ench: switch Chat completions to Responses API agent

.gitignore

@@ -1,5 +1,8 @@
 .env
 .vscode
+.idea
+.DS_Store
+**/.DS_Store
 __pycache__
 .pytest_cache
 .venv

README.md

@@ -37,7 +37,7 @@ Agentic-Starter-Kits/
 │   ├── base/
 │   │   ├── langgraph_react_agent/       # LangGraph ReAct agent 
 │   │   └── llamaindex_websearch_agent/  # LlamaIndex web search agent
-│   │   └── llamastack_agent/            # Llamastack bare API 
+│   │   └── openai_responses_agent/      # OpenAI Responses API (no framework)
 │   └── community/
 │       └── langgraph_agentic_rag/       # RAG agent with Milvus vector store
 ├── run_llama_server.yaml                # Llama Stack server configuration
@@ -85,7 +85,7 @@ After completing the setup, choose an agent and follow its specific README:
 **Base Agents:**
 - **[LangGraph ReAct Agent](./agents/base/langgraph_react_agent/README.md)** - General-purpose agent with tool use
 - **[LlamaIndex WebSearch Agent](./agents/base/llamaindex_websearch_agent/README.md)** - Web search capabilities
-- **[Llama Stack bare API](./agents/base/llamastack_agent/README.md)** - Web search capabilities
+- **[OpenAI Responses Agent](./agents/base/openai_responses_agent/README.md)** - OpenAI client + pure Python (Responses API)
 
 **Community Agents:**
 - **[LangGraph Agentic RAG](./agents/community/langgraph_agentic_rag/README.md)** - RAG with Milvus vector store

agents/base/llamastack_agent/Dockerfile → agents/base/openai_responses_agent/Dockerfile

@@ -1,4 +1,4 @@
-# LlamaStack Agent (LlamaStack API only, no LlamaIndex). Python 3.12+ required by llama-stack-client.
+# OpenAI Responses Agent – OpenAI client + pure Python (Responses API, no agentic framework). Python 3.12+.
 FROM python:3.12-slim
 
 WORKDIR /app

agents/base/openai_responses_agent/README.md

@@ -0,0 +1,123 @@
+# OpenAI Responses Agent
+
+Agent **without any agentic framework**: uses only the **OpenAI Python client** and **pure Python** (Responses API). No LlamaStack, LangChain, LlamaIndex, etc. – to show it can be done without frameworks. Uses `AIAgent` with chat, tools, and Action/Observation loop. Compatible with OpenAI API or any OpenAI-compatible endpoint (e.g. `BASE_URL` override). Python 3.12+.
+
+# Use Agent Locally
+
+### Installation
+
+```bash
+git clone <repository-url>
+cd Agentic-Starter-Kits
+```
+```bash
+python -m venv .venv
+source .venv/bin/activate  # On Windows: .venv\Scripts\activate
+```
+
+If you want to install Ollama: [Ollama site](https://ollama.com/) or [Brew](https://formulae.brew.sh/formula/ollama#default).
+
+**Install agent dependencies** (OpenAI client):
+
+```bash
+cd agents/base/openai_responses_agent
+uv pip install -e .
+# or: poetry install
+```
+
+### Setup Instructions
+
+**Option A – OpenAI API**
+
+Create `.env` in the agent directory (or use repo `template.env`):
+
+```env
+BASE_URL=https://api.openai.com/v1
+MODEL_ID=gpt-4o-mini
+API_KEY=sk-...
+```
+
+**Option B – Local OpenAI-compatible endpoint (e.g. Ollama)**
+
+1. Pull model and run Ollama (or another OpenAI-compatible server).
+2. In `.env` set e.g. `BASE_URL=http://localhost:11434/v1`, `MODEL_ID=llama3.2`, `API_KEY=not-needed` (if not required).
+
+**Configure Environment Variables**
+
+Copy the template (from repo root: `template.env`) or create `.env` in the agent directory:
+
+```bash
+cp ../../../template.env .env
+```
+
+Edit `.env` with `BASE_URL`, `MODEL_ID`, and `API_KEY` as above.
+
+**Run the example**
+
+```bash
+cd examples
+python execute_ai_service_locally.py
+```
+
+**⚡ Or with [uv](https://docs.astral.sh/uv/)** (from repo root):
+
+1. Create venv and activate:
+```bash
+uv venv --python 3.12
+source .venv/bin/activate
+```
+
+2. Copy shared utils into the agent package:
+```bash
+cp utils.py agents/base/openai_responses_agent/src/openai_responses_agent_base/
+```
+
+3. Install agent (editable) and its requirements:
+```bash
+uv pip install -e agents/base/openai_responses_agent/. -r agents/base/openai_responses_agent/requirements.txt
+```
+
+4. Run the example:
+```bash
+uv run agents/base/openai_responses_agent/examples/execute_ai_service_locally.py
+```
+
+# Deployment on Red Hat OpenShift Cluster
+
+### Step 1: Initialize the Agent
+
+```bash
+cd agents/base/openai_responses_agent
+chmod +x init.sh deploy.sh
+./init.sh
+```
+
+This loads `.env`, validates variables, and copies `utils.py` into the agent package.
+
+### Step 2: Build Image and Deploy
+
+```bash
+./deploy.sh
+```
+
+This creates the API key secret, builds and pushes the image, and deploys the agent (Deployment, Service, Route).
+
+### Step 3: Test the Agent
+
+Get the route host:
+
+```bash
+oc get route openai-responses-agent -o jsonpath='{.spec.host}'
+```
+
+Send a test request:
+
+```bash
+curl -X POST https://<YOUR_ROUTE_URL>/chat \
+  -H "Content-Type: application/json" \
+  -d '{"message": "How much does a Lenovo Laptop costs and what are the reviews?"}'
+```
+
+## References
+
+- [OpenAI Python client](https://github.com/openai/openai-python) and [Responses API](https://platform.openai.com/docs/api-reference/responses/create)