langchain/docs/extras/integrations/providers/baseten.md

# Baseten

Learn how to use LangChain with models deployed on Baseten.

## Installation and setup

- Create a [Baseten](https://baseten.co) account and [API key](https://docs.baseten.co/settings/api-keys).
- Install the Baseten Python client with `pip install baseten`
- Use your API key to authenticate with `baseten login`

## Invoking a model

Baseten integrates with LangChain through the LLM module, which provides a standardized and interoperable interface for models that are deployed on your Baseten workspace.

You can deploy foundation models like WizardLM and Alpaca with one click from the [Baseten model library](https://app.baseten.co/explore/) or if you have your own model, [deploy it with this tutorial](https://docs.baseten.co/deploying-models/deploy).

In this example, we'll work with WizardLM. [Deploy WizardLM here](https://app.baseten.co/explore/wizardlm) and follow along with the deployed [model's version ID](https://docs.baseten.co/managing-models/manage).

```python
from langchain.llms import Baseten

wizardlm = Baseten(model="MODEL_VERSION_ID", verbose=True)

wizardlm("What is the difference between a Wizard and a Sorcerer?")
```
Baseten integration (#5862) This PR adds a Baseten integration. I've done my best to follow the contributor's guidelines and add docs, an example notebook, and an integration test modeled after similar integrations' test. Please let me know if there is anything I can do to improve the PR. When it is merged, please tag https://twitter.com/basetenco and https://twitter.com/philip_kiely as contributors (the note on the PR template said to include Twitter accounts) 1 year ago			`# Baseten`

			`Learn how to use LangChain with models deployed on Baseten.`

			`## Installation and setup`

			`- Create a [Baseten](https://baseten.co) account and [API key](https://docs.baseten.co/settings/api-keys).`
			- Install the Baseten Python client with `pip install baseten`
			- Use your API key to authenticate with `baseten login`

			`## Invoking a model`

			`Baseten integrates with LangChain through the LLM module, which provides a standardized and interoperable interface for models that are deployed on your Baseten workspace.`

			`You can deploy foundation models like WizardLM and Alpaca with one click from the [Baseten model library](https://app.baseten.co/explore/) or if you have your own model, [deploy it with this tutorial](https://docs.baseten.co/deploying-models/deploy).`

			`In this example, we'll work with WizardLM. [Deploy WizardLM here](https://app.baseten.co/explore/wizardlm) and follow along with the deployed [model's version ID](https://docs.baseten.co/managing-models/manage).`

			```python
			`from langchain.llms import Baseten`

			`wizardlm = Baseten(model="MODEL_VERSION_ID", verbose=True)`

			`wizardlm("What is the difference between a Wizard and a Sorcerer?")`
			```