RAG & Knowledge
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Self-hosted RAG search across GitHub, Drive, Notion, and local files.
★ 115 starsMIT
View guide →Ask questions of your Obsidian notes with private, local AI RAG.
ObsidianRAG is an open-source ai chat project by Vasallo94 (Vasallo94/ObsidianRAG on GitHub). It has 123 GitHub stars and 18 forks, is released under the MIT license, and was last updated on GitHub on 18 September 2026.
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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Free and open — grab the source, star the repo, and start creating.