Plugins#
LLM plugins can enhance LLM by making alternative Large Language Models available, either via API or by running the models locally on your machine.
Plugins can also add new commands to the llm CLI tool.
The plugin directory lists available plugins that you can install and use.
Writing a plugin to support a new model describes how to build a new plugin in detail.
- Installing plugins
- Plugin directory
- Plugin hooks
- Writing a plugin to support a new model
- The initial structure of the plugin
- Installing your plugin to try it out
- Building the Markov chain
- Executing the Markov chain
- Adding that to the plugin
- Understanding execute()
- Prompts and responses are logged to the database
- Adding options
- Distributing your plugin
- GitHub repositories
- Publishing plugins to PyPI
- Adding metadata
- What to do if it breaks
- Utility functions for plugins