RAG и базы знаний
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Self-hosted RAG search across GitHub, Drive, Notion, and local files.
★ 115 звёздMIT
Смотреть руководство →ObsidianRAG — проект с открытым исходным кодом из категории «Чат с ИИ» от Vasallo94 (Vasallo94/ObsidianRAG на GitHub). У него 123 звезды на GitHub и 18 форков, он распространяется по лицензии MIT и последний раз обновлялся на GitHub 18 сентября 2026.
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.
Другие проекты из категории «Чат с ИИ» с наибольшим числом звёзд в каталоге LibreAI — реалистичный список альтернатив, если ObsidianRAG вам не подходит.
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