# Current Focus: Report Generation Module Implementation (Phase 2)

## Latest Update (2025-02-27)

We have successfully implemented Phase 1 of the Report Generation module, which includes document scraping and SQLite storage. The next focus is on Phase 2: Document Prioritization and Chunking, followed by integration with the search execution pipeline.

### Recent Progress

1. **Report Generation Module Phase 1 Implementation**:
   - Created a SQLite database manager with tables for documents and metadata
   - Implemented a document scraper with Jina Reader API integration and fallback mechanisms
   - Developed the basic report generator structure
   - Added URL retention, metadata storage, and content deduplication
   - Created comprehensive test scripts to verify functionality
   - Successfully tested document scraping, storage, and retrieval

2. **Configuration Enhancements**:
   - Implemented module-specific model assignments in the configuration
   - Added support for different LLM providers and endpoints
   - Added configuration for Jina AI's reranker
   - Added support for OpenRouter and Groq as LLM providers
   - Configured the system to use Groq's Llama 3.1 and 3.3 models for testing

3. **LLM Interface Updates**:
   - Enhanced the LLMInterface to support different models for different modules
   - Implemented dynamic model switching based on the module and function
   - Added support for Groq and OpenRouter providers
   - Optimized prompt templates for different LLM models

4. **Search Execution Updates**:
   - Fixed issues with the Serper API integration
   - Updated the search handler interface for better error handling
   - Implemented parallel search execution using thread pools
   - Enhanced the result collector to properly process and deduplicate results

5. **Jina Reranker Integration**:
   - Successfully integrated the Jina AI Reranker API to improve search result relevance
   - Fixed issues with API request and response format compatibility
   - Updated the reranker to handle different response structures
   - Improved error handling for a more robust integration

### Current Tasks

1. **Report Generation Module Implementation (Phase 2)**:
   - Implementing document prioritization based on relevance scores
   - Developing chunking strategies for long documents
   - Creating token budget management system
   - Designing document selection algorithm

2. **Integration with Search Execution**:
   - Connecting the report generation module to the search execution pipeline
   - Implementing automatic processing of search results
   - Creating end-to-end test cases for the integrated pipeline

3. **UI Enhancement**:
   - Adding report generation options to the UI
   - Implementing progress indicators for document scraping and report generation
   - Creating visualization components for search results

### Next Steps

1. **Complete Phase 2 of Report Generation Module**:
   - Implement relevance-based document prioritization
   - Develop section-based and fixed-size chunking strategies
   - Create token budget management system
   - Design and implement document selection algorithm

2. **Begin Phase 3 of Report Generation Module**:
   - Integrate with Groq's Llama 3.3 70B Versatile model for report synthesis
   - Implement map-reduce approach for processing documents
   - Create report templates for different query types
   - Add citation generation and reference management

3. **Comprehensive Testing**:
   - Create end-to-end tests for the complete pipeline
   - Test with various document types and sizes
   - Evaluate performance and optimize as needed

### Technical Notes

- Using Jina Reader API for web scraping with BeautifulSoup as fallback
- Implemented SQLite database for document storage with proper schema
- Using asynchronous processing for improved performance in web scraping
- Managing API keys securely through environment variables and configuration files
- Planning to use Groq's Llama 3.3 70B Versatile model for report synthesis