Creating an End-to-End PDF Chat Application Using Google Generative AI
Hello everyone! Welcome to my blog where we delve into creating a fascinating end-to-end project: a chat application that interacts with multiple PDF documents using Google Generative AI. This application will leverage LangChain and various vector embedding techniques, including one developed by Facebook. Let's dive in step-by-step to build this application from scratch. Project Overview The application allows users to chat with multiple PDF documents. Users can upload multiple PDFs, and the application will convert these PDFs into vector embeddings. These embeddings are stored locally (or in a database). Users can then ask questions related to the content of these PDFs, and the application will retrieve and provide detailed answers. Tools and Libraries Streamlit : For the web interface. Google Generative AI : For generating text responses. LangChain : For handling and processing PDFs. FAISS : For storing and retrieving vector embeddings. PyPDF2 : For reading PDF content. dotenv ...