RAG・知識ベース
wenlan
Agent-fed knowledge base that distills learnings into cited wiki pages.
★ 79 スターApache-2.0
ガイドを見る →QAnythingは、netease-youdaoが公開しているオープンソースのRAG・知識ベースプロジェクトです（GitHub: netease-youdao/QAnything）。GitHubスターは14,197、フォークは1,354で、AGPL-3.0ライセンスの下で公開されています。GitHubでの最終更新は2026年9月23日です。
Local knowledge-base Q&A over PDFs, Office files, images and web pages - offline and CPU-friendly.
Install Docker and Docker Compose and make sure you have at least 20GB of RAM; no GPU is required for the default setup.
Pull the QAnything repo, which contains the per-platform Docker Compose files for one-click startup.
Run the Docker Compose file for your operating system and wait for the 'qanything backend service is ready' log line (about 30 seconds).
Open the web UI at http://localhost:8777/qanything/, set your OpenAI-compatible API base and key (or a local Ollama model) in the front-end settings, upload documents and start asking.
Embedding retrieval followed by reranking with BCEmbedding models keeps answer quality stable as data volume grows, instead of degrading like single-stage retrieval.
Supports PDF, Word, PPT, Excel, Markdown, email, TXT, images (with OCR), CSV and web links, with strong parsing of tables, columns and cross-page layouts.
Designed for data security: install and use it with the network unplugged, running by default in a pure CPU environment on Windows, Mac or Linux.
Ask in Chinese or English regardless of the language of the source files.
Quick-start mode (upload and ask, or fileless chat), retrieval-only mode, FAQ matching, custom Bots and hybrid BM25-plus-embedding search.
PDF parsing, OCR, embedding and rerank services are independent and replaceable, and can be called separately over HTTP.
Pull the QAnything code with its Docker Compose files.
git clone https://github.com/netease-youdao/QAnything.git
cd QAnythingLaunch the stack with the compose file for your platform (Linux shown).
docker compose -f docker-compose-linux.yaml upOnce the log says the backend service is ready, open the front end in your browser.
# Open http://localhost:8777/qanything/ - see README for detailsQAnything is developed by NetEase Youdao's open-source team and community contributors.
The code is AGPL-3.0 licensed; note the README says commercial use should also follow the license of the underlying QwenLM models if you use them.
Version 2.0 gets its LLM through an OpenAI-compatible interface: that can be a paid hosted API with your key, or a free local model served by Ollama.
Those are broader LLM app platforms; QAnything focuses specifically on local knowledge-base Q&A with strong document parsing and two-stage retrieval, deployable fully offline on CPU.
Clone the repo, run the Docker Compose file for your OS, open http://localhost:8777/qanything/, set your model endpoint, and upload your first files.
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LibreAIカタログに掲載されたRAG・知識ベースプロジェクトの中で最もスターの多いもの — QAnythingが合わなかった場合に検討したい、現実的な候補リストです。
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