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import gradio as gr
import fitz # PyMuPDF
from transformers import pipeline
import textwrap
# Load summarization model
summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
# Extract text from PDF
def extract_text_from_pdf(pdf_file):
text = ""
#with fitz.open(stream=file_obj.read(), filetype="pdf") as doc:
with fitz.open(pdf_file.name) as doc:
for page in doc:
text += page.get_text()
return text.strip().replace("\n", " ")
# Chunk long text into manageable sizes
def chunk_text(text, max_chunk_len=1000):
return textwrap.wrap(text, max_chunk_len)
# Summarize long PDFs by chunking
def summarize_long_pdf(file_obj):
full_text = extract_text_from_pdf(file_obj)
if not full_text:
return "❌ No readable text extracted from the PDF."
chunks = chunk_text(full_text, max_chunk_len=1000)
summaries = []
for i, chunk in enumerate(chunks):
try:
summary = summarizer(chunk, max_length=120, min_length=30, do_sample=False)[0]['summary_text']
summaries.append(f"🔹 Part {i+1}: {summary}")
except Exception as e:
summaries.append(f"⚠️ Error summarizing part {i+1}: {e}")
return "\n\n".join(summaries)
# Gradio UI
gr.Interface(
fn=summarize_long_pdf,
inputs=gr.File(label="📥 Upload Multi-page PDF"),
outputs=gr.Textbox(label="📝 Full Summary"),
title="📘 Multi-Page PDF Summarizer",
description="Upload long PDFs (e.g., Morningstar reports). Summarized in chunks using BART."
).launch() |