📅 2025-02-01 — Session: Resolved Supabase ‘created_at’ Column Error and Enhanced Upload Logic
🕒 17:00–17:40
🏷️ Labels: Supabase, Python, Error Handling, Embeddings, Vectorstore
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The session aimed to resolve the ‘created_at’ column error in the Supabase ‘chunks’ table and enhance the error handling in file upload logic.
Key Activities
- Supabase Error Resolution: Followed a step-by-step guide to troubleshoot and fix the missing ‘created_at’ column error in the Supabase ‘chunks’ table. This involved checking the table structure, inspecting payloads, clearing caches, and debugging code.
- Enhanced Error Handling: Implemented a Python function to improve file upload logic to Supabase, focusing on graceful handling of warnings and critical errors.
- Embeddings and Metadata Management: Explored strategies for using embeddings in data retrieval and model training, focusing on metadata for context reconstruction.
- Vectorstore Management: Developed workflows for managing vectorstores in RAG workflows using FAISS and OpenAI tools.
Achievements
- Successfully resolved the ‘created_at’ column error in Supabase.
- Improved the Python file upload logic for better error handling.
- Gained insights into the use of embeddings and metadata in semantic search and model training.
- Established a workflow for managing vectorstores in RAG workflows.
Pending Tasks
- Further exploration of fine-tuning models with original text chunks versus embeddings.
- Optimization of vectorstore management processes for efficiency.