import os
from transformers import pipeline

# Set custom cache directory to avoid permission issues
os.environ["TRANSFORMERS_CACHE"] = "/app/cache"

# Load the model with TensorFlow weights if PyTorch version is unavailable
summarizer = pipeline("summarization", model="t5-base", from_tf=True)

from flask import Flask, request, jsonify

app = Flask(__name__)

@app.route("/summarize", methods=["POST"])
def summarize():
    data = request.json
    text = data.get("text", "")
    summary = summarizer(text, max_length=150, min_length=30, do_sample=False)
    return jsonify({"summary": summary[0]["summary_text"]})

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