--- LinkTitle: Create Bedrock knowledge base Title: Create a Bedrock knowledge base alwaysopen: false categories: - docs - integrate - oss - rs - rc description: Shows how to set up your Knowledge base in Amazon Bedrock. group: cloud-service summary: With Amazon Bedrock, users can access foundational AI models from a variety of vendors through a single API, streamlining the process of leveraging generative artificial intelligence. type: integration weight: 2 --- After you have set up a vector database with Redis Cloud, you can use it to create a knowledge base for your models. Before you begin this guide, you will need: - An [AWS S3 Bucket](https://docs.aws.amazon.com/AmazonS3/latest/userguide/creating-buckets-s3.html) with text data that you want to use to train your models. - An [AWS IAM Role](https://docs.aws.amazon.com/IAM/latest/UserGuide/id_roles_create_for-service.html) with permissions for the Bedrock knowledge base. - A Redis database that is [set up for Amazon Bedrock]({{< relref "/integrate/amazon-bedrock/set-up-redis" >}}) ## Create knowledge base To use your Redis database to create a knowledge base on Amazon Bedrock: 1. Sign in to the [AWS console](https://console.aws.amazon.com/). 1. Use the **Services** menu to locate and select **Machine Learning** > **Amazon Bedrock**. This takes you to the Amazon Bedrock admin panel. 1. Select **Knowledge base** > **Create knowledge base** to create your knowledge base. {{The Create knowledge base button.}} 1. In the **Knowledge base details** section, enter a name and description for your knowledge base. 1. Select the IAM role for the Bedrock knowledge base in the **IAM Permissions** section. Select **Next** to add the data source. 1. Enter a name for the data source and connect your S3 bucket in the **Data source** section. 1. In the **Vector database** section, select **Redis Cloud** and select the checkbox to agree with the legal disclaimer. {{The Redis Cloud selection for your vector database.}} Fill in the fields with the following information: - **Endpoint URL**: Public endpoint of your database. This can be found in the [Redis Cloud console](https://cloud.redis.io/) from the database list or from the **General** section of the **Configuration** tab for the source database. - **Credentials Secret ARN**: [Amazon Resource Name (ARN)](https://docs.aws.amazon.com/secretsmanager/latest/userguide/reference_iam-permissions.html#iam-resources) of your [database credentials secret]({{< relref "/integrate/amazon-bedrock/set-up-redis#store-secret" >}}). - **Vector Index name**: Name of the [vector index]({{< relref "/integrate/amazon-bedrock/set-up-redis#create-vector-index" >}}) - **Vector field**: Name of the [vector field]({{< relref "/integrate/amazon-bedrock/set-up-redis#create-vector-index" >}}) of the vector index - **Text field**: Name of the [text field]({{< relref "/integrate/amazon-bedrock/set-up-redis#create-vector-index" >}}) of the vector index - **Metadata field**: Name of the [metadata field]({{< relref "/integrate/amazon-bedrock/set-up-redis#create-vector-index" >}}) of the vector index Select **Next** to review your settings. 1. Review your knowledge base before you create it. Select **Create knowledge base** to finish creation. {{The Create knowledge base button.}} Amazon Bedrock will sync the data from the S3 bucket and load it into your Redis database. This will take some time. Your knowledge base will have a status of **Ready** when it is ready to be connected to an Agent. {{A Bedrock knowledge base with a Ready status.}} Select the name of your knowledge base to view the syncing status of your data sources. The data source will have a status of **Ready** when it is synced to the vector database. {{A Bedrock data source with a Ready status.}} After the knowledge base is ready, you can use it to [Create an agent]({{< relref "/integrate/amazon-bedrock/create-agent" >}}).