- Implemented a new SPA page for LLM Bridge and MCP Server settings in `llm-config.js`.
- Added functionality for managing LLM and MCP configurations, including toggling, saving settings, and testing connections.
- Created HTTP endpoints in `llm_utils.py` for handling LLM chat, status checks, and MCP server configuration.
- Integrated model fetching from LaRuche and Ollama backends.
- Enhanced error handling and logging for better debugging and user feedback.
- Implemented methods for fetching AI stats, training history, and recent experiences.
- Added functionality to set operation mode (MANUAL, AUTO, AI) with appropriate handling.
- Included helper methods for querying the database and sending JSON responses.
- Integrated model metadata extraction for visualization purposes.
