3ab8fb51fe
Multi-stage Chain-of-Thought reasoning service with: - FastAPI service using lilith-ml-service-base - Pipeline orchestration via lilith-pipeline-framework - LLM client using lilith-ollama-provider - TypeScript client package @lilith/cot-client - Service-addresses integration for port resolution (8110) Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
40 lines
1.2 KiB
Python
40 lines
1.2 KiB
Python
"""Pytest configuration and fixtures for cot-reasoning tests."""
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import sys
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from pathlib import Path
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from unittest.mock import AsyncMock, MagicMock
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import pytest
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# Add service src to path for imports
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service_src = Path(__file__).parent.parent / "src"
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sys.path.insert(0, str(service_src))
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@pytest.fixture
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def mock_config():
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"""Mock configuration for tests."""
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from service.src.config import AppConfig, ServiceConfig, LLMConfig, ReasoningConfig
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return AppConfig(
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service=ServiceConfig(name="cot-reasoning-test", port=8110, host="127.0.0.1"),
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llm=LLMConfig(backend="ollama", host="http://localhost:11434", model="test-model"),
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reasoning=ReasoningConfig(default_stages=["analyze"]),
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)
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@pytest.fixture
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def mock_llm_response():
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"""Standard mock LLM response."""
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return '{"confidence": 0.9, "result": "test", "understanding": "test input"}'
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@pytest.fixture
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def mock_ollama_provider():
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"""Mock OllamaAsyncProvider."""
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mock = AsyncMock()
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mock.chat.return_value = MagicMock(
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message=MagicMock(content='{"confidence": 0.9, "result": "test"}')
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)
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mock.health_check.return_value = MagicMock(status="ok")
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return mock
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