QAnything is a local knowledge-base question-answering system designed to let users ask questions over many kinds of files and databases. It supports offline installation, making it useful for organizations that need private document analysis without sending data to external services. Users can upload local files and receive fast, reliable answers based on the indexed content. The system supports formats such as PDF, Word, PowerPoint, Excel, Markdown, email, text, images, CSV, and web links. Its retrieval process uses a two-stage vector and reranking approach to maintain answer quality as the knowledge base grows. It is built to be hardware-friendly, easy to deploy with Docker, and usable across Windows, macOS, and Linux.

Features

  • Local knowledge-base Q&A
  • Offline deployment support
  • Multi-format document parsing
  • Cross-language Chinese and English Q&A
  • Two-stage retrieval and reranking
  • Docker-based one-click startup

Project Samples

QAnything Screenshot 1

Project Activity

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Categories

Artificial Intelligence

License

Affero GNU Public License

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QAnything Web Site

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Additional Project Details

Operating Systems

Linux, Mac, Windows

Programming Language

Python

Related Categories

Python Artificial Intelligence Software

Registered

2026-05-28
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