Introduces testing setup for gen-ai service

Author: JonathanPschl

.github/workflows/test-build-push.yml

@@ -33,9 +33,29 @@ jobs:
       - name: Run tests with Maven
         run: cd server/${{ matrix.service }} && ./mvnw -B test
 
+  test-gen-ai:
+    name: Run Gen-AI Tests
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+
+      - name: Set up Python 3.12
+        uses: actions/setup-python@v5
+        with:
+          python-version: '3.12'
+          cache: pip
+          cache-dependency-path: gen-ai/requirements*.txt
+
+      - name: Install dependencies
+        run: pip install -r gen-ai/requirements-dev.txt
+
+      - name: Run tests with pytest
+        run: pytest gen-ai
+
   test-gatekeeper:
-    name: Run Java Tests  
-    needs: test
+    name: Run Java Tests
+    needs: [test, test-gen-ai]
     runs-on: ubuntu-latest
     steps:
       - name: Success Gate

gen-ai/.gitignore

@@ -1,3 +1,4 @@
 .env
 __pycache__/
 *.pyc
+.coverage

gen-ai/main.py

@@ -219,10 +219,10 @@ def parse_json_content(content: str | None) -> dict:
 
     try:
         return json.loads(content)
-    except json.JSONDecodeError:
+    except json.JSONDecodeError as e:
         match = re.search(r"\{.*\}", content, re.DOTALL)
         if not match:
-            raise
+            raise ValueError(f"LLM response was not valid JSON: {e}") from None
         return json.loads(match.group(0))
 
 

gen-ai/pytest.ini

@@ -0,0 +1,3 @@
+[pytest]
+testpaths = tests
+addopts = -ra --cov=main --cov-report=term-missing --cov-fail-under=85

gen-ai/requirements-dev.txt

@@ -0,0 +1,4 @@
+-r requirements.txt
+pytest
+pytest-cov
+httpx

gen-ai/tests/__init__.py

@@ -0,0 +1,61 @@
+import json
+from types import SimpleNamespace
+from unittest.mock import MagicMock, patch
+
+import pytest
+from fastapi.testclient import TestClient
+
+import main
+
+
+@pytest.fixture(autouse=True)
+def stub_env(monkeypatch):
+    monkeypatch.setenv("OPENAI_API_KEY", "test-openai-key")
+    monkeypatch.setenv("LOGOS_KEY", "test-logos-key")
+
+
+@pytest.fixture
+def client():
+    return TestClient(main.app)
+
+
+def _fake_response(content: str):
+    return SimpleNamespace(
+        choices=[SimpleNamespace(message=SimpleNamespace(content=content))]
+    )
+
+
+@pytest.fixture
+def mock_openai_client():
+    with patch("main.OpenAI") as mock_openai_cls:
+        mock_instance = mock_openai_cls.return_value
+        mock_instance.chat.completions.create = MagicMock(
+            return_value=_fake_response(json.dumps({"ingredients": []}))
+        )
+        yield mock_openai_cls
+
+
+@pytest.fixture
+def sample_ingredient_json():
+    return json.dumps(
+        {
+            "ingredients": [
+                {
+                    "name": "flour",
+                    "quantity": "200",
+                    "unit": "g",
+                    "category": "Pantry",
+                    "restricted": False,
+                    "alternative": None,
+                },
+                {
+                    "name": "milk",
+                    "quantity": "240",
+                    "unit": "ml",
+                    "category": "Dairy",
+                    "restricted": True,
+                    "alternative": "oat milk",
+                },
+            ]
+        }
+    )

gen-ai/tests/conftest.py

@@ -0,0 +1,4 @@
+def test_health_returns_ok(client):
+    response = client.get("/health")
+    assert response.status_code == 200
+    assert response.json() == {"status": "ok"}

gen-ai/tests/test_endpoint_health.py

@@ -0,0 +1,81 @@
+import json
+
+from tests.conftest import _fake_response
+
+
+def _set_llm_content(mock_openai_client, content):
+    mock_openai_client.return_value.chat.completions.create.return_value = (
+        _fake_response(content)
+    )
+
+
+def _ingredient(name="flour", quantity="100", unit="g", category="Pantry"):
+    return {
+        "name": name,
+        "quantity": quantity,
+        "unit": unit,
+        "category": category,
+        "restricted": False,
+        "alternative": None,
+    }
+
+
+def test_happy_path_merges_and_returns_ingredients(
+    client, mock_openai_client, sample_ingredient_json
+):
+    _set_llm_content(mock_openai_client, sample_ingredient_json)
+    response = client.post(
+        "/api/ai/merge",
+        json={"recipes": [[_ingredient()], [_ingredient(name="sugar")]]},
+    )
+    assert response.status_code == 200
+    assert len(response.json()["ingredients"]) == 2
+
+
+def test_recipes_serialized_into_user_message(
+    client, mock_openai_client, sample_ingredient_json
+):
+    _set_llm_content(mock_openai_client, sample_ingredient_json)
+    recipes = [[_ingredient()], [_ingredient(name="sugar")]]
+    client.post("/api/ai/merge", json={"recipes": recipes})
+    _, kwargs = mock_openai_client.return_value.chat.completions.create.call_args
+    user_message = next(m for m in kwargs["messages"] if m["role"] == "user")
+    sent = json.loads(user_message["content"])
+    assert sent == recipes
+
+
+def test_malformed_llm_json_returns_500(client, mock_openai_client):
+    _set_llm_content(mock_openai_client, "not json")
+    response = client.post("/api/ai/merge", json={"recipes": [[_ingredient()]]})
+    assert response.status_code == 500
+
+
+def test_openai_error_returns_502(client, mock_openai_client):
+    from openai import OpenAIError
+
+    mock_openai_client.return_value.chat.completions.create.side_effect = OpenAIError(
+        "boom"
+    )
+    response = client.post(
+        "/api/ai/merge",
+        json={"recipes": [[_ingredient()]], "llm_provider": "openai"},
+    )
+    assert response.status_code == 502
+
+
+def test_missing_api_key_returns_500(client, monkeypatch):
+    monkeypatch.delenv("OPENAI_API_KEY", raising=False)
+    response = client.post(
+        "/api/ai/merge",
+        json={"recipes": [[_ingredient()]], "llm_provider": "openai"},
+    )
+    assert response.status_code == 500
+
+
+def test_empty_recipes_list_still_calls_llm(
+    client, mock_openai_client, sample_ingredient_json
+):
+    _set_llm_content(mock_openai_client, sample_ingredient_json)
+    response = client.post("/api/ai/merge", json={"recipes": []})
+    assert response.status_code == 200
+    mock_openai_client.return_value.chat.completions.create.assert_called_once()

gen-ai/tests/test_endpoint_merge.py

@@ -0,0 +1,99 @@
+import json
+
+from main import LOGOS_BASE_URL, LOGOS_MODEL, OPENAI_MODEL
+
+from tests.conftest import _fake_response
+
+
+def _set_llm_content(mock_openai_client, content):
+    mock_openai_client.return_value.chat.completions.create.return_value = (
+        _fake_response(content)
+    )
+
+
+def test_happy_path_returns_ingredients(client, mock_openai_client, sample_ingredient_json):
+    _set_llm_content(mock_openai_client, sample_ingredient_json)
+    response = client.post("/api/ai/parse", json={"dish": "Pancakes"})
+    assert response.status_code == 200
+    body = response.json()
+    assert body["dish"] == "Pancakes"
+    assert len(body["ingredients"]) == 2
+
+
+def test_restricted_and_alternative_fields_roundtrip(
+    client, mock_openai_client, sample_ingredient_json
+):
+    _set_llm_content(mock_openai_client, sample_ingredient_json)
+    response = client.post("/api/ai/parse", json={"dish": "Pancakes"})
+    milk = next(i for i in response.json()["ingredients"] if i["name"] == "milk")
+    assert milk["restricted"] is True
+    assert milk["alternative"] == "oat milk"
+
+
+def test_malformed_llm_json_returns_500(client, mock_openai_client):
+    _set_llm_content(mock_openai_client, "not json at all")
+    response = client.post("/api/ai/parse", json={"dish": "Pancakes"})
+    assert response.status_code == 500
+    assert "Failed to parse LLM response" in response.json()["detail"]
+
+
+def test_missing_ingredients_key_returns_500(client, mock_openai_client):
+    _set_llm_content(mock_openai_client, json.dumps({"foo": "bar"}))
+    response = client.post("/api/ai/parse", json={"dish": "Pancakes"})
+    assert response.status_code == 500
+    assert "Failed to parse LLM response" in response.json()["detail"]
+
+
+def test_openai_error_returns_502(client, mock_openai_client):
+    from openai import OpenAIError
+
+    mock_openai_client.return_value.chat.completions.create.side_effect = OpenAIError(
+        "boom"
+    )
+    response = client.post(
+        "/api/ai/parse", json={"dish": "Pancakes", "llm_provider": "openai"}
+    )
+    assert response.status_code == 502
+    assert "openai error" in response.json()["detail"]
+
+
+def test_missing_api_key_returns_500(client, monkeypatch):
+    monkeypatch.delenv("OPENAI_API_KEY", raising=False)
+    response = client.post(
+        "/api/ai/parse", json={"dish": "Pancakes", "llm_provider": "openai"}
+    )
+    assert response.status_code == 500
+    assert "OPENAI_API_KEY" in response.json()["detail"]
+
+
+def test_default_provider_is_logos(client, mock_openai_client, sample_ingredient_json):
+    _set_llm_content(mock_openai_client, sample_ingredient_json)
+    client.post("/api/ai/parse", json={"dish": "Pancakes"})
+    _, kwargs = mock_openai_client.return_value.chat.completions.create.call_args
+    assert kwargs["model"] == LOGOS_MODEL
+    assert "response_format" not in kwargs
+    _, client_kwargs = mock_openai_client.call_args
+    assert client_kwargs["base_url"] == LOGOS_BASE_URL
+
+
+def test_openai_provider_selected(client, mock_openai_client, sample_ingredient_json):
+    _set_llm_content(mock_openai_client, sample_ingredient_json)
+    client.post(
+        "/api/ai/parse", json={"dish": "Pancakes", "llm_provider": "openai"}
+    )
+    _, kwargs = mock_openai_client.return_value.chat.completions.create.call_args
+    assert kwargs["model"] == OPENAI_MODEL
+    assert kwargs["response_format"] == {"type": "json_object"}
+
+
+def test_dietary_restrictions_passed_into_system_prompt(
+    client, mock_openai_client, sample_ingredient_json
+):
+    _set_llm_content(mock_openai_client, sample_ingredient_json)
+    client.post(
+        "/api/ai/parse",
+        json={"dish": "Pancakes", "dietary_restrictions": ["Vegan"]},
+    )
+    _, kwargs = mock_openai_client.return_value.chat.completions.create.call_args
+    system_message = next(m for m in kwargs["messages"] if m["role"] == "system")
+    assert "animal product" in system_message["content"]