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RAG Chat

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Description

This plugin has not been manually reviewed by Obsidian staff. Chat with your vault using local vector search (RAG) and any AI provider — OpenAI, Claude, Gemini, Mistral, Groq, Ollama, and more.

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Latest Version

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Changelog

See all version on GitHub

README file from

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RAG Chat

Chat with your Obsidian vault using any AI provider. Ask questions in natural language and get answers grounded in your actual notes, with clickable source citations.

No Python backend, no external server, no setup required. Everything runs inside Obsidian.

How it works

  1. When the plugin loads it indexes all your markdown notes using a built-in BM25 full-text search engine — no embeddings, no external model, no network calls for indexing.
  2. When you ask a question, the top matching note chunks are retrieved and sent as context to your chosen LLM.
  3. The answer is displayed in a chat panel alongside clickable source citations that open the referenced note.
  4. The index stays up to date automatically as you create, edit, rename or delete notes.

Supported AI providers

Provider Notes
OpenAI GPT-4o, GPT-4, GPT-3.5, etc.
Anthropic Claude 3.5 Sonnet, Claude 3, etc.
Google Gemini 2.0 Flash, Gemini 1.5, etc.
Mistral Mistral Large, Mistral Small, etc.
Groq Fast inference for Llama, Mixtral, etc.
xAI Grok
DeepSeek DeepSeek Chat, DeepSeek Coder
Cohere Command R+
Together AI Open-source models
Perplexity Sonar models
Ollama Local — llama3, mistral, phi3, etc.
llama.cpp Local — any GGUF model
LM Studio Local — any model
Jan Local — any model
Custom Any OpenAI-compatible API

Installation

Install via Obsidian's Community Plugins browser:

  1. Open Settings → Community plugins
  2. Disable Restricted mode if enabled
  3. Click Browse and search for RAG Chat
  4. Click Install, then Enable

Setup

  1. Open Settings → RAG Chat
  2. Select your provider from the dropdown
  3. Enter your API key (not required for local providers)
  4. Check the data consent toggle
  5. The plugin will automatically index your vault on first load

Usage

  • Click the chat icon (💬) in the left ribbon to open the chat panel
  • Type a question and press Enter (or Shift+Enter for a new line)
  • Click any source citation to jump directly to that note
  • Use Settings → Rebuild index if you ever need to force a full re-index

Privacy

  • Indexing is fully local. Note content is tokenised and stored on-device only; nothing is sent to any server during indexing.
  • Your notes are sent to your chosen LLM provider when you ask a question (only the top matching chunks, not your entire vault). If this concerns you, use a local provider such as Ollama.
  • API keys are stored in Obsidian's plugin data folder on your device.

Local LLM (no API key needed)

Select Local LLM as the provider, choose your server type (Ollama, llama.cpp, LM Studio, Jan, or other OpenAI-compatible), enter the server URL and model name, and you're done. No API key required.

Quick start with Ollama:

ollama serve
ollama pull llama3

Then set provider → Local LLM, type → Ollama, URL → http://localhost:11434, model → llama3.

Troubleshooting

No results / poor answers Go to Settings → RAG Chat and click Rebuild index. This re-indexes all notes from scratch.

API errors Check that your API key is correct and the selected model name matches what your provider offers.

Local LLM not reachable Use the Test button in settings to verify the server URL. Make sure your local server is running before sending a message.

License

MIT — see LICENSE

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