Cursor Rules for the llm/ollama Module

# Cursor Rules for the llm/ollama Module

## 0. Preamble
These rules are specific to the `llm/ollama` module and supplement `general.cursorrules`. Always adhere to `general.cursorrules` unless explicitly overridden here for a specific reason pertinent to this module.

## 1. Module Purpose & Context
-   **Core Functionality**: This module integrates with Ollama local Large Language Models, providing model management and execution.
-   **Key Technologies/Tools**: Python, Ollama API, model management, configuration management, output processing.
-   Refer to the module's main `README.md` for an overview.

## 2. Key Files & Structure in `llm/ollama` Module
When working within this module, pay close attention to:
-   `README.md`: High-level overview, setup, and usage of the Ollama Integration module.
-   `API_SPECIFICATION.md`: Details for programmatic interfaces (functions, classes) provided by this module.
-   `CHANGELOG.md`: All notable changes to this module must be logged here.
-   `SECURITY.md`: Specific security considerations for Ollama integration and model interactions.
-   `pyproject.toml`: Python dependencies (managed centrally via uv).
-   `docs/`: In-depth documentation, technical overviews, and tutorials specific to Ollama Integration.
-   `src/codomyrmex/llm/ollama/`: Core logic of the module.
-   `tests/`: Unit and integration tests for this module.
-   `.gitignore`: Module-specific ignored files.
-   `ollama_manager.py`: Core Ollama API interaction and model management.
-   `model_runner.py`: Model execution and management functionality.
-   `config_manager.py`: Configuration management for Ollama integration.
-   `output_manager.py`: Model output processing and handling.

## 3. Coding Standards & Practices for `llm/ollama`
-   **Consistency**: Adhere to existing coding styles, naming conventions, and architectural patterns found within the `llm/ollama` module.
-   **Language Specifics**: Primarily Python. Follow PEP 8. Use type hinting extensively for model configurations and responses.
-   **Model Management**: Implement robust model lifecycle management and resource handling.
-   **Error Handling**: Provide comprehensive error handling for Ollama API failures and model issues.
-   **Configuration**: Support flexible configuration for different Ollama setups and models.

## 4. Testing in `llm/ollama`
-   New features (e.g., new model support, output processing) or bug fixes MUST be accompanied by relevant tests in `tests/unit/` and/or `tests/integration/`.
-   Tests should cover Ollama API interactions, model execution, configuration management, and error scenarios.
-   Use real Ollama API with environment-gated tests for deterministic behavior (Zero-Mock policy).
-   Run existing tests to ensure no regressions. Refer to `src/codomyrmex/tests/unit/test_ollama_integration.py`.

## 5. Documentation for `llm/ollama`
-   Keep this module's `README.md`, `API_SPECIFICATION.md`, `docs/` directory, and other relevant documentation files meticulously up-to-date.
-   Document Ollama configuration options, model management, and integration patterns clearly.
-   Include examples of model execution and output handling.

## 6. Specific Considerations for `llm/ollama`
-   **Ollama Compatibility**: Ensure compatibility with different Ollama versions and model formats.
-   **Resource Management**: Implement proper resource management for model loading and execution.
-   **Output Processing**: Provide flexible output processing and formatting capabilities.
-   **Error Recovery**: Implement robust error recovery for model failures and API issues.

## 7. Final Check for `llm/ollama`
-   Before finalizing changes, ensure all module-specific documentation is updated.
-   Verify that all tests for this module pass.
-   Confirm that Ollama integration works correctly with actual Ollama services.
-   Test integration with related modules like `language_models` and `ai_code_editing`.