Update app.py

app.py

@@ -1,48 +1,33 @@
 import torch
+from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
 import gradio as gr
-from transformers import AutoTokenizer, AutoModelForCausalLM, TextStreamer
 
-# اختار نموذج 7B من Hugging Face - مثال:
-model_name = "NousResearch/Nous-Hermes-2-Mistral-7B"
+model_name = "mistralai/Mistral-7B-Instruct-v0.2"
 
 tokenizer = AutoTokenizer.from_pretrained(model_name)
 model = AutoModelForCausalLM.from_pretrained(
-    model_name,
-    torch_dtype=torch.float16,
+    model_name, 
+    torch_dtype=torch.float16, 
     device_map="auto"
 )
 
-streamer = TextStreamer(tokenizer)
-
-# system prompt
-system_prompt = """<|system|>
-Your name is Friday, an advanced AI chatbot developed by Assem Sabry. 
-Assem Sabry is a 17-year-old artificial intelligence engineer from Egypt with multiple AI projects and chatbots.
-
-Instructions:
-- Always be helpful, polite, and professional.
-- When asked about your identity, introduce yourself as "Friday, an AI assistant created by Assem Sabry".
-- Answer in fluent English with clear and informative responses.
-- Keep your tone friendly and intelligent.
-</s>
-"""
-
-def chat(user_input, history=[]):
-    # إعداد الحوار بالكامل
-    full_prompt = system_prompt
-    for user_msg, bot_msg in history:
-        full_prompt += f"<|user|>\n{user_msg.strip()}\n<|assistant|>\n{bot_msg.strip()}\n</s>\n"
-    full_prompt += f"<|user|>\n{user_input.strip()}\n<|assistant|>"
-
-    inputs = tokenizer(full_prompt, return_tensors="pt").to(model.device)
-    outputs = model.generate(**inputs, max_new_tokens=512, pad_token_id=tokenizer.eos_token_id)
-
-    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+# برومبت ثابت يوضع قبل كل رسالة
+system_prompt = (
+    "You are Friday, a helpful, smart, and honest AI chatbot created by Assem Sabry. "
+    "Assem is a talented 17-year-old AI engineer from Egypt who builds advanced AI systems and chatbots. "
+    "You always respond clearly and helpfully, while keeping answers professional and accurate."
+)
 
-    # استخراج آخر رد فقط
-    response = response.split("<|assistant|>")[-1].strip().split("</s>")[0].strip()
+def respond(message, history=[]):
+    messages = [{"role": "system", "content": system_prompt}]
+    for user, bot in history:
+        messages.append({"role": "user", "content": user})
+        messages.append({"role": "assistant", "content": bot})
+    messages.append({"role": "user", "content": message})
 
-    history.append((user_input, response))
-    return response, history
+    inputs = tokenizer.apply_chat_template(messages, return_tensors="pt").to(model.device)
+    outputs = model.generate(inputs, max_new_tokens=512, do_sample=True, temperature=0.7)
+    reply = tokenizer.decode(outputs[0], skip_special_tokens=True).split("assistant")[-1].strip()
+    return reply
 
-gr.ChatInterface(fn=chat, title="Friday AI - by Assem Sabry").launch(share=True)
+gr.Interface(fn=respond, inputs="text", outputs="text", title="Friday Chatbot").launch()