Document ChatBot

Conversational RAG

A Document ChatBot based on Conversational RAG(Retrieval-augmented generation) that retrieves and summarizes information from uploaded documents (PDF files or URLs). It provides concise, context-based answers to user questions by analyzing the contents of the uploaded files or web pages.

Features

Document Retrieval: Upload PDF files or provide URLs to retrieve content.
Conversational RAG: Uses Retrieval-Augmented Generation to offer more accurate, context-aware answers.
Contextualized Question Reformulation: Rephrases questions for standalone clarity, retaining chat history context.
Concise Responses: Generates short, clear answers, using minimal text for easy readability.
Session Management: Independently manages chat history and session data.

Installation

To get started with the PDF Q&A System, follow these steps:

2.Clone the repository:

   git clone https://github.com/vishnun0027/Document-ChatBot.git
   cd Document-ChatBot

2.Install the required packages:

   pip install -r requirements.txt

3.Set up environment variables: Create a .env file in the root directory of the project and add your API keys:

   GROQ_API_KEY=your_groq_api_key
   HF_API_KEY=your_hugging_face_api_key

Usage

Run the Streamlit application:
run app

   streamlit run bot.py

Upload a PDF: Use the sidebar to upload your PDF/link of document.
Ask Questions in chat: After processing, enter your questions in the chat input field to receive answers based on the content of the document.