Amazon Bedrock Knowledge Bases help you take advantage of Retrieval Augmented Generation (RAG), a popular technique that involves drawing information from a data store to augment the responses generated by Large Language Models (LLMs). When you set up a knowledge base with your data source and vector store, your application can query the knowledge base to return information to answer the query either with direct quotations from sources or with natural responses generated from the query results.
To use Amazon Bedrock Knowledge Bases with your Amazon Bedrock Agent, you'll have to first create a knowledge base and then associate the knowledge base with the agent. If you haven't yet created a knowledge base, see Retrieve data and generate AI responses with Amazon Bedrock Knowledge Bases to learn about knowledge bases and create one. You can associate a knowledge base during agent creation or after an agent has been created. To associate a knowledge base to an existing agent, choose the tab for your preferred method, and then follow the steps:
To add a knowledge base
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Sign in to the AWS Management Console using an IAM role with Amazon Bedrock permissions, and open the Amazon Bedrock console at https://console.aws.amazon.com/bedrock/
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Select Agents from the left navigation pane. Then, choose an agent in the Agents section.
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Choose Edit in Agent builder
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For the Knowledge bases section, choose Add.
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Choose a knowledge base that you have created and provide instructions for how the agent should interact with it.
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Choose Add. A success banner appears at the top.
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To apply the changes that you made to the agent before testing it, choose Prepare before testing it.
You can modify the query configurations of a knowledge base attached to your agent by using the sessionState field in the InvokeAgent request when you invoke your agent. For more information, see Control agent session context.
