Enhanced Flask App with Vectorstore and Logging

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📅 2025-01-23 — Session: Enhanced Flask App with Vectorstore and Logging

🕒 23:00–23:40
🏷️ Labels: Flask, Vectorstore, Logging, Python, Raptor Pipeline
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The primary goal of this session was to enhance a Flask application by integrating vectorstore management, improving logging, and ensuring robust error handling.

Key Activities

  • Modified the Flask app to use hardcoded file paths, eliminating the need for dynamic PDF uploads.
  • Troubleshot and resolved issues with the OPENAI_API_KEY environment variable in Python scripts.
  • Implemented automatic initialization of the vectorstore on app startup.
  • Enhanced verbose logging in the Flask app to aid in debugging and tracking processes.
  • Debugged vectorstore initialization issues, ensuring backend logic and UI are synchronized.
  • Fixed the OpenAI API key issue and refactored the code to integrate with the Raptor Pipeline.
  • Delegated vectorstore management to the Raptor Pipeline, incorporating embedding, clustering, and summarization capabilities.
  • Planned refactoring of app logic to make vectorstore optional, allowing fallback processing when not initialized.

Achievements

  • Successfully integrated vectorstore management into the Flask app.
  • Improved logging and debugging capabilities.
  • Resolved environment variable and API key issues.

Pending Tasks

  • Complete the refactoring of app logic for vectorstore independence, ensuring fallback mechanisms are fully operational.

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