app.py

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

app = Flask(__name__)

# Load model
model_name = "VietAI/vit5-base"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSeq2SeqLM.from_pretrained(model_name)

@app.route("/summarize", methods=["POST"])
def summarize():
    data = request.json
    text = data.get("text", "")
    if not text.strip():
        return jsonify({"error": "Missing text"}), 400

    inputs = tokenizer.encode(text, return_tensors="pt", max_length=512, truncation=True)
    summary_ids = model.generate(
        inputs,
        max_length=100,
        min_length=30,
        num_beams=4,
        length_penalty=2.0,
        early_stopping=True
    )
    summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
    return jsonify({"summary": summary})

@app.route("/", methods=["GET"])
def root():
    return "ViT5 summarization API is running."

if __name__ == "__main__":
    app.run(host="0.0.0.0", port=7860)