Obsidian Ollama Plugin

A plugin that integrates Ollama with Obsidian, allowing you to chat with local AI models, search your vault context, and use AI tools like creating files.

Features

• Chat with Ollama models directly in Obsidian
• Vault context search — the assistant can reference your notes
• Semantic/RAG vault indexing — automatically index your vault into a vector database for intelligent retrieval
• Tool integration — create files based on chat responses
• Streaming responses
• Semantic response cache — repeated or similar queries are answered instantly without hitting the model (requires ChromaDB)
• Customisable model, URL, and cache settings

Prerequisites

1. Install Ollama: Follow the instructions at ollama.ai
2. Start Ollama: ollama serve
3. Pull a chat model: ollama pull llama3 (or any other model you prefer)

Optional — Vault Semantic Index (RAG)

The vault semantic index automatically indexes your Obsidian notes into a local ChromaDB vector database. When you ask a question, the plugin performs semantic search against your notes and includes the most relevant passages as context for the AI.

1. Install ChromaDB:

   pip install chromadb
   

2. Start ChromaDB:

   chroma run --host localhost --port 8000
   

3. Pull an embedding model:

   ollama pull nomic-embed-text
   

4. Enable the vault semantic index in the plugin settings and configure the ChromaDB URL.

Optional — Semantic Cache

The semantic cache stores responses in a local ChromaDB vector database. When you ask a question that is semantically similar to one already cached, the stored answer is returned immediately instead of calling the model.

1. Install ChromaDB:

   pip install chromadb
   

2. Start ChromaDB:

   chroma run --host localhost --port 8000
   

3. Pull an embedding model (used to generate vectors for cache lookups):

   ollama pull nomic-embed-text
   

4. Enable the cache in the plugin settings and configure the ChromaDB URL.

Installation

Quick install (recommended)

Use the included install script. It handles dependency installation, building, and copying the plugin into your vault:

# Clone or download this repository, then run:
./install.sh /path/to/your/obsidian/vault

The script will:

• Install npm dependencies (excluding Ollama — you install that separately)
• Compile the TypeScript plugin
• Copy the built plugin into <vault>/.obsidian/plugins/ollama-plugin/

Manual install

If you prefer to install manually:

npm install
npm run build

Then copy the plugin into your vault:

mkdir -p /path/to/vault/.obsidian/plugins/ollama-plugin
cp manifest.json /path/to/vault/.obsidian/plugins/ollama-plugin/
cp main.js /path/to/vault/.obsidian/plugins/ollama-plugin/
cp styles.css /path/to/vault/.obsidian/plugins/ollama-plugin/
# Remove old dist/ from previous installs (no longer needed with bundling)
rm -rf /path/to/vault/.obsidian/plugins/ollama-plugin/dist

Note: The plugin is now bundled into a single main.js via esbuild. The obsidian npm package is a dev-only type stub — Obsidian provides its own API at runtime. The chromadb client library is also bundled into main.js, so no extra node_modules copy is needed for the semantic cache feature.

After installation

1. Restart Obsidian (or reload: Ctrl+Shift+P → "Reload app without saving")
2. Go to Settings → Community plugins → enable Ollama Plugin
3. Configure the plugin at Settings → Ollama Settings

Configuration

Open Settings → Ollama Settings to configure the plugin.

Setting	Default	Description
Ollama URL	http://localhost:11434	Base URL of your Ollama instance
Model	llama3	Model used for chat responses
Vault Search Limit	5	Maximum number of vault entries to include in context
Max Context Length	8000	Maximum characters of vault content sent to the AI per message
Max Message History	50	Maximum number of messages kept in conversation history
Enable Vault Semantic Index	Off	Index vault notes into a vector DB for semantic/RAG search
Vault Index ChromaDB URL	http://localhost:8000	URL of your ChromaDB instance for the vault index
Vault Index Embedding Model	nomic-embed-text	Ollama model used to generate vault embeddings
Vault Index Similarity Threshold	0.75	Minimum cosine similarity (0–1) for a vault search hit
Rebuild Vault Index	—	Button to rebuild the entire vault semantic index
Clear Vault Index	—	Button to delete all indexed vault notes
Enable Semantic Cache	Off	Cache responses for fast repeated queries
ChromaDB URL	http://localhost:8000	URL of your running ChromaDB instance
Cache Embedding Model	nomic-embed-text	Ollama model used to generate cache embeddings
Cache Similarity Threshold	0.85	Minimum cosine similarity (0–1) for a cache hit — higher values require closer matches
Clear Semantic Cache	—	Button to wipe all cached responses from ChromaDB

Usage

1. Open the chat view via the command palette (Ctrl+P → "Open Ollama Chat") or the ribbon icon
2. Type your message in the input box
3. Press Enter or click Send to send your message
4. Press Shift+Enter to insert a line break
5. Click New Chat to start a fresh conversation

Semantic Cache Behaviour

• The cache is bypassed when tool calls are involved (e.g. file creation), since those requests have side effects.
• Responses are stored against the last user message in the conversation. If a new query is sufficiently similar (above the configured threshold), the cached response is returned.
• Re-asking the same question updates the existing cache entry rather than creating a duplicate.
• Use the Clear Semantic Cache button in settings to remove all stored responses (for example after switching embedding models).

Vault Context

When you send a message, the plugin searches your vault for relevant notes and includes them as context. If the Vault Semantic Index is enabled, search is performed via semantic/RAG retrieval using vector embeddings. Otherwise, it falls back to a weighted keyword search:

• Headings — 5x weight
• Frontmatter title — 3x weight
• Frontmatter tags — 2.5x weight
• First paragraph — 1.5x weight
• General content — 1x weight

The plugin automatically watches your vault for changes (create, modify, delete, rename) and updates the semantic index in real time when enabled.

Tools

The plugin exposes a create_file tool that allows the AI to create new markdown files in your vault. Paths are validated for safety (no .obsidian/.git access, no path traversal).

Supported Models

Any Ollama-supported model works. Popular choices:

• llama3
• llama2
• mistral
• codellama
• and many more — see ollama.com/library

Development

npm install
npm run build
npm test

Troubleshooting

Symptom	Likely cause	Fix
Plugin doesn't appear in Obsidian	Install script was not run or failed	Run ./install.sh /path/to/vault and reload Obsidian
Cannot connect to Ollama	Ollama is not running	Run ollama serve
Model not found	Model not pulled	Run ollama pull <model>
Semantic cache unavailable (notice shown)	ChromaDB is not running, or the ChromaDB URL is wrong	Start ChromaDB (chroma run) and verify the URL in settings
Cache always misses	Similarity threshold is too high, or the embedding model was changed	Lower the threshold or click Clear Semantic Cache and let the cache rebuild
Slow first response after enabling cache	Embedding model not yet pulled	Run ollama pull nomic-embed-text (or the model you configured)
Permission issues	Vault write permissions	Check that your Obsidian vault has proper write permissions

Security

• File paths are validated to prevent access to .obsidian/ and .git/ directories
• Path traversal attempts (..) are blocked
• Absolute paths and Windows drive letters are rejected
• Maximum path length is enforced (200 characters)

License

MIT License

Copyright (c) 2024 Flo Egger

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.