MCP AI POC

# Development Guide ## Getting Started ### Prerequisites - Python 3.11 or higher - OpenAI API key ### Environment Setup 1. **Clone and navigate to the repository** ```bash git clone <repository-url> cd mcp-ai-poc ``` 2. **Create virtual environment** ```bash python3 -m venv venv source venv/bin/activate # On Windows: venv\Scripts\activate ``` 3. **Install dependencies** ```bash ./scripts/install_deps.sh ``` 4. **Install package in editable mode** ```bash pip install -e . ``` 5. **Set up environment variables** ```bash export OPENAI_API_KEY="your-api-key-here" ``` ## Running the Application ### Interactive Chat Mode ```bash python -m mcp_poc.app ``` ### Using as a Module ```python from mcp_poc.app import generate_completion messages = [{"role": "user", "content": "Hello!"}] response = generate_completion(messages) print(response) ``` ## Testing ### Run All Tests ```bash pytest ``` ### Run with Coverage ```bash pytest --cov=mcp_poc ``` ### Run Specific Test ```bash pytest src/tests/test_app.py::test_generate_completion ``` ## Code Quality ### Project Structure Guidelines - Keep core logic in `src/mcp_poc/` - Place tests in `src/tests/` - Use descriptive function and variable names - Follow PEP 8 style guidelines ### Testing Guidelines - Mock external API calls in tests - Test error conditions (missing API keys, network failures) - Maintain good test coverage - Use descriptive test names ## Common Development Tasks ### Adding New Features 1. Create feature branch 2. Implement functionality in `src/mcp_poc/` 3. Add corresponding tests in `src/tests/` 4. Run tests to ensure no regressions 5. Update documentation if needed ### Debugging - Use environment variable `OPENAI_LOG=debug` for detailed API logs - Check API key configuration if authentication fails - Review OpenAI API documentation for model-specific requirements