Update app.py

app.py

@@ -0,0 +1,50 @@
+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM
+from typing import List, Tuple
+
+
+model_name = "Hawoly18/Adia_Llama3.1"
+
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+def respond(
+    message: str,
+    history: List[Tuple[str, str]],
+    system_message: str,
+    max_tokens: int,
+    temperature: float,
+    top_p: float,
+) -> str:
+    
+    prompt = system_message
+    for user_msg, assistant_msg in history:
+        prompt += f"\nUser: {user_msg}\nAssistant: {assistant_msg}"
+    prompt += f"\nUser: {message}\nAssistant:"
+
+    
+    inputs = tokenizer(prompt, return_tensors="pt")
+    outputs = model.generate(
+        **inputs,
+        max_length=max_tokens,
+        temperature=temperature,
+        top_p=top_p,
+        do_sample=True,
+    )
+    response = tokenizer.decode(outputs[0], skip_special_tokens=True).split("Assistant:")[-1].strip()
+    return response
+
+
+demo = gr.ChatInterface(
+    respond,
+    additional_inputs=[
+        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
+        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
+        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),  # Fixed syntax error
+        gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)"),
+    ],
+    title="Chatbot Interface"
+)
+
+if __name__ == "__main__":
+    demo.launch()