Initial deploy setup

tests/unit/test_ai.py

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+import json
+from pathlib import Path
+
+import httpx
+import pytest
+from django.test import override_settings
+
+from apps.jobs.models import AiAnalysisCache
+from apps.jobs.services import ai as ai_service
+from apps.jobs.services.ai import analyze_job_text
+
+
+def _evaluation_cases() -> list[dict[str, object]]:
+    path = Path(__file__).resolve().parents[1] / "fixtures" / "ai" / "evaluation_set.json"
+    return json.loads(path.read_text(encoding="utf-8"))["cases"]
+
+
+@pytest.mark.parametrize("case", _evaluation_cases(), ids=lambda case: case["id"])
+def test_ai_evaluation_cases(monkeypatch, case):
+    if case["response_type"] == "disabled":
+        with override_settings(OLLAMA_ENABLED=False, OLLAMA_MODEL=""):
+            result = analyze_job_text(
+                title=case["title"],
+                description=case["description"],
+                content_hash=case["content_hash"],
+            )
+        assert result.status == ai_service.AiAnalysisCache.Status.DISABLED
+        assert result.error_category == "ollama_disabled"
+        assert result.cached is False
+        assert result.summary_nl == ""
+        return
+
+    if case["response_type"] == "timeout":
+        class FakeClient:
+            def __init__(self, *args, **kwargs):
+                pass
+
+            def __enter__(self):
+                return self
+
+            def __exit__(self, exc_type, exc, tb):
+                return False
+
+            def post(self, *args, **kwargs):
+                raise httpx.TimeoutException("timeout")
+
+        monkeypatch.setattr(httpx, "Client", FakeClient)
+    else:
+        class FakeClient:
+            def __init__(self, *args, **kwargs):
+                pass
+
+            def __enter__(self):
+                return self
+
+            def __exit__(self, exc_type, exc, tb):
+                return False
+
+            def post(self, *args, **kwargs):
+                return _fake_response(case["response"])
+
+        monkeypatch.setattr(httpx, "Client", FakeClient)
+
+    with override_settings(
+        OLLAMA_ENABLED=True,
+        OLLAMA_MODEL="local-model",
+        OLLAMA_BASE_URL="http://ollama:11434",
+        OLLAMA_TIMEOUT_SECONDS=2,
+    ):
+        result = analyze_job_text(
+            title=case["title"],
+            description=case["description"],
+            content_hash=case["content_hash"],
+        )
+
+    assert result.status == case["expected_status"]
+    assert result.error_category == case["expected_error_category"]
+    assert result.schema_version == "1.0.0"
+    if result.status == ai_service.AiAnalysisCache.Status.OK:
+        assert result.summary_nl == case["expected_summary"]
+        assert round(result.features.get("support_ratio", 0), 3) == case["expected_support_ratio"]
+        assert result.features.get("evidence") == case["expected_evidence"]
+    if result.status != ai_service.AiAnalysisCache.Status.OK:
+        assert result.features == {}
+
+
+def _fake_response(response_text: object):
+    class FakeResponse:
+        def raise_for_status(self):
+            return None
+
+        def json(self):
+            return {"response": response_text}
+
+    return FakeResponse()
+
+
+def test_ai_cache_reuses_result(monkeypatch):
+    calls = 0
+
+    class FakeClient:
+        def __init__(self, *args, **kwargs):
+            pass
+
+        def __enter__(self):
+            return self
+
+        def __exit__(self, exc_type, exc, tb):
+            return False
+
+        def post(self, *args, **kwargs):
+            nonlocal calls
+            calls += 1
+            return _fake_response(
+                '{"summary_nl":"Gevalideerde IT-ops advertentie.","features":{"support_ratio":0.03,"consultancy_ratio":0.01,"travel_ratio":0.02,"seniority":"senior","evidence":["IT"]},"warnings":[]}'
+            )
+
+    monkeypatch.setattr(httpx, "Client", FakeClient)
+
+    with override_settings(
+        OLLAMA_ENABLED=True,
+        OLLAMA_MODEL="local-model",
+        OLLAMA_BASE_URL="http://ollama:11434",
+    ):
+        first = analyze_job_text(
+            "Cloud Engineer",
+            "Cloud Engineer vacature. IT-ops taken incl. Azure en Linux.",
+            content_hash="cache-hit-case",
+        )
+        second = analyze_job_text(
+            "Cloud Engineer",
+            "Cloud Engineer vacature. IT-ops taken incl. Azure en Linux.",
+            content_hash="cache-hit-case",
+        )
+
+    assert first.status == ai_service.AiAnalysisCache.Status.OK
+    assert second.status == ai_service.AiAnalysisCache.Status.OK
+    assert first.cached is False
+    assert second.cached is True
+    assert calls == 1
+    assert AiAnalysisCache.objects.count() == 1