diff --git a/docker-bake.hcl b/docker-bake.hcl index f2a66a06cd..03d01fa368 100644 --- a/docker-bake.hcl +++ b/docker-bake.hcl @@ -593,6 +593,23 @@ target "nmp-cpu-tasks-docker" { platforms = get_platforms() } +# Experimentalist control plane. This target is built on demand by the default +# OpenShell runtime and remains outside the platform's default image groups. +target "nmp-experimentalist-docker" { + target = "runtime" + context = "." + dockerfile = "plugins/nemo-experimentalist/Dockerfile" + contexts = { + nmp-python-base = "target:nmp-python-base" + nmp-workspace = "target:nmp-workspace" + } + cache-to = maybe_registry_cache_to("nmp-experimentalist") + cache-from = maybe_registry_cache_from("nmp-experimentalist") + tags = sha_and_maybe_latest_tags("nmp-experimentalist") + output = image_output() + platforms = get_platforms() +} + # Python wheel builders (causal-conv1d, mamba-ssm, av, opencv-python-headless). # CUDA extensions only ship source on PyPI; av/opencv bundle FFmpeg. Pre-built for # amd64 and arm64. Wheels live at /wheels/*.whl inside each image. diff --git a/packages/nmp_platform_runner/src/nmp/platform_runner/registry.py b/packages/nmp_platform_runner/src/nmp/platform_runner/registry.py index 79693fcbc6..0d85607a86 100644 --- a/packages/nmp_platform_runner/src/nmp/platform_runner/registry.py +++ b/packages/nmp_platform_runner/src/nmp/platform_runner/registry.py @@ -38,6 +38,7 @@ AVAILABLE_SIDECARS: dict[str, str] = { "adapters": "nmp.core.models.sidecars.adapters.main:run", "auth-proxy": "nmp.common.auth.workload_proxy.main:run", + "clickhouse": "nmp.intake.sidecars.clickhouse:run", } SERVICE_SIDECAR_DEPENDENCIES: dict[str, set[str]] = { diff --git a/plugins/nemo-eval-author/src/nemo_eval_author_plugin/eval_author/agent.py b/plugins/nemo-eval-author/src/nemo_eval_author_plugin/eval_author/agent.py index 780a372c10..3d43d0d577 100644 --- a/plugins/nemo-eval-author/src/nemo_eval_author_plugin/eval_author/agent.py +++ b/plugins/nemo-eval-author/src/nemo_eval_author_plugin/eval_author/agent.py @@ -9,6 +9,7 @@ import asyncio import logging +from collections.abc import Callable from pathlib import Path from typing import Any @@ -25,7 +26,10 @@ Task, TrialResult, ) -from nemo_experimentalist_plugin.experimentalist.components.evaluator.models import ResourceRef +from nemo_experimentalist_plugin.experimentalist.components.evaluator.models import ( + DependencyRuntimeError, + ResourceRef, +) from nemo_experimentalist_plugin.experimentalist.components.tools import GuardedShellTools from nemo_experimentalist_plugin.experimentalist.components.trace_analyzer import ( Diagnostic, @@ -199,7 +203,11 @@ async def fill_task_template( The caller has already copied the template to its durable candidate path; edit this directory in place and do not copy or rename it. 2. Fetch the trace via ``client`` and populate the template's placeholders - with values from the trace (instruction, environment config, etc.). + with values from the trace. A trusted task may contain + ``nemo-task-envelope.json``; in that case edit only its declared + ``task_data`` paths. Never edit Dockerfiles, Compose files, image + references, mounts, environment-variable bindings, network policy, + resource policy, or verifier files while filling a task. Leave unfillable placeholders as-is. 3. Keep ``task.toml`` parseable and keep ``[task] name`` in ``org/name`` format. The caller will deterministically finalize the name and provenance. @@ -243,6 +251,7 @@ async def run( validation_dataset: Dataset, *, client: AsyncNeMoPlatform, + prepare_dataset: Callable[[Dataset], Dataset] | None = None, ) -> EvalAuthorResult: """Curate an evaluation suite and always close the owned shell session.""" try: @@ -253,6 +262,7 @@ async def run( train_dataset=train_dataset, validation_dataset=validation_dataset, client=client, + prepare_dataset=prepare_dataset, ) finally: await self.shell.close() @@ -266,6 +276,7 @@ async def _run( validation_dataset: Dataset, *, client: AsyncNeMoPlatform, + prepare_dataset: Callable[[Dataset], Dataset] | None = None, ) -> EvalAuthorResult: """Curate an evaluation suite from an Insight and its production traces. @@ -276,6 +287,7 @@ async def _run( train_dataset: The train dataset, returned unchanged. validation_dataset: The validation dataset, returned unchanged. client: Existing NeMo Platform client used for Intake requests. + prepare_dataset: Optional evaluator hook that binds task runtimes. """ resolved_agent = self.experiment_dir / agent_path insight_id = insight.id @@ -299,8 +311,11 @@ async def _run( staged_tasks = insight_suite.stage(refs) for staged in staged_tasks: await self.fill_task_template(staged.trace_ref, staged.task, client, insight.workspace) + insight_suite.validate_fill_mutations(staged) insight_suite.validate(staged) materialized_dataset = insight_suite.promote_local(refs, staged_tasks) + if prepare_dataset is not None: + materialized_dataset = prepare_dataset(materialized_dataset) except BaseException: insight_suite.discard() raise @@ -332,6 +347,8 @@ async def _run( for task, ref, result in zip(tasks, refs, raw_diagnostics, strict=True): if isinstance(result, asyncio.CancelledError): raise result + if isinstance(result, DependencyRuntimeError): + raise result if isinstance(result, BaseException): logger.warning("Trace analysis failed for %s: %s", ref, result) analysis_statuses[task.id] = ("failed", str(result)) @@ -343,12 +360,14 @@ async def _run( self.context["dataset_documentation"] = doc(type(materialized_dataset), inline_depth=1) runner_conventions = await self.discover_runner(materialized_dataset) + metric_mutation_snapshot = insight_suite.metric_mutation_snapshot() summary = await self.author_insight_metrics( insight, diagnostics, materialized_dataset, runner_conventions, ) + insight_suite.validate_metric_mutations(metric_mutation_snapshot) for repair_attempt in range(self._config.max_validation_repair_attempts + 1): try: await materialized_dataset.validate() @@ -368,6 +387,7 @@ async def _run( runner_conventions, validation_feedback=str(exc), ) + insight_suite.validate_metric_mutations(metric_mutation_snapshot) else: finalized_suite = insight_suite.finalize() return EvalAuthorResult( diff --git a/plugins/nemo-eval-author/src/nemo_eval_author_plugin/eval_author/materialization.py b/plugins/nemo-eval-author/src/nemo_eval_author_plugin/eval_author/materialization.py index 4e084dccb8..02e93febaf 100644 --- a/plugins/nemo-eval-author/src/nemo_eval_author_plugin/eval_author/materialization.py +++ b/plugins/nemo-eval-author/src/nemo_eval_author_plugin/eval_author/materialization.py @@ -25,6 +25,8 @@ _CONTENT_HASH_SCHEMA_VERSION = 1 _METRIC_CONTRACT_VERSION = 1 _SLUG_RE = re.compile(r"[^a-z0-9]+") +_ENVELOPE_DESCRIPTOR_FILENAME = ".nemo-trusted-harbor-envelope.json" +_ENVELOPE_POLICY_FILENAME = "nemo-task-envelope.json" def _slug(value: str, *, fallback: str, max_length: int = 48) -> str: @@ -52,6 +54,89 @@ def _file_hashes(root: Path) -> dict[str, str]: } +def _contains(parent: str, child: str) -> bool: + parent_path = Path(parent) + child_path = Path(child) + return child_path == parent_path or parent_path in child_path.parents + + +@dataclass(frozen=True, slots=True) +class _MutationPolicy: + task_data_paths: tuple[str, ...] + verifier_paths: tuple[str, ...] + + +def _mutation_policy(task_dir: Path) -> _MutationPolicy | None: + """Load the trusted-envelope policy without importing Experimentalist helpers.""" + descriptor = task_dir / _ENVELOPE_DESCRIPTOR_FILENAME + if not descriptor.is_file(): + return None + policy_path = task_dir / _ENVELOPE_POLICY_FILENAME + if not policy_path.is_file(): + raise ValueError(f"Trusted Eval Author task is missing {_ENVELOPE_POLICY_FILENAME}: {task_dir}") + try: + payload = json.loads(policy_path.read_text(encoding="utf-8")) + except (OSError, UnicodeError, json.JSONDecodeError) as exc: + raise ValueError(f"Invalid trusted task mutation policy {policy_path}: {exc}") from exc + if payload.get("schema_version") != 1: + raise ValueError(f"Unsupported trusted task mutation policy version in {policy_path}") + + def paths_from_values(raw: object, key: str) -> tuple[str, ...]: + if not isinstance(raw, list): + raise ValueError(f"Trusted task mutation policy {key} must be a list of paths: {policy_path}") + normalized: list[str] = [] + for item in raw: + if not isinstance(item, str) or not item: + raise ValueError(f"Trusted task mutation policy {key} must be a list of paths: {policy_path}") + path = Path(item) + if path.is_absolute() or any(part in ("", ".", "..") for part in path.parts): + raise ValueError(f"Unsafe trusted task mutation path {item!r}: {policy_path}") + normalized.append(path.as_posix()) + if len(set(normalized)) != len(normalized): + raise ValueError(f"Duplicate trusted task mutation paths in {policy_path}") + return tuple(normalized) + + def paths(key: str) -> tuple[str, ...]: + return paths_from_values(payload.get(key, []), key) + + raw_task_data = payload.get("task_data", []) + if not isinstance(raw_task_data, list): + raise ValueError(f"Trusted task mutation policy task_data must be a list: {policy_path}") + task_data_paths: list[str] = [] + for slot in raw_task_data: + if not isinstance(slot, dict) or not isinstance(slot.get("path"), str): + raise ValueError(f"Trusted task mutation policy task_data contains an invalid slot: {policy_path}") + task_data_paths.extend(paths_from_values([slot["path"]], "task_data")) + return _MutationPolicy( + task_data_paths=tuple(task_data_paths), + verifier_paths=paths("verifier_paths"), + ) + + +def _immutable_snapshot(task_dir: Path, *, mutable_paths: tuple[str, ...]) -> dict[str, str]: + return { + relative: digest + for relative, digest in _file_hashes(task_dir).items() + if not any(_contains(mutable, relative) for mutable in mutable_paths) + } + + +def _assert_snapshot( + task_dir: Path, + *, + mutable_paths: tuple[str, ...], + expected: dict[str, str], + phase: str, +) -> None: + actual = _immutable_snapshot(task_dir, mutable_paths=mutable_paths) + if actual == expected: + return + changed = sorted(path for path in set(expected) | set(actual) if expected.get(path) != actual.get(path)) + raise ValueError( + f"Eval Author {phase} modified trusted task paths outside its envelope slots: " + ", ".join(changed[:20]) + ) + + def _verifier_dir(task_dir: Path) -> Path: config = tomllib.loads((task_dir / "task.toml").read_text(encoding="utf-8")) verifier = config.get("verifier") @@ -144,6 +229,8 @@ class StagedInsightTask: slug: str path: Path task: Task + mutation_policy: _MutationPolicy | None + immutable_before_fill: dict[str, str] | None @dataclass(frozen=True, slots=True) @@ -200,9 +287,61 @@ def stage(self, trace_refs: list[str]) -> list[StagedInsightTask]: task_dir = self._candidate_suite / slug shutil.copytree(self.template_dir, task_dir) task = list(HarborDataset.from_path(task_dir).list_tasks())[0] - staged.append(StagedInsightTask(index=index, trace_ref=trace_ref, slug=slug, path=task_dir, task=task)) + policy = _mutation_policy(task_dir) + staged.append( + StagedInsightTask( + index=index, + trace_ref=trace_ref, + slug=slug, + path=task_dir, + task=task, + mutation_policy=policy, + immutable_before_fill=( + _immutable_snapshot(task_dir, mutable_paths=policy.task_data_paths) + if policy is not None + else None + ), + ) + ) return staged + def validate_fill_mutations(self, staged: StagedInsightTask) -> None: + """Reject coding-agent edits outside declared trace-data slots.""" + if staged.mutation_policy is None or staged.immutable_before_fill is None: + return + _assert_snapshot( + staged.path, + mutable_paths=staged.mutation_policy.task_data_paths, + expected=staged.immutable_before_fill, + phase="template filling", + ) + + def metric_mutation_snapshot(self) -> dict[str, tuple[tuple[str, ...], dict[str, str]]]: + """Capture non-verifier content before metric authoring begins.""" + snapshot: dict[str, tuple[tuple[str, ...], dict[str, str]]] = {} + for task_dir in sorted(path for path in self.suite_dir.iterdir() if path.is_dir()): + policy = _mutation_policy(task_dir) + if policy is None: + continue + snapshot[task_dir.name] = ( + policy.verifier_paths, + _immutable_snapshot(task_dir, mutable_paths=policy.verifier_paths), + ) + return snapshot + + def validate_metric_mutations( + self, + snapshot: dict[str, tuple[tuple[str, ...], dict[str, str]]], + ) -> None: + """Reject metric-author edits outside declared verifier slots.""" + for task_name, (mutable_paths, expected) in snapshot.items(): + _assert_snapshot( + self.suite_dir / task_name, + mutable_paths=mutable_paths, + expected=expected, + phase="metric authoring", + ) + def discard(self) -> None: """Remove an unpromoted candidate suite and reset its staging state.""" if self._candidate_root is not None and self._candidate_root.exists(): diff --git a/plugins/nemo-eval-author/tests/test_eval_author_agent.py b/plugins/nemo-eval-author/tests/test_eval_author_agent.py index e6177c7318..6441e18cb0 100644 --- a/plugins/nemo-eval-author/tests/test_eval_author_agent.py +++ b/plugins/nemo-eval-author/tests/test_eval_author_agent.py @@ -18,6 +18,7 @@ from nemo_experimentalist_plugin.experimentalist.components.evaluator import ( Dataset, DatasetValidationError, + DependencyRuntimeError, Task, TrialResult, ) @@ -184,6 +185,9 @@ def stage(self, trace_refs: list[str]) -> list[Any]: def validate(self, staged: Any) -> None: staged.result = calls.fill_task_template[-1].result + def validate_fill_mutations(self, staged: Any) -> None: + pass + def promote_local(self, trace_refs: list[str], staged_tasks: list[Any]) -> Dataset: assert trace_refs == [staged.trace_ref for staged in staged_tasks] tasks = [staged.result for staged in staged_tasks] @@ -200,6 +204,12 @@ def discard(self) -> None: def record_analysis(self, statuses: dict[str, tuple[str, str | None]]) -> None: pass + def metric_mutation_snapshot(self) -> dict: + return {} + + def validate_metric_mutations(self, snapshot: dict) -> None: + pass + def finalize(self) -> SimpleNamespace: identity = "sha256:" + "a" * 64 scorer_identity = "sha256:" + "b" * 64 @@ -372,6 +382,34 @@ async def test_run_enforces_max_traces( assert [call.trial.metadata["trace_ref"] for call in calls.analyzer_run] == ["trace-1", "trace-2"] +@pytest.mark.asyncio +async def test_run_prepares_materialized_dataset_before_trace_analysis( + tmp_path: Path, + monkeypatch: pytest.MonkeyPatch, +) -> None: + eval_author = _eval_author(tmp_path) + calls = _install_pipeline(monkeypatch, [_diagnostic("prepared")], eval_author) + monkeypatch.setattr(eval_author_module.cache, "store", lambda *args: None) + prepared: list[Dataset] = [] + + def prepare_dataset(dataset: Dataset) -> Dataset: + prepared.append(dataset) + return dataset + + await eval_author.run( + _insight(["trace-1"]), + Path("agent"), + Task(id="template"), + Dataset(id="train"), + Dataset(id="validation"), + client=cast(Any, object()), + prepare_dataset=prepare_dataset, + ) + + assert len(prepared) == 1 + assert calls.analyzer_run[0].task is prepared[0].tasks[0] + + @pytest.mark.asyncio async def test_run_discards_staged_suite_when_filling_fails( tmp_path: Path, @@ -473,6 +511,29 @@ async def test_run_skips_failed_trace_analysis_and_keeps_successes( assert "Trace analysis failed for trace-bad: analysis failed" in caplog.text +@pytest.mark.asyncio +async def test_run_propagates_dependency_runtime_failure( + tmp_path: Path, + monkeypatch: pytest.MonkeyPatch, +) -> None: + eval_author = _eval_author(tmp_path) + _install_pipeline( + monkeypatch, + [DependencyRuntimeError("remote Harbor dependency startup failed")], + eval_author, + ) + + with pytest.raises(DependencyRuntimeError, match="remote Harbor dependency startup failed"): + await eval_author.run( + _insight(["trace-bad"]), + Path("agent"), + Task(id="template"), + Dataset(id="train"), + Dataset(id="validation"), + client=cast(Any, object()), + ) + + @pytest.mark.asyncio async def test_run_propagates_trace_analysis_cancellation( tmp_path: Path, diff --git a/plugins/nemo-eval-author/tests/test_eval_author_materialization.py b/plugins/nemo-eval-author/tests/test_eval_author_materialization.py index a110fcfcf0..70d2212865 100644 --- a/plugins/nemo-eval-author/tests/test_eval_author_materialization.py +++ b/plugins/nemo-eval-author/tests/test_eval_author_materialization.py @@ -46,6 +46,25 @@ def _write_template(root: Path) -> Task: return Task(id="task-template", uri=root.as_uri()) +def _mark_trusted(root: Path) -> None: + (root / ".nemo-trusted-harbor-envelope.json").write_text( + '{"schema_version":1,"envelope_id":"template-a","envelope_digest":"sha256:' + + "a" * 64 + + '","tasks":[{"task_id":"template","path":".","content_digest":"sha256:' + + "b" * 64 + + '","policy":{"schema_version":1,"task_data":[' + '{"path":"instruction.md","media_type":"text/plain","max_bytes":4096}],' + '"verifier_paths":["tests/test.sh","tests/metrics"]}}]}', + encoding="utf-8", + ) + (root / "nemo-task-envelope.json").write_text( + '{"schema_version":1,"task_data":[' + '{"path":"instruction.md","media_type":"text/plain","max_bytes":4096}],' + '"verifier_paths":["tests/test.sh","tests/metrics"]}\n', + encoding="utf-8", + ) + + def test_insight_suite_materializes_discoverable_tasks_with_provenance(tmp_path: Path) -> None: template = _write_template(tmp_path / "template") refs = ["intake/traces/unsafe ref", "intake/traces/unsafe ref"] @@ -170,6 +189,40 @@ def test_insight_suite_rejects_empty_instruction_before_materialization(tmp_path assert not suite.suite_dir.exists() +def test_trusted_template_fill_may_only_change_declared_task_data(tmp_path: Path) -> None: + template = _write_template(tmp_path / "template") + _mark_trusted(Path(template.uri.removeprefix("file://"))) + suite = InsightSuite(experiment_dir=tmp_path, insight_id="insight-1", task_template=template) + staged = suite.stage(["trace-1"])[0] + + (staged.path / "instruction.md").write_text("Allowed trace instruction.\n", encoding="utf-8") + suite.validate_fill_mutations(staged) + (staged.path / "environment" / "Dockerfile").write_text("FROM malicious\n", encoding="utf-8") + + with pytest.raises(ValueError, match="outside its envelope slots.*environment/Dockerfile"): + suite.validate_fill_mutations(staged) + + +def test_trusted_metric_author_may_only_change_declared_verifier_files(tmp_path: Path) -> None: + template = _write_template(tmp_path / "template") + _mark_trusted(Path(template.uri.removeprefix("file://"))) + suite = InsightSuite(experiment_dir=tmp_path, insight_id="insight-1", task_template=template) + staged = suite.stage(["trace-1"])[0] + (staged.path / "instruction.md").write_text("Materialized instruction.\n", encoding="utf-8") + suite.validate_fill_mutations(staged) + suite.validate(staged) + suite.promote_local(["trace-1"], [staged]) + + snapshot = suite.metric_mutation_snapshot() + task_dir = next(path for path in suite.suite_dir.iterdir() if path.is_dir()) + (task_dir / "tests" / "test.sh").write_text("#!/bin/sh\necho new metric\n", encoding="utf-8") + suite.validate_metric_mutations(snapshot) + (task_dir / "instruction.md").write_text("Rewritten by metric author.\n", encoding="utf-8") + + with pytest.raises(ValueError, match="outside its envelope slots.*instruction.md"): + suite.validate_metric_mutations(snapshot) + + def test_discard_removes_candidate_and_allows_restaging(tmp_path: Path) -> None: template = _write_template(tmp_path / "template") suite = InsightSuite(experiment_dir=tmp_path, insight_id="insight-1", task_template=template) diff --git a/plugins/nemo-experimentalist/Dockerfile b/plugins/nemo-experimentalist/Dockerfile new file mode 100644 index 0000000000..90b1f70d68 --- /dev/null +++ b/plugins/nemo-experimentalist/Dockerfile @@ -0,0 +1,49 @@ +# syntax=docker/dockerfile:1 +# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 + +# Experimentalist control plane. Harbor task execution deliberately does not +# live in this image: it has no Docker CLI and must never receive a Docker +# socket. It submits Harbor work through the authenticated bridge API instead. + +ARG NMP_PYTHON_BASE=nmp-python-base + +FROM ${NMP_PYTHON_BASE} AS builder +COPY --from=nmp-workspace . . +RUN --mount=type=cache,target=/root/.cache/uv \ + uv sync --frozen --only-group experimentalist --no-editable + +FROM ${NMP_PYTHON_BASE} AS runtime + +LABEL com.nvidia.nemo.experimentalist.openshell-runtime="1" + +# OpenShell's supervisor resolves the sandbox user by name. iproute2 and +# nftables are required for full network-policy enforcement. Experimentalist +# calls gh/glab directly when publishing the winning candidate. +RUN apt-get update && apt-get install -y --no-install-recommends \ + gh \ + glab \ + iproute2 \ + nftables \ + && apt-get clean \ + && rm -rf /var/lib/apt/lists/* \ + && groupadd --system sandbox \ + && useradd --system --gid sandbox --create-home --home-dir /home/sandbox --shell /bin/bash sandbox \ + && mkdir -p /sandbox \ + && chown sandbox:sandbox /sandbox \ + && touch /etc/nemo-experimentalist-container + +COPY --from=builder /app/.venv /app/.venv +COPY --chmod=0755 plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/openshell/git-askpass.sh \ + /usr/local/bin/nemo-experimentalist-git-askpass + +ENV HOME=/home/sandbox \ + PATH="/app/.venv/bin:$PATH" \ + XDG_CACHE_HOME=/sandbox/.cache \ + NEMO_EXPERIMENTALIST_RUNTIME_CACHE=/sandbox/.cache/runtime + +WORKDIR /sandbox +USER sandbox + +ENTRYPOINT ["nemo", "experimentalist"] +CMD ["--help"] diff --git a/plugins/nemo-experimentalist/README.md b/plugins/nemo-experimentalist/README.md index 4ccd8c7f72..1aa669074e 100644 --- a/plugins/nemo-experimentalist/README.md +++ b/plugins/nemo-experimentalist/README.md @@ -33,19 +33,21 @@ commit, currently one past `v0.0.6` that carries an MCP transport-timeout fix. ## Insight-to-experiment flow -The supported handoff is: +The Tau2 dogfood fixture exercises the supported handoff with three commands +after the Platform is running: -```text -nemo insights analyze → .nemo-optimizer/insights.yaml or Platform Insight ID - → nemo experimentalist doctor - → nemo experimentalist run +```bash +cd examples/tau2-nemo-oo-agent +nemo traces import state-v9 +nemo insights analyze +nemo experimentalist run ``` -Run `nemo insights analyze` using the Platform Insights plugin and its -documented trace, workspace, and output options. The producer may write the -local profile default, `.nemo-optimizer/insights.yaml`, or persist an Insight -on Platform and report its ID. The Experimentalist does not analyze traces, -schedule analysis, or host an Insight API. +See the fixture's [four-command playbook](examples/tau2-nemo-oo-agent/README.md) +for the required Platform services and credential file. The trace import writes +the selected workspace and corpus time range into profile-local workflow +context. Insights writes `.nemo-optimizer/insights.yaml`; Experimentalist reads +both files without workspace, base-URL, or Insight flags. From an agent directory with an `optimizer.yaml` profile, validate the effective inputs: @@ -54,18 +56,25 @@ effective inputs: $NEMO experimentalist doctor ``` -## Run the Experimentalist locally +## Run the Experimentalist + +`nemo experimentalist run` runs Experimentalist inside OpenShell by default. +The sandbox contains the optimization agents but has no Docker CLI or socket. +Harbor evaluation crosses a narrow API to the local bridge described in the +[OpenShell setup](src/nemo_experimentalist_plugin/openshell/README.md). +Rationalizer and TraceAnalyzer use bridge-owned task dependency sessions, so +their shell commands run inside the Harbor task environment without granting +Docker authority to the sandbox. -`nemo experimentalist run` runs the local Experimentalist loop. It evaluates -a baseline agent on Harbor-compatible train and validation datasets, proposes -candidate mutations, and records its artifacts under the selected experiment -directory. +From a source checkout, the CLI reuses a compatible +`local/nmp-experimentalist:local` image and otherwise builds that image for the +host architecture. Set `NEMO_EXPERIMENTALIST_IMAGE` to use a different image. -Configure the models before running an experiment: +The CLI starts an ephemeral Harbor bridge and configures the dedicated +OpenShell bridge, inference, and source-control providers for each run. Model +names remain ordinary environment settings: ```bash -export EXPERIMENTALIST_API_BASE=https://inference-api.nvidia.com/v1 -export EXPERIMENTALIST_API_KEY=sk-... export EXPERIMENTALIST_SMART_MODEL_NAME=openai/openai/openai/gpt-5.5 export EXPERIMENTALIST_FAST_MODEL_NAME=openai/openai/openai/gpt-5-mini ``` @@ -121,7 +130,9 @@ the agent needs framework-specific modification guidance. The checked-in Tau2 profile demonstrates profile-owned datasets and task template configuration: [`examples/tau2-nemo-oo-agent/optimizer.yaml`](examples/tau2-nemo-oo-agent/optimizer.yaml). -Each run writes its local artifacts under `--experiment-dir`, or under -`.nemo-optimizer/experiments/` beside the governing profile by default. +Each OpenShell run downloads its artifacts to `--experiment-dir`, or to +`./tmp/experimentalist-openshell` by default. +There is no host-execution mode or automatic fallback when OpenShell setup or +image preparation fails. License: Apache-2.0. diff --git a/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/.env.example b/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/.env.example new file mode 100644 index 0000000000..134cd16db8 --- /dev/null +++ b/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/.env.example @@ -0,0 +1,34 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Copy to `.env` in this directory: `nemo insights analyze` and +# `nemo experimentalist run` auto-load it from the profile dir on every run +# (variables already exported in your shell win). Use each command's `doctor` +# verb for owned prerequisites. + +# The one required credential: an NVIDIA Inference Gateway virtual key +# (sk-...). Use `nemo insights doctor` and `nemo experimentalist doctor` to verify +# the producer and consumer prerequisites respectively. +# Insights consumes it directly; Experimentalist fills EXPERIMENTALIST_API_KEY from it +# only when using the NVIDIA gateway. +INFERENCE_API_KEY=sk-... + +# Required to download the train and validation datasets from the internal +# GitLab registry configured in optimizer.yaml. The OpenShell launcher creates +# the narrow read-only provider automatically. +GITLAB_TOKEN=glpat-... + +# Only needed for a non-gateway LLM provider (then set both; the gateway key +# is never sent to a custom endpoint): +# EXPERIMENTALIST_API_BASE=https://inference-api.nvidia.com/v1 +# EXPERIMENTALIST_API_KEY=sk-... + +# Optional model overrides. Must be models your key serves — list them with: +# curl -s $EXPERIMENTALIST_API_BASE/models -H "Authorization: Bearer $EXPERIMENTALIST_API_KEY" +# EXPERIMENTALIST_SMART_MODEL_NAME=openai/openai/openai/gpt-5.5 +# EXPERIMENTALIST_FAST_MODEL_NAME=openai/openai/openai/gpt-5-mini + +# NeMo platform hosting traces/insights. Default is a local from-source +# platform; the team's shared remote is the freeplay instance. +# NMP_BASE_URL=http://localhost:8080 +# NMP_BASE_URL=https://nemo-platform-freeplay.dev.aire.nvidia.com diff --git a/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/.gitignore b/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/.gitignore new file mode 100644 index 0000000000..5becc36033 --- /dev/null +++ b/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/.gitignore @@ -0,0 +1,5 @@ +.env +.venv/ +.nemo-optimizer/ +tmp/ +uv.lock diff --git a/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/AGENT-SPEC.md b/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/AGENT-SPEC.md new file mode 100644 index 0000000000..bbec587f92 --- /dev/null +++ b/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/AGENT-SPEC.md @@ -0,0 +1,167 @@ +# Airline Agent Policy + +The current time is 2024-05-15 15:00:00 EST. + +As an airline agent, you can help users **book**, **modify**, or **cancel** flight reservations. You also handle **refunds and compensation**. + +Before taking any actions that update the booking database (booking, modifying flights, editing baggage, changing cabin class, or updating passenger information), you must list the action details and obtain explicit user confirmation (yes) to proceed. + +You should not provide any information, knowledge, or procedures not provided by the user or available tools, or give subjective recommendations or comments. + +You should only make one tool call at a time, and if you make a tool call, you should not respond to the user simultaneously. If you respond to the user, you should not make a tool call at the same time. + +You should deny user requests that are against this policy. + +You should transfer the user to a human agent if and only if the request cannot be handled within the scope of your actions. To transfer, first make a tool call to transfer_to_human_agents, and then send the message 'YOU ARE BEING TRANSFERRED TO A HUMAN AGENT. PLEASE HOLD ON.' to the user. + +## Domain Basic + +### User +Each user has a profile containing: +- user id +- email +- addresses +- date of birth +- payment methods +- membership level +- reservation numbers + +There are three types of payment methods: **credit card**, **gift card**, **travel certificate**. + +There are three membership levels: **regular**, **silver**, **gold**. + +### Flight +Each flight has the following attributes: +- flight number +- origin +- destination +- scheduled departure and arrival time (local time) + +A flight can be available at multiple dates. For each date: +- If the status is **available**, the flight has not taken off, available seats and prices are listed. +- If the status is **delayed** or **on time**, the flight has not taken off, cannot be booked. +- If the status is **flying**, the flight has taken off but not landed, cannot be booked. + +There are three cabin classes: **basic economy**, **economy**, **business**. **basic economy** is its own class, completely distinct from **economy**. + +Seat availability and prices are listed for each cabin class. + +### Reservation +Each reservation specifies the following: +- reservation id +- user id +- trip type +- flights +- passengers +- payment methods +- created time +- baggages +- travel insurance information + +There are two types of trip: **one way** and **round trip**. + +## Book flight + +The agent must first obtain the user id from the user. + +The agent should then ask for the trip type, origin, destination. + +Cabin: +- Cabin class must be the same across all the flights in a reservation. + +Passengers: +- Each reservation can have at most five passengers. +- The agent needs to collect the first name, last name, and date of birth for each passenger. +- All passengers must fly the same flights in the same cabin. + +Payment: +- Each reservation can use at most one travel certificate, at most one credit card, and at most three gift cards. +- The remaining amount of a travel certificate is not refundable. +- All payment methods must already be in user profile for safety reasons. + +Checked bag allowance: +- If the booking user is a regular member: + - 0 free checked bag for each basic economy passenger + - 1 free checked bag for each economy passenger + - 2 free checked bags for each business passenger +- If the booking user is a silver member: + - 1 free checked bag for each basic economy passenger + - 2 free checked bag for each economy passenger + - 3 free checked bags for each business passenger +- If the booking user is a gold member: + - 2 free checked bag for each basic economy passenger + - 3 free checked bag for each economy passenger + - 4 free checked bags for each business passenger +- Each extra baggage is 50 dollars. + +Do not add checked bags that the user does not need. + +Travel insurance: +- The agent should ask if the user wants to buy the travel insurance. +- The travel insurance is 30 dollars per passenger and enables full refund if the user needs to cancel the flight given health or weather reasons. + +## Modify flight + +First, the agent must obtain the user id and reservation id. +- The user must provide their user id. +- If the user doesn't know their reservation id, the agent should help locate it using available tools. + +Change flights: +- Basic economy flights cannot be modified. +- Other reservations can be modified without changing the origin, destination, and trip type. +- Some flight segments can be kept, but their prices will not be updated based on the current price. +- The API does not check these for the agent, so the agent must make sure the rules apply before calling the API! + +Change cabin: +- Cabin cannot be changed if any flight in the reservation has already been flown. +- In other cases, all reservations, including basic economy, can change cabin without changing the flights. +- Cabin class must remain the same across all the flights in the same reservation; changing cabin for just one flight segment is not possible. +- If the price after cabin change is higher than the original price, the user is required to pay for the difference. +- If the price after cabin change is lower than the original price, the user is should be refunded the difference. + +Change baggage and insurance: +- The user can add but not remove checked bags. +- The user cannot add insurance after initial booking. + +Change passengers: +- The user can modify passengers but cannot modify the number of passengers. +- Even a human agent cannot modify the number of passengers. + +Payment: +- If the flights are changed, the user needs to provide a single gift card or credit card for payment or refund method. The payment method must already be in user profile for safety reasons. + +## Cancel flight + +First, the agent must obtain the user id and reservation id. +- The user must provide their user id. +- If the user doesn't know their reservation id, the agent should help locate it using available tools. + +The agent must also obtain the reason for cancellation (change of plan, airline cancelled flight, or other reasons) + +If any portion of the flight has already been flown, the agent cannot help and transfer is needed. + +Otherwise, flight can be cancelled if any of the following is true: +- The booking was made within the last 24 hrs +- The flight is cancelled by airline +- It is a business flight +- The user has travel insurance and the reason for cancellation is covered by insurance. + +The API does not check that cancellation rules are met, so the agent must make sure the rules apply before calling the API! + +Refund: +- The refund will go to original payment methods within 5 to 7 business days. + +## Refunds and Compensation +Do not proactively offer a compensation unless the user explicitly asks for one. + +Do not compensate if the user is regular member and has no travel insurance and flies (basic) economy. + +Always confirms the facts before offering compensation. + +Only compensate if the user is a silver/gold member or has travel insurance or flies business. + +- If the user complains about cancelled flights in a reservation, the agent can offer a certificate as a gesture after confirming the facts, with the amount being $100 times the number of passengers. + +- If the user complains about delayed flights in a reservation and wants to change or cancel the reservation, the agent can offer a certificate as a gesture after confirming the facts and changing or cancelling the reservation, with the amount being $50 times the number of passengers. + +Do not offer compensation for any other reason than the ones listed above. \ No newline at end of file diff --git a/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/README.md b/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/README.md new file mode 100644 index 0000000000..f2a7927d77 --- /dev/null +++ b/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/README.md @@ -0,0 +1,52 @@ + + + +# Tau2 NeMo OO Agent optimization fixture + +This is the agent under test for the NeMo Experimentalist dogfood flow. The +checked-in `optimizer.yaml` connects the existing `state-v9` trace corpus, +NeMo Insights, and the Dockerless OpenShell Experimentalist runtime. + +## Prerequisites + +Run from a bootstrapped NeMo Platform source checkout with Docker Desktop and +OpenShell available. The Platform must expose `auth`, `entities`, `intake`, +`models`, `inference-gateway`, and `secrets`, plus the `models` controller. +Intake's ClickHouse span store must also be running. + +If the Platform is not already running: + +```bash +nemo services start \ + --services auth,entities,intake,models,inference-gateway,secrets \ + --controllers models \ + --sidecars clickhouse +``` + +Copy `.env.example` to the ignored `.env` file and fill in the inference key. +The internal GitLab dataset registry also requires `GITLAB_TOKEN`. + +## Four-command playbook + +From this directory: + +```bash +nemo traces import state-v9 +nemo insights analyze +nemo experimentalist run +``` + +`nemo traces import` downloads the existing 270-span corpus, restores it into +the profile's `tau2-airline` workspace, and records the corpus time range. +`nemo insights analyze` reads that context and writes +`.nemo-optimizer/insights.yaml`. If the file contains multiple Insights, +`nemo experimentalist run` prompts for one before it starts OpenShell. + +The Experimentalist command starts its ephemeral Harbor bridge, configures the +dedicated OpenShell providers, selects the Docker Desktop policy on macOS, +builds or reuses the container image, runs the optimization loop, downloads +the artifacts, and stops the bridge. + +The fixture assumes the published `nemo-oo-airline` traces represent this +checked-in agent revision. That provenance is not encoded in the legacy +`state-v9` bundle. diff --git a/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/agent.py b/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/agent.py new file mode 100644 index 0000000000..2db29ead55 --- /dev/null +++ b/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/agent.py @@ -0,0 +1,51 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 + +import os + +import requests # noqa: F401 +from nooa import Agent, CodeActStrategy, strategy +from nooa.config import CodeActConfig +from nooa.mcp import MCPManager +from nooa.tools import ShellTools +from nooa.tracing import enable_tracing, exporters +from nooa.unifiedllm import CompletionClient + +enable_tracing( + exporters=[ + exporters.jsonl(trace_dir="/app/traces/"), + ] +) + +llm = CompletionClient( + model=os.environ.get("NEMO_AGENT_MODEL", "openai/azure/anthropic/claude-haiku-4-5"), + api_key=os.environ.get("INFERENCE_API_KEY"), + api_base=os.environ.get("INFERENCE_BASE_URL", "https://inference-api.nvidia.com/v1"), +) + + +class Codeact(Agent, llm=llm): + def __init__(self, *args, **kwargs): + super().__init__(*args, **kwargs) + self.shell = ShellTools() + self.tau3_runtime = MCPManager.create_from_server( + "tau3-runtime", + url=os.environ.get("TAU3_RUNTIME_URL", "http://tau3-runtime:8000/mcp"), + transport="streamable-http", + ) + + @strategy(CodeActStrategy(config=CodeActConfig(max_iterations=60))) + async def solve(self, instruction: str) -> None: + """Solve the task given the instruction. + + Start by calling ``await self.tau3_runtime.start_conversation()``. Use + the returned state and subsequent tau3-runtime tools to complete the + conversation before returning. + """ + self.context["instruction"] = instruction + self.context["mcp_usage"] = ( + "Use await self.tau3_runtime.(...) to call the " + "tau3-runtime MCP tools. Start with " + "await self.tau3_runtime.start_conversation()." + ) + ... diff --git a/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/dataset/template/task_template/environment/Dockerfile b/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/dataset/template/task_template/environment/Dockerfile new file mode 100644 index 0000000000..38c188b207 --- /dev/null +++ b/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/dataset/template/task_template/environment/Dockerfile @@ -0,0 +1,18 @@ +FROM python:3.12-slim@sha256:57cd7c3a7a273101a6485ba99423ee568157882804b1124b4dd04266317710de + +WORKDIR /app + +ARG TAU2_BENCH_REPO="https://github.com/sierra-research/tau2-bench.git" +ARG TAU2_BENCH_REF="363133ada1936491fb5bcec33cd62c3518a99f65" + +ENV TAU2_BENCH_ROOT=/opt/tau2-bench +ENV TAU2_DATA_DIR=/opt/tau2-bench/data + +RUN apt-get update && apt-get install -y --no-install-recommends \ + git \ + && git init "${TAU2_BENCH_ROOT}" \ + && git -C "${TAU2_BENCH_ROOT}" remote add origin "${TAU2_BENCH_REPO}" \ + && git -C "${TAU2_BENCH_ROOT}" fetch --depth=1 origin "${TAU2_BENCH_REF}" \ + && git -C "${TAU2_BENCH_ROOT}" checkout --detach FETCH_HEAD \ + && pip install --no-cache-dir uv "${TAU2_BENCH_ROOT}[knowledge]" \ + && rm -rf /var/lib/apt/lists/* diff --git a/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/dataset/template/task_template/environment/docker-compose.yaml b/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/dataset/template/task_template/environment/docker-compose.yaml new file mode 100644 index 0000000000..8baf672cfd --- /dev/null +++ b/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/dataset/template/task_template/environment/docker-compose.yaml @@ -0,0 +1,27 @@ +services: + main: + depends_on: + tau3-runtime: + condition: service_healthy + environment: + - INFERENCE_API_KEY=${INFERENCE_API_KEY:-} + - INFERENCE_BASE_URL=${INFERENCE_BASE_URL:-https://inference-api.nvidia.com/v1} + + tau3-runtime: + build: + context: ./runtime-server + environment: + - INFERENCE_API_KEY=${INFERENCE_API_KEY:-} + - INFERENCE_BASE_URL=${INFERENCE_BASE_URL:-https://inference-api.nvidia.com/v1} + - TAU2_USER_MODEL=${TAU2_USER_MODEL:-openai/openai/gpt-5.2} + - TAU2_USER_REASONING_EFFORT=${TAU2_USER_REASONING_EFFORT:-low} + volumes: + - ${HOST_AGENT_LOGS_PATH}:${ENV_AGENT_LOGS_PATH} + expose: + - "8000" + healthcheck: + test: ["CMD", "python3", "-c", "import socket; s=socket.create_connection(('localhost',8000),timeout=2); s.close()"] + interval: 2s + timeout: 5s + retries: 15 + start_period: 5s diff --git a/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/dataset/template/task_template/environment/runtime-server/Dockerfile b/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/dataset/template/task_template/environment/runtime-server/Dockerfile new file mode 100644 index 0000000000..25444f6020 --- /dev/null +++ b/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/dataset/template/task_template/environment/runtime-server/Dockerfile @@ -0,0 +1,27 @@ +FROM python:3.12-slim@sha256:57cd7c3a7a273101a6485ba99423ee568157882804b1124b4dd04266317710de + +WORKDIR /app + +ARG TAU2_BENCH_REPO="https://github.com/sierra-research/tau2-bench.git" +ARG TAU2_BENCH_REF="363133ada1936491fb5bcec33cd62c3518a99f65" + +ENV TAU2_BENCH_ROOT=/opt/tau2-bench +ENV TAU2_DATA_DIR=/opt/tau2-bench/data +ENV PYTHONUNBUFFERED=1 + +RUN apt-get update && apt-get install -y --no-install-recommends \ + git \ + && git init "${TAU2_BENCH_ROOT}" \ + && git -C "${TAU2_BENCH_ROOT}" remote add origin "${TAU2_BENCH_REPO}" \ + && git -C "${TAU2_BENCH_ROOT}" fetch --depth=1 origin "${TAU2_BENCH_REF}" \ + && git -C "${TAU2_BENCH_ROOT}" checkout --detach FETCH_HEAD \ + && pip install --no-cache-dir uv "${TAU2_BENCH_ROOT}[knowledge]" "fastmcp>=3.0" \ + && apt-get purge -y --auto-remove git \ + && rm -rf /var/lib/apt/lists/* + +COPY server.py ./ +COPY task_config.json ./ + +EXPOSE 8000 + +CMD ["python3", "server.py"] diff --git a/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/dataset/template/task_template/environment/runtime-server/server.py b/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/dataset/template/task_template/environment/runtime-server/server.py new file mode 100644 index 0000000000..7835799a5d --- /dev/null +++ b/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/dataset/template/task_template/environment/runtime-server/server.py @@ -0,0 +1,636 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 + +from __future__ import annotations + +import inspect +import json +import os +import sys +from copy import deepcopy +from pathlib import Path +from typing import Any, Callable + +from fastmcp import FastMCP + + +def make_domain_tool_handler( + tool: Any, + call_assistant_tool: Callable[[str, dict[str, Any]], str], +) -> Callable[..., str]: + tool_name = tool.name + raw_signature = getattr(tool, "__signature__", None) or inspect.signature(tool) + signature = raw_signature.replace(return_annotation=str) + + annotations: dict[str, Any] = {"return": str} + for param_name, param in signature.parameters.items(): + annotation = param.annotation + if annotation is inspect.Signature.empty: + annotation = Any + annotations[param_name] = annotation + + def _tool_handler(**kwargs: Any) -> str: + return call_assistant_tool(tool_name, kwargs) + + _tool_handler.__name__ = tool_name + _tool_handler.__qualname__ = tool_name + _tool_handler.__doc__ = getattr(tool, "__doc__", None) or (f"Call the {tool_name} tool.") + _tool_handler.__signature__ = signature + _tool_handler.__annotations__ = annotations + return _tool_handler + + +TAU2_RUNTIME_ROOT = Path("/opt/tau2-bench") +TASK_CONFIG_PATH = Path("/app/task_config.json") +STATE_LOG_PATH = Path(os.environ.get("TAU3_RUNTIME_STATE_PATH", "/logs/agent/tau3_runtime_state.json")) +DEFAULT_INFERENCE_BASE_URL = "https://inference-api.nvidia.com/v1" + +mcp = FastMCP("tau3-runtime") + + +def _to_litellm_model(model_name: str) -> str: + if ( + (os.getenv("INFERENCE_API_KEY") or os.getenv("INFERENCE_BASE_URL")) + and model_name.startswith("openai/openai/") + and not model_name.startswith("openai/openai/openai/") + ): + return f"openai/{model_name}" + return model_name + + +def _require_attr(module_name: str, attr_name: str) -> Any: + module = __import__(module_name, fromlist=[attr_name]) + return getattr(module, attr_name) + + +def _prepare_tau2_imports() -> None: + src = TAU2_RUNTIME_ROOT / "src" + if not (src / "tau2").exists(): + raise ImportError(f"Could not locate tau2 sources under {src}") + + sys.path.insert(0, str(src)) + if not os.getenv("TAU2_DATA_DIR"): + data_dir = TAU2_RUNTIME_ROOT / "data" + if data_dir.exists(): + os.environ["TAU2_DATA_DIR"] = str(data_dir) + + +def _build_user_llm_args(*, seed: int | None = None, override_json: str | None = None) -> dict[str, Any]: + if override_json: + decoded = json.loads(override_json) + if not isinstance(decoded, dict): + raise ValueError("User LLM args override must decode to a JSON object.") + llm_args: dict[str, Any] = decoded + else: + llm_args = {} + + temperature = os.getenv("TAU2_USER_TEMPERATURE") + if temperature: + llm_args["temperature"] = float(temperature) + + reasoning_effort = os.getenv("TAU2_USER_REASONING_EFFORT", "low").strip() + if reasoning_effort: + llm_args["reasoning_effort"] = reasoning_effort + + api_key = os.getenv("INFERENCE_API_KEY") + api_base = os.getenv("INFERENCE_BASE_URL", DEFAULT_INFERENCE_BASE_URL) + if api_key: + llm_args.setdefault("api_key", api_key) + if api_base: + llm_args.setdefault("api_base", api_base) + if seed is not None: + llm_args["seed"] = seed + + return llm_args + + +def _get_tau2_domain_constructor(domain: str, config: dict[str, Any], task_model: Any) -> tuple[Any, dict[str, Any]]: + if domain == "airline": + return _require_attr("tau2.domains.airline.environment", "get_environment"), {} + if domain == "retail": + return _require_attr("tau2.domains.retail.environment", "get_environment"), {} + if domain == "telecom": + return ( + _require_attr("tau2.domains.telecom.environment", "get_environment_manual_policy"), + {}, + ) + if domain == "banking_knowledge": + return _require_attr("tau2.domains.banking_knowledge.environment", "get_environment"), { + "retrieval_variant": str(config.get("retrieval_variant") or "bm25"), + "task": task_model, + } + raise ValueError(f"Unsupported tau2 domain: {domain}") + + +class Tau3Runtime: + def __init__(self, config_path: Path): + _prepare_tau2_imports() + + self.config = json.loads(config_path.read_text(encoding="utf-8")) + self.domain = str(self.config["domain"]) + + self.Task = _require_attr("tau2.data_model.tasks", "Task") + self.ToolCall = _require_attr("tau2.data_model.message", "ToolCall") + self.ToolMessage = _require_attr("tau2.data_model.message", "ToolMessage") + self.AssistantMessage = _require_attr("tau2.data_model.message", "AssistantMessage") + self.UserMessage = _require_attr("tau2.data_model.message", "UserMessage") + self.MultiToolMessage = _require_attr("tau2.data_model.message", "MultiToolMessage") + self.TerminationReason = _require_attr("tau2.data_model.simulation", "TerminationReason") + self.DEFAULT_FIRST_AGENT_MESSAGE = _require_attr( + "tau2.orchestrator.orchestrator", "DEFAULT_FIRST_AGENT_MESSAGE" + ) + self.UserSimulator = _require_attr("tau2.user.user_simulator", "UserSimulator") + self.is_valid_user_history_message = _require_attr( + "tau2.user.user_simulator_base", "is_valid_user_history_message" + ) + + self.task = self.Task.model_validate(self.config["task"]) + self.environment_constructor, self.env_kwargs = _get_tau2_domain_constructor( + self.domain, self.config, self.task + ) + self.environment = self.environment_constructor(solo_mode=False, **self.env_kwargs) + + self.messages: list[Any] = [] + self.termination_reason: str | None = None + self.step_count = 0 + self.num_errors = 0 + self.max_steps = int(self.config.get("max_steps") or 200) + self.max_errors = int(self.config.get("max_errors") or 10) + self.seed: int | None = None + self.bootstrap_complete = False + self.start_tool_called = False + self.last_agent_observation: str = "" + + initial_state = self.task.initial_state + initialization_data = initial_state.initialization_data if initial_state is not None else None + initialization_actions = initial_state.initialization_actions if initial_state is not None else None + message_history = ( + deepcopy(initial_state.message_history) + if initial_state is not None and initial_state.message_history is not None + else [] + ) + self.environment.set_state( + initialization_data=initialization_data, + initialization_actions=initialization_actions, + message_history=message_history, + ) + self.messages = list(message_history) + + user_tools = None + try: + user_tools = self.environment.get_user_tools(include=self.task.user_tools) or None + except Exception: + user_tools = None + + self.user = self.UserSimulator( + llm=_to_litellm_model(os.getenv("TAU2_USER_MODEL", "openai/openai/gpt-5.2")), + instructions=str(self.task.user_scenario), + tools=user_tools, + llm_args=_build_user_llm_args(), + ) + + self._bootstrap_mode = "fresh" + self._bootstrap_message: Any | None = None + self._initialize_user_state(message_history) + self._tool_call_counter = self._count_existing_tool_calls(self.messages) + self._write_state() + + def _count_existing_tool_calls(self, messages: list[Any]) -> int: + count = 0 + for message in messages: + tool_calls = getattr(message, "tool_calls", None) + if tool_calls: + count += len(tool_calls) + return count + + def _initialize_user_state(self, message_history: list[Any]) -> None: + if not message_history: + self.user_state = self.user.get_init_state() + self._bootstrap_mode = "fresh" + self._bootstrap_message = None + return + + valid_user_history = [msg for msg in message_history if self.is_valid_user_history_message(msg)] + valid_user_history_without_last = [ + msg for msg in message_history[:-1] if self.is_valid_user_history_message(msg) + ] + last_message = message_history[-1] + + if isinstance(last_message, self.AssistantMessage): + self._bootstrap_message = last_message + if last_message.is_tool_call(): + self.user_state = self.user.get_init_state(valid_user_history) + self._bootstrap_mode = "assistant_tool_call" + else: + self.user_state = self.user.get_init_state(valid_user_history_without_last) + self._bootstrap_mode = "assistant_to_user" + return + + if isinstance(last_message, self.UserMessage): + self.user_state = self.user.get_init_state(valid_user_history) + self._bootstrap_message = last_message + self._bootstrap_mode = "user_tool_call" if last_message.is_tool_call() else "pending_user_message" + return + + if isinstance(last_message, self.ToolMessage): + self._bootstrap_message = last_message + if last_message.requestor == "assistant": + self.user_state = self.user.get_init_state(valid_user_history) + self._bootstrap_mode = "assistant_tool_result" + else: + self.user_state = self.user.get_init_state(valid_user_history_without_last) + self._bootstrap_mode = "user_tool_result" + return + + raise ValueError(f"Unsupported last message type: {type(last_message)}") + + def _next_tool_call_id(self) -> str: + self._tool_call_counter += 1 + return f"runtime_tool_{self._tool_call_counter}" + + def _write_state(self) -> None: + STATE_LOG_PATH.parent.mkdir(parents=True, exist_ok=True) + payload = { + "domain": self.domain, + "task_id": self.task.id, + "termination_reason": self.termination_reason, + "step_count": self.step_count, + "num_errors": self.num_errors, + "max_steps": self.max_steps, + "max_errors": self.max_errors, + "seed": self.seed, + "bootstrap_complete": self.bootstrap_complete, + "start_tool_called": self.start_tool_called, + "messages": [message.model_dump(mode="json") for message in self.messages], + } + STATE_LOG_PATH.write_text(json.dumps(payload, indent=2), encoding="utf-8") + + def _require_active(self) -> None: + if self.termination_reason is not None: + raise RuntimeError(f"Conversation has already ended with reason '{self.termination_reason}'.") + + def _check_termination(self) -> None: + if self.step_count >= self.max_steps: + self.termination_reason = self.TerminationReason.MAX_STEPS.value + if self.num_errors >= self.max_errors: + self.termination_reason = self.TerminationReason.TOO_MANY_ERRORS.value + + def _finish_step(self, *, waiting_for_environment: bool = False) -> None: + self.step_count += 1 + self.environment.sync_tools() + if not waiting_for_environment: + self._check_termination() + self._write_state() + + def _execute_tool_calls(self, tool_calls: list[Any]) -> list[Any]: + results = [self.environment.get_response(tool_call) for tool_call in tool_calls] + for result in results: + if getattr(result, "error", False): + self.num_errors += 1 + self.messages.extend(results) + self._write_state() + return results + + def _execute_environment_step(self, tool_calls: list[Any]) -> list[Any]: + tool_results = self._execute_tool_calls(tool_calls) + self._finish_step() + return tool_results + + def _wrap_tool_results(self, tool_results: list[Any]) -> Any: + if len(tool_results) == 1: + return tool_results[0] + return self.MultiToolMessage(role="tool", tool_messages=tool_results) + + def _format_observation(self, message: Any) -> str: + if isinstance(message, self.MultiToolMessage): + return "\n\n".join(tool_message.content or "" for tool_message in message.tool_messages) + content = getattr(message, "content", None) + return "" if content is None else str(content) + + def _run_user_until_agent_observation(self, incoming_message: Any) -> Any: + current_message = incoming_message + while True: + self._require_active() + user_message, self.user_state = self.user.generate_next_message(current_message, self.user_state) + user_message.validate() + self.messages.append(user_message) + if self.UserSimulator.is_stop(user_message): + self.termination_reason = self.TerminationReason.USER_STOP.value + self._finish_step() + return user_message + + if user_message.is_tool_call(): + self._finish_step(waiting_for_environment=True) + self._require_active() + tool_results = self._execute_environment_step(user_message.tool_calls) + current_message = self._wrap_tool_results(tool_results) + if self.termination_reason is not None: + return current_message + continue + + self._finish_step() + return user_message + + def _bootstrap(self) -> str: + if self.bootstrap_complete: + return self.last_agent_observation + + mode = self._bootstrap_mode + observation_message: Any + + if mode == "fresh": + first_message = deepcopy(self.DEFAULT_FIRST_AGENT_MESSAGE) + self.messages.append(first_message) + self._write_state() + observation_message = self._run_user_until_agent_observation(first_message) + elif mode == "pending_user_message": + observation_message = self._bootstrap_message + elif mode == "assistant_to_user": + observation_message = self._run_user_until_agent_observation(self._bootstrap_message) + elif mode == "user_tool_call": + tool_results = self._execute_environment_step(self._bootstrap_message.tool_calls) + observation_message = self._run_user_until_agent_observation(self._wrap_tool_results(tool_results)) + elif mode == "assistant_tool_call": + tool_results = self._execute_environment_step(self._bootstrap_message.tool_calls) + observation_message = self._wrap_tool_results(tool_results) + elif mode == "assistant_tool_result": + observation_message = self._bootstrap_message + elif mode == "user_tool_result": + observation_message = self._run_user_until_agent_observation(self._bootstrap_message) + else: + raise ValueError(f"Unsupported bootstrap mode: {mode}") + + self.bootstrap_complete = True + self.last_agent_observation = self._format_observation(observation_message) + self._write_state() + return self.last_agent_observation + + def configure_run( + self, + *, + seed: int | None = None, + max_steps: int | None = None, + max_errors: int | None = None, + user_llm_args_json: str | None = None, + ) -> str: + if self.bootstrap_complete: + raise RuntimeError("Run must be configured before start_conversation.") + + if max_steps is not None: + self.max_steps = max_steps + if max_errors is not None: + self.max_errors = max_errors + self.seed = seed + self.user.llm_args = _build_user_llm_args( + seed=seed, + override_json=user_llm_args_json or os.getenv("TAU2_USER_LLM_ARGS_JSON"), + ) + self._write_state() + return self.get_runtime_status() + + def get_runtime_status(self) -> str: + return json.dumps( + { + "termination_reason": self.termination_reason, + "step_count": self.step_count, + "num_errors": self.num_errors, + "max_steps": self.max_steps, + "max_errors": self.max_errors, + "seed": self.seed, + }, + sort_keys=True, + ) + + def get_assistant_tool_schemas(self) -> str: + schemas = [tool.openai_schema for tool in self.environment.get_tools()] + return json.dumps(schemas, sort_keys=True) + + def start_conversation(self) -> str: + self.start_tool_called = True + observation = self._bootstrap() + self._write_state() + return observation + + def submit_assistant_message(self, message: str) -> str: + if not message.strip(): + raise ValueError("Message must not be empty.") + self._require_active() + if not self.bootstrap_complete: + raise RuntimeError("Call start_conversation before messaging the user.") + + assistant_message = self.AssistantMessage(role="assistant", content=message) + assistant_message.validate() + self.messages.append(assistant_message) + + if "###STOP###" in message: + self.termination_reason = self.TerminationReason.AGENT_STOP.value + self._finish_step() + return json.dumps( + { + "observation": None, + "termination_reason": self.termination_reason, + "step_count": self.step_count, + "num_errors": self.num_errors, + }, + sort_keys=True, + ) + + self._finish_step() + if self.termination_reason is not None: + return json.dumps( + { + "observation": None, + "termination_reason": self.termination_reason, + "step_count": self.step_count, + "num_errors": self.num_errors, + }, + sort_keys=True, + ) + + observation_message = self._run_user_until_agent_observation(assistant_message) + self.last_agent_observation = self._format_observation(observation_message) + self._write_state() + return json.dumps( + { + "observation": self.last_agent_observation, + "termination_reason": self.termination_reason, + "step_count": self.step_count, + "num_errors": self.num_errors, + }, + sort_keys=True, + ) + + def send_message_to_user(self, message: str) -> str: + response = json.loads(self.submit_assistant_message(message)) + return str(response.get("observation") or "") + + def submit_assistant_tool_calls(self, tool_calls_json: str, content: str | None = None) -> str: + self._require_active() + if not self.bootstrap_complete: + raise RuntimeError("Call start_conversation before using domain tools.") + + raw_tool_calls = json.loads(tool_calls_json) + if not isinstance(raw_tool_calls, list): + raise ValueError("tool_calls_json must decode to a list.") + + tool_calls = [] + for raw_call in raw_tool_calls: + if not isinstance(raw_call, dict): + raise ValueError("Each tool call must be an object.") + tool_calls.append( + self.ToolCall( + id=str(raw_call["id"]), + name=str(raw_call["name"]), + arguments=dict(raw_call.get("arguments") or {}), + requestor="assistant", + ) + ) + + assistant_message = self.AssistantMessage(role="assistant", tool_calls=tool_calls, content=content) + assistant_message.validate() + self.messages.append(assistant_message) + self._finish_step(waiting_for_environment=True) + self._require_active() + + tool_results = self._execute_environment_step(tool_calls) + observation = self._format_observation(self._wrap_tool_results(tool_results)) + self.last_agent_observation = observation + self._write_state() + return json.dumps( + { + "tool_results": [ + { + "id": tool_result.id, + "content": tool_result.content or "", + "error": bool(getattr(tool_result, "error", False)), + } + for tool_result in tool_results + ], + "observation": observation, + "termination_reason": self.termination_reason, + "step_count": self.step_count, + "num_errors": self.num_errors, + }, + sort_keys=True, + ) + + def call_assistant_tool(self, tool_name: str, arguments: dict[str, Any]) -> str: + self._require_active() + if not self.bootstrap_complete: + raise RuntimeError("Call start_conversation before using domain tools.") + + tool_call = self.ToolCall( + id=self._next_tool_call_id(), + name=tool_name, + arguments=arguments, + requestor="assistant", + ) + assistant_message = self.AssistantMessage(role="assistant", tool_calls=[tool_call], content=None) + assistant_message.validate() + self.messages.append(assistant_message) + self._finish_step(waiting_for_environment=True) + self._require_active() + tool_results = self._execute_environment_step([tool_call]) + observation = self._format_observation(self._wrap_tool_results(tool_results)) + self.last_agent_observation = observation + self._write_state() + return observation + + def end_conversation(self, message: str = "###STOP###") -> str: + if self.termination_reason is not None: + return f"Conversation already ended with reason '{self.termination_reason}'." + if not self.bootstrap_complete: + raise RuntimeError("Call start_conversation before ending the conversation.") + + stop_message = self.AssistantMessage(role="assistant", content=message) + stop_message.validate() + self.messages.append(stop_message) + self.termination_reason = self.TerminationReason.AGENT_STOP.value + self._finish_step() + return "Conversation ended." + + def record_termination(self, reason: str) -> str: + if reason not in {item.value for item in self.TerminationReason}: + raise ValueError(f"Unsupported termination reason: {reason}") + self.termination_reason = reason + self._write_state() + return self.get_runtime_status() + + +runtime = Tau3Runtime(TASK_CONFIG_PATH) + + +@mcp.tool() +def configure_run( + seed: int | None = None, + max_steps: int | None = None, + max_errors: int | None = None, + user_llm_args_json: str | None = None, +) -> str: + """Configure tau2 run parameters before the first conversation turn.""" + return runtime.configure_run( + seed=seed, + max_steps=max_steps, + max_errors=max_errors, + user_llm_args_json=user_llm_args_json, + ) + + +@mcp.tool() +def get_runtime_status() -> str: + """Return tau2-style runtime step, error, seed, and termination metadata.""" + return runtime.get_runtime_status() + + +@mcp.tool() +def get_assistant_tool_schemas() -> str: + """Return the original tau2 OpenAI tool schemas for assistant tools.""" + return runtime.get_assistant_tool_schemas() + + +@mcp.tool() +def start_conversation() -> str: + """Start or resume the task conversation and return the current observation for the agent.""" + return runtime.start_conversation() + + +@mcp.tool() +def submit_assistant_message(message: str) -> str: + """Record an assistant message and advance the tau2 runtime.""" + return runtime.submit_assistant_message(message) + + +@mcp.tool() +def submit_assistant_tool_calls(tool_calls_json: str, content: str | None = None) -> str: + """Record one assistant tool-call message and execute all requested tools.""" + return runtime.submit_assistant_tool_calls(tool_calls_json, content) + + +@mcp.tool() +def send_message_to_user(message: str) -> str: + """Send a message to the user and return the user's next message.""" + return runtime.send_message_to_user(message) + + +@mcp.tool() +def end_conversation(message: str = "###STOP###") -> str: + """End the conversation once the user's issue has been resolved.""" + return runtime.end_conversation(message) + + +@mcp.tool() +def record_termination(reason: str) -> str: + """Record a non-success tau2 termination reason.""" + return runtime.record_termination(reason) + + +def _register_domain_tools() -> None: + for tool in runtime.environment.get_tools(): + mcp.tool()(make_domain_tool_handler(tool, runtime.call_assistant_tool)) + + +_register_domain_tools() + + +if __name__ == "__main__": + mcp.run(transport="streamable-http", host="0.0.0.0", port=8000) diff --git a/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/dataset/template/task_template/environment/runtime-server/task_config.json b/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/dataset/template/task_template/environment/runtime-server/task_config.json new file mode 100644 index 0000000000..9cd888b55d --- /dev/null +++ b/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/dataset/template/task_template/environment/runtime-server/task_config.json @@ -0,0 +1,42 @@ +{ + "domain": "airline", + "source_task_id": "{{source_task_id}}", + "retrieval_variant": null, + "task": { + "id": "{{task_id}}", + "description": { + "purpose": "{{purpose}}", + "relevant_policies": null, + "notes": null + }, + "user_scenario": { + "persona": null, + "instructions": { + "task_instructions": "{{task_instructions}}", + "domain": "airline", + "reason_for_call": "{{reason_for_call}}", + "known_info": "You are {{name}}.\nYour user id is {{user_id}}.", + "unknown_info": null + } + }, + "initial_state": null, + "evaluation_criteria": { + "actions": [], + "communicate_info": [], + "nl_assertions": [ + "{{nl_assertions}}" + ], + "reward_basis": [ + "DB", + "COMMUNICATE" + ] + }, + "annotations": null + }, + "expected_actions": [], + "expected_communicate_info": [], + "reward_basis": [ + "DB", + "COMMUNICATE" + ] +} \ No newline at end of file diff --git a/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/dataset/template/task_template/instruction.md b/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/dataset/template/task_template/instruction.md new file mode 100644 index 0000000000..0576b9cef5 --- /dev/null +++ b/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/dataset/template/task_template/instruction.md @@ -0,0 +1,182 @@ + +You are a customer service agent that helps a simulated user according to the provided below. + +Use the MCP tools exposed by the `tau3-runtime` server: +- Call `start_conversation` exactly once at the beginning to start or resume the conversation and get the current user message. +- Call `send_message_to_user` whenever you want to say something to the user. It returns the user's next message after any user-side tool interactions have been completed. +- Use the domain tools on the same MCP server to inspect or modify the environment. +- When you are confident the case is resolved, end the conversation. If your agent emits stop tokens directly, reply with `###STOP###`; otherwise call `end_conversation`. + +In each step, either talk to the user or call a domain tool. Do not combine both in the same step. +Always follow the policy. + + + +# Airline Agent Policy + +The current time is 2024-05-15 15:00:00 EST. + +As an airline agent, you can help users **book**, **modify**, or **cancel** flight reservations. You also handle **refunds and compensation**. + +Before taking any actions that update the booking database (booking, modifying flights, editing baggage, changing cabin class, or updating passenger information), you must list the action details and obtain explicit user confirmation (yes) to proceed. + +You should not provide any information, knowledge, or procedures not provided by the user or available tools, or give subjective recommendations or comments. + +You should only make one tool call at a time, and if you make a tool call, you should not respond to the user simultaneously. If you respond to the user, you should not make a tool call at the same time. + +You should deny user requests that are against this policy. + +You should transfer the user to a human agent if and only if the request cannot be handled within the scope of your actions. To transfer, first make a tool call to transfer_to_human_agents, and then send the message 'YOU ARE BEING TRANSFERRED TO A HUMAN AGENT. PLEASE HOLD ON.' to the user. + +## Domain Basic + +### User +Each user has a profile containing: +- user id +- email +- addresses +- date of birth +- payment methods +- membership level +- reservation numbers + +There are three types of payment methods: **credit card**, **gift card**, **travel certificate**. + +There are three membership levels: **regular**, **silver**, **gold**. + +### Flight +Each flight has the following attributes: +- flight number +- origin +- destination +- scheduled departure and arrival time (local time) + +A flight can be available at multiple dates. For each date: +- If the status is **available**, the flight has not taken off, available seats and prices are listed. +- If the status is **delayed** or **on time**, the flight has not taken off, cannot be booked. +- If the status is **flying**, the flight has taken off but not landed, cannot be booked. + +There are three cabin classes: **basic economy**, **economy**, **business**. **basic economy** is its own class, completely distinct from **economy**. + +Seat availability and prices are listed for each cabin class. + +### Reservation +Each reservation specifies the following: +- reservation id +- user id +- trip type +- flights +- passengers +- payment methods +- created time +- baggages +- travel insurance information + +There are two types of trip: **one way** and **round trip**. + +## Book flight + +The agent must first obtain the user id from the user. + +The agent should then ask for the trip type, origin, destination. + +Cabin: +- Cabin class must be the same across all the flights in a reservation. + +Passengers: +- Each reservation can have at most five passengers. +- The agent needs to collect the first name, last name, and date of birth for each passenger. +- All passengers must fly the same flights in the same cabin. + +Payment: +- Each reservation can use at most one travel certificate, at most one credit card, and at most three gift cards. +- The remaining amount of a travel certificate is not refundable. +- All payment methods must already be in user profile for safety reasons. + +Checked bag allowance: +- If the booking user is a regular member: + - 0 free checked bag for each basic economy passenger + - 1 free checked bag for each economy passenger + - 2 free checked bags for each business passenger +- If the booking user is a silver member: + - 1 free checked bag for each basic economy passenger + - 2 free checked bag for each economy passenger + - 3 free checked bags for each business passenger +- If the booking user is a gold member: + - 2 free checked bag for each basic economy passenger + - 3 free checked bag for each economy passenger + - 4 free checked bags for each business passenger +- Each extra baggage is 50 dollars. + +Do not add checked bags that the user does not need. + +Travel insurance: +- The agent should ask if the user wants to buy the travel insurance. +- The travel insurance is 30 dollars per passenger and enables full refund if the user needs to cancel the flight given health or weather reasons. + +## Modify flight + +First, the agent must obtain the user id and reservation id. +- The user must provide their user id. +- If the user doesn't know their reservation id, the agent should help locate it using available tools. + +Change flights: +- Basic economy flights cannot be modified. +- Other reservations can be modified without changing the origin, destination, and trip type. +- Some flight segments can be kept, but their prices will not be updated based on the current price. +- The API does not check these for the agent, so the agent must make sure the rules apply before calling the API! + +Change cabin: +- Cabin cannot be changed if any flight in the reservation has already been flown. +- In other cases, all reservations, including basic economy, can change cabin without changing the flights. +- Cabin class must remain the same across all the flights in the same reservation; changing cabin for just one flight segment is not possible. +- If the price after cabin change is higher than the original price, the user is required to pay for the difference. +- If the price after cabin change is lower than the original price, the user is should be refunded the difference. + +Change baggage and insurance: +- The user can add but not remove checked bags. +- The user cannot add insurance after initial booking. + +Change passengers: +- The user can modify passengers but cannot modify the number of passengers. +- Even a human agent cannot modify the number of passengers. + +Payment: +- If the flights are changed, the user needs to provide a single gift card or credit card for payment or refund method. The payment method must already be in user profile for safety reasons. + +## Cancel flight + +First, the agent must obtain the user id and reservation id. +- The user must provide their user id. +- If the user doesn't know their reservation id, the agent should help locate it using available tools. + +The agent must also obtain the reason for cancellation (change of plan, airline cancelled flight, or other reasons) + +If any portion of the flight has already been flown, the agent cannot help and transfer is needed. + +Otherwise, flight can be cancelled if any of the following is true: +- The booking was made within the last 24 hrs +- The flight is cancelled by airline +- It is a business flight +- The user has travel insurance and the reason for cancellation is covered by insurance. + +The API does not check that cancellation rules are met, so the agent must make sure the rules apply before calling the API! + +Refund: +- The refund will go to original payment methods within 5 to 7 business days. + +## Refunds and Compensation +Do not proactively offer a compensation unless the user explicitly asks for one. + +Do not compensate if the user is regular member and has no travel insurance and flies (basic) economy. + +Always confirms the facts before offering compensation. + +Only compensate if the user is a silver/gold member or has travel insurance or flies business. + +- If the user complains about cancelled flights in a reservation, the agent can offer a certificate as a gesture after confirming the facts, with the amount being $100 times the number of passengers. + +- If the user complains about delayed flights in a reservation and wants to change or cancel the reservation, the agent can offer a certificate as a gesture after confirming the facts and changing or cancelling the reservation, with the amount being $50 times the number of passengers. + +Do not offer compensation for any other reason than the ones listed above. + diff --git a/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/dataset/template/task_template/nemo-task-envelope.json b/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/dataset/template/task_template/nemo-task-envelope.json new file mode 100644 index 0000000000..721e0bda76 --- /dev/null +++ b/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/dataset/template/task_template/nemo-task-envelope.json @@ -0,0 +1,19 @@ +{ + "schema_version": 1, + "task_data": [ + { + "path": "instruction.md", + "media_type": "text/plain", + "max_bytes": 262144 + }, + { + "path": "environment/runtime-server/task_config.json", + "media_type": "application/json", + "max_bytes": 1048576 + } + ], + "verifier_paths": [ + "tests/test.sh", + "tests/insight_metrics" + ] +} diff --git a/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/dataset/template/task_template/task.toml b/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/dataset/template/task_template/task.toml new file mode 100644 index 0000000000..17e0cf51d3 --- /dev/null +++ b/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/dataset/template/task_template/task.toml @@ -0,0 +1,35 @@ +schema_version = "1.1" + +[task] +name = "sierra-research/tau2-bench__tau2-airline-0" +authors = [ + { name = "Victor Barres", email = "victor@sierra.ai" }, + { name = "Honghua Dong" }, + { name = "Soham Ray" }, + { name = "Xujie Si" }, + { name = "Karthik Narasimhan" }, +] +keywords = ["tau2-bench", "airline", "tool-use"] + +[metadata] +difficulty = "medium" +category = "customer_service" + +[verifier] +timeout_sec = 300.0 +env = { INFERENCE_API_KEY = "${INFERENCE_API_KEY}", INFERENCE_BASE_URL = "${INFERENCE_BASE_URL:-https://inference-api.nvidia.com/v1}", TAU2_NL_ASSERTIONS_MODEL = "${TAU2_NL_ASSERTIONS_MODEL:-openai/openai/gpt-5.2}" } + +[agent] +timeout_sec = 3600.0 + +[environment] +build_timeout_sec = 600.0 +cpus = 4 +memory_mb = 8192 +storage_mb = 10240 +env = { INFERENCE_API_KEY = "${INFERENCE_API_KEY}", INFERENCE_BASE_URL = "${INFERENCE_BASE_URL:-https://inference-api.nvidia.com/v1}", TAU2_USER_MODEL = "${TAU2_USER_MODEL:-openai/openai/gpt-5.2}", TAU2_USER_REASONING_EFFORT = "${TAU2_USER_REASONING_EFFORT:-low}", TAU2_USER_TEMPERATURE = "${TAU2_USER_TEMPERATURE:-}", TAU2_USER_LLM_ARGS_JSON = "${TAU2_USER_LLM_ARGS_JSON:-}" } + +[[environment.mcp_servers]] +name = "tau3-runtime" +transport = "streamable-http" +url = "http://tau3-runtime:8000/mcp" diff --git a/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/dataset/template/task_template/tests/Dockerfile b/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/dataset/template/task_template/tests/Dockerfile new file mode 100644 index 0000000000..c77b3730cb --- /dev/null +++ b/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/dataset/template/task_template/tests/Dockerfile @@ -0,0 +1,6 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 + +FROM python:3.12-slim@sha256:57cd7c3a7a273101a6485ba99423ee568157882804b1124b4dd04266317710de + +WORKDIR /app diff --git a/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/dataset/template/task_template/tests/test.sh b/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/dataset/template/task_template/tests/test.sh new file mode 100755 index 0000000000..e69de29bb2 diff --git a/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/harbor_wrapper.py b/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/harbor_wrapper.py new file mode 100644 index 0000000000..5131de7aed --- /dev/null +++ b/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/harbor_wrapper.py @@ -0,0 +1,230 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 + +import fnmatch +import glob +import json +import logging +import os +import shlex +import shutil +import tempfile +from pathlib import Path + +from harbor import AgentContext, BaseAgent, BaseEnvironment + +logger = logging.getLogger(__name__) + +AGENT_DIR = Path(__file__).parent +ARTIFACTS_DIR = "/app/artifacts" +TRACES_DIR = "/app/traces" +COLLECTED_ARTIFACTS_DIR = "/logs/artifacts" + +# Artifact contract: +# - Files intended for review/fetching must be written under /app/artifacts. +# - Agent traces must be written under /app/traces. +# - Verifier diagnostics should be printed by the verifier so Harbor captures them +# in verifier/test-stdout.txt; do not create custom diagnostic artifact files. +# The wrapper mirrors only these locations into /logs/artifacts for Harbor collection. + +EXCLUDE = { + "eval-and-optimize", + "__pycache__", + ".git", + ".claude", + ".uv", + ".venv", + ".env", + "traces", + "artifacts", + "dataset", +} +EXCLUDE_GLOB = {"output.*"} + + +class WrappedAgent(BaseAgent): + @staticmethod + def name() -> str: + return "agent-0" + + def version(self) -> str | None: + return "1.0.0" + + async def _upload_mcp_config(self, environment: BaseEnvironment) -> None: + if not self.mcp_servers: + return + + mcp_servers = {} + for server in self.mcp_servers: + server_config = server.model_dump(exclude_none=True) + name = server_config.pop("name") + mcp_servers[name] = server_config + + with tempfile.NamedTemporaryFile("w", suffix=".json", delete=False) as tmp: + tmp_path = Path(tmp.name) + json.dump({"mcpServers": mcp_servers}, tmp) + + try: + await environment.upload_file(tmp_path, "/app/.mcp.json") + finally: + tmp_path.unlink(missing_ok=True) + + @staticmethod + async def _upload_nooa_override(environment: BaseEnvironment) -> None: + wheel_value = os.environ.get("NOOA_WHEEL") + if not wheel_value: + return + wheel = Path(wheel_value).expanduser().resolve() + if not wheel.is_file(): + raise RuntimeError(f"NOOA_WHEEL does not name a file: {wheel}") + + vendor_dir = "/app/vendor" + mkdir = await environment.exec(f"mkdir -p {vendor_dir}") + if mkdir.return_code != 0: + raise RuntimeError(f"Could not create {vendor_dir}: {mkdir.stderr or mkdir.stdout}") + + remote_wheel = f"{vendor_dir}/{wheel.name}" + await environment.upload_file(wheel, remote_wheel) + + source_key = "nooa" + project_lines = (AGENT_DIR / "pyproject.toml").read_text(encoding="utf-8").splitlines() + in_sources = False + replaced = False + for index, line in enumerate(project_lines): + stripped = line.strip() + if stripped == "[tool.uv.sources]": + in_sources = True + continue + if in_sources and stripped.startswith("["): + break + if in_sources and stripped.partition("=")[0].strip() == source_key: + project_lines[index] = f'{source_key} = {{ path = "vendor/{wheel.name}" }}' + replaced = True + break + if not replaced: + raise RuntimeError(f"Could not find {source_key} in [tool.uv.sources]") + + with tempfile.NamedTemporaryFile("w", suffix=".toml", delete=False) as tmp: + project_path = Path(tmp.name) + tmp.write("\n".join(project_lines) + "\n") + project_path.chmod(0o644) + try: + await environment.upload_file(project_path, "/app/pyproject.toml") + finally: + project_path.unlink(missing_ok=True) + + async def setup(self, environment: BaseEnvironment) -> None: + """Upload agent files to the container and install dependencies.""" + for entry in AGENT_DIR.iterdir(): + name = entry.name + if name in EXCLUDE: + continue + if any(fnmatch.fnmatch(name, pat) for pat in EXCLUDE_GLOB): + continue + if entry.is_file(): + await environment.upload_file(entry, f"/app/{name}") + elif entry.is_dir(): + await environment.upload_dir(entry, f"/app/{name}") + await self._upload_mcp_config(environment) + await self._upload_nooa_override(environment) + import asyncio as _asyncio + + proc = None + for _attempt in range(3): + proc = await environment.exec("cd /app && UV_HTTP_TIMEOUT=300 uv sync") + if proc.return_code == 0: + break + logger.warning( + f"[setup] install attempt {_attempt + 1} failed (rc={proc.return_code}): stdout={(proc.stdout or '')[-500:]} stderr={(proc.stderr or '')[-500:]}" + ) + if _attempt < 2: + await _asyncio.sleep(10) + if proc and proc.return_code != 0: + logger.error( + f"[setup] install failed after 3 attempts (rc={proc.return_code}): stdout={(proc.stdout or '')[-500:]} stderr={(proc.stderr or '')[-500:]}" + ) + raise RuntimeError( + f"Installation failed after 3 attempts. " + f"Last error (rc={proc.return_code}): {proc.stderr or proc.stdout}" + ) + + logger.info(f"[setup] {proc.stdout if proc else ''}") + + @staticmethod + def _parse_trace_metrics(traces_dir: str) -> dict[str, int]: + def token_count(attributes: dict[str, dict[str, object]], key: str) -> int: + value = attributes.get(key, {}) + raw_count = value.get("intValue", value.get("doubleValue", 0)) + if not isinstance(raw_count, int | float | str): + raise TypeError(f"Invalid token count for {key}: {raw_count!r}") + return int(raw_count) + + n_input = n_output = n_cache = 0 + paths = glob.glob(f"{traces_dir}/**/*.jsonl", recursive=True) + if not paths: + raise FileNotFoundError(f"No JSONL traces found under {traces_dir}") + + for path in paths: + with open(path, encoding="utf-8") as trace_file: + for line_number, line in enumerate(trace_file, start=1): + line = line.strip() + if not line: + continue + try: + data = json.loads(line) + for resource_spans in data.get("resourceSpans", []): + for scope_spans in resource_spans.get("scopeSpans", []): + for span in scope_spans.get("spans", []): + attributes = { + attribute["key"]: attribute["value"] for attribute in span.get("attributes", []) + } + if attributes.get("openinference.span.kind", {}).get("stringValue") != "LLM": + continue + n_input += token_count(attributes, "llm.token_count.prompt") + n_output += token_count(attributes, "llm.token_count.completion") + n_cache += token_count( + attributes, + "llm.token_count.prompt_details.cache_read", + ) + except (AttributeError, KeyError, TypeError, ValueError, json.JSONDecodeError) as exc: + raise ValueError(f"Invalid trace data in {path}:{line_number}: {exc}") from exc + return {"n_input_tokens": n_input, "n_output_tokens": n_output, "n_cache_tokens": n_cache} + + async def run( + self, + instruction: str, + environment: BaseEnvironment, + context: AgentContext, + ) -> None: + env = {"NEMO_AGENT_MODEL": self.model_name} if self.model_name else None + proc = await environment.exec( + f"cd /app && uv run python main.py --prompt {shlex.quote(instruction.strip())}", + env=env, + ) + # download traces from container to parse token counts on the host + _tmp = tempfile.mkdtemp(prefix="agent_traces_") + metrics_error = None + try: + await environment.download_dir(TRACES_DIR, _tmp) + metrics = self._parse_trace_metrics(_tmp) + context.n_input_tokens = metrics["n_input_tokens"] + context.n_output_tokens = metrics["n_output_tokens"] + context.n_cache_tokens = metrics["n_cache_tokens"] + except (FileNotFoundError, OSError, ValueError) as exc: + metrics_error = f"Trace metrics unavailable: {type(exc).__name__}: {exc}" + logger.warning(metrics_error) + finally: + shutil.rmtree(_tmp, ignore_errors=True) + # copy the traces directory to the artifacts directory (no-op if absent) + await environment.exec(f"cp -r {TRACES_DIR} {COLLECTED_ARTIFACTS_DIR}/traces 2>/dev/null || true") + # recursive so subdirs like artifacts/traces/ survive if the agent wrote there + await environment.exec(f"sh -c 'cp -r {ARTIFACTS_DIR}/* {COLLECTED_ARTIFACTS_DIR}/ 2>/dev/null || true'") + + context.metadata = { + "stdout": proc.stdout, + "stderr": proc.stderr, + "returncode": proc.return_code, + "metrics_error": metrics_error, + } + if proc.return_code != 0: + raise RuntimeError(f"Agent process failed with exit code {proc.return_code}: {proc.stderr or proc.stdout}") diff --git a/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/main.py b/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/main.py new file mode 100644 index 0000000000..86ee6813b8 --- /dev/null +++ b/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/main.py @@ -0,0 +1,15 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 + +import argparse +import asyncio + +from agent import Codeact + +if __name__ == "__main__": + parser = argparse.ArgumentParser() + parser.add_argument("--prompt", type=str, required=True) + args = parser.parse_args() + + agent = Codeact() + asyncio.run(agent.solve(args.prompt)) diff --git a/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/optimizer.yaml b/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/optimizer.yaml new file mode 100644 index 0000000000..ee7f4b2495 --- /dev/null +++ b/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/optimizer.yaml @@ -0,0 +1,21 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# Agent optimization profile — `nemo insights analyze` writes +# .nemo-optimizer/insights.yaml here; `nemo experimentalist run` reads it +# by default. Both commands run flag-free from this directory. +# Use each command's `doctor` verb for owned prerequisites. + +agent: nemo-oo-airline +task_template: ./dataset/template/task_template +datasets: + # Registry refs auto-download to ~/.cache/nemo-experimentalist/datasets/ on first use. + # validation is a distinct held-out split: the loop reacts to train scores, + # so the winner must be picked on data it never optimized against + # (tau2-bench-live-test stays untouched for final evaluation). + train: tau2-bench-live-train@1.0 + validation: tau2-bench-live-validation@1.0 + registry_url: "https://gitlab-master.nvidia.com/gdilorenzo/optimization-datasets/-/raw/main/registry.json?ref_type=heads" +# Developers: use the Platform Insights testbed's documented fixture-recovery +# workflow to populate this workspace. Experimentalist does not vendor or invoke that +# testbed; real deployments already have their traces in this workspace. +workspace: tau2-airline diff --git a/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/pyproject.toml b/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/pyproject.toml new file mode 100644 index 0000000000..cff47c615e --- /dev/null +++ b/plugins/nemo-experimentalist/examples/tau2-nemo-oo-agent/pyproject.toml @@ -0,0 +1,17 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 + +[project] +name = "nemo-oo-agent" +version = "0.1.0" +description = "Basic NVIDIA-labs OO Agent" +readme = "README.md" +requires-python = ">=3.12,<3.14" +dependencies = [ + "mcp==1.25.0", + "nooa[tracing]", + "opentelemetry-exporter-otlp-proto-http", + "orjson==3.11.9", +] +[tool.uv.sources] +nooa = { git = "https://github.com/NVIDIA-NeMo/labs-OO-Agents.git", tag = "v0.0.6" } diff --git a/plugins/nemo-experimentalist/pyproject.toml b/plugins/nemo-experimentalist/pyproject.toml index e0add47d4f..a478f7a91f 100644 --- a/plugins/nemo-experimentalist/pyproject.toml +++ b/plugins/nemo-experimentalist/pyproject.toml @@ -4,6 +4,7 @@ version = "0.1.0" description = "NeMo Experimentalist plugin for NeMo Platform." requires-python = ">=3.12,<3.14" dependencies = [ + "fastapi>=0.115.4", "pydantic>=2", "httpx", "harbor>=0.16", @@ -15,9 +16,14 @@ dependencies = [ "nemo-insights-plugin", "nemo-platform", "nemo-platform-plugin", + "python-multipart>=0.0.20", "tomlkit>=0.13.3", + "uvicorn>=0.34.0", ] +[project.scripts] +nemo-experimentalist-harbor-bridge = "nemo_experimentalist_plugin.harbor_bridge.service:main" + [project.entry-points."nemo.cli"] experimentalist = "nemo_experimentalist_plugin.cli:ExperimentalistCLI" diff --git a/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/cli.py b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/cli.py index f8049e0b4a..67cb005ef9 100644 --- a/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/cli.py +++ b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/cli.py @@ -5,6 +5,7 @@ import asyncio import os +import sys import uuid from collections.abc import MutableMapping from datetime import UTC, datetime @@ -15,6 +16,15 @@ import typer import yaml from nemo_experimentalist_plugin.client import make_client +from nemo_experimentalist_plugin.harbor_bridge.envelopes import HARBOR_ENVELOPE_CATALOG_ENV +from nemo_experimentalist_plugin.harbor_bridge.preparation import ( + PreparedTrustedInputs, + prepare_trusted_inputs, +) +from nemo_experimentalist_plugin.openshell.launcher import ( + OpenShellLaunchError, + launch_in_openshell, +) from nemo_experimentalist_plugin.preflight import ( Probes, check_artifacts, @@ -26,8 +36,11 @@ from nemo_experimentalist_plugin.resolve import ( ResolveError, build_effective_experiment_plan, + parse_local_insights, resolve_effective_insight, + resolve_experiment_config, resolve_experiment_inputs, + select_local_insight, ) from nemo_insights_plugin.contracts.checks import ( CheckResult, @@ -42,11 +55,19 @@ load_env_file, resolve_base_url, ) +from nemo_insights_plugin.contracts.workflow_context import ( + load_workflow_context, + resolve_context_base_url, +) from nemo_platform_plugin.cli import NemoCLI DEFAULT_WORKSPACE = "default" +_CONTAINER_MARKER = Path("/etc/nemo-experimentalist-container") _PREFLIGHT_PROBES: Probes | None = None # test seam; None → real probes +_OPEN_SHELL_LAUNCHER = launch_in_openshell # test seam +_TRUSTED_INPUT_PREPARER = prepare_trusted_inputs # test seam +_CONTAINER_RUNTIME: bool | None = None # test seam; None → inspect image marker # Lazily imported in the experiment command: importing experimentalist.run reaches model # construction that requires EXPERIMENTALIST_API_* env at import time, and this module @@ -57,6 +78,117 @@ # TODO: Add remote train/validation dataset support when remote experiment mode is implemented. +def _inside_experimentalist_container() -> bool: + return _CONTAINER_RUNTIME if _CONTAINER_RUNTIME is not None else _CONTAINER_MARKER.is_file() + + +def _sandbox_path(value: str | Path, *, workspace_dir: Path, option: str) -> str: + """Translate an existing host path into the uploaded OpenShell workspace.""" + text = str(value) + candidate = Path(text).expanduser() + if not candidate.exists(): + return text + + resolved_workspace = workspace_dir.resolve() + resolved_candidate = candidate.resolve() + try: + relative = resolved_candidate.relative_to(resolved_workspace) + except ValueError as exc: + raise OpenShellLaunchError( + f"{option} resolves outside the OpenShell workspace {resolved_workspace}: {resolved_candidate}. " + "Run from a directory that contains every local input." + ) from exc + return str(Path("/sandbox/project") / resolved_workspace.name / relative) + + +def _openshell_run_args( + *, + workspace_dir: Path, + agent: str | None, + agent_spec: str | None, + insight: str | None, + insight_id: str | None, + no_insight: bool, + profile_path: Path | None, + train_dataset: str | None, + validation_dataset: str | None, + task_template: str | None, + mode: Literal["local", "remote"], + workspace: str | None, + config: Path | None, + framework_skills: list[Path], +) -> list[str]: + args: list[str] = [] + path_options: tuple[tuple[str, str | Path | None], ...] = ( + ("--agent", agent), + ("--agent-spec", agent_spec), + ("--insight", insight), + ("--profile", profile_path), + ("--train-dataset", train_dataset), + ("--validation-dataset", validation_dataset), + ("--task-template", task_template), + ("--config", config), + ) + for option, value in path_options: + if value is not None: + args.extend([option, _sandbox_path(value, workspace_dir=workspace_dir, option=option)]) + if insight_id is not None: + args.extend(["--insight-id", insight_id]) + if no_insight: + args.append("--no-insight") + args.extend(["--mode", mode]) + if workspace is not None: + args.extend(["--workspace", workspace]) + for skills_dir in framework_skills: + args.extend( + [ + "--framework-skills", + _sandbox_path(skills_dir, workspace_dir=workspace_dir, option="--framework-skills"), + ] + ) + return args + + +def _openshell_doctor_args( + *, + workspace_dir: Path, + insight: str | None, + insight_id: str | None, + profile_path: Path | None, +) -> list[str]: + args: list[str] = [] + if insight is not None: + args.extend(["--insight", _sandbox_path(insight, workspace_dir=workspace_dir, option="--insight")]) + if insight_id is not None: + args.extend(["--insight-id", insight_id]) + if profile_path is not None: + args.extend( + [ + "--profile", + _sandbox_path(profile_path, workspace_dir=workspace_dir, option="--profile"), + ] + ) + return args + + +def _run_in_openshell( + command: Literal["run", "doctor"], + args: list[str], + *, + output_dir: Path | None, + platform_url: str | None, +) -> None: + exit_code = _OPEN_SHELL_LAUNCHER( + command, + args, + workspace_dir=Path.cwd(), + output_dir=output_dir, + platform_url=platform_url, + ) + if exit_code != 0: + raise typer.Exit(code=exit_code) + + def _default_experiment_dir(profile: AgentProfile | None) -> Path: if profile is None: experiments_root = Path("tmp") @@ -73,6 +205,52 @@ def _default_experiment_dir(profile: AgentProfile | None) -> Path: return candidate +def _select_host_insight( + profile: AgentProfile | None, + *, + insight: str | None, + insight_id: str | None, + no_insight: bool, +) -> str | None: + """Prompt for one profile-local Insight before creating the sandbox.""" + if no_insight: + return insight_id + effective = resolve_effective_insight( + profile=profile, + insight=insight, + insight_id=insight_id, + disabled=False, + ) + if effective.ref is None or effective.selector is not None: + return effective.selector + items = parse_local_insights(effective.ref) + if items is None or len(items) <= 1: + return effective.selector + if not sys.stdin.isatty(): + raise OpenShellLaunchError( + f"{effective.ref} contains {len(items)} insights. " + "Run from an interactive terminal to choose one, or pass --insight-id." + ) + typer.echo("Choose an Insight to optimize:", err=True) + for index, item in enumerate(items): + typer.echo(f" [{index}] {item.get('title', item.get('id', 'untitled'))}", err=True) + selector = typer.prompt("Insight", default="0") + selected = select_local_insight(items, selector, effective.ref) + return str(selected.get("id") or selector) + + +def _apply_profile_runtime_defaults(profile: AgentProfile | None) -> None: + """Select the narrow source provider needed by a profile's dataset registry.""" + if profile is None or not profile.datasets.registry_url: + return + host = (urlsplit(profile.datasets.registry_url).hostname or "").lower() + if "gitlab" in host: + os.environ.setdefault("NEMO_EXPERIMENTALIST_SOURCE_CONTROL", "gitlab-read") + os.environ.setdefault("NEMO_EXPERIMENTALIST_GITLAB_HOST", host) + elif host in {"github.com", "raw.githubusercontent.com"}: + os.environ.setdefault("NEMO_EXPERIMENTALIST_SOURCE_CONTROL", "github-read") + + class ExperimentalistCLI(NemoCLI): """``nemo experimentalist ...`` subcommands.""" @@ -158,9 +336,8 @@ def run( "--experiments-output", "-o", help=( - "Local experiment directory; writes eval-and-optimize/ here. " - "Default: /.nemo-optimizer/experiments/ " - "when a profile governs the run, else ./tmp." + "Host experiment directory. OpenShell downloads its artifacts here " + "(default: ./tmp/experimentalist-openshell)." ), file_okay=False, dir_okay=True, @@ -211,6 +388,103 @@ def run( if mode == "remote": typer.echo("Remote mode is not implemented yet", err=True) raise typer.Exit(code=1) + if not _inside_experimentalist_container(): + try: + host_profile, host_profile_error = _load_profile_or_error(profile_path) + if host_profile_error is not None: + raise ProfileError(host_profile_error) + context = ( + load_workflow_context( + host_profile.profile_dir, + agent=host_profile.agent, + ) + if host_profile is not None + else None + ) + resolved_platform_url = resolve_context_base_url(base_url, context) + resolved_workspace = ( + workspace + if workspace is not None + else ( + context.workspace + if context is not None + else (host_profile.workspace if host_profile is not None else None) + ) + ) + selected_insight_id = _select_host_insight( + host_profile, + insight=insight, + insight_id=insight_id, + no_insight=no_insight, + ) + _apply_profile_runtime_defaults(host_profile) + # Preserve the fail-fast OpenShell boundary check before + # resolving any registry inputs or constructing the plan. + for option, value in ( + ("--agent", agent), + ("--agent-spec", agent_spec), + ("--insight", insight), + ("--profile", profile_path), + ("--train-dataset", train_dataset), + ("--validation-dataset", validation_dataset), + ("--task-template", task_template), + ("--config", config), + ): + if value is not None: + _sandbox_path(value, workspace_dir=Path.cwd(), option=option) + for skills_dir in framework_skills: + _sandbox_path( + skills_dir, + workspace_dir=Path.cwd(), + option="--framework-skills", + ) + config_payload = _load_config_payload(config) + host_plan = build_effective_experiment_plan( + profile=host_profile, + agent=agent, + agent_spec=agent_spec, + insight=insight, + insight_id=selected_insight_id, + no_insight=no_insight, + train_dataset=train_dataset, + validation_dataset=validation_dataset, + task_template=task_template, + workspace=resolved_workspace, + config_payload=config_payload, + framework_skills=framework_skills or None, + ) + trusted_inputs: PreparedTrustedInputs = asyncio.run( + _TRUSTED_INPUT_PREPARER(host_plan, workspace=Path.cwd()) + ) + os.environ[HARBOR_ENVELOPE_CATALOG_ENV] = str(trusted_inputs.catalog_root) + forwarded_args = _openshell_run_args( + workspace_dir=Path.cwd(), + agent=agent, + agent_spec=agent_spec, + insight=insight, + insight_id=selected_insight_id, + no_insight=no_insight, + profile_path=profile_path, + train_dataset=str(trusted_inputs.train_dataset), + validation_dataset=str(trusted_inputs.validation_dataset), + task_template=( + str(trusted_inputs.task_template) if trusted_inputs.task_template is not None else None + ), + mode=mode, + workspace=resolved_workspace, + config=config, + framework_skills=framework_skills, + ) + _run_in_openshell( + "run", + forwarded_args, + output_dir=experiment_dir, + platform_url=resolved_platform_url, + ) + except (OpenShellLaunchError, ProfileError, ResolveError, OSError) as exc: + typer.echo(str(exc), err=True) + raise typer.Exit(code=1) from None + return async def _flow() -> str: """Resolve inputs (profile + flags) and run the Experimentalist.""" @@ -233,6 +507,13 @@ async def _flow() -> str: err=True, ) _announce_credential_defaults() + config_payload = _load_config_payload(config) + effective_config = resolve_experiment_config(config_payload, profile) + bridge_url = effective_config.evaluator.get("bridge_url") + bridge_token_env = effective_config.evaluator.get( + "bridge_token_env", + "NEMO_EXPERIMENTALIST_HARBOR_BRIDGE_TOKEN", + ) # Phase 1 — cheap environment checks BEFORE resolution: certain failures # (missing creds, docker down, harbor absent) surface as the grouped # report before any dataset download or the loop-chain import (which @@ -245,11 +526,12 @@ async def _flow() -> str: insight=effective_insight.ref, insight_id=effective_insight.selector, base_url=base_url_resolved, + harbor_bridge_url=str(bridge_url) if bridge_url is not None else None, + harbor_bridge_token_env=str(bridge_token_env), enforce_insight_agent=agent is None, probes=_PREFLIGHT_PROBES, ) ) - config_payload = _load_config_payload(config) try: plan = build_effective_experiment_plan( profile=profile, @@ -346,6 +628,41 @@ def doctor( ), ) -> None: """Diagnose Experimentalist setup: profile, artifacts, credentials, platform, runtime.""" + if not _inside_experimentalist_container(): + try: + host_profile, host_profile_error = _load_profile_or_error(profile_path) + if host_profile_error is not None: + raise ProfileError(host_profile_error) + context = ( + load_workflow_context( + host_profile.profile_dir, + agent=host_profile.agent, + ) + if host_profile is not None + else None + ) + selected_insight_id = _select_host_insight( + host_profile, + insight=insight, + insight_id=insight_id, + no_insight=False, + ) + _apply_profile_runtime_defaults(host_profile) + _run_in_openshell( + "doctor", + _openshell_doctor_args( + workspace_dir=Path.cwd(), + insight=insight, + insight_id=selected_insight_id, + profile_path=profile_path, + ), + output_dir=None, + platform_url=resolve_context_base_url(base_url, context), + ) + except (OpenShellLaunchError, ProfileError, ResolveError, OSError) as exc: + typer.echo(str(exc), err=True) + raise typer.Exit(code=1) from None + return found = profile_path or discover_profile() profile_obj, profile_error = None, None env_results: list[CheckResult] = [] @@ -413,6 +730,21 @@ def doctor( insight=effective_insight.ref if effective_insight is not None else None, insight_id=effective_insight.selector if effective_insight is not None else None, base_url=base_url_resolved, + harbor_bridge_url=( + str(plan.config.evaluator.get("bridge_url")) + if plan is not None and plan.config.evaluator.get("bridge_url") is not None + else None + ), + harbor_bridge_token_env=( + str( + plan.config.evaluator.get( + "bridge_token_env", + "NEMO_EXPERIMENTALIST_HARBOR_BRIDGE_TOKEN", + ) + ) + if plan is not None + else "NEMO_EXPERIMENTALIST_HARBOR_BRIDGE_TOKEN" + ), probes=_PREFLIGHT_PROBES, ) if profile_obj is not None: diff --git a/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/experimentalist/components/analyzer.py b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/experimentalist/components/analyzer.py index 335441e571..b6df7e0f1d 100644 --- a/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/experimentalist/components/analyzer.py +++ b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/experimentalist/components/analyzer.py @@ -17,6 +17,7 @@ Task, TrialResult, ) +from nemo_experimentalist_plugin.experimentalist.components.evaluator.models import DependencyRuntimeError from nemo_experimentalist_plugin.experimentalist.components.trace_analyzer import ( # noqa: F401 Diagnostic, TraceAnalyzer, @@ -638,6 +639,8 @@ async def run( for task_id, result in zip(unique_tasks, rationales_list, strict=True): if isinstance(result, asyncio.CancelledError): raise result + if isinstance(result, DependencyRuntimeError): + raise result if isinstance(result, BaseException): logging.getLogger(__name__).warning(f"Rationalizer failed for {agent_id}/{task_id}: {result}") continue @@ -665,6 +668,8 @@ async def run( for (trial, _), result in zip(trial_tasks, diagnoses_list, strict=True): if isinstance(result, asyncio.CancelledError): raise result + if isinstance(result, DependencyRuntimeError): + raise result if isinstance(result, BaseException): logging.getLogger(__name__).warning( "TraceAnalyzer failed for %s/%s: %s", diff --git a/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/experimentalist/components/evaluator/__init__.py b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/experimentalist/components/evaluator/__init__.py index 59fee57c2f..8df724d5e2 100644 --- a/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/experimentalist/components/evaluator/__init__.py +++ b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/experimentalist/components/evaluator/__init__.py @@ -12,7 +12,10 @@ DatasetRef, DatasetValidationError, DataValue, + DependencyCommandExecutor, + DependencyCommandResult, DependencyRuntime, + DependencyRuntimeError, EvaluationResult, MetricResult, MetricSpec, @@ -23,6 +26,11 @@ TrialStatus, local_path_from_uri, ) +from nemo_experimentalist_plugin.experimentalist.components.evaluator.remote_harbor import ( + RemoteHarborDependencyRuntime, + RemoteHarborEvaluator, + RemoteHarborEvaluatorConfig, +) __all__ = [ "CommandSpec", @@ -30,11 +38,17 @@ "Dataset", "DatasetRef", "DatasetValidationError", + "DependencyCommandExecutor", + "DependencyCommandResult", "DependencyRuntime", + "DependencyRuntimeError", "EvaluationResult", "Evaluator", "EvaluatorConfig", "EvaluatorType", + "RemoteHarborEvaluator", + "RemoteHarborEvaluatorConfig", + "RemoteHarborDependencyRuntime", "MetricResult", "MetricSpec", "MetricValue", diff --git a/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/experimentalist/components/evaluator/base.py b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/experimentalist/components/evaluator/base.py index 25261b4e21..b5933b24a0 100644 --- a/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/experimentalist/components/evaluator/base.py +++ b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/experimentalist/components/evaluator/base.py @@ -39,6 +39,10 @@ def __init__(self, options: EvaluatorConfig, experiment_dir: Path | None = None) self.options = options self.experiment_dir = experiment_dir + def prepare_dataset(self, dataset: Dataset) -> Dataset: + """Bind evaluator-specific runtime behavior to a dataset.""" + return dataset + async def aggregate_results(self, results: Sequence[TrialResult]) -> dict[str, float | int]: """ Aggregate evaluation results from multiple runs. diff --git a/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/experimentalist/components/evaluator/factory.py b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/experimentalist/components/evaluator/factory.py index 3b59226cec..7b677fcc86 100644 --- a/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/experimentalist/components/evaluator/factory.py +++ b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/experimentalist/components/evaluator/factory.py @@ -3,6 +3,7 @@ """Factories for evaluator-specific datasets and evaluators.""" +import os from pathlib import Path from typing import Any @@ -17,6 +18,11 @@ HarborEvaluatorConfig, ) from nemo_experimentalist_plugin.experimentalist.components.evaluator.models import Dataset, DatasetRef, Task +from nemo_experimentalist_plugin.experimentalist.components.evaluator.remote_harbor import ( + BRIDGE_URL_ENV, + RemoteHarborEvaluator, + RemoteHarborEvaluatorConfig, +) _SUPPORTED_EVALUATOR_TYPES = { "harbor": (HarborDataset, HarborEvaluator, HarborEvaluatorConfig), @@ -94,6 +100,21 @@ def build_evaluator( ValueError: If the evaluator type is not supported. TypeError: If the evaluator config is not an EvaluatorConfig or dict. """ + bridge_url = os.environ.get(BRIDGE_URL_ENV) + if evaluator_type == "harbor" and ( + isinstance(config, RemoteHarborEvaluatorConfig) + or (isinstance(config, dict) and config.get("bridge_url") is not None) + or bridge_url + ): + if isinstance(config, RemoteHarborEvaluatorConfig): + remote_config = config + else: + remote_payload = config.model_dump() if isinstance(config, EvaluatorConfig) else dict(config) + if bridge_url: + remote_payload.setdefault("bridge_url", bridge_url) + remote_config = RemoteHarborEvaluatorConfig.model_validate(remote_payload) + return RemoteHarborEvaluator(options=remote_config, experiment_dir=experiment_dir) + if evaluator_type in _SUPPORTED_EVALUATOR_TYPES: if isinstance(config, EvaluatorConfig): config = config.model_dump() diff --git a/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/experimentalist/components/evaluator/harbor.py b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/experimentalist/components/evaluator/harbor.py index 24a60ffa37..2b6f2e8777 100644 --- a/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/experimentalist/components/evaluator/harbor.py +++ b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/experimentalist/components/evaluator/harbor.py @@ -24,7 +24,7 @@ from uuid import uuid4 from harbor.constants import MAIN_SERVICE_NAME -from harbor.environments.base import BaseEnvironment +from harbor.environments.base import BaseEnvironment, ExecResult from harbor.environments.factory import EnvironmentFactory from harbor.job import DatasetConfig, Job, JobConfig from harbor.models.environment_type import EnvironmentType @@ -179,6 +179,7 @@ class HarborEvaluatorConfig(EvaluatorConfig): ) n_attempts: int = Field(default=1) n_concurrent_trials: int = Field(default=os.cpu_count() or 4) + agent_model_name: str | None = Field(default=None) quiet: bool = Field(default=False) verifier_timeout_multiplier: float | None = Field(default=1.0) agent_timeout_multiplier: float | None = Field(default=1.0) @@ -187,6 +188,10 @@ class HarborEvaluatorConfig(EvaluatorConfig): artifacts: list[str] = Field(default=[]) retry: RetryConfig = Field(default=RetryConfig(exclude_exceptions=set())) import_path: str = Field(default="harbor_wrapper:WrappedAgent") + scope_import_path: bool = Field( + default=True, + description="Scope a candidate-owned import path to the candidate directory before Harbor imports it.", + ) trace_dir: str = Field(default=_TRACE_ARTIFACT_SOURCE) @@ -208,8 +213,9 @@ def context(self) -> HarborDependencyContext: class HarborDependencyContext: """Async context manager that starts and stops Harbor task dependencies.""" - def __init__(self, runtime: HarborDependencyRuntime) -> None: + def __init__(self, runtime: HarborDependencyRuntime, *, temp_root: Path | None = None) -> None: self._runtime = runtime + self._temp_root = temp_root self._environment: BaseEnvironment | None = None self._temp_dir: tempfile.TemporaryDirectory[str] | None = None @@ -247,7 +253,9 @@ async def _start_harbor_runtime(self) -> None: harbor_task = HarborTaskModel(task_path) context_id = uuid4() session_id = f"{harbor_task.short_name}__{context_id.hex[:12]}__env" - temp_dir = tempfile.TemporaryDirectory(prefix="nemo-harbor-deps-") + if self._temp_root is not None: + self._temp_root.mkdir(parents=True, exist_ok=True) + temp_dir = tempfile.TemporaryDirectory(prefix="nemo-harbor-deps-", dir=self._temp_root) trial_paths = TrialPaths(Path(temp_dir.name)) trial_paths.mkdir() @@ -335,6 +343,22 @@ async def _stop_started_runtime(self) -> None: if stop_error is not None: raise stop_error + async def execute( + self, + command: str, + *, + cwd: str | None = None, + timeout_sec: int | None = None, + ) -> ExecResult: + """Execute a command inside the active Harbor task environment.""" + if self._environment is None: + raise RuntimeError("Harbor dependency environment is not running") + return await self._environment.exec( + command, + cwd=cwd, + timeout_sec=timeout_sec, + ) + def _chmod_path_chain(path: Path, stop_at: Path) -> None: current = path @@ -1245,9 +1269,13 @@ class HarborEvaluator(Evaluator): evaluator_type: EvaluatorType = "harbor" def __init__(self, options: HarborEvaluatorConfig | None = None, experiment_dir: Path | None = None) -> None: - super().__init__(options or HarborEvaluatorConfig(), experiment_dir=experiment_dir) + resolved_options = options or HarborEvaluatorConfig() + super().__init__(resolved_options, experiment_dir=experiment_dir) + self.options = resolved_options - async def _run(self, agent: Path, dataset: Dataset, options: HarborEvaluatorConfig) -> Sequence[TrialResult]: + async def _run(self, agent: Path, dataset: Dataset, options: EvaluatorConfig) -> Sequence[TrialResult]: + if not isinstance(options, HarborEvaluatorConfig): + raise TypeError("Harbor evaluator requires HarborEvaluatorConfig") if not isinstance(dataset, HarborDataset): raise ValueError("Dataset must be a Harbor dataset") @@ -1260,7 +1288,9 @@ async def _run(self, agent: Path, dataset: Dataset, options: HarborEvaluatorConf options_dict["jobs_dir"] = experiment_dir / options.jobs_dir options_dict["job_name"] = options.job_name or f"{agent.name}-{dataset.id}" import_path: str = options_dict.pop("import_path") + scope_import_path: bool = options_dict.pop("scope_import_path", True) trace_dir: str = options_dict.pop("trace_dir", _TRACE_ARTIFACT_SOURCE) + agent_model_name: str | None = options_dict.pop("agent_model_name", None) options_dict["artifacts"] = _with_trace_artifact(options_dict.get("artifacts") or [], trace_dir) force_rerun: bool = options_dict.pop("force_rerun", False) @@ -1271,8 +1301,12 @@ async def _run(self, agent: Path, dataset: Dataset, options: HarborEvaluatorConf await dataset.validate() - scoped_import_path, scoped_package = _scoped_import_path(agent_path, import_path) - agents_config = [AgentConfig(import_path=scoped_import_path)] + scoped_package: str | None = None + if scope_import_path: + scoped_import_path, scoped_package = _scoped_import_path(agent_path, import_path) + else: + scoped_import_path = import_path + agents_config = [AgentConfig(import_path=scoped_import_path, model_name=agent_model_name)] datasets_config = [DatasetConfig(path=dataset_path, task_names=[task.id for task in dataset.tasks])] job_config = JobConfig(**options_dict, agents=agents_config, datasets=datasets_config) if force_rerun: @@ -1284,7 +1318,8 @@ async def _run(self, agent: Path, dataset: Dataset, options: HarborEvaluatorConf job = await Job.create(job_config) await job.run() finally: - _cleanup_scoped_imports(scoped_package) + if scoped_package is not None: + _cleanup_scoped_imports(scoped_package) trials = await self._trials_from_dir(job.job_dir, dataset.tasks) return trials diff --git a/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/experimentalist/components/evaluator/models.py b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/experimentalist/components/evaluator/models.py index 8b59ce67f3..d29b0de807 100644 --- a/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/experimentalist/components/evaluator/models.py +++ b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/experimentalist/components/evaluator/models.py @@ -14,7 +14,7 @@ from contextlib import AbstractAsyncContextManager from pathlib import Path from types import TracebackType -from typing import Any, Literal, TypeAlias +from typing import Any, Literal, Protocol, TypeAlias, runtime_checkable from urllib.parse import unquote, urlparse from pydantic import BaseModel, Field, SerializeAsAny @@ -86,6 +86,31 @@ def context(self) -> AbstractAsyncContextManager[DependencyRuntime | None]: return DependencyContext(self) +class DependencyRuntimeError(RuntimeError): + """Task dependency setup or transport failed outside the analyzed agent.""" + + +class DependencyCommandResult(BaseModel): + """Result of running one command through a task dependency runtime.""" + + stdout: str = "" + stderr: str = "" + returncode: int + + +@runtime_checkable +class DependencyCommandExecutor(Protocol): + """Dependency runtime that can execute analyzer shell commands.""" + + async def execute( + self, + command: str, + *, + stdin: str | None = None, + timeout: float = 30.0, + ) -> DependencyCommandResult: ... + + async def run_dependency_command(spec: CommandSpec, phase: str) -> None: """Run a dependency command. diff --git a/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/experimentalist/components/evaluator/remote_harbor.py b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/experimentalist/components/evaluator/remote_harbor.py new file mode 100644 index 0000000000..38850af3ef --- /dev/null +++ b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/experimentalist/components/evaluator/remote_harbor.py @@ -0,0 +1,567 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 + +"""Remote Harbor evaluator that never receives Docker authority.""" + +from __future__ import annotations + +import asyncio +import hashlib +import json +import math +import os +import re +import shutil +from pathlib import Path +from types import TracebackType +from typing import Any +from uuid import uuid4 + +import httpx +from nemo_experimentalist_plugin.experimentalist.components.evaluator.base import ( + Evaluator, + EvaluatorConfig, + EvaluatorType, +) +from nemo_experimentalist_plugin.experimentalist.components.evaluator.harbor import ( + HarborDataset, + HarborDependencyRuntime, +) +from nemo_experimentalist_plugin.experimentalist.components.evaluator.models import ( + Dataset, + DependencyCommandResult, + DependencyRuntime, + DependencyRuntimeError, + EvaluationResult, + ResourceRef, + TrialResult, + local_path_from_uri, +) +from nemo_experimentalist_plugin.harbor_bridge.archives import ( + DEFAULT_MAX_ARCHIVE_BYTES, + create_directory_archive, + materialize_result_archive, +) +from nemo_experimentalist_plugin.harbor_bridge.contracts import ( + HarborBridgeRequest, + HarborDependencyExecRequest, + HarborDependencyExecResponse, + HarborDependencyRequest, + HarborDependencySessionResponse, +) +from nemo_experimentalist_plugin.harbor_bridge.envelopes import ( + EnvelopeTaskSelection, + ResolvedEnvelopeTask, + TaskEnvelopePolicy, + create_overlay_directory, + resolve_envelope_task, + transport_tree_digest, +) +from pydantic import AnyHttpUrl, ConfigDict, Field, PrivateAttr, model_validator + +BRIDGE_URL_ENV = "NEMO_EXPERIMENTALIST_HARBOR_BRIDGE_URL" + + +class RemoteHarborEvaluatorConfig(EvaluatorConfig): + """Bounded client configuration for the trusted Harbor bridge.""" + + model_config = ConfigDict(extra="forbid") + + bridge_url: AnyHttpUrl + bridge_token_env: str = Field( + default="NEMO_EXPERIMENTALIST_HARBOR_BRIDGE_TOKEN", + pattern=r"^[A-Z_][A-Z0-9_]*$", + ) + request_timeout_sec: float = Field(default=3600.0, ge=1.0, le=86_400.0) + max_archive_bytes: int = Field(default=DEFAULT_MAX_ARCHIVE_BYTES, ge=1, le=2 * 1024 * 1024 * 1024) + result_dir: Path = Field(default=Path("eval-and-optimize") / "remote-results") + job_name: str | None = Field(default=None, min_length=1, max_length=80) + n_attempts: int = Field(default=1, ge=1, le=8) + n_concurrent_trials: int = Field(default=4, ge=1, le=16) + quiet: bool = Field( + default=True, + description="Accepted for compatibility; the trusted bridge always runs Harbor quietly.", + ) + agent_model_name: str | None = Field(default=None, min_length=1, max_length=256) + agent_timeout_multiplier: float | None = Field(default=1.0, ge=0.1, le=10.0) + verifier_timeout_multiplier: float | None = Field(default=1.0, ge=0.1, le=10.0) + agent_setup_timeout_multiplier: float | None = Field(default=1.0, ge=0.1, le=10.0) + environment_build_timeout_multiplier: float | None = Field(default=1.0, ge=0.1, le=10.0) + + +class RemoteHarborDependencyRuntime(DependencyRuntime): + """Harbor task environment owned by the authenticated bridge.""" + + model_config = ConfigDict(extra="forbid") + + task_id: str = Field(min_length=1, max_length=256, pattern=r"^[A-Za-z0-9][A-Za-z0-9_.-]*$") + base_task_id: str = Field(min_length=1, max_length=256, pattern=r"^[A-Za-z0-9][A-Za-z0-9_.-]*$") + envelope_id: str = Field(min_length=1, max_length=128, pattern=r"^[A-Za-z0-9][A-Za-z0-9_.-]*$") + envelope_digest: str = Field(pattern=r"^sha256:[0-9a-f]{64}$") + task_path: ResourceRef + overlay_policy: TaskEnvelopePolicy = Field(default_factory=TaskEnvelopePolicy) + bridge_url: AnyHttpUrl + bridge_token_env: str = Field( + default="NEMO_EXPERIMENTALIST_HARBOR_BRIDGE_TOKEN", + pattern=r"^[A-Z_][A-Z0-9_]*$", + ) + request_timeout_sec: float = Field(default=3600.0, ge=1.0, le=86_400.0) + max_archive_bytes: int = Field(default=DEFAULT_MAX_ARCHIVE_BYTES, ge=1, le=2 * 1024 * 1024 * 1024) + force_build: bool = True + run_healthcheck: bool = True + build_timeout_sec: int | None = Field(default=None, ge=1, le=3600) + + _session_id: str | None = PrivateAttr(default=None) + _session_capability: str | None = PrivateAttr(default=None) + _client: httpx.AsyncClient | None = PrivateAttr(default=None) + + @model_validator(mode="after") + def reject_local_commands(self) -> RemoteHarborDependencyRuntime: + """Keep task commands behind the bridge instead of spawning locally.""" + if self.start is not None or self.stop is not None or self.readiness is not None: + raise ValueError("Remote Harbor dependencies do not accept local start, readiness, or stop commands") + return self + + def context(self) -> RemoteHarborDependencyContext: + """Return the bridge-backed dependency context.""" + session_runtime = self.model_copy(deep=False) + session_runtime._session_id = None + session_runtime._session_capability = None + session_runtime._client = self._client + return RemoteHarborDependencyContext(session_runtime) + + async def execute( + self, + command: str, + *, + stdin: str | None = None, + timeout: float = 30.0, + ) -> DependencyCommandResult: + """Execute an analyzer shell command in the active Harbor task environment.""" + if self._session_id is None: + raise DependencyRuntimeError("Remote Harbor dependency session is not running") + if self._session_capability is None: + raise DependencyRuntimeError("Remote Harbor dependency session capability is missing") + request = HarborDependencyExecRequest( + command=command, + stdin=stdin, + timeout_sec=max(1, math.ceil(timeout)), + ) + response = await self._send( + "POST", + f"/v1/dependencies/{self._session_id}/exec", + json=request.model_dump(), + timeout_sec=max(self.request_timeout_sec, request.timeout_sec + 30), + capability_token=self._session_capability, + ) + self._require_status(response, 200, context="command") + try: + result = HarborDependencyExecResponse.model_validate_json(response.content) + except ValueError as exc: + raise DependencyRuntimeError("Harbor bridge returned an invalid dependency command response") from exc + return DependencyCommandResult( + stdout=result.stdout, + stderr=result.stderr, + returncode=result.returncode, + ) + + async def _start(self) -> None: + if self._session_id is not None: + raise DependencyRuntimeError("Remote Harbor dependency session is already running") + + task_path = local_path_from_uri(self.task_path.uri, context="Harbor task reference").resolve() + if not task_path.is_dir(): + raise DependencyRuntimeError(f"Harbor task path not found: {task_path}") + + request = HarborDependencyRequest( + request_id=_dependency_request_id(self.task_id, task_path), + envelope_id=self.envelope_id, + envelope_digest=self.envelope_digest, + task_id=self.task_id, + base_task_id=self.base_task_id, + force_build=self.force_build, + run_healthcheck=self.run_healthcheck, + build_timeout_sec=self.build_timeout_sec, + ) + staging = Path.cwd().resolve() / "tmp" / "harbor-bridge" / f"{request.request_id}-{uuid4().hex[:8]}" + staging.mkdir(parents=True, exist_ok=False) + overlay_dir = staging / "overlay" + overlay_archive = staging / "overlay.tar.gz" + try: + overlay_digest = create_overlay_directory( + [ + ResolvedEnvelopeTask( + envelope_id=self.envelope_id, + envelope_digest=self.envelope_digest, + task_id=self.task_id, + base_task_id=self.base_task_id, + task_path=task_path, + policy=self.overlay_policy, + ) + ], + overlay_dir, + ) + request = request.model_copy(update={"overlay_digest": overlay_digest}) + files: dict[str, tuple[str, Any, str]] | None = None + overlay_handle = None + if overlay_digest is not None: + create_directory_archive(overlay_dir, overlay_archive, max_bytes=self.max_archive_bytes) + overlay_handle = overlay_archive.open("rb") + files = {"overlay": ("overlay.tar.gz", overlay_handle, "application/gzip")} + try: + response = await self._send( + "POST", + "/v1/dependencies", + data={"request": request.model_dump_json()}, + files=files, + timeout_sec=self.request_timeout_sec, + ) + finally: + if overlay_handle is not None: + overlay_handle.close() + self._require_status(response, 201, context="startup") + try: + session = HarborDependencySessionResponse.model_validate_json(response.content) + except ValueError as exc: + raise DependencyRuntimeError("Harbor bridge returned an invalid dependency startup response") from exc + self._session_id = session.session_id + self._session_capability = session.capability_token + self.metadata.update( + { + "execution_boundary": "remote-harbor-bridge", + "harbor_dependency_session_id": session.session_id, + } + ) + finally: + shutil.rmtree(staging, ignore_errors=True) + + async def _stop(self) -> None: + if self._session_id is None: + return + session_id = self._session_id + response = await self._send( + "DELETE", + f"/v1/dependencies/{session_id}", + timeout_sec=self.request_timeout_sec, + capability_token=self._session_capability, + ) + self._require_status(response, 204, context="shutdown") + self._session_id = None + self._session_capability = None + self.metadata.pop("harbor_dependency_session_id", None) + + async def _send( + self, + method: str, + path: str, + *, + timeout_sec: float, + capability_token: str | None = None, + **kwargs: Any, + ) -> httpx.Response: + token = os.environ.get(self.bridge_token_env) + if not token: + raise DependencyRuntimeError( + f"Harbor bridge token environment variable is not set: {self.bridge_token_env}" + ) + url = f"{str(self.bridge_url).rstrip('/')}{path}" + headers = {"Authorization": f"Bearer {token}"} + if capability_token is not None: + headers["X-Nemo-Dependency-Capability"] = capability_token + try: + if self._client is not None: + return await self._client.request(method, url, headers=headers, **kwargs) + async with httpx.AsyncClient(timeout=httpx.Timeout(timeout_sec)) as client: + return await client.request(method, url, headers=headers, **kwargs) + except httpx.HTTPError as exc: + raise DependencyRuntimeError(f"Harbor bridge dependency request failed: {exc}") from exc + + @staticmethod + def _require_status(response: httpx.Response, expected: int, *, context: str) -> None: + if response.status_code == expected: + return + detail = response.text[:4000] + raise DependencyRuntimeError( + f"Harbor bridge dependency {context} returned HTTP {response.status_code}: {detail}" + ) + + +class RemoteHarborDependencyContext: + """Start and stop one bridge-owned Harbor dependency session.""" + + def __init__(self, runtime: RemoteHarborDependencyRuntime) -> None: + self._runtime = runtime + + async def __aenter__(self) -> DependencyRuntime: + try: + await self._runtime._start() + except asyncio.CancelledError: + try: + await self._runtime._stop() + except Exception: + pass + raise + except Exception as exc: + try: + await self._runtime._stop() + except Exception: + pass + if isinstance(exc, DependencyRuntimeError): + raise + raise DependencyRuntimeError(f"Remote Harbor dependency startup failed: {exc}") from exc + return self._runtime + + async def __aexit__( + self, + exc_type: type[BaseException] | None, + exc: BaseException | None, + traceback: TracebackType | None, + ) -> bool: + try: + await self._runtime._stop() + except Exception: + if exc_type is None: + raise + return False + + +def _dependency_request_id(task_id: str, task_path: Path) -> str: + raw = f"{task_id}:{task_path}" + normalized = re.sub(r"[^A-Za-z0-9_.-]+", "-", task_id).strip("._-") or "task" + digest = hashlib.sha256(raw.encode("utf-8")).hexdigest()[:10] + return f"dependency-{normalized[:48]}-{digest}" + + +def _request_id(agent: Path, dataset: Dataset, configured: str | None) -> str: + raw = configured or f"{agent.name}-{dataset.id}" + normalized = re.sub(r"[^A-Za-z0-9_.-]+", "-", raw).strip("._-") or "evaluation" + digest = hashlib.sha256(raw.encode("utf-8")).hexdigest()[:10] + return f"{normalized[:60]}-{digest}" + + +def _scorer_identity(dataset_path: Path) -> str | None: + """Read the sealed Eval Author scorer identity when this is an Insight suite.""" + manifest_path = dataset_path / "manifest.json" + if not manifest_path.is_file(): + return None + try: + payload = json.loads(manifest_path.read_text(encoding="utf-8")) + except (OSError, UnicodeError, json.JSONDecodeError) as exc: + raise ValueError(f"Invalid Harbor dataset manifest {manifest_path}: {exc}") from exc + value = payload.get("scorer_identity") + if value is None: + return None + if not isinstance(value, str) or re.fullmatch(r"sha256:[0-9a-f]{64}", value) is None: + raise ValueError(f"Invalid scorer_identity in {manifest_path}: {value!r}") + return value + + +class RemoteHarborEvaluator(Evaluator): + """Submit candidate and dataset bundles to the narrow Harbor bridge.""" + + evaluator_type: EvaluatorType = "harbor" + options: RemoteHarborEvaluatorConfig + + def __init__( + self, + options: RemoteHarborEvaluatorConfig, + experiment_dir: Path | None = None, + *, + client: httpx.AsyncClient | None = None, + ) -> None: + super().__init__(options, experiment_dir=experiment_dir) + self.options = options + self._client = client + + def prepare_dataset( + self, + dataset: Dataset, + options: RemoteHarborEvaluatorConfig | None = None, + ) -> Dataset: + """Replace Docker-backed Harbor task runtimes with bridge-backed runtimes.""" + if not isinstance(dataset, HarborDataset): + raise ValueError("Dataset must be a Harbor dataset") + if dataset.source is None: + raise ValueError("Harbor dataset source is required") + runtime_options = options or self.options + dataset_path = local_path_from_uri(dataset.source.uri, context="Harbor dataset reference").resolve() + for task in dataset.tasks: + dependencies = task.dependencies + if dependencies is None: + continue + if isinstance(dependencies, RemoteHarborDependencyRuntime): + continue + if not isinstance(dependencies, HarborDependencyRuntime): + raise DependencyRuntimeError( + f"Remote Harbor evaluator will not run unsupported task dependencies locally: {task.id}" + ) + if dependencies.environment_type != "docker": + raise DependencyRuntimeError(f"Remote Harbor dependencies require environment_type='docker': {task.id}") + if not dependencies.delete: + raise DependencyRuntimeError( + f"Remote Harbor dependencies require delete=true so bridge sessions cannot leak: {task.id}" + ) + if dependencies.start is not None or dependencies.readiness is not None or dependencies.stop is not None: + raise DependencyRuntimeError( + f"Remote Harbor dependencies do not support custom lifecycle commands: {task.id}" + ) + task_path = local_path_from_uri(dependencies.task_path.uri, context="Harbor task reference").resolve() + binding = resolve_envelope_task(dataset_path, task_path, task_id=task.id) + task.dependencies = RemoteHarborDependencyRuntime( + task_id=task.id, + base_task_id=binding.base_task_id, + envelope_id=binding.envelope_id, + envelope_digest=binding.envelope_digest, + task_path=dependencies.task_path, + overlay_policy=binding.policy, + bridge_url=runtime_options.bridge_url, + bridge_token_env=runtime_options.bridge_token_env, + request_timeout_sec=runtime_options.request_timeout_sec, + max_archive_bytes=runtime_options.max_archive_bytes, + force_build=dependencies.force_build, + run_healthcheck=dependencies.run_healthcheck, + build_timeout_sec=dependencies.build_timeout_sec, + metadata={ + **dependencies.metadata, + "execution_boundary": "remote-harbor-bridge", + }, + ) + return dataset + + async def _run( + self, + agent: Path, + dataset: Dataset, + options: EvaluatorConfig, + ) -> list[TrialResult]: + if not isinstance(options, RemoteHarborEvaluatorConfig): + raise TypeError("Remote Harbor evaluator requires RemoteHarborEvaluatorConfig") + if not isinstance(dataset, HarborDataset): + raise ValueError("Dataset must be a Harbor dataset") + if dataset.source is None: + raise ValueError("Harbor dataset source is required") + self.prepare_dataset(dataset, options) + + agent_path = agent.expanduser().resolve() + dataset_path = local_path_from_uri(dataset.source.uri, context="Harbor dataset reference").resolve() + if not agent_path.is_dir(): + raise FileNotFoundError(f"Harbor agent path not found: {agent_path}") + if not dataset_path.is_dir(): + raise FileNotFoundError(f"Harbor dataset path not found: {dataset_path}") + await dataset.validate() + bindings = [ + resolve_envelope_task( + dataset_path, + local_path_from_uri(task.uri, context="Harbor task reference").resolve(), + task_id=task.id, + ) + for task in dataset.tasks + ] + envelope_keys = {(binding.envelope_id, binding.envelope_digest) for binding in bindings} + if len(envelope_keys) != 1: + raise ValueError("One Harbor evaluation may reference exactly one trusted task envelope") + envelope_id, envelope_digest = envelope_keys.pop() + + token = os.environ.get(options.bridge_token_env) + if not token: + raise ValueError(f"Harbor bridge token environment variable is not set: {options.bridge_token_env}") + + request_id = _request_id(agent_path, dataset, options.job_name) + experiment_dir = (self.experiment_dir or Path.cwd()).resolve() + result_dir = experiment_dir / options.result_dir / request_id + result_path = result_dir / "result.json" + if result_path.is_file() and not options.force_rerun: + return list(materialize_result_archive_from_directory(result_dir).trials) + + staging = experiment_dir / "tmp" / "harbor-bridge" / f"{request_id}-{uuid4().hex[:8]}" + staging.mkdir(parents=True, exist_ok=False) + candidate_archive = staging / "candidate.tar.gz" + overlay_dir = staging / "overlay" + overlay_archive = staging / "overlay.tar.gz" + response_archive = staging / "response.tar.gz" + try: + create_directory_archive(agent_path, candidate_archive, max_bytes=options.max_archive_bytes) + overlay_digest = create_overlay_directory(bindings, overlay_dir) + if overlay_digest is not None: + create_directory_archive(overlay_dir, overlay_archive, max_bytes=options.max_archive_bytes) + request = HarborBridgeRequest( + request_id=request_id, + envelope_id=envelope_id, + envelope_digest=envelope_digest, + tasks=[ + EnvelopeTaskSelection(task_id=binding.task_id, base_task_id=binding.base_task_id) + for binding in bindings + ], + candidate_digest=transport_tree_digest(agent_path), + overlay_digest=overlay_digest, + scorer_identity=_scorer_identity(dataset_path), + n_attempts=options.n_attempts, + n_concurrent_trials=options.n_concurrent_trials, + agent_model_name=options.agent_model_name, + agent_timeout_multiplier=options.agent_timeout_multiplier, + verifier_timeout_multiplier=options.verifier_timeout_multiplier, + agent_setup_timeout_multiplier=options.agent_setup_timeout_multiplier, + environment_build_timeout_multiplier=options.environment_build_timeout_multiplier, + ) + await self._submit( + options, + token=token, + request=request, + candidate_archive=candidate_archive, + overlay_archive=overlay_archive if overlay_digest is not None else None, + response_archive=response_archive, + ) + if result_dir.exists(): + shutil.rmtree(result_dir) + result_dir.mkdir(parents=True) + result = materialize_result_archive(response_archive, result_dir) + return list(result.trials) + finally: + shutil.rmtree(staging, ignore_errors=True) + + async def _submit( + self, + options: RemoteHarborEvaluatorConfig, + *, + token: str, + request: HarborBridgeRequest, + candidate_archive: Path, + overlay_archive: Path | None, + response_archive: Path, + ) -> None: + url = f"{str(options.bridge_url).rstrip('/')}/v1/evaluations" + with candidate_archive.open("rb") as candidate: + files = { + "candidate": ("candidate.tar.gz", candidate, "application/gzip"), + } + overlay_handle = None + if overlay_archive is not None: + overlay_handle = overlay_archive.open("rb") + files["overlay"] = ("overlay.tar.gz", overlay_handle, "application/gzip") + data = {"request": request.model_dump_json()} + headers = {"Authorization": f"Bearer {token}"} + try: + if self._client is not None: + response = await self._client.post(url, data=data, files=files, headers=headers) + else: + timeout = httpx.Timeout(options.request_timeout_sec) + async with httpx.AsyncClient(timeout=timeout) as client: + response = await client.post(url, data=data, files=files, headers=headers) + finally: + if overlay_handle is not None: + overlay_handle.close() + if response.status_code != 200: + detail = response.text[:4000] + raise RuntimeError(f"Harbor bridge returned HTTP {response.status_code}: {detail}") + if response.headers.get("content-type", "").split(";", 1)[0] != "application/gzip": + raise RuntimeError( + f"Harbor bridge returned unexpected content type: {response.headers.get('content-type')}" + ) + if len(response.content) > options.max_archive_bytes: + raise RuntimeError(f"Harbor bridge response exceeds {options.max_archive_bytes} bytes") + response_archive.write_bytes(response.content) + + +def materialize_result_archive_from_directory(result_dir: Path) -> EvaluationResult: + """Load a previously materialized bridge result without changing its URIs.""" + return EvaluationResult.model_validate_json((result_dir / "result.json").read_text(encoding="utf-8")) diff --git a/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/experimentalist/components/loop.py b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/experimentalist/components/loop.py index 0dade05043..011b3ba263 100644 --- a/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/experimentalist/components/loop.py +++ b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/experimentalist/components/loop.py @@ -433,14 +433,18 @@ async def _run(self, deps: ExperimentalistDeps) -> ExperimentalistResult: task_template_ref = staged_inputs.task_template # ---- Resolve datasets to evaluator-domain objects ----------------- - train_eval_dataset = dataset_factory.build_dataset( - deps.evaluator_type, - train_dataset_ref, + train_eval_dataset = evaluator.prepare_dataset( + dataset_factory.build_dataset( + deps.evaluator_type, + train_dataset_ref, + ) ) - validation_eval_dataset = dataset_factory.build_dataset( - deps.evaluator_type, - validation_dataset_ref, + validation_eval_dataset = evaluator.prepare_dataset( + dataset_factory.build_dataset( + deps.evaluator_type, + validation_dataset_ref, + ) ) # ---- Resolve insight (Mode 1) vs local agent (Mode 2) ----------- @@ -486,9 +490,10 @@ async def _run(self, deps: ExperimentalistDeps) -> ExperimentalistResult: train_dataset=train_eval_dataset, validation_dataset=validation_eval_dataset, client=backend.client, + prepare_dataset=evaluator.prepare_dataset, ) - train_eval_dataset = eval_author_result.train_dataset - validation_eval_dataset = eval_author_result.validation_dataset + train_eval_dataset = evaluator.prepare_dataset(eval_author_result.train_dataset) + validation_eval_dataset = evaluator.prepare_dataset(eval_author_result.validation_dataset) insight_eval_dataset = eval_author_result.insight_suite else: # Mode 2: local agent directory as baseline, no insight required. diff --git a/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/experimentalist/components/rationalizer.py b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/experimentalist/components/rationalizer.py index 6be50d9423..123029b75c 100644 --- a/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/experimentalist/components/rationalizer.py +++ b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/experimentalist/components/rationalizer.py @@ -116,9 +116,19 @@ async def run(self, task: Task, agent_spec: Path | None = None) -> Rationale: if cached is not None: return cached async with task.start_deps() as runtime: - rationale = await self.solve(task, runtime, agent_spec=agent_spec) - rationale = await self.verify(task, runtime, rationale, agent_spec=agent_spec) - cache.store(self._workspace_path, key, rationale) + had_dependencies = "dependencies" in self.context + previous_dependencies = self.context.get("dependencies") + self.context["dependencies"] = runtime + try: + with self.shell.use_dependency_runtime(runtime): + rationale = await self.solve(task, runtime, agent_spec=agent_spec) + rationale = await self.verify(task, runtime, rationale, agent_spec=agent_spec) + cache.store(self._workspace_path, key, rationale) + finally: + if had_dependencies: + self.context["dependencies"] = previous_dependencies + else: + self.context.pop("dependencies", None) return rationale @strategy(CodeActStrategy(config=CodeActConfig(max_iterations=30, cell_timeout=120.0))) @@ -472,12 +482,11 @@ async def solve(self, task: Task, runtime: DependencyRuntime | None, agent_spec: runtime injects to discover how to reach it — do not assume any specific mechanism (container, process, HTTP service, etc.). - The rationalizer's ``self.shell`` runs on the host. It can reach the - task's runtime only through whatever interface the runtime exposes - (e.g. env vars pointing to endpoints or exec wrappers). Never execute - host-side commands and record their output as if they were the AUT's - in-runtime experience — the paths, permissions, and tools available - on the host differ from those in the task runtime. + During this method, ``self.shell`` is bound to the active task runtime + when that runtime exposes command execution. Otherwise it runs on the + rationalizer host and can reach the task only through interfaces the + runtime exposes (for example, env vars pointing to endpoints). Never + record host-only output as if it were the AUT's in-runtime experience. Never include in rationale steps: - Paths or commands that only work on the rationalizer host, not in diff --git a/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/experimentalist/components/tools.py b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/experimentalist/components/tools.py index 97c635b963..717feac902 100644 --- a/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/experimentalist/components/tools.py +++ b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/experimentalist/components/tools.py @@ -2,10 +2,16 @@ # SPDX-License-Identifier: Apache-2.0 import logging -from collections.abc import Sequence +from collections.abc import Iterator, Sequence +from contextlib import contextmanager +from contextvars import ContextVar from pathlib import Path from nemo_experimentalist_plugin.entities import Candidate +from nemo_experimentalist_plugin.experimentalist.components.evaluator.models import ( + DependencyCommandExecutor, + DependencyRuntime, +) from nooa.tools import ShellResult, ShellTools from .holdout_utils import ( @@ -49,6 +55,20 @@ def __init__( """Initialize with a working directory and an optional set of blocked path tokens.""" super().__init__(cwd=str(cwd), init_command=init_command) self._blocked_paths = tuple(blocked_paths) + self._dependency_executor: ContextVar[DependencyCommandExecutor | None] = ContextVar( + f"dependency_executor_{id(self)}", + default=None, + ) + + @contextmanager + def use_dependency_runtime(self, runtime: DependencyRuntime | None) -> Iterator[None]: + """Route shell calls through an executable task runtime while it is active.""" + executor = runtime if isinstance(runtime, DependencyCommandExecutor) else None + token = self._dependency_executor.set(executor) + try: + yield + finally: + self._dependency_executor.reset(token) def is_blocked(self, command: str) -> bool: """Return True if the command references any held-out split path token. @@ -85,6 +105,13 @@ async def run( if self.is_blocked(command): logger.warning(f"GuardedShellTools blocked held-out access: {command}") return ShellResult(stdout="", stderr=BLOCKED_MESSAGE, returncode=1) + if executor := self._dependency_executor.get(): + result = await executor.execute(command, stdin=stdin, timeout=timeout) + return ShellResult( + stdout=result.stdout, + stderr=result.stderr, + returncode=result.returncode, + ) return await super().run(command, stdin=stdin, timeout=timeout) diff --git a/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/experimentalist/components/trace_analyzer.py b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/experimentalist/components/trace_analyzer.py index e46ae16ffe..bf42b28572 100644 --- a/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/experimentalist/components/trace_analyzer.py +++ b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/experimentalist/components/trace_analyzer.py @@ -336,17 +336,27 @@ async def run( rationale = rationale or Rationale(task_name=task.id, steps=[]) async with task.start_deps() as runtime: - overview = await self.get_overview(trace, trial) - analysis = await self.analyze_trajectory( - trace=trace, - trial=trial, - task=task, - overview=overview, - rationale=rationale, - insight=insight, - agent_path=agent_path, - runtime=runtime, - ) - diagnostic = await self.diagnose(trace, analysis, insight) - cache.store(self._experiment_dir, key, diagnostic) + had_dependencies = "dependencies" in self.context + previous_dependencies = self.context.get("dependencies") + self.context["dependencies"] = runtime + try: + with self.shell.use_dependency_runtime(runtime): + overview = await self.get_overview(trace, trial) + analysis = await self.analyze_trajectory( + trace=trace, + trial=trial, + task=task, + overview=overview, + rationale=rationale, + insight=insight, + agent_path=agent_path, + runtime=runtime, + ) + diagnostic = await self.diagnose(trace, analysis, insight) + cache.store(self._experiment_dir, key, diagnostic) + finally: + if had_dependencies: + self.context["dependencies"] = previous_dependencies + else: + self.context.pop("dependencies", None) return diagnostic diff --git a/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/harbor_bridge/archives.py b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/harbor_bridge/archives.py new file mode 100644 index 0000000000..fb730550d8 --- /dev/null +++ b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/harbor_bridge/archives.py @@ -0,0 +1,241 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 + +"""Validated archive transport for Harbor bridge inputs and results.""" + +from __future__ import annotations + +import shutil +import tarfile +from collections.abc import Iterator +from pathlib import Path, PurePosixPath +from typing import Mapping +from urllib.parse import quote, unquote, urlparse + +from nemo_experimentalist_plugin.experimentalist.components.evaluator.models import ( + EvaluationResult, + ResourceRef, +) + +BRIDGE_ARTIFACT_SCHEME = "nemo-harbor-bridge" +DEFAULT_MAX_ARCHIVE_BYTES = 512 * 1024 * 1024 +DEFAULT_MAX_ARCHIVE_FILES = 20_000 +_IGNORED_PARTS = frozenset({".git", ".venv", "__pycache__"}) + + +def _archive_paths(root: Path) -> Iterator[Path]: + for path in sorted(root.rglob("*")): + relative = path.relative_to(root) + if any(part in _IGNORED_PARTS for part in relative.parts): + continue + yield path + + +def create_directory_archive( + root: Path, + destination: Path, + *, + max_bytes: int = DEFAULT_MAX_ARCHIVE_BYTES, + max_files: int = DEFAULT_MAX_ARCHIVE_FILES, +) -> None: + """Archive one directory without following links or special files.""" + source = root.expanduser().resolve() + if not source.is_dir(): + raise FileNotFoundError(f"Archive source directory not found: {source}") + + destination.parent.mkdir(parents=True, exist_ok=True) + total_bytes = 0 + entry_count = 0 + with tarfile.open(destination, mode="w:gz", dereference=False) as archive: + for path in _archive_paths(source): + relative = path.relative_to(source) + entry_count += 1 + if entry_count > max_files: + raise ValueError(f"Archive source exceeds {max_files} entries") + if path.is_symlink(): + raise ValueError(f"Archive source contains a symbolic link: {relative}") + if path.is_dir(): + archive.add(path, arcname=relative.as_posix(), recursive=False) + continue + if not path.is_file(): + raise ValueError(f"Archive source contains a special file: {relative}") + total_bytes += path.stat().st_size + if total_bytes > max_bytes: + raise ValueError(f"Archive source exceeds {max_bytes} uncompressed bytes") + archive.add(path, arcname=relative.as_posix(), recursive=False) + + +def _validated_member_path(member: tarfile.TarInfo) -> PurePosixPath: + path = PurePosixPath(member.name) + if path.is_absolute() or not path.parts or any(part in ("", ".", "..") for part in path.parts): + raise ValueError(f"Unsafe archive member path: {member.name!r}") + if member.issym() or member.islnk() or member.isdev(): + raise ValueError(f"Unsupported archive member type: {member.name!r}") + if not member.isdir() and not member.isfile(): + raise ValueError(f"Unsupported archive member type: {member.name!r}") + return path + + +def extract_directory_archive( + archive_path: Path, + destination: Path, + *, + max_bytes: int = DEFAULT_MAX_ARCHIVE_BYTES, + max_files: int = DEFAULT_MAX_ARCHIVE_FILES, +) -> None: + """Extract a gzip tar after validating paths, types, counts, and sizes.""" + destination.mkdir(parents=True, exist_ok=True) + with tarfile.open(archive_path, mode="r:gz") as archive: + members = archive.getmembers() + if len(members) > max_files: + raise ValueError(f"Archive exceeds {max_files} entries") + member_names = [member.name for member in members] + if len(set(member_names)) != len(member_names): + raise ValueError("Archive contains duplicate member paths") + files = [member for member in members if member.isfile()] + total_bytes = sum(member.size for member in files) + if total_bytes > max_bytes: + raise ValueError(f"Archive exceeds {max_bytes} uncompressed bytes") + + for member in members: + relative = _validated_member_path(member) + target = destination.joinpath(*relative.parts) + if member.isdir(): + target.mkdir(parents=True, exist_ok=True) + continue + target.parent.mkdir(parents=True, exist_ok=True) + source = archive.extractfile(member) + if source is None: + raise ValueError(f"Archive file has no readable content: {member.name!r}") + with source, target.open("wb") as output: + shutil.copyfileobj(source, output) + target.chmod(member.mode & 0o777) + + +def _result_resource_refs(result: EvaluationResult) -> Iterator[ResourceRef]: + for trial in result.trials: + if trial.trace is not None: + yield trial.trace + yield from trial.resources.values() + for output in trial.outputs.values(): + if isinstance(output, ResourceRef): + yield output + for metric in trial.metrics.values(): + if metric.spec is not None and metric.spec.ref is not None: + yield metric.spec.ref + + +def _bridge_uri(relative: Path) -> str: + return f"{BRIDGE_ARTIFACT_SCHEME}:///{quote(relative.as_posix())}" + + +def _copy_external_resource(source: Path, destination: Path) -> None: + if source.is_symlink(): + raise ValueError(f"Evaluation resource is a symbolic link: {source}") + if source.is_dir(): + shutil.copytree(source, destination, symlinks=True, dirs_exist_ok=True) + elif source.is_file(): + destination.parent.mkdir(parents=True, exist_ok=True) + shutil.copy2(source, destination) + else: + raise ValueError(f"Evaluation resource does not exist or is a special file: {source}") + + +def _rewrite_result_for_transport( + result: EvaluationResult, + artifact_root: Path, + additional_resource_roots: Mapping[str, Path], +) -> EvaluationResult: + transported = EvaluationResult.model_validate_json(result.model_dump_json()) + root = artifact_root.resolve() + allowed_roots = {label: path.expanduser().resolve() for label, path in additional_resource_roots.items()} + for resource in _result_resource_refs(transported): + parsed = urlparse(resource.uri) + if parsed.scheme not in ("", "file"): + continue + raw_path = unquote(parsed.path) if parsed.scheme == "file" else resource.uri + path = Path(raw_path).expanduser().resolve() + try: + relative = path.relative_to(root) + except ValueError: + for label, allowed_root in allowed_roots.items(): + try: + external_relative = path.relative_to(allowed_root) + except ValueError: + continue + relative = Path("_bridge_resources") / label / external_relative + _copy_external_resource(path, root / relative) + break + else: + raise ValueError(f"Evaluation resource escapes the bridge artifact roots: {path}") from None + resource.uri = _bridge_uri(relative) + return transported + + +def create_result_archive( + result: EvaluationResult, + artifact_root: Path, + destination: Path, + *, + additional_resource_roots: Mapping[str, Path] | None = None, + max_bytes: int = DEFAULT_MAX_ARCHIVE_BYTES, + max_files: int = DEFAULT_MAX_ARCHIVE_FILES, +) -> None: + """Bundle an evaluation result and every referenced Harbor artifact.""" + root = artifact_root.expanduser().resolve() + if not root.is_dir(): + raise FileNotFoundError(f"Bridge artifact root not found: {root}") + transported = _rewrite_result_for_transport(result, root, additional_resource_roots or {}) + destination.parent.mkdir(parents=True, exist_ok=True) + result_path = destination.with_name(f"{destination.name}.result.json") + result_path.write_text(transported.model_dump_json(indent=2), encoding="utf-8") + try: + total_bytes = result_path.stat().st_size + entry_count = 1 + if total_bytes > max_bytes: + raise ValueError(f"Bridge result exceeds {max_bytes} uncompressed bytes") + with tarfile.open(destination, mode="w:gz", dereference=False) as archive: + for path in _archive_paths(root): + relative = path.relative_to(root) + entry_count += 1 + if entry_count > max_files: + raise ValueError(f"Bridge result exceeds {max_files} entries") + if path.is_symlink(): + raise ValueError(f"Bridge artifact contains a symbolic link: {relative}") + if not path.is_dir() and not path.is_file(): + raise ValueError(f"Bridge artifact contains a special file: {relative}") + if path.is_file(): + total_bytes += path.stat().st_size + if total_bytes > max_bytes: + raise ValueError(f"Bridge result exceeds {max_bytes} uncompressed bytes") + archive.add(path, arcname=relative.as_posix(), recursive=False) + archive.add(result_path, arcname="result.json", recursive=False) + finally: + result_path.unlink(missing_ok=True) + + +def materialize_result_archive(archive_path: Path, destination: Path) -> EvaluationResult: + """Extract a bridge result and rewrite artifact URIs to local file URIs.""" + extract_directory_archive(archive_path, destination) + result_path = destination / "result.json" + if not result_path.is_file(): + raise ValueError("Harbor bridge response does not contain result.json") + result = EvaluationResult.model_validate_json(result_path.read_text(encoding="utf-8")) + root = destination.resolve() + for resource in _result_resource_refs(result): + parsed = urlparse(resource.uri) + if parsed.scheme != BRIDGE_ARTIFACT_SCHEME: + continue + if parsed.netloc: + raise ValueError(f"Bridge artifact URI must not contain an authority: {resource.uri}") + relative = PurePosixPath(unquote(parsed.path).lstrip("/")) + if not relative.parts or any(part in ("", ".", "..") for part in relative.parts): + raise ValueError(f"Unsafe bridge artifact URI: {resource.uri}") + local_path = root.joinpath(*relative.parts).resolve() + try: + local_path.relative_to(root) + except ValueError as exc: + raise ValueError(f"Bridge artifact URI escapes the result directory: {resource.uri}") from exc + resource.uri = local_path.as_uri() + result_path.write_text(result.model_dump_json(indent=2), encoding="utf-8") + return result diff --git a/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/harbor_bridge/contracts.py b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/harbor_bridge/contracts.py new file mode 100644 index 0000000000..ed937a2efb --- /dev/null +++ b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/harbor_bridge/contracts.py @@ -0,0 +1,96 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 + +"""Narrow wire contract between Experimentalist and the Harbor bridge.""" + +from typing import Annotated + +from nemo_experimentalist_plugin.harbor_bridge.envelopes import ( + EnvelopeId, + EnvelopeTaskSelection, + Sha256Digest, +) +from pydantic import BaseModel, ConfigDict, Field, field_validator + +TaskId = Annotated[str, Field(min_length=1, max_length=256, pattern=r"^[A-Za-z0-9][A-Za-z0-9_.-]*$")] +DEPENDENCY_OUTPUT_LIMIT_CHARS = 30_000 + + +class HarborBridgeRequest(BaseModel): + """Bounded Harbor run parameters accepted from an OpenShell sandbox.""" + + model_config = ConfigDict(extra="forbid") + + request_id: str = Field(min_length=1, max_length=80, pattern=r"^[A-Za-z0-9][A-Za-z0-9_.-]*$") + envelope_id: EnvelopeId + envelope_digest: Sha256Digest + tasks: list[EnvelopeTaskSelection] = Field(min_length=1, max_length=1024) + candidate_digest: Sha256Digest + overlay_digest: Sha256Digest | None = None + scorer_identity: Sha256Digest | None = None + n_attempts: int = Field(default=1, ge=1, le=8) + n_concurrent_trials: int = Field(default=4, ge=1, le=16) + agent_model_name: str | None = Field(default=None, min_length=1, max_length=256) + agent_timeout_multiplier: float | None = Field(default=1.0, ge=0.1, le=10.0) + verifier_timeout_multiplier: float | None = Field(default=1.0, ge=0.1, le=10.0) + agent_setup_timeout_multiplier: float | None = Field(default=1.0, ge=0.1, le=10.0) + environment_build_timeout_multiplier: float | None = Field(default=1.0, ge=0.1, le=10.0) + + @field_validator("tasks") + @classmethod + def validate_unique_task_ids(cls, value: list[EnvelopeTaskSelection]) -> list[EnvelopeTaskSelection]: + """Reject ambiguous selections before they become filesystem inputs.""" + task_ids = [task.task_id for task in value] + if len(set(task_ids)) != len(task_ids): + raise ValueError("tasks must not contain duplicate task ids") + return value + + @property + def task_ids(self) -> list[str]: + """Return materialized task ids for evaluator compatibility.""" + return [task.task_id for task in self.tasks] + + +class HarborDependencyRequest(BaseModel): + """Bounded request to start one Harbor task environment.""" + + model_config = ConfigDict(extra="forbid") + + request_id: str = Field(min_length=1, max_length=80, pattern=r"^[A-Za-z0-9][A-Za-z0-9_.-]*$") + envelope_id: EnvelopeId + envelope_digest: Sha256Digest + task_id: TaskId + base_task_id: TaskId + overlay_digest: Sha256Digest | None = None + force_build: bool = True + run_healthcheck: bool = True + build_timeout_sec: int | None = Field(default=None, ge=1, le=3600) + + +class HarborDependencySessionResponse(BaseModel): + """Opaque handle for one bridge-owned Harbor task environment.""" + + model_config = ConfigDict(extra="forbid") + + session_id: str = Field(min_length=1, max_length=128, pattern=r"^[A-Za-z0-9][A-Za-z0-9_.-]*$") + capability_token: str = Field(min_length=16, max_length=256) + + +class HarborDependencyExecRequest(BaseModel): + """One shell command executed inside a bridge-owned task environment.""" + + model_config = ConfigDict(extra="forbid") + + command: str = Field(min_length=1, max_length=65_536) + stdin: str | None = Field(default=None, max_length=1_048_576) + timeout_sec: int = Field(default=30, ge=1, le=3600) + + +class HarborDependencyExecResponse(BaseModel): + """Captured result from a task-environment command.""" + + model_config = ConfigDict(extra="forbid") + + stdout: str = Field(default="", max_length=DEPENDENCY_OUTPUT_LIMIT_CHARS + 64) + stderr: str = Field(default="", max_length=DEPENDENCY_OUTPUT_LIMIT_CHARS + 64) + returncode: int diff --git a/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/harbor_bridge/dependencies.py b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/harbor_bridge/dependencies.py new file mode 100644 index 0000000000..157dadb4be --- /dev/null +++ b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/harbor_bridge/dependencies.py @@ -0,0 +1,164 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 + +"""Bridge-owned Harbor task environments for analyzer dependency access.""" + +from __future__ import annotations + +import asyncio +import logging +import shlex +from dataclasses import dataclass, field +from pathlib import Path +from uuid import uuid4 + +from nemo_experimentalist_plugin.experimentalist.components.evaluator.harbor import ( + HarborDependencyContext, + HarborDependencyRuntime, +) +from nemo_experimentalist_plugin.experimentalist.components.evaluator.models import ResourceRef +from nemo_experimentalist_plugin.harbor_bridge.contracts import ( + DEPENDENCY_OUTPUT_LIMIT_CHARS, + HarborDependencyExecRequest, + HarborDependencyExecResponse, + HarborDependencyRequest, +) +from nemo_experimentalist_plugin.harbor_bridge.runner import _harden_task + +logger = logging.getLogger(__name__) + + +def _truncate_output(value: str, *, stream: str) -> str: + if len(value) <= DEPENDENCY_OUTPUT_LIMIT_CHARS: + return value + return value[:DEPENDENCY_OUTPUT_LIMIT_CHARS] + f"\n... ({stream} truncated)" + + +class HarborDependencyCapacityError(RuntimeError): + """The bridge has no free dependency-session capacity.""" + + +@dataclass +class _SessionState: + context: HarborDependencyContext + cwd: str = "/app" + lock: asyncio.Lock = field(default_factory=asyncio.Lock) + + +class HarborDependencySessionManager: + """Own active Harbor environments and expose only in-container execution.""" + + def __init__(self, *, max_concurrent_sessions: int) -> None: + self._max_concurrent_sessions = max_concurrent_sessions + self._sessions: dict[str, _SessionState] = {} + self._starting = 0 + self._lock = asyncio.Lock() + + async def start( + self, + request: HarborDependencyRequest, + *, + task_dir: Path, + ) -> str: + """Validate and start one uploaded Harbor task environment.""" + async with self._lock: + if len(self._sessions) + self._starting >= self._max_concurrent_sessions: + raise HarborDependencyCapacityError( + f"Harbor dependency session capacity reached ({self._max_concurrent_sessions})" + ) + self._starting += 1 + + context: HarborDependencyContext | None = None + try: + _harden_task(task_dir) + runtime = HarborDependencyRuntime( + task_path=ResourceRef( + uri=task_dir.resolve().as_uri(), + description="Bridge-local Harbor task dependency environment.", + ), + force_build=request.force_build, + delete=True, + run_healthcheck=request.run_healthcheck, + build_timeout_sec=request.build_timeout_sec, + ) + context = HarborDependencyContext( + runtime, + temp_root=task_dir.parent.parent / "runtime", + ) + await context.__aenter__() + session_id = f"{request.request_id}-{uuid4().hex[:16]}" + async with self._lock: + self._sessions[session_id] = _SessionState(context=context) + return session_id + except BaseException: + if context is not None: + try: + await context.__aexit__(None, None, None) + except Exception: + logger.exception("Harbor dependency cleanup failed after startup error") + raise + finally: + async with self._lock: + self._starting -= 1 + + async def execute( + self, + session_id: str, + request: HarborDependencyExecRequest, + ) -> HarborDependencyExecResponse: + """Execute one command inside an active task environment.""" + async with self._lock: + state = self._sessions.get(session_id) + if state is None: + raise KeyError(session_id) + + async with state.lock: + marker = f"__NEMO_DEPENDENCY_CWD_{uuid4().hex}__" + command = request.command + if request.stdin is not None: + command = f"printf %s {shlex.quote(request.stdin)} | (\n{command}\n)" + wrapped = ( + f"{command}\n" + "_nemo_dependency_status=$?\n" + f"printf '\\036{marker}%s\\036' \"$PWD\"\n" + 'exit "$_nemo_dependency_status"' + ) + result = await state.context.execute( + wrapped, + cwd=state.cwd, + timeout_sec=request.timeout_sec, + ) + + stdout = result.stdout or "" + marker_start = stdout.rfind(f"\x1e{marker}") + if marker_start >= 0: + cwd_start = marker_start + len(marker) + 1 + marker_end = stdout.find("\x1e", cwd_start) + if marker_end >= 0: + state.cwd = stdout[cwd_start:marker_end] + stdout = stdout[:marker_start] + stdout[marker_end + 1 :] + + return HarborDependencyExecResponse( + stdout=_truncate_output(stdout, stream="output"), + stderr=_truncate_output(result.stderr or "", stream="stderr"), + returncode=result.return_code, + ) + + async def stop(self, session_id: str) -> None: + """Stop and forget one dependency environment.""" + async with self._lock: + state = self._sessions.pop(session_id, None) + if state is None: + raise KeyError(session_id) + async with state.lock: + await state.context.__aexit__(None, None, None) + + async def close(self) -> None: + """Stop every dependency environment still owned by the bridge.""" + async with self._lock: + session_ids = list(self._sessions) + for session_id in session_ids: + try: + await self.stop(session_id) + except Exception: + logger.exception("Failed to stop Harbor dependency session %s", session_id) diff --git a/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/harbor_bridge/envelopes.py b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/harbor_bridge/envelopes.py new file mode 100644 index 0000000000..d42481178a --- /dev/null +++ b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/harbor_bridge/envelopes.py @@ -0,0 +1,568 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 + +"""Content-addressed, host-owned Harbor task envelopes.""" + +from __future__ import annotations + +import hashlib +import json +import os +import re +import shutil +import stat +import tomllib +from collections.abc import Iterable +from pathlib import Path, PurePosixPath +from typing import Annotated, Literal + +import tomlkit +from nemo_experimentalist_plugin.experimentalist.components.evaluator.harbor import HarborDataset +from nemo_experimentalist_plugin.experimentalist.components.evaluator.models import DatasetRef, local_path_from_uri +from pydantic import BaseModel, ConfigDict, Field, field_validator, model_validator + +ENVELOPE_DESCRIPTOR_FILENAME = ".nemo-trusted-harbor-envelope.json" +ENVELOPE_POLICY_FILENAME = "nemo-task-envelope.json" +ENVELOPE_MANIFEST_FILENAME = "manifest.json" +ENVELOPE_SCHEMA_VERSION = 1 +HARBOR_ENVELOPE_CATALOG_ENV = "NEMO_EXPERIMENTALIST_HARBOR_ENVELOPE_CATALOG" +_TRANSPORT_IGNORED_PARTS = frozenset({".git", ".venv", "__pycache__"}) +_FORBIDDEN_OVERLAY_FILENAMES = frozenset( + { + ".dockerignore", + "Containerfile", + "Dockerfile", + ENVELOPE_DESCRIPTOR_FILENAME, + ENVELOPE_POLICY_FILENAME, + "compose.yaml", + "compose.yml", + "docker-compose.yaml", + "docker-compose.yml", + "task.toml", + } +) + +EnvelopeId = Annotated[str, Field(min_length=1, max_length=128, pattern=r"^[A-Za-z0-9][A-Za-z0-9_.-]*$")] +Sha256Digest = Annotated[str, Field(pattern=r"^sha256:[0-9a-f]{64}$")] +RelativePath = Annotated[str, Field(min_length=1, max_length=1024)] + + +def _validated_relative_path(value: str) -> str: + path = PurePosixPath(value) + if path.is_absolute() or not path.parts or any(part in ("", ".", "..") for part in path.parts): + raise ValueError(f"path must be a safe relative POSIX path: {value!r}") + return path.as_posix() + + +class TaskDataSlot(BaseModel): + """One exact, typed trace-data file that Eval Author may populate.""" + + model_config = ConfigDict(extra="forbid") + + path: RelativePath + media_type: Literal["application/json", "text/plain"] + max_bytes: int = Field(ge=1, le=16 * 1024 * 1024) + + @field_validator("path") + @classmethod + def validate_path(cls, value: str) -> str: + return _validated_relative_path(value) + + +class TaskEnvelopePolicy(BaseModel): + """Mutable slots intentionally exposed by one trusted task template.""" + + model_config = ConfigDict(extra="forbid") + + schema_version: Literal[1] = ENVELOPE_SCHEMA_VERSION + task_data: list[TaskDataSlot] = Field(default_factory=list, max_length=128) + verifier_paths: list[RelativePath] = Field(default_factory=list, max_length=32) + + @field_validator("verifier_paths") + @classmethod + def validate_paths(cls, value: list[str]) -> list[str]: + normalized = [_validated_relative_path(item) for item in value] + if len(set(normalized)) != len(normalized): + raise ValueError("mutable paths must not contain duplicates") + return normalized + + @model_validator(mode="after") + def reject_overlapping_authorities(self) -> TaskEnvelopePolicy: + task_paths = [PurePosixPath(slot.path) for slot in self.task_data] + verifier_paths = [PurePosixPath(value) for value in self.verifier_paths] + if len({slot.path for slot in self.task_data}) != len(self.task_data): + raise ValueError("task-data paths must not contain duplicates") + for task_path in task_paths: + for verifier_path in verifier_paths: + if _contains(task_path, verifier_path) or _contains(verifier_path, task_path): + raise ValueError(f"task-data and verifier paths must not overlap: {task_path} and {verifier_path}") + return self + + @property + def task_data_paths(self) -> list[str]: + """Return exact trace-data file slots.""" + return [slot.path for slot in self.task_data] + + +class TrustedTaskManifest(BaseModel): + """One immutable task and its declared overlay policy.""" + + model_config = ConfigDict(extra="forbid") + + task_id: str = Field(min_length=1, max_length=256, pattern=r"^[A-Za-z0-9][A-Za-z0-9_.-]*$") + path: str + content_digest: Sha256Digest + policy: TaskEnvelopePolicy = Field(default_factory=TaskEnvelopePolicy) + + @field_validator("path") + @classmethod + def validate_path(cls, value: str) -> str: + if value == ".": + return value + return _validated_relative_path(value) + + +class TrustedEnvelopeManifest(BaseModel): + """Bridge-owned manifest for one registered Harbor dataset.""" + + model_config = ConfigDict(extra="forbid") + + schema_version: Literal[1] = ENVELOPE_SCHEMA_VERSION + envelope_id: EnvelopeId + envelope_digest: Sha256Digest + source: str + tasks: list[TrustedTaskManifest] = Field(min_length=1, max_length=4096) + + @field_validator("tasks") + @classmethod + def validate_unique_tasks(cls, value: list[TrustedTaskManifest]) -> list[TrustedTaskManifest]: + ids = [task.task_id for task in value] + paths = [task.path for task in value] + if len(set(ids)) != len(ids): + raise ValueError("envelope task ids must be unique") + if len(set(paths)) != len(paths): + raise ValueError("envelope task paths must be unique") + return value + + +class TrustedEnvelopeDescriptor(BaseModel): + """Untrusted-readable handle that binds local task paths to a host envelope.""" + + model_config = ConfigDict(extra="forbid") + + schema_version: Literal[1] = ENVELOPE_SCHEMA_VERSION + envelope_id: EnvelopeId + envelope_digest: Sha256Digest + tasks: list[TrustedTaskManifest] = Field(min_length=1, max_length=4096) + + +class EnvelopeTaskSelection(BaseModel): + """One requested materialization from a registered base task.""" + + model_config = ConfigDict(extra="forbid") + + task_id: str = Field(min_length=1, max_length=256, pattern=r"^[A-Za-z0-9][A-Za-z0-9_.-]*$") + base_task_id: str = Field(min_length=1, max_length=256, pattern=r"^[A-Za-z0-9][A-Za-z0-9_.-]*$") + + +class ResolvedEnvelopeTask(BaseModel): + """Envelope binding and policy resolved for one sandbox-visible task.""" + + model_config = ConfigDict(extra="forbid", arbitrary_types_allowed=True) + + envelope_id: EnvelopeId + envelope_digest: Sha256Digest + task_id: str + base_task_id: str + task_path: Path + policy: TaskEnvelopePolicy + + +class RegisteredEnvelope(BaseModel): + """Host-side registration result used to forward trusted inputs.""" + + model_config = ConfigDict(extra="forbid", arbitrary_types_allowed=True) + + manifest: TrustedEnvelopeManifest + dataset_path: Path + + +def _sha256_bytes(value: bytes) -> str: + return f"sha256:{hashlib.sha256(value).hexdigest()}" + + +def _canonical_digest(value: object) -> str: + payload = json.dumps(value, ensure_ascii=False, separators=(",", ":"), sort_keys=True).encode("utf-8") + return _sha256_bytes(payload) + + +def _contains(parent: PurePosixPath, child: PurePosixPath) -> bool: + return child == parent or parent in child.parents + + +def path_is_allowed(relative: str, allowed: Iterable[str]) -> bool: + """Return whether *relative* is equal to or below one declared slot.""" + path = PurePosixPath(_validated_relative_path(relative)) + return any(_contains(PurePosixPath(value), path) for value in allowed) + + +def _tree_entries( + root: Path, + *, + exclude: set[str] | None = None, + ignored_parts: frozenset[str] = frozenset(), +) -> list[dict[str, str]]: + excluded = exclude or set() + entries: list[dict[str, str]] = [] + for path in sorted(root.rglob("*")): + relative = path.relative_to(root).as_posix() + if relative in excluded: + continue + if any(part in ignored_parts for part in PurePosixPath(relative).parts): + continue + mode = path.lstat().st_mode + if stat.S_ISLNK(mode): + raise ValueError(f"Trusted envelope source contains a symbolic link: {relative}") + if stat.S_ISDIR(mode): + entries.append({"path": relative, "type": "directory"}) + continue + if not stat.S_ISREG(mode): + raise ValueError(f"Trusted envelope source contains a special file: {relative}") + entries.append( + { + "path": relative, + "type": "file", + "digest": _sha256_bytes(path.read_bytes()), + "mode": oct(stat.S_IMODE(mode)), + } + ) + return entries + + +def tree_digest(root: Path, *, exclude: set[str] | None = None) -> str: + """Hash paths, content, modes, and empty directories without following links.""" + source = root.expanduser().resolve() + if not source.is_dir(): + raise FileNotFoundError(f"Envelope tree not found: {source}") + return _canonical_digest(_tree_entries(source, exclude=exclude)) + + +def transport_tree_digest(root: Path) -> str: + """Hash the files transported by ``create_directory_archive``.""" + source = root.expanduser().resolve() + if not source.is_dir(): + raise FileNotFoundError(f"Transport tree not found: {source}") + return _canonical_digest(_tree_entries(source, ignored_parts=_TRANSPORT_IGNORED_PARTS)) + + +def _safe_copy_tree(source: Path, destination: Path) -> None: + """Copy a tree only after rejecting links and special files.""" + _tree_entries(source) + shutil.copytree(source, destination, copy_function=shutil.copy2) + + +def _policy_for_task(task_dir: Path) -> TaskEnvelopePolicy: + policy_path = task_dir / ENVELOPE_POLICY_FILENAME + if not policy_path.is_file(): + return TaskEnvelopePolicy() + try: + policy = TaskEnvelopePolicy.model_validate_json(policy_path.read_text(encoding="utf-8")) + except (OSError, UnicodeError, ValueError) as exc: + raise ValueError(f"Invalid task envelope policy {policy_path}: {exc}") from exc + for slot in policy.task_data: + path = task_dir / slot.path + if path.exists() and not path.is_file(): + raise ValueError(f"Trusted task-data slot must name a file: {path}") + return policy + + +def _slug(value: str) -> str: + normalized = re.sub(r"[^A-Za-z0-9_.-]+", "-", value).strip("._-") + return normalized[:72] or "dataset" + + +def register_dataset_envelope( + source: Path, + *, + catalog_root: Path, + name: str, + provenance: str | None = None, +) -> RegisteredEnvelope: + """Copy a host-resolved dataset into a content-addressed trusted catalog.""" + source_path = source.expanduser().resolve() + if not source_path.is_dir(): + raise FileNotFoundError(f"Trusted Harbor dataset not found: {source_path}") + # Validate the source before any partial catalog entry is created. + _tree_entries(source_path) + source_dataset = HarborDataset.from_ref(DatasetRef(uri=source_path.as_uri(), metadata={"id": name})) + + task_sources: list[tuple[str, Path, str, TaskEnvelopePolicy]] = [] + for task in source_dataset.tasks: + task_path = local_path_from_uri(task.uri, context="Trusted Harbor task").resolve() + relative = task_path.relative_to(source_path).as_posix() + if relative == "": + relative = "." + task_sources.append((task.id, task_path, relative, _policy_for_task(task_path))) + + source_digest = tree_digest(source_path, exclude={ENVELOPE_DESCRIPTOR_FILENAME}) + envelope_id = f"{_slug(name)}-{source_digest.removeprefix('sha256:')[:16]}" + envelope_root = catalog_root.expanduser().resolve() / "envelopes" / envelope_id + dataset_path = envelope_root / "dataset" + manifest_path = envelope_root / ENVELOPE_MANIFEST_FILENAME + + if envelope_root.exists(): + manifest = TrustedEnvelopeManifest.model_validate_json(manifest_path.read_text(encoding="utf-8")) + if manifest.envelope_digest != source_digest: + raise ValueError(f"Trusted envelope id collision: {envelope_id}") + return RegisteredEnvelope(manifest=manifest, dataset_path=dataset_path) + + envelope_root.parent.mkdir(parents=True, exist_ok=True) + partial = envelope_root.with_name(f".{envelope_root.name}.{os.getpid()}.partial") + if partial.exists(): + shutil.rmtree(partial) + try: + _safe_copy_tree(source_path, partial / "dataset") + tasks = [ + TrustedTaskManifest( + task_id=task_id, + path=relative, + content_digest=tree_digest( + partial / "dataset" if relative == "." else partial / "dataset" / relative, + exclude={ENVELOPE_DESCRIPTOR_FILENAME}, + ), + policy=policy, + ) + for task_id, _task_path, relative, policy in task_sources + ] + manifest = TrustedEnvelopeManifest( + envelope_id=envelope_id, + envelope_digest=source_digest, + source=provenance or str(source_path), + tasks=tasks, + ) + descriptor = TrustedEnvelopeDescriptor( + envelope_id=manifest.envelope_id, + envelope_digest=manifest.envelope_digest, + tasks=manifest.tasks, + ) + (partial / ENVELOPE_MANIFEST_FILENAME).write_text( + manifest.model_dump_json(indent=2) + "\n", + encoding="utf-8", + ) + (partial / "dataset" / ENVELOPE_DESCRIPTOR_FILENAME).write_text( + descriptor.model_dump_json(indent=2) + "\n", + encoding="utf-8", + ) + os.replace(partial, envelope_root) + except BaseException: + shutil.rmtree(partial, ignore_errors=True) + raise + return RegisteredEnvelope(manifest=manifest, dataset_path=dataset_path) + + +def _descriptor_at(dataset_path: Path, task_path: Path) -> tuple[TrustedEnvelopeDescriptor, Path]: + candidates = ( + task_path / ENVELOPE_DESCRIPTOR_FILENAME, + dataset_path / ENVELOPE_DESCRIPTOR_FILENAME, + ) + for path in candidates: + if path.is_file(): + try: + return TrustedEnvelopeDescriptor.model_validate_json(path.read_text(encoding="utf-8")), path.parent + except (OSError, UnicodeError, ValueError) as exc: + raise ValueError(f"Invalid trusted envelope descriptor {path}: {exc}") from exc + raise ValueError( + f"Harbor task is not bound to a trusted host envelope: {task_path}. " + "Run it through the Experimentalist host launcher." + ) + + +def resolve_envelope_task(dataset_path: Path, task_path: Path, *, task_id: str) -> ResolvedEnvelopeTask: + """Resolve one local task against its host-generated envelope descriptor.""" + descriptor, descriptor_root = _descriptor_at(dataset_path.resolve(), task_path.resolve()) + relative = task_path.resolve().relative_to(descriptor_root.resolve()).as_posix() + if relative == "": + relative = "." + + matches = [task for task in descriptor.tasks if task.path == relative] + if not matches and len(descriptor.tasks) == 1 and descriptor.tasks[0].path == ".": + # Eval Author copies a one-task template into per-trace directories. The + # copied descriptor still intentionally binds each derivative to that base. + matches = descriptor.tasks + if len(matches) != 1: + raise ValueError(f"Trusted envelope descriptor does not bind task path {task_path}") + base = matches[0] + return ResolvedEnvelopeTask( + envelope_id=descriptor.envelope_id, + envelope_digest=descriptor.envelope_digest, + task_id=task_id, + base_task_id=base.task_id, + task_path=task_path.resolve(), + policy=base.policy, + ) + + +def create_overlay_directory(bindings: list[ResolvedEnvelopeTask], destination: Path) -> str | None: + """Copy only declared mutable files into a request-scoped overlay tree.""" + copied = False + destination.mkdir(parents=True, exist_ok=False) + for binding in bindings: + allowed = [*binding.policy.task_data_paths, *binding.policy.verifier_paths] + for declared in allowed: + source = binding.task_path / declared + if not source.exists(): + continue + target = destination / binding.task_id / declared + if source.is_symlink(): + raise ValueError(f"Task overlay contains a symbolic link: {source}") + if source.is_dir(): + _safe_copy_tree(source, target) + elif source.is_file(): + target.parent.mkdir(parents=True, exist_ok=True) + shutil.copy2(source, target) + else: + raise ValueError(f"Task overlay contains a special file: {source}") + copied = True + if not copied: + shutil.rmtree(destination) + return None + return transport_tree_digest(destination) + + +def _task_path(dataset_root: Path, task: TrustedTaskManifest) -> Path: + return dataset_root if task.path == "." else dataset_root / task.path + + +def _set_materialized_identity(task_dir: Path, task_id: str, base_task_id: str) -> None: + if task_id == base_task_id: + return + toml_path = task_dir / "task.toml" + document = tomlkit.parse(toml_path.read_text(encoding="utf-8")) + task_table = document.get("task") + if task_table is None: + raise ValueError(f"Trusted Harbor task has no [task] table: {toml_path}") + raw_name = task_table.get("name") + if not isinstance(raw_name, str) or "/" not in raw_name: + raise ValueError(f"Trusted Harbor task name must use org/name format: {raw_name!r}") + organization, short_name = raw_name.rsplit("/", 1) + base_name = short_name.split("__", 1)[0] + task_table["name"] = f"{organization}/{base_name}__{task_id}" + metadata = document.get("metadata") + if metadata is None: + metadata = tomlkit.table() + document["metadata"] = metadata + provenance = metadata.get("nemo_experimentalist") + if provenance is None: + provenance = tomlkit.table() + metadata["nemo_experimentalist"] = provenance + provenance["trusted_envelope_base_task"] = base_task_id + toml_path.write_text(tomlkit.dumps(document), encoding="utf-8") + + +def _validate_task_data_file(path: Path, slot: TaskDataSlot) -> None: + size = path.stat().st_size + if size > slot.max_bytes: + raise ValueError(f"Task-data overlay exceeds {slot.max_bytes} bytes: {slot.path}") + try: + text = path.read_text(encoding="utf-8") + except UnicodeError as exc: + raise ValueError(f"Task-data overlay must be UTF-8 {slot.media_type}: {slot.path}") from exc + if slot.media_type == "application/json": + try: + json.loads(text) + except json.JSONDecodeError as exc: + raise ValueError(f"Task-data overlay is not valid JSON: {slot.path}: {exc}") from exc + + +class TrustedEnvelopeCatalog: + """Read-only catalog and materializer used exclusively by the host bridge.""" + + def __init__(self, root: Path) -> None: + self.root = root.expanduser().resolve() + if not self.root.is_dir(): + raise FileNotFoundError(f"Trusted Harbor envelope catalog not found: {self.root}") + + def load(self, envelope_id: str, envelope_digest: str) -> tuple[TrustedEnvelopeManifest, Path]: + envelope_root = self.root / "envelopes" / envelope_id + try: + envelope_root.resolve().relative_to((self.root / "envelopes").resolve()) + except ValueError as exc: + raise ValueError(f"Trusted envelope id escapes the catalog: {envelope_id!r}") from exc + manifest_path = envelope_root / ENVELOPE_MANIFEST_FILENAME + if not manifest_path.is_file(): + raise KeyError(envelope_id) + manifest = TrustedEnvelopeManifest.model_validate_json(manifest_path.read_text(encoding="utf-8")) + if manifest.envelope_id != envelope_id or manifest.envelope_digest != envelope_digest: + raise ValueError(f"Trusted envelope identity mismatch: {envelope_id}") + dataset_root = envelope_root / "dataset" + current_digest = tree_digest(dataset_root, exclude={ENVELOPE_DESCRIPTOR_FILENAME}) + if current_digest != manifest.envelope_digest: + raise ValueError(f"Trusted envelope content changed after registration: {envelope_id}") + return manifest, dataset_root + + def materialize( + self, + *, + envelope_id: str, + envelope_digest: str, + selections: list[EnvelopeTaskSelection], + destination: Path, + overlay_dir: Path | None = None, + ) -> Path: + """Materialize selected immutable tasks and apply only declared overlays.""" + manifest, dataset_root = self.load(envelope_id, envelope_digest) + tasks = {task.task_id: task for task in manifest.tasks} + destination.mkdir(parents=True, exist_ok=False) + selected_ids = {selection.task_id for selection in selections} + if len(selected_ids) != len(selections): + raise ValueError("Materialized task ids must be unique") + + if overlay_dir is not None: + overlay_task_dirs = {path.name for path in overlay_dir.iterdir()} + unexpected = overlay_task_dirs - selected_ids + if unexpected: + raise ValueError(f"Task overlay contains unknown task ids: {', '.join(sorted(unexpected))}") + + for selection in selections: + try: + base = tasks[selection.base_task_id] + except KeyError as exc: + raise ValueError(f"Trusted envelope {envelope_id} has no task {selection.base_task_id!r}") from exc + source = _task_path(dataset_root, base) + if tree_digest(source, exclude={ENVELOPE_DESCRIPTOR_FILENAME}) != base.content_digest: + raise ValueError(f"Trusted task content changed after registration: {selection.base_task_id}") + target = destination / selection.task_id + _safe_copy_tree(source, target) + (target / ENVELOPE_DESCRIPTOR_FILENAME).unlink(missing_ok=True) + + task_overlay = overlay_dir / selection.task_id if overlay_dir is not None else None + if task_overlay is not None and task_overlay.exists(): + for path in sorted(task_overlay.rglob("*")): + relative = path.relative_to(task_overlay).as_posix() + if path.name in _FORBIDDEN_OVERLAY_FILENAMES: + raise ValueError( + f"Task overlay may not modify runtime-control file {selection.task_id}/{relative}" + ) + if path.is_dir(): + continue + task_data_slot = next( + (slot for slot in base.policy.task_data if slot.path == relative), + None, + ) + verifier_allowed = path_is_allowed(relative, base.policy.verifier_paths) + if task_data_slot is None and not verifier_allowed: + raise ValueError(f"Task overlay may not modify undeclared path {selection.task_id}/{relative}") + if path.is_symlink() or not path.is_file(): + raise ValueError(f"Task overlay contains an unsupported file: {path}") + if task_data_slot is not None: + _validate_task_data_file(path, task_data_slot) + output = target / relative + output.parent.mkdir(parents=True, exist_ok=True) + shutil.copy2(path, output) + _set_materialized_identity(target, selection.task_id, selection.base_task_id) + return destination + + +def task_config(task_dir: Path) -> dict[str, object]: + """Return the raw task TOML for focused policy and test assertions.""" + return tomllib.loads((task_dir / "task.toml").read_text(encoding="utf-8")) diff --git a/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/harbor_bridge/preparation.py b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/harbor_bridge/preparation.py new file mode 100644 index 0000000000..678c6be3a9 --- /dev/null +++ b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/harbor_bridge/preparation.py @@ -0,0 +1,89 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 + +"""Host-side preparation of trusted Harbor inputs before OpenShell launches.""" + +from __future__ import annotations + +import asyncio +from dataclasses import dataclass +from pathlib import Path +from uuid import uuid4 + +from nemo_experimentalist_plugin.harbor_bridge.envelopes import register_dataset_envelope +from nemo_experimentalist_plugin.resolve import EffectiveExperimentPlan, resolve_dataset + + +@dataclass(frozen=True, slots=True) +class PreparedTrustedInputs: + """Host-owned catalog paths that are also uploaded read-only-by-copy to OpenShell.""" + + catalog_root: Path + train_dataset: Path + validation_dataset: Path + task_template: Path | None + + +async def prepare_trusted_inputs( + plan: EffectiveExperimentPlan, + *, + workspace: Path, +) -> PreparedTrustedInputs: + """Resolve and snapshot the run's Harbor inputs under the host workspace.""" + workspace_path = workspace.expanduser().resolve() + run_root = workspace_path / "tmp" / "experimentalist-openshell" / "trusted-envelopes" / f"run-{uuid4().hex}" + catalog_root = run_root / "catalog" + + if plan.train_dataset == plan.validation_dataset and plan.train_anchor == plan.validation_anchor: + train_source = validation_source = Path( + await resolve_dataset( + plan.train_dataset, + plan.train_anchor, + registry_url=plan.registry_url, + ) + ) + else: + train_value, validation_value = await asyncio.gather( + resolve_dataset( + plan.train_dataset, + plan.train_anchor, + registry_url=plan.registry_url, + ), + resolve_dataset( + plan.validation_dataset, + plan.validation_anchor, + registry_url=plan.registry_url, + ), + ) + train_source = Path(train_value) + validation_source = Path(validation_value) + + train = register_dataset_envelope( + train_source, + catalog_root=catalog_root, + name="train", + provenance=plan.train_dataset, + ) + validation = register_dataset_envelope( + validation_source, + catalog_root=catalog_root, + name="validation", + provenance=plan.validation_dataset, + ) + template_path: Path | None = None + if plan.task_template is not None: + template_source = Path(plan.task_template).expanduser().resolve() + template = register_dataset_envelope( + template_source, + catalog_root=catalog_root, + name="task-template", + provenance=plan.task_template, + ) + template_path = template.dataset_path + + return PreparedTrustedInputs( + catalog_root=catalog_root, + train_dataset=train.dataset_path, + validation_dataset=validation.dataset_path, + task_template=template_path, + ) diff --git a/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/harbor_bridge/runner.py b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/harbor_bridge/runner.py new file mode 100644 index 0000000000..b8c21f1da6 --- /dev/null +++ b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/harbor_bridge/runner.py @@ -0,0 +1,115 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 + +"""Trusted server-side Harbor evaluation runner.""" + +from __future__ import annotations + +from pathlib import Path + +from harbor.models.task.config import EnvironmentConfig, TaskOS, VerifierEnvironmentMode +from harbor.models.task.task import Task as HarborTask +from harbor.models.task.verifier_mode import resolve_effective_verifier_env_config +from nemo_experimentalist_plugin.experimentalist.components.evaluator.harbor import ( + HarborDataset, + HarborEvaluator, + HarborEvaluatorConfig, +) +from nemo_experimentalist_plugin.experimentalist.components.evaluator.models import ( + DatasetRef, + EvaluationResult, + local_path_from_uri, +) +from nemo_experimentalist_plugin.harbor_bridge.contracts import HarborBridgeRequest +from nemo_experimentalist_plugin.harbor_bridge.trusted_agent import candidate_agent_import + + +def _validate_environment(environment: EnvironmentConfig, *, context: str) -> None: + if environment.os != TaskOS.LINUX: + raise ValueError(f"Harbor bridge accepts only Linux {context}") + + +def _require_verifier_definition(task: HarborTask, *, step_index: int | None = None) -> None: + config = task.config + step = config.steps[step_index] if step_index is not None and config.steps is not None else None + environment = resolve_effective_verifier_env_config(config, step) + if environment is None: + raise ValueError(f"Harbor bridge could not resolve a separate verifier environment: {task.task_dir.name}") + if environment.docker_image: + return + tests_dir = task.paths.tests_dir + if step is not None: + step_tests_dir = task.paths.step_tests_dir(step.name) + if step_tests_dir.exists(): + tests_dir = step_tests_dir + if not (tests_dir / "Dockerfile").is_file(): + relative = tests_dir.relative_to(task.task_dir) / "Dockerfile" + raise ValueError( + f"Harbor bridge separate verifier requires {relative.as_posix()} " + f"or verifier.environment.docker_image: {task.task_dir.name}" + ) + + +def _harden_task(task_dir: Path) -> None: + """Apply bridge-owned runtime invariants to a catalog-verified task.""" + task = HarborTask(task_dir) + config = task.config + _validate_environment(config.environment, context=f"task environment {task_dir.name}") + if config.verifier.environment is not None: + _validate_environment(config.verifier.environment, context=f"verifier environment {task_dir.name}") + for index, step in enumerate(config.steps or []): + if step.verifier.environment is not None: + _validate_environment( + step.verifier.environment, + context=f"step verifier environment {task_dir.name}/{step.name}", + ) + step.verifier.environment_mode = VerifierEnvironmentMode.SEPARATE + _require_verifier_definition(task, step_index=index) + + config.verifier.environment_mode = VerifierEnvironmentMode.SEPARATE + if not config.steps: + _require_verifier_definition(task) + (task_dir / "task.toml").write_text(config.model_dump_toml(), encoding="utf-8") + + +class HarborBridgeRunner: + """Run a fixed Harbor adapter over validated, request-scoped inputs.""" + + async def run( + self, + request: HarborBridgeRequest, + *, + candidate_dir: Path, + dataset_dir: Path, + work_dir: Path, + ) -> EvaluationResult: + dataset = HarborDataset.from_ref( + DatasetRef( + uri=dataset_dir.resolve().as_uri(), + metadata={"id": request.request_id, "task_ids": request.task_ids}, + ) + ) + for task in dataset.tasks: + _harden_task(local_path_from_uri(task.uri, context="Harbor task reference").resolve()) + await dataset.validate() + + with candidate_agent_import(candidate_dir) as trusted_import_path: + evaluator = HarborEvaluator( + HarborEvaluatorConfig( + job_name=request.request_id, + jobs_dir=Path("results"), + n_attempts=request.n_attempts, + n_concurrent_trials=request.n_concurrent_trials, + agent_model_name=request.agent_model_name, + quiet=True, + verifier_timeout_multiplier=request.verifier_timeout_multiplier, + agent_timeout_multiplier=request.agent_timeout_multiplier, + agent_setup_timeout_multiplier=request.agent_setup_timeout_multiplier, + environment_build_timeout_multiplier=request.environment_build_timeout_multiplier, + import_path=trusted_import_path, + scope_import_path=False, + trace_dir="/app/traces", + ), + experiment_dir=work_dir, + ) + return await evaluator.run(candidate_dir, dataset) diff --git a/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/harbor_bridge/service.py b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/harbor_bridge/service.py new file mode 100644 index 0000000000..3923db1cc4 --- /dev/null +++ b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/harbor_bridge/service.py @@ -0,0 +1,470 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 + +"""Authenticated local FastAPI boundary around trusted Harbor execution.""" + +from __future__ import annotations + +import argparse +import asyncio +import logging +import os +import secrets +import shutil +from contextlib import asynccontextmanager +from pathlib import Path +from typing import Annotated, Protocol +from uuid import uuid4 + +import uvicorn +from fastapi import Depends, FastAPI, Header, HTTPException, Request +from fastapi.responses import FileResponse +from nemo_experimentalist_plugin.experimentalist.components.evaluator.models import EvaluationResult +from nemo_experimentalist_plugin.harbor_bridge.archives import ( + DEFAULT_MAX_ARCHIVE_BYTES, + create_result_archive, + extract_directory_archive, +) +from nemo_experimentalist_plugin.harbor_bridge.contracts import ( + HarborBridgeRequest, + HarborDependencyExecRequest, + HarborDependencyExecResponse, + HarborDependencyRequest, + HarborDependencySessionResponse, +) +from nemo_experimentalist_plugin.harbor_bridge.dependencies import ( + HarborDependencyCapacityError, + HarborDependencySessionManager, +) +from nemo_experimentalist_plugin.harbor_bridge.envelopes import ( + EnvelopeTaskSelection, + TrustedEnvelopeCatalog, + tree_digest, +) +from nemo_experimentalist_plugin.harbor_bridge.runner import HarborBridgeRunner +from pydantic import BaseModel, ConfigDict, Field, ValidationError +from starlette.background import BackgroundTask +from starlette.datastructures import FormData, UploadFile + +logger = logging.getLogger(__name__) + + +class EvaluationRunner(Protocol): + """Trusted implementation seam used by the HTTP boundary.""" + + async def run( + self, + request: HarborBridgeRequest, + *, + candidate_dir: Path, + dataset_dir: Path, + work_dir: Path, + ) -> EvaluationResult: ... + + +class DependencySessionRunner(Protocol): + """Trusted seam for bridge-owned task dependency environments.""" + + async def start(self, request: HarborDependencyRequest, *, task_dir: Path) -> str: ... + + async def execute( + self, + session_id: str, + request: HarborDependencyExecRequest, + ) -> HarborDependencyExecResponse: ... + + async def stop(self, session_id: str) -> None: ... + + async def close(self) -> None: ... + + +class HarborBridgeSettings(BaseModel): + """Local service limits and storage configuration.""" + + model_config = ConfigDict(extra="forbid") + + storage_root: Path + catalog_root: Path + token: str = Field(min_length=16) + max_archive_bytes: int = Field(default=DEFAULT_MAX_ARCHIVE_BYTES, ge=1, le=2 * 1024 * 1024 * 1024) + max_concurrent_requests: int = Field(default=1, ge=1, le=8) + max_concurrent_dependency_sessions: int = Field(default=8, ge=1, le=64) + + +async def _save_upload(upload: UploadFile, destination: Path, *, max_bytes: int) -> None: + if upload.content_type not in ("application/gzip", "application/x-gzip", "application/octet-stream"): + raise HTTPException(status_code=415, detail=f"Unsupported archive content type: {upload.content_type}") + total = 0 + destination.parent.mkdir(parents=True, exist_ok=True) + try: + with destination.open("wb") as output: + while chunk := await upload.read(1024 * 1024): + total += len(chunk) + if total > max_bytes: + raise HTTPException(status_code=413, detail=f"Archive exceeds {max_bytes} bytes") + output.write(chunk) + finally: + await upload.close() + + +async def _require_form_parts( + request: Request, + *, + required: set[str], + optional: set[str], +) -> FormData: + """Reject legacy or duplicate multipart authorities explicitly.""" + form = await request.form() + keys = [key for key, _value in form.multi_items()] + allowed = required | optional + unexpected = sorted(set(keys) - allowed) + if unexpected: + raise HTTPException(status_code=422, detail=f"Unexpected multipart field(s): {', '.join(unexpected)}") + missing = sorted(required - set(keys)) + if missing: + raise HTTPException(status_code=422, detail=f"Missing multipart field(s): {', '.join(missing)}") + duplicated = sorted(key for key in allowed if keys.count(key) > 1) + if duplicated: + raise HTTPException(status_code=422, detail=f"Duplicate multipart field(s): {', '.join(duplicated)}") + return form + + +def create_app( + *, + settings: HarborBridgeSettings, + runner: EvaluationRunner | None = None, + dependency_sessions: DependencySessionRunner | None = None, + catalog: TrustedEnvelopeCatalog | None = None, +) -> FastAPI: + """Build the local-only bridge application.""" + service_runner = runner or HarborBridgeRunner() + session_runner = dependency_sessions or HarborDependencySessionManager( + max_concurrent_sessions=settings.max_concurrent_dependency_sessions + ) + dependency_work_dirs: dict[str, Path] = {} + dependency_capabilities: dict[str, str] = {} + trusted_catalog = catalog or TrustedEnvelopeCatalog(settings.catalog_root) + sealed_scorers: dict[tuple[str, tuple[tuple[str, str], ...]], tuple[str, str | None]] = {} + storage_root = settings.storage_root.expanduser().resolve() + storage_root.mkdir(parents=True, exist_ok=True) + + @asynccontextmanager + async def lifespan(_: FastAPI): + try: + yield + finally: + try: + await session_runner.close() + finally: + for work_dir in dependency_work_dirs.values(): + shutil.rmtree(work_dir, ignore_errors=True) + dependency_work_dirs.clear() + dependency_capabilities.clear() + + app = FastAPI( + title="NeMo Experimentalist Harbor Bridge", + description="Narrow research-preview boundary around trusted Harbor execution.", + version="0.1.0", + lifespan=lifespan, + ) + semaphore = asyncio.Semaphore(settings.max_concurrent_requests) + + def authorize(authorization: Annotated[str | None, Header()] = None) -> None: + expected = f"Bearer {settings.token}" + if authorization is None or not secrets.compare_digest(authorization, expected): + raise HTTPException(status_code=401, detail="Invalid Harbor bridge bearer token") + + def authorize_dependency_session(session_id: str, capability: str | None) -> None: + expected = dependency_capabilities.get(session_id) + if expected is None: + raise HTTPException(status_code=404, detail="Harbor dependency session not found") + if capability is None or not secrets.compare_digest(capability, expected): + raise HTTPException(status_code=403, detail="Invalid Harbor dependency session capability") + + @app.get("/health/ready") + async def ready() -> dict[str, str]: + return {"status": "ready"} + + @app.post( + "/v1/evaluations", + response_class=FileResponse, + dependencies=[Depends(authorize)], + ) + async def evaluate(raw_request: Request) -> FileResponse: + form = await _require_form_parts( + raw_request, + required={"request", "candidate"}, + optional={"overlay"}, + ) + request = form["request"] + candidate = form["candidate"] + overlay = form.get("overlay") + if not isinstance(request, str): + raise HTTPException(status_code=422, detail="Multipart request field must be text") + if not isinstance(candidate, UploadFile): + raise HTTPException(status_code=422, detail="Multipart candidate field must be a file") + if overlay is not None and not isinstance(overlay, UploadFile): + raise HTTPException(status_code=422, detail="Multipart overlay field must be a file") + try: + bridge_request = HarborBridgeRequest.model_validate_json(request) + except ValidationError as exc: + raise HTTPException(status_code=422, detail=exc.errors(include_url=False)) from exc + + work_dir = storage_root / f"{bridge_request.request_id}-{uuid4().hex[:8]}" + work_dir.mkdir(parents=True, exist_ok=False) + candidate_archive = work_dir / "candidate.tar.gz" + overlay_archive = work_dir / "overlay.tar.gz" + candidate_dir = work_dir / "candidate" + overlay_dir = work_dir / "overlay" + dataset_dir = work_dir / "dataset" + response_archive = work_dir / "response.tar.gz" + try: + await _save_upload(candidate, candidate_archive, max_bytes=settings.max_archive_bytes) + extract_directory_archive( + candidate_archive, + candidate_dir, + max_bytes=settings.max_archive_bytes, + ) + if tree_digest(candidate_dir) != bridge_request.candidate_digest: + raise HTTPException(status_code=422, detail="Candidate content digest does not match request") + if overlay is None and bridge_request.overlay_digest is not None: + raise HTTPException(status_code=422, detail="Task overlay archive is missing") + if overlay is not None and bridge_request.overlay_digest is None: + raise HTTPException(status_code=422, detail="Unexpected task overlay archive") + if overlay is not None: + await _save_upload(overlay, overlay_archive, max_bytes=settings.max_archive_bytes) + extract_directory_archive( + overlay_archive, + overlay_dir, + max_bytes=settings.max_archive_bytes, + ) + if tree_digest(overlay_dir) != bridge_request.overlay_digest: + raise HTTPException(status_code=422, detail="Task overlay content digest does not match request") + + trusted_catalog.materialize( + envelope_id=bridge_request.envelope_id, + envelope_digest=bridge_request.envelope_digest, + selections=bridge_request.tasks, + destination=dataset_dir, + overlay_dir=overlay_dir if overlay is not None else None, + ) + if bridge_request.scorer_identity is not None: + scorer_key = ( + bridge_request.envelope_id, + tuple((task.task_id, task.base_task_id) for task in bridge_request.tasks), + ) + scorer_value = (bridge_request.scorer_identity, bridge_request.overlay_digest) + sealed = sealed_scorers.setdefault(scorer_key, scorer_value) + if sealed != scorer_value: + raise HTTPException( + status_code=409, + detail="Insight scorer is already sealed for this trusted task selection", + ) + async with semaphore: + result = await service_runner.run( + bridge_request, + candidate_dir=candidate_dir, + dataset_dir=dataset_dir, + work_dir=work_dir, + ) + result.metadata.update( + { + "trusted_envelope_id": bridge_request.envelope_id, + "trusted_envelope_digest": bridge_request.envelope_digest, + "candidate_digest": bridge_request.candidate_digest, + "task_overlay_digest": bridge_request.overlay_digest or "", + "scorer_identity": bridge_request.scorer_identity or "", + } + ) + create_result_archive( + result, + work_dir / "results", + response_archive, + additional_resource_roots={"dataset": dataset_dir}, + max_bytes=settings.max_archive_bytes, + ) + if response_archive.stat().st_size > settings.max_archive_bytes: + raise HTTPException( + status_code=413, + detail=f"Evaluation result exceeds {settings.max_archive_bytes} bytes", + ) + return FileResponse( + response_archive, + media_type="application/gzip", + filename=f"{bridge_request.request_id}.tar.gz", + background=BackgroundTask(shutil.rmtree, work_dir, ignore_errors=True), + ) + except HTTPException: + shutil.rmtree(work_dir, ignore_errors=True) + raise + except (KeyError, ValueError) as exc: + shutil.rmtree(work_dir, ignore_errors=True) + raise HTTPException(status_code=422, detail=str(exc)) from exc + except asyncio.CancelledError: + shutil.rmtree(work_dir, ignore_errors=True) + raise + except Exception as exc: + shutil.rmtree(work_dir, ignore_errors=True) + logger.exception("Harbor bridge evaluation failed") + raise HTTPException(status_code=500, detail="Harbor evaluation failed") from exc + + @app.post( + "/v1/dependencies", + response_model=HarborDependencySessionResponse, + status_code=201, + dependencies=[Depends(authorize)], + ) + async def start_dependency(raw_request: Request) -> HarborDependencySessionResponse: + form = await _require_form_parts( + raw_request, + required={"request"}, + optional={"overlay"}, + ) + request = form["request"] + overlay = form.get("overlay") + if not isinstance(request, str): + raise HTTPException(status_code=422, detail="Multipart request field must be text") + if overlay is not None and not isinstance(overlay, UploadFile): + raise HTTPException(status_code=422, detail="Multipart overlay field must be a file") + try: + dependency_request = HarborDependencyRequest.model_validate_json(request) + except ValidationError as exc: + raise HTTPException(status_code=422, detail=exc.errors(include_url=False)) from exc + + work_dir = storage_root / f"dependency-{dependency_request.request_id}-{uuid4().hex[:8]}" + work_dir.mkdir(parents=True, exist_ok=False) + overlay_archive = work_dir / "overlay.tar.gz" + overlay_dir = work_dir / "overlay" + task_dir = work_dir / "task" / dependency_request.task_id + try: + if overlay is None and dependency_request.overlay_digest is not None: + raise HTTPException(status_code=422, detail="Task overlay archive is missing") + if overlay is not None and dependency_request.overlay_digest is None: + raise HTTPException(status_code=422, detail="Unexpected task overlay archive") + if overlay is not None: + await _save_upload(overlay, overlay_archive, max_bytes=settings.max_archive_bytes) + extract_directory_archive( + overlay_archive, + overlay_dir, + max_bytes=settings.max_archive_bytes, + ) + if tree_digest(overlay_dir) != dependency_request.overlay_digest: + raise HTTPException(status_code=422, detail="Task overlay content digest does not match request") + materialized_root = work_dir / "task" + trusted_catalog.materialize( + envelope_id=dependency_request.envelope_id, + envelope_digest=dependency_request.envelope_digest, + selections=[ + EnvelopeTaskSelection( + task_id=dependency_request.task_id, + base_task_id=dependency_request.base_task_id, + ) + ], + destination=materialized_root, + overlay_dir=overlay_dir if overlay is not None else None, + ) + session_id = await session_runner.start( + dependency_request, + task_dir=task_dir, + ) + dependency_work_dirs[session_id] = work_dir + capability_token = secrets.token_urlsafe(32) + dependency_capabilities[session_id] = capability_token + return HarborDependencySessionResponse( + session_id=session_id, + capability_token=capability_token, + ) + except HarborDependencyCapacityError as exc: + shutil.rmtree(work_dir, ignore_errors=True) + raise HTTPException(status_code=429, detail=str(exc)) from exc + except HTTPException: + shutil.rmtree(work_dir, ignore_errors=True) + raise + except (KeyError, ValueError) as exc: + shutil.rmtree(work_dir, ignore_errors=True) + raise HTTPException(status_code=422, detail=str(exc)) from exc + except asyncio.CancelledError: + shutil.rmtree(work_dir, ignore_errors=True) + raise + except Exception as exc: + shutil.rmtree(work_dir, ignore_errors=True) + logger.exception("Harbor dependency startup failed") + raise HTTPException(status_code=500, detail="Harbor dependency startup failed") from exc + + @app.post( + "/v1/dependencies/{session_id}/exec", + response_model=HarborDependencyExecResponse, + dependencies=[Depends(authorize)], + ) + async def execute_dependency( + session_id: str, + request: HarborDependencyExecRequest, + capability: Annotated[str | None, Header(alias="X-Nemo-Dependency-Capability")] = None, + ) -> HarborDependencyExecResponse: + authorize_dependency_session(session_id, capability) + try: + return await session_runner.execute(session_id, request) + except KeyError as exc: + raise HTTPException(status_code=404, detail="Harbor dependency session not found") from exc + except asyncio.CancelledError: + raise + except Exception as exc: + logger.exception("Harbor dependency command failed") + raise HTTPException(status_code=500, detail="Harbor dependency command failed") from exc + + @app.delete( + "/v1/dependencies/{session_id}", + status_code=204, + dependencies=[Depends(authorize)], + ) + async def stop_dependency( + session_id: str, + capability: Annotated[str | None, Header(alias="X-Nemo-Dependency-Capability")] = None, + ) -> None: + authorize_dependency_session(session_id, capability) + work_dir = dependency_work_dirs.get(session_id) + try: + await session_runner.stop(session_id) + except KeyError as exc: + raise HTTPException(status_code=404, detail="Harbor dependency session not found") from exc + except asyncio.CancelledError: + raise + except Exception as exc: + logger.exception("Harbor dependency shutdown failed") + raise HTTPException(status_code=500, detail="Harbor dependency shutdown failed") from exc + finally: + dependency_work_dirs.pop(session_id, None) + dependency_capabilities.pop(session_id, None) + if work_dir is not None: + shutil.rmtree(work_dir, ignore_errors=True) + + return app + + +def main() -> None: + """Run the local research-preview bridge.""" + parser = argparse.ArgumentParser(description="Run the NeMo Experimentalist Harbor bridge") + parser.add_argument("--host", default="127.0.0.1") + parser.add_argument("--port", type=int, default=8765) + parser.add_argument("--storage-root", type=Path, default=Path.cwd() / "tmp" / "experimentalist-harbor-bridge") + parser.add_argument("--catalog-root", type=Path, required=True) + parser.add_argument("--token-env", default="NEMO_EXPERIMENTALIST_HARBOR_BRIDGE_TOKEN") + parser.add_argument("--max-archive-bytes", type=int, default=DEFAULT_MAX_ARCHIVE_BYTES) + parser.add_argument("--max-dependency-sessions", type=int, default=8) + args = parser.parse_args() + + token = os.environ.get(args.token_env) + if not token: + parser.error(f"Harbor bridge token environment variable is not set: {args.token_env}") + settings = HarborBridgeSettings( + storage_root=args.storage_root, + catalog_root=args.catalog_root, + token=token, + max_archive_bytes=args.max_archive_bytes, + max_concurrent_dependency_sessions=args.max_dependency_sessions, + ) + uvicorn.run(create_app(settings=settings), host=args.host, port=args.port) + + +if __name__ == "__main__": + main() diff --git a/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/harbor_bridge/trusted_agent.py b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/harbor_bridge/trusted_agent.py new file mode 100644 index 0000000000..bc99612970 --- /dev/null +++ b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/harbor_bridge/trusted_agent.py @@ -0,0 +1,309 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 + +"""Trusted Harbor adapter that treats an Experimentalist candidate as data.""" + +from __future__ import annotations + +import contextlib +import hashlib +import json +import os +import shlex +import shutil +import sys +import tarfile +import urllib.request +import uuid +from collections.abc import Iterator +from pathlib import Path +from types import ModuleType +from typing import ClassVar, override + +from harbor.agents.installed.base import BaseInstalledAgent, with_prompt_template +from harbor.environments.base import BaseEnvironment +from harbor.models.agent.context import AgentContext + +REMOTE_ROOT = "/installed-agent" +REMOTE_PROJECT = f"{REMOTE_ROOT}/project" +REMOTE_UV = f"{REMOTE_ROOT}/bin/uv" +REMOTE_VENV = f"{REMOTE_ROOT}/venv" +REMOTE_PYTHON_INSTALLS = f"{REMOTE_ROOT}/python" +REMOTE_UV_CACHE = f"{REMOTE_ROOT}/uv-cache" +UV_VERSION = "0.9.5" +UV_ASSETS: dict[str, tuple[str, str]] = { + "aarch64": ( + "uv-aarch64-unknown-linux-musl.tar.gz", + "42b9b83933a289fe9c0e48f4973dee49ce0dfb95e19ea0b525ca0dbca3bce71f", + ), + "x86_64": ( + "uv-x86_64-unknown-linux-musl.tar.gz", + "3665ffb6c429c31ad6c778ac0489b7746e691acf025cf530b3510b2f9b1660ff", + ), +} +_IGNORED_PARTS = frozenset({".git", ".venv", "__pycache__", "tmp"}) + + +def _normalize_architecture(raw: str) -> str: + aliases = { + "amd64": "x86_64", + "arm64": "aarch64", + "aarch64": "aarch64", + "x86_64": "x86_64", + } + normalized = aliases.get(raw.strip().lower()) + if normalized is None: + supported = ", ".join(sorted(UV_ASSETS)) + raise RuntimeError(f"Unsupported task-container architecture {raw!r}; supported: {supported}") + return normalized + + +def _sha256(path: Path) -> str: + digest = hashlib.sha256() + with path.open("rb") as binary_file: + for chunk in iter(lambda: binary_file.read(1024 * 1024), b""): + digest.update(chunk) + return digest.hexdigest() + + +def _download_archive(url: str, destination: Path, expected_sha256: str) -> None: + destination.parent.mkdir(parents=True, exist_ok=True) + partial = destination.with_name(f"{destination.name}.{uuid.uuid4().hex}.partial") + try: + request = urllib.request.Request(url, headers={"User-Agent": "nemo-experimentalist-harbor-bridge"}) + with urllib.request.urlopen(request, timeout=300) as response, partial.open("wb") as output: # noqa: S310 + shutil.copyfileobj(response, output) + actual_sha256 = _sha256(partial) + if actual_sha256 != expected_sha256: + raise RuntimeError( + f"Downloaded uv archive checksum mismatch: expected {expected_sha256}, got {actual_sha256}" + ) + os.replace(partial, destination) + finally: + partial.unlink(missing_ok=True) + + +def _cached_uv_binary(architecture: str) -> Path: + asset_name, expected_sha256 = UV_ASSETS[architecture] + default_cache = Path.cwd() / "tmp" / "runtime-cache" + cache_root = Path(os.environ.get("NEMO_EXPERIMENTALIST_RUNTIME_CACHE", default_cache)) + release_dir = cache_root / f"uv-{UV_VERSION}" + archive = release_dir / asset_name + if not archive.is_file() or _sha256(archive) != expected_sha256: + archive.unlink(missing_ok=True) + url = f"https://github.com/astral-sh/uv/releases/download/{UV_VERSION}/{asset_name}" + _download_archive(url, archive, expected_sha256) + + binary = release_dir / architecture / "uv" + binary.parent.mkdir(parents=True, exist_ok=True) + temporary_binary = binary.with_name(f"uv.{uuid.uuid4().hex}.partial") + member_name = f"{asset_name.removesuffix('.tar.gz')}/uv" + try: + with tarfile.open(archive, mode="r:gz") as bundle: + member = bundle.getmember(member_name) + source = bundle.extractfile(member) + if source is None: + raise RuntimeError(f"Pinned uv archive does not contain {member_name}") + with source, temporary_binary.open("wb") as output: + shutil.copyfileobj(source, output) + temporary_binary.chmod(0o755) + os.replace(temporary_binary, binary) + finally: + temporary_binary.unlink(missing_ok=True) + return binary + + +def _candidate_files(root: Path) -> list[Path]: + required = ("main.py", "pyproject.toml", "uv.lock") + missing = [name for name in required if not (root / name).is_file()] + if missing: + raise RuntimeError(f"Candidate bundle is incomplete; missing: {', '.join(missing)}") + + files: list[Path] = [] + for path in sorted(root.rglob("*")): + relative = path.relative_to(root) + if any(part in _IGNORED_PARTS for part in relative.parts): + continue + if path.is_symlink(): + raise RuntimeError(f"Candidate bundle contains a symbolic link: {relative}") + if path.is_file(): + files.append(path) + elif not path.is_dir(): + raise RuntimeError(f"Candidate bundle contains a special file: {relative}") + return files + + +class TrustedCandidateAgent(BaseInstalledAgent): + """Fixed adapter for the preview's uv-managed ``python -m main`` candidates.""" + + candidate_dir: ClassVar[Path | None] = None + + @staticmethod + @override + def name() -> str: + return "nemo-experimentalist-candidate" + + @override + def version(self) -> str | None: + return "0.1.0" + + @classmethod + def _candidate_root(cls) -> Path: + if cls.candidate_dir is None: + raise RuntimeError("Trusted candidate adapter has no candidate bundle") + return cls.candidate_dir + + @staticmethod + async def _target_architecture(environment: BaseEnvironment) -> str: + result = await environment.exec("uname -s && uname -m") + if result.return_code != 0: + raise RuntimeError(f"Could not detect task-container platform: {result.stderr or result.stdout}") + lines = (result.stdout or "").splitlines() + if len(lines) != 2 or lines[0].strip() != "Linux": + raise RuntimeError(f"Experimentalist candidate requires a Linux task container, got {lines!r}") + return _normalize_architecture(lines[1]) + + @staticmethod + def _runtime_env() -> dict[str, str]: + return { + "UV_CACHE_DIR": REMOTE_UV_CACHE, + "UV_HTTP_TIMEOUT": "300", + "UV_NO_PROGRESS": "1", + "UV_PROJECT_ENVIRONMENT": REMOTE_VENV, + "UV_PYTHON_INSTALL_DIR": REMOTE_PYTHON_INSTALLS, + "UV_PYTHON_PREFERENCE": "only-managed", + } + + @override + async def install(self, environment: BaseEnvironment) -> None: + """Upload candidate files as data and build the runtime inside the task container.""" + architecture = await self._target_architecture(environment) + uv_binary = _cached_uv_binary(architecture) + candidate_root = self._candidate_root() + candidate_files = _candidate_files(candidate_root) + + await self.exec_as_root( + environment, + command=( + f"mkdir -p {REMOTE_ROOT}/bin {REMOTE_PROJECT} {REMOTE_VENV} " + f"{REMOTE_PYTHON_INSTALLS} {REMOTE_UV_CACHE} && " + f"chmod -R a+rwx {REMOTE_ROOT}" + ), + ) + await environment.upload_file(uv_binary, REMOTE_UV) + for source in candidate_files: + relative = source.relative_to(candidate_root).as_posix() + target = f"{REMOTE_PROJECT}/{relative}" + target_parent = str(Path(target).parent) + await self.exec_as_root(environment, command=f"mkdir -p {shlex.quote(target_parent)}") + await environment.upload_file(source, target) + await self.exec_as_root( + environment, + command=f"chmod 0755 {REMOTE_UV} && chmod -R a+rX {REMOTE_PROJECT}", + ) + await self.exec_as_agent( + environment, + command=( + f"{REMOTE_UV} python install 3.12 && " + f"{REMOTE_UV} sync --project {REMOTE_PROJECT} --frozen --no-dev && " + f"{REMOTE_VENV}/bin/python -m py_compile {REMOTE_PROJECT}/main.py" + ), + env=self._runtime_env(), + timeout_sec=600, + ) + + def _apply_summary(self, context: AgentContext) -> None: + summary_path = self.logs_dir / "summary.json" + try: + summary = json.loads(summary_path.read_text(encoding="utf-8")) + except (OSError, json.JSONDecodeError): + return + if not isinstance(summary, dict): + return + answer = summary.get("answer") + if isinstance(answer, str): + context.metadata = {**(context.metadata or {}), "answer": answer} + usage = summary.get("usage") + if not isinstance(usage, dict): + return + if isinstance(usage.get("input_tokens"), int): + context.n_input_tokens = usage["input_tokens"] + if isinstance(usage.get("output_tokens"), int): + context.n_output_tokens = usage["output_tokens"] + if isinstance(usage.get("cache_read_tokens"), int): + context.n_cache_tokens = usage["cache_read_tokens"] + + @with_prompt_template + @override + async def run( + self, + instruction: str, + environment: BaseEnvironment, + context: AgentContext, + ) -> None: + """Execute only the fixed preview entrypoint inside the Harbor task container.""" + api_key = self._get_env("INFERENCE_API_KEY") + if not api_key: + raise RuntimeError("INFERENCE_API_KEY is required for the Experimentalist candidate") + + prompt_path = self.logs_dir / "instruction.txt" + prompt_path.write_text(instruction, encoding="utf-8") + remote_prompt = f"{REMOTE_ROOT}/instruction.txt" + await environment.upload_file(prompt_path, remote_prompt) + + env = { + "INFERENCE_API_KEY": api_key, + "INFERENCE_API_BASE": self._get_env("INFERENCE_API_BASE") or "https://inference-api.nvidia.com/v1", + "PYTHONPATH": REMOTE_PROJECT, + } + model_name = self.model_name or self._get_env("AUT_MODEL_NAME") + if model_name: + env["EXPERIMENTALIST_MODEL"] = model_name + + command = ( + f"{REMOTE_VENV}/bin/python -m main " + f"--prompt-file {shlex.quote(remote_prompt)} " + "--trace-path /app/traces/trace.jsonl " + "--summary-path /logs/agent/summary.json " + "> /logs/agent/experimentalist-candidate.txt 2>&1; " + "status=$?; " + "cat /logs/agent/experimentalist-candidate.txt; " + "mkdir -p /logs/artifacts/traces && " + "cp -r /app/traces/. /logs/artifacts/traces/ 2>/dev/null || true; " + "exit $status" + ) + try: + result = await self.exec_as_agent( + environment, + command=command, + env=env, + cwd="/app", + ) + context.metadata = { + **(context.metadata or {}), + "stdout": result.stdout, + "stderr": result.stderr, + "returncode": result.return_code, + } + finally: + self._apply_summary(context) + + +@contextlib.contextmanager +def candidate_agent_import(candidate_dir: Path) -> Iterator[str]: + """Register a request-scoped subclass without importing candidate Python.""" + candidate_root = candidate_dir.expanduser().resolve() + _candidate_files(candidate_root) + module_name = f"{__package__}._candidate_{uuid.uuid4().hex}" + module = ModuleType(module_name) + adapter = type( + f"RequestCandidateAgent_{uuid.uuid4().hex}", + (TrustedCandidateAgent,), + {"candidate_dir": candidate_root}, + ) + setattr(module, "RequestCandidateAgent", adapter) + sys.modules[module_name] = module + try: + yield f"{module_name}:RequestCandidateAgent" + finally: + sys.modules.pop(module_name, None) diff --git a/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/openshell/README.md b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/openshell/README.md new file mode 100644 index 0000000000..1476a22ba6 --- /dev/null +++ b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/openshell/README.md @@ -0,0 +1,250 @@ + + + +# Default Experimentalist OpenShell runtime + +`nemo experimentalist run` and `nemo experimentalist doctor` use this runtime +by default. It separates the Experimentalist control plane from Harbor task +execution: + +```text +developer files + | + v +OpenShell sandbox: nmp-experimentalist + - NOOA / Experimentalist agents + - candidate mutation and orchestration + - git, gh, and glab clients + - no Docker CLI + - no Docker socket + | + | authenticated evaluation and dependency-session API + v +local Harbor bridge + - fixed trusted candidate adapter + - host-owned, content-addressed task catalog + - materializes only declared task/verifier overlays + - owns analyzer task environments + - owns Harbor and the host Docker client + | + v +Harbor task containers +``` + +The host CLI resolves each configured Harbor dataset and task template before +OpenShell starts, copies it into a content-addressed run catalog, and gives the +sandbox only its envelope ID and digest. The sandbox cannot register a task, +upload a Dockerfile or Compose topology, or select a container image. Candidate +Python is archived as data and uploaded by fixed bridge code into each +catalog-materialized Harbor task container. + +Insight tasks carry an explicit `nemo-task-envelope.json`. Eval Author may +populate only its typed `task_data` files and may add verifier code only at its +declared `verifier_paths`. Runtime-control files such as Dockerfiles, Compose +files, `.dockerignore`, and `task.toml` are always rejected from overlays. +Rationalizer and TraceAnalyzer start task dependency sessions through the same +bridge and route their shell commands into the bridge-owned task container. +Each session has a separate capability token. The Docker-owning bridge never +imports the candidate's `harbor_wrapper.py`, and analyzer commands never execute +in the bridge host process. + +## Start the local components + +Install the OpenShell CLI and select a running gateway. + +The command needs an Experimentalist container image. It first looks for +`local/nmp-experimentalist:local` with the current runtime compatibility label. +When that image is absent or stale and the command is running from a NeMo +Platform source checkout, the CLI builds it for the host architecture. To +build it ahead of time: + +```bash +export NEMO_EXPERIMENTALIST_PLATFORM=linux/arm64 # use linux/amd64 on x86 hosts +IMAGE_REGISTRY=local BAKE_TAG=local BUILD_ARCH=$NEMO_EXPERIMENTALIST_PLATFORM \ + docker buildx bake nmp-experimentalist-docker --load +``` + +Set `NEMO_EXPERIMENTALIST_IMAGE` to use a published or differently tagged +image. Generate one bridge token and keep it in the shell used for both the +bridge and provider setup: + +```bash +export NEMO_EXPERIMENTALIST_HARBOR_BRIDGE_TOKEN="$(openssl rand -hex 32)" +``` + +The normal CLI prepares the trusted catalog and starts the bridge automatically. +For a bridge-only health check, point the lower-level service at an existing or +empty host-owned catalog: + +```bash +mkdir -p tmp/experimentalist-harbor-catalog +uv run --frozen nemo-experimentalist-harbor-bridge \ + --host 0.0.0.0 \ + --catalog-root tmp/experimentalist-harbor-catalog +``` + +`0.0.0.0` is required for Docker Desktop sandboxes to reach the host through +`host.docker.internal`. The bearer token is required on every evaluation +request; use a host firewall on untrusted networks. There is intentionally no +HTTP endpoint for registering catalog entries. + +In another shell with the same token, configure the provider profiles. The +NVIDIA provider is explicitly configured with +`NVIDIA_BASE_URL=https://inference-api.nvidia.com/v1` and is held by the gateway +behind `inference.local`; its credential is never attached to the sandbox. The +bridge and selected source-control provider expose randomized placeholders in +the sandbox, which OpenShell replaces only in proxied requests: + +```bash +export NVIDIA_API_KEY=nvapi-... +export NEMO_EXPERIMENTALIST_INFERENCE_MODEL=aws/anthropic/claude-haiku-4-5-v1 +export EXPERIMENTALIST_SMART_MODEL_NAME=openai/aws/anthropic/claude-haiku-4-5-v1 +export EXPERIMENTALIST_MID_MODEL_NAME="$EXPERIMENTALIST_SMART_MODEL_NAME" +export EXPERIMENTALIST_FAST_MODEL_NAME="$EXPERIMENTALIST_SMART_MODEL_NAME" + +# Configure either or both source-control credentials. Only one is attached +# to any individual sandbox by run.sh. +export GH_TOKEN="$(gh auth token)" +export GITLAB_TOKEN=glpat-... +# For self-managed GitLab: +export NEMO_EXPERIMENTALIST_GITLAB_HOST=gitlab.example.com + +plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/openshell/configure-providers.sh +``` + +`NEMO_EXPERIMENTALIST_INFERENCE_MODEL` is the raw Inference Hub model ID. +Experimentalist's NOOA model names add the `openai/` transport prefix. When the +explicit inference model is unset, the setup script derives it from the smart +model by removing that prefix. + +The setup script enables the gateway-global OpenShell +`providers_v2_enabled=true` setting. Without it OpenShell injects credential +placeholders but does not compose the provider profiles' endpoint rules into +the sandbox policy. + +`NVIDIA_INTERNAL_API_KEY` is also accepted for the default NVIDIA inference +provider. To use another OpenShell inference profile, set +`NEMO_EXPERIMENTALIST_INFERENCE_PROVIDER_TYPE` and the credential environment +variables that profile discovers. + +Then run the normal Experimentalist commands. Source control is disabled by +default: + +```bash +nemo experimentalist doctor +nemo experimentalist run +``` + +For a GitHub or GitLab agent source, attach one provider with the least +authority the run needs: + +```bash +# HTTPS clone/fetch and API reads +export NEMO_EXPERIMENTALIST_SOURCE_CONTROL=github-read + +# Or allow HTTPS branch push and draft winner PR creation +export NEMO_EXPERIMENTALIST_SOURCE_CONTROL=github-publish + +# GitLab equivalents +export NEMO_EXPERIMENTALIST_SOURCE_CONTROL=gitlab-read +export NEMO_EXPERIMENTALIST_SOURCE_CONTROL=gitlab-publish +``` + +The current profiles support `github.com` and either `gitlab.com` or one exact +self-managed GitLab hostname configured before provider setup and launch. SSH, +Git LFS, and GitHub Enterprise are not included in this research-preview +policy. + +Run the command from a directory that contains every local input passed on the +command line. The launcher rejects existing local paths outside that directory, +uploads the directory into `/sandbox/project`, applies +[`policy.yaml`](policy.yaml), attaches the bridge provider, and runs as the +non-root `sandbox` user. When selected, it also attaches exactly one +source-control provider. `--experiment-dir` remains a host path: the launcher +downloads sandbox artifacts there after the run. The launcher sets +`NEMO_EXPERIMENTALIST_HARBOR_BRIDGE_URL`, which selects the remote evaluator +and makes preflight probe the bridge instead of local Docker. + +OpenShell applies `.gitignore` filtering to uploads inside Git repositories. +The sandbox can read every file that is uploaded, so secrets must remain in +ignored files or in the configured providers rather than tracked workspace +files. + +The packaged `run.sh` is the lower-level launcher used by the CLI. Invoke it +directly only when debugging the OpenShell integration. + +For a release smoke against a workspace with a complete `optimizer.yaml`, run: + +```bash +plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/openshell/smoke-full-run.sh \ + path/to/agent-workspace +``` + +The smoke uses the normal Dockerless OpenShell launcher, requires a complete +optimization round to produce a round-analysis artifact, and fails if the +artifact contains `analysis_error`. Pass normal `nemo experimentalist run` +options after the workspace path when the profile needs overrides. + +Experimentalist itself calls `git` for clone, fetch, checkout, commit, and +push. It calls `gh pr create` for a GitHub winner and `glab mr create` for a +GitLab winner; preflight also calls `gh auth status` or `glab auth status`. +The image therefore includes all three CLIs. `GIT_ASKPASS` supplies provider +placeholders to HTTPS Git without storing a real source-control token in the +container. For GitLab, the launcher writes the placeholder—not the real +token—to `glab`'s per-host config so its auth-status check recognizes the +self-managed host. + +For Docker Desktop, set +`NEMO_EXPERIMENTALIST_POLICY_MODE=docker-desktop`. That uses +[`policy.docker-desktop.yaml`](policy.docker-desktop.yaml), which keeps process +and network enforcement but falls back to best-effort filesystem isolation +because the Docker Desktop kernel does not expose Landlock. + +## Boundary and remaining risk + +The bridge accepts bounded evaluator settings, an AUT candidate archive, +declared task/verifier overlay files, trusted envelope/task IDs, and +authenticated analyzer commands scoped to an active task environment. It +explicitly rejects the former `dataset` and `task` archive fields. Dependency +sessions expose start, capability-bound in-container exec, and stop; they do +not expose Docker commands, image/runtime selection, host paths, service +selection, or host command execution. Harbor's verifier is forced into a +separate container. + +Docker Compose, MCP servers, environment bindings, images, mounts, and +accelerators are permitted only when they already exist in the host-registered +envelope. This is what permits the trusted Tau main-container plus +`tau3-runtime` sidecar without giving the sandbox topology authority. + +The bridge still owns a host-root-equivalent Docker socket. The host-selected +datasets and templates may contain Dockerfiles, and the candidate receives its +model credential inside the Harbor task container. The envelope prevents the +OpenShell agent from changing those inputs; it does not make a malicious +host-selected task or compromised dataset registry safe against Docker/Harbor +escapes, resource exhaustion, or credential exfiltration from that task's own +container. A production worker should additionally enforce organization-owned +registries, digest-pinned images, resource quotas, scoped task networks, and +short-lived inference credentials. + +OpenShell static provider placeholders are currently resolved from a +sandbox-wide map rather than being cryptographically bound to one target +hostname. This launcher never attaches GitHub and GitLab providers together, +so one source-control token cannot be substituted into a request to the other +service. The source-control placeholder can still be sent to the trusted local +bridge endpoint, and the bridge placeholder can be sent to the selected source +host; neither endpoint reflects the resolved Authorization header. Endpoint +binding in OpenShell would make this defense stronger. + +Registry download is not granted by this policy. + +The preview keeps dependency sessions in bridge memory. A bridge restart stops +the sessions and fails the optimization run clearly; there is no durable +reattachment, distributed scheduling, or multi-bridge routing yet. +Only Docker-backed Harbor task dependencies with `delete=true` and no custom +start, readiness, or stop commands are supported. Other dependency runtime +forms fail before analysis begins. The existing force-build, health-check, and +build-timeout behavior is preserved across the bridge. + +The host CLI has no direct-execution option. Experimentalist's in-process +command path is enabled only inside the marked container image used by the +OpenShell launcher. diff --git a/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/openshell/configure-providers.sh b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/openshell/configure-providers.sh new file mode 100755 index 0000000000..1f473f7d76 --- /dev/null +++ b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/openshell/configure-providers.sh @@ -0,0 +1,173 @@ +#!/usr/bin/env bash +# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 + +set -euo pipefail + +if ! command -v openshell >/dev/null 2>&1; then + echo "openshell CLI is required: https://docs.nvidia.com/openshell/latest/get-started/quickstart" >&2 + exit 127 +fi + +script_dir="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" +profile_template_dir="$script_dir/provider-profiles" +profile_dir="${NEMO_EXPERIMENTALIST_PROVIDER_PROFILE_DIR:-$PWD/tmp/experimentalist-openshell-provider-profiles}" +bridge_provider="${NEMO_EXPERIMENTALIST_HARBOR_BRIDGE_PROVIDER:-nemo-experimentalist-harbor-bridge}" +inference_provider="${NEMO_EXPERIMENTALIST_INFERENCE_PROVIDER:-nemo-experimentalist-inference}" +inference_provider_type="${NEMO_EXPERIMENTALIST_INFERENCE_PROVIDER_TYPE:-nvidia}" +inference_model="${NEMO_EXPERIMENTALIST_INFERENCE_MODEL:-}" +if [[ -z "$inference_model" && -n "${EXPERIMENTALIST_SMART_MODEL_NAME:-}" ]]; then + # NOOA prefixes OpenAI-compatible transports with "openai/"; OpenShell needs + # the provider's raw model ID when configuring inference.local. + inference_model="${EXPERIMENTALIST_SMART_MODEL_NAME#openai/}" +fi +gitlab_host="${NEMO_EXPERIMENTALIST_GITLAB_HOST:-${GITLAB_HOST:-gitlab.com}}" + +if [[ "$inference_provider_type" == "nvidia" && -z "${NVIDIA_API_KEY:-}" && -n "${NVIDIA_INTERNAL_API_KEY:-}" ]]; then + export NVIDIA_API_KEY="$NVIDIA_INTERNAL_API_KEY" +fi + +if [[ -z "${NEMO_EXPERIMENTALIST_HARBOR_BRIDGE_TOKEN:-}" ]]; then + echo "NEMO_EXPERIMENTALIST_HARBOR_BRIDGE_TOKEN is required" >&2 + exit 2 +fi + +if [[ ! "$gitlab_host" =~ ^[A-Za-z0-9]([A-Za-z0-9.-]*[A-Za-z0-9])?$ ]]; then + echo "invalid GitLab hostname: $gitlab_host" >&2 + exit 2 +fi + +mkdir -p "$profile_dir" +for profile_path in "$profile_template_dir"/*.yaml; do + sed "s/host: gitlab\\.com/host: $gitlab_host/g" "$profile_path" >"$profile_dir/$(basename "$profile_path")" +done + +delete_provider_if_present() { + local provider_name="$1" + + # These names are dedicated to this runtime. Recreating them makes profile + # changes deterministic and migrates the earlier generic bridge provider. + if openshell provider get "$provider_name" >/dev/null 2>&1; then + openshell provider delete "$provider_name" + fi +} + +delete_profile_if_present() { + local profile_name="$1" + local profile_yaml + local profile_scope + + if ! profile_yaml="$(openshell provider profile export "$profile_name" 2>/dev/null)"; then + return + fi + + profile_scope="$(awk '$1 == "scope:" { print $2; exit }' <<<"$profile_yaml")" + if [[ "$profile_scope" == "platform" ]]; then + openshell provider profile delete --global "$profile_name" + else + openshell provider profile delete "$profile_name" + fi +} + +replace_provider_from_existing() { + local provider_name="$1" + local provider_type="$2" + shift 2 + + delete_provider_if_present "$provider_name" + openshell provider create --name "$provider_name" --type "$provider_type" --from-existing "$@" +} + +replace_provider_with_credential() { + local provider_name="$1" + local provider_type="$2" + local credential_env="$3" + + delete_provider_if_present "$provider_name" + + # Custom profiles are not part of the legacy gateway's built-in credential + # discovery. The key-only form reads the value from the environment, keeping + # it out of command arguments. + openshell provider create \ + --name "$provider_name" \ + --type "$provider_type" \ + --credential "$credential_env" +} + +for provider_name in \ + "$bridge_provider" \ + nemo-experimentalist-github-read \ + nemo-experimentalist-github-publish \ + nemo-experimentalist-gitlab-read \ + nemo-experimentalist-gitlab-publish; do + delete_provider_if_present "$provider_name" +done + +for profile_path in "$profile_dir"/*.yaml; do + profile_id="$(basename "$profile_path" .yaml)" + delete_profile_if_present "$profile_id" +done + +# Provider credentials are injected without this gate, but provider endpoint +# policies are composed into sandbox policy only when providers v2 is enabled. +openshell settings set \ + --global \ + --key providers_v2_enabled \ + --value true \ + --yes + +openshell provider profile lint --from "$profile_dir" +openshell provider profile import --from "$profile_dir" + +replace_provider_with_credential \ + "$bridge_provider" \ + nemo-experimentalist-harbor-bridge \ + NEMO_EXPERIMENTALIST_HARBOR_BRIDGE_TOKEN + +if [[ -n "$inference_model" ]]; then + if [[ "$inference_provider_type" == "nvidia" ]]; then + replace_provider_from_existing \ + "$inference_provider" \ + "$inference_provider_type" \ + --config NVIDIA_BASE_URL=https://inference-api.nvidia.com/v1 + else + replace_provider_from_existing "$inference_provider" "$inference_provider_type" + fi + openshell inference set --provider "$inference_provider" --model "$inference_model" + echo "Configured inference.local with provider '$inference_provider' and model '$inference_model'." +else + echo "Inference route unchanged. Set NEMO_EXPERIMENTALIST_INFERENCE_MODEL to configure inference.local." +fi + +if [[ -n "${GH_TOKEN:-${GITHUB_TOKEN:-}}" ]]; then + if [[ -n "${GH_TOKEN:-}" ]]; then + github_credential_env=GH_TOKEN + else + github_credential_env=GITHUB_TOKEN + fi + replace_provider_with_credential \ + nemo-experimentalist-github-read \ + nemo-experimentalist-github-read \ + "$github_credential_env" + replace_provider_with_credential \ + nemo-experimentalist-github-publish \ + nemo-experimentalist-github-publish \ + "$github_credential_env" + echo "Configured GitHub read and publish providers." +else + echo "GitHub providers skipped. Export GH_TOKEN or GITHUB_TOKEN to configure them." +fi + +if [[ -n "${GITLAB_TOKEN:-}" ]]; then + replace_provider_with_credential \ + nemo-experimentalist-gitlab-read \ + nemo-experimentalist-gitlab-read \ + GITLAB_TOKEN + replace_provider_with_credential \ + nemo-experimentalist-gitlab-publish \ + nemo-experimentalist-gitlab-publish \ + GITLAB_TOKEN + echo "Configured GitLab read and publish providers." +else + echo "GitLab providers skipped. Export GITLAB_TOKEN to configure them." +fi diff --git a/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/openshell/git-askpass.sh b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/openshell/git-askpass.sh new file mode 100755 index 0000000000..ca293cbc70 --- /dev/null +++ b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/openshell/git-askpass.sh @@ -0,0 +1,31 @@ +#!/usr/bin/env bash +# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 + +set -euo pipefail + +prompt="${1:-}" +lower_prompt="${prompt,,}" +gitlab_host="${GITLAB_HOST:-gitlab.com}" +lower_gitlab_host="${gitlab_host,,}" + +if [[ "$lower_prompt" == *username*github.com* ]]; then + printf '%s\n' "x-access-token" +elif [[ "$lower_prompt" == *password*github.com* ]]; then + if [[ -z "${GH_TOKEN:-${GITHUB_TOKEN:-}}" ]]; then + echo "GitHub provider placeholder is unavailable" >&2 + exit 1 + fi + printf '%s\n' "${GH_TOKEN:-${GITHUB_TOKEN}}" +elif [[ "$lower_prompt" == *username*"$lower_gitlab_host"* ]]; then + printf '%s\n' "oauth2" +elif [[ "$lower_prompt" == *password*"$lower_gitlab_host"* ]]; then + if [[ -z "${GITLAB_TOKEN:-}" ]]; then + echo "GitLab provider placeholder is unavailable" >&2 + exit 1 + fi + printf '%s\n' "$GITLAB_TOKEN" +else + echo "unsupported Git credential prompt: $prompt" >&2 + exit 1 +fi diff --git a/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/openshell/launcher.py b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/openshell/launcher.py new file mode 100644 index 0000000000..51f5a5c5e7 --- /dev/null +++ b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/openshell/launcher.py @@ -0,0 +1,339 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 + +"""Host-side launcher for the default Experimentalist OpenShell runtime.""" + +from __future__ import annotations + +import os +import platform +import secrets +import shutil +import subprocess +import sys +import time +from collections.abc import Mapping +from dataclasses import dataclass +from pathlib import Path +from typing import BinaryIO, Literal +from urllib.parse import urlsplit, urlunsplit + +import httpx +from nemo_experimentalist_plugin.harbor_bridge.envelopes import HARBOR_ENVELOPE_CATALOG_ENV + +DEFAULT_IMAGE = "local/nmp-experimentalist:local" +IMAGE_ENV = "NEMO_EXPERIMENTALIST_IMAGE" +PLATFORM_ENV = "NEMO_EXPERIMENTALIST_PLATFORM" +OUTPUT_DIR_ENV = "NEMO_EXPERIMENTALIST_OUTPUT_DIR" +RUNTIME_IMAGE_LABEL = "com.nvidia.nemo.experimentalist.openshell-runtime" +RUNTIME_IMAGE_API = "1" +BRIDGE_TOKEN_ENV = "NEMO_EXPERIMENTALIST_HARBOR_BRIDGE_TOKEN" +BRIDGE_URL_ENV = "NEMO_EXPERIMENTALIST_HARBOR_BRIDGE_URL" +DEFAULT_BRIDGE_HOST_URL = "http://127.0.0.1:8765" +DEFAULT_BRIDGE_CONTAINER_URL = "http://host.docker.internal:8765" +DEFAULT_SMART_MODEL = "openai/openai/openai/gpt-5.5" + + +class OpenShellLaunchError(RuntimeError): + """Raised when the fail-closed OpenShell launch cannot be prepared.""" + + +@dataclass +class _ManagedBridge: + process: subprocess.Popen[bytes] + log_path: Path + log_handle: BinaryIO + + def stop(self) -> None: + """Stop only the bridge process created for this launch.""" + if self.process.poll() is None: + self.process.terminate() + try: + self.process.wait(timeout=10) + except subprocess.TimeoutExpired: + self.process.kill() + self.process.wait(timeout=5) + self.log_handle.close() + + +def _find_repo_root(*starts: Path) -> Path | None: + for start in starts: + for candidate in (start, *start.parents): + if (candidate / "docker-bake.hcl").is_file() and ( + candidate / "plugins" / "nemo-experimentalist" / "Dockerfile" + ).is_file(): + return candidate + return None + + +def _host_platform(machine: str | None = None) -> str: + normalized = (machine or platform.machine()).strip().lower() + if normalized in {"aarch64", "arm64"}: + return "linux/arm64" + if normalized in {"amd64", "x86_64"}: + return "linux/amd64" + raise OpenShellLaunchError( + f"Unsupported host architecture {normalized!r}; set {PLATFORM_ENV} to linux/arm64 or linux/amd64" + ) + + +def _container_platform_url(value: str) -> str: + """Rewrite a host loopback URL for a Docker-backed OpenShell sandbox.""" + try: + parsed = urlsplit(value) + port = parsed.port + except ValueError as exc: + raise OpenShellLaunchError(f"Invalid NeMo Platform URL: {value}") from exc + if parsed.hostname not in {"localhost", "127.0.0.1", "::1"}: + return value + if parsed.username is not None or parsed.password is not None: + raise OpenShellLaunchError("NeMo Platform URL must not contain user information") + port_suffix = f":{port}" if port is not None else "" + return urlunsplit((parsed.scheme, f"host.docker.internal{port_suffix}", parsed.path, parsed.query, parsed.fragment)) + + +def _acquire_default_image( + *, + docker: str, + image: str, + workspace_dir: Path, + runtime_env: dict[str, str], +) -> None: + inspected = subprocess.run( # noqa: S603 + [ + docker, + "image", + "inspect", + "--format", + f'{{{{ index .Config.Labels "{RUNTIME_IMAGE_LABEL}" }}}}', + image, + ], + check=False, + stdout=subprocess.PIPE, + text=True, + stderr=subprocess.DEVNULL, + ) + if inspected.returncode == 0 and inspected.stdout.strip() == RUNTIME_IMAGE_API: + return + + repo_root = _find_repo_root(workspace_dir, Path(__file__).resolve()) + if repo_root is None: + raise OpenShellLaunchError( + f"A compatible Experimentalist image {image!r} is not available locally. " + f"Set {IMAGE_ENV} to a published image, or run from a nemo-platform source checkout " + "so the CLI can build it." + ) + + selected_platform = runtime_env.get(PLATFORM_ENV, "").strip() or _host_platform() + if selected_platform not in {"linux/arm64", "linux/amd64"}: + raise OpenShellLaunchError(f"{PLATFORM_ENV} must be linux/arm64 or linux/amd64") + build_env = { + **runtime_env, + "IMAGE_REGISTRY": "local", + "BAKE_TAG": "local", + "BUILD_ARCH": selected_platform, + } + built = subprocess.run( # noqa: S603 + [docker, "buildx", "bake", "nmp-experimentalist-docker", "--load"], + cwd=repo_root, + env=build_env, + check=False, + ) + if built.returncode != 0: + raise OpenShellLaunchError( + f"Could not build {image!r} for {selected_platform}; set {IMAGE_ENV} to a usable published or local image" + ) + + +def _bridge_ready(url: str) -> bool: + try: + return httpx.get(f"{url.rstrip('/')}/health/ready", timeout=1.0).status_code == 200 + except httpx.HTTPError: + return False + + +def _host_bridge_url(value: str) -> str: + """Translate the Docker host alias back to loopback for host-side probes.""" + parsed = urlsplit(value) + if parsed.hostname != "host.docker.internal": + return value + port_suffix = f":{parsed.port}" if parsed.port is not None else "" + return urlunsplit( + ( + parsed.scheme, + f"127.0.0.1{port_suffix}", + parsed.path, + parsed.query, + parsed.fragment, + ) + ) + + +def _start_bridge( + *, + workspace: Path, + runtime_env: dict[str, str], +) -> _ManagedBridge | None: + """Reuse an explicitly configured bridge or start an ephemeral local one.""" + configured_url = runtime_env.get(BRIDGE_URL_ENV, "").strip() + token = runtime_env.get(BRIDGE_TOKEN_ENV, "").strip() + host_url = _host_bridge_url(configured_url) if configured_url else DEFAULT_BRIDGE_HOST_URL + if configured_url: + if not token: + raise OpenShellLaunchError(f"{BRIDGE_TOKEN_ENV} is required with an explicit {BRIDGE_URL_ENV}") + if not _bridge_ready(host_url): + raise OpenShellLaunchError(f"Configured Harbor bridge is not ready: {host_url}") + return None + if _bridge_ready(host_url): + if not token: + raise OpenShellLaunchError( + f"A Harbor bridge is already listening at {host_url}, but {BRIDGE_TOKEN_ENV} " + "is not set. Stop it or export its token." + ) + runtime_env[BRIDGE_URL_ENV] = DEFAULT_BRIDGE_CONTAINER_URL + return None + + token = token or secrets.token_urlsafe(32) + runtime_env[BRIDGE_TOKEN_ENV] = token + runtime_env[BRIDGE_URL_ENV] = DEFAULT_BRIDGE_CONTAINER_URL + runtime_root = workspace / "tmp" / "experimentalist-openshell" + storage_root = runtime_root / "bridge" + runtime_root.mkdir(parents=True, exist_ok=True) + catalog_value = runtime_env.get(HARBOR_ENVELOPE_CATALOG_ENV, "").strip() + catalog_root = Path(catalog_value).expanduser().resolve() if catalog_value else runtime_root / "empty-catalog" + catalog_root.mkdir(parents=True, exist_ok=True) + log_path = runtime_root / "bridge.log" + log_handle = log_path.open("ab") + process = subprocess.Popen( # noqa: S603 + [ + sys.executable, + "-m", + "nemo_experimentalist_plugin.harbor_bridge.service", + "--host", + "0.0.0.0", + "--port", + "8765", + "--storage-root", + str(storage_root), + "--catalog-root", + str(catalog_root), + ], + cwd=workspace, + env=runtime_env, + stdout=log_handle, + stderr=subprocess.STDOUT, + ) + managed = _ManagedBridge(process=process, log_path=log_path, log_handle=log_handle) + deadline = time.monotonic() + 20 + while time.monotonic() < deadline: + if process.poll() is not None: + managed.stop() + detail = log_path.read_text(encoding="utf-8", errors="replace").strip() + raise OpenShellLaunchError( + "The Experimentalist Harbor bridge exited before becoming ready" + (f": {detail}" if detail else "") + ) + if _bridge_ready(host_url): + return managed + time.sleep(0.2) + managed.stop() + raise OpenShellLaunchError(f"The Experimentalist Harbor bridge did not become ready at {host_url}; see {log_path}") + + +def _configure_providers(runtime_env: dict[str, str]) -> None: + """Create the dedicated OpenShell providers used by this runtime.""" + source_control = runtime_env.get("NEMO_EXPERIMENTALIST_SOURCE_CONTROL", "none") + if source_control.startswith("gitlab-") and not runtime_env.get("GITLAB_TOKEN"): + raise OpenShellLaunchError( + "This profile uses a GitLab dataset registry. Add GITLAB_TOKEN to the " + "profile's ignored .env file, then rerun the command." + ) + if source_control.startswith("github-") and not (runtime_env.get("GH_TOKEN") or runtime_env.get("GITHUB_TOKEN")): + raise OpenShellLaunchError( + "This profile uses a GitHub dataset registry. Add GH_TOKEN to the " + "profile's ignored .env file, then rerun the command." + ) + script_path = Path(__file__).with_name("configure-providers.sh") + if not script_path.is_file(): + raise OpenShellLaunchError(f"Packaged provider setup is missing: {script_path}") + completed = subprocess.run( # noqa: S603 + [str(script_path)], + env=runtime_env, + check=False, + ) + if completed.returncode != 0: + raise OpenShellLaunchError( + "Could not configure the Experimentalist OpenShell providers. " + "Check inference and source-control credentials above." + ) + + +def _apply_runtime_defaults(runtime_env: dict[str, str]) -> None: + """Fill safe, process-local defaults needed by the one-command launcher.""" + runtime_env.setdefault("EXPERIMENTALIST_SMART_MODEL_NAME", DEFAULT_SMART_MODEL) + if not runtime_env.get("NVIDIA_API_KEY") and runtime_env.get("INFERENCE_API_KEY"): + runtime_env["NVIDIA_API_KEY"] = runtime_env["INFERENCE_API_KEY"] + if platform.system() == "Darwin": + runtime_env.setdefault("NEMO_EXPERIMENTALIST_POLICY_MODE", "docker-desktop") + + +def launch_in_openshell( + command: Literal["run", "doctor"], + forwarded_args: list[str], + *, + workspace_dir: Path, + output_dir: Path | None = None, + platform_url: str | None = None, + env: Mapping[str, str] | None = None, +) -> int: + """Launch one Experimentalist command inside OpenShell without local fallback.""" + workspace = workspace_dir.expanduser().resolve() + if not workspace.is_dir(): + raise OpenShellLaunchError(f"OpenShell workspace directory not found: {workspace}") + if not workspace.name: + raise OpenShellLaunchError("The filesystem root cannot be used as an OpenShell workspace") + + runtime_env = dict(os.environ if env is None else env) + openshell = shutil.which("openshell", path=runtime_env.get("PATH")) + if openshell is None: + raise OpenShellLaunchError( + "OpenShell is the default Experimentalist runtime but its CLI is not on PATH. " + "Install and configure OpenShell before running Experimentalist." + ) + + image = runtime_env.get(IMAGE_ENV, "").strip() or DEFAULT_IMAGE + runtime_env[IMAGE_ENV] = image + if image == DEFAULT_IMAGE: + docker = shutil.which("docker", path=runtime_env.get("PATH")) + if docker is None: + raise OpenShellLaunchError( + f"Default image {image!r} requires Docker for local image discovery/build. " + f"Set {IMAGE_ENV} to an image available to the OpenShell gateway." + ) + _acquire_default_image( + docker=docker, + image=image, + workspace_dir=workspace, + runtime_env=runtime_env, + ) + + if output_dir is not None: + runtime_env[OUTPUT_DIR_ENV] = str(output_dir.expanduser().resolve()) + if platform_url: + runtime_env["NMP_BASE_URL"] = _container_platform_url(platform_url) + + script_path = Path(__file__).with_name("run.sh") + if not script_path.is_file(): + raise OpenShellLaunchError(f"Packaged OpenShell launcher is missing: {script_path}") + _apply_runtime_defaults(runtime_env) + managed_bridge = _start_bridge(workspace=workspace, runtime_env=runtime_env) + try: + _configure_providers(runtime_env) + completed = subprocess.run( # noqa: S603 + [str(script_path), str(workspace), command, *forwarded_args], + env=runtime_env, + check=False, + ) + return completed.returncode + finally: + if managed_bridge is not None: + managed_bridge.stop() diff --git a/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/openshell/policy.docker-desktop.yaml b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/openshell/policy.docker-desktop.yaml new file mode 100644 index 0000000000..cbcc46f13e --- /dev/null +++ b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/openshell/policy.docker-desktop.yaml @@ -0,0 +1,62 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 + +# Explicit local-development fallback for Docker Desktop kernels that do not +# expose Landlock. Process, seccomp, and network controls remain active, but +# filesystem access is not kernel-enforced when Landlock is unavailable. +version: 1 + +filesystem_policy: + include_workdir: true + read_only: + - /app + - /bin + - /dev/urandom + - /etc + - /lib + - /opt + - /proc + - /usr + - /var/log + read_write: + - /dev/null + - /dev/shm + - /home/sandbox + - /sandbox + - /tmp + +landlock: + compatibility: best_effort + +process: + run_as_user: sandbox + run_as_group: sandbox + +network_policies: + nemo_platform: + name: nemo-platform + endpoints: + - host: host.docker.internal + port: 8080 + protocol: rest + enforcement: enforce + rules: + - allow: + method: GET + path: /health/ready + - allow: + method: GET + path: /apis/intake/v2/workspaces/** + - allow: + method: POST + path: /apis/intake/v2/workspaces/** + - allow: + method: PUT + path: /apis/intake/v2/workspaces/** + - allow: + method: GET + path: /apis/insights/v2/workspaces/** + binaries: + - path: /app/.venv/bin/python + - path: /app/.venv/bin/python3.13 + - path: /usr/local/bin/python3.13 diff --git a/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/openshell/policy.yaml b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/openshell/policy.yaml new file mode 100644 index 0000000000..29b8ceb75f --- /dev/null +++ b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/openshell/policy.yaml @@ -0,0 +1,67 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 + +# Fail-closed policy for the Experimentalist control plane. Harbor evaluation +# does not run here, so neither the Docker socket nor a Docker daemon endpoint +# is allowed. +version: 1 + +filesystem_policy: + include_workdir: true + read_only: + - /app + - /bin + - /dev/urandom + - /etc + - /lib + - /opt + - /proc + - /usr + - /var/log + read_write: + - /dev/null + - /dev/shm + - /home/sandbox + - /sandbox + - /tmp + +landlock: + compatibility: hard_requirement + +process: + run_as_user: sandbox + run_as_group: sandbox + +# Model calls use the gateway-managed inference.local route. Direct Platform +# access is limited to readiness plus the Intake/Insights APIs used to load the +# selected traces and mirror optimization results. Provider profiles add the +# selected Harbor bridge and source-control endpoints; the sandbox never +# receives Docker API access. +network_policies: + nemo_platform: + name: nemo-platform + endpoints: + - host: host.docker.internal + port: 8080 + protocol: rest + enforcement: enforce + rules: + - allow: + method: GET + path: /health/ready + - allow: + method: GET + path: /apis/intake/v2/workspaces/** + - allow: + method: POST + path: /apis/intake/v2/workspaces/** + - allow: + method: PUT + path: /apis/intake/v2/workspaces/** + - allow: + method: GET + path: /apis/insights/v2/workspaces/** + binaries: + - path: /app/.venv/bin/python + - path: /app/.venv/bin/python3.13 + - path: /usr/local/bin/python3.13 diff --git a/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/openshell/provider-profiles/nemo-experimentalist-github-publish.yaml b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/openshell/provider-profiles/nemo-experimentalist-github-publish.yaml new file mode 100644 index 0000000000..80e668b186 --- /dev/null +++ b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/openshell/provider-profiles/nemo-experimentalist-github-publish.yaml @@ -0,0 +1,59 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 + +id: nemo-experimentalist-github-publish +display_name: NeMo Experimentalist GitHub publish +description: GitHub HTTPS clone/fetch, branch push, and winner pull-request creation +category: source_control +credentials: + - name: api_token + description: GitHub token + env_vars: [GH_TOKEN, GITHUB_TOKEN] + required: true + auth_style: bearer + header_name: authorization +discovery: + credentials: [api_token] +endpoints: + - host: api.github.com + port: 443 + protocol: rest + enforcement: enforce + rules: + - allow: + method: GET + path: /** + - allow: + method: HEAD + path: /** + - host: api.github.com + port: 443 + path: /graphql + protocol: graphql + enforcement: enforce + rules: + - allow: + operation_type: query + - allow: + operation_type: mutation + operation_name: PullRequestCreate* + - host: github.com + port: 443 + protocol: rest + enforcement: enforce + rules: + - allow: + method: GET + path: /** + - allow: + method: HEAD + path: /** + - allow: + method: POST + path: /**/git-upload-pack + - allow: + method: POST + path: /**/git-receive-pack +binaries: + - /usr/bin/git + - /usr/bin/gh diff --git a/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/openshell/provider-profiles/nemo-experimentalist-github-read.yaml b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/openshell/provider-profiles/nemo-experimentalist-github-read.yaml new file mode 100644 index 0000000000..27cf7b22bd --- /dev/null +++ b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/openshell/provider-profiles/nemo-experimentalist-github-read.yaml @@ -0,0 +1,53 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 + +id: nemo-experimentalist-github-read +display_name: NeMo Experimentalist GitHub read +description: GitHub HTTPS clone/fetch and read-only API access +category: source_control +credentials: + - name: api_token + description: GitHub token + env_vars: [GH_TOKEN, GITHUB_TOKEN] + required: true + auth_style: bearer + header_name: authorization +discovery: + credentials: [api_token] +endpoints: + - host: api.github.com + port: 443 + protocol: rest + enforcement: enforce + rules: + - allow: + method: GET + path: /** + - allow: + method: HEAD + path: /** + - host: api.github.com + port: 443 + path: /graphql + protocol: graphql + enforcement: enforce + rules: + - allow: + operation_type: query + - host: github.com + port: 443 + protocol: rest + enforcement: enforce + rules: + - allow: + method: GET + path: /** + - allow: + method: HEAD + path: /** + - allow: + method: POST + path: /**/git-upload-pack +binaries: + - /usr/bin/git + - /usr/bin/gh diff --git a/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/openshell/provider-profiles/nemo-experimentalist-gitlab-publish.yaml b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/openshell/provider-profiles/nemo-experimentalist-gitlab-publish.yaml new file mode 100644 index 0000000000..28db5dc9fd --- /dev/null +++ b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/openshell/provider-profiles/nemo-experimentalist-gitlab-publish.yaml @@ -0,0 +1,41 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 + +id: nemo-experimentalist-gitlab-publish +display_name: NeMo Experimentalist GitLab publish +description: GitLab HTTPS clone/fetch, branch push, and winner merge-request creation +category: source_control +credentials: + - name: api_token + description: GitLab token + env_vars: [GITLAB_TOKEN] + required: true + auth_style: bearer + header_name: authorization +discovery: + credentials: [api_token] +endpoints: + - host: gitlab.com + port: 443 + protocol: rest + enforcement: enforce + allow_encoded_slash: true + rules: + - allow: + method: GET + path: /** + - allow: + method: HEAD + path: /** + - allow: + method: POST + path: /**/git-upload-pack + - allow: + method: POST + path: /**/git-receive-pack + - allow: + method: POST + path: /api/v4/projects/**/merge_requests +binaries: + - /usr/bin/git + - /usr/bin/glab diff --git a/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/openshell/provider-profiles/nemo-experimentalist-gitlab-read.yaml b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/openshell/provider-profiles/nemo-experimentalist-gitlab-read.yaml new file mode 100644 index 0000000000..d54f27951b --- /dev/null +++ b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/openshell/provider-profiles/nemo-experimentalist-gitlab-read.yaml @@ -0,0 +1,35 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 + +id: nemo-experimentalist-gitlab-read +display_name: NeMo Experimentalist GitLab read +description: GitLab HTTPS clone/fetch and read-only API access +category: source_control +credentials: + - name: api_token + description: GitLab token + env_vars: [GITLAB_TOKEN] + required: true + auth_style: bearer + header_name: authorization +discovery: + credentials: [api_token] +endpoints: + - host: gitlab.com + port: 443 + protocol: rest + enforcement: enforce + allow_encoded_slash: true + rules: + - allow: + method: GET + path: /** + - allow: + method: HEAD + path: /** + - allow: + method: POST + path: /**/git-upload-pack +binaries: + - /usr/bin/git + - /usr/bin/glab diff --git a/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/openshell/provider-profiles/nemo-experimentalist-harbor-bridge.yaml b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/openshell/provider-profiles/nemo-experimentalist-harbor-bridge.yaml new file mode 100644 index 0000000000..6bb4f00f6d --- /dev/null +++ b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/openshell/provider-profiles/nemo-experimentalist-harbor-bridge.yaml @@ -0,0 +1,41 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 + +id: nemo-experimentalist-harbor-bridge +display_name: NeMo Experimentalist Harbor bridge +description: Authenticated access to local Harbor evaluation and task dependency sessions +category: other +credentials: + - name: bridge_token + description: Ephemeral bearer token shared with the local Harbor bridge + env_vars: [NEMO_EXPERIMENTALIST_HARBOR_BRIDGE_TOKEN] + required: true + auth_style: bearer + header_name: authorization +discovery: + credentials: [bridge_token] +endpoints: + - host: host.docker.internal + port: 8765 + protocol: rest + enforcement: enforce + rules: + - allow: + method: GET + path: /health/ready + - allow: + method: POST + path: /v1/evaluations + - allow: + method: POST + path: /v1/dependencies + - allow: + method: POST + path: /v1/dependencies/*/exec + - allow: + method: DELETE + path: /v1/dependencies/* +binaries: + - /app/.venv/bin/python + - /app/.venv/bin/python3.13 + - /usr/local/bin/python3.13 diff --git a/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/openshell/run.sh b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/openshell/run.sh new file mode 100755 index 0000000000..647ac3a921 --- /dev/null +++ b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/openshell/run.sh @@ -0,0 +1,176 @@ +#!/usr/bin/env bash +# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 + +set -euo pipefail + +usage() { + echo "usage: $0 WORKSPACE_DIR {doctor|run} [experimentalist options...]" >&2 +} + +if [[ $# -lt 2 ]]; then + usage + exit 2 +fi + +workspace_dir="$(cd "$1" && pwd)" +remote_workspace="/sandbox/project/$(basename "$workspace_dir")" +subcommand="$2" +shift 2 + +if [[ "$subcommand" != "doctor" && "$subcommand" != "run" ]]; then + usage + exit 2 +fi + +if ! command -v openshell >/dev/null 2>&1; then + echo "openshell CLI is required: https://docs.nvidia.com/openshell/latest/get-started/quickstart" >&2 + exit 127 +fi + +script_dir="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" +image="${NEMO_EXPERIMENTALIST_IMAGE:-local/nmp-experimentalist:local}" +sandbox_name="${NEMO_EXPERIMENTALIST_SANDBOX_NAME:-nemo-exp-$$}" +platform_url="${NMP_BASE_URL:-http://host.docker.internal:8080}" +bridge_url="${NEMO_EXPERIMENTALIST_HARBOR_BRIDGE_URL:-http://host.docker.internal:8765}" +bridge_provider="${NEMO_EXPERIMENTALIST_HARBOR_BRIDGE_PROVIDER:-nemo-experimentalist-harbor-bridge}" +envelope_catalog="${NEMO_EXPERIMENTALIST_HARBOR_ENVELOPE_CATALOG:-}" +source_control="${NEMO_EXPERIMENTALIST_SOURCE_CONTROL:-none}" +gitlab_host="${NEMO_EXPERIMENTALIST_GITLAB_HOST:-${GITLAB_HOST:-gitlab.com}}" +output_dir="${NEMO_EXPERIMENTALIST_OUTPUT_DIR:-$workspace_dir/tmp/experimentalist-openshell}" +policy_mode="${NEMO_EXPERIMENTALIST_POLICY_MODE:-strict}" +git_author_name="${NEMO_EXPERIMENTALIST_GIT_AUTHOR_NAME:-NeMo Experimentalist}" +git_author_email="${NEMO_EXPERIMENTALIST_GIT_AUTHOR_EMAIL:-nemo-experimentalist@localhost}" + +if (( ${#sandbox_name} > 19 )); then + echo "OpenShell sandbox names are limited to 19 characters: $sandbox_name" >&2 + exit 2 +fi + +case "$policy_mode" in + strict) + policy_path="$script_dir/policy.yaml" + ;; + docker-desktop) + policy_path="$script_dir/policy.docker-desktop.yaml" + echo "WARNING: Docker Desktop mode continues without Landlock filesystem enforcement." >&2 + ;; + *) + echo "NEMO_EXPERIMENTALIST_POLICY_MODE must be 'strict' or 'docker-desktop'" >&2 + exit 2 + ;; +esac + +case "$source_control" in + none) + source_provider="" + ;; + github-read | github-publish | gitlab-read | gitlab-publish) + source_provider="${NEMO_EXPERIMENTALIST_SOURCE_PROVIDER:-nemo-experimentalist-$source_control}" + ;; + *) + echo "NEMO_EXPERIMENTALIST_SOURCE_CONTROL must be one of: none, github-read, github-publish, gitlab-read, gitlab-publish" >&2 + exit 2 + ;; +esac + +cleanup() { + if [[ "${NEMO_EXPERIMENTALIST_KEEP_SANDBOX:-0}" != "1" ]]; then + openshell sandbox delete "$sandbox_name" >/dev/null 2>&1 || true + fi +} +trap cleanup EXIT + +create_args=( + sandbox create + --name "$sandbox_name" + --from "$image" + --policy "$policy_path" + --no-auto-providers + --provider "$bridge_provider" + --upload "$workspace_dir:/sandbox/project" + --env "NMP_BASE_URL=$platform_url" + --env "NEMO_EXPERIMENTALIST_HARBOR_BRIDGE_URL=$bridge_url" + --env "EXPERIMENTALIST_API_BASE=https://inference.local/v1" + --env "EXPERIMENTALIST_API_KEY=not-used" + --env "GIT_ASKPASS=/usr/local/bin/nemo-experimentalist-git-askpass" + --env "GIT_TERMINAL_PROMPT=0" + --env "GH_PROMPT_DISABLED=1" + --env "GLAB_NO_PROMPT=1" + --env "GIT_AUTHOR_NAME=$git_author_name" + --env "GIT_AUTHOR_EMAIL=$git_author_email" + --env "GIT_COMMITTER_NAME=$git_author_name" + --env "GIT_COMMITTER_EMAIL=$git_author_email" +) + +if [[ -n "$envelope_catalog" ]]; then + envelope_catalog="$(cd "$envelope_catalog" && pwd)" + case "$envelope_catalog" in + "$workspace_dir"/*) + catalog_relative="${envelope_catalog#"$workspace_dir"/}" + create_args+=(--upload "$envelope_catalog:$remote_workspace/$catalog_relative") + ;; + *) + echo "Trusted Harbor envelope catalog must be inside the uploaded workspace: $envelope_catalog" >&2 + exit 2 + ;; + esac +fi + +if [[ -n "$source_provider" ]]; then + create_args+=(--provider "$source_provider") +fi + +if [[ "$source_control" == gitlab-* ]]; then + create_args+=(--env "GITLAB_HOST=$gitlab_host") +fi + +for name in \ + EXPERIMENTALIST_SMART_MODEL_NAME \ + EXPERIMENTALIST_MID_MODEL_NAME \ + EXPERIMENTALIST_FAST_MODEL_NAME; do + if [[ -n "${!name:-}" ]]; then + create_args+=(--env "$name=${!name}") + fi +done + +# Provision non-interactively without attaching a host credential provider. +# OpenShell keeps the sandbox alive after the initial command exits; subsequent +# work runs through `sandbox exec`. +openshell "${create_args[@]}" -- /bin/true + +openshell sandbox exec --name "$sandbox_name" -- \ + /bin/bash -c ' + set -euo pipefail + if command -v docker >/dev/null 2>&1; then + echo "Experimentalist OpenShell image unexpectedly contains the Docker CLI" >&2 + exit 1 + fi + if [[ -e /var/run/docker.sock || -e /run/docker.sock ]]; then + echo "Experimentalist OpenShell sandbox unexpectedly exposes a Docker socket" >&2 + exit 1 + fi + ' + +if [[ "$source_control" == gitlab-* ]]; then + # glab's auth-status check requires a per-host config entry even when + # GITLAB_TOKEN is set. Store only the OpenShell placeholder in the sandbox. + openshell sandbox exec --name "$sandbox_name" -- \ + /bin/bash -c ' + set -euo pipefail + glab config set token "$GITLAB_TOKEN" --host "$GITLAB_HOST" + glab config set git_protocol https --host "$GITLAB_HOST" + ' +fi + +if [[ "$subcommand" == "doctor" ]]; then + openshell sandbox exec --name "$sandbox_name" --workdir "$remote_workspace" -- \ + /app/.venv/bin/nemo experimentalist doctor "$@" + exit +fi + +openshell sandbox exec --name "$sandbox_name" --workdir "$remote_workspace" -- \ + /app/.venv/bin/nemo experimentalist run --experiment-dir /sandbox/output "$@" + +mkdir -p "$output_dir" +openshell sandbox download "$sandbox_name" /sandbox/output "$output_dir" diff --git a/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/openshell/smoke-full-run.sh b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/openshell/smoke-full-run.sh new file mode 100755 index 0000000000..7c8088c066 --- /dev/null +++ b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/openshell/smoke-full-run.sh @@ -0,0 +1,47 @@ +#!/usr/bin/env bash +# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 + +set -euo pipefail + +usage() { + echo "usage: $0 WORKSPACE_DIR [experimentalist run options...]" >&2 +} + +if [[ $# -lt 1 ]]; then + usage + exit 2 +fi + +workspace_dir="$(cd "$1" && pwd)" +shift +smoke_output="${NEMO_EXPERIMENTALIST_SMOKE_OUTPUT:-$workspace_dir/tmp/experimentalist-full-run-smoke-$$}" +nemo_bin="${NEMO_EXPERIMENTALIST_CLI:-$(command -v nemo || true)}" + +if [[ -e "$smoke_output" ]]; then + echo "smoke output already exists: $smoke_output" >&2 + exit 2 +fi + +if [[ -z "$nemo_bin" || ! -x "$nemo_bin" ]]; then + echo "nemo CLI is required; set NEMO_EXPERIMENTALIST_CLI to its executable path" >&2 + exit 127 +fi + +( + cd "$workspace_dir" + "$nemo_bin" experimentalist run --experiment-dir "$smoke_output" "$@" +) + +analysis_file="$(find "$smoke_output" -type f -path "*/eval-and-optimize/analysis/round-*.md" -print -quit)" +if [[ -z "$analysis_file" ]]; then + echo "full-run smoke produced no round analysis under $smoke_output" >&2 + exit 1 +fi + +if grep -R -n -F "analysis_error" "$smoke_output"; then + echo "full-run smoke degraded trace analysis to analysis_error" >&2 + exit 1 +fi + +echo "OpenShell full-run smoke passed: $smoke_output" diff --git a/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/preflight.py b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/preflight.py index d47b23fbec..2bbb48c32a 100644 --- a/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/preflight.py +++ b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/preflight.py @@ -40,6 +40,8 @@ " agent: \n task_template: ./path/to/task_template\n" " datasets:\n train: ./path\n validation: ./path" ) +_HARBOR_BRIDGE_URL_ENV = "NEMO_EXPERIMENTALIST_HARBOR_BRIDGE_URL" +_HARBOR_BRIDGE_TOKEN_ENV = "NEMO_EXPERIMENTALIST_HARBOR_BRIDGE_TOKEN" def _default_run_cmd(argv: list[str]) -> tuple[int, str]: @@ -114,6 +116,8 @@ def check_environment( insight: str | None, insight_id: str | None = None, base_url: str, + harbor_bridge_url: str | None = None, + harbor_bridge_token_env: str = _HARBOR_BRIDGE_TOKEN_ENV, enforce_insight_agent: bool = True, probes: Probes | None = None, ) -> list[CheckResult]: @@ -162,30 +166,48 @@ def check_environment( ) profile_agent = profile.agent if (profile is not None and enforce_insight_agent) else None results += _check_insight_file(insight, insight_id, profile_agent) - code, _ = p.run_cmd(["docker", "info"]) - results.append( - make_check_result( - "docker", - "runtime", - code == 0, - "required", - "docker daemon running", - "docker daemon not running", - hint="start Docker; Harbor evaluation requires it", + bridge_url = harbor_bridge_url or p.env.get(_HARBOR_BRIDGE_URL_ENV) + if bridge_url: + results += _check_env(p, "runtime", (harbor_bridge_token_env,), profile_dir) + health_url = f"{bridge_url.rstrip('/')}/health/ready" + bridge_ok = p.http_ok(health_url) + display_health_url = f"{_redact_url(bridge_url).rstrip('/')}/health/ready" + results.append( + make_check_result( + "harbor-bridge", + "runtime", + bridge_ok, + "required", + f"{display_health_url} reachable", + f"{display_health_url} unreachable", + hint="start nemo-experimentalist-harbor-bridge and check OpenShell network policy", + ) ) - ) - has_harbor = importlib.util.find_spec("harbor") is not None - results.append( - make_check_result( - "harbor-import", - "runtime", - has_harbor, - "required", - "harbor importable", - "harbor not importable", - hint="uv sync", + else: + code, _ = p.run_cmd(["docker", "info"]) + results.append( + make_check_result( + "docker", + "runtime", + code == 0, + "required", + "docker daemon running", + "docker daemon not running", + hint="start Docker; Harbor evaluation requires it", + ) + ) + has_harbor = importlib.util.find_spec("harbor") is not None + results.append( + make_check_result( + "harbor-import", + "runtime", + has_harbor, + "required", + "harbor importable", + "harbor not importable", + hint="uv sync", + ) ) - ) return results diff --git a/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/resolve.py b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/resolve.py index 82be6af0b4..efdcb38e4d 100644 --- a/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/resolve.py +++ b/plugins/nemo-experimentalist/src/nemo_experimentalist_plugin/resolve.py @@ -623,6 +623,14 @@ def profile_storage_flags(profile: AgentProfile) -> dict: return _resolve_config(None, profile).storage.model_dump(exclude_defaults=True) +def resolve_experiment_config( + config_payload: Any | None, + profile: AgentProfile | None, +) -> EvolutionaryOptimizerConfig: + """Resolve and validate optimizer configuration without materializing inputs.""" + return _resolve_config(config_payload, profile) + + def pick_agent_spec(profile: AgentProfile) -> str | None: """Resolve and read-check the configured or conventional agent spec.""" try: diff --git a/plugins/nemo-experimentalist/tests/experimentalist/test_dataset_staging_loop.py b/plugins/nemo-experimentalist/tests/experimentalist/test_dataset_staging_loop.py index a03990f009..472af53d45 100644 --- a/plugins/nemo-experimentalist/tests/experimentalist/test_dataset_staging_loop.py +++ b/plugins/nemo-experimentalist/tests/experimentalist/test_dataset_staging_loop.py @@ -64,7 +64,9 @@ async def run( monkeypatch.setattr( loop_module, "EvaluatorFactory", - lambda: SimpleNamespace(build_evaluator=lambda *args, **kwargs: object()), + lambda: SimpleNamespace( + build_evaluator=lambda *args, **kwargs: SimpleNamespace(prepare_dataset=lambda dataset: dataset) + ), ) monkeypatch.setattr(loop_module, "DatasetFactory", RecordingDatasetFactory) monkeypatch.setattr(loop_module, "EvalAuthor", MutatingEvalAuthor) diff --git a/plugins/nemo-experimentalist/tests/experimentalist/test_evaluator_harbor.py b/plugins/nemo-experimentalist/tests/experimentalist/test_evaluator_harbor.py index f869a74586..4a6ddd8f0a 100644 --- a/plugins/nemo-experimentalist/tests/experimentalist/test_evaluator_harbor.py +++ b/plugins/nemo-experimentalist/tests/experimentalist/test_evaluator_harbor.py @@ -1118,6 +1118,15 @@ async def test_harbor_dependency_context_stop_started_runtime_no_environment(mon await ctx._stop_started_runtime() +@pytest.mark.asyncio +async def test_harbor_dependency_context_execute_requires_running_environment(tmp_path): + runtime = HarborDependencyRuntime(task_path=ResourceRef(uri=(tmp_path / "task").as_uri(), description="")) + ctx = HarborDependencyContext(runtime) + + with pytest.raises(RuntimeError, match="environment is not running"): + await ctx.execute("pwd") + + @pytest.mark.asyncio async def test_harbor_dependency_context_stop_started_runtime_with_environment(monkeypatch): runtime = HarborDependencyRuntime(task_path=ResourceRef(uri="file:///tmp/task", description=""), delete=True) diff --git a/plugins/nemo-experimentalist/tests/experimentalist/test_loop_failure.py b/plugins/nemo-experimentalist/tests/experimentalist/test_loop_failure.py index b5f17225eb..2274f68ce2 100644 --- a/plugins/nemo-experimentalist/tests/experimentalist/test_loop_failure.py +++ b/plugins/nemo-experimentalist/tests/experimentalist/test_loop_failure.py @@ -35,7 +35,9 @@ async def test_baseline_failure_marks_run_failed(monkeypatch, tmp_path, failure_ monkeypatch.setattr( loop_module, "EvaluatorFactory", - lambda: SimpleNamespace(build_evaluator=lambda *args, **kwargs: object()), + lambda: SimpleNamespace( + build_evaluator=lambda *args, **kwargs: SimpleNamespace(prepare_dataset=lambda dataset: dataset) + ), ) monkeypatch.setattr( loop_module, diff --git a/plugins/nemo-experimentalist/tests/experimentalist/test_loop_insight_suite.py b/plugins/nemo-experimentalist/tests/experimentalist/test_loop_insight_suite.py index e959de65be..020a59deef 100644 --- a/plugins/nemo-experimentalist/tests/experimentalist/test_loop_insight_suite.py +++ b/plugins/nemo-experimentalist/tests/experimentalist/test_loop_insight_suite.py @@ -173,7 +173,9 @@ async def run(self, **kwargs: object) -> SimpleNamespace: monkeypatch.setattr( loop_module, "EvaluatorFactory", - lambda: SimpleNamespace(build_evaluator=lambda *args, **kwargs: object()), + lambda: SimpleNamespace( + build_evaluator=lambda *args, **kwargs: SimpleNamespace(prepare_dataset=lambda dataset: dataset) + ), ) monkeypatch.setattr(loop_module, "EvalAuthor", ReturningEvalAuthor) monkeypatch.setattr( diff --git a/plugins/nemo-experimentalist/tests/experimentalist/test_tools.py b/plugins/nemo-experimentalist/tests/experimentalist/test_tools.py index 7a0ea7af33..db5e9959c3 100644 --- a/plugins/nemo-experimentalist/tests/experimentalist/test_tools.py +++ b/plugins/nemo-experimentalist/tests/experimentalist/test_tools.py @@ -2,8 +2,10 @@ # SPDX-License-Identifier: Apache-2.0 from pathlib import Path +from typing import Any, cast from nemo_experimentalist_plugin.experimentalist.components.coder import Coder +from nemo_experimentalist_plugin.experimentalist.components.evaluator.models import DependencyCommandResult from nemo_experimentalist_plugin.experimentalist.components.holdout_utils import BLOCKED_MESSAGE from nemo_experimentalist_plugin.experimentalist.components.tools import GuardedShellTools from nooa.agentdoc import pformat @@ -36,6 +38,32 @@ async def test_guarded_shell_tools_returns_failure_for_blocked_paths(tmp_path): assert not result.success +async def test_guarded_shell_tools_routes_through_executable_dependency_runtime(tmp_path): + class FakeRuntime: + commands: list[tuple[str, str | None, float]] = [] + + async def execute( + self, + command: str, + *, + stdin: str | None = None, + timeout: float = 30.0, + ) -> DependencyCommandResult: + self.commands.append((command, stdin, timeout)) + return DependencyCommandResult(stdout="/app\n", returncode=0) + + runtime = FakeRuntime() + shell = GuardedShellTools(cwd=tmp_path) + try: + with shell.use_dependency_runtime(cast(Any, runtime)): + result = await shell.run("pwd", stdin="input", timeout=12.5) + finally: + await shell.close() + + assert result == ShellResult(stdout="/app\n", stderr="", returncode=0) + assert runtime.commands == [("pwd", "input", 12.5)] + + def test_coder_hides_skill_registry_that_can_replace_guarded_shell(tmp_path): nooa_skill = Path(__file__).resolve().parents[2] / "framework-skills" / "nooa" coder = Coder(workspace=tmp_path, framework_skills_dirs=[nooa_skill]) diff --git a/plugins/nemo-experimentalist/tests/test_cli_profile.py b/plugins/nemo-experimentalist/tests/test_cli_profile.py index 5f25fc7b78..9c15495cd0 100644 --- a/plugins/nemo-experimentalist/tests/test_cli_profile.py +++ b/plugins/nemo-experimentalist/tests/test_cli_profile.py @@ -39,6 +39,7 @@ def _quiet_preflight(monkeypatch): """Deterministic probes for every test; tests override with their own monkeypatch.setattr when they exercise specific probe behavior.""" monkeypatch.setattr(cli, "_PREFLIGHT_PROBES", quiet_probes()) + monkeypatch.setattr(cli, "_CONTAINER_RUNTIME", True) @dataclass @@ -304,6 +305,63 @@ def test_doctor_healthy_exits_zero(app, profile_tree: Path, monkeypatch) -> None assert "✓" in result.output +def test_doctor_uses_openshell_by_default(app, profile_tree: Path, monkeypatch: pytest.MonkeyPatch) -> None: + profile_path = profile_tree / "optimizer.yaml" + captured: dict[str, object] = {} + + def launch( + command: str, + args: list[str], + *, + workspace_dir: Path, + output_dir: Path | None, + platform_url: str | None, + ) -> int: + captured.update( + command=command, + args=args, + workspace_dir=workspace_dir, + output_dir=output_dir, + platform_url=platform_url, + ) + return 0 + + monkeypatch.setattr(cli, "_CONTAINER_RUNTIME", False) + monkeypatch.setattr(cli, "_OPEN_SHELL_LAUNCHER", launch) + monkeypatch.chdir(profile_tree) + + result = runner.invoke( + app, + [ + "doctor", + "--profile", + str(profile_path), + "--insight", + "platform-insight-id", + "--insight-id", + "selected", + "--base-url", + "https://platform.example", + ], + ) + + assert result.exit_code == 0, result.output + assert captured == { + "command": "doctor", + "args": [ + "--insight", + "platform-insight-id", + "--insight-id", + "selected", + "--profile", + f"/sandbox/project/{profile_tree.name}/optimizer.yaml", + ], + "workspace_dir": profile_tree, + "output_dir": None, + "platform_url": "https://platform.example", + } + + def test_doctor_no_profile_exits_one_with_skeleton(app, tmp_path: Path, monkeypatch) -> None: monkeypatch.setattr(cli, "_PREFLIGHT_PROBES", quiet_probes()) monkeypatch.chdir(tmp_path) diff --git a/plugins/nemo-experimentalist/tests/test_experiment_cli.py b/plugins/nemo-experimentalist/tests/test_experiment_cli.py index f4460ae4a9..51d8cd2ec0 100644 --- a/plugins/nemo-experimentalist/tests/test_experiment_cli.py +++ b/plugins/nemo-experimentalist/tests/test_experiment_cli.py @@ -1,6 +1,7 @@ # SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. # SPDX-License-Identifier: Apache-2.0 +import os from dataclasses import dataclass from pathlib import Path from typing import Literal, cast @@ -10,7 +11,9 @@ from nemo_experimentalist_plugin import cli from nemo_experimentalist_plugin.experimentalist.components.evaluator.models import DatasetRef from nemo_experimentalist_plugin.experimentalist.components.loop import EvolutionaryOptimizerConfig +from nemo_experimentalist_plugin.harbor_bridge.preparation import PreparedTrustedInputs from nemo_experimentalist_plugin.preflight import Probes +from nemo_experimentalist_plugin.profile import AgentProfile, DatasetsSpec from nemo_platform import AsyncNeMoPlatform from typer.testing import CliRunner @@ -31,6 +34,21 @@ def quiet_preflight(monkeypatch: pytest.MonkeyPatch) -> None: env={"EXPERIMENTALIST_API_BASE": "http://llm", "EXPERIMENTALIST_API_KEY": "k"}, ), ) + monkeypatch.setattr(cli, "_CONTAINER_RUNTIME", True) + + async def prepare(plan, *, workspace: Path) -> PreparedTrustedInputs: + def local(value: str, anchor: Path) -> Path: + path = Path(value) + return path.resolve() if path.is_absolute() else (anchor / path).resolve() + + return PreparedTrustedInputs( + catalog_root=workspace / "catalog", + train_dataset=local(plan.train_dataset, plan.train_anchor), + validation_dataset=local(plan.validation_dataset, plan.validation_anchor), + task_template=Path(plan.task_template) if plan.task_template is not None else None, + ) + + monkeypatch.setattr(cli, "_TRUSTED_INPUT_PREPARER", prepare) @pytest.fixture(autouse=True) @@ -159,6 +177,64 @@ async def _fail_if_runner_starts(**_: object) -> str: raise AssertionError("invalid CLI input must not start the experimentalist runner") +def test_host_prompts_for_profile_multi_insight( + monkeypatch: pytest.MonkeyPatch, + tmp_path: Path, +) -> None: + profile = AgentProfile( + agent="nemo-oo-airline", + task_template="./template", + datasets=DatasetsSpec(train="train", validation="validation"), + profile_dir=tmp_path, + ) + insight_dir = tmp_path / ".nemo-optimizer" + insight_dir.mkdir() + (insight_dir / "insights.yaml").write_text( + "insights:\n - id: insight-one\n title: First problem\n - id: insight-two\n title: Second problem\n", + encoding="utf-8", + ) + + class InteractiveInput: + @staticmethod + def isatty() -> bool: + return True + + monkeypatch.setattr(cli.sys, "stdin", InteractiveInput()) + monkeypatch.setattr(cli.typer, "prompt", lambda *args, **kwargs: "1") + + selected = cli._select_host_insight( + profile, + insight=None, + insight_id=None, + no_insight=False, + ) + + assert selected == "insight-two" + + +def test_profile_registry_selects_gitlab_read_provider( + monkeypatch: pytest.MonkeyPatch, + tmp_path: Path, +) -> None: + profile = AgentProfile( + agent="nemo-oo-airline", + task_template="./template", + datasets=DatasetsSpec( + train="train", + validation="validation", + registry_url="https://gitlab.example/group/registry.json", + ), + profile_dir=tmp_path, + ) + monkeypatch.delenv("NEMO_EXPERIMENTALIST_SOURCE_CONTROL", raising=False) + monkeypatch.delenv("NEMO_EXPERIMENTALIST_GITLAB_HOST", raising=False) + + cli._apply_profile_runtime_defaults(profile) + + assert os.environ["NEMO_EXPERIMENTALIST_SOURCE_CONTROL"] == "gitlab-read" + assert os.environ["NEMO_EXPERIMENTALIST_GITLAB_HOST"] == "gitlab.example" + + def test_cli_help_exposes_only_run_and_doctor() -> None: app = cli.ExperimentalistCLI().get_cli() result = CliRunner().invoke(app, ["--help"]) @@ -168,6 +244,117 @@ def test_cli_help_exposes_only_run_and_doctor() -> None: assert "doctor" in result.output assert "analyze" not in result.output assert "analysis" not in result.output + run_help = CliRunner().invoke(app, ["run", "--help"]) + assert "--runtime" not in run_help.output + + +def test_experiment_cli_uses_openshell_by_default( + monkeypatch: pytest.MonkeyPatch, + tmp_path: Path, +) -> None: + paths = _make_paths(tmp_path) + agent_spec = tmp_path / "agent-spec.md" + insight = tmp_path / "insight.yaml" + config = tmp_path / "config.yaml" + skills = _make_dir(tmp_path / "skills") + agent_spec.write_text("# Agent\n", encoding="utf-8") + insight.write_text("id: insight-1\n", encoding="utf-8") + config.write_text("max_rounds: 1\n", encoding="utf-8") + captured: dict[str, object] = {} + + def launch( + command: Literal["run", "doctor"], + args: list[str], + *, + workspace_dir: Path, + output_dir: Path | None, + platform_url: str | None, + ) -> int: + captured.update( + command=command, + args=args, + workspace_dir=workspace_dir, + output_dir=output_dir, + platform_url=platform_url, + ) + return 0 + + monkeypatch.setattr(cli, "_CONTAINER_RUNTIME", False) + monkeypatch.setattr(cli, "_OPEN_SHELL_LAUNCHER", launch) + monkeypatch.setattr(cli, "run_experimentalist", _fail_if_runner_starts) + + result = _run_experiment( + [ + *paths.args(), + "--agent-spec", + str(agent_spec), + "--insight", + str(insight), + "--config", + str(config), + "--framework-skills", + str(skills), + "--workspace", + "workspace-a", + "--base-url", + "http://localhost:8080", + ] + ) + + sandbox_root = Path("/sandbox/project") / tmp_path.name + assert result.exit_code == 0, result.output + assert captured == { + "command": "run", + "args": [ + "--agent", + str(sandbox_root / "agent"), + "--agent-spec", + str(sandbox_root / "agent-spec.md"), + "--insight", + str(sandbox_root / "insight.yaml"), + "--train-dataset", + str(sandbox_root / "train"), + "--validation-dataset", + str(sandbox_root / "validation"), + "--task-template", + str(sandbox_root / "template"), + "--config", + str(sandbox_root / "config.yaml"), + "--mode", + "local", + "--workspace", + "workspace-a", + "--framework-skills", + str(sandbox_root / "skills"), + ], + "workspace_dir": tmp_path, + "output_dir": paths.experiment, + "platform_url": "http://localhost:8080", + } + + +def test_experiment_cli_rejects_local_inputs_outside_openshell_workspace( + monkeypatch: pytest.MonkeyPatch, + tmp_path: Path, +) -> None: + outside_agent = tmp_path.parent / f"{tmp_path.name}-outside-agent" + outside_agent.mkdir() + launched = False + + def launch(*args: object, **kwargs: object) -> int: + nonlocal launched + launched = True + return 0 + + monkeypatch.setattr(cli, "_CONTAINER_RUNTIME", False) + monkeypatch.setattr(cli, "_OPEN_SHELL_LAUNCHER", launch) + + result = _run_experiment(["--agent", str(outside_agent), "--no-insight"]) + + assert result.exit_code == 1 + assert "resolves outside the OpenShell workspace" in result.output + assert "Run from a directory that contains every local input" in result.output + assert not launched @pytest.mark.parametrize( @@ -229,6 +416,7 @@ def test_experiment_cli_passes_dataset_driven_contract_to_runner( # reads insight files with json.loads, so YAML-authored files must not # reach it raw); platform ids still pass through verbatim. assert runner.captured.insight == str(paths.experiment / "resolved" / "insight.json") + assert isinstance(runner.captured.insight, str | Path) assert Path(runner.captured.insight).read_text(encoding="utf-8").strip() == "{}" # Datasets and the task template are forwarded as DatasetRef URI handles, # tagged with a stable id the evaluator adapter uses when building datasets. diff --git a/plugins/nemo-experimentalist/tests/test_experimentalist_analyzer.py b/plugins/nemo-experimentalist/tests/test_experimentalist_analyzer.py index 48ab2c4f44..c2586a5876 100644 --- a/plugins/nemo-experimentalist/tests/test_experimentalist_analyzer.py +++ b/plugins/nemo-experimentalist/tests/test_experimentalist_analyzer.py @@ -28,6 +28,7 @@ FailureClassification, PeerComparison, ) +from nemo_experimentalist_plugin.experimentalist.components.evaluator.models import DependencyRuntimeError from nemo_experimentalist_plugin.experimentalist.components.rationalizer import Rationale from nemo_experimentalist_plugin.experimentalist.components.trace_analyzer import Diagnostic @@ -218,3 +219,29 @@ async def test_intake_availability_is_part_of_cache_key(tmp_path: Path, monkeypa assert len(calls) == 2 assert calls[0]["client"] is None assert calls[1]["client"] is not None + + +@pytest.mark.asyncio +async def test_dependency_runtime_failure_is_not_converted_to_analysis_error( + tmp_path: Path, + monkeypatch: pytest.MonkeyPatch, +) -> None: + class FailingRationalizer(_FakeRationalizer): + async def run(self, task: Any, agent_spec: Any = None) -> Rationale: + raise DependencyRuntimeError("remote Harbor dependency startup failed") + + calls: list[dict[str, Any]] = [] + _install_fakes(monkeypatch, calls) + monkeypatch.setattr(analyzer_module, "Rationalizer", FailingRationalizer) + trial, dataset, evaluation = _fixtures() + analyzer = _make_analyzer(tmp_path, [trial]) + + with pytest.raises(DependencyRuntimeError, match="remote Harbor dependency startup failed"): + await analyzer.run( + agent="agent-a", + dataset=cast(Any, dataset), + evaluation=cast(Any, evaluation), + round=0, + ) + + assert calls == [] diff --git a/plugins/nemo-experimentalist/tests/test_harbor_bridge.py b/plugins/nemo-experimentalist/tests/test_harbor_bridge.py new file mode 100644 index 0000000000..bc473b6687 --- /dev/null +++ b/plugins/nemo-experimentalist/tests/test_harbor_bridge.py @@ -0,0 +1,1053 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 + +from __future__ import annotations + +import importlib +import io +import json +import sys +import tarfile +from pathlib import Path +from urllib.parse import parse_qs + +import httpx +import pytest +from harbor.models.task.config import VerifierEnvironmentMode +from harbor.models.task.task import Task as HarborTask +from nemo_experimentalist_plugin.experimentalist.components.evaluator.factory import EvaluatorFactory +from nemo_experimentalist_plugin.experimentalist.components.evaluator.harbor import ( + HarborDataset, + HarborDependencyRuntime, +) +from nemo_experimentalist_plugin.experimentalist.components.evaluator.models import ( + CommandSpec, + DependencyRuntime, + DependencyRuntimeError, + EvaluationResult, + MetricResult, + MetricSpec, + ResourceRef, + Task, + TrialResult, +) +from nemo_experimentalist_plugin.experimentalist.components.evaluator.remote_harbor import ( + RemoteHarborDependencyRuntime, + RemoteHarborEvaluator, + RemoteHarborEvaluatorConfig, +) +from nemo_experimentalist_plugin.harbor_bridge import dependencies as dependency_module +from nemo_experimentalist_plugin.harbor_bridge.archives import ( + create_directory_archive, + create_result_archive, + extract_directory_archive, + materialize_result_archive, +) +from nemo_experimentalist_plugin.harbor_bridge.contracts import ( + DEPENDENCY_OUTPUT_LIMIT_CHARS, + HarborBridgeRequest, + HarborDependencyExecRequest, + HarborDependencyExecResponse, + HarborDependencyRequest, +) +from nemo_experimentalist_plugin.harbor_bridge.envelopes import ( + ENVELOPE_DESCRIPTOR_FILENAME, + EnvelopeTaskSelection, + TaskDataSlot, + TaskEnvelopePolicy, + TrustedEnvelopeCatalog, + register_dataset_envelope, + transport_tree_digest, +) +from nemo_experimentalist_plugin.harbor_bridge.preparation import prepare_trusted_inputs +from nemo_experimentalist_plugin.harbor_bridge.runner import _harden_task +from nemo_experimentalist_plugin.harbor_bridge.service import HarborBridgeSettings, create_app +from nemo_experimentalist_plugin.harbor_bridge.trusted_agent import ( + TrustedCandidateAgent, + candidate_agent_import, +) +from nemo_experimentalist_plugin.resolve import build_effective_experiment_plan +from pydantic import ValidationError + +_DIGEST = "sha256:" + "a" * 64 + + +def _completed_result(trace_path: Path) -> EvaluationResult: + return EvaluationResult( + id="bridge-evaluation", + aggregate_metrics={"reward": 1.0}, + trials=[ + TrialResult( + id="trial-1", + task_id="task-1", + status="completed", + trace=ResourceRef(uri=trace_path.as_uri()), + ) + ], + ) + + +def _candidate(root: Path) -> Path: + root.mkdir(parents=True) + (root / "main.py").write_text("print('candidate')\n", encoding="utf-8") + (root / "pyproject.toml").write_text("[project]\nname='candidate'\nversion='0.1.0'\n", encoding="utf-8") + (root / "uv.lock").write_text("version = 1\nrevision = 3\n", encoding="utf-8") + return root + + +def _complete_task_files(task_dir: Path) -> None: + (task_dir / "instruction.md").write_text("Do the task.\n", encoding="utf-8") + environment_dir = task_dir / "environment" + environment_dir.mkdir() + (environment_dir / "Dockerfile").write_text("FROM ubuntu:24.04\n", encoding="utf-8") + tests_dir = task_dir / "tests" + tests_dir.mkdir() + (tests_dir / "Dockerfile").write_text("FROM ubuntu:24.04\n", encoding="utf-8") + (tests_dir / "test.sh").write_text("#!/bin/sh\nexit 0\n", encoding="utf-8") + + +def _registered_dataset(tmp_path: Path, *, mutable: bool = False): + source = tmp_path / "trusted-source" + task_dir = source / "task-1" + task_dir.mkdir(parents=True) + (task_dir / "task.toml").write_text( + 'schema_version = "1.1"\n[task]\nname = "example/task-1"\n', + encoding="utf-8", + ) + _complete_task_files(task_dir) + if mutable: + (task_dir / "nemo-task-envelope.json").write_text( + TaskEnvelopePolicy( + task_data=[ + TaskDataSlot( + path="instruction.md", + media_type="text/plain", + max_bytes=4096, + ) + ], + verifier_paths=["tests/test.sh", "tests/metrics"], + ).model_dump_json(indent=2), + encoding="utf-8", + ) + catalog_root = tmp_path / "catalog" + registered = register_dataset_envelope(source, catalog_root=catalog_root, name="test") + return registered, TrustedEnvelopeCatalog(catalog_root) + + +def test_bridge_contract_rejects_execution_authority() -> None: + with pytest.raises(ValidationError, match="import_path"): + HarborBridgeRequest.model_validate( + { + "request_id": "request-1", + "envelope_id": "envelope-1", + "envelope_digest": _DIGEST, + "tasks": [{"task_id": "task-1", "base_task_id": "task-1"}], + "candidate_digest": _DIGEST, + "import_path": "candidate:Agent", + } + ) + + +def test_dependency_contract_rejects_docker_authority() -> None: + with pytest.raises(ValidationError, match="environment_type"): + HarborDependencyRequest.model_validate( + { + "request_id": "dependency-task-1", + "envelope_id": "envelope-1", + "envelope_digest": _DIGEST, + "task_id": "task-1", + "base_task_id": "task-1", + "environment_type": "docker", + } + ) + + +@pytest.mark.parametrize( + "tasks", + [ + [ + {"task_id": "task-a", "base_task_id": "task-a"}, + {"task_id": "task-a", "base_task_id": "task-a"}, + ], + [{"task_id": "../escape", "base_task_id": "task-a"}], + [{"task_id": "task/a", "base_task_id": "task-a"}], + ], +) +def test_bridge_contract_rejects_unsafe_task_ids(tasks: list[dict[str, str]]) -> None: + with pytest.raises(ValidationError, match="tasks|task_id"): + HarborBridgeRequest.model_validate( + { + "request_id": "request-1", + "envelope_id": "envelope-1", + "envelope_digest": _DIGEST, + "tasks": tasks, + "candidate_digest": _DIGEST, + } + ) + + +def test_directory_archive_rejects_links_and_traversal(tmp_path: Path) -> None: + source = tmp_path / "source" + source.mkdir() + (source / "target.txt").write_text("target", encoding="utf-8") + (source / "link.txt").symlink_to(source / "target.txt") + + with pytest.raises(ValueError, match="symbolic link"): + create_directory_archive(source, tmp_path / "source.tar.gz") + + malicious = tmp_path / "malicious.tar.gz" + with tarfile.open(malicious, mode="w:gz") as archive: + info = tarfile.TarInfo("../escape.txt") + payload = b"escape" + info.size = len(payload) + archive.addfile(info, io.BytesIO(payload)) + with pytest.raises(ValueError, match="Unsafe archive member path"): + extract_directory_archive(malicious, tmp_path / "extract") + assert not (tmp_path / "escape.txt").exists() + + +def test_directory_archive_rejects_duplicate_paths(tmp_path: Path) -> None: + archive_path = tmp_path / "duplicate.tar.gz" + with tarfile.open(archive_path, mode="w:gz") as archive: + for payload in (b"first", b"second"): + info = tarfile.TarInfo("duplicate.txt") + info.size = len(payload) + archive.addfile(info, io.BytesIO(payload)) + + with pytest.raises(ValueError, match="duplicate member paths"): + extract_directory_archive(archive_path, tmp_path / "extract") + + +def test_trusted_envelope_materializes_only_declared_overlays(tmp_path: Path) -> None: + registered, catalog = _registered_dataset(tmp_path, mutable=True) + overlay = tmp_path / "overlay" + task_overlay = overlay / "derived-task" + (task_overlay / "tests").mkdir(parents=True) + (task_overlay / "instruction.md").write_text("Derived instruction.\n", encoding="utf-8") + (task_overlay / "tests" / "test.sh").write_text("#!/bin/sh\necho metric\n", encoding="utf-8") + + output = catalog.materialize( + envelope_id=registered.manifest.envelope_id, + envelope_digest=registered.manifest.envelope_digest, + selections=[EnvelopeTaskSelection(task_id="derived-task", base_task_id="task-1")], + destination=tmp_path / "materialized", + overlay_dir=overlay, + ) + task = output / "derived-task" + + assert (task / "instruction.md").read_text(encoding="utf-8") == "Derived instruction.\n" + assert (task / "tests" / "test.sh").read_text(encoding="utf-8") == "#!/bin/sh\necho metric\n" + assert (task / "tests" / "Dockerfile").read_text(encoding="utf-8") == "FROM ubuntu:24.04\n" + assert not (task / ENVELOPE_DESCRIPTOR_FILENAME).exists() + task_config = HarborTask(task).config.task + assert task_config is not None + assert task_config.name == "example/task-1__derived-task" + + +def test_trusted_envelope_detects_catalog_tampering(tmp_path: Path) -> None: + registered, catalog = _registered_dataset(tmp_path) + (registered.dataset_path / "task-1" / "environment" / "Dockerfile").write_text( + "FROM tampered\n", + encoding="utf-8", + ) + + with pytest.raises(ValueError, match="content changed after registration"): + catalog.materialize( + envelope_id=registered.manifest.envelope_id, + envelope_digest=registered.manifest.envelope_digest, + selections=[EnvelopeTaskSelection(task_id="task-1", base_task_id="task-1")], + destination=tmp_path / "materialized", + ) + + +def test_trusted_envelope_registration_rejects_symlinks(tmp_path: Path) -> None: + source = tmp_path / "source" + source.mkdir() + (source / "task.toml").write_text( + 'schema_version = "1.1"\n[task]\nname = "example/task"\n', + encoding="utf-8", + ) + _complete_task_files(source) + (source / "linked-Dockerfile").symlink_to(source / "environment" / "Dockerfile") + + with pytest.raises(ValueError, match="symbolic link"): + register_dataset_envelope(source, catalog_root=tmp_path / "catalog", name="unsafe") + + +def test_tau_template_is_a_trusted_multi_container_envelope(tmp_path: Path) -> None: + template = Path(__file__).parents[1] / "examples" / "tau2-nemo-oo-agent" / "dataset" / "template" / "task_template" + registered = register_dataset_envelope( + template, + catalog_root=tmp_path / "catalog", + name="tau-template", + ) + base_task_id = registered.manifest.tasks[0].task_id + task = ( + TrustedEnvelopeCatalog(tmp_path / "catalog").materialize( + envelope_id=registered.manifest.envelope_id, + envelope_digest=registered.manifest.envelope_digest, + selections=[EnvelopeTaskSelection(task_id="tau-derived", base_task_id=base_task_id)], + destination=tmp_path / "materialized", + ) + / "tau-derived" + ) + + _harden_task(task) + + assert (task / "environment" / "docker-compose.yaml").is_file() + assert HarborTask(task).config.environment.mcp_servers[0].name == "tau3-runtime" + assert HarborTask(task).config.verifier.environment_mode == VerifierEnvironmentMode.SEPARATE + + +def test_tau_envelope_rejects_invalid_typed_task_data(tmp_path: Path) -> None: + template = Path(__file__).parents[1] / "examples" / "tau2-nemo-oo-agent" / "dataset" / "template" / "task_template" + registered = register_dataset_envelope( + template, + catalog_root=tmp_path / "catalog", + name="tau-template", + ) + base_task_id = registered.manifest.tasks[0].task_id + overlay = tmp_path / "overlay" + invalid = overlay / "tau-derived" / "environment" / "runtime-server" / "task_config.json" + invalid.parent.mkdir(parents=True) + invalid.write_text("{not-json", encoding="utf-8") + + with pytest.raises(ValueError, match="not valid JSON"): + TrustedEnvelopeCatalog(tmp_path / "catalog").materialize( + envelope_id=registered.manifest.envelope_id, + envelope_digest=registered.manifest.envelope_digest, + selections=[EnvelopeTaskSelection(task_id="tau-derived", base_task_id=base_task_id)], + destination=tmp_path / "materialized", + overlay_dir=overlay, + ) + + +@pytest.mark.asyncio +async def test_host_prepares_trusted_inputs_without_a_sandbox_registration_api(tmp_path: Path) -> None: + agent = _candidate(tmp_path / "agent") + train_source = tmp_path / "train-source" + validation_source = tmp_path / "validation-source" + for source, task_name in ((train_source, "train-task"), (validation_source, "validation-task")): + task = source / task_name + task.mkdir(parents=True) + (task / "task.toml").write_text( + f'schema_version = "1.1"\n[task]\nname = "example/{task_name}"\n', + encoding="utf-8", + ) + _complete_task_files(task) + plan = build_effective_experiment_plan( + profile=None, + agent=str(agent), + no_insight=True, + train_dataset=str(train_source), + validation_dataset=str(validation_source), + ) + + prepared = await prepare_trusted_inputs(plan, workspace=tmp_path) + + assert prepared.catalog_root.is_dir() + assert (prepared.train_dataset / ENVELOPE_DESCRIPTOR_FILENAME).is_file() + assert (prepared.validation_dataset / ENVELOPE_DESCRIPTOR_FILENAME).is_file() + assert prepared.task_template is None + assert list((prepared.catalog_root / "envelopes").glob("*/manifest.json")) + + +def test_result_archive_rewrites_artifacts_to_local_paths(tmp_path: Path) -> None: + artifact_root = tmp_path / "artifacts" + trace = artifact_root / "trial-1" / "trace.jsonl" + trace.parent.mkdir(parents=True) + trace.write_text('{"span":"ok"}\n', encoding="utf-8") + + archive = tmp_path / "result.tar.gz" + create_result_archive(_completed_result(trace), artifact_root, archive) + + materialized = materialize_result_archive(archive, tmp_path / "materialized") + materialized_trace_ref = materialized.trials[0].trace + assert materialized_trace_ref is not None + materialized_trace = Path(materialized_trace_ref.uri.removeprefix("file://")) + assert materialized_trace.read_text(encoding="utf-8") == '{"span":"ok"}\n' + + +def test_result_archive_enforces_uncompressed_size_limit(tmp_path: Path) -> None: + artifact_root = tmp_path / "artifacts" + trace = artifact_root / "trial-1" / "trace.jsonl" + trace.parent.mkdir(parents=True) + trace.write_text("large trace", encoding="utf-8") + + with pytest.raises(ValueError, match="uncompressed bytes"): + create_result_archive( + _completed_result(trace), + artifact_root, + tmp_path / "result.tar.gz", + max_bytes=1, + ) + + +def test_result_archive_bundles_allowed_dataset_resources(tmp_path: Path) -> None: + artifact_root = tmp_path / "artifacts" + trace = artifact_root / "trial-1" / "trace.jsonl" + trace.parent.mkdir(parents=True) + trace.write_text('{"span":"ok"}\n', encoding="utf-8") + dataset_root = tmp_path / "dataset" + verifier = dataset_root / "task-a" / "tests" + verifier.mkdir(parents=True) + (verifier / "test.sh").write_text("#!/bin/sh\n", encoding="utf-8") + result = _completed_result(trace) + result.trials[0].metrics["reward"] = MetricResult( + name="reward", + value=1.0, + spec=MetricSpec( + name="reward", + description="Harbor verifier reward.", + ref=ResourceRef(uri=verifier.as_uri()), + ), + ) + + archive = tmp_path / "result.tar.gz" + create_result_archive( + result, + artifact_root, + archive, + additional_resource_roots={"dataset": dataset_root}, + ) + materialized = materialize_result_archive(archive, tmp_path / "materialized") + + metric_spec = materialized.trials[0].metrics["reward"].spec + assert metric_spec is not None + metric_ref = metric_spec.ref + assert metric_ref is not None + metric_path = Path(metric_ref.uri.removeprefix("file://")) + assert (metric_path / "test.sh").read_text(encoding="utf-8") == "#!/bin/sh\n" + + +def test_factory_selects_remote_harbor_evaluator(tmp_path: Path) -> None: + evaluator = EvaluatorFactory().build_evaluator( + "harbor", + {"bridge_url": "http://bridge.test:8765"}, + experiment_dir=tmp_path, + ) + + assert isinstance(evaluator, RemoteHarborEvaluator) + assert evaluator.options == RemoteHarborEvaluatorConfig.model_validate({"bridge_url": "http://bridge.test:8765"}) + + +def test_factory_selects_remote_harbor_evaluator_from_environment( + tmp_path: Path, + monkeypatch: pytest.MonkeyPatch, +) -> None: + monkeypatch.setenv("NEMO_EXPERIMENTALIST_HARBOR_BRIDGE_URL", "http://bridge.test:8765") + + evaluator = EvaluatorFactory().build_evaluator("harbor", {}, experiment_dir=tmp_path) + + assert isinstance(evaluator, RemoteHarborEvaluator) + assert evaluator.options == RemoteHarborEvaluatorConfig.model_validate({"bridge_url": "http://bridge.test:8765"}) + + +def test_remote_evaluator_replaces_local_harbor_dependency_runtime(tmp_path: Path) -> None: + registered, _catalog = _registered_dataset(tmp_path) + task_dir = registered.dataset_path / "task-1" + dataset = HarborDataset( + id="dataset", + source=ResourceRef(uri=registered.dataset_path.as_uri()), + tasks=[ + Task( + id="task-1", + uri=task_dir.as_uri(), + dependencies=HarborDependencyRuntime( + task_path=ResourceRef(uri=task_dir.as_uri()), + force_build=False, + run_healthcheck=False, + build_timeout_sec=120, + ), + ) + ], + ) + evaluator = RemoteHarborEvaluator( + RemoteHarborEvaluatorConfig(bridge_url="http://bridge.test:8765"), + experiment_dir=tmp_path, + ) + + assert evaluator.prepare_dataset(dataset) is dataset + runtime = dataset.tasks[0].dependencies + assert isinstance(runtime, RemoteHarborDependencyRuntime) + assert runtime.task_path.uri == task_dir.as_uri() + assert runtime.envelope_id == registered.manifest.envelope_id + assert runtime.envelope_digest == registered.manifest.envelope_digest + assert runtime.base_task_id == "task-1" + assert runtime.force_build is False + assert runtime.run_healthcheck is False + assert runtime.build_timeout_sec == 120 + assert runtime.start is None + assert runtime.readiness is None + assert runtime.stop is None + + +@pytest.mark.parametrize( + ("runtime_options", "match"), + [ + ({"environment_type": "podman"}, "environment_type='docker'"), + ({"delete": False}, "delete=true"), + ({"start": CommandSpec(argv=["echo", "unsupported"])}, "custom lifecycle commands"), + ], +) +def test_remote_evaluator_rejects_unsupported_dependency_runtime_options( + tmp_path: Path, + runtime_options: dict[str, object], + match: str, +) -> None: + task_dir = tmp_path / "task-1" + task_dir.mkdir() + dataset = HarborDataset( + id="dataset", + source=ResourceRef(uri=tmp_path.as_uri()), + tasks=[ + Task( + id="task-1", + dependencies=HarborDependencyRuntime( + task_path=ResourceRef(uri=task_dir.as_uri()), + **runtime_options, + ), + ) + ], + ) + evaluator = RemoteHarborEvaluator( + RemoteHarborEvaluatorConfig(bridge_url="http://bridge.test:8765"), + experiment_dir=tmp_path, + ) + + with pytest.raises(DependencyRuntimeError, match=match): + evaluator.prepare_dataset(dataset) + + +def test_remote_evaluator_rejects_non_harbor_dependency_runtime(tmp_path: Path) -> None: + dataset = HarborDataset( + id="dataset", + source=ResourceRef(uri=tmp_path.as_uri()), + tasks=[ + Task( + id="task-1", + dependencies=DependencyRuntime(start=CommandSpec(argv=["docker", "run", "untrusted"])), + ) + ], + ) + evaluator = RemoteHarborEvaluator( + RemoteHarborEvaluatorConfig(bridge_url="http://bridge.test:8765"), + experiment_dir=tmp_path, + ) + + with pytest.raises(DependencyRuntimeError, match="will not run unsupported task dependencies locally"): + evaluator.prepare_dataset(dataset) + + +@pytest.mark.asyncio +async def test_remote_dependency_runtime_starts_executes_and_stops( + tmp_path: Path, + monkeypatch: pytest.MonkeyPatch, +) -> None: + task_dir = tmp_path / "task-1" + task_dir.mkdir() + (task_dir / "task.toml").write_text("", encoding="utf-8") + requests: list[tuple[str, str]] = [] + + async def handler(request: httpx.Request) -> httpx.Response: + body = await request.aread() + requests.append((request.method, request.url.path)) + assert request.headers["authorization"] == "Bearer dependency-token" + if request.url.path == "/v1/dependencies": + payload = json.loads(parse_qs(body.decode())["request"][0]) + assert payload["task_id"] == "task-1" + assert payload["base_task_id"] == "task-1" + assert payload["envelope_id"] == "envelope-1" + assert b'name="task"' not in body + assert b"docker.sock" not in body + return httpx.Response( + 201, + json={ + "session_id": "dependency-session-1", + "capability_token": "session-capability-token", + }, + ) + if request.url.path == "/v1/dependencies/dependency-session-1/exec": + assert request.headers["x-nemo-dependency-capability"] == "session-capability-token" + assert b'"command":"pwd"' in body + return httpx.Response( + 200, + json={"stdout": "/app\n", "stderr": "", "returncode": 0}, + ) + if request.url.path == "/v1/dependencies/dependency-session-1": + assert request.headers["x-nemo-dependency-capability"] == "session-capability-token" + return httpx.Response(204) + raise AssertionError(f"unexpected request: {request.method} {request.url}") + + monkeypatch.chdir(tmp_path) + monkeypatch.setenv("BRIDGE_TOKEN", "dependency-token") + runtime = RemoteHarborDependencyRuntime( + task_id="task-1", + base_task_id="task-1", + envelope_id="envelope-1", + envelope_digest=_DIGEST, + task_path=ResourceRef(uri=task_dir.as_uri()), + bridge_url="http://bridge.test:8765", + bridge_token_env="BRIDGE_TOKEN", + ) + async with httpx.AsyncClient(transport=httpx.MockTransport(handler)) as client: + runtime._client = client + async with runtime.context() as entered: + assert isinstance(entered, RemoteHarborDependencyRuntime) + assert entered is not runtime + result = await entered.execute("pwd") + + assert result.stdout == "/app\n" + assert result.returncode == 0 + assert requests == [ + ("POST", "/v1/dependencies"), + ("POST", "/v1/dependencies/dependency-session-1/exec"), + ("DELETE", "/v1/dependencies/dependency-session-1"), + ] + assert runtime._session_id is None + assert not list((tmp_path / "tmp" / "harbor-bridge").glob("*")) + + first_context = runtime.context() + second_context = runtime.context() + assert first_context._runtime is not second_context._runtime + + +@pytest.mark.asyncio +async def test_dependency_session_manager_executes_inside_environment_and_tracks_cwd( + tmp_path: Path, + monkeypatch: pytest.MonkeyPatch, +) -> None: + class FakeExecResult: + stdout: str + stderr = None + return_code = 0 + + def __init__(self, stdout: str) -> None: + self.stdout = stdout + + class FakeContext: + calls: list[tuple[str, str | None, int | None]] = [] + stopped = False + + async def __aenter__(self): + return None + + async def __aexit__(self, exc_type, exc, traceback): + self.stopped = True + return False + + async def execute(self, command: str, *, cwd: str | None, timeout_sec: int | None): + self.calls.append((command, cwd, timeout_sec)) + marker_prefix = "__NEMO_DEPENDENCY_CWD_" + marker_start = command.index(marker_prefix) + marker_end = command.index("__", marker_start + len(marker_prefix)) + 2 + marker = command[marker_start:marker_end] + return FakeExecResult(f"command output\n\x1e{marker}/workspace\x1e") + + context = FakeContext() + monkeypatch.setattr(dependency_module, "_harden_task", lambda task_dir: None) + monkeypatch.setattr( + dependency_module, + "HarborDependencyContext", + lambda runtime, temp_root: context, + ) + task_dir = tmp_path / "task-a" + task_dir.mkdir() + manager = dependency_module.HarborDependencySessionManager(max_concurrent_sessions=1) + session_id = await manager.start( + HarborDependencyRequest( + request_id="dependency-task-a", + envelope_id="envelope-1", + envelope_digest=_DIGEST, + task_id="task-a", + base_task_id="task-a", + ), + task_dir=task_dir, + ) + + first = await manager.execute( + session_id, + HarborDependencyExecRequest(command="cd /workspace", timeout_sec=12), + ) + second = await manager.execute( + session_id, + HarborDependencyExecRequest(command="pwd"), + ) + await manager.stop(session_id) + + assert first.stdout == "command output\n" + assert second.stdout == "command output\n" + assert context.calls[0][1:] == ("/app", 12) + assert context.calls[1][1] == "/workspace" + assert context.stopped + + +def test_dependency_output_is_bounded() -> None: + value = "x" * (DEPENDENCY_OUTPUT_LIMIT_CHARS + 1) + truncated = dependency_module._truncate_output(value, stream="output") + + assert truncated.endswith("... (output truncated)") + assert len(truncated) <= DEPENDENCY_OUTPUT_LIMIT_CHARS + 64 + + +@pytest.mark.asyncio +async def test_remote_evaluator_submits_bundles_and_materializes_results( + tmp_path: Path, + monkeypatch: pytest.MonkeyPatch, +) -> None: + agent = tmp_path / "agent" + agent.mkdir() + (agent / "main.py").write_text("print('candidate')\n", encoding="utf-8") + registered, _catalog = _registered_dataset(tmp_path) + dataset_path = registered.dataset_path + task_path = dataset_path / "task-1" + dataset = HarborDataset( + id="dataset", + source=ResourceRef(uri=dataset_path.as_uri()), + tasks=[Task(id="task-1", uri=task_path.as_uri())], + ) + + async def validate() -> None: + return None + + monkeypatch.setattr(dataset, "validate", validate) + + bridge_artifacts = tmp_path / "bridge-artifacts" + trace = bridge_artifacts / "trial-1" / "trace.jsonl" + trace.parent.mkdir(parents=True) + trace.write_text('{"span":"bridge"}\n', encoding="utf-8") + response_archive = tmp_path / "bridge-response.tar.gz" + create_result_archive(_completed_result(trace), bridge_artifacts, response_archive) + + async def handler(request: httpx.Request) -> httpx.Response: + body = await request.aread() + assert request.headers["authorization"] == "Bearer test-token" + assert request.url == httpx.URL("http://bridge.test:8765/v1/evaluations") + assert b'"tasks":[{"task_id":"task-1","base_task_id":"task-1"}]' in body + assert b'"envelope_id":"' + registered.manifest.envelope_id.encode() + b'"' in body + assert b'name="dataset"' not in body + assert b"import_path" not in body + assert b"docker.sock" not in body + return httpx.Response( + 200, + headers={"content-type": "application/gzip"}, + content=response_archive.read_bytes(), + ) + + monkeypatch.setenv("NEMO_EXPERIMENTALIST_HARBOR_BRIDGE_TOKEN", "test-token") + async with httpx.AsyncClient(transport=httpx.MockTransport(handler)) as client: + evaluator = RemoteHarborEvaluator( + RemoteHarborEvaluatorConfig.model_validate( + { + "bridge_url": "http://bridge.test:8765", + "force_rerun": True, + } + ), + experiment_dir=tmp_path / "experiment", + client=client, + ) + trials = await evaluator._run(agent, dataset, evaluator.options) + + assert trials[0].status == "completed" + assert trials[0].trace is not None + local_trace = Path(trials[0].trace.uri.removeprefix("file://")) + assert local_trace.read_text(encoding="utf-8") == '{"span":"bridge"}\n' + + +def test_candidate_agent_import_uses_trusted_code(tmp_path: Path) -> None: + candidate = _candidate(tmp_path / "candidate") + (candidate / "harbor_wrapper.py").write_text("raise RuntimeError('candidate code imported')\n", encoding="utf-8") + + with candidate_agent_import(candidate) as import_path: + module_name, class_name = import_path.split(":") + adapter = getattr(importlib.import_module(module_name), class_name) + + assert issubclass(adapter, TrustedCandidateAgent) + assert adapter.candidate_dir == candidate.resolve() + + assert module_name not in sys.modules + + +def test_harden_task_forces_separate_verifier(tmp_path: Path) -> None: + task_dir = tmp_path / "task-a" + task_dir.mkdir() + (task_dir / "task.toml").write_text("", encoding="utf-8") + _complete_task_files(task_dir) + + _harden_task(task_dir) + + assert HarborTask(task_dir).config.verifier.environment_mode == VerifierEnvironmentMode.SEPARATE + + +def test_harden_task_requires_separate_verifier_definition(tmp_path: Path) -> None: + task_dir = tmp_path / "task-a" + task_dir.mkdir() + (task_dir / "task.toml").write_text("", encoding="utf-8") + (task_dir / "instruction.md").write_text("Do the task.\n", encoding="utf-8") + tests_dir = task_dir / "tests" + tests_dir.mkdir() + (tests_dir / "test.sh").write_text("#!/bin/sh\nexit 0\n", encoding="utf-8") + + with pytest.raises(ValueError, match="separate verifier requires tests/Dockerfile"): + _harden_task(task_dir) + + +@pytest.mark.parametrize( + ("relative_path", "content"), + [ + ("environment/compose.yaml", "services: {}\n"), + ("task.toml", '[environment.env]\nSECRET = "${HOST_SECRET}"\n'), + ], +) +def test_harden_task_accepts_host_registered_runtime_configuration( + tmp_path: Path, + relative_path: str, + content: str, +) -> None: + task_dir = tmp_path / "task-a" + task_dir.mkdir() + (task_dir / "task.toml").write_text("", encoding="utf-8") + _complete_task_files(task_dir) + target = task_dir / relative_path + target.parent.mkdir(parents=True, exist_ok=True) + target.write_text(content, encoding="utf-8") + + _harden_task(task_dir) + + +def test_trusted_envelope_rejects_runtime_overlay(tmp_path: Path) -> None: + registered, catalog = _registered_dataset(tmp_path, mutable=True) + overlay = tmp_path / "overlay" + malicious = overlay / "task-derived" / "environment" / "Dockerfile" + malicious.parent.mkdir(parents=True) + malicious.write_text("FROM malicious\n", encoding="utf-8") + + with pytest.raises(ValueError, match="runtime-control file"): + catalog.materialize( + envelope_id=registered.manifest.envelope_id, + envelope_digest=registered.manifest.envelope_digest, + selections=[EnvelopeTaskSelection(task_id="task-derived", base_task_id="task-1")], + destination=tmp_path / "materialized", + overlay_dir=overlay, + ) + + +@pytest.mark.asyncio +async def test_bridge_service_authenticates_and_returns_materialized_result(tmp_path: Path) -> None: + class RecordingRunner: + requests: list[HarborBridgeRequest] = [] + + async def run( + self, + request: HarborBridgeRequest, + *, + candidate_dir: Path, + dataset_dir: Path, + work_dir: Path, + ) -> EvaluationResult: + self.requests.append(request) + assert (candidate_dir / "main.py").read_text(encoding="utf-8") == "print('candidate')\n" + assert (dataset_dir / "task-1" / "task.toml").is_file() + trace = work_dir / "results" / "trial-1" / "trace.jsonl" + trace.parent.mkdir(parents=True) + trace.write_text('{"span":"service"}\n', encoding="utf-8") + return _completed_result(trace) + + candidate = _candidate(tmp_path / "candidate") + registered, catalog = _registered_dataset(tmp_path) + candidate_archive = tmp_path / "candidate.tar.gz" + create_directory_archive(candidate, candidate_archive) + + runner = RecordingRunner() + storage_root = tmp_path / "bridge-work" + app = create_app( + settings=HarborBridgeSettings( + storage_root=storage_root, + catalog_root=catalog.root, + token="test-token-is-long-enough", + ), + runner=runner, + catalog=catalog, + ) + transport = httpx.ASGITransport(app=app) + async with httpx.AsyncClient(transport=transport, base_url="http://bridge.test") as client: + unauthorized = await client.post("/v1/evaluations") + assert unauthorized.status_code == 401 + + with candidate_archive.open("rb") as candidate_file: + response = await client.post( + "/v1/evaluations", + headers={"authorization": "Bearer test-token-is-long-enough"}, + data={ + "request": HarborBridgeRequest( + request_id="request-1", + envelope_id=registered.manifest.envelope_id, + envelope_digest=registered.manifest.envelope_digest, + tasks=[EnvelopeTaskSelection(task_id="task-1", base_task_id="task-1")], + candidate_digest=transport_tree_digest(candidate), + ).model_dump_json() + }, + files={ + "candidate": ("candidate.tar.gz", candidate_file, "application/gzip"), + }, + ) + with candidate_archive.open("rb") as candidate_file, candidate_archive.open("rb") as legacy_dataset: + legacy = await client.post( + "/v1/evaluations", + headers={"authorization": "Bearer test-token-is-long-enough"}, + data={ + "request": HarborBridgeRequest( + request_id="request-legacy", + envelope_id=registered.manifest.envelope_id, + envelope_digest=registered.manifest.envelope_digest, + tasks=[EnvelopeTaskSelection(task_id="task-1", base_task_id="task-1")], + candidate_digest=transport_tree_digest(candidate), + ).model_dump_json() + }, + files={ + "candidate": ("candidate.tar.gz", candidate_file, "application/gzip"), + "dataset": ("dataset.tar.gz", legacy_dataset, "application/gzip"), + }, + ) + + assert response.status_code == 200 + assert legacy.status_code == 422 + assert "dataset" in legacy.text + response_archive = tmp_path / "response.tar.gz" + response_archive.write_bytes(response.content) + result = materialize_result_archive(response_archive, tmp_path / "materialized") + assert result.trials[0].trace is not None + trace = Path(result.trials[0].trace.uri.removeprefix("file://")) + assert trace.read_text(encoding="utf-8") == '{"span":"service"}\n' + assert runner.requests == [ + HarborBridgeRequest( + request_id="request-1", + envelope_id=registered.manifest.envelope_id, + envelope_digest=registered.manifest.envelope_digest, + tasks=[EnvelopeTaskSelection(task_id="task-1", base_task_id="task-1")], + candidate_digest=transport_tree_digest(candidate), + ) + ] + assert list(storage_root.iterdir()) == [] + + +@pytest.mark.asyncio +async def test_bridge_service_owns_dependency_session_lifecycle(tmp_path: Path) -> None: + class RecordingDependencySessions: + starts: list[HarborDependencyRequest] = [] + commands: list[tuple[str, HarborDependencyExecRequest]] = [] + stops: list[str] = [] + + async def start(self, request: HarborDependencyRequest, *, task_dir: Path) -> str: + self.starts.append(request) + assert (task_dir / "task.toml").is_file() + return "dependency-session-1" + + async def execute( + self, + session_id: str, + request: HarborDependencyExecRequest, + ) -> HarborDependencyExecResponse: + self.commands.append((session_id, request)) + return HarborDependencyExecResponse(stdout="/app\n", returncode=0) + + async def stop(self, session_id: str) -> None: + self.stops.append(session_id) + + async def close(self) -> None: + return None + + registered, catalog = _registered_dataset(tmp_path) + legacy_task_archive = tmp_path / "legacy-task.tar.gz" + create_directory_archive(registered.dataset_path / "task-1", legacy_task_archive) + + sessions = RecordingDependencySessions() + storage_root = tmp_path / "bridge-work" + app = create_app( + settings=HarborBridgeSettings( + storage_root=storage_root, + catalog_root=catalog.root, + token="test-token-is-long-enough", + ), + dependency_sessions=sessions, + catalog=catalog, + ) + transport = httpx.ASGITransport(app=app) + headers = {"authorization": "Bearer test-token-is-long-enough"} + async with httpx.AsyncClient(transport=transport, base_url="http://bridge.test") as client: + started = await client.post( + "/v1/dependencies", + headers=headers, + data={ + "request": HarborDependencyRequest( + request_id="dependency-task-a", + envelope_id=registered.manifest.envelope_id, + envelope_digest=registered.manifest.envelope_digest, + task_id="task-1", + base_task_id="task-1", + ).model_dump_json() + }, + ) + with legacy_task_archive.open("rb") as legacy_task: + legacy = await client.post( + "/v1/dependencies", + headers=headers, + data={ + "request": HarborDependencyRequest( + request_id="dependency-legacy", + envelope_id=registered.manifest.envelope_id, + envelope_digest=registered.manifest.envelope_digest, + task_id="task-1", + base_task_id="task-1", + ).model_dump_json() + }, + files={"task": ("task.tar.gz", legacy_task, "application/gzip")}, + ) + missing = await client.post( + "/v1/dependencies/dependency-session-1/exec", + headers=headers, + json=HarborDependencyExecRequest(command="pwd").model_dump(), + ) + denied = await client.post( + "/v1/dependencies/dependency-session-1/exec", + headers={**headers, "X-Nemo-Dependency-Capability": "wrong-capability-token"}, + json=HarborDependencyExecRequest(command="pwd").model_dump(), + ) + capability = started.json()["capability_token"] + executed = await client.post( + "/v1/dependencies/dependency-session-1/exec", + headers={**headers, "X-Nemo-Dependency-Capability": capability}, + json=HarborDependencyExecRequest(command="pwd").model_dump(), + ) + stopped = await client.delete( + "/v1/dependencies/dependency-session-1", + headers={**headers, "X-Nemo-Dependency-Capability": capability}, + ) + + assert started.status_code == 201 + assert legacy.status_code == 422 + assert "task" in legacy.text + assert started.json()["session_id"] == "dependency-session-1" + assert len(started.json()["capability_token"]) >= 16 + assert missing.status_code == 403 + assert denied.status_code == 403 + assert executed.status_code == 200 + assert executed.json() == {"stdout": "/app\n", "stderr": "", "returncode": 0} + assert stopped.status_code == 204 + assert sessions.starts == [ + HarborDependencyRequest( + request_id="dependency-task-a", + envelope_id=registered.manifest.envelope_id, + envelope_digest=registered.manifest.envelope_digest, + task_id="task-1", + base_task_id="task-1", + ) + ] + assert sessions.commands == [ + ( + "dependency-session-1", + HarborDependencyExecRequest(command="pwd"), + ) + ] + assert sessions.stops == ["dependency-session-1"] + assert list(storage_root.iterdir()) == [] diff --git a/plugins/nemo-experimentalist/tests/test_openshell_assets.py b/plugins/nemo-experimentalist/tests/test_openshell_assets.py new file mode 100644 index 0000000000..380e6eb486 --- /dev/null +++ b/plugins/nemo-experimentalist/tests/test_openshell_assets.py @@ -0,0 +1,323 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 + +import os +import subprocess +from pathlib import Path + +import yaml + +PLUGIN_ROOT = Path(__file__).resolve().parents[1] +REPO_ROOT = PLUGIN_ROOT.parents[1] +OPENSHELL_ROOT = PLUGIN_ROOT / "src" / "nemo_experimentalist_plugin" / "openshell" +POLICY_PATH = OPENSHELL_ROOT / "policy.yaml" +DOCKER_DESKTOP_POLICY_PATH = OPENSHELL_ROOT / "policy.docker-desktop.yaml" +LAUNCHER_PATH = OPENSHELL_ROOT / "launcher.py" +RUNNER_PATH = OPENSHELL_ROOT / "run.sh" +FULL_RUN_SMOKE_PATH = OPENSHELL_ROOT / "smoke-full-run.sh" +PROVIDER_SETUP_PATH = OPENSHELL_ROOT / "configure-providers.sh" +ASKPASS_PATH = OPENSHELL_ROOT / "git-askpass.sh" +PROVIDER_PROFILE_DIR = OPENSHELL_ROOT / "provider-profiles" +DOCKERFILE_PATH = PLUGIN_ROOT / "Dockerfile" +DOCKER_BAKE_PATH = REPO_ROOT / "docker-bake.hcl" + + +def test_openshell_policy_fails_closed_without_docker_access() -> None: + policy = yaml.safe_load(POLICY_PATH.read_text(encoding="utf-8")) + + assert policy["landlock"]["compatibility"] == "hard_requirement" + assert policy["process"] == {"run_as_user": "sandbox", "run_as_group": "sandbox"} + assert "/dev/urandom" in policy["filesystem_policy"]["read_only"] + serialized = POLICY_PATH.read_text(encoding="utf-8").lower() + assert "docker.sock" not in serialized + assert "docker_host" not in serialized + assert set(policy["network_policies"]) == {"nemo_platform"} + endpoint = policy["network_policies"]["nemo_platform"]["endpoints"][0] + assert "access" not in endpoint + assert endpoint["rules"] == [ + {"allow": {"method": "GET", "path": "/health/ready"}}, + {"allow": {"method": "GET", "path": "/apis/intake/v2/workspaces/**"}}, + {"allow": {"method": "POST", "path": "/apis/intake/v2/workspaces/**"}}, + {"allow": {"method": "PUT", "path": "/apis/intake/v2/workspaces/**"}}, + {"allow": {"method": "GET", "path": "/apis/insights/v2/workspaces/**"}}, + ] + binaries = {item["path"] for item in policy["network_policies"]["nemo_platform"]["binaries"]} + assert "/usr/local/bin/python3.13" in binaries + + +def test_docker_desktop_policy_is_an_explicit_landlock_fallback() -> None: + strict = yaml.safe_load(POLICY_PATH.read_text(encoding="utf-8")) + development = yaml.safe_load(DOCKER_DESKTOP_POLICY_PATH.read_text(encoding="utf-8")) + + assert development["landlock"]["compatibility"] == "best_effort" + assert development["filesystem_policy"] == strict["filesystem_policy"] + assert development["process"] == strict["process"] + assert development["network_policies"] == strict["network_policies"] + + +def test_experimentalist_image_has_no_docker_client_or_socket() -> None: + dockerfile = DOCKERFILE_PATH.read_text(encoding="utf-8") + docker_bake = DOCKER_BAKE_PATH.read_text(encoding="utf-8") + + assert "iproute2" in dockerfile + assert "nftables" in dockerfile + assert "gh" in dockerfile + assert "glab" in dockerfile + assert "nemo-experimentalist-git-askpass" in dockerfile + assert "touch /etc/nemo-experimentalist-container" in dockerfile + assert "USER sandbox" in dockerfile + assert 'com.nvidia.nemo.experimentalist.openshell-runtime="1"' in dockerfile + assert "docker.sock" not in dockerfile + assert "docker-ce-cli" not in dockerfile + assert 'dockerfile = "plugins/nemo-experimentalist/Dockerfile"' in docker_bake + + +def test_openshell_launcher_uses_policy_and_inference_route() -> None: + runner = RUNNER_PATH.read_text(encoding="utf-8") + + assert '--policy "$policy_path"' in runner + assert "command -v openshell" in runner + assert "EXPERIMENTALIST_API_BASE=https://inference.local/v1" in runner + assert "host.docker.internal:8080" in runner + assert 'sandbox_name="${NEMO_EXPERIMENTALIST_SANDBOX_NAME:-nemo-exp-$$}"' in runner + assert "NEMO_EXPERIMENTALIST_POLICY_MODE" in runner + assert "policy.docker-desktop.yaml" in runner + assert '--provider "$bridge_provider"' in runner + assert 'source_control="${NEMO_EXPERIMENTALIST_SOURCE_CONTROL:-none}"' in runner + assert 'create_args+=(--provider "$source_provider")' in runner + assert "github-read | github-publish | gitlab-read | gitlab-publish" in runner + assert "NEMO_EXPERIMENTALIST_INFERENCE_PROVIDER" not in runner + assert "NEMO_EXPERIMENTALIST_HARBOR_BRIDGE_URL" in runner + assert "NEMO_EXPERIMENTALIST_HARBOR_ENVELOPE_CATALOG" in runner + assert 'create_args+=(--upload "$envelope_catalog:$remote_workspace/$catalog_relative")' in runner + assert "Trusted Harbor envelope catalog must be inside the uploaded workspace" in runner + assert "GIT_ASKPASS=/usr/local/bin/nemo-experimentalist-git-askpass" in runner + assert "GIT_TERMINAL_PROMPT=0" in runner + assert "GH_PROMPT_DISABLED=1" in runner + assert "GLAB_NO_PROMPT=1" in runner + assert 'create_args+=(--env "GITLAB_HOST=$gitlab_host")' in runner + assert 'glab config set token "$GITLAB_TOKEN" --host "$GITLAB_HOST"' in runner + assert 'glab config set git_protocol https --host "$GITLAB_HOST"' in runner + assert 'remote_workspace="/sandbox/project/$(basename "$workspace_dir")"' in runner + assert "/app/.venv/bin/nemo experimentalist" in runner + assert "--runtime" not in runner + assert "local/nmp-experimentalist:local" in runner + assert "--no-git-ignore" not in runner + assert "command -v docker" in runner + assert "/var/run/docker.sock" in runner + assert LAUNCHER_PATH.is_file() + + +def test_provider_setup_imports_scoped_profiles_and_keeps_inference_on_gateway() -> None: + setup = PROVIDER_SETUP_PATH.read_text(encoding="utf-8") + + assert "provider profile lint" in setup + assert "provider profile import" in setup + assert "provider profile delete" in setup + assert "providers_v2_enabled" in setup + assert "NEMO_EXPERIMENTALIST_GITLAB_HOST" in setup + assert "host: gitlab\\\\.com" in setup + assert "nemo-experimentalist-harbor-bridge" in setup + assert "nemo-experimentalist-github-read" in setup + assert "nemo-experimentalist-github-publish" in setup + assert "nemo-experimentalist-gitlab-read" in setup + assert "nemo-experimentalist-gitlab-publish" in setup + assert "openshell inference set" in setup + assert "--from-existing" in setup + assert "NVIDIA_BASE_URL=https://inference-api.nvidia.com/v1" in setup + assert '--credential "$credential_env"' in setup + + +def test_provider_setup_deletes_platform_scoped_profiles(tmp_path: Path) -> None: + fake_bin = tmp_path / "bin" + fake_bin.mkdir() + openshell_log = tmp_path / "openshell.log" + fake_openshell = fake_bin / "openshell" + fake_openshell.write_text( + """#!/usr/bin/env bash +set -euo pipefail +printf '%s\\n' "$*" >>"$FAKE_OPENSHELL_LOG" +if [[ "$1 $2" == "provider get" ]]; then + exit 1 +fi +if [[ "$1 $2 $3" == "provider profile export" ]]; then + printf 'id: %s\\nscope: platform\\n' "$4" +fi +""", + encoding="utf-8", + ) + fake_openshell.chmod(0o755) + + result = subprocess.run( + ["bash", str(PROVIDER_SETUP_PATH)], + check=False, + capture_output=True, + text=True, + env=os.environ + | { + "FAKE_OPENSHELL_LOG": str(openshell_log), + "NEMO_EXPERIMENTALIST_HARBOR_BRIDGE_TOKEN": "bridge-placeholder", + "NEMO_EXPERIMENTALIST_PROVIDER_PROFILE_DIR": str(tmp_path / "profiles"), + "PATH": f"{fake_bin}:/usr/bin:/bin", + }, + ) + + assert result.returncode == 0, result.stderr + log = openshell_log.read_text(encoding="utf-8") + for profile_path in PROVIDER_PROFILE_DIR.glob("*.yaml"): + assert f"provider profile delete --global {profile_path.stem}" in log + + +def test_provider_setup_derives_raw_inference_hub_model_id(tmp_path: Path) -> None: + fake_bin = tmp_path / "bin" + fake_bin.mkdir() + openshell_log = tmp_path / "openshell.log" + fake_openshell = fake_bin / "openshell" + fake_openshell.write_text( + """#!/usr/bin/env bash +set -euo pipefail +printf '%s\\n' "$*" >>"$FAKE_OPENSHELL_LOG" +if [[ "$1 $2" == "provider get" || "$1 $2 $3" == "provider profile export" ]]; then + exit 1 +fi +""", + encoding="utf-8", + ) + fake_openshell.chmod(0o755) + env = os.environ.copy() + env.pop("NEMO_EXPERIMENTALIST_INFERENCE_MODEL", None) + env |= { + "EXPERIMENTALIST_SMART_MODEL_NAME": "openai/aws/anthropic/claude-haiku-4-5-v1", + "FAKE_OPENSHELL_LOG": str(openshell_log), + "NEMO_EXPERIMENTALIST_HARBOR_BRIDGE_TOKEN": "bridge-placeholder", + "NEMO_EXPERIMENTALIST_PROVIDER_PROFILE_DIR": str(tmp_path / "profiles"), + "PATH": f"{fake_bin}:/usr/bin:/bin", + } + + result = subprocess.run( + ["bash", str(PROVIDER_SETUP_PATH)], + check=False, + capture_output=True, + text=True, + env=env, + ) + + assert result.returncode == 0, result.stderr + log = openshell_log.read_text(encoding="utf-8") + assert "inference set --provider nemo-experimentalist-inference --model aws/anthropic/claude-haiku-4-5-v1" in log + + +def test_source_control_profiles_separate_read_and_publish_authority() -> None: + profiles = { + path.stem: yaml.safe_load(path.read_text(encoding="utf-8")) for path in PROVIDER_PROFILE_DIR.glob("*.yaml") + } + + assert set(profiles) == { + "nemo-experimentalist-github-publish", + "nemo-experimentalist-github-read", + "nemo-experimentalist-gitlab-publish", + "nemo-experimentalist-gitlab-read", + "nemo-experimentalist-harbor-bridge", + } + for name, profile in profiles.items(): + assert profile["id"] == name + + github_read = profiles["nemo-experimentalist-github-read"] + github_publish = profiles["nemo-experimentalist-github-publish"] + github_read_git = next(endpoint for endpoint in github_read["endpoints"] if endpoint["host"] == "github.com") + github_publish_git = next(endpoint for endpoint in github_publish["endpoints"] if endpoint["host"] == "github.com") + github_read_posts = { + rule["allow"]["path"] for rule in github_read_git["rules"] if rule["allow"]["method"] == "POST" + } + github_publish_posts = { + rule["allow"]["path"] for rule in github_publish_git["rules"] if rule["allow"]["method"] == "POST" + } + assert github_read_posts == {"/**/git-upload-pack"} + assert github_publish_posts == {"/**/git-upload-pack", "/**/git-receive-pack"} + + github_read_graphql = next(endpoint for endpoint in github_read["endpoints"] if endpoint["protocol"] == "graphql") + github_publish_graphql = next( + endpoint for endpoint in github_publish["endpoints"] if endpoint["protocol"] == "graphql" + ) + assert {rule["allow"]["operation_type"] for rule in github_read_graphql["rules"]} == {"query"} + assert github_publish_graphql["rules"][-1]["allow"] == { + "operation_type": "mutation", + "operation_name": "PullRequestCreate*", + } + + gitlab_read = profiles["nemo-experimentalist-gitlab-read"] + gitlab_publish = profiles["nemo-experimentalist-gitlab-publish"] + gitlab_read_posts = { + rule["allow"]["path"] for rule in gitlab_read["endpoints"][0]["rules"] if rule["allow"]["method"] == "POST" + } + gitlab_publish_posts = { + rule["allow"]["path"] for rule in gitlab_publish["endpoints"][0]["rules"] if rule["allow"]["method"] == "POST" + } + assert gitlab_read_posts == {"/**/git-upload-pack"} + assert gitlab_publish_posts == { + "/**/git-upload-pack", + "/**/git-receive-pack", + "/api/v4/projects/**/merge_requests", + } + + +def test_harbor_bridge_profile_has_only_bounded_evaluation_and_dependency_contracts() -> None: + profile = yaml.safe_load( + (PROVIDER_PROFILE_DIR / "nemo-experimentalist-harbor-bridge.yaml").read_text(encoding="utf-8") + ) + endpoint = profile["endpoints"][0] + + assert endpoint["host"] == "host.docker.internal" + assert endpoint["port"] == 8765 + assert [rule["allow"] for rule in endpoint["rules"]] == [ + {"method": "GET", "path": "/health/ready"}, + {"method": "POST", "path": "/v1/evaluations"}, + {"method": "POST", "path": "/v1/dependencies"}, + {"method": "POST", "path": "/v1/dependencies/*/exec"}, + {"method": "DELETE", "path": "/v1/dependencies/*"}, + ] + + +def test_openshell_shell_assets_parse() -> None: + for path in (RUNNER_PATH, FULL_RUN_SMOKE_PATH, PROVIDER_SETUP_PATH, ASKPASS_PATH): + result = subprocess.run( + ["bash", "-n", str(path)], + check=False, + capture_output=True, + text=True, + ) + assert result.returncode == 0, result.stderr + + +def test_full_run_smoke_invokes_normal_runtime_and_rejects_degraded_analysis() -> None: + smoke = FULL_RUN_SMOKE_PATH.read_text(encoding="utf-8") + + assert '"$nemo_bin" experimentalist run --experiment-dir "$smoke_output" "$@"' in smoke + assert "eval-and-optimize/analysis/round-*.md" in smoke + assert "analysis_error" in smoke + + +def test_git_askpass_uses_provider_placeholders() -> None: + github_env = os.environ | {"GH_TOKEN": "github-placeholder"} + gitlab_env = os.environ | { + "GITLAB_HOST": "gitlab.example.com", + "GITLAB_TOKEN": "gitlab-placeholder", + } + + github = subprocess.run( + ["bash", str(ASKPASS_PATH), "Password for 'https://github.com':"], + check=True, + capture_output=True, + text=True, + env=github_env, + ) + gitlab = subprocess.run( + ["bash", str(ASKPASS_PATH), "Password for 'https://gitlab.example.com':"], + check=True, + capture_output=True, + text=True, + env=gitlab_env, + ) + + assert github.stdout.strip() == "github-placeholder" + assert gitlab.stdout.strip() == "gitlab-placeholder" diff --git a/plugins/nemo-experimentalist/tests/test_openshell_launcher.py b/plugins/nemo-experimentalist/tests/test_openshell_launcher.py new file mode 100644 index 0000000000..5011fb473e --- /dev/null +++ b/plugins/nemo-experimentalist/tests/test_openshell_launcher.py @@ -0,0 +1,242 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 + +import subprocess +from pathlib import Path +from typing import cast + +import pytest +from nemo_experimentalist_plugin.openshell import launcher + +_APPLY_RUNTIME_DEFAULTS = launcher._apply_runtime_defaults +_START_BRIDGE = launcher._start_bridge + + +@pytest.fixture(autouse=True) +def isolate_runtime_services(monkeypatch: pytest.MonkeyPatch) -> None: + """Launcher command tests own subprocess wiring, not bridge/provider internals.""" + monkeypatch.setattr(launcher, "_apply_runtime_defaults", lambda env: None) + monkeypatch.setattr( + launcher, + "_start_bridge", + lambda *, workspace, runtime_env: None, + ) + monkeypatch.setattr(launcher, "_configure_providers", lambda env: None) + + +def _completed( + argv: list[str], + returncode: int = 0, + stdout: str = "", +) -> subprocess.CompletedProcess: + return subprocess.CompletedProcess(argv, returncode, stdout=stdout) + + +def test_custom_image_launches_without_host_docker( + monkeypatch: pytest.MonkeyPatch, + tmp_path: Path, +) -> None: + calls: list[tuple[list[str], dict[str, object]]] = [] + + def which(name: str, *, path: str | None = None) -> str | None: + assert path == "/test/bin" + return "/test/bin/openshell" if name == "openshell" else None + + def run(argv: list[str], **kwargs: object) -> subprocess.CompletedProcess: + calls.append((argv, kwargs)) + return _completed(argv) + + monkeypatch.setattr(launcher.shutil, "which", which) + monkeypatch.setattr(launcher.subprocess, "run", run) + + result = launcher.launch_in_openshell( + "doctor", + ["--insight", "insight-1"], + workspace_dir=tmp_path, + platform_url="http://localhost:8080", + env={ + "PATH": "/test/bin", + launcher.IMAGE_ENV: "registry.example/experimentalist:v1", + }, + ) + + assert result == 0 + assert len(calls) == 1 + argv, kwargs = calls[0] + assert argv == [ + str(Path(launcher.__file__).with_name("run.sh")), + str(tmp_path), + "doctor", + "--insight", + "insight-1", + ] + assert kwargs["env"] == { + "PATH": "/test/bin", + launcher.IMAGE_ENV: "registry.example/experimentalist:v1", + "NMP_BASE_URL": "http://host.docker.internal:8080", + } + + +def test_missing_default_image_builds_for_selected_host_platform( + monkeypatch: pytest.MonkeyPatch, + tmp_path: Path, +) -> None: + repo_root = tmp_path / "repo" + workspace = tmp_path / "workspace" + repo_root.mkdir() + workspace.mkdir() + calls: list[tuple[list[str], dict[str, object]]] = [] + + def which(name: str, *, path: str | None = None) -> str | None: + assert path == "/test/bin" + return f"/test/bin/{name}" + + def run(argv: list[str], **kwargs: object) -> subprocess.CompletedProcess: + calls.append((argv, kwargs)) + return _completed(argv, returncode=1 if argv[1:3] == ["image", "inspect"] else 0) + + monkeypatch.setattr(launcher.shutil, "which", which) + monkeypatch.setattr(launcher.subprocess, "run", run) + monkeypatch.setattr(launcher, "_find_repo_root", lambda *starts: repo_root) + + result = launcher.launch_in_openshell( + "run", + ["--no-insight"], + workspace_dir=workspace, + output_dir=workspace / "output", + env={ + "PATH": "/test/bin", + launcher.PLATFORM_ENV: "linux/arm64", + }, + ) + + assert result == 0 + assert calls[0][0] == [ + "/test/bin/docker", + "image", + "inspect", + "--format", + f'{{{{ index .Config.Labels "{launcher.RUNTIME_IMAGE_LABEL}" }}}}', + launcher.DEFAULT_IMAGE, + ] + assert calls[1][0] == [ + "/test/bin/docker", + "buildx", + "bake", + "nmp-experimentalist-docker", + "--load", + ] + assert calls[1][1]["cwd"] == repo_root + assert calls[1][1]["env"] == { + "PATH": "/test/bin", + launcher.PLATFORM_ENV: "linux/arm64", + launcher.IMAGE_ENV: launcher.DEFAULT_IMAGE, + "IMAGE_REGISTRY": "local", + "BAKE_TAG": "local", + "BUILD_ARCH": "linux/arm64", + } + run_env = cast(dict[str, str], calls[2][1]["env"]) + assert run_env[launcher.OUTPUT_DIR_ENV] == str((workspace / "output").resolve()) + + +def test_compatible_default_image_is_reused( + monkeypatch: pytest.MonkeyPatch, + tmp_path: Path, +) -> None: + calls: list[list[str]] = [] + + def which(name: str, *, path: str | None = None) -> str | None: + assert path == "/test/bin" + return f"/test/bin/{name}" + + def run(argv: list[str], **kwargs: object) -> subprocess.CompletedProcess: + calls.append(argv) + if argv[1:3] == ["image", "inspect"]: + return _completed(argv, stdout=f"{launcher.RUNTIME_IMAGE_API}\n") + return _completed(argv) + + monkeypatch.setattr(launcher.shutil, "which", which) + monkeypatch.setattr(launcher.subprocess, "run", run) + + result = launcher.launch_in_openshell( + "doctor", + [], + workspace_dir=tmp_path, + env={"PATH": "/test/bin"}, + ) + + assert result == 0 + assert len(calls) == 2 + assert calls[0][1:3] == ["image", "inspect"] + assert calls[1][0] == str(Path(launcher.__file__).with_name("run.sh")) + + +def test_missing_openshell_fails_without_local_fallback(tmp_path: Path) -> None: + with pytest.raises(launcher.OpenShellLaunchError, match="default Experimentalist runtime"): + launcher.launch_in_openshell( + "doctor", + [], + workspace_dir=tmp_path, + env={"PATH": ""}, + ) + + +@pytest.mark.parametrize( + ("host_url", "container_url"), + [ + ("http://localhost:8080", "http://host.docker.internal:8080"), + ("https://127.0.0.1/api", "https://host.docker.internal/api"), + ("http://[::1]:9000/ready", "http://host.docker.internal:9000/ready"), + ("https://platform.example/api", "https://platform.example/api"), + ], +) +def test_container_platform_url_rewrites_only_loopback(host_url: str, container_url: str) -> None: + assert launcher._container_platform_url(host_url) == container_url + + +def test_container_platform_url_rejects_invalid_port() -> None: + with pytest.raises(launcher.OpenShellLaunchError, match="Invalid NeMo Platform URL"): + launcher._container_platform_url("http://localhost:not-a-port") + + +def test_runtime_defaults_connect_profile_key_and_select_docker_desktop( + monkeypatch: pytest.MonkeyPatch, +) -> None: + runtime_env = {"INFERENCE_API_KEY": "sk-test"} + monkeypatch.setattr(launcher.platform, "system", lambda: "Darwin") + + _APPLY_RUNTIME_DEFAULTS(runtime_env) + + assert runtime_env["NVIDIA_API_KEY"] == "sk-test" + assert runtime_env["EXPERIMENTALIST_SMART_MODEL_NAME"] == launcher.DEFAULT_SMART_MODEL + assert runtime_env["NEMO_EXPERIMENTALIST_POLICY_MODE"] == "docker-desktop" + + +def test_explicit_ready_bridge_is_reused( + monkeypatch: pytest.MonkeyPatch, + tmp_path: Path, +) -> None: + monkeypatch.setattr(launcher, "_bridge_ready", lambda url: url == "http://127.0.0.1:8765") + runtime_env = { + launcher.BRIDGE_URL_ENV: "http://host.docker.internal:8765", + launcher.BRIDGE_TOKEN_ENV: "secret", + } + + managed = _START_BRIDGE(workspace=tmp_path, runtime_env=runtime_env) + + assert managed is None + + +def test_explicit_bridge_requires_token( + monkeypatch: pytest.MonkeyPatch, + tmp_path: Path, +) -> None: + monkeypatch.setattr(launcher, "_bridge_ready", lambda url: True) + + with pytest.raises(launcher.OpenShellLaunchError, match=launcher.BRIDGE_TOKEN_ENV): + _START_BRIDGE( + workspace=tmp_path, + runtime_env={ + launcher.BRIDGE_URL_ENV: "http://host.docker.internal:8765", + }, + ) diff --git a/plugins/nemo-experimentalist/tests/test_preflight.py b/plugins/nemo-experimentalist/tests/test_preflight.py index 8b3b8b5c37..c27eec714d 100644 --- a/plugins/nemo-experimentalist/tests/test_preflight.py +++ b/plugins/nemo-experimentalist/tests/test_preflight.py @@ -107,6 +107,63 @@ def test_docker_down_is_required_failure(tmp_path: Path) -> None: assert any(r.severity == "required" and r.status == "fail" and "docker" in r.name for r in results) +def test_remote_harbor_preflight_checks_bridge_without_local_docker(tmp_path: Path) -> None: + commands: list[list[str]] = [] + urls: list[str] = [] + + def run_cmd(argv: list[str]) -> tuple[int, str]: + commands.append(argv) + return 1, "docker unavailable" + + def http_ok(url: str) -> bool: + urls.append(url) + return True + + results = check_environment( + profile=full_profile(tmp_path), + insight=None, + base_url="http://platform", + harbor_bridge_url="http://bridge:8765", + probes=Probes( + run_cmd=run_cmd, + http_ok=http_ok, + env={ + "EXPERIMENTALIST_API_BASE": "http://llm", + "EXPERIMENTALIST_API_KEY": "key", + "NEMO_EXPERIMENTALIST_HARBOR_BRIDGE_TOKEN": "placeholder", + }, + ), + ) + + assert commands == [] + assert urls == [ + "http://llm/models", + "http://platform/health/ready", + "http://bridge:8765/health/ready", + ] + assert next(result for result in results if result.name == "harbor-bridge").status == "pass" + assert not any(result.name in ("docker", "harbor-import") for result in results) + + +def test_remote_harbor_preflight_requires_bridge_token(tmp_path: Path) -> None: + results = check_environment( + profile=full_profile(tmp_path), + insight=None, + base_url="http://platform", + harbor_bridge_url="http://bridge:8765", + probes=make_probes( + env={ + "EXPERIMENTALIST_API_BASE": "http://llm", + "EXPERIMENTALIST_API_KEY": "key", + } + ), + ) + + token = next(result for result in results if result.name == "NEMO_EXPERIMENTALIST_HARBOR_BRIDGE_TOKEN") + assert token.status == "fail" + assert token.severity == "required" + + def test_unreachable_platform_is_advisory(tmp_path: Path) -> None: results = check_environment( profile=full_profile(tmp_path), diff --git a/plugins/nemo-insights/README.md b/plugins/nemo-insights/README.md index cc3a9d28a4..e2a9aee494 100644 --- a/plugins/nemo-insights/README.md +++ b/plugins/nemo-insights/README.md @@ -22,6 +22,19 @@ uv run nemo insights doctor uv run nemo insights analyze ``` +For a reusable trace bundle, import it from the agent directory first: + +```bash +uv run nemo traces import state-v9 +uv run nemo insights analyze +``` + +The import targets the workspace in `optimizer.yaml`, is idempotent, and writes +`.nemo-optimizer/context.yaml` with the Platform URL and bundle time range. +Analysis consumes that context automatically, so restored spans outside +Intake's default lookback window remain visible without a manual `--since`, +`--workspace`, or `--base-url`. + The profile contract consumed by Insights is deliberately small: ```yaml diff --git a/plugins/nemo-insights/pyproject.toml b/plugins/nemo-insights/pyproject.toml index c1538d7e8f..4872f002cd 100644 --- a/plugins/nemo-insights/pyproject.toml +++ b/plugins/nemo-insights/pyproject.toml @@ -10,6 +10,7 @@ dependencies = [ "nemo-platform", "nemo-platform-plugin", "opentelemetry-exporter-otlp>=1.42.1", + "opentelemetry-proto>=1.42.1", "opentelemetry-sdk>=1.42.1", "pydantic>=2.10.6", "pydantic-ai-harness[code-mode]==0.3.0", @@ -21,6 +22,7 @@ dependencies = [ [project.entry-points."nemo.cli"] insights = "nemo_insights_plugin.cli:InsightsCLI" +traces = "nemo_insights_plugin.traces_cli:TracesCLI" [project.entry-points."nemo.services"] insights = "nemo_insights_plugin.service:InsightsService" @@ -41,6 +43,13 @@ build-backend = "hatchling.build" [tool.hatch.build.targets.wheel] packages = ["src/nemo_insights_plugin"] +[tool.hatch.build.targets.wheel.force-include] +"testbed/export.py" = "testbed/export.py" +"testbed/ingest.py" = "testbed/ingest.py" +"testbed/otlp_ingest.py" = "testbed/otlp_ingest.py" +"testbed/reingest.py" = "testbed/reingest.py" +"testbed/release.py" = "testbed/release.py" + [tool.pytest.ini_options] asyncio_mode = "auto" pythonpath = ["src", "."] diff --git a/plugins/nemo-insights/src/nemo_insights_plugin/cli.py b/plugins/nemo-insights/src/nemo_insights_plugin/cli.py index 918002c4f1..b417efaba9 100644 --- a/plugins/nemo-insights/src/nemo_insights_plugin/cli.py +++ b/plugins/nemo-insights/src/nemo_insights_plugin/cli.py @@ -7,6 +7,7 @@ import json import os from dataclasses import dataclass +from datetime import datetime from importlib.metadata import entry_points from pathlib import Path from typing import ClassVar @@ -25,6 +26,11 @@ load_env_file, resolve_base_url, ) +from nemo_insights_plugin.contracts.workflow_context import ( + WorkflowContext, + load_workflow_context, + resolve_context_base_url, +) from nemo_insights_plugin.preflight import ( AnalysisProbes, check_credentials, @@ -50,6 +56,7 @@ class _ResolvedAnalysis: insights_output: Path | None profile_output: Path | None profile_dir: Path | None + since: datetime | None spec_checks: tuple[CheckResult, ...] @@ -110,8 +117,14 @@ def _resolve_analysis( raise ProfileError( "No --agent given and no optimizer.yaml profile found. Pass --agent or run from a directory with a profile." ) + context: WorkflowContext | None = None + if profile is not None: + context = load_workflow_context(profile.profile_dir, agent=profile.agent) + if workspace is not None: resolved_workspace = workspace + elif context is not None: + resolved_workspace = context.workspace else: resolved_workspace = profile.workspace if profile is not None else DEFAULT_WORKSPACE @@ -124,7 +137,7 @@ def _resolve_analysis( spec_error = str(exc) spec_content, spec_checks = read_agent_spec(spec_path, spec_error) - resolved_base_url = resolve_base_url(base_url) + resolved_base_url = resolve_context_base_url(base_url, context) profile_output = None if insights_output is None and profile is not None: profile_output = profile.profile_dir / ".nemo-optimizer" / "insights.yaml" @@ -139,6 +152,7 @@ def _resolve_analysis( insights_output=resolved_output, profile_output=profile_output, profile_dir=profile.profile_dir if profile is not None else None, + since=(context.trace_since if context is not None and context.workspace == resolved_workspace else None), spec_checks=tuple(spec_checks), ) @@ -164,6 +178,7 @@ async def _run_analysis(analysis: _ResolvedAnalysis, *, verbose: bool) -> str: client=client, insights_output=analysis.insights_output, verbose=verbose, + since=analysis.since, ) except AgentRunError as exc: detail = _one_line_error(exc).rstrip(".") diff --git a/plugins/nemo-insights/src/nemo_insights_plugin/contracts/workflow_context.py b/plugins/nemo-insights/src/nemo_insights_plugin/contracts/workflow_context.py new file mode 100644 index 0000000000..b6be2f7c0e --- /dev/null +++ b/plugins/nemo-insights/src/nemo_insights_plugin/contracts/workflow_context.py @@ -0,0 +1,88 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 + +"""Local handoff state for the trace → Insight → experiment workflow.""" + +import os +from collections.abc import Mapping +from datetime import datetime +from pathlib import Path +from typing import Literal +from uuid import uuid4 + +import yaml +from nemo_insights_plugin.contracts.profile import DEFAULT_BASE_URL, ProfileError +from pydantic import BaseModel, ConfigDict, Field, ValidationError + +CONTEXT_RELPATH = Path(".nemo-optimizer") / "context.yaml" + + +class WorkflowContext(BaseModel): + """The latest trace corpus selected for an agent profile.""" + + model_config = ConfigDict(extra="forbid") + + schema_version: Literal[1] = 1 + agent: str = Field(min_length=1) + workspace: str = Field(min_length=1) + base_url: str = Field(min_length=1) + trace_source: str = Field(min_length=1) + trace_since: datetime + + +def context_path(profile_dir: Path) -> Path: + """Return the profile-owned workflow context path.""" + return profile_dir / CONTEXT_RELPATH + + +def load_workflow_context(profile_dir: Path, *, agent: str | None = None) -> WorkflowContext | None: + """Load the profile's workflow context and reject stale cross-agent state.""" + path = context_path(profile_dir) + try: + payload = yaml.safe_load(path.read_text(encoding="utf-8")) + except FileNotFoundError: + return None + except (OSError, UnicodeError, yaml.YAMLError) as exc: + raise ProfileError(f"Could not read workflow context {path}: {exc}") from None + if not isinstance(payload, dict): + raise ProfileError(f"Could not read workflow context {path}: expected a YAML mapping") + try: + context = WorkflowContext.model_validate(payload) + except ValidationError as exc: + details = "; ".join(f"{'.'.join(str(item) for item in error['loc'])}: {error['msg']}" for error in exc.errors()) + raise ProfileError(f"Invalid workflow context {path}: {details}") from None + if agent is not None and context.agent != agent: + raise ProfileError( + f"Workflow context {path} belongs to agent {context.agent!r}, " + f"but optimizer.yaml selects {agent!r}. Run `nemo traces import` again." + ) + return context + + +def write_workflow_context(profile_dir: Path, context: WorkflowContext) -> Path: + """Atomically persist the latest trace selection beside ``optimizer.yaml``.""" + path = context_path(profile_dir) + path.parent.mkdir(parents=True, exist_ok=True) + temporary = path.with_name(f".{path.name}.{uuid4().hex}.tmp") + temporary.write_text( + yaml.safe_dump(context.model_dump(mode="json"), sort_keys=False), + encoding="utf-8", + ) + temporary.replace(path) + return path + + +def resolve_context_base_url( + explicit: str | None, + context: WorkflowContext | None, + *, + env: Mapping[str, str] = os.environ, +) -> str: + """Apply flag, shell, imported-context, then localhost precedence.""" + if explicit is not None: + return explicit + if value := env.get("NMP_BASE_URL"): + return value + if context is not None: + return context.base_url + return DEFAULT_BASE_URL diff --git a/plugins/nemo-insights/src/nemo_insights_plugin/traces_cli.py b/plugins/nemo-insights/src/nemo_insights_plugin/traces_cli.py new file mode 100644 index 0000000000..b9106d5dfa --- /dev/null +++ b/plugins/nemo-insights/src/nemo_insights_plugin/traces_cli.py @@ -0,0 +1,228 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 + +"""Product CLI for importing a reusable Intake trace corpus.""" + +import json +import re +import subprocess +import sys +import tempfile +from importlib.util import find_spec +from pathlib import Path +from typing import ClassVar + +import typer +from nemo_insights_plugin.contracts.profile import ( + ProfileError, + discover_profile, + load_env_file, +) +from nemo_insights_plugin.contracts.workflow_context import ( + WorkflowContext, + resolve_context_base_url, + write_workflow_context, +) +from nemo_insights_plugin.profile import load_profile +from nemo_platform_plugin.cli import NemoCLI + +# The wheel force-includes the mature bundle importer as the ``testbed`` +# namespace. Editable source installs leave it beside ``src/`` instead, so make +# that checkout-local namespace discoverable without changing global pytest +# configuration. +if find_spec("testbed") is None: + plugin_root = Path(__file__).resolve().parents[2] + if (plugin_root / "testbed").is_dir(): + sys.path.insert(0, str(plugin_root)) + +from testbed import reingest, release + + +def _resolve_platform_root(explicit: Path | None, profile_dir: Path) -> Path: + """Find the source checkout from the profile/cwd before legacy fallbacks.""" + if explicit is not None: + return explicit + for start in (profile_dir.resolve(), Path.cwd().resolve()): + for candidate in (start, *start.parents): + if (candidate / reingest.CATALOG_RELPATH).is_file(): + return candidate + return reingest.resolve_platform_root() + + +def _read_bundle_manifest(bundle: Path) -> dict: + """Read and validate ``state/manifest.json`` without extracting the bundle.""" + if not bundle.is_file(): + raise ValueError(f"Trace bundle not found: {bundle}") + listing = subprocess.run( + ["tar", "--zstd", "-tf", str(bundle)], + capture_output=True, + text=True, + check=False, + ) + if listing.returncode != 0: + reason = (listing.stderr.strip().splitlines() or ["tar failed"])[0] + raise ValueError(f"Could not read trace bundle {bundle.name}: {reason}") + if "state/manifest.json" not in listing.stdout.splitlines(): + raise ValueError(f"{bundle.name} is not a supported trace bundle (missing state/manifest.json)") + manifest = subprocess.run( + ["tar", "--zstd", "-xOf", str(bundle), "state/manifest.json"], + capture_output=True, + text=True, + check=False, + ) + if manifest.returncode != 0: + reason = (manifest.stderr.strip().splitlines() or ["tar failed"])[0] + raise ValueError(f"Could not read trace bundle {bundle.name}: {reason}") + try: + payload = json.loads(manifest.stdout) + except json.JSONDecodeError as exc: + raise ValueError(f"{bundle.name} has an invalid state/manifest.json: {exc}") from None + if payload.get("kind") != "testbed-export": + raise ValueError( + f"{bundle.name} uses an unsupported legacy bundle format; " + "re-export it with the current NeMo Insights testbed" + ) + workspaces = payload.get("workspaces") + if not isinstance(workspaces, list) or not workspaces: + raise ValueError(f"{bundle.name} manifest has no workspaces") + return payload + + +def _resolve_bundle(source: str, cache_dir: Path) -> tuple[Path, str]: + candidate = Path(source).expanduser() + if candidate.is_file(): + return candidate.resolve(), candidate.name + if not re.fullmatch(r"state-v\d+", source): + raise ValueError(f"Unknown trace source {source!r}; pass a published state-v ref or a local .tar.zst bundle") + typer.echo(f"Resolving trace corpus: {source}", err=True) + return release.download_ref(source, cache_dir), source + + +def _import_bundle( + bundle: Path, + *, + manifest: dict, + workspace: str, + base_url: str, + platform_root: Path | None, + scratch_root: Path, +) -> dict[str, dict]: + """Extract and idempotently ingest a single-workspace bundle.""" + workspaces = [str(value) for value in manifest["workspaces"]] + workspace_map = reingest.explicit_workspace_map(workspaces, workspace) + catalog = reingest.load_catalog(reingest.resolve_platform_root(platform_root)) + scratch_root.mkdir(parents=True, exist_ok=True) + with tempfile.TemporaryDirectory(dir=scratch_root) as temporary: + extracted = Path(temporary) + completed = subprocess.run( + ["tar", "--zstd", "-xf", str(bundle), "-C", str(extracted)], + capture_output=True, + text=True, + check=False, + ) + if completed.returncode != 0: + reason = (completed.stderr.strip().splitlines() or ["tar failed"])[0] + raise ValueError(f"Could not extract trace bundle {bundle.name}: {reason}") + return reingest.ingest_bundle( + base_url, + extracted / "state" / "export", + manifest, + workspace_map=workspace_map, + catalog=catalog, + require_empty=False, + ) + + +class TracesCLI(NemoCLI): + """``nemo traces ...`` commands.""" + + name: ClassVar[str] = "traces" + description: ClassVar[str] = "Import reusable agent trace corpora." + + def get_cli(self) -> typer.Typer: + app = typer.Typer(help=self.description, no_args_is_help=True) + + @app.callback() + def _root() -> None: + """Force subcommand dispatch.""" + + @app.command("import") + def import_traces( + source: str = typer.Argument( + ..., + help="Published state-v ref or local .tar.zst trace bundle.", + ), + workspace: str | None = typer.Option( + None, + "--workspace", + help="Target Intake workspace. Default: optimizer.yaml workspace.", + ), + base_url: str | None = typer.Option( + None, + "--base-url", + help="Target NeMo Platform URL. Default: NMP_BASE_URL, then localhost.", + ), + profile_path: Path | None = typer.Option( + None, + "--profile", + help="Path to optimizer.yaml. Default: discovered from cwd.", + exists=True, + dir_okay=False, + readable=True, + ), + platform_root: Path | None = typer.Option( + None, + "--platform-root", + help="NeMo Platform checkout root. Auto-detected in source checkouts.", + exists=True, + file_okay=False, + readable=True, + ), + ) -> None: + """Import a trace corpus and select it for the current agent profile.""" + try: + found = profile_path or discover_profile() + if found is None: + raise ProfileError("No optimizer.yaml found. Run from an agent directory or pass --profile.") + profile = load_profile(found) + load_env_file(profile.profile_dir / ".env") + resolved_base_url = resolve_context_base_url(base_url, None) + resolved_workspace = workspace or profile.workspace + state_dir = profile.profile_dir / ".nemo-optimizer" + bundle, source_label = _resolve_bundle(source, state_dir / "cache" / "traces") + manifest = _read_bundle_manifest(bundle) + outcome = _import_bundle( + bundle, + manifest=manifest, + workspace=resolved_workspace, + base_url=resolved_base_url, + platform_root=_resolve_platform_root(platform_root, profile.profile_dir), + scratch_root=state_dir / "tmp", + ) + since = reingest.manifest_since(manifest) + context = WorkflowContext( + agent=profile.agent, + workspace=resolved_workspace, + base_url=resolved_base_url, + trace_source=source_label, + trace_since=since, + ) + context_file = write_workflow_context(profile.profile_dir, context) + except ( + OSError, + ProfileError, + RuntimeError, + subprocess.SubprocessError, + ValueError, + ) as exc: + typer.echo(f"Error: {exc}", err=True) + raise typer.Exit(code=1) from None + + ingested = sum(item["spans"]["ingested"] for item in outcome.values()) + skipped = sum(item["spans"]["skipped"] for item in outcome.values()) + typer.echo( + f"Trace corpus ready: {resolved_workspace} ({ingested} spans ingested, {skipped} already present)" + ) + typer.echo(f"Workflow context: {context_file}", err=True) + + return app diff --git a/plugins/nemo-insights/tests/test_cli_profile.py b/plugins/nemo-insights/tests/test_cli_profile.py index 418fcece24..0c2dff75e8 100644 --- a/plugins/nemo-insights/tests/test_cli_profile.py +++ b/plugins/nemo-insights/tests/test_cli_profile.py @@ -3,6 +3,7 @@ import os from collections.abc import Iterator +from datetime import UTC, datetime from pathlib import Path import httpx @@ -10,6 +11,10 @@ import typer from nemo_insights_plugin import cli from nemo_insights_plugin.contracts.profile import DEFAULT_BASE_URL +from nemo_insights_plugin.contracts.workflow_context import ( + WorkflowContext, + write_workflow_context, +) from nemo_insights_plugin.preflight import AnalysisProbes from nemo_platform import NeMoPlatformError from pydantic_ai import AgentRunError @@ -105,6 +110,35 @@ def test_analyze_flags_override_profile(app: typer.Typer, profile_tree: Path, mo assert recorder.kwargs["workspace"] == "other-ws" +def test_analyze_uses_imported_trace_context( + app: typer.Typer, + profile_tree: Path, + monkeypatch: pytest.MonkeyPatch, +) -> None: + recorder = AnalystRecorder() + monkeypatch.setattr(cli, "run_analyst", recorder) + monkeypatch.delenv("NMP_BASE_URL", raising=False) + write_workflow_context( + profile_tree, + WorkflowContext( + agent="flight-planner", + workspace="imported-flight-traces", + base_url="http://import-platform.test", + trace_source="state-v9", + trace_since=datetime(2026, 7, 9, 12, tzinfo=UTC), + ), + ) + monkeypatch.chdir(profile_tree) + + result = runner.invoke(app, ["analyze"]) + + assert result.exit_code == 0, result.output + assert recorder.kwargs is not None + assert recorder.kwargs["workspace"] == "imported-flight-traces" + assert recorder.kwargs["base_url"] == "http://import-platform.test" + assert recorder.kwargs["since"] == datetime(2026, 7, 9, 12, tzinfo=UTC) + + def test_profile_env_is_loaded_before_base_url_resolution(app: typer.Typer, profile_tree: Path, monkeypatch) -> None: recorder = AnalystRecorder() monkeypatch.setattr(cli, "run_analyst", recorder) diff --git a/plugins/nemo-insights/tests/test_traces_cli.py b/plugins/nemo-insights/tests/test_traces_cli.py new file mode 100644 index 0000000000..95b4a965e5 --- /dev/null +++ b/plugins/nemo-insights/tests/test_traces_cli.py @@ -0,0 +1,86 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 + +from datetime import UTC, datetime +from pathlib import Path + +import pytest +from nemo_insights_plugin import traces_cli +from nemo_insights_plugin.contracts.workflow_context import load_workflow_context +from typer.testing import CliRunner + + +def test_import_uses_profile_workspace_and_writes_context( + monkeypatch: pytest.MonkeyPatch, + tmp_path: Path, +) -> None: + (tmp_path / "optimizer.yaml").write_text( + "agent: nemo-oo-airline\nworkspace: tau2-airline\n", + encoding="utf-8", + ) + bundle = tmp_path / "state-v9.tar.zst" + bundle.touch() + manifest = { + "kind": "testbed-export", + "workspaces": ["old-workspace"], + "min_start_time": "2026-07-10T12:00:00+00:00", + } + captured: dict[str, object] = {} + + monkeypatch.chdir(tmp_path) + monkeypatch.delenv("NMP_BASE_URL", raising=False) + monkeypatch.setattr( + traces_cli, + "_resolve_bundle", + lambda source, cache_dir: (bundle, source), + ) + monkeypatch.setattr(traces_cli, "_read_bundle_manifest", lambda path: manifest) + monkeypatch.setattr( + traces_cli, + "_resolve_platform_root", + lambda explicit, profile_dir: tmp_path, + ) + monkeypatch.setattr( + traces_cli, + "_import_bundle", + lambda path, **kwargs: ( + captured.update(kwargs) + or { + "old-workspace": { + "spans": {"ingested": 270, "skipped": 0}, + } + } + ), + ) + monkeypatch.setattr( + traces_cli.reingest, + "manifest_since", + lambda payload: datetime(2026, 7, 9, 12, tzinfo=UTC), + ) + + result = CliRunner().invoke( + traces_cli.TracesCLI().get_cli(), + ["import", "state-v9"], + ) + + assert result.exit_code == 0, result.output + assert "Trace corpus ready: tau2-airline (270 spans ingested" in result.output + assert captured["workspace"] == "tau2-airline" + assert captured["base_url"] == "http://localhost:8080" + context = load_workflow_context(tmp_path, agent="nemo-oo-airline") + assert context is not None + assert context.workspace == "tau2-airline" + assert context.trace_source == "state-v9" + assert context.trace_since == datetime(2026, 7, 9, 12, tzinfo=UTC) + + +def test_import_requires_profile(tmp_path: Path, monkeypatch: pytest.MonkeyPatch) -> None: + monkeypatch.chdir(tmp_path) + + result = CliRunner().invoke( + traces_cli.TracesCLI().get_cli(), + ["import", "state-v9"], + ) + + assert result.exit_code == 1 + assert "No optimizer.yaml found" in result.output diff --git a/plugins/nemo-insights/tests/test_workflow_context.py b/plugins/nemo-insights/tests/test_workflow_context.py new file mode 100644 index 0000000000..93be1e1153 --- /dev/null +++ b/plugins/nemo-insights/tests/test_workflow_context.py @@ -0,0 +1,60 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 + +from datetime import UTC, datetime +from pathlib import Path + +import pytest +from nemo_insights_plugin.contracts.profile import ProfileError +from nemo_insights_plugin.contracts.workflow_context import ( + WorkflowContext, + load_workflow_context, + resolve_context_base_url, + write_workflow_context, +) + + +def _context() -> WorkflowContext: + return WorkflowContext( + agent="airline", + workspace="airline-traces", + base_url="http://platform.test", + trace_source="state-v9", + trace_since=datetime(2026, 7, 9, tzinfo=UTC), + ) + + +def test_workflow_context_round_trips(tmp_path: Path) -> None: + path = write_workflow_context(tmp_path, _context()) + + assert path == tmp_path / ".nemo-optimizer" / "context.yaml" + assert load_workflow_context(tmp_path, agent="airline") == _context() + + +def test_workflow_context_rejects_another_agent(tmp_path: Path) -> None: + write_workflow_context(tmp_path, _context()) + + with pytest.raises(ProfileError, match="belongs to agent 'airline'"): + load_workflow_context(tmp_path, agent="hotel") + + +def test_context_base_url_precedence() -> None: + context = _context() + + assert ( + resolve_context_base_url( + "http://flag.test", + context, + env={"NMP_BASE_URL": "http://shell.test"}, + ) + == "http://flag.test" + ) + assert ( + resolve_context_base_url( + None, + context, + env={"NMP_BASE_URL": "http://shell.test"}, + ) + == "http://shell.test" + ) + assert resolve_context_base_url(None, context, env={}) == "http://platform.test" diff --git a/services/intake/src/nmp/intake/sidecars/clickhouse.py b/services/intake/src/nmp/intake/sidecars/clickhouse.py new file mode 100644 index 0000000000..c56f79e4a8 --- /dev/null +++ b/services/intake/src/nmp/intake/sidecars/clickhouse.py @@ -0,0 +1,30 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 + +"""Local ClickHouse lifecycle sidecar for ``nemo services`` source checkouts.""" + +import subprocess +import threading +from pathlib import Path + +_SCRIPT = Path("services/intake/scripts/spans/run_clickhouse.sh") + + +def _find_start_script() -> Path: + for start in (Path.cwd().resolve(), Path(__file__).resolve()): + for candidate in (start, *start.parents): + script = candidate / _SCRIPT + if script.is_file(): + return script + raise RuntimeError( + f"The Intake ClickHouse sidecar requires a NeMo Platform source checkout; could not find {_SCRIPT}" + ) + + +def run(stop_signal: threading.Event) -> None: + """Ensure the persistent local ClickHouse container is running.""" + script = _find_start_script() + completed = subprocess.run([str(script)], check=False) # noqa: S603 + if completed.returncode != 0: + raise RuntimeError(f"Could not start Intake ClickHouse with {script}") + stop_signal.wait() diff --git a/services/intake/tests/test_clickhouse_sidecar.py b/services/intake/tests/test_clickhouse_sidecar.py new file mode 100644 index 0000000000..a2a5ad03d3 --- /dev/null +++ b/services/intake/tests/test_clickhouse_sidecar.py @@ -0,0 +1,48 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 + +import subprocess +import threading +from pathlib import Path + +import pytest +from nmp.intake.sidecars import clickhouse + + +def test_clickhouse_sidecar_starts_then_waits( + monkeypatch: pytest.MonkeyPatch, + tmp_path: Path, +) -> None: + script = tmp_path / "run_clickhouse.sh" + script.touch() + stop_signal = threading.Event() + calls: list[list[str]] = [] + + monkeypatch.setattr(clickhouse, "_find_start_script", lambda: script) + monkeypatch.setattr( + clickhouse.subprocess, + "run", + lambda argv, **kwargs: calls.append(argv) or subprocess.CompletedProcess(argv, returncode=0), + ) + stop_signal.set() + + clickhouse.run(stop_signal) + + assert calls == [[str(script)]] + + +def test_clickhouse_sidecar_surfaces_start_failure( + monkeypatch: pytest.MonkeyPatch, + tmp_path: Path, +) -> None: + script = tmp_path / "run_clickhouse.sh" + script.touch() + monkeypatch.setattr(clickhouse, "_find_start_script", lambda: script) + monkeypatch.setattr( + clickhouse.subprocess, + "run", + lambda argv, **kwargs: subprocess.CompletedProcess(argv, returncode=1), + ) + + with pytest.raises(RuntimeError, match="Could not start Intake ClickHouse"): + clickhouse.run(threading.Event()) diff --git a/uv.lock b/uv.lock index 61520d9a0e..f39e4db4ef 100644 --- a/uv.lock +++ b/uv.lock @@ -255,16 +255,8 @@ wheels = [ { url = "https://files.pythonhosted.org/packages/1d/21/151624b51cd92553d95424daf4bf19f19ce9be9002d19253e7e7ce67197b/aiohttp-3.14.1-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:d35143e27778b4bb0fb189562d7f275bff79c62ab8e98459717c0ea617ff2480", size = 757402, upload-time = "2026-06-07T21:06:40.311Z" }, { url = "https://files.pythonhosted.org/packages/55/b2/2aac325583aaa1353045f96dffa586d8a34e8322e14a7ba49cffeb103ab4/aiohttp-3.14.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:27fd7c91e51729b4f7e1577865fa6d34c9adccbc39aabe9000285b48af9f0ec2", size = 512448, upload-time = "2026-06-07T21:06:43.813Z" }, { 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