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# Runhouse

This page covers how to use the Runhouse ecosystem within LangChain. It is broken into three parts: installation and setup, LLMs, and Embeddings.

## Installation and Setup

- Install the Python SDK with `pip install runhouse`

- If you’d like to use on-demand cluster, check your cloud credentials with `sky check`

## Self-hosted LLMs

For a basic self-hosted LLM, you can use the `SelfHostedHuggingFaceLLM` class. For more custom LLMs, you can use the `SelfHostedPipeline` parent class.

    from langchain.llms import SelfHostedPipeline, SelfHostedHuggingFaceLLM

For a more detailed walkthrough of the Self-hosted LLMs, see this notebook

## Self-hosted Embeddings

There are several ways to use self-hosted embeddings with LangChain via Runhouse.

For a basic self-hosted embedding from a Hugging Face Transformers model, you can use the `SelfHostedEmbedding` class.

    from langchain.llms import SelfHostedPipeline, SelfHostedHuggingFaceLLM

For a more detailed walkthrough of the Self-hosted Embeddings, see this notebook