Overview
This workflow automates the process of enabling AI-powered chat interactions with documents stored in Supabase. By integrating file retrieval, document parsing, text splitting, and OpenAI embeddings, it streamlines the preparation of files for conversational AI agents.
Key Features
- Retrieves all files from Supabase storage
- Loads and parses documents (including PDFs)
- Splits text into manageable chunks for processing
- Generates semantic embeddings using OpenAI
- Stores processed data back in Supabase for efficient querying
- Supports batch processing and conditional logic for robust automation
Benefits
- Saves significant manual effort in preparing documents for AI chat
- Ensures scalable, repeatable processing of large document sets
- Enhances user experience by enabling intelligent, context-aware chat with stored files
- Reduces time-to-insight by automating data extraction and embedding
Use Cases
- Customer support chatbots referencing internal documents
- Knowledge base search and Q&A systems
- Automated document analysis for sales or HR teams
- Any scenario requiring conversational AI access to stored files
Integrations
- Supabase (file storage and database)
- OpenAI (embeddings)
- n8n LangChain nodes (document loading, text splitting)
- HTTP requests for external data handling
