* feat: Implement model registry and capabilities for multi-provider support
- Added ModelRegistry to manage available models and their capabilities.
- Introduced ModelProvider enum for different LLM providers.
- Created ModelCapabilities dataclass to define model features.
- Implemented methods to load models based on API keys and settings.
- Added utility functions for model management in model_utils.py.
- Updated settings.py to include provider-specific API keys.
- Refactored LLM classes (Anthropic, OpenAI, Google, etc.) to utilize new model registry.
- Enhanced utility functions to handle token limits and model validation.
- Improved code structure and logging for better maintainability.
* feat: Add model selection feature with API integration and UI component
* feat: Add model selection and default model functionality in agent management
* test: Update assertions and formatting in stream processing tests
* refactor(llm): Standardize model identifier to model_id
* fix tests
---------
Co-authored-by: Alex <a@tushynski.me>
- Added MCPOAuthManager to handle OAuth authorization.
- Updated MCPServerSave resource to manage OAuth status and callback.
- Introduced new endpoints for OAuth status and callback handling.
- Enhanced user interface to support OAuth authentication type.
- Implemented polling mechanism for OAuth status in MCPServerModal.
- Updated frontend services and endpoints to accommodate new OAuth features.
- Improved error handling and user feedback for OAuth processes.
- Implemented encryption utility for securely storing sensitive credentials.
- Added MCPServerModal component for managing MCP server configurations.
- Updated AddToolModal to include MCP server management.
- Enhanced localization with new strings for MCP server features.
- Introduced SVG icons for MCP tools in the frontend.
- Created a new settings section for MCP server configurations in the application.