Update app.py

app.py

@@ -1,8 +1,7 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
-import json
 
-# Initialize the client with the token
+# Initialize the client
 client = InferenceClient(
     model="davnas/Italian_Cousine_2.1",
     headers={"Content-Type": "application/json"}
@@ -10,31 +9,19 @@ client = InferenceClient(
 
 def respond(message, history, system_message, max_tokens, temperature, top_p):
     # Format the prompt including history and system message
-    conversation = []
+    prompt = ""
     
     # Add system message if provided
     if system_message:
-        conversation.append({"role": "system", "content": system_message})
+        prompt += f"{system_message}\n"
     
     # Add conversation history
-    for user_msg, assistant_msg in history:
-        conversation.append({"role": "user", "content": user_msg})
-        conversation.append({"role": "assistant", "content": assistant_msg})
+    for msg in history:
+        if isinstance(msg, list) and len(msg) == 2:
+            prompt += f"User: {msg[0]}\nAssistant: {msg[1]}\n"
     
     # Add current message
-    conversation.append({"role": "user", "content": message})
-    
-    # Convert conversation to prompt format
-    prompt = ""
-    for msg in conversation:
-        if msg["role"] == "system":
-            prompt += f"{msg['content']}\n"
-        elif msg["role"] == "user":
-            prompt += f"User: {msg['content']}\n"
-        elif msg["role"] == "assistant":
-            prompt += f"Assistant: {msg['content']}\n"
-    
-    prompt += "Assistant:"
+    prompt += f"User: {message}\nAssistant:"
     
     # Prepare parameters for text generation
     parameters = {
@@ -57,7 +44,7 @@ def respond(message, history, system_message, max_tokens, temperature, top_p):
     except Exception as e:
         yield f"Error: {str(e)}"
 
-# Create the interface with message type
+# Create the interface
 demo = gr.ChatInterface(
     respond,
     additional_inputs=[
@@ -86,8 +73,7 @@ demo = gr.ChatInterface(
             step=0.05,
             label="Top-p (nucleus sampling)"
         ),
-    ],
-    chatbot=gr.Chatbot(type="messages")  # Use messages format instead of tuples
+    ]
 )
 
 if __name__ == "__main__":