Chat with your PDF – Gen AI App – With Amazon Bedrock

In this hands-on tutorial by My Cloud Tutorials, Girish demonstrates how to build a chatbot application that allows users to chat with a PDF document using AWS Amazon Bedrock, Docker, Python, Langchain, and Streamlit. The application leverages Retrieval-Augmented Generation (RAG) to provide context to the Large Language Model (LLM) along with user queries to generate responses from the knowledge base.

The video is divided into several key sections:

1. **Introduction and Demo**: Girish introduces the concept of the application and provides a quick demo showing how the chatbot interacts with a PDF document by answering questions based on the content of the PDF.

2. **Application Architecture**: Girish explains the architecture of the application, which consists of two parts: the Admin Web App and the Client Web App. The Admin Web App allows administrators to upload PDFs, split the text into chunks, create vector embeddings using the Amazon Titan Embedding Model, and store the embeddings in an S3 bucket. The Client Web App allows users to query the PDF by converting their queries into vector embeddings, performing a similarity search, and using the Claude model from Anthropic to generate responses.

3. **Building the Admin Web App**: Girish walks through the process of building the Admin Web App, including creating the S3 bucket, setting up the required libraries, creating the Docker image, and writing the code to upload and process the PDF, split the text, create vector embeddings, and upload the embeddings to S3.

4. **Building the Client Web App**: Girish demonstrates how to build the Client Web App, which involves downloading the index files from S3, creating a local FAISS index, and setting up the interface for users to ask questions. He explains how to use Langchain’s RetrievalQA to convert user queries into vector embeddings, perform a similarity search, and generate responses using the Claude model.

5. **Testing and Finalizing the Application**: Throughout the tutorial, Girish frequently tests the application to ensure each part works correctly. He demonstrates how to handle errors, refine the code, and ensure the application runs smoothly.

The source code for the application is available on GitHub, and Girish encourages viewers to like, share, and subscribe to his channel for more tutorials on cloud and AI technologies.

Overall, the video provides a detailed, step-by-step guide to building a chatbot that interacts with PDF documents, making it accessible for developers looking to integrate AI and cloud technologies into their applications.