RAG & Wissen
OpenDocuments
Self-hosted RAG search across GitHub, Drive, Notion, and local files.
★ 115 SterneMIT
Anleitung ansehen →ObsidianRAG ist ein Open-Source-Projekt aus der Kategorie KI-Chat von Vasallo94 (Vasallo94/ObsidianRAG auf GitHub). Es hat 123 Sterne auf GitHub und 18 Forks, wird unter der Lizenz MIT veröffentlicht und wurde zuletzt am 18. September 2026 auf GitHub aktualisiert.
Ask questions of your Obsidian notes with private, local AI RAG.
Get it from PyPI or pull the Docker image.
Configure the path to your Obsidian notes.
Use Ollama, LM Studio, or any compatible server.
Query from the plugin or the API.
Ask questions without leaving your notes.
Ollama, LM Studio, or OpenAI-compatible servers.
Your vault never leaves your machine.
Semantic search over your notes.
Two easy ways to run it.
Modern RAG orchestration.
Get it from PyPI.
pip install obsidianragPull and run the container instead.
docker run -p 8000:8000 obsidianragPoint it at your vault and model per the README.
# see README for the config file formatIt is an open-source project at Vasallo94/ObsidianRAG with 18 forks.
Yes. It is MIT licensed.
No. Models and vectors run locally by design.
Ollama, LM Studio, or any OpenAI-compatible server.
Via the Obsidian plugin, Docker, or the PyPI package.
Self-hosted RAG search across GitHub, Drive, Notion, and local files.
Transparent Python RAG reference with FAISS + BM25 hybrid retrieval.
Bring local LLMs into your Obsidian vault.
Turn a local CLI agent into in-vault Obsidian AI chat.
A modern, local-first AI roleplay platform you host yourself.
Private desktop AI hub: chat, code, images, music, docs — no cloud, no account.
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Kostenlos und offen — hol dir den Quellcode, gib dem Repository einen Stern und leg los.