Create app.py

app.py

@@ -0,0 +1,36 @@
+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)