VaultChat

A local-first AI chat for Obsidian that can actually edit your vault.

Point it at Ollama, LM Studio, or any OpenAI-compatible server and the model can read your notes, propose edits as a reviewable diff, create new notes, and delete files behind a double confirmation. Nothing leaves your machine unless you choose a hosted provider.

Plenty of Obsidian plugins talk to local models, and a couple of the largest can edit your vault too. Three things are different here:

• Local is the default, not a provider you go and configure. A fresh install points at 127.0.0.1 and never asks for a key.
• Every write stays reviewable. There is no "accept all future edits" switch to flip, so a proposal can never apply itself.
• An ambiguous edit is refused, not guessed. If the text the model wants to replace appears more than once, nothing is written and it is asked for more context.

Hosted providers are supported too and are entirely optional: Anthropic (Claude), OpenAI, Google Gemini, and OpenRouter.

Local needs no API key. Hosted providers each need their own standard key. Claude Code OAuth tokens (sk-ant-oat01-...) do not work, and using them in a third-party tool violates Anthropic's terms.

Features

• Runs fully local - Ollama, LM Studio, llama.cpp, vLLM, LocalAI, Jan, or anything else speaking the OpenAI API. No key, no cost, no data leaving your machine
• Multi-provider - switch between local models, Anthropic, OpenAI, Gemini, and OpenRouter from a single dropdown
• File reading - attach any vault file to the conversation with the + button; the AI sees the full contents
• File editing - the AI proposes edits in a diff format; review each one with Preview/Apply, or turn on auto-apply (with Confirm/Revert) from the chat footer or settings
• Path safety - edit and delete blocks that point outside the vault are refused
• Ambiguous edits refused - if the text to replace appears more than once, nothing is written
• No executable code from the model - Obsidian runs code-block processors registered by other plugins, so a dataviewjs fence would execute JavaScript with vault access. Fences that known executors claim are rewritten before rendering; the code stays readable, it just cannot run
• API keys in Obsidian secret storage - moved out of the plugin's data.json, with existing keys migrated automatically
• File creation - ask the AI to create new notes in any folder
• File deletion - the AI can propose file deletions with a double-confirmation safety prompt
• Vault awareness - the AI sees your full file tree so it uses correct paths
• Chat history - persistent sessions stored per-vault, grouped by date, searchable, and resumable
• Stop button - cancel any streaming response mid-generation
• Include current note - one-click toggle to send your active note as context
• Streaming - real-time token streaming from all providers
• Dynamic model lists - local servers report their loaded models; OpenRouter fetches all available models. Refresh from the chat header or from settings

Providers

Installation

From Obsidian (recommended)

1. Open Settings > Community Plugins
2. Click Browse and search for VaultChat
3. Click Install, then Enable

Build from source

If you prefer to install manually or want to contribute:

git clone https://github.com/kpulik/VaultChat
cd VaultChat
npm install
npm run build

Then copy the built files into your vault:

mkdir -p /path/to/your/vault/.obsidian/plugins/VaultChat
cp main.js manifest.json styles.css /path/to/your/vault/.obsidian/plugins/VaultChat/

Restart Obsidian. The plugin will appear in Settings > Community Plugins.

Local model setup

The Local (OpenAI-compatible) provider works with any server that exposes the OpenAI chat-completions API. No API key, no cost, no data leaving your machine. Tested with Ollama and LM Studio; llama.cpp, vLLM, LocalAI, and Jan expose the same API and should work too.

1. Install a server

2. Get a model

With Ollama, pull one from the terminal:

ollama pull llama3.2        # 2GB, good general purpose
ollama pull llama3.2:1b     # 1GB, fastest and smallest
ollama pull mistral         # 4GB, strong reasoning
ollama pull qwen2.5         # 4GB, strong at multilingual

With LM Studio, download a model from its in-app browser and start the local server from the Developer tab.

3. Open VaultChat

Select Local (OpenAI-compatible) from the provider dropdown and set the base URL to match your server. The model list populates from the server's /v1/models endpoint, so it shows whatever that server has available.

If your server needs an API key (vLLM started with --api-key, a LiteLLM proxy, and similar), put it in the API key field for this provider. Leave it blank when the server does not use one.

Note: the server must be running for the model list to load. If the dropdown shows "Fetch failed", start the server, confirm the base URL and port, then hit the refresh button.

Use 127.0.0.1 rather than localhost. Most local servers listen on IPv4 only, while localhost can resolve to IPv6 first and fail with a connection-refused error. VaultChat now substitutes the address automatically, but typing it directly avoids the whole class of problem.

Upgrading from an older version: your Ollama base URL and model carry over automatically.

Reasoning models

Reasoning models stream their chain of thought separately from their answer. VaultChat shows a "Thinking…" indicator while that is happening and then renders the answer when it arrives. The chain of thought is not added to the transcript.

Empty responses

If a model or router accepts the request but sends nothing back, VaultChat says so rather than leaving a blank message. This usually means the route you picked has no working upstream, so try a different model.

Usage

• Click the bot icon in the left ribbon to open the chat panel
• Select your provider and model from the dropdowns in the header
• Use the + button to attach vault files as context. The AI reads their full contents
• Check Include current note to also send your active note
• Press Enter to send, Cmd+Enter for a new line
• Click Stop to cancel a streaming response at any time
• Hover over any assistant message to see Copy and Insert buttons
• When the AI proposes file edits, you'll see a diff with Confirm/Revert (auto-apply mode) or Preview/Apply (manual mode)
• File deletions always require a double confirmation before anything is removed
• Click the menu icon in the header to open chat history. Sessions are grouped by date and show attached files

Settings

Go to Settings > VaultChat to configure:

• API keys for each provider (stored locally, obfuscated after entry). The key for a local server is optional; leave it blank unless the server was started with one
• Default model per provider, with a refresh button for providers that report their own model list
• Custom base URL per provider (for proxies or self-hosted endpoints)
• Context window (num_ctx) for local servers - controls RAM usage on Ollama. Leave at 0 (the default) to let the server choose; servers that do not support the option ignore it
• System prompt - customize the AI's behavior
• Max tokens - maximum response length. Leave at 0 (the default) to let the model decide. Anthropic's API requires the field, so 0 sends 4096 there
• Auto-apply edits - toggle between auto-apply (with Confirm/Revert) and manual Apply mode. Off by default, and also togglable from the chat footer so you can flip it without leaving the conversation

Development

npm run dev   # watch mode, rebuilds on every save

For live reloading inside Obsidian, install the Hot Reload community plugin and symlink the project folder into your vault's plugins directory:

ln -s /path/to/VaultChat /path/to/vault/.obsidian/plugins/VaultChat

Open Obsidian's developer tools with Cmd+Option+I to debug.

Support

If VaultChat is useful to you, consider buying me a coffee.

License

MIT