Update app.py

app.py

@@ -1,51 +1,45 @@
-from flask import Flask, render_template, request, jsonify, session
+from flask import Flask, render_template, request, jsonify
 from transformers import AutoModelForCausalLM, AutoTokenizer
-import torch
-from datetime import datetime
+import datetime
 
 app = Flask(__name__)
-app.secret_key = "supersecretkey"  # Dùng để quản lý session
 
-# Tải mô hình và tokenizer từ Hugging Face
+# Load the model and tokenizer
 model_path = "phamhai/Llama-3.2-3B-Instruct-Frog"
 tokenizer = AutoTokenizer.from_pretrained(model_path)
 model = AutoModelForCausalLM.from_pretrained(model_path)
 
+# Store chat history
+chat_history = []
+
 @app.route('/')
 def index():
-    session.setdefault('history', [])  # Tạo session nếu chưa có
-    return render_template('index.html', history=session['history'])
+    return render_template('index.html', history=chat_history)
 
 @app.route('/chat', methods=['POST'])
 def chat():
-    user_input = request.json.get("message")
-    if not user_input:
-        return jsonify({"response": "Xin hãy nhập tin nhắn!"})
-
-    # Tokenize input và sinh output
-    messages = [
-        {"role": "system", "content": "Bạn là trợ lý của tôi, tên là Vivi."},
-        {"role": "user", "content": user_input}
-    ]
-    tokenized_chat = tokenizer.apply_chat_template(messages, tokenize=True, add_generation_prompt=True, return_tensors="pt")
-    outputs = model.generate(tokenized_chat, max_new_tokens=128)
-    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
-
-    # Lưu lại vào lịch sử chat
-    chat_entry = {
-        "user": user_input,
-        "bot": response,
-        "timestamp": datetime.now().strftime("%H:%M:%S")  # Thêm thời gian
-    }
-    session['history'].append(chat_entry)
-    session.modified = True  # Cập nhật session
-
-    return jsonify({"response": response, "timestamp": chat_entry["timestamp"]})
+    user_message = request.json['message']
+    
+    # Append user message to chat history
+    timestamp = datetime.datetime.now().strftime("%H:%M:%S")
+    chat_history.append({'timestamp': timestamp, 'user': user_message})
+
+    # Generate a response
+    input_text = user_message  # Modify this as needed for your model's input
+    inputs = tokenizer(input_text, return_tensors='pt')
+    outputs = model.generate(**inputs, max_new_tokens=128)
+    bot_response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+    # Append bot response to chat history
+    chat_history.append({'timestamp': timestamp, 'bot': bot_response})
+    
+    return jsonify({'timestamp': timestamp, 'response': bot_response})
 
 @app.route('/clear', methods=['POST'])
 def clear():
-    session['history'] = []  # Xóa lịch sử chat
-    return jsonify({"status": "ok"})
+    global chat_history
+    chat_history = []  # Clear chat history
+    return jsonify(success=True)
 
-if __name__ == "__main__":
-    app.run(debug=False)
+if __name__ == '__main__':
+    app.run(host='0.0.0.0', port=7860)  # Set host and port for Hugging Face Spaces