--- title: raggy: A lightweight CLI tool for RAG over your local... description: raggy is a lightweight command-line tool that lets you run Retrieval-Augmented Generation over your own local documents. It combines LangChain, Chroma, and... canonical: https://daily.dev/posts/raggy-a-lightweight-cli-tool-for-rag-over-your-local-documents-jwotafitx twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: raggy: A lightweight CLI tool for RAG over your local documents | daily.dev og:description: raggy is a lightweight command-line tool that lets you run Retrieval-Augmented Generation over your own local documents. It combines LangChain, Chroma, and... og:url: https://daily.dev/posts/raggy-a-lightweight-cli-tool-for-rag-over-your-local-documents-jwotafitx og:image: https://api.daily.dev/og/posts/jWotaFItX.png og:image:alt: raggy: A lightweight CLI tool for RAG over your local documents og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # raggy: A lightweight CLI tool for RAG over your local documents **[Deleted user](https://daily.dev/sources/404)** · [@ghost](https://daily.dev/ghost) · 1 min read · 0 upvotes · 0 comments ## Summary raggy is a lightweight command-line tool that lets you run Retrieval-Augmented Generation over your own local documents. It combines LangChain, Chroma, and Ollama to build a hybrid vector plus BM25 search index and generate embeddings entirely on your machine. Answer generation can run locally through a local LLM or remotely via an API key. It supports most common document formats and automatically handles images and scanned documents through OCR. ## Content  [https://github.com/paulknysh/raggy](https://github.com/paulknysh/raggy) A lightweight CLI tool for Retrieval-Augmented Generation (RAG) over local documents built with LangChain, Chroma, and Ollama. Hybrid database (vector + BM25 index) and embedding generation run fully locally. Answer generation can run either via a local LLM or remotely using an API key. `raggy` supports most common document formats and handles images/scans automatically via OCR. ## Similar posts on daily.dev - [RAG Explained Simply with a Real Project](https://daily.dev/posts/rag-explained-simply-with-a-real-project-pgy15jzg7) · freeCodeCamp · 23 upvotes · 1 comments - [Medium](https://daily.dev/posts/medium-ollye3mqw) · Medium · 1 upvotes · 0 comments --- Tags: [#rag](https://daily.dev/tags/rag), [#vector-search](https://daily.dev/tags/vector-search), [#langchain](https://daily.dev/tags/langchain), [#ollama](https://daily.dev/tags/ollama) [View this post on daily.dev](https://daily.dev/posts/raggy-a-lightweight-cli-tool-for-rag-over-your-local-documents-jwotafitx) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"DiscussionForumPosting","mainEntityOfPage":"https://daily.dev/posts/raggy-a-lightweight-cli-tool-for-rag-over-your-local-documents-jwotafitx","headline":"raggy: A lightweight CLI tool for RAG over your local documents","text":"raggy is a lightweight command-line tool that lets you run Retrieval-Augmented Generation over your own local documents. 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