app.py

import gradio as gr
import pdfplumber
from transformers import pipeline

qa_pipeline = pipeline("question-answering", model="distilbert-base-uncased-distilled-squad")

def extract_text_from_pdf(file):
    with pdfplumber.open(file.name) as pdf:
        return "\n".join(page.extract_text() or '' for page in pdf.pages)

def answer_question(file, question):
    if file.name.endswith('.pdf'):
        context = extract_text_from_pdf(file)
    elif file.name.endswith('.txt'):
        context = file.read().decode("utf-8")
    else:
        return "Unsupported file format. Please upload a PDF or .txt file."

    if not question.strip():
        return "Please enter a question."

    result = qa_pipeline(question=question, context=context)
    return result["answer"]
with gr.Blocks() as demo:
    gr.Markdown("## 📄 Document Question Answering with DistilBERT")
    with gr.Row():
        file_input = gr.File(label="Upload a PDF or TXT file")
        question_input = gr.Textbox(label="Ask a question", placeholder="e.g. What is the main topic?")
    answer_output = gr.Textbox(label="Answer", placeholder="The answer will appear here.")
    
    submit_btn = gr.Button("Get Answer")
    
    submit_btn.click(fn=answer_question, inputs=[file_input, question_input], outputs=answer_output)

demo.launch()