langchain/docs/integrations/runhouse.md
Leonid Ganeline e2d7677526
docs: compound ecosystem and integrations (#4870)
# Docs: compound ecosystem and integrations

**Problem statement:** We have a big overlap between the
References/Integrations and Ecosystem/LongChain Ecosystem pages. It
confuses users. It creates a situation when new integration is added
only on one of these pages, which creates even more confusion.
- removed References/Integrations page (but move all its information
into the individual integration pages - in the next PR).
- renamed Ecosystem/LongChain Ecosystem into Integrations/Integrations.
I like the Ecosystem term. It is more generic and semantically richer
than the Integration term. But it mentally overloads users. The
`integration` term is more concrete.
UPDATE: after discussion, the Ecosystem is the term.
Ecosystem/Integrations is the page (in place of Ecosystem/LongChain
Ecosystem).

As a result, a user gets a single place to start with the individual
integration.
2023-05-18 09:29:57 -07:00

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Markdown

# Runhouse
This page covers how to use the [Runhouse](https://github.com/run-house/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.
```python
from langchain.llms import SelfHostedPipeline, SelfHostedHuggingFaceLLM
```
For a more detailed walkthrough of the Self-hosted LLMs, see [this notebook](../modules/models/llms/integrations/runhouse.ipynb)
## 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.
```python
from langchain.llms import SelfHostedPipeline, SelfHostedHuggingFaceLLM
```
For a more detailed walkthrough of the Self-hosted Embeddings, see [this notebook](../modules/models/text_embedding/examples/self-hosted.ipynb)