raggy
A lightweight open-source command-line tool built on LangChain, Chroma, and Ollama. It supports local document retrieval-augmented generation (RAG) question answering, featuring hybrid retrieval combining vector search and BM25, as well as OCR processing for scanned documents. The tool operates entirely locally.
Timeline (last 90 days)
raggy is a lightweight CLI tool built on LangChain, Chroma, and Ollama, focused on implementing retrieval-augmented generation for local documents.
The GitHub project page for raggy is located at github.com/paulknysh/raggy.
raggy adopts a hybrid database design, using both vector retrieval and BM25 keyword retrieval mechanisms simultaneously.
raggy's hybrid database and embedding generation run entirely locally, and document content is not sent to external services.
raggy offers two modes for the answer generation stage: completing the full process through a local LLM (via Ollama), or calling remote models such as GPT and Claude through an API Key.
raggy supports most common document formats and can automatically process images and scanned documents via OCR.
As a lightweight CLI tool, raggy is better suited for quick and convenient local use cases rather than enterprise-grade RAG systems targeting large-scale production environments.
raggy has attracted attention in the Reddit community.
All Facts (7)
raggy is a lightweight CLI tool built on LangChain, Chroma, and Ollama, focused on implementing retrieval-augmented generation for local documents.
50%UnverifiedThe GitHub project page for raggy is located at github.com/paulknysh/raggy.
50%Unverifiedraggy adopts a hybrid database design, using both vector retrieval and BM25 keyword retrieval mechanisms simultaneously.
50%Unverifiedraggy's hybrid database and embedding generation run entirely locally, and document content is not sent to external services.
50%Unverifiedraggy offers two modes for the answer generation stage: completing the full process through a local LLM (via Ollama), or calling remote models such as GPT and Claude through an API Key.
50%Unverifiedraggy supports most common document formats and can automatically process images and scanned documents via OCR.
50%UnverifiedAs a lightweight CLI tool, raggy is better suited for quick and convenient local use cases rather than enterprise-grade RAG systems targeting large-scale production environments.
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