BarnacleLabs/RAGmatic
A pragmatic approach to continuously vectorize your PostgreSQL tables with the flexibility of your own embedding pipelines.
RAGmatic helps developers keep their PostgreSQL data continuously updated with vector embeddings, which are crucial for advanced search and AI applications like chatbots. It automatically detects changes in your database tables and processes them through custom embedding pipelines. The output is a highly performant vector index within PostgreSQL, enabling developers to build sophisticated RAG (Retrieval Augmented Generation) systems directly on their existing data.
No commits in the last 6 months. Available on npm.
Use this if you are a developer building AI-powered features and need to maintain up-to-date vector embeddings for your PostgreSQL data without adding another dedicated vector database service.
Not ideal if you prefer a fully managed, out-of-the-box solution with pre-built embedding models, or if your data is not stored in PostgreSQL.
Stars
27
Forks
2
Language
TypeScript
License
MIT
Category
Last pushed
Jul 29, 2025
Commits (30d)
0
Dependencies
4
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