📅 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.