This project involves developing a Retrieval-Augmented Generation (RAG) chatbot designed to answer user queries related to Air India. The application combines information retrieval techniques with large language models to generate context-aware responses based on information available in a designated knowledge base.
The system follows a RAG architecture in which user queries are processed to retrieve relevant contextual information. The retrieved content is then supplied to a language model through Amazon Bedrock to generate a natural language response. This approach aims to improve the relevance of responses by grounding them in domain-specific information rather than relying exclusively on the model's pretrained knowledge.
The implementation includes designing the application architecture, configuring AWS services, setting up the development environment, and integrating the components required for retrieval and response generation. The project demonstrates how managed cloud-based AI services can be used to build conversational applications for specific business domains.
Overall, the project provides hands-on experience in Generative AI, RAG architecture, foundation model integration, information retrieval, and cloud-based chatbot development.