convert 'yesterday' to 'recently'" - - # Should have absolute date in text (November 12 or specific date) - assert any(term in all_facts_text for term in ["november", "12", "nov"]), \ - "Should convert 'yesterday' to absolute date in fact text" diff --git a/memora/tests/test_fact_classification.py b/memora/tests/test_fact_classification.py deleted file mode 100644 index 0cc4abb263..0000000000 --- a/memora/tests/test_fact_classification.py +++ /dev/null @@ -1,289 +0,0 @@ -""" -Test that fact classification correctly identifies agent vs world facts. -""" -import pytest -from datetime import datetime -from memora.fact_extraction import extract_facts_from_text -from memora.llm_wrapper import LLMConfig - - -@pytest.mark.asyncio -async def test_agent_facts_from_podcast_transcript(): - """ - Test that when context identifies someone as 'you', their actions are classified as agent facts. - - This test addresses the issue where podcast transcripts with context like - "this was podcast episode between you (Marcus) and Jamie" were extracting - all facts as 'world' instead of properly identifying Marcus's statements as 'agent'. - """ - - # Podcast transcript where Marcus (identified as "you") discusses his work - transcript = """ -Marcus: I've been working on AI safety research for the past six months. -Jamie: That's really interesting! What specifically are you focusing on? -Marcus: I'm investigating interpretability methods. I believe we need to understand -how models make decisions before we can trust them in critical applications. -Jamie: I completely agree with that approach. -Marcus: I published a paper on this topic last month, and I'm presenting it at -the conference next week. -Jamie: Congratulations! I'd love to read it. -""" - - context = "Podcast episode between you (Marcus) and Jamie discussing AI research" - - llm_config = LLMConfig.for_memory() - - facts = await extract_facts_from_text( - text=transcript, - event_date=datetime(2024, 11, 13), - context=context, - llm_config=llm_config - ) - - # Should extract at least one fact - assert len(facts) > 0, "Should extract at least one fact from the transcript" - - print(f"\nExtracted {len(facts)} facts:") - for i, f in enumerate(facts): - print(f"{i+1}. [{f['fact_type']}] {f['fact']}") - - # Marcus's work should be classified as 'agent' since context says "you (Marcus)" - agent_facts = [f for f in facts if f["fact_type"] == "agent"] - - assert len(agent_facts) > 0, \ - f"Should have at least one 'agent' fact when context identifies 'you (Marcus)'. " \ - f"Got facts: {[f['fact'] + ' [' + f['fact_type'] + ']' for f in facts]}" - - # Verify that agent facts use FIRST PERSON (not "Marcus", but "I") - for agent_fact in agent_facts: - fact_text = agent_fact["fact"] - # Agent facts should use "I" not the person's name in third person - assert fact_text.startswith("I ") or " I " in fact_text, \ - f"Agent facts must use first person ('I'). Got: {fact_text}" - - # Should NOT contain "Marcus" as the subject in third person constructions - # (It's ok to have "Marcus" when referring to oneself, but not "Marcus published" style) - import re - # Check for third-person patterns like "Marcus said", "Marcus worked", etc. - third_person_pattern = r'\bMarcus\s+(said|worked|has|published|explained|believes|attended|completed)' - match = re.search(third_person_pattern, fact_text) - assert not match, \ - f"Agent facts should use first person, not third person. " \ - f"Found '{match.group()}' in: {fact_text}" - - print(f"\nโœ… All {len(agent_facts)} agent facts use first person ('I')") - - # Jamie's statements should be 'world' facts - jamie_facts = [f for f in facts if "Jamie" in f["fact"] and "Jamie" == f["fact"].split()[0]] - if jamie_facts: - world_jamie_facts = [f for f in jamie_facts if f["fact_type"] == "world"] - assert len(world_jamie_facts) > 0, \ - f"Jamie's statements should be 'world' facts. " \ - f"Jamie facts: {[f['fact'] + ' [' + f['fact_type'] + ']' for f in jamie_facts]}" - - print(f"\nโœ… Successfully classified {len(agent_facts)} agent facts and {len([f for f in facts if f['fact_type'] == 'world'])} world facts") - print(f"\nAgent facts:") - for f in agent_facts: - print(f" - {f['fact']}") - print(f"\nWorld facts:") - for f in facts: - if f['fact_type'] == 'world': - print(f" - {f['fact']}") - - -@pytest.mark.asyncio -async def test_agent_facts_without_explicit_context(): - """ - Test that when 'you' is used in the text itself, it gets properly classified. - """ - - text = """ -I completed the project on machine learning interpretability last week. -My colleague Sarah helped me with the data analysis. -We presented our findings to the team yesterday. -""" - - context = "Personal work log" - - llm_config = LLMConfig.for_memory() - - facts = await extract_facts_from_text( - text=text, - event_date=datetime(2024, 11, 13), - context=context, - llm_config=llm_config - ) - - assert len(facts) > 0, "Should extract facts" - - # When text uses "I", those should likely be agent facts - # (though without explicit "you (Name)" in context, this is harder to guarantee) - agent_facts = [f for f in facts if f["fact_type"] == "agent"] - - print(f"\nโœ… Extracted {len(facts)} total facts") - print(f"Agent facts: {len(agent_facts)}") - print(f"World facts: {len([f for f in facts if f['fact_type'] == 'world'])}") - - if agent_facts: - print(f"\nAgent facts found:") - for f in agent_facts: - print(f" - {f['fact']}") - - -@pytest.mark.asyncio -async def test_speaker_attribution_predictions(): - """ - Test that predictions made by different speakers are correctly attributed. - - This addresses the issue where Jamie's prediction of "Niners 27-13" was being - incorrectly attributed to Marcus (the agent) in the extracted facts. - """ - - # Simplified transcript with clear predictions from each speaker - transcript = """ -Marcus: [excited] I'm calling it now, Rams will win twenty seven to twenty four, their defense is too strong! -Jamie: [laughs] No way, I predict the Niners will win twenty seven to thirteen, comfy win at home. -Marcus: [angry] That's ridiculous, I stand by my Rams prediction. -Jamie: [teasing] We'll see who's right, my Niners pick is solid. -""" - - context = "podcast episode on match prediction of week 10 - Marcus (you) and Jamie - 14 nov" - agent_name = "Marcus" - - llm_config = LLMConfig.for_memory() - - facts = await extract_facts_from_text( - text=transcript, - event_date=datetime(2024, 11, 14), - context=context, - llm_config=llm_config, - agent_name=agent_name - ) - - assert len(facts) > 0, "Should extract at least one fact" - - print(f"\nExtracted {len(facts)} facts:") - for i, f in enumerate(facts): - print(f"{i+1}. [{f['fact_type']}] {f['fact']}") - - # Find agent facts (Marcus's statements) - agent_facts = [f for f in facts if f["fact_type"] == "agent"] - - # Find world facts about Jamie - jamie_facts = [f for f in facts if f["fact_type"] == "world" and "Jamie" in f["fact"]] - - print(f"\nAgent facts (Marcus): {len(agent_facts)}") - for f in agent_facts: - print(f" - {f['fact']}") - - print(f"\nWorld facts (Jamie): {len(jamie_facts)}") - for f in jamie_facts: - print(f" - {f['fact']}") - - # CRITICAL: Marcus's prediction should be in agent facts, NOT Jamie's prediction - # Marcus predicted: Rams 27-24 - # Jamie predicted: Niners 27-13 - - agent_facts_text = " ".join([f["fact"].lower() for f in agent_facts]) - - # Marcus (agent) should have mentioned Rams 27-24 - assert "rams" in agent_facts_text or "twenty seven to twenty four" in agent_facts_text or "27" in agent_facts_text, \ - f"Agent facts should contain Marcus's Rams prediction. Agent facts: {[f['fact'] for f in agent_facts]}" - - # Marcus (agent) should NOT have predicted Niners 27-13 (that was Jamie!) - # Check that agent facts don't incorrectly contain Jamie's prediction - has_niners_27_13 = False - for fact in agent_facts: - fact_lower = fact["fact"].lower() - # Look for patterns that suggest 27-13 Niners prediction - if ("niners" in fact_lower or "49ers" in fact_lower) and ("27" in fact_lower or "twenty seven") and ("13" in fact_lower or "thirteen"): - # This is Jamie's prediction, should NOT be in agent facts! - has_niners_27_13 = True - print(f"\nโŒ ERROR: Found Jamie's Niners 27-13 prediction in agent facts: {fact['fact']}") - - assert not has_niners_27_13, \ - f"Agent facts should NOT contain Jamie's Niners 27-13 prediction! " \ - f"Agent facts: {[f['fact'] for f in agent_facts]}" - - # Jamie's facts should contain Niners prediction - if jamie_facts: - jamie_facts_text = " ".join([f["fact"].lower() for f in jamie_facts]) - # Jamie predicted Niners, so world facts about Jamie might mention it - print(f"\nโœ… Jamie facts correctly classified as world facts") - - print(f"\nโœ… Speaker attribution test passed: Predictions correctly attributed to their speakers") - - -@pytest.mark.asyncio -async def test_skip_podcast_meta_commentary(): - """ - Test that podcast intros, outros, and calls to action are skipped. - - This addresses the issue where podcast outros like "that's all for today, - don't forget to subscribe" were being extracted as facts. - """ - - transcript = """ -Marcus: Welcome everyone to today's episode! Before we dive in, don't forget to -subscribe and leave a rating. - -Marcus: Today I want to talk about my research on interpretability in AI systems. -I've been working on this for about a year now. - -Jamie: That sounds really interesting! What made you focus on that area? - -Marcus: I believe it's crucial for AI safety. We need to understand how these -models make decisions before we can trust them in critical applications. - -Jamie: I completely agree with that approach. - -Marcus: Well, I think that's gonna do it for us today! Thanks for listening everyone. -Don't forget to tap follow or subscribe, tell a friend, and drop a quick rating -so the algorithm learns to box out. See you next week! -""" - - context = "Podcast episode between you (Marcus) and Jamie about AI" - - llm_config = LLMConfig.for_memory() - - facts = await extract_facts_from_text( - text=transcript, - event_date=datetime(2024, 11, 13), - context=context, - llm_config=llm_config - ) - - print(f"\nExtracted {len(facts)} facts:") - for i, f in enumerate(facts): - print(f"{i+1}. [{f['fact_type']}] {f['fact']}") - - # Should extract at least one fact - assert len(facts) > 0, "Should extract at least one fact" - - # Check that no facts contain meta-commentary phrases - meta_phrases = [ - "subscribe", - "leave a rating", - "tap follow", - "tell a friend", - "that's gonna do it", - "thanks for listening", - "see you next week", - "welcome everyone", - "before we dive in" - ] - - for fact in facts: - fact_lower = fact["fact"].lower() - for phrase in meta_phrases: - assert phrase not in fact_lower, \ - f"Fact should not contain meta-commentary phrase '{phrase}'. " \ - f"Found in: {fact['fact']}" - - # Should have facts about the actual content (interpretability research) - content_facts = [f for f in facts if "interpretability" in f["fact"].lower()] - assert len(content_facts) > 0, \ - "Should extract facts about the actual content discussed (interpretability)" - - print(f"\nโœ… Successfully filtered out meta-commentary") - print(f"โœ… Extracted {len(content_facts)} facts about actual content") diff --git a/memora/tests/test_personality_inference.py b/memora/tests/test_personality_inference.py deleted file mode 100644 index c7ba847361..0000000000 --- a/memora/tests/test_personality_inference.py +++ /dev/null @@ -1,183 +0,0 @@ -""" -Tests for LLM-based personality trait inference from background. -""" -import pytest -import uuid -from memora import TemporalSemanticMemory - - -def unique_agent_id(prefix: str) -> str: - """Generate a unique agent ID for testing.""" - return f"{prefix}_{uuid.uuid4().hex[:8]}" - - -@pytest.mark.asyncio -async def test_background_merge_with_personality_inference(memory: TemporalSemanticMemory): - """Test that background merge infers personality traits by default.""" - agent_id = unique_agent_id("test_infer") - - # Add background with creative/artistic traits - result = await memory.merge_agent_background( - agent_id, - "I am a creative software engineer who loves innovation and trying new technologies", - update_personality=True - ) - - assert "background" in result - assert "personality" in result - - background = result["background"] - personality = result["personality"] - - # Check background was merged - assert "creative" in background.lower() or "innovation" in background.lower() - - # Check personality was inferred (should have high openness due to "creative" and "innovation") - assert "openness" in personality - assert personality["openness"] > 0.5 # Should be higher than neutral - assert 0.0 <= personality["openness"] <= 1.0 - - # Check all required traits are present - required_traits = ["openness", "conscientiousness", "extraversion", - "agreeableness", "neuroticism", "bias_strength"] - for trait in required_traits: - assert trait in personality - assert 0.0 <= personality[trait] <= 1.0 - - -@pytest.mark.asyncio -async def test_background_merge_without_personality_inference(memory: TemporalSemanticMemory): - """Test that background merge skips personality inference when disabled.""" - agent_id = unique_agent_id("test_no_infer") - - # Get initial personality - initial_profile = await memory.get_agent_profile(agent_id) - initial_personality = initial_profile["personality"] - - # Add background WITHOUT personality inference - result = await memory.merge_agent_background( - agent_id, - "I am a data scientist", - update_personality=False - ) - - assert "background" in result - assert "personality" not in result # Should NOT have personality in response - - # Check personality unchanged in database - final_profile = await memory.get_agent_profile(agent_id) - final_personality = final_profile["personality"] - - assert initial_personality == final_personality - - -@pytest.mark.asyncio -async def test_personality_inference_for_organized_engineer(memory: TemporalSemanticMemory): - """Test personality inference for organized/conscientious profile.""" - agent_id = unique_agent_id("test_organized") - - result = await memory.merge_agent_background( - agent_id, - "I am a methodical engineer who values organization and systematic planning", - update_personality=True - ) - - personality = result["personality"] - - # Should have high conscientiousness - assert personality["conscientiousness"] > 0.5 - - -@pytest.mark.asyncio -async def test_personality_inference_for_startup_founder(memory: TemporalSemanticMemory): - """Test personality inference for entrepreneurial profile.""" - agent_id = unique_agent_id("test_founder") - - result = await memory.merge_agent_background( - agent_id, - "I am a startup founder who thrives on risk and social interaction", - update_personality=True - ) - - personality = result["personality"] - - # Should have high openness (risk-taking) and extraversion (social) - assert personality["openness"] > 0.5 - assert personality["extraversion"] > 0.5 - - -@pytest.mark.asyncio -async def test_personality_updates_in_database(memory: TemporalSemanticMemory): - """Test that inferred personality is actually stored in database.""" - agent_id = unique_agent_id("test_db_update") - - # Merge with personality inference - result = await memory.merge_agent_background( - agent_id, - "I am an innovative designer", - update_personality=True - ) - - inferred_personality = result["personality"] - - # Retrieve from database - profile = await memory.get_agent_profile(agent_id) - db_personality = profile["personality"] - - # Should match - assert db_personality == inferred_personality - - -@pytest.mark.asyncio -async def test_multiple_background_merges_update_personality(memory: TemporalSemanticMemory): - """Test that each background merge can update personality.""" - agent_id = unique_agent_id("test_multi_merge") - - # First merge - neutral background - result1 = await memory.merge_agent_background( - agent_id, - "I am a software engineer", - update_personality=True - ) - personality1 = result1["personality"] - - # Second merge - add creative aspect - result2 = await memory.merge_agent_background( - agent_id, - "I love creative problem solving and innovation", - update_personality=True - ) - personality2 = result2["personality"] - - # Personality should have evolved (likely higher openness now) - # Background should contain both pieces - assert "engineer" in result2["background"].lower() or "software" in result2["background"].lower() - assert "creative" in result2["background"].lower() or "innovation" in result2["background"].lower() - - -@pytest.mark.asyncio -async def test_background_merge_conflict_resolution_with_personality(memory: TemporalSemanticMemory): - """Test that conflicts are resolved and personality reflects final background.""" - agent_id = unique_agent_id("test_conflict") - - # First background - await memory.merge_agent_background( - agent_id, - "I was born in Colorado and prefer stability", - update_personality=True - ) - - # Conflicting background - result = await memory.merge_agent_background( - agent_id, - "You were born in Texas and love taking risks", - update_personality=True - ) - - background = result["background"] - personality = result["personality"] - - # Should have Texas (new info), not Colorado - assert "texas" in background.lower() - # Personality should reflect risk-taking - assert personality["openness"] > 0.5 diff --git a/memora/tests/test_temporal_extraction.py b/memora/tests/test_temporal_extraction.py deleted file mode 100644 index 0349a49311..0000000000 --- a/memora/tests/test_temporal_extraction.py +++ /dev/null @@ -1,94 +0,0 @@ -""" -Test temporal extraction and per-fact dating. -""" -import pytest -from datetime import datetime, timezone, timedelta -from memora.fact_extraction import extract_facts_from_text - - -@pytest.mark.asyncio -async def test_extract_facts_with_relative_dates(memory): - """Test that relative dates are converted to absolute dates.""" - - reference_date = datetime(2024, 3, 20, 14, 0, 0, tzinfo=timezone.utc) - - text = """ - Yesterday I went hiking in Yosemite. - Last week I started my new job at Google. - This morning I had coffee with Alice. - """ - - facts = await extract_facts_from_text(text, reference_date, "Personal diary", llm_config=memory._llm_config) - - print(f"\nExtracted {len(facts)} facts:") - for fact in facts: - print(f"- {fact['fact']}") - print(f" Date: {fact['date']}") - - # Verify we got facts - assert len(facts) > 0, "Should extract at least one fact" - - # Check that all facts have dates - for fact in facts: - assert 'fact' in fact, "Each fact should have 'fact' field" - assert 'date' in fact, "Each fact should have 'date' field" - assert fact['date'], f"Date should not be empty for fact: {fact['fact']}" - - # Verify dates are different (not all using reference date) - dates = [f['date'] for f in facts] - unique_dates = set(dates) - if len(facts) >= 3: - assert len(unique_dates) >= 2, "Should have different dates for different temporal facts" - - print(f"\nโœ… All facts have absolute dates") - - -@pytest.mark.asyncio -async def test_extract_facts_with_no_temporal_info(memory): - """Test that facts without temporal info use the reference date.""" - - reference_date = datetime(2024, 3, 20, 14, 0, 0, tzinfo=timezone.utc) - - text = "Alice works at Google. She loves Python programming." - - facts = await extract_facts_from_text(text, reference_date, "General info", llm_config=memory._llm_config) - - print(f"\nExtracted {len(facts)} facts:") - for fact in facts: - print(f"- {fact['fact']}") - print(f" Date: {fact['date']}") - - assert len(facts) > 0, "Should extract at least one fact" - - # All facts should use the reference date since no temporal info is mentioned - for fact in facts: - assert fact['date'], f"Fact should have a date: {fact['fact']}" - - -@pytest.mark.asyncio -async def test_extract_facts_with_absolute_dates(memory): - """Test that absolute dates in text are preserved.""" - - reference_date = datetime(2024, 3, 20, 14, 0, 0, tzinfo=timezone.utc) - - text = """ - On March 15, 2024, Alice joined Google. - Bob will start his vacation on April 1st. - """ - - facts = await extract_facts_from_text(text, reference_date, "Calendar events", llm_config=memory._llm_config) - - print(f"\nExtracted {len(facts)} facts:") - for fact in facts: - print(f"- {fact['fact']}") - print(f" Date: {fact['date']}") - - assert len(facts) > 0, "Should extract at least one fact" - - # Check that dates are present - for fact in facts: - assert fact['date'], f"Fact should have a date: {fact['fact']}" - - -if __name__ == "__main__": - pytest.main([__file__, "-v", "-s"]) diff --git a/pyproject.toml b/pyproject.toml index ea89cbb1d0..2d8184182c 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,5 +1,5 @@ [tool.uv.workspace] -members = ["memora", "memora-dev", "memora-dev/benchmarks", "memora-mcp-server", "memora-openai", "memora-langmem", "memora-clients/python"] +members = ["hindsight", "hindsight-api", "hindsight-dev", "hindsight-dev/benchmarks", "hindsight-mcp-server", "hindsight-openai", "hindsight-langmem", "hindsight-clients/python"] [tool.uv] dev-dependencies = [] diff --git a/scripts/dev/start-api.sh b/scripts/dev/start-api.sh index 0125092749..941efd10db 100755 --- a/scripts/dev/start-api.sh +++ b/scripts/dev/start-api.sh @@ -17,7 +17,7 @@ while [[ $# -gt 0 ]]; do echo "" echo "Uvicorn options (passed to server):" echo " --host HOST Host to bind to (default: 0.0.0.0)" - echo " --port PORT Port to bind to (default: 8080)" + echo " --port PORT Port to bind to (default: 8888)" echo " --reload Enable auto-reload on code changes" echo " --workers WORKERS Number of worker processes (default: 1)" echo " --log-level LEVEL Log level: critical/error/warning/info/debug/trace" @@ -29,7 +29,7 @@ while [[ $# -gt 0 ]]; do echo " --ssl-certfile FILE SSL certificate file" echo "" echo "Example:" - echo " $0 --env dev --reload --port 8000 --log-level debug" + echo " $0 --env dev --reload --port 8888 --log-level debug" exit 0 ;; *) @@ -56,7 +56,7 @@ source "$ENV_FILE" set +a # Extract port from SERVER_ARGS if provided, otherwise use default -PORT=8080 +PORT=8888 for ((i=0; i<${#SERVER_ARGS[@]}; i++)); do if [[ "${SERVER_ARGS[$i]}" == "--port" ]]; then PORT="${SERVER_ARGS[$((i+1))]}" @@ -69,7 +69,7 @@ echo "" # Set default arguments if not provided if [[ ${#SERVER_ARGS[@]} -eq 0 ]]; then - SERVER_ARGS=(--host 0.0.0.0 --port 8080) + SERVER_ARGS=(--host 0.0.0.0 --port 8888) fi -uv run python -m memora.web.server "${SERVER_ARGS[@]}" +uv run python -m hindsight_api.web.server "${SERVER_ARGS[@]}" diff --git a/scripts/dev/start-control-plane.sh b/scripts/dev/start-control-plane.sh index 7910ea4d82..5dbdb74895 100755 --- a/scripts/dev/start-control-plane.sh +++ b/scripts/dev/start-control-plane.sh @@ -2,13 +2,13 @@ set -e ROOT_DIR="$(git rev-parse --show-toplevel)" -cd "$ROOT_DIR/memora-control-plane" || exit 1 +cd "$ROOT_DIR/hindsight-control-plane" || exit 1 # Check if .env exists in workspace root if [ ! -f "$ROOT_DIR/.env" ]; then echo "โš ๏ธ Warning: .env not found in workspace root at $ROOT_DIR/.env" - echo "๐Ÿ“ Please create a .env file if you need to set MEMORA_CP_DATAPLANE_API_URL" - echo " Default will use http://localhost:8080" + echo "๐Ÿ“ Please create a .env file if you need to set HINDSIGHT_CP_DATAPLANE_API_URL" + echo " Default will use http://localhost:8888" echo "" fi @@ -20,14 +20,9 @@ if [ -f "$ROOT_DIR/.env" ]; then source "$ROOT_DIR/.env" set +a fi -PORT=3000 -echo "" -echo "Control plane will be available at: http://localhost:${PORT}" -echo "" # Map prefixed env vars to Next.js standard vars -export HOSTNAME="${MEMORA_CP_HOSTNAME:-0.0.0.0}" -export PORT="${MEMORA_CP_PORT:-$PORT}" +export HOSTNAME="${HINDSIGHT_CP_HOSTNAME:-0.0.0.0}" # Run dev server -npm run dev +npm run dev \ No newline at end of file diff --git a/scripts/generate-clients.sh b/scripts/generate-clients.sh index d81b4fbdf4..578dbf3ce9 100755 --- a/scripts/generate-clients.sh +++ b/scripts/generate-clients.sh @@ -6,11 +6,11 @@ set -e SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" PROJECT_ROOT="$(cd "$SCRIPT_DIR/.." && pwd)" -CLIENTS_DIR="$PROJECT_ROOT/memora-clients" +CLIENTS_DIR="$PROJECT_ROOT/hindsight-clients" OPENAPI_SPEC="$PROJECT_ROOT/openapi.json" echo "==================================================" -echo "Memora API Client Generator (openapi-generator)" +echo "Hindsight API Client Generator (openapi-generator)" echo "==================================================" echo "Project root: $PROJECT_ROOT" echo "Clients directory: $CLIENTS_DIR" @@ -42,17 +42,17 @@ echo "==================================================" PYTHON_CLIENT_DIR="$CLIENTS_DIR/python" # Backup the maintained wrapper file -WRAPPER_FILE="$PYTHON_CLIENT_DIR/memora_client.py" -WRAPPER_BACKUP="/tmp/memora_client_backup.py" +WRAPPER_FILE="$PYTHON_CLIENT_DIR/hindsight_client/hindsight_client.py" +WRAPPER_BACKUP="/tmp/hindsight_client_backup.py" if [ -f "$WRAPPER_FILE" ]; then - echo "๐Ÿ“ฆ Backing up maintained wrapper: memora_client.py" + echo "๐Ÿ“ฆ Backing up maintained wrapper: hindsight_client.py" cp "$WRAPPER_FILE" "$WRAPPER_BACKUP" fi # Remove old generated code (but keep config and maintained files) -if [ -d "$PYTHON_CLIENT_DIR/agent_memory_api_client" ]; then +if [ -d "$PYTHON_CLIENT_DIR/hindsight_client_api" ]; then echo "Removing old generated code..." - rm -rf "$PYTHON_CLIENT_DIR/agent_memory_api_client" + rm -rf "$PYTHON_CLIENT_DIR/hindsight_client_api" fi # Remove other generated files but keep pyproject.toml and config @@ -83,7 +83,7 @@ echo "Organizing generated files..." # Restore the maintained wrapper file if [ -f "$WRAPPER_BACKUP" ]; then - echo "๐Ÿ“ฆ Restoring maintained wrapper: memora_client.py" + echo "๐Ÿ“ฆ Restoring maintained wrapper: hindsight_client.py" cp "$WRAPPER_BACKUP" "$WRAPPER_FILE" rm "$WRAPPER_BACKUP" fi @@ -103,23 +103,20 @@ echo "==================================================" TYPESCRIPT_CLIENT_DIR="$CLIENTS_DIR/typescript" -# Remove old generated client -if [ -d "$TYPESCRIPT_CLIENT_DIR/src" ]; then - echo "Removing old TypeScript client..." - rm -rf "$TYPESCRIPT_CLIENT_DIR/src" -fi +# Remove old generated client (keep package.json, tsconfig.json, tests, src/, and config) +echo "Removing old TypeScript generated code..." +rm -rf "$TYPESCRIPT_CLIENT_DIR/generated" + +# Also remove legacy structure from old generator if it exists +rm -rf "$TYPESCRIPT_CLIENT_DIR/core" +rm -rf "$TYPESCRIPT_CLIENT_DIR/models" +rm -rf "$TYPESCRIPT_CLIENT_DIR/services" +rm -f "$TYPESCRIPT_CLIENT_DIR/index.ts" -# Generate new client +# Generate new client using @hey-api/openapi-ts echo "Generating from $OPENAPI_SPEC..." -npx --yes openapi-typescript-codegen \ - --input "$OPENAPI_SPEC" \ - --output "$TYPESCRIPT_CLIENT_DIR" \ - --client axios \ - --useOptions \ - --useUnionTypes \ - --exportCore true \ - --exportServices true \ - --exportModels true +cd "$TYPESCRIPT_CLIENT_DIR" +npx --yes @hey-api/openapi-ts echo "โœ“ TypeScript client generated at $TYPESCRIPT_CLIENT_DIR" echo "" @@ -131,7 +128,7 @@ echo "" echo "Python client: $PYTHON_CLIENT_DIR" echo "TypeScript client: $TYPESCRIPT_CLIENT_DIR" echo "" -echo "โš ๏ธ Important: The maintained wrapper memora_client.py was preserved" +echo "โš ๏ธ Important: The maintained wrapper hindsight_client.py was preserved" echo "" echo "Next steps:" echo " 1. Review the generated clients" diff --git a/scripts/release.sh b/scripts/release.sh index ab0d35bd9e..e3cfef204c 100755 --- a/scripts/release.sh +++ b/scripts/release.sh @@ -65,7 +65,7 @@ fi print_info "Updating version in all components..." # Update Python packages -PYTHON_PACKAGES=("memora" "memora-dev" "memora-dev/benchmarks") +PYTHON_PACKAGES=("hindsight-api" "hindsight-dev" "hindsight-dev/benchmarks") for package in "${PYTHON_PACKAGES[@]}"; do PYPROJECT_FILE="$package/pyproject.toml" if [ -f "$PYPROJECT_FILE" ]; then @@ -78,7 +78,7 @@ for package in "${PYTHON_PACKAGES[@]}"; do done # Update Rust CLI -CARGO_FILE="memora-cli/Cargo.toml" +CARGO_FILE="hindsight-cli/Cargo.toml" if [ -f "$CARGO_FILE" ]; then print_info "Updating $CARGO_FILE" sed -i.bak "s/^version = \".*\"/version = \"$VERSION\"/" "$CARGO_FILE" @@ -88,7 +88,7 @@ else fi # Update Helm chart -HELM_CHART_FILE="helm/memora/Chart.yaml" +HELM_CHART_FILE="helm/hindsight/Chart.yaml" if [ -f "$HELM_CHART_FILE" ]; then print_info "Updating $HELM_CHART_FILE" sed -i.bak "s/^version: .*/version: $VERSION/" "$HELM_CHART_FILE" @@ -99,7 +99,7 @@ else fi # Update Control Plane package.json -CONTROL_PLANE_PKG="memora-control-plane/package.json" +CONTROL_PLANE_PKG="hindsight-control-plane/package.json" if [ -f "$CONTROL_PLANE_PKG" ]; then print_info "Updating $CONTROL_PLANE_PKG" sed -i.bak "s/\"version\": \".*\"/\"version\": \"$VERSION\"/" "$CONTROL_PLANE_PKG" @@ -109,7 +109,7 @@ else fi # Update Python API client -PYTHON_CLIENT_PKG="memora-clients/python/pyproject.toml" +PYTHON_CLIENT_PKG="hindsight-clients/python/pyproject.toml" if [ -f "$PYTHON_CLIENT_PKG" ]; then print_info "Updating $PYTHON_CLIENT_PKG" sed -i.bak "s/^version = \".*\"/version = \"$VERSION\"/" "$PYTHON_CLIENT_PKG" @@ -119,7 +119,7 @@ else fi # Update TypeScript API client -TYPESCRIPT_CLIENT_PKG="memora-clients/typescript/package.json" +TYPESCRIPT_CLIENT_PKG="hindsight-clients/typescript/package.json" if [ -f "$TYPESCRIPT_CLIENT_PKG" ]; then 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