pagina unica

tests/unit/test_api_promotions.py

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+"""Governance promotion flow: train → evaluate → request → approve."""
+
+import shutil
+from pathlib import Path
+
+import pytest
+from fastapi.testclient import TestClient
+
+from forja_core.api import deps
+from forja_core.main import create_app
+
+FIXTURES = Path(__file__).parent.parent / "fixtures"
+
+
+@pytest.fixture(autouse=True)
+def patch_settings(tmp_path: Path, monkeypatch: pytest.MonkeyPatch) -> None:
+    agents_dir = tmp_path / "agents"
+    shutil.copytree(FIXTURES / "agents", agents_dir)
+    monkeypatch.setenv("DATA_DIR", str(tmp_path))
+    monkeypatch.setenv("AGENTS_DIR", str(agents_dir))
+    monkeypatch.setenv("POLICIES_DIR", str(FIXTURES / "policies"))
+    monkeypatch.setenv("DATASETS_DIR", str(FIXTURES / "datasets"))
+    monkeypatch.setenv("MODELS_DIR", str(FIXTURES / "models"))
+    monkeypatch.setenv("TRAINING_BACKEND", "mock")
+    for fn in (
+        deps.get_settings,
+        deps.get_registry,
+        deps.get_policy_store,
+        deps.get_dataset_store,
+        deps.get_model_store,
+        deps.get_training_backend,
+        deps.get_orchestrator,
+        deps.get_llm_provider,
+        deps.get_guardrail_engine,
+    ):
+        fn.cache_clear()
+
+
+def test_promotion_flow_approve_activates_draft_version() -> None:
+    client = TestClient(create_app())
+
+    run = client.post(
+        "/api/training/runs",
+        json={
+            "dataset_name": "incident_sft",
+            "model_name": "gpt4o_lora_base",
+            "agent_name": "test_agent",
+            "agent_version": "v2",
+        },
+    ).json()
+    run_id = run["id"]
+
+    # Evaluation must cover the candidate version, not the active one.
+    eval_report = client.post(f"/api/training/runs/{run_id}/evaluate").json()
+    assert eval_report["passed"] is True
+    assert eval_report["agent_version"] == "v2"
+
+    promo = client.post(
+        "/api/promotions",
+        json={
+            "agent_name": "test_agent",
+            "agent_version": "v2",
+            "training_run_id": run_id,
+            "evaluation_report_id": eval_report["id"],
+        },
+    )
+    assert promo.status_code == 201
+    request_id = promo.json()["id"]
+
+    approve = client.post(
+        f"/api/promotions/{request_id}/approve",
+        json={"approved_by": "ops-lead", "comment": "Eval gate passed"},
+    )
+    assert approve.status_code == 200
+
+    agent = client.get("/api/agents/test_agent").json()
+    assert agent["version"] == "v2"
+    assert agent["state"] == "active"
+
+
+def test_promotion_blocked_when_eval_failed(tmp_path: Path) -> None:
+    """Promotion returns 422 if linked evaluation did not pass."""
+    from datetime import UTC, datetime
+    from uuid import uuid4
+
+    from forja_core.api.evaluation_persistence import save_evaluation
+    from forja_core.api.training_persistence import save_training_run
+    from forja_core.domain.training import (
+        EvaluationReport,
+        TrainingHyperparameters,
+        TrainingJobSpec,
+        TrainingRun,
+    )
+
+    client = TestClient(create_app())
+    settings = deps.get_settings()
+    run_id = uuid4()
+    now = datetime.now(UTC)
+    spec = TrainingJobSpec(
+        dataset_name="incident_sft",
+        dataset_version="v1",
+        model_name="gpt4o_lora_base",
+        model_version="v1",
+        agent_name="test_agent",
+        hyperparameters=TrainingHyperparameters(),
+    )
+    save_training_run(
+        settings.data_dir,
+        TrainingRun(
+            id=run_id,
+            backend="mock",
+            status="succeeded",
+            spec=spec,
+            external_job_id="mock:x",
+            created_at=now,
+            updated_at=now,
+        ),
+    )
+    report = EvaluationReport(
+        id=uuid4(),
+        training_run_id=run_id,
+        agent_name="test_agent",
+        agent_version="v1",
+        passed=False,
+        scenario_count=1,
+        violation_count=1,
+        created_at=now,
+        notes="forced failure",
+    )
+    save_evaluation(settings.data_dir, report)
+
+    r = client.post(
+        "/api/promotions",
+        json={
+            "agent_name": "test_agent",
+            "agent_version": "v2",
+            "training_run_id": str(run_id),
+            "evaluation_report_id": str(report.id),
+        },
+    )
+    assert r.status_code == 422
+
+
+def test_promotion_blocked_when_eval_covers_other_version() -> None:
+    """Evaluating the active version must not unlock promoting a different draft."""
+    client = TestClient(create_app())
+
+    # No agent_version on the run → evaluation covers the active version (v1).
+    run = client.post(
+        "/api/training/runs",
+        json={
+            "dataset_name": "incident_sft",
+            "model_name": "gpt4o_lora_base",
+            "agent_name": "test_agent",
+        },
+    ).json()
+    run_id = run["id"]
+
+    eval_report = client.post(f"/api/training/runs/{run_id}/evaluate").json()
+    assert eval_report["passed"] is True
+    assert eval_report["agent_version"] == "v1"
+
+    r = client.post(
+        "/api/promotions",
+        json={
+            "agent_name": "test_agent",
+            "agent_version": "v2",
+            "training_run_id": run_id,
+            "evaluation_report_id": eval_report["id"],
+        },
+    )
+    assert r.status_code == 422
+    assert "evaluate the candidate version" in r.json()["detail"]