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from flask import Flask, request, jsonify
import os
import pdfplumber
import pytesseract
from PIL import Image
from transformers import PegasusForConditionalGeneration, PegasusTokenizer
import torch
import logging
app = Flask(__name__)
# Set up logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
# Load Pegasus Model
logger.info("Loading Pegasus model and tokenizer...")
tokenizer = PegasusTokenizer.from_pretrained("google/pegasus-xsum")
model = PegasusForConditionalGeneration.from_pretrained("google/pegasus-xsum")
logger.info("Model loaded successfully.")
# Extract text from PDF with page limit and timeout handling
def extract_text_from_pdf(file_path, max_pages=10):
text = ""
try:
with pdfplumber.open(file_path) as pdf:
total_pages = len(pdf.pages)
pages_to_process = min(total_pages, max_pages)
logger.info(f"Extracting text from {pages_to_process} of {total_pages} pages in {file_path}")
for i, page in enumerate(pdf.pages[:pages_to_process]):
try:
extracted = page.extract_text()
if extracted:
text += extracted + "\n"
except Exception as e:
logger.warning(f"Error extracting text from page {i+1}: {e}")
continue
except Exception as e:
logger.error(f"Failed to process PDF {file_path}: {e}")
return ""
return text.strip()
# Extract text from image (OCR)
def extract_text_from_image(file_path):
try:
logger.info(f"Extracting text from image {file_path} using OCR...")
image = Image.open(file_path)
text = pytesseract.image_to_string(image)
return text.strip()
except Exception as e:
logger.error(f"Failed to process image {file_path}: {e}")
return ""
# Summarize text using Pegasus with truncation
def summarize_text(text, max_input_length=512, max_output_length=150):
try:
logger.info("Summarizing text...")
inputs = tokenizer(text, return_tensors="pt", truncation=True, max_length=max_input_length)
summary_ids = model.generate(
inputs["input_ids"],
max_length=max_output_length,
min_length=30,
num_beams=4,
early_stopping=True
)
summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
logger.info("Summarization completed.")
return summary
except Exception as e:
logger.error(f"Error during summarization: {e}")
return ""
@app.route('/summarize', methods=['POST'])
def summarize_document():
if 'file' not in request.files:
logger.error("No file uploaded in request.")
return jsonify({"error": "No file uploaded"}), 400
file = request.files['file']
filename = file.filename
if not filename:
logger.error("Empty filename in request.")
return jsonify({"error": "No file uploaded"}), 400
file_path = os.path.join("/tmp", filename)
try:
file.save(file_path)
logger.info(f"File saved to {file_path}")
if filename.lower().endswith('.pdf'):
text = extract_text_from_pdf(file_path, max_pages=5)
elif filename.lower().endswith(('.png', '.jpeg', '.jpg')):
text = extract_text_from_image(file_path)
else:
logger.error(f"Unsupported file format: {filename}")
return jsonify({"error": "Unsupported file format. Use PDF, PNG, JPEG, or JPG"}), 400
if not text:
logger.warning(f"No text extracted from {filename}")
return jsonify({"error": "No text extracted from the file"}), 400
summary = summarize_text(text)
if not summary:
logger.warning("Summarization failed to produce output.")
return jsonify({"error": "Failed to generate summary"}), 500
logger.info(f"Summary generated for {filename}")
return jsonify({"summary": summary})
except Exception as e:
logger.error(f"Unexpected error processing {filename}: {e}")
return jsonify({"error": str(e)}), 500
finally:
if os.path.exists(file_path):
try:
os.remove(file_path)
logger.info(f"Cleaned up file: {file_path}")
except Exception as e:
logger.warning(f"Failed to delete {file_path}: {e}")
if __name__ == '__main__':
logger.info("Starting Flask app...")
app.run(host='0.0.0.0', port=7860) |