As AI technology advances, more organizations are utilizing digital assistants like Retrieval Augmented Generation (RAG) to answer domain-specific questions using enterprise data sources. The shift to production workloads requires minimal operational overhead and security measures like identity and access management. A solution presented here details creating a web application-based digital assistant with a serverless architecture, offering benefits like automatic scaling and cost optimization.
The architecture includes hybrid search with Amazon Bedrock’s Knowledge Bases for improved results relevancy. A semantic and keyword search combination ensures precision and coverage in response generation. Integrating AWS services like Amazon Bedrock, Amazon OpenSearch Serverless vector engine, AWS Amplify, Amazon API Gateway, AWS Lambda, Amazon Cognito, and Amazon S3, and operational flow is established.
Prerequisites include an AWS account with access to Amazon Bedrock models like Titan Embeddings G1 – Text and Claude Instant. Steps involve creating a knowledge base with a vector store to enrich user prompts, establishing APIs, and backend for authentication and permission management. A user pool in Amazon Cognito and Lambda functions handle user validations and query submissions.
Configuring Amazon Cognito user pool includes creating a test user via console or script for web application login. The subsequent setup covers establishing a web application using Amplify, integrating with user pools and APIs. Upon deployment, testing the digital assistant by logging in, and querying provides a demonstration.
Resource cleanup is vital to prevent unnecessary costs. Deleting knowledge bases, CloudFormation stacks, Amplify applications, and S3 buckets ensures proper resource disposal. The post wraps up by highlighting the digital assistant creation workflow and pointing readers to further resources for in-depth exploration.
The solution author, Mehdi Amrane, is a Senior Solutions Architect at Amazon Web Services who assists customers in achieving their cloud goals with expertise in application architecture, DevOps, and Serverless technologies. By following the outlined steps and precautions detailed in this solution, organizations can successfully implement a personalized digital assistant using serverless architecture and AI technology.
Article Source
https://aws.amazon.com/blogs/machine-learning/create-an-end-to-end-serverless-digital-assistant-for-semantic-search-with-amazon-bedrock/