Backstage AI Agent

This agent provides an interactive communication channel to query an analyze documentation stored in Backstage.

1. For each document entry in Backstage s3 bucket there is a correspondent search_index.json that contains all document data. The data in search_index.json is split in chunks (one per subheading). Content Creator function reads the file and assembles those chunks together. It also adds backstage links that point to the correspondent subheadings. The resulted document is stored in Bedrock S3 bucket.
2. Bedrock has an option to build a Knowledge Base from the documents (which is essentially RAG). The build process works as follows:
   • The Knowledge Base agent takes a document form the s3 bucket and pipes it thorough amazon.titan-embed-text-v1 model to generate a vector representation of the document text.
   • The Knowledge Base agent then stores this vector together with the document text in OpenSearch as inverted index for the later use.
3. The Bedrock Agent is a middle man that processes user requests. The flow looks as follows:
   • The user sends a query to the Bedrock Agent.
   • The Bedrock Agent pipes the query through amazon.titan-embed-text-v1 model to generate a vector representation of the query.
   • The Bedrock Agent then sends this vector to OpenSearch to find the most similar documents.
   • The found documents and the query are piped through anthropic.claude-3-5-sonnet-20240620-v1:0 to get an answer.
   • The Bedrock Agent has a set of preconfigured actions that it can perform by invoking Action Performer lambda function. For example, it can check that Backstage links are not broken before returning them to the user.

Installation

Pre-requisites

• Thechdocs is deployed following Recommended Deployment guide and AWS S3 used as a storage. If the bucket is located in another account, then s3:ListBucket and s3:GetObject permissions should be granted for the target account.
• Bedrock models are enabled and allowed in the target AWS Account. Namely amazon.titan-embed-text-v1 and anthropic.claude-3-5-sonnet-20240620-v1:0 are used.

The backend is built with CDK using Amplify.

To deploy a sandboxed version of the agent, execute from the root:

SOURCE_BUCKET_NAME=<your_s3_bucket_name> BACKSTAGE_URL=<your_backstage.url> npx ampx sandbox