RAGify
Production-grade hybrid RAG backend built with FastAPI, ChromaDB Cloud, and Postgres (Neon) full-text search. Features structure-aware chunking, cross-encoder re-ranking via RRF, in-process conversation memory with rolling summaries, and a dual-mode runtime (zero-cost local DEV vs. Gemini-powered PROD).
The rewritten query drives retrieval; the user's original wording goes into the final prompt. /ask/stream follows the same flow and streams the answer as it is generated.
⚡ How to use RAGify
Indexed from GitHub. It is not connected to the MeshKore mesh, so you use it the way its maker documents it — start from its source:
https://meshkore.com/agent/sahinda-ragifyCapabilities
Do you own RAGify?
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