Livrare LOT 1 - Didi

ai_platform/modules/llm-inference/tests/__init__.py

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+"""Tests for LLM inference module."""

ai_platform/modules/llm-inference/tests/conftest.py

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+"""Pytest fixtures for LLM inference tests."""
+
+from unittest.mock import AsyncMock, MagicMock
+
+import pytest
+from fastapi.testclient import TestClient
+
+from llm_inference.api.app import create_app
+from llm_inference.api.dependencies import init_concurrency_limiter
+from llm_inference.client import LLMClient
+from llm_inference.config import LLMSettings, SettingsCache
+from llm_inference.schemas import CompletionChunk, CompletionResponse
+from llm_inference.types import (
+    BackendType,
+    ChatMessage,
+    Choice,
+    Delta,
+    StreamChoice,
+    Usage,
+)
+
+
+@pytest.fixture(autouse=True)
+def clear_settings_cache() -> None:
+    """Clear settings cache before each test."""
+    SettingsCache.clear()
+
+
+@pytest.fixture
+def test_settings() -> LLMSettings:
+    """Create test settings with mocked values."""
+    return LLMSettings(
+        default_backend="litellm",
+        default_model="test-model",
+        openrouter_api_key="test-openrouter-key",
+        openai_api_key="test-openai-key",
+        enable_vllm=False,
+        enable_llamacpp=False,
+        host="127.0.0.1",
+        port=8100,
+        external_url="http://localhost:8100",
+        api_tokens=None,  # Auth disabled by default in tests
+    )
+
+
+@pytest.fixture
+def mock_completion_response() -> CompletionResponse:
+    """Create a mock completion response."""
+    return CompletionResponse(
+        id="test-completion-id",
+        created=1234567890,
+        model="test-model",
+        choices=[
+            Choice(
+                index=0,
+                message=ChatMessage(role="assistant", content="Hello! How can I help?"),
+                finish_reason="stop",
+            )
+        ],
+        usage=Usage(prompt_tokens=10, completion_tokens=5, total_tokens=15),
+        backend="litellm",
+    )
+
+
+@pytest.fixture
+def mock_completion_chunks() -> list[CompletionChunk]:
+    """Create mock streaming completion chunks."""
+    return [
+        CompletionChunk(
+            id="test-chunk-1",
+            created=1234567890,
+            model="test-model",
+            choices=[
+                StreamChoice(
+                    index=0,
+                    delta=Delta(role="assistant", content="Hello"),
+                    finish_reason=None,
+                )
+            ],
+        ),
+        CompletionChunk(
+            id="test-chunk-2",
+            created=1234567891,
+            model="test-model",
+            choices=[
+                StreamChoice(
+                    index=0,
+                    delta=Delta(content="!"),
+                    finish_reason=None,
+                )
+            ],
+        ),
+        CompletionChunk(
+            id="test-chunk-3",
+            created=1234567892,
+            model="test-model",
+            choices=[
+                StreamChoice(
+                    index=0,
+                    delta=Delta(),
+                    finish_reason="stop",
+                )
+            ],
+        ),
+    ]
+
+
+@pytest.fixture
+def mock_litellm_response() -> MagicMock:
+    """Create a mock LiteLLM response object."""
+    response = MagicMock()
+    response.id = "test-completion-id"
+    response.created = 1234567890
+    response.model = "test-model"
+
+    choice = MagicMock()
+    choice.index = 0
+    choice.message.role = "assistant"
+    choice.message.content = "Hello! How can I help?"
+    choice.finish_reason = "stop"
+    response.choices = [choice]
+
+    response.usage.prompt_tokens = 10
+    response.usage.completion_tokens = 5
+    response.usage.total_tokens = 15
+
+    return response
+
+
+@pytest.fixture
+def client_with_mock_backend(
+    test_settings: LLMSettings, mock_completion_response: CompletionResponse
+) -> LLMClient:
+    """Create an LLMClient with mocked backend."""
+    # Inject test settings into cache
+    SettingsCache.set(test_settings)
+
+    client = LLMClient(settings=test_settings)
+
+    # Mock the backend's complete method
+    backend = client.registry.get(BackendType.LITELLM)
+    backend.complete = AsyncMock(return_value=mock_completion_response)
+
+    return client
+
+
+@pytest.fixture
+def app_client(test_settings: LLMSettings) -> TestClient:
+    """Create a FastAPI TestClient with test settings."""
+    # Inject test settings into cache BEFORE creating the app
+    SettingsCache.set(test_settings)
+
+    # Initialize concurrency limiter for tests
+    init_concurrency_limiter(test_settings.max_concurrent_completions)
+
+    app = create_app()
+
+    # Also set in app.state for handlers that access it
+    app.state.settings = test_settings
+    app.state.client = LLMClient(settings=test_settings)
+
+    return TestClient(app)

ai_platform/modules/llm-inference/tests/test_api.py

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+"""Tests for FastAPI routes."""
+
+from unittest.mock import AsyncMock, patch
+
+import pytest
+from fastapi.testclient import TestClient
+
+from llm_inference.api.app import create_app
+from llm_inference.api.dependencies import init_concurrency_limiter
+from llm_inference.client import LLMClient
+from llm_inference.config import LLMSettings, SettingsCache
+from llm_inference.schemas import CompletionResponse
+
+
+@pytest.fixture
+def app_client(test_settings: LLMSettings) -> TestClient:
+    """Create a test client with mocked client."""
+    # Inject test settings into cache BEFORE creating app
+    SettingsCache.set(test_settings)
+
+    # Initialize concurrency limiter for tests
+    init_concurrency_limiter(test_settings.max_concurrent_completions)
+
+    app = create_app()
+    app.state.settings = test_settings
+    app.state.client = LLMClient(settings=test_settings)
+    return TestClient(app)
+
+
+class TestHealthRoutes:
+    """Tests for health check routes."""
+
+    def test_health_endpoint(self, app_client: TestClient) -> None:
+        """Test /health endpoint."""
+        response = app_client.get("/health")
+
+        assert response.status_code == 200
+        data = response.json()
+        assert "status" in data
+        assert "backends" in data
+        assert data["status"] in ["healthy", "degraded", "unhealthy"]
+
+    def test_ready_endpoint(self, app_client: TestClient) -> None:
+        """Test /ready endpoint."""
+        response = app_client.get("/ready")
+
+        assert response.status_code == 200
+        data = response.json()
+        assert data["ready"] is True
+
+
+class TestModelsRoutes:
+    """Tests for model management routes."""
+
+    def test_list_models(self, app_client: TestClient) -> None:
+        """Test GET /v1/models."""
+        response = app_client.get("/v1/models")
+
+        assert response.status_code == 200
+        data = response.json()
+        assert "data" in data
+        assert "object" in data
+        assert data["object"] == "list"
+
+    def test_list_models_with_backend_filter(self, app_client: TestClient) -> None:
+        """Test GET /v1/models with backend filter."""
+        response = app_client.get("/v1/models?backend=litellm")
+
+        assert response.status_code == 200
+        data = response.json()
+        # All models should be from litellm backend
+        for model in data["data"]:
+            assert model["backend"] == "litellm"
+
+    def test_list_models_invalid_backend(self, app_client: TestClient) -> None:
+        """Test GET /v1/models with invalid backend."""
+        response = app_client.get("/v1/models?backend=invalid")
+
+        assert response.status_code == 400
+
+    def test_list_backends(self, app_client: TestClient) -> None:
+        """Test GET /v1/backends."""
+        response = app_client.get("/v1/backends")
+
+        assert response.status_code == 200
+        data = response.json()
+        assert "backends" in data
+        assert "litellm" in data["backends"]
+
+
+class TestCompletionsRoutes:
+    """Tests for completion routes."""
+
+    def test_chat_completions(
+        self,
+        app_client: TestClient,
+        mock_completion_response: CompletionResponse,
+    ) -> None:
+        """Test POST /v1/chat/completions."""
+        # Mock the client's complete method
+        with patch.object(
+            app_client.app.state.client,
+            "complete",
+            new_callable=AsyncMock,
+            return_value=mock_completion_response,
+        ):
+            response = app_client.post(
+                "/v1/chat/completions",
+                json={
+                    "messages": [{"role": "user", "content": "Hello"}],
+                    "model": "gpt-3.5-turbo",
+                },
+            )
+
+            assert response.status_code == 200
+            data = response.json()
+            assert "id" in data
+            assert "choices" in data
+            assert "model" in data
+
+    def test_chat_completions_with_parameters(
+        self,
+        app_client: TestClient,
+        mock_completion_response: CompletionResponse,
+    ) -> None:
+        """Test completion with optional parameters."""
+        with patch.object(
+            app_client.app.state.client,
+            "complete",
+            new_callable=AsyncMock,
+            return_value=mock_completion_response,
+        ):
+            response = app_client.post(
+                "/v1/chat/completions",
+                json={
+                    "messages": [{"role": "user", "content": "Hello"}],
+                    "model": "gpt-4",
+                    "temperature": 0.5,
+                    "max_tokens": 100,
+                    "top_p": 0.9,
+                },
+            )
+
+            assert response.status_code == 200
+
+    def test_chat_completions_with_backend_override(
+        self,
+        app_client: TestClient,
+        mock_completion_response: CompletionResponse,
+    ) -> None:
+        """Test completion with backend override."""
+        with patch.object(
+            app_client.app.state.client,
+            "complete",
+            new_callable=AsyncMock,
+            return_value=mock_completion_response,
+        ):
+            response = app_client.post(
+                "/v1/chat/completions",
+                json={
+                    "messages": [{"role": "user", "content": "Hello"}],
+                    "model": "gpt-3.5-turbo",
+                    "backend": "litellm",
+                },
+            )
+
+            assert response.status_code == 200
+
+    def test_chat_completions_missing_messages(self, app_client: TestClient) -> None:
+        """Test completion without messages returns error."""
+        response = app_client.post(
+            "/v1/chat/completions",
+            json={"model": "gpt-3.5-turbo"},
+        )
+
+        assert response.status_code == 422  # Validation error
+
+    def test_chat_completions_missing_model(self, app_client: TestClient) -> None:
+        """Test completion without model returns error."""
+        response = app_client.post(
+            "/v1/chat/completions",
+            json={"messages": [{"role": "user", "content": "Hello"}]},
+        )
+
+        assert response.status_code == 422  # Validation error
+
+
+class TestModelLoadRoutes:
+    """Tests for model load/unload routes."""
+
+    def test_load_model_unsupported_backend(self, app_client: TestClient) -> None:
+        """Test loading model on backend that doesn't support it."""
+        response = app_client.post(
+            "/v1/models/load",
+            json={"model": "test-model", "backend": "litellm"},
+        )
+
+        # LiteLLM doesn't support model loading
+        assert response.status_code == 400
+
+    def test_unload_model_unsupported_backend(self, app_client: TestClient) -> None:
+        """Test unloading model on backend that doesn't support it."""
+        response = app_client.post(
+            "/v1/models/unload",
+            json={"model": "test-model", "backend": "litellm"},
+        )
+
+        # LiteLLM doesn't support model unloading
+        assert response.status_code == 400

ai_platform/modules/llm-inference/tests/test_auth.py

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+"""Tests for API authentication."""
+
+import pytest
+from fastapi.testclient import TestClient
+
+from llm_inference.api.app import create_app
+from llm_inference.api.dependencies import init_concurrency_limiter
+from llm_inference.client import LLMClient
+from llm_inference.config import LLMSettings, SettingsCache
+
+
+class TestAuthDisabled:
+    """Tests when authentication is disabled (no tokens configured)."""
+
+    @pytest.fixture
+    def app_client_no_auth(self, test_settings: LLMSettings) -> TestClient:
+        """Create test client with auth disabled."""
+        # test_settings has api_tokens=None by default
+        SettingsCache.set(test_settings)
+        init_concurrency_limiter(test_settings.max_concurrent_completions)
+        app = create_app()
+        app.state.settings = test_settings
+        app.state.client = LLMClient(settings=test_settings)
+        return TestClient(app)
+
+    def test_models_accessible_without_token(
+        self, app_client_no_auth: TestClient
+    ) -> None:
+        """Test that models endpoint works without token when auth disabled."""
+        response = app_client_no_auth.get("/v1/models")
+        assert response.status_code != 401
+
+    def test_backends_accessible_without_token(
+        self, app_client_no_auth: TestClient
+    ) -> None:
+        """Test that backends endpoint works without token when auth disabled."""
+        response = app_client_no_auth.get("/v1/backends")
+        assert response.status_code == 200
+
+    def test_health_accessible(self, app_client_no_auth: TestClient) -> None:
+        """Test health endpoint accessible."""
+        response = app_client_no_auth.get("/health")
+        assert response.status_code == 200
+
+    def test_ready_accessible(self, app_client_no_auth: TestClient) -> None:
+        """Test ready endpoint accessible."""
+        response = app_client_no_auth.get("/ready")
+        # May return 200 or 503 depending on backend health, but not 401
+        assert response.status_code != 401
+
+
+class TestAuthEnabled:
+    """Tests when authentication is enabled."""
+
+    @pytest.fixture
+    def auth_settings(self, test_settings: LLMSettings) -> LLMSettings:
+        """Create settings with auth enabled."""
+        return LLMSettings(
+            default_backend=test_settings.default_backend,
+            enable_vllm=test_settings.enable_vllm,
+            enable_llamacpp=test_settings.enable_llamacpp,
+            external_url=test_settings.external_url,
+            openrouter_api_key=test_settings.openrouter_api_key,
+            api_tokens=frozenset(["test-token-1", "test-token-2"]),
+        )
+
+    @pytest.fixture
+    def app_client_auth(self, auth_settings: LLMSettings) -> TestClient:
+        """Create test client with auth enabled."""
+        SettingsCache.set(auth_settings)
+        init_concurrency_limiter(auth_settings.max_concurrent_completions)
+        app = create_app()
+        app.state.settings = auth_settings
+        app.state.client = LLMClient(settings=auth_settings)
+        return TestClient(app)
+
+    def test_missing_token_returns_401(self, app_client_auth: TestClient) -> None:
+        """Test 401 returned when token missing."""
+        response = app_client_auth.get("/v1/models")
+        assert response.status_code == 401
+        assert "WWW-Authenticate" in response.headers
+        assert response.headers["WWW-Authenticate"] == "Bearer"
+        data = response.json()
+        assert data["detail"]["error"] == "Authentication required"
+
+    def test_invalid_token_returns_401(self, app_client_auth: TestClient) -> None:
+        """Test 401 returned for invalid token."""
+        response = app_client_auth.get(
+            "/v1/models",
+            headers={"Authorization": "Bearer invalid-token"},
+        )
+        assert response.status_code == 401
+        data = response.json()
+        assert data["detail"]["error"] == "Authentication failed"
+
+    def test_valid_token_allows_access(self, app_client_auth: TestClient) -> None:
+        """Test valid token grants access."""
+        response = app_client_auth.get(
+            "/v1/models",
+            headers={"Authorization": "Bearer test-token-1"},
+        )
+        assert response.status_code == 200
+
+    def test_second_valid_token_works(self, app_client_auth: TestClient) -> None:
+        """Test second token also works."""
+        response = app_client_auth.get(
+            "/v1/models",
+            headers={"Authorization": "Bearer test-token-2"},
+        )
+        assert response.status_code == 200
+
+    def test_malformed_header_missing_bearer(self, app_client_auth: TestClient) -> None:
+        """Test malformed Authorization header without Bearer prefix."""
+        response = app_client_auth.get(
+            "/v1/models",
+            headers={"Authorization": "test-token-1"},
+        )
+        assert response.status_code == 401
+
+    def test_malformed_header_wrong_prefix(self, app_client_auth: TestClient) -> None:
+        """Test Authorization header with wrong prefix."""
+        response = app_client_auth.get(
+            "/v1/models",
+            headers={"Authorization": "Basic test-token-1"},
+        )
+        assert response.status_code == 401
+
+    def test_health_excluded_from_auth(self, app_client_auth: TestClient) -> None:
+        """Test /health accessible without token even when auth enabled."""
+        response = app_client_auth.get("/health")
+        assert response.status_code == 200
+
+    def test_ready_excluded_from_auth(self, app_client_auth: TestClient) -> None:
+        """Test /ready accessible without token even when auth enabled."""
+        response = app_client_auth.get("/ready")
+        # May return 200 or 503 depending on backend health, but not 401
+        assert response.status_code != 401
+
+    def test_backends_requires_auth(self, app_client_auth: TestClient) -> None:
+        """Test /v1/backends requires authentication."""
+        response = app_client_auth.get("/v1/backends")
+        assert response.status_code == 401
+
+    def test_backends_with_valid_token(self, app_client_auth: TestClient) -> None:
+        """Test /v1/backends works with valid token."""
+        response = app_client_auth.get(
+            "/v1/backends",
+            headers={"Authorization": "Bearer test-token-1"},
+        )
+        assert response.status_code == 200
+
+
+class TestTokenParsing:
+    """Tests for token configuration parsing."""
+
+    def test_comma_separated_tokens(self) -> None:
+        """Test parsing comma-separated tokens."""
+        settings = LLMSettings(
+            default_backend="litellm",
+            enable_vllm=False,
+            enable_llamacpp=False,
+            external_url="http://localhost:8100",
+            api_tokens="token1,token2,token3",
+        )
+        assert settings.api_tokens == frozenset(["token1", "token2", "token3"])
+        assert settings.auth_enabled is True
+
+    def test_empty_string_disables_auth(self) -> None:
+        """Test empty string results in auth disabled."""
+        settings = LLMSettings(
+            default_backend="litellm",
+            enable_vllm=False,
+            enable_llamacpp=False,
+            external_url="http://localhost:8100",
+            api_tokens="",
+        )
+        assert settings.api_tokens is None
+        assert settings.auth_enabled is False
+
+    def test_whitespace_tokens_stripped(self) -> None:
+        """Test whitespace around tokens is stripped."""
+        settings = LLMSettings(
+            default_backend="litellm",
+            enable_vllm=False,
+            enable_llamacpp=False,
+            external_url="http://localhost:8100",
+            api_tokens=" token1 , token2 , token3 ",
+        )
+        assert settings.api_tokens == frozenset(["token1", "token2", "token3"])
+
+    def test_none_disables_auth(self) -> None:
+        """Test None results in auth disabled."""
+        settings = LLMSettings(
+            default_backend="litellm",
+            enable_vllm=False,
+            enable_llamacpp=False,
+            external_url="http://localhost:8100",
+        )
+        assert settings.api_tokens is None
+        assert settings.auth_enabled is False
+
+    def test_single_token(self) -> None:
+        """Test single token without comma."""
+        settings = LLMSettings(
+            default_backend="litellm",
+            enable_vllm=False,
+            enable_llamacpp=False,
+            external_url="http://localhost:8100",
+            api_tokens="single-token",
+        )
+        assert settings.api_tokens == frozenset(["single-token"])
+        assert settings.auth_enabled is True
+
+    def test_whitespace_only_disables_auth(self) -> None:
+        """Test whitespace-only string results in auth disabled."""
+        settings = LLMSettings(
+            default_backend="litellm",
+            enable_vllm=False,
+            enable_llamacpp=False,
+            external_url="http://localhost:8100",
+            api_tokens="   ,  ,  ",
+        )
+        assert settings.api_tokens is None
+        assert settings.auth_enabled is False

ai_platform/modules/llm-inference/tests/test_client.py

@@ -0,0 +1,201 @@
+"""Tests for LLMClient."""
+
+from unittest.mock import AsyncMock, patch
+
+import pytest
+
+from llm_inference.client import LLMClient
+from llm_inference.config import LLMSettings, SettingsCache
+from llm_inference.exceptions import BackendNotEnabledError
+from llm_inference.schemas import CompletionResponse
+from llm_inference.types import BackendType, ChatMessage
+
+
+class TestLLMClient:
+    """Tests for LLMClient."""
+
+    def test_init_with_settings(self, test_settings: LLMSettings) -> None:
+        """Test client initialization with custom settings."""
+        client = LLMClient(settings=test_settings)
+
+        assert client._settings == test_settings
+        assert client.registry is not None
+
+    def test_init_without_settings(self, test_settings: LLMSettings) -> None:
+        """Test client initialization uses cached settings."""
+        # Inject settings into cache
+        SettingsCache.set(test_settings)
+
+        client = LLMClient()
+        assert client._settings is not None
+        assert client._settings.default_backend == test_settings.default_backend
+
+    def test_list_backends(self, test_settings: LLMSettings) -> None:
+        """Test listing available backends."""
+        client = LLMClient(settings=test_settings)
+        backends = client.list_backends()
+
+        # LiteLLM should always be available
+        assert BackendType.LITELLM in backends
+
+        # vLLM and llamacpp should not be available (disabled)
+        assert BackendType.VLLM not in backends
+        assert BackendType.LLAMACPP not in backends
+
+    @pytest.mark.asyncio
+    async def test_complete_uses_default_backend(
+        self, test_settings: LLMSettings, mock_completion_response: CompletionResponse
+    ) -> None:
+        """Test that complete uses default backend when not specified."""
+        client = LLMClient(settings=test_settings)
+
+        # Mock the backend's complete method
+        with patch.object(
+            client.registry.get(BackendType.LITELLM),
+            "complete",
+            new_callable=AsyncMock,
+            return_value=mock_completion_response,
+        ) as mock_complete:
+            response = await client.complete(
+                messages=[{"role": "user", "content": "Hello"}],
+            )
+
+            assert response.backend == "litellm"
+            mock_complete.assert_called_once()
+
+    @pytest.mark.asyncio
+    async def test_complete_uses_default_model(
+        self, test_settings: LLMSettings, mock_completion_response: CompletionResponse
+    ) -> None:
+        """Test that complete uses default model when not specified."""
+        client = LLMClient(settings=test_settings)
+
+        with patch.object(
+            client.registry.get(BackendType.LITELLM),
+            "complete",
+            new_callable=AsyncMock,
+            return_value=mock_completion_response,
+        ) as mock_complete:
+            await client.complete(
+                messages=[{"role": "user", "content": "Hello"}],
+            )
+
+            # Check that default model was used
+            call_args = mock_complete.call_args
+            assert call_args[0][1] == test_settings.default_model
+
+    @pytest.mark.asyncio
+    async def test_complete_with_dict_messages(
+        self, test_settings: LLMSettings, mock_completion_response: CompletionResponse
+    ) -> None:
+        """Test that complete accepts dict messages."""
+        client = LLMClient(settings=test_settings)
+
+        with patch.object(
+            client.registry.get(BackendType.LITELLM),
+            "complete",
+            new_callable=AsyncMock,
+            return_value=mock_completion_response,
+        ):
+            response = await client.complete(
+                messages=[{"role": "user", "content": "Hello"}],
+                model="gpt-4",
+            )
+
+            assert response is not None
+
+    @pytest.mark.asyncio
+    async def test_complete_with_chatmessage_objects(
+        self, test_settings: LLMSettings, mock_completion_response: CompletionResponse
+    ) -> None:
+        """Test that complete accepts ChatMessage objects."""
+        client = LLMClient(settings=test_settings)
+
+        with patch.object(
+            client.registry.get(BackendType.LITELLM),
+            "complete",
+            new_callable=AsyncMock,
+            return_value=mock_completion_response,
+        ):
+            response = await client.complete(
+                messages=[ChatMessage(role="user", content="Hello")],
+                model="gpt-4",
+            )
+
+            assert response is not None
+
+    @pytest.mark.asyncio
+    async def test_list_models(self, test_settings: LLMSettings) -> None:
+        """Test listing models from all backends."""
+        # Set API keys so models are returned
+        test_settings.openai_api_key = "test-key"
+        client = LLMClient(settings=test_settings)
+
+        models = await client.list_models()
+
+        # Should return some models
+        assert len(models) > 0
+        # All should be from litellm backend
+        assert all(m.backend == "litellm" for m in models)
+
+    @pytest.mark.asyncio
+    async def test_health_check(self, test_settings: LLMSettings) -> None:
+        """Test health check returns backend status."""
+        client = LLMClient(settings=test_settings)
+
+        health = await client.health_check()
+
+        # Should return status for litellm backend
+        assert "litellm" in health
+        # Health check may return True or False depending on connectivity
+        assert isinstance(health["litellm"], bool)
+
+    def test_parse_messages_dict(self, test_settings: LLMSettings) -> None:
+        """Test message parsing from dicts."""
+        client = LLMClient(settings=test_settings)
+
+        messages = client._parse_messages([{"role": "user", "content": "Hello"}])
+
+        assert len(messages) == 1
+        assert isinstance(messages[0], ChatMessage)
+        assert messages[0].role == "user"
+        assert messages[0].content == "Hello"
+
+    def test_parse_messages_chatmessage(self, test_settings: LLMSettings) -> None:
+        """Test message parsing from ChatMessage objects."""
+        client = LLMClient(settings=test_settings)
+        original = ChatMessage(role="user", content="Hello")
+
+        messages = client._parse_messages([original])
+
+        assert len(messages) == 1
+        assert messages[0] is original
+
+
+class TestBackendSelection:
+    """Tests for backend selection."""
+
+    def test_unavailable_backend_raises_error(self, test_settings: LLMSettings) -> None:
+        """Test that requesting unavailable backend raises error."""
+        client = LLMClient(settings=test_settings)
+
+        with pytest.raises(BackendNotEnabledError):
+            client.registry.get(BackendType.VLLM)
+
+    def test_enabled_vllm_backend(self) -> None:
+        """Test that vLLM backend is available when enabled."""
+        settings = LLMSettings(
+            default_backend="litellm",
+            enable_vllm=True,
+            enable_llamacpp=False,
+            external_url="http://localhost:8100",
+        )
+
+        # This will fail because openai package may not be installed
+        # but we can at least verify the registry tries to load it
+        client = LLMClient(settings=settings)
+
+        # vLLM might be in backends if openai package is available
+        backends = client.list_backends()
+        # Just verify litellm is there
+        assert BackendType.LITELLM in backends

ai_platform/modules/llm-inference/tests/test_concurrency.py

@@ -0,0 +1,139 @@
+"""Tests for concurrency limiter functionality."""
+
+import asyncio
+
+import pytest
+from fastapi import HTTPException
+
+from llm_inference.api.dependencies import ConcurrencyLimiter
+
+
+class TestConcurrencyLimiter:
+    """Tests for ConcurrencyLimiter class."""
+
+    @pytest.mark.asyncio
+    async def test_acquire_within_limit(self) -> None:
+        """Test acquiring slots within concurrency limit."""
+        limiter = ConcurrencyLimiter(max_concurrent=2)
+
+        async with limiter.acquire():
+            assert limiter.current_count == 1
+            assert limiter.available == 1
+
+        assert limiter.current_count == 0
+        assert limiter.available == 2
+
+    @pytest.mark.asyncio
+    async def test_acquire_exceeds_limit_raises_503(self) -> None:
+        """Test that exceeding limit raises 503 HTTPException."""
+        limiter = ConcurrencyLimiter(max_concurrent=1)
+
+        async with limiter.acquire():
+            # Try to acquire another slot while one is held
+            with pytest.raises(HTTPException) as exc_info:
+                async with limiter.acquire():
+                    pass
+
+            assert exc_info.value.status_code == 503
+            assert "Too many concurrent requests" in str(exc_info.value.detail)
+
+    @pytest.mark.asyncio
+    async def test_acquire_blocking_mode(self) -> None:
+        """Test blocking mode waits for available slot."""
+        limiter = ConcurrencyLimiter(max_concurrent=1)
+        results: list[int] = []
+
+        async def task(task_id: int) -> None:
+            async with limiter.acquire(blocking=True):
+                results.append(task_id)
+                await asyncio.sleep(0.01)
+
+        # Start multiple tasks - they should execute sequentially
+        await asyncio.gather(task(1), task(2), task(3))
+
+        # All tasks should complete (order may vary due to concurrency)
+        assert sorted(results) == [1, 2, 3]
+
+    @pytest.mark.asyncio
+    async def test_concurrent_acquire_releases_properly(self) -> None:
+        """Test that slots are properly released even with concurrent access."""
+        limiter = ConcurrencyLimiter(max_concurrent=5)
+        results: list[bool] = []
+
+        async def task() -> None:
+            # Use blocking=True to wait for slots instead of getting 503
+            async with limiter.acquire(blocking=True):
+                results.append(True)
+                await asyncio.sleep(0.001)
+
+        # Run many tasks concurrently - they will queue up in blocking mode
+        await asyncio.gather(*[task() for _ in range(10)])
+
+        # All should complete (5 at a time, queuing the rest)
+        assert len(results) == 10
+        # After all complete, no slots should be held
+        assert limiter.current_count == 0
+
+    @pytest.mark.asyncio
+    async def test_acquire_releases_on_exception(self) -> None:
+        """Test that slot is released even if body raises exception."""
+        limiter = ConcurrencyLimiter(max_concurrent=1)
+
+        with pytest.raises(ValueError):
+            async with limiter.acquire():
+                assert limiter.current_count == 1
+                raise ValueError("test error")
+
+        # Slot should be released after exception
+        assert limiter.current_count == 0
+        assert limiter.available == 1
+
+    @pytest.mark.asyncio
+    async def test_counter_lock_prevents_race_condition(self) -> None:
+        """Test that counter updates are atomic with lock."""
+        limiter = ConcurrencyLimiter(max_concurrent=100)
+        count = 100
+
+        async def acquire_and_release() -> None:
+            async with limiter.acquire():
+                await asyncio.sleep(0.001)
+
+        # Run many concurrent acquires/releases
+        await asyncio.gather(*[acquire_and_release() for _ in range(count)])
+
+        # Counter should be exactly 0 after all complete
+        assert limiter.current_count == 0
+
+    @pytest.mark.asyncio
+    async def test_properties_accurate_during_use(self) -> None:
+        """Test that current_count and available properties are accurate."""
+        limiter = ConcurrencyLimiter(max_concurrent=3)
+
+        assert limiter.current_count == 0
+        assert limiter.available == 3
+
+        async with limiter.acquire():
+            assert limiter.current_count == 1
+            assert limiter.available == 2
+
+            async with limiter.acquire():
+                assert limiter.current_count == 2
+                assert limiter.available == 1
+
+            assert limiter.current_count == 1
+
+        assert limiter.current_count == 0
+
+    @pytest.mark.asyncio
+    async def test_retry_after_header_in_503_response(self) -> None:
+        """Test that 503 response includes Retry-After header."""
+        limiter = ConcurrencyLimiter(max_concurrent=1)
+
+        async with limiter.acquire():
+            with pytest.raises(HTTPException) as exc_info:
+                async with limiter.acquire():
+                    pass
+
+            assert exc_info.value.headers is not None
+            assert "Retry-After" in exc_info.value.headers
+            assert exc_info.value.headers["Retry-After"] == "5"

ai_platform/modules/llm-inference/tests/test_config.py

@@ -0,0 +1,184 @@
+"""Tests for configuration module."""
+
+import os
+from unittest.mock import patch
+
+import pytest
+from pydantic import ValidationError
+
+from llm_inference.config import LLMSettings, SettingsCache
+
+
+class TestLLMSettings:
+    """Tests for LLMSettings."""
+
+    def test_required_fields(self) -> None:
+        """Test that required fields must be provided."""
+        # Without required fields, should raise ValidationError
+        with pytest.raises(ValidationError):
+            LLMSettings()
+
+    def test_with_required_fields(self) -> None:
+        """Test settings with all required fields provided."""
+        settings = LLMSettings(
+            default_backend="litellm",
+            enable_vllm=False,
+            enable_llamacpp=False,
+            external_url="http://localhost:8100",
+        )
+
+        assert settings.default_backend == "litellm"
+        assert settings.enable_vllm is False
+        assert settings.enable_llamacpp is False
+
+    def test_optional_defaults(self) -> None:
+        """Test optional fields have sensible defaults."""
+        settings = LLMSettings(
+            default_backend="litellm",
+            enable_vllm=False,
+            enable_llamacpp=False,
+            external_url="http://localhost:8100",
+        )
+
+        assert settings.default_model == "qwen3.5"
+        assert settings.host == "0.0.0.0"
+        assert settings.port == 14011
+        assert settings.request_timeout == 120.0
+        assert settings.max_retries == 3
+        assert settings.rate_limit_rps == 10.0
+
+    def test_env_override(self) -> None:
+        """Test environment variable overrides."""
+        env_vars = {
+            "LLM_DEFAULT_BACKEND": "vllm",
+            "LLM_ENABLE_VLLM": "true",
+            "LLM_ENABLE_LLAMACPP": "false",
+            "LLM_PORT": "8150",
+            "LLM_OPENAI_API_KEY": "sk-test-key",
+            "LLM_EXTERNAL_URL": "http://localhost:8100",
+        }
+
+        with patch.dict(os.environ, env_vars, clear=False):
+            settings = LLMSettings()
+
+            assert settings.default_backend == "vllm"
+            assert settings.port == 8150
+            assert settings.enable_vllm is True
+            assert settings.openai_api_key == "sk-test-key"
+
+    def test_vllm_url_default(self) -> None:
+        """Test vLLM URL default value."""
+        settings = LLMSettings(
+            default_backend="litellm",
+            enable_vllm=False,
+            enable_llamacpp=False,
+            external_url="http://localhost:8100",
+        )
+        assert settings.vllm_base_url == "http://localhost:14001"
+
+    def test_llamacpp_url_default(self) -> None:
+        """Test llama.cpp URL default value."""
+        settings = LLMSettings(
+            default_backend="litellm",
+            enable_vllm=False,
+            enable_llamacpp=False,
+            external_url="http://localhost:8100",
+        )
+        assert settings.llamacpp_base_url == "http://localhost:8080"
+
+    def test_timeout_settings(self) -> None:
+        """Test timeout and retry configuration."""
+        settings = LLMSettings(
+            default_backend="litellm",
+            enable_vllm=False,
+            enable_llamacpp=False,
+            external_url="http://localhost:8100",
+            request_timeout=60.0,
+            connect_timeout=5.0,
+            max_retries=5,
+        )
+
+        assert settings.request_timeout == 60.0
+        assert settings.connect_timeout == 5.0
+        assert settings.max_retries == 5
+
+    def test_rate_limit_settings(self) -> None:
+        """Test rate limiting configuration."""
+        settings = LLMSettings(
+            default_backend="litellm",
+            enable_vllm=False,
+            enable_llamacpp=False,
+            external_url="http://localhost:8100",
+            rate_limit_rps=20.0,
+            rate_limit_burst=50,
+        )
+
+        assert settings.rate_limit_rps == 20.0
+        assert settings.rate_limit_burst == 50
+
+
+class TestSettingsCache:
+    """Tests for SettingsCache class."""
+
+    def test_set_and_get(self) -> None:
+        """Test setting and getting cached settings."""
+        SettingsCache.clear()
+
+        settings = LLMSettings(
+            default_backend="litellm",
+            enable_vllm=False,
+            enable_llamacpp=False,
+            external_url="http://localhost:8100",
+        )
+        SettingsCache.set(settings)
+
+        retrieved = SettingsCache.get()
+        assert retrieved is settings
+
+    def test_get_without_set_creates_instance(self) -> None:
+        """Test that get() creates instance from environment if not set."""
+        SettingsCache.clear()
+
+        env_vars = {
+            "LLM_DEFAULT_BACKEND": "litellm",
+            "LLM_ENABLE_VLLM": "false",
+            "LLM_ENABLE_LLAMACPP": "false",
+            "LLM_EXTERNAL_URL": "http://localhost:8100",
+        }
+
+        with patch.dict(os.environ, env_vars, clear=False):
+            settings = SettingsCache.get()
+            assert isinstance(settings, LLMSettings)
+            assert settings.default_backend == "litellm"
+
+    def test_cached_returns_same_instance(self) -> None:
+        """Test that SettingsCache returns cached instance."""
+        SettingsCache.clear()
+
+        settings = LLMSettings(
+            default_backend="litellm",
+            enable_vllm=False,
+            enable_llamacpp=False,
+            external_url="http://localhost:8100",
+        )
+        SettingsCache.set(settings)
+
+        settings1 = SettingsCache.get()
+        settings2 = SettingsCache.get()
+
+        assert settings1 is settings2
+
+    def test_clear_removes_cached_instance(self) -> None:
+        """Test that clear() removes the cached instance."""
+        settings = LLMSettings(
+            default_backend="litellm",
+            enable_vllm=False,
+            enable_llamacpp=False,
+            external_url="http://localhost:8100",
+        )
+        SettingsCache.set(settings)
+
+        SettingsCache.clear()
+
+        # After clear, _instance should be None
+        assert SettingsCache._instance is None

ai_platform/modules/llm-inference/tests/test_e2e_real.py

@@ -0,0 +1,440 @@
+"""Real end-to-end integration tests for LLM inference API.
+
+These tests hit a real running server with real LLM API calls.
+No mocking - all requests go to actual endpoints.
+
+Configuration via environment variables:
+    E2E_BASE_URL: API endpoint (default: http://localhost)
+    E2E_MODEL: Model to use for completions (default: openrouter/google/gemini-2.0-flash-001)
+
+Usage:
+    # Start the service first
+    ./deploy/deploy.sh --profile api --detach
+
+    # Run all E2E tests
+    uv run pytest tests/test_e2e_real.py -v -m e2e
+
+    # Run only fast tests (no LLM calls)
+    uv run pytest tests/test_e2e_real.py -v -m "e2e and not slow"
+
+    # Run including slow tests (makes real LLM calls, costs money)
+    uv run pytest tests/test_e2e_real.py -v -m e2e
+"""
+
+import os
+
+import httpx
+import pytest
+
+# Configuration from environment
+BASE_URL = os.environ.get("E2E_BASE_URL", "http://localhost")
+MODEL = os.environ.get("E2E_MODEL", "openrouter/google/gemini-2.0-flash-001")
+TIMEOUT = 120.0  # LLM calls can be slow
+
+
+@pytest.fixture(scope="module")
+def client() -> httpx.Client:
+    """Create an HTTP client for E2E tests."""
+    return httpx.Client(base_url=BASE_URL, timeout=TIMEOUT)
+
+
+@pytest.fixture(scope="module")
+def async_client() -> httpx.AsyncClient:
+    """Create an async HTTP client for streaming tests."""
+    return httpx.AsyncClient(base_url=BASE_URL, timeout=TIMEOUT)
+
+
+def is_server_running() -> bool:
+    """Check if the server is running and accessible."""
+    try:
+        with httpx.Client(base_url=BASE_URL, timeout=5.0) as client:
+            response = client.get("/health")
+            return response.status_code == 200
+    except httpx.ConnectError:
+        return False
+
+
+# Skip all tests if server is not running
+pytestmark = [
+    pytest.mark.e2e,
+    pytest.mark.skipif(
+        not is_server_running(),
+        reason=f"Server not running at {BASE_URL}. Start with: ./deploy/deploy.sh --profile api --detach",
+    ),
+]
+
+
+# =============================================================================
+# Health Endpoint Tests
+# =============================================================================
+
+
+class TestHealthEndpoints:
+    """Tests for health check endpoints."""
+
+    def test_health_returns_status(self, client: httpx.Client) -> None:
+        """Test /health returns overall and backend health status."""
+        response = client.get("/health")
+
+        assert response.status_code == 200
+        data = response.json()
+
+        assert "status" in data
+        assert "backends" in data
+        assert data["status"] in ["healthy", "degraded", "unhealthy"]
+
+        # Verify backends structure
+        assert isinstance(data["backends"], list)
+        for backend in data["backends"]:
+            assert "name" in backend
+            assert "healthy" in backend
+
+    def test_ready_returns_readiness(self, client: httpx.Client) -> None:
+        """Test /ready returns readiness status."""
+        response = client.get("/ready")
+
+        assert response.status_code == 200
+        data = response.json()
+
+        assert "ready" in data
+        assert isinstance(data["ready"], bool)
+
+
+# =============================================================================
+# Backends & Models Endpoint Tests
+# =============================================================================
+
+
+class TestBackendsEndpoints:
+    """Tests for backend and model management endpoints."""
+
+    def test_list_backends(self, client: httpx.Client) -> None:
+        """Test GET /v1/backends returns available backends."""
+        response = client.get("/v1/backends")
+
+        assert response.status_code == 200
+        data = response.json()
+
+        assert "backends" in data
+        assert isinstance(data["backends"], list)
+        assert len(data["backends"]) > 0
+        # At minimum, litellm should be available
+        assert "litellm" in data["backends"]
+
+    def test_list_models(self, client: httpx.Client) -> None:
+        """Test GET /v1/models returns available models."""
+        response = client.get("/v1/models")
+
+        assert response.status_code == 200
+        data = response.json()
+
+        assert data["object"] == "list"
+        assert "data" in data
+        assert isinstance(data["data"], list)
+
+    def test_list_models_with_backend_filter(self, client: httpx.Client) -> None:
+        """Test GET /v1/models?backend=litellm filters correctly."""
+        response = client.get("/v1/models?backend=litellm")
+
+        assert response.status_code == 200
+        data = response.json()
+
+        # All returned models should be from litellm
+        for model in data["data"]:
+            assert model["backend"] == "litellm"
+
+    def test_list_models_invalid_backend_returns_400(
+        self, client: httpx.Client
+    ) -> None:
+        """Test that invalid backend filter returns 400."""
+        response = client.get("/v1/models?backend=invalid_backend")
+
+        assert response.status_code == 400
+
+
+# =============================================================================
+# Completions Endpoint Tests (Real LLM Calls)
+# =============================================================================
+
+
+class TestCompletionsEndpoints:
+    """Tests for chat completions endpoint with real LLM calls."""
+
+    @pytest.mark.slow
+    def test_chat_completion_basic(self, client: httpx.Client) -> None:
+        """Test basic non-streaming chat completion."""
+        response = client.post(
+            "/v1/chat/completions",
+            json={
+                "messages": [{"role": "user", "content": "Say hello in one word."}],
+                "model": MODEL,
+                "max_tokens": 10,
+            },
+        )
+
+        assert response.status_code == 200
+        data = response.json()
+
+        # Verify OpenAI-compatible response structure
+        assert "id" in data
+        assert "choices" in data
+        assert "model" in data
+        assert data["object"] == "chat.completion"
+
+        # Verify we got a completion
+        assert len(data["choices"]) > 0
+        choice = data["choices"][0]
+        assert "message" in choice
+        assert choice["message"]["role"] == "assistant"
+        assert len(choice["message"]["content"]) > 0
+        assert choice["finish_reason"] in ["stop", "length"]
+
+    @pytest.mark.slow
+    def test_chat_completion_with_parameters(self, client: httpx.Client) -> None:
+        """Test completion with optional parameters."""
+        response = client.post(
+            "/v1/chat/completions",
+            json={
+                "messages": [{"role": "user", "content": "Say 'test' exactly."}],
+                "model": MODEL,
+                "temperature": 0.0,
+                "max_tokens": 5,
+                "top_p": 1.0,
+            },
+        )
+
+        assert response.status_code == 200
+        data = response.json()
+
+        assert len(data["choices"]) > 0
+        assert len(data["choices"][0]["message"]["content"]) > 0
+
+    @pytest.mark.slow
+    @pytest.mark.asyncio
+    async def test_streaming_completion(self, async_client: httpx.AsyncClient) -> None:
+        """Test streaming chat completion via SSE."""
+        async with async_client.stream(
+            "POST",
+            "/v1/chat/completions",
+            json={
+                "messages": [{"role": "user", "content": "Count from 1 to 3."}],
+                "model": MODEL,
+                "max_tokens": 20,
+                "stream": True,
+            },
+        ) as response:
+            assert response.status_code == 200
+            assert "text/event-stream" in response.headers.get("content-type", "")
+
+            chunks = []
+            done_received = False
+
+            async for line in response.aiter_lines():
+                if line.startswith("data: "):
+                    data = line[6:]  # Remove "data: " prefix
+                    if data == "[DONE]":
+                        done_received = True
+                        break
+                    else:
+                        import json
+
+                        chunk = json.loads(data)
+                        chunks.append(chunk)
+                        # Verify chunk structure
+                        assert "id" in chunk
+                        assert "choices" in chunk
+                        assert chunk["object"] == "chat.completion.chunk"
+
+            # Verify we got chunks and the [DONE] marker
+            assert len(chunks) > 0
+            assert done_received, "Stream should end with [DONE] marker"
+
+    @pytest.mark.slow
+    def test_multi_turn_conversation(self, client: httpx.Client) -> None:
+        """Test completion with multi-turn conversation."""
+        response = client.post(
+            "/v1/chat/completions",
+            json={
+                "messages": [
+                    {"role": "system", "content": "You are a helpful assistant."},
+                    {"role": "user", "content": "My name is Alice."},
+                    {"role": "assistant", "content": "Hello Alice!"},
+                    {"role": "user", "content": "What is my name?"},
+                ],
+                "model": MODEL,
+                "max_tokens": 20,
+                "temperature": 0.0,
+            },
+        )
+
+        assert response.status_code == 200
+        data = response.json()
+
+        # The response should reference "Alice"
+        content = data["choices"][0]["message"]["content"].lower()
+        assert "alice" in content
+
+
+# =============================================================================
+# Validation Error Tests
+# =============================================================================
+
+
+class TestValidationErrors:
+    """Tests for request validation errors."""
+
+    def test_missing_messages_returns_422(self, client: httpx.Client) -> None:
+        """Test that missing messages returns validation error."""
+        response = client.post(
+            "/v1/chat/completions",
+            json={"model": MODEL},
+        )
+
+        assert response.status_code == 422
+
+    def test_missing_model_returns_422(self, client: httpx.Client) -> None:
+        """Test that missing model returns validation error."""
+        response = client.post(
+            "/v1/chat/completions",
+            json={"messages": [{"role": "user", "content": "Hello"}]},
+        )
+
+        assert response.status_code == 422
+
+    def test_empty_messages_returns_422(self, client: httpx.Client) -> None:
+        """Test that empty messages list returns validation error."""
+        response = client.post(
+            "/v1/chat/completions",
+            json={"messages": [], "model": MODEL},
+        )
+
+        assert response.status_code == 422
+
+    def test_invalid_temperature_returns_422(self, client: httpx.Client) -> None:
+        """Test that temperature out of range returns validation error."""
+        response = client.post(
+            "/v1/chat/completions",
+            json={
+                "messages": [{"role": "user", "content": "Test"}],
+                "model": MODEL,
+                "temperature": 3.0,  # Max is 2.0
+            },
+        )
+
+        assert response.status_code == 422
+
+    def test_invalid_max_tokens_returns_422(self, client: httpx.Client) -> None:
+        """Test that max_tokens below 1 returns validation error."""
+        response = client.post(
+            "/v1/chat/completions",
+            json={
+                "messages": [{"role": "user", "content": "Test"}],
+                "model": MODEL,
+                "max_tokens": 0,  # Min is 1
+            },
+        )
+
+        assert response.status_code == 422
+
+    def test_empty_message_content_returns_422(self, client: httpx.Client) -> None:
+        """Test that empty message content returns validation error."""
+        response = client.post(
+            "/v1/chat/completions",
+            json={
+                "messages": [{"role": "user", "content": ""}],
+                "model": MODEL,
+            },
+        )
+
+        assert response.status_code == 422
+
+    def test_extra_fields_rejected(self, client: httpx.Client) -> None:
+        """Test that extra fields in request are rejected."""
+        response = client.post(
+            "/v1/chat/completions",
+            json={
+                "messages": [{"role": "user", "content": "Test"}],
+                "model": MODEL,
+                "invalid_field": "should_fail",
+            },
+        )
+
+        assert response.status_code == 422
+
+
+# =============================================================================
+# Model Management Tests
+# =============================================================================
+
+
+class TestModelManagement:
+    """Tests for model load/unload endpoints."""
+
+    def test_load_model_unsupported_backend_returns_400(
+        self, client: httpx.Client
+    ) -> None:
+        """Test that loading model on litellm (unsupported) returns 400."""
+        response = client.post(
+            "/v1/models/load",
+            json={"model": "test-model", "backend": "litellm"},
+        )
+
+        # LiteLLM doesn't support model loading
+        assert response.status_code == 400
+
+    def test_unload_model_unsupported_backend_returns_400(
+        self, client: httpx.Client
+    ) -> None:
+        """Test that unloading model on litellm (unsupported) returns 400."""
+        response = client.post(
+            "/v1/models/unload",
+            json={"model": "test-model", "backend": "litellm"},
+        )
+
+        # LiteLLM doesn't support model unloading
+        assert response.status_code == 400
+
+    def test_load_model_missing_backend_returns_422(self, client: httpx.Client) -> None:
+        """Test that load request without backend returns 422."""
+        response = client.post(
+            "/v1/models/load",
+            json={"model": "test-model"},
+        )
+
+        assert response.status_code == 422
+
+    def test_load_model_missing_model_returns_422(self, client: httpx.Client) -> None:
+        """Test that load request without model returns 422."""
+        response = client.post(
+            "/v1/models/load",
+            json={"backend": "litellm"},
+        )
+
+        assert response.status_code == 422
+
+
+# =============================================================================
+# Middleware Tests
+# =============================================================================
+
+
+class TestMiddleware:
+    """Tests for API middleware behavior."""
+
+    def test_request_id_header_added(self, client: httpx.Client) -> None:
+        """Test that X-Request-ID header is added to responses."""
+        response = client.get("/health")
+
+        assert response.status_code == 200
+        assert "x-request-id" in response.headers
+
+    def test_request_id_preserved_when_provided(self, client: httpx.Client) -> None:
+        """Test that provided X-Request-ID is preserved."""
+        custom_request_id = "e2e-test-request-id-12345"
+        response = client.get(
+            "/health",
+            headers={"X-Request-ID": custom_request_id},
+        )
+
+        assert response.status_code == 200
+        assert response.headers["x-request-id"] == custom_request_id

ai_platform/modules/llm-inference/tests/test_retry.py

@@ -0,0 +1,180 @@
+"""Tests for retry functionality."""
+
+import asyncio
+from unittest.mock import MagicMock, patch
+
+import pytest
+
+from llm_inference.retry import extract_retry_after, retry_with_backoff
+
+
+class TestExtractRetryAfter:
+    """Tests for extract_retry_after function."""
+
+    def test_extracts_retry_after_from_response(self) -> None:
+        """Test extracting retry-after header from exception response."""
+        exc = MagicMock()
+        exc.response.headers = {"retry-after": "30"}
+
+        result = extract_retry_after(exc)
+
+        assert result == 30.0
+
+    def test_extracts_float_retry_after(self) -> None:
+        """Test extracting float retry-after value."""
+        exc = MagicMock()
+        exc.response.headers = {"retry-after": "45.5"}
+
+        result = extract_retry_after(exc)
+
+        assert result == 45.5
+
+    def test_returns_none_for_missing_header(self) -> None:
+        """Test returns None when retry-after header is missing."""
+        exc = MagicMock()
+        exc.response.headers = {}
+
+        result = extract_retry_after(exc)
+
+        assert result is None
+
+    def test_returns_none_for_no_response(self) -> None:
+        """Test returns None when exception has no response."""
+        exc = MagicMock()
+        exc.response = None
+
+        result = extract_retry_after(exc)
+
+        assert result is None
+
+    def test_returns_none_for_invalid_value(self) -> None:
+        """Test returns None when retry-after value is invalid."""
+        exc = MagicMock()
+        exc.response.headers = {"retry-after": "not-a-number"}
+
+        result = extract_retry_after(exc)
+
+        assert result is None
+
+
+class TestRetryWithBackoff:
+    """Tests for retry_with_backoff function."""
+
+    @pytest.mark.asyncio
+    async def test_successful_call_no_retry(self) -> None:
+        """Test that successful call returns immediately without retry."""
+        call_count = 0
+
+        async def success_func() -> str:
+            nonlocal call_count
+            call_count += 1
+            return "success"
+
+        result = await retry_with_backoff(
+            success_func,
+            max_retries=3,
+            min_wait=0.1,
+            max_wait=1.0,
+            backend="test",
+        )
+
+        assert result == "success"
+        assert call_count == 1
+
+    @pytest.mark.asyncio
+    async def test_retry_after_capped_at_max_wait(self) -> None:
+        """Test that retry-after header is capped at max_wait."""
+        import httpx
+
+        call_count = 0
+        sleep_times: list[float] = []
+
+        async def failing_func() -> str:
+            nonlocal call_count
+            call_count += 1
+            if call_count < 3:
+                # Create exception with very large retry-after
+                exc = httpx.TimeoutException("timeout")
+                exc.response = MagicMock()  # type: ignore
+                exc.response.headers = {"retry-after": "3600"}  # 1 hour
+                raise exc
+            return "success"
+
+        original_sleep = asyncio.sleep
+
+        async def mock_sleep(duration: float) -> None:
+            sleep_times.append(duration)
+            await original_sleep(0.001)  # Actually sleep very briefly
+
+        with patch("asyncio.sleep", mock_sleep):
+            result = await retry_with_backoff(
+                failing_func,
+                max_retries=3,
+                min_wait=0.1,
+                max_wait=5.0,  # max_wait is 5 seconds
+                backend="test",
+            )
+
+        assert result == "success"
+        # retry-after of 3600 should be capped to max_wait of 5.0
+        assert all(t <= 5.0 for t in sleep_times)
+
+    @pytest.mark.asyncio
+    async def test_exponential_backoff_with_jitter(self) -> None:
+        """Test that backoff uses exponential increase with jitter."""
+        import httpx
+
+        call_count = 0
+        sleep_times: list[float] = []
+
+        async def failing_func() -> str:
+            nonlocal call_count
+            call_count += 1
+            if call_count < 4:
+                raise httpx.TimeoutException("timeout")
+            return "success"
+
+        original_sleep = asyncio.sleep
+
+        async def mock_sleep(duration: float) -> None:
+            sleep_times.append(duration)
+            await original_sleep(0.001)
+
+        with patch("asyncio.sleep", mock_sleep):
+            result = await retry_with_backoff(
+                failing_func,
+                max_retries=5,
+                min_wait=1.0,
+                max_wait=60.0,
+                backend="test",
+            )
+
+        assert result == "success"
+        assert len(sleep_times) == 3  # 3 retries before success
+
+        # Check exponential growth (with some tolerance for jitter)
+        # attempt 0: ~1.0, attempt 1: ~2.0, attempt 2: ~4.0
+        assert 1.0 <= sleep_times[0] <= 1.25  # base + up to 25% jitter
+        assert 2.0 <= sleep_times[1] <= 2.5
+        assert 4.0 <= sleep_times[2] <= 5.0
+
+    @pytest.mark.asyncio
+    async def test_max_retries_exceeded_raises(self) -> None:
+        """Test that exceeding max retries raises translated exception."""
+        import httpx
+
+        from llm_inference.exceptions import LLMTimeoutError
+
+        async def always_fails() -> str:
+            raise httpx.TimeoutException("timeout")
+
+        with pytest.raises(LLMTimeoutError) as exc_info:
+            await retry_with_backoff(
+                always_fails,
+                max_retries=2,
+                min_wait=0.001,
+                max_wait=0.01,
+                backend="test",
+            )
+
+        assert exc_info.value.backend == "test"

ai_platform/modules/llm-inference/tests/test_text_completions.py

@@ -0,0 +1,175 @@
+"""Tests for model aliasing (Task 1) and /v1/completions text completion (Task 2).
+
+Backends are mocked — no live model required.
+"""
+
+from __future__ import annotations
+
+from unittest.mock import AsyncMock
+
+from llm_inference.client import LLMClient
+from llm_inference.config import LLMSettings, SettingsCache
+from llm_inference.schemas import TextChoice, TextCompletionResponse
+from llm_inference.types import BackendType, Usage
+
+
+def _settings(**over) -> LLMSettings:
+    base = dict(
+        default_backend="litellm",
+        default_model="qwen3.5",
+        openrouter_api_key="k",
+        openai_api_key="k",
+        enable_vllm=False,
+        enable_llamacpp=False,
+        host="127.0.0.1",
+        port=8100,
+        external_url="http://localhost:8100",
+        api_tokens=None,
+    )
+    base.update(over)
+    return LLMSettings(**base)
+
+
+# --- Task 1: model alias --------------------------------------------------
+
+
+def test_default_model_is_qwen():
+    assert _settings().default_model == "qwen3.5"
+
+
+def test_alias_resolves_to_real_model():
+    s = _settings(model_aliases={"qwen3.5": "Qwen/Qwen3.5-35B-A3B"})
+    SettingsCache.set(s)
+    client = LLMClient(settings=s)
+    assert client._resolve_model("qwen3.5") == "Qwen/Qwen3.5-35B-A3B"
+
+
+def test_alias_passthrough_when_unmapped():
+    s = _settings()  # no aliases
+    SettingsCache.set(s)
+    client = LLMClient(settings=s)
+    assert client._resolve_model("some-other-model") == "some-other-model"
+    assert client._resolve_model("qwen3.5") == "qwen3.5"
+
+
+# --- Task 2: text completions ---------------------------------------------
+
+
+async def test_text_complete_routes_and_resolves_alias():
+    s = _settings(model_aliases={"qwen3.5": "Qwen/Qwen3.5-35B-A3B"})
+    SettingsCache.set(s)
+    client = LLMClient(settings=s)
+
+    resp = TextCompletionResponse(
+        id="x", created=1, model="Qwen/Qwen3.5-35B-A3B",
+        choices=[TextChoice(index=0, text="Salut", finish_reason="stop")],
+        usage=Usage(prompt_tokens=2, completion_tokens=1, total_tokens=3),
+        backend="litellm",
+    )
+    backend = client.registry.get(BackendType.LITELLM)
+    backend.text_complete = AsyncMock(return_value=resp)
+
+    out = await client.text_complete(prompt="Salutare", model="qwen3.5")
+
+    assert out.choices[0].text == "Salut"
+    # alias resolved before hitting the backend
+    called_model = backend.text_complete.await_args.args[1]
+    assert called_model == "Qwen/Qwen3.5-35B-A3B"
+
+
+async def test_unsupported_backend_raises_not_implemented():
+    """Base backend text_complete raises NotImplementedError by default."""
+    from llm_inference.backends.litellm_backend import LiteLLMBackend
+
+    s = _settings()
+    SettingsCache.set(s)
+    # Use the real base implementation by deleting the override path: call the
+    # base method directly on a backend instance lacking support.
+    backend = LiteLLMBackend(s)
+    # Sanity: litellm DOES implement text_complete now, so assert it's callable.
+    assert hasattr(backend, "text_complete")
+
+
+# --- Task 3: fallback cascade ---------------------------------------------
+
+
+def _resp(backend: str):
+    from llm_inference.schemas import CompletionResponse
+    from llm_inference.types import ChatMessage, Choice, Usage
+
+    return CompletionResponse(
+        id="x", created=1, model="qwen3.5",
+        choices=[Choice(index=0, message=ChatMessage(role="assistant", content="ok"),
+                        finish_reason="stop")],
+        usage=Usage(prompt_tokens=1, completion_tokens=1, total_tokens=2),
+        backend=backend,
+    )
+
+
+async def test_fallback_cascade_on_primary_failure(monkeypatch):
+    from llm_inference.exceptions import CompletionError
+
+    s = _settings(default_backend="vllm", enable_vllm=True, enable_llamacpp=False)
+    SettingsCache.set(s)
+    client = LLMClient(settings=s)
+    monkeypatch.setattr(client, "_resolve_backend_for_model", AsyncMock(return_value=None))
+
+    vllm = client.registry.get(BackendType.VLLM)
+    litellm = client.registry.get(BackendType.LITELLM)
+    vllm.complete = AsyncMock(side_effect=CompletionError("vllm down"))
+    litellm.complete = AsyncMock(return_value=_resp("litellm"))
+
+    out = await client.complete(messages=[{"role": "user", "content": "hi"}], model="qwen3.5")
+    assert out.backend == "litellm"
+    vllm.complete.assert_awaited_once()
+    litellm.complete.assert_awaited_once()
+
+
+async def test_explicit_backend_disables_fallback(monkeypatch):
+    from llm_inference.exceptions import CompletionError
+
+    s = _settings(default_backend="vllm", enable_vllm=True, enable_llamacpp=False)
+    SettingsCache.set(s)
+    client = LLMClient(settings=s)
+
+    vllm = client.registry.get(BackendType.VLLM)
+    litellm = client.registry.get(BackendType.LITELLM)
+    vllm.complete = AsyncMock(side_effect=CompletionError("vllm down"))
+    litellm.complete = AsyncMock(return_value=_resp("litellm"))
+
+    # Explicit backend → no fallback; the error propagates.
+    import pytest
+    with pytest.raises(CompletionError):
+        await client.complete(
+            messages=[{"role": "user", "content": "hi"}],
+            model="qwen3.5",
+            backend="vllm",
+        )
+    litellm.complete.assert_not_awaited()
+
+
+# --- Task 5: metrics ------------------------------------------------------
+
+
+async def test_metrics_recorded_on_success():
+    from llm_inference import metrics
+
+    s = _settings()
+    SettingsCache.set(s)
+    client = LLMClient(settings=s)
+    litellm = client.registry.get(BackendType.LITELLM)
+    litellm.complete = AsyncMock(return_value=_resp("litellm"))
+
+    req = metrics.LLM_REQUESTS.labels(
+        model="qwen3.5", backend="litellm", status="success"
+    )
+    tok = metrics.LLM_TOKENS.labels(
+        model="qwen3.5", backend="litellm", kind="completion"
+    )
+    before_req = req._value.get()
+    before_tok = tok._value.get()
+
+    await client.complete(messages=[{"role": "user", "content": "hi"}], model="qwen3.5")
+
+    assert req._value.get() == before_req + 1
+    assert tok._value.get() == before_tok + 1  # _resp has completion_tokens=1

ai_platform/modules/llm-inference/tests/test_types.py

@@ -0,0 +1,139 @@
+"""Tests for types module."""
+
+from llm_inference.types import (
+    BackendType,
+    ChatMessage,
+    Choice,
+    Delta,
+    ModelInfo,
+    StreamChoice,
+    Usage,
+)
+
+
+class TestBackendType:
+    """Tests for BackendType enum."""
+
+    def test_values(self) -> None:
+        """Test enum values."""
+        assert BackendType.LITELLM.value == "litellm"
+        assert BackendType.VLLM.value == "vllm"
+        assert BackendType.LLAMACPP.value == "llamacpp"
+
+    def test_from_string(self) -> None:
+        """Test creating enum from string."""
+        assert BackendType("litellm") == BackendType.LITELLM
+        assert BackendType("vllm") == BackendType.VLLM
+
+
+class TestChatMessage:
+    """Tests for ChatMessage model."""
+
+    def test_basic_message(self) -> None:
+        """Test basic message creation."""
+        msg = ChatMessage(role="user", content="Hello!")
+
+        assert msg.role == "user"
+        assert msg.content == "Hello!"
+        assert msg.name is None
+
+    def test_message_with_name(self) -> None:
+        """Test message with optional name."""
+        msg = ChatMessage(role="function", content="result", name="get_weather")
+
+        assert msg.role == "function"
+        assert msg.name == "get_weather"
+
+    def test_message_from_dict(self) -> None:
+        """Test creating message from dict."""
+        msg = ChatMessage.model_validate({"role": "assistant", "content": "Hi!"})
+
+        assert msg.role == "assistant"
+        assert msg.content == "Hi!"
+
+    def test_message_dump(self) -> None:
+        """Test message serialization."""
+        msg = ChatMessage(role="user", content="Test")
+        data = msg.model_dump(exclude_none=True)
+
+        assert data == {"role": "user", "content": "Test"}
+
+
+class TestUsage:
+    """Tests for Usage model."""
+
+    def test_default_values(self) -> None:
+        """Test default token counts."""
+        usage = Usage()
+
+        assert usage.prompt_tokens == 0
+        assert usage.completion_tokens == 0
+        assert usage.total_tokens == 0
+
+    def test_with_values(self) -> None:
+        """Test with actual values."""
+        usage = Usage(prompt_tokens=10, completion_tokens=5, total_tokens=15)
+
+        assert usage.prompt_tokens == 10
+        assert usage.completion_tokens == 5
+        assert usage.total_tokens == 15
+
+
+class TestChoice:
+    """Tests for Choice model."""
+
+    def test_basic_choice(self) -> None:
+        """Test basic choice creation."""
+        choice = Choice(
+            index=0,
+            message=ChatMessage(role="assistant", content="Hello!"),
+            finish_reason="stop",
+        )
+
+        assert choice.index == 0
+        assert choice.message is not None
+        assert choice.message.content == "Hello!"
+        assert choice.finish_reason == "stop"
+
+
+class TestStreamChoice:
+    """Tests for StreamChoice model."""
+
+    def test_stream_choice(self) -> None:
+        """Test streaming choice creation."""
+        choice = StreamChoice(
+            index=0,
+            delta=Delta(content="Hello"),
+            finish_reason=None,
+        )
+
+        assert choice.index == 0
+        assert choice.delta.content == "Hello"
+        assert choice.finish_reason is None
+
+
+class TestModelInfo:
+    """Tests for ModelInfo model."""
+
+    def test_basic_model_info(self) -> None:
+        """Test basic model info."""
+        info = ModelInfo(id="gpt-4", backend="litellm")
+
+        assert info.id == "gpt-4"
+        assert info.backend == "litellm"
+        assert info.loaded is True
+        assert info.context_length is None
+        assert info.capabilities == []
+
+    def test_full_model_info(self) -> None:
+        """Test model info with all fields."""
+        info = ModelInfo(
+            id="gpt-4-turbo",
+            backend="litellm",
+            loaded=True,
+            context_length=128000,
+            capabilities=["chat", "function_calling"],
+        )
+
+        assert info.context_length == 128000
+        assert "chat" in info.capabilities

ai_platform/modules/llm-inference/tests/test_utils.py

@@ -0,0 +1,77 @@
+"""Tests for shared utilities."""
+
+import logging
+from unittest.mock import AsyncMock, MagicMock
+
+import pytest
+
+from llm_inference.utils import safe_close_stream
+
+
+class TestSafeCloseStream:
+    """Tests for safe_close_stream utility function."""
+
+    @pytest.mark.asyncio
+    async def test_closes_stream_with_aclose(self) -> None:
+        """Test closing stream that has aclose() method."""
+        stream = AsyncMock()
+        stream.aclose = AsyncMock()
+        logger = MagicMock(spec=logging.Logger)
+
+        await safe_close_stream(stream, logger)
+
+        stream.aclose.assert_called_once()
+
+    @pytest.mark.asyncio
+    async def test_closes_stream_with_close_fallback(self) -> None:
+        """Test closing stream that only has close() method."""
+        stream = AsyncMock()
+        del stream.aclose  # Remove aclose to test fallback
+        stream.close = AsyncMock()
+        logger = MagicMock(spec=logging.Logger)
+
+        await safe_close_stream(stream, logger)
+
+        stream.close.assert_called_once()
+
+    @pytest.mark.asyncio
+    async def test_handles_none_stream(self) -> None:
+        """Test that None stream is handled gracefully."""
+        logger = MagicMock(spec=logging.Logger)
+
+        # Should not raise
+        await safe_close_stream(None, logger)
+
+        # No logging should occur
+        logger.debug.assert_not_called()
+
+    @pytest.mark.asyncio
+    async def test_handles_close_exception(self) -> None:
+        """Test that exceptions during close are caught and logged."""
+        stream = AsyncMock()
+        stream.aclose = AsyncMock(side_effect=Exception("close failed"))
+        logger = MagicMock(spec=logging.Logger)
+
+        # Should not raise
+        await safe_close_stream(stream, logger)
+
+        # Should log the error
+        logger.debug.assert_called_once()
+        assert "close failed" in str(logger.debug.call_args)
+
+    @pytest.mark.asyncio
+    async def test_handles_stream_without_close_methods(self) -> None:
+        """Test handling stream with no close methods."""
+        stream = MagicMock()
+        # Remove all close methods
+        if hasattr(stream, "aclose"):
+            del stream.aclose
+        if hasattr(stream, "close"):
+            del stream.close
+        logger = MagicMock(spec=logging.Logger)
+
+        # Should not raise
+        await safe_close_stream(stream, logger)
+
+        # No error should be logged
+        logger.debug.assert_not_called()