README.md

metadata

title: Rag PdfQA Chatbot
emoji: 👁
colorFrom: purple
colorTo: gray
sdk: streamlit
sdk_version: 1.38.0
app_file: app.py
pinned: false

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

PDF Query Chatbot

Overview

The PDF Query Chatbot is a Streamlit-based application hosted on Hugging Face Spaces. It allows users to upload a PDF document and ask questions about its content. The chatbot utilizes a transformer model to generate responses based on the text extracted from the PDF.

Live Demo

You can try the PDF Query Chatbot live here: PDF Query Chatbot on Hugging Face Spaces

Features

• Upload PDF Files: Upload PDF files directly from your local machine.
• Query Input: Enter questions related to the uploaded PDF content.
• Text Extraction: Extracts text from the PDF for querying.
• Response Generation: Uses a transformer model to generate answers based on your query and the PDF content.

How to Use

1. Upload PDF File: Use the sidebar to upload a PDF file.
2. Enter Query: Type your question related to the PDF content in the query input field.
3. Submit: Click the "Submit" button to process the file and get a response.
4. View Response: The generated response will be displayed below the input fields.

Requirements

To run this app locally, ensure you have the following Python packages installed:

• transformers: For using pre-trained transformer models.
• PyPDF2: For extracting text from PDF files.
• torch: PyTorch library for running the model.
• streamlit: For the web app interface.

Installation

1. Clone the repository:

   git clone https://github.com/mldatascientist23/Generative_AI_Projects.git
   cd your-repository
   

2. Install the required packages:

   pip install transformers PyPDF2 torch streamlit
   

3. Run the Streamlit app:

   streamlit run app.py
   ``