Add shared ai-service container as AI provider intermediary
All feature containers now POST messages to ai-service (port 8010) instead of calling AI providers directly. ai-service routes to LM Studio, Ollama, or Anthropic based on /config/ai_service_config.json. doc-service AI providers removed; replaced by httpx ai_client.py. Backend settings restructured to /api/settings/ai. Frontend gets dedicated AIAdminSettingsPage and AI Service card in AppsPage. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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curo1305
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"""Tests for POST /chat."""
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import asyncio
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from unittest.mock import AsyncMock, MagicMock, patch
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import pytest
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from tests.conftest import ANTHROPIC_CONFIG, LMSTUDIO_CONFIG, OLLAMA_CONFIG
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# ---------------------------------------------------------------------------
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# Helpers
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# ---------------------------------------------------------------------------
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_LOAD_CONFIG = "app.routers.chat.load_ai_config"
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_PROVIDER_CHAT = "app.providers.openai_compat.OpenAICompatProvider.chat"
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_ANTHROPIC_CHAT = "app.providers.anthropic_provider.AnthropicProvider.chat"
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MESSAGES = [{"role": "user", "content": "Hello"}]
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SYSTEM_MESSAGES = [
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{"role": "system", "content": "You are helpful."},
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{"role": "user", "content": "Hello"},
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]
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def _mock_chat_response(content="ok", input_tokens=10, output_tokens=5):
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return AsyncMock(return_value=(content, input_tokens, output_tokens))
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# ---------------------------------------------------------------------------
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# Success: each provider
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# ---------------------------------------------------------------------------
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@pytest.mark.asyncio
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async def test_chat_lmstudio_success(ai_client):
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with patch(_LOAD_CONFIG, return_value=LMSTUDIO_CONFIG), patch(
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_PROVIDER_CHAT, new=_mock_chat_response("lmstudio reply")
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):
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resp = await ai_client.post("/chat", json={"messages": MESSAGES})
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assert resp.status_code == 200
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data = resp.json()
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assert data["content"] == "lmstudio reply"
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assert data["provider"] == "lmstudio"
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assert data["model"] == "test-model"
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assert data["input_tokens"] == 10
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assert data["output_tokens"] == 5
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@pytest.mark.asyncio
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async def test_chat_ollama_success(ai_client):
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with patch(_LOAD_CONFIG, return_value=OLLAMA_CONFIG), patch(
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_PROVIDER_CHAT, new=_mock_chat_response("ollama reply")
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):
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resp = await ai_client.post("/chat", json={"messages": MESSAGES})
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assert resp.status_code == 200
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data = resp.json()
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assert data["content"] == "ollama reply"
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assert data["provider"] == "ollama"
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@pytest.mark.asyncio
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async def test_chat_anthropic_success(ai_client):
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with patch(_LOAD_CONFIG, return_value=ANTHROPIC_CONFIG), patch(
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_ANTHROPIC_CHAT, new=_mock_chat_response("anthropic reply")
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):
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resp = await ai_client.post("/chat", json={"messages": MESSAGES})
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assert resp.status_code == 200
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data = resp.json()
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assert data["content"] == "anthropic reply"
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assert data["provider"] == "anthropic"
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# ---------------------------------------------------------------------------
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# response_format
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# ---------------------------------------------------------------------------
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@pytest.mark.asyncio
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async def test_response_format_json_strips_fences(ai_client):
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fenced = "```json\n{\"key\": \"value\"}\n```"
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with patch(_LOAD_CONFIG, return_value=LMSTUDIO_CONFIG), patch(
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_PROVIDER_CHAT, new=_mock_chat_response(fenced)
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):
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resp = await ai_client.post(
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"/chat",
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json={"messages": MESSAGES, "response_format": "json"},
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)
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assert resp.status_code == 200
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assert resp.json()["content"] == '{"key": "value"}'
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@pytest.mark.asyncio
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async def test_response_format_text_preserves_fences(ai_client):
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fenced = "```python\nprint('hi')\n```"
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with patch(_LOAD_CONFIG, return_value=LMSTUDIO_CONFIG), patch(
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_PROVIDER_CHAT, new=_mock_chat_response(fenced)
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):
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resp = await ai_client.post(
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"/chat",
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json={"messages": MESSAGES, "response_format": "text"},
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)
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assert resp.status_code == 200
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assert "```" in resp.json()["content"]
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# ---------------------------------------------------------------------------
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# Validation errors
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# ---------------------------------------------------------------------------
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@pytest.mark.asyncio
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async def test_chat_missing_messages_returns_422(ai_client):
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resp = await ai_client.post("/chat", json={})
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assert resp.status_code == 422
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@pytest.mark.asyncio
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async def test_chat_empty_messages_returns_422(ai_client):
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resp = await ai_client.post("/chat", json={"messages": []})
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assert resp.status_code == 422
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# ---------------------------------------------------------------------------
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# Provider errors
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# ---------------------------------------------------------------------------
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@pytest.mark.asyncio
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async def test_chat_connection_error_returns_502(ai_client):
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from app.providers.openai_compat import ProviderConnectionError
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with patch(_LOAD_CONFIG, return_value=LMSTUDIO_CONFIG), patch(
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_PROVIDER_CHAT, side_effect=ProviderConnectionError("refused")
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):
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resp = await ai_client.post("/chat", json={"messages": MESSAGES})
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assert resp.status_code == 502
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@pytest.mark.asyncio
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async def test_chat_timeout_returns_504(ai_client):
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async def _slow(*_args, **_kwargs):
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await asyncio.sleep(100)
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with patch(_LOAD_CONFIG, return_value={**LMSTUDIO_CONFIG, "timeout_seconds": 0.01}), patch(
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_PROVIDER_CHAT, new=_slow
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):
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resp = await ai_client.post("/chat", json={"messages": MESSAGES})
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assert resp.status_code == 504
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@pytest.mark.asyncio
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async def test_chat_unknown_provider_returns_503(ai_client):
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bad_config = {**LMSTUDIO_CONFIG, "provider": "unknown-llm"}
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with patch(_LOAD_CONFIG, return_value=bad_config):
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resp = await ai_client.post("/chat", json={"messages": MESSAGES})
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assert resp.status_code == 503
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# ---------------------------------------------------------------------------
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# Anthropic system message extraction
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# ---------------------------------------------------------------------------
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@pytest.mark.asyncio
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async def test_anthropic_system_message_extracted(ai_client):
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"""System-role messages must not appear in the user_messages list sent to Anthropic."""
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captured_kwargs: dict = {}
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async def _fake_create(**kwargs):
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captured_kwargs.update(kwargs)
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mock_resp = MagicMock()
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mock_resp.content = [MagicMock(text="ok")]
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mock_resp.usage = MagicMock(input_tokens=5, output_tokens=2)
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return mock_resp
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with patch(_LOAD_CONFIG, return_value=ANTHROPIC_CONFIG), patch(
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"anthropic.AsyncAnthropic.messages",
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new_callable=lambda: type(
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"Messages",
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(),
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{"create": staticmethod(AsyncMock(side_effect=_fake_create))},
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),
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):
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resp = await ai_client.post("/chat", json={"messages": SYSTEM_MESSAGES})
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# Whether the call succeeded or not, no system role should reach the messages list
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if "messages" in captured_kwargs:
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roles = [m["role"] for m in captured_kwargs["messages"]]
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assert "system" not in roles
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# ---------------------------------------------------------------------------
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# Parameter forwarding
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# ---------------------------------------------------------------------------
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@pytest.mark.asyncio
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async def test_max_tokens_and_temperature_forwarded(ai_client):
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captured: dict = {}
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async def _capture(messages, max_tokens, temperature):
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captured["max_tokens"] = max_tokens
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captured["temperature"] = temperature
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return ("ok", 1, 1)
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with patch(_LOAD_CONFIG, return_value=LMSTUDIO_CONFIG), patch(_PROVIDER_CHAT, new=_capture):
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resp = await ai_client.post(
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"/chat",
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json={"messages": MESSAGES, "max_tokens": 512, "temperature": 0.7},
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)
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assert resp.status_code == 200
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assert captured["max_tokens"] == 512
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assert captured["temperature"] == pytest.approx(0.7)
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