Open-Source LocalRAG Lets Teams Query Documents Without Cloud AI APIs

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A developer has released LocalRAG, an open-source document question-answering system designed to run entirely within a private or air-gapped environment. The stack lets users upload PDF, DOCX, TXT, or Markdown files, which are chunked, embedded with a local bge-m3 model, and stored in Qdrant for retrieval. Answers are generated by a local LLM through Ollama and returned with source references, with no cloud AI calls at runtime. The project is aimed at sectors like legal, healthcare, and finance that cannot send confidential data to external services. Initial setup still requires network access to pull Docker images and models, and the developer noted that the large unpacked image size can be a problem on slow connections.

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