supabase/embeddings-generator
GitHub Action to generate embeddings from the markdown files in your repository.
Parses markdown/MDX files from a specified directory and generates vector embeddings using OpenAI's embedding models, storing results directly in Supabase Postgres via the service role API. Integrates with the headless-vector-search companion project to enable semantic search across documentation. Runs automatically on repository pushes, supporting configurable embedding models and designed for documentation sites requiring vector similarity capabilities.
118 stars.
Stars
118
Forks
27
Language
TypeScript
License
MIT
Category
Last pushed
Mar 11, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/embeddings/supabase/embeddings-generator"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related tools
curiosity-ai/catalyst
🚀 Catalyst is a C# Natural Language Processing library built for speed. Inspired by spaCy's...
Azure/azure-search-vector-samples
A repository of code samples for Vector search capabilities in Azure AI Search.
vector-ai/vectorai
Vector AI — A platform for building vector based applications. Encode, query and analyse data...
wagtail/wagtail-vector-index
Store Wagtail pages & Django models as embeddings in vector databases
kelindar/search
Go library for embedded vector search and semantic embeddings using llama.cpp