Create Amazon Knowledge Base
- Updated: 2024/09/07
Create Amazon Knowledge Base
This is a prerequisite step before you create a Grounded by knowledge baseModel connection.
To use the Amazon Bedrock-RAG capability, you would first create a Knowledge Base in Amazon Bedrock.
The Amazon Knowledge Base comprises of a data source, an embedding model,
and a vector store that you would configure in the Amazon Bedrock
console in the following order:
- Within Amazon Bedrock, navigate to Knowledge
Bases to create a knowledge base.Note: See Create a knowledge base.
- Next, you would choose your data source from options such as Amazon S3, web
crawler, Confluence, Salesforce, or SharePoint, and configure it with the
default settings.Note: Use default settings for the Chunking and parsing configurations section, unless you would like to choose a chunking strategy as per your use case.
- Then you would choose from the available list of Embeddings model in Amazon Bedrock as per your requirement, and keep the default Vector dimensions of the chosen model.
- Next, choose from the available list of vector stores in the Vector database section, and create the knowledge base.
- Then you would test the knowledge base against your data by sending a
prompt-query in the Amazon Bedrock knowledge base console.
The query will validate against the data source you created as a knowledge base,
and get a relevant response.Note: See Test your knowledge base.
- As a logical next step, you would now navigate to the Automation Anywhere Control Room and navigate to to begin creating one.
- Use the Knowledge base ID from Amazon Bedrock to
create the Model connection in .
Adding this ID ensures that the Amazon Bedrock model references the specific content when retrieving a response to ensure response relevance and accuracy.
See: Create Grounded Model connections with Amazon Bedrock RAG capability.
Refer to the following resources for a better understanding of how Amazon Knowledge Base works and the steps to create a knowledge base: