ChatPDF: A Conversational Interface for arXiv Papers

Project Overview

ChatPDF leverages advanced AI technologies to create a conversational interface that interacts with research papers from arXiv, providing users with an intuitive way to explore and understand complex scientific documents. Using a sophisticated Retriever-Reader-Generator (RAG) pipeline, the application ingests PDF documents, extracts text, and enables real-time chat functionalities to discuss the papers' content.

Key Components

• LangChain: Utilizes LangChain for document processing and embedding.
• Chroma Vector Store: Employs Chroma for efficient document retrieval based on semantic similarity.
• Ollama: Leverages Ollama for generating conversational responses.
• Sentence Transformers & FastEmbed Embeddings: Integrates advanced embedding techniques for accurate context understanding.

Installation

Prerequisites

• Python 3.8+
• Pip

Setup Environment

python -m venv chatpdf-env
source chatpdf-env/bin/activate  # On Windows use `chatpdf-env\Scripts\activate`

Usage

Initialize the Application

Clone the repository and navigate to the project directory. Install all required dependencies. Start the Streamlit Application

Run the following command in your terminal:

streamlit run chatrag.py

The Streamlit interface will open in your browser, where you can upload PDF documents and interact with the chat interface.

License

This project is licensed under the MIT License - see the LICENSE file for details.