📅 2025-02-07 — Session: Enhanced Chunk Processing and Error Handling
🕒 00:00–01:50
🏷️ Labels: Chunk Processing, Error Handling, JSON, Python, Data Storage
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The main objective of this session was to enhance the chunk processing systems and address JSON parsing errors in various components.
Key Activities
- ChunkHandler & ChunkEnricher Patterns: Explored and documented AI processing patterns using chunk-based architectures.
- Design Plan for Chunk Processing System: Outlined a design plan to enhance ChunkManager and ChunkProcessor for better adaptability and scalability.
- Enhanced ChunkManager: Introduced a query language for dynamic filtering of metadata.
- Flow for Academic Chunks: Developed a workflow for filtering and summarizing academic chunks using Python.
- JSON Parsing Error Fixes: Addressed JSON parsing errors in OpenAI API responses and
summarize_research()
function. - Data Storage Enhancements: Upgraded enrichment data storage with multi-collection support and implemented
get_collection_data()
in ChunkManager.
Achievements
- Successfully documented and implemented enhancements in chunk processing and error handling.
- Improved data storage solutions with multi-collection support.
- Fixed JSON parsing issues, enhancing the robustness of the system.
Pending Tasks
- Further optimize the summarization workflow for academic chunks.
- Continue to refine JSON schema for academic draft summarizer.