Integrate Amazon Bedrock with Astra DB Serverless
You can use Astra DB Serverless (Vector) databases with Amazon Bedrock.
This tutorial explains how to run a notebook in an Amazon SageMaker Studio environment. The notebook demonstrates a basic question-and-answer system with LangChain, Amazon Bedrock, and an Astra DB Serverless database.
Prerequisites
To complete this tutorial, you need the following:
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An active Astra account
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An active Serverless (Vector) database
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An application token with the Database Administrator role
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Credentials for an AWS identity with access to Amazon Bedrock
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Access to Amazon SageMaker
Run the notebook in Amazon SageMaker
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Download the tutorial notebook from GitHub and save it locally.
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In the Amazon SageMaker console navigation pane, click Studio.
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Create or select a SageMaker domain.
If you create a domain, set up a single user domain with the default settings.
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Create or select a user profile.
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Click Open Studio.
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Click JupyterLab.
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Click Create Jupyter Lab space.
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Enter a name for the space, and then click Create space.
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Leave the default settings as configured, and then click Run space.
When the space is ready, the status changes to Running.
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To open the Jupyter Lab space, click Open.
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In the Jupyter Lab space, click Upload Files.
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Upload the tutorial notebook.
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To open the notebook, double-click it.
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To run the notebook, click Run, and then select Run All Cells.
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When prompted, input secrets required by the notebook, such as your application token.
