app.py

from flask import Flask, request, jsonify
import json
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

app = Flask(__name__)

# Load AI Model
model_name = "HuggingFaceH4/zephyr-7b-beta"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

# Load Personal Data
with open("data.json", "r") as f:
    user_data = json.load(f)

def get_ai_response(user_message):
    """ Generate AI response using Hugging Face Model """
    inputs = tokenizer(user_message, return_tensors="pt")
    outputs = model.generate(**inputs, max_length=200)
    reply = tokenizer.decode(outputs[0], skip_special_tokens=True)
    return f"This is {user_data['assistant_name']}: {reply}"

@app.route("/reply", methods=["POST"])
def reply():
    data = request.json
    user_message = data.get("message", "")

    if not user_message:
        return jsonify({"reply": "I will answer later."})

    ai_reply = get_ai_response(user_message)
    return jsonify({"reply": ai_reply})

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