supabot
Vectorized Search Query

Your AI-Powered
Supabase
Assistant

Get instant answers from Supabase documentation using advanced AI. Search, analyze, and understand complex database concepts with intelligent routing across multiple AI providers.

Smart Query Routing

Automatically routes queries to the best AI model - OpenAI for SQL, Claude for summaries, Cohere for semantic search.

Performance Analytics

Track accuracy, latency, cost, and reliability metrics across all AI providers with detailed logging.

Vector Search

Powered by pgvector embeddings for semantic search across the entire Supabase documentation.

Technical Architecture

From raw documentation to intelligent AI responses

GitHub Repository Of Pipeline

Data Processing Pipeline

HTML Scraping

Scrape Supabase documentation

Text Cleaning

Extract and clean content

Vector Embeddings

Generate 1536-dimensional vectors

Hybrid Search

Semantic + keyword search

AI Response

Generate contextual answers

Supabase + pgvector

PostgreSQL with pgvector extension storing 1536-dimensional embeddings for semantic search

Hybrid Search Engine

Combines semantic vector search with traditional keyword matching for optimal results

Multi-Provider AI

OpenAI for SQL queries, Claude for summaries, Cohere for embeddings with intelligent routing

MCP Router

Model Context Protocol server orchestrating the entire pipeline from query to response