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app.py

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+
+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+model_name = "Qwen/Qwen2.5-1.5B-Instruct"
+
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(
+    model_name,
+    torch_dtype=torch.float16,
+    device_map="auto"
+)
+
+SYSTEM_PROMPT = """
+أنت مساعد ذكي تتحدث العربية بطلاقة.
+رد على المستخدم بالعربية الفصحى أو باللهجة السعودية حسب أسلوبه.
+"""
+
+def chat(prompt):
+    inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
+    outputs = model.generate(**inputs, max_new_tokens=200)
+    return tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+def respond(message, history):
+    full_prompt = SYSTEM_PROMPT + "\n"
+    for user, bot in history:
+        full_prompt += f"User: {user}\nBot: {bot}\n"
+    full_prompt += f"User: {message}\nBot:"
+    reply = chat(full_prompt)
+    return reply
+
+demo = gr.ChatInterface(respond, title="Arabic Chatbot")
+
+if __name__ == "__main__":
+    demo.launch()