Update session log with progressive report generation planning
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@ -791,7 +791,7 @@ Focused on resolving issues with the report generation template system and ensur
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## Session: 2025-03-12
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### Overview
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Implemented a dedicated report templates module to standardize report generation across different query types and detail levels.
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Implemented a dedicated report templates module to standardize report generation across different query types and detail levels, and planned progressive report generation for comprehensive reports.
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### Key Activities
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1. **Created Report Templates Module**:
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@ -812,8 +812,16 @@ Implemented a dedicated report templates module to standardize report generation
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- Implemented `test_brief_report.py` to test brief report generation with a simple query
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- Verified that all templates can be correctly retrieved and used
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4. **Updated Memory Bank**:
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4. **Planned Progressive Report Generation**:
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- Analyzed the current map-reduce approach for handling large document collections
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- Identified limitations with the current approach for very large document sets
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- Designed a progressive report generation approach for comprehensive detail level
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- Created a detailed implementation plan with four phases
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- Developed a hybrid strategy that uses map-reduce for brief/standard/detailed levels and progressive generation for comprehensive level
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5. **Updated Memory Bank**:
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- Added report templates information to code_structure.md
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- Updated current_focus.md with implementation plan for progressive report generation
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- Updated session_log.md with details about the implementation
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- Ensured all new files are properly documented
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@ -822,14 +830,21 @@ Implemented a dedicated report templates module to standardize report generation
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- Different query types require specialized report structures
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- Validation ensures all required sections are present in templates
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- Enums provide type safety and prevent errors from string comparisons
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- Progressive report generation could provide better results for very large document collections
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- A hybrid approach leverages the strengths of both map-reduce and progressive methods
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### Challenges
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- Designing templates that are flexible enough for various content types
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- Balancing between standardization and customization for different query types
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- Ensuring proper integration with the existing report synthesis process
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- Managing state and tracking progress in progressive report generation
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- Preventing entrenchment of initial report structure in progressive approach
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- Optimizing token usage when sending entire reports for refinement
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### Next Steps
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1. Integrate the template system with the UI to allow users to select detail levels
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2. Add more specialized templates for specific research domains
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3. Implement template customization options for users
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4. Create a visual preview of templates in the UI
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1. Implement the core functionality for progressive report generation
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2. Add model flexibility to support different LLMs beyond Gemini
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3. Integrate the progressive approach with the UI
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4. Conduct comprehensive testing and optimization
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5. Add specialized templates for specific research domains
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6. Implement template customization options for users
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