- Added DEXSCREENER_CONNECTOR to _CONNECTOR_TYPE_TO_SEARCHABLE in chat_deepagent.py
- This fixes LLM's inability to search DexScreener data despite it being indexed
- Root cause: connector was enabled in DB but missing from mapping, causing it to be filtered out
- Verified: LLM now successfully retrieves WETH price (~$2,442) with DexScreener citations
Related files:
- chat_deepagent.py: Added connector mapping
- knowledge_base.py: Added debug logging for DexScreener search
- connector_service.py: Fixed metadata field names (base_symbol, quote_symbol, dex)
- 85_add_dexscreener_connector.py: Migration for connector type
- Added functionality to dynamically discover available connectors and document types for the knowledge base tool, enhancing its flexibility and usability.
- Introduced new mapping functions and updated existing search methods to accommodate Composio connectors, improving integration with external services.
- Enhanced error handling and logging for connector discovery processes, ensuring better feedback during failures.
- Removed the write_todos tool as it is now included by default through TodoListMiddleware in the deep agent.
- Updated the system prompt and documentation to reflect the integration of TodoListMiddleware, clarifying its capabilities for managing planning and todo lists.
- Enhanced the chat handling logic to extract todos directly from the deep agent's command output, ensuring seamless user experience.
- Refactored UI components to align with the new data structure and improve rendering of todo items, including updates to the Plan and TodoItem components.
- Cleaned up code for better maintainability and readability, following recent refactoring efforts.
- Enhanced the new chat agent module to allow for configurable tools, enabling users to customize their experience with various functionalities.
- Removed outdated tools including display image, knowledge base search, link preview, podcast generation, and web scraping, streamlining the codebase.
- Updated the system prompt and agent factory to reflect these changes, ensuring a more cohesive and efficient architecture.
