mirror of
https://github.com/hwchase17/langchain
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26 lines
1.1 KiB
Markdown
26 lines
1.1 KiB
Markdown
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# Baseten
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Learn how to use LangChain with models deployed on Baseten.
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## Installation and setup
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- Create a [Baseten](https://baseten.co) account and [API key](https://docs.baseten.co/settings/api-keys).
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- Install the Baseten Python client with `pip install baseten`
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- Use your API key to authenticate with `baseten login`
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## Invoking a model
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Baseten integrates with LangChain through the LLM module, which provides a standardized and interoperable interface for models that are deployed on your Baseten workspace.
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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).
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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).
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```python
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from langchain.llms import Baseten
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wizardlm = Baseten(model="MODEL_VERSION_ID", verbose=True)
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wizardlm("What is the difference between a Wizard and a Sorcerer?")
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```
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