If you've ever built a RAG (Retrieval-Augmented Generation) system, you know the pain: every new project means rewriting the same boilerplate — vector store setup, embeddings, chunking, LLM wiring. I got tired of it, so I packaged it up.

pyragcore is a modular RAG library built on FAISS and Ollama. The idea is simple: give you a solid foundation so you can focus on your actual use case instead of reinventing the plumbing every time.

What I'm most proud of is that it runs entirely locally — no external APIs, no data leaving your machine. Just Ollama for the LLM and SentenceTransformers for embeddings.

What's inside

FAISS vector store with persistence, deduplication, and metadata filtering

Semantic search with MMR support

Local LLM inference via Ollama

Modular installs — grab only what you need

Abstract base classes so you can extend it your way

How to install it:

pip install pyragcore [ all ]

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from pyragcore import BasePipeline

class MyPipeline (…