Building a RAG-Based Chatbot with Amazon Bedrock, React and Lambda (PART 2)
Building a RAG-Based Chatbot with Amazon Bedrock, React, and Lambda (PART 2) Table of Contents A. Introduction B. Background C. Backend Chatbot API D. Frontend Chatbot Application E. Deploy React Application to S3 F. Resulting Application G. Conclusion A. Introduction In the previous article , we built a RAG (Retrieval-Augmented Generation) agent using Amazon Bedrock . The agent answers customer queries about training courses by combining static information from a CSV file (stored in the Bedrock Knowledge Base) and real-time course status from DynamoDB . In this second part, we will: Build a backend REST API using Python Lambda to invoke the Bedrock RAG agent. Develop a frontend chatbot application using React and the React Chatbotify component. Host the React application as a static website on S3 . Integrate the frontend and backend using API Gateway . Provide full code...