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# LLM Provider Tests This directory contains tests for the various LLM provider implementations in the MCP Agent library. The tests validate the core functionality of each provider's `AugmentedLLM` implementation. ## Test Coverage The tests cover the following functionality: - Basic text generation - Structured output generation - Message history handling - Tool usage - Error handling - Type conversion between provider-specific types and MCP types - Request parameter handling - Model selection ## Running the Tests ### Prerequisites Make sure you have installed all the required dependencies: ```bash # Install required packages uv sync --all-extras ``` ### Running All Tests To run all the LLM provider tests: ```bash # From the project root pytest tests/workflows/llm/ # Or with more detailed output pytest tests/workflows/llm/ -v ``` ### Running Specific Provider Tests To run tests for a specific provider: ```bash # OpenAI tests pytest tests/workflows/llm/test_augmented_llm_openai.py -v # Anthropic tests pytest tests/workflows/llm/test_augmented_llm_anthropic.py -v ``` ### Running a Specific Test To run a specific test case: ```bash pytest tests/workflows/llm/test_augmented_llm_openai.py::TestOpenAIAugmentedLLM::test_basic_text_generation -v ``` ### Running with Coverage To run tests with coverage reports: ```bash # Generate coverage for all LLM provider tests pytest tests/workflows/llm/ --cov=src/mcp_agent/workflows/llm # Generate coverage for a specific provider pytest --cov=src/mcp_agent/workflows/llm --cov-report=term tests/workflows/llm/test_augmented_llm_openai.py # Generate an HTML coverage report pytest --cov=src/mcp_agent/workflows/llm --cov-report=html tests/workflows/llm/test_augmented_llm_openai.py ``` ## Adding New Provider Tests When adding tests for a new provider: 1. Create a new test file following the naming convention: `test_augmented_llm_<provider>.py` 2. Use the existing tests as a template 3. Implement provider-specific test fixtures and helper methods 4. Make sure to cover all core functionality ## Notes on Mocking The tests use extensive mocking to avoid making actual API calls to LLM providers. The key components that are mocked: - Context - Aggregator (for tool calls) - Executor - Response objects This ensures tests can run quickly and without requiring API keys or network access.