Documentation
Predicting with LLMs
Agentic Flows
Plugins
Tools Provider
Prompt Preprocessor
Generators
Custom Configuration
Publishing a Plugin
Text Embedding
Tokenization
API Reference
Model Info
Predicting with LLMs
Agentic Flows
Plugins
Tools Provider
Prompt Preprocessor
Generators
Custom Configuration
Publishing a Plugin
Text Embedding
Tokenization
API Reference
Model Info
Introduction to Plugins
Plugin support is currently in private beta. Join the beta here.
Plugins extend LM Studio's functionality by providing "hook functions" that execute at specific points during operation.
Plugins are currently written in JavaScript/TypeScript and run on Node.js v20.18.0. Python support is in development.
LM Studio includes Node.js, so no separate installation is required.
To create a new plugin, navigate to LM Studio... [TO BE CONTINUED]
Once you've created a plugin, run this command in the plugin directory to start development mode:
lms dev
Your plugin will appear in LM Studio's plugin list. Development mode automatically rebuilds and reloads your plugin when you make code changes.
You only need lms dev
during development. When the plugin is installed, LM Studio automatically runs them as needed. Learn more about distributing and installing plugins in the Sharing Plugins section.
Give models extra capabilities by creating tools they can use during generation, like accessing external APIs or performing calculations.
Modify user input before it reaches the model - handle file uploads, inject context, or transform queries.
Create custom text generation sources that replace the local model, perfect for online model adapters.
Add configuration UIs so users can customize your plugin's behavior.
Use npm packages to leverage existing libraries in your plugins.
Package and share your plugins with the community.
On this page
Getting Started
Create a new plugin
Run a plugin in development mode
Next Steps