app.py

import fitz
import gradio as gr
import requests
import io
import re
from PIL import Image

summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
qa_model = pipeline("question-answering", model="deepset/bert-large-uncased-whole-word-masking-squad2")

def extract_text_from_pdf(pdf_file):
    with fitz.open(pdf_file) as pdf:
        text = ""
        for page in pdf:
            text += page.get_text("text")

    text = re.sub(r'\s+', ' ', text).strip()
    return text

def summarize(text):
    if len(text) > 1000:
        chunks = [text[i:i+1000] for i in range(0, len(text), 1000)]
        summary = ""
        for chunk in chunks:
            summary += summarizer(chunk, max_length=150, min_length=50, do_sample=False)[0]['summary_text'] + " "
    else:
        summary = summarizer(text, max_length=150, min_length=50, do_sample=False)[0]['summary_text']

    return summary

# API_URL = "https://api-inference.huggingface.co/models/deepset/bert-large-uncased-whole-word-masking-squad2"
# headers = {"Authorization": f"Bearer {my_key}"}

# def query(payload):
# 	response = requests.post(API_URL, headers=headers, json=payload)
# 	return response.content

def answer_question(text, question):
    response = qa_model(question=question, context=text)
    answer = response['answer'] 
    return answer

def summarize_and_qa(pdf_file, question):
    text = extract_text_from_pdf(pdf_file)
    summary = summarize(text)
    answer = answer_question(text, question)
    # image_bytes = query({"inputs": answer})
    # if image_bytes:
    #     try:
    #         image = Image.open(io.BytesIO(image_bytes))
    #     except Exception as e:
    #         return summary, answer, None
    # else:
    #     image = None
    return summary, answer

gr.Interface(
    fn=summarize_and_qa,
    inputs=["file", "text"],
    outputs=["textbox", "textbox"],
    title="Understand your PDF Better",
    description="Upload a PDF to get a summary. You can ask any question regardging the content of the PDF. It will also generate a picture to help you better understand the content."
).launch(debug=True, share=True)