RAG & Wissen
knowledge-agent-template
Starter template for AI agents that stay synced with your knowledge base.
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Anleitung ansehen →Local_Pdf_Chat_RAG ist ein Open-Source-Projekt aus der Kategorie RAG & Wissen von weiwill88 (weiwill88/Local_Pdf_Chat_RAG auf GitHub). Es hat 957 Sterne auf GitHub und 180 Forks, wird unter der Lizenz MIT veröffentlicht und wurde zuletzt am 31. August 2026 auf GitHub aktualisiert.
Transparent Python RAG reference with FAISS + BM25 hybrid retrieval.
The README documents setup; start with the install section.
Decide what you want Local_Pdf_Chat_RAG to do first — transparent Python RAG reference with FAISS + BM25 hybrid retrieval, r.
Pull the latest changes to stay current with fixes.
Change the config to match your workflow, then run it daily.
Working bm25 support built in.
Working chinese nlp support built in.
Working deepseek support built in.
Working document qa support built in.
Readable code that is easy to modify.
Use it freely, even commercially.
Download the source and move into the project folder.
git clone https://github.com/weiwill88/Local_Pdf_Chat_RAG.git
cd local-pdf-chat-ragInstall the Python dependencies from the project.
pip install -r requirements.txtLaunch with the project entry point — check the README for the exact command.
python main.py # see README for the exact entry pointAlso on this shelf: nano-graphrag — a small, hackable GraphRAG implementation in about 1,100 lines — no Microsoft GraphRAG bulk. Readers working through the RAG & Knowledge shelf also stop at libratory, In TypeScript — built for your free book and audiobook laboratory. turn the... Also on this shelf: quivr — open-source engine turning continuous content streams into search, monitoring and alerts.
Yes. It is MIT licensed, so you can use it freely, including commercially, with attribution.
No. It is a self-run project — clone it and run it on your own machine. Some features may optionally call external APIs; check the README.
Yes, that is the point. The code is public, so you can run, modify, and host it yourself.
It is released under MIT. Read the LICENSE file in the repo for the exact terms.
Start with the README, then the issue tracker on the GitHub repo at weiwill88/Local_Pdf_Chat_RAG, where maintainers and users answer questions.
Starter template for AI agents that stay synced with your knowledge base.
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