Enhance regulatory query handling by implementing improved detection for new regulatory questions versus follow-ups. Update parameter extraction to include report type, refining response generation based on user intent. Revise README to reflect these new features and clarify functionality. Update UIHandler to incorporate conversation context in general chat responses for better user experience.

Refactor tool information panel in app.py to improve clarity by removing unnecessary markdown artifacts and enhancing the presentation of available tools.

Enhance app.py to implement a Gradio interface for the RegRadar AI Regulatory Compliance Assistant, featuring a chatbot, example queries, and a tool information panel. Refactor UIHandler to streamline chat processing and improve regulatory query handling. Update web_tools.py to modularize crawling and searching functionalities, enhancing code readability and maintainability.

Enhance app.py by adding warnings filter to ignore DeprecationWarnings, improving user experience. Refactor UIHandler in agents/ui_handler.py to remove unnecessary break condition in results display logic. Update web_tools.py to clarify crawl instructions for regulatory updates, enhancing readability and context.

Refactor app.py to create a dedicated demo function for UI initialization. Update UIHandler to generate a unique user ID per session and pass it to the regulatory query processing. Enhance memory management by ensuring user-specific data is utilized. Modify LLM streaming function to include a system prompt for improved response context.

Refactor app.py to streamline the RegRadar application, consolidating regulatory compliance features into a cohesive UI. Enhance user interaction with improved query processing, tool detection, and memory integration. Update main function to initialize and launch the application effectively.

Update .gitignore to include __pycache__ and enhance app.py with improved regulatory query processing, tool detection, and user interaction features. Refactor streaming chat functionality and add memory search capabilities. Update requirements.txt to include openai-agents and gradio dependencies.

Enhance caching mechanism and regulatory query processing in chat interface. Update cache check and save methods to align with Mem0 best practices. Improve intent detection and result summarization for regulatory updates, ensuring clearer user interactions and responses.

Refactor message processing to support open Q&A style interactions, enhancing user engagement. Update greeting and response handling for improved clarity. Revise UI elements for better user experience, including feature presentation.

Refactor regulatory monitoring workflow into a chat-based interface with caching and improved error handling. Update OpenAI API key usage and adjust regulatory crawling logic. Change Gradio app structure for enhanced user interaction. Update README with SDK version change.

Implement initial project structure and setup