The Conversational PDF Reader is an innovative application that allows users to upload PDF documents and interact with their content using natural language. Built using Streamlit and integrated with advanced NLP capabilities, the app leverages Hugging Face's MiniLM-L6-v2 model for generating embeddings from uploaded PDFs. These embeddings enable efficient querying and retrieval of information from the documents.

Key Features

• PDF Upload: Users can upload PDF files directly to the app.
• Natural Language Interface: Utilizes ChatGroq and LangChain to provide a conversational interface for querying PDF content.
• Document Processing: Implements PyPDFLoader for loading and processing PDF documents into text.
• Embeddings Generation: Employs Chroma for generating embeddings using Hugging Face's embeddings model.
• Question-Answering: Enables users to ask questions about the uploaded PDFs, with responses generated by the integrated Hugging Face model.
• Chat History Management: Maintains session-based chat history to provide context-aware responses.

This project is ideal for users who need to quickly access and interact with information stored in PDF documents through a user-friendly conversational interface.