from flask import Flask, render_template, request, jsonify
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
import os

app = Flask(__name__)

# Load the fine-tuned model and tokenizer
model_dir = "./finetune_model"  # Replace with your model's directory
tokenizer = AutoTokenizer.from_pretrained(model_dir)
model = AutoModelForSeq2SeqLM.from_pretrained(model_dir)

def generate_headline(article):
    """
    Generate a headline from the given article using the fine-tuned model.
    """
    inputs = tokenizer.encode(article, return_tensors="pt", max_length=512, truncation=True)
    outputs = model.generate(inputs, max_length=128, num_beams=5, early_stopping=True)
    headline = tokenizer.decode(outputs[0], skip_special_tokens=True)
    return headline

@app.route("/", methods=["GET", "POST"])
def home():
    headline = None
    if request.method == "POST":
        article = request.form.get("article")
        if article:
            headline = generate_headline(article)
    return render_template("index.html", headline=headline)

if __name__ == "__main__":
    # Use dynamic port for compatibility
    port = int(os.environ.get("PORT", 5000))  # Default to 5000 if no PORT is set
    app.run(host="0.0.0.0", port=port, debug=False)