Update app.py

app.py

@@ -4,33 +4,65 @@ from huggingface_hub import InferenceClient
 client = InferenceClient("Grandediw/lora_model")
 
 def respond(message, history, system_message, max_tokens, temperature, top_p):
-    # Build the prompt from system_message and the conversation history
-    # history is a list of (user_message, assistant_message) tuples
-    prompt = system_message.strip() + "\n\n"
-
+    # Convert tuple-based history to messages if needed
+    messages = [{"role": "system", "content": system_message}]
     for user_msg, assistant_msg in history:
         if user_msg:
-            prompt += f"User: {user_msg}\n"
+            messages.append({"role": "user", "content": user_msg})
         if assistant_msg:
-            prompt += f"Assistant: {assistant_msg}\n"
-    
-    # Add the latest user message
-    prompt += f"User: {message}\nAssistant:"
+            messages.append({"role": "assistant", "content": assistant_msg})
+    messages.append({"role": "user", "content": message})
 
     response = ""
-    # Use text_generation instead of chat_completion
-    for partial in client.text_generation(
-        prompt=prompt,
-        max_new_tokens=max_tokens,
+    for partial in client.chat_completion(
+        messages,
+        max_tokens=max_tokens,
+        stream=True,
         temperature=temperature,
         top_p=top_p,
-        stream=True
     ):
-        # partial is a TextGenerationStreamResponse
-        token = partial.token.text  # Extract the generated token text
+        token = partial.choices[0].delta.content
         response += token
         yield response
 
+with gr.Blocks(title="Enhanced LORA Chat Interface") as demo:
+    gr.Markdown(
+        """
+        # LORA Chat Assistant
+        Welcome! This is a demo of a LORA-based Chat Assistant.  
+        Start by entering your prompt below.
+        """
+    )
+
+    with gr.Row():
+        # System message and other parameters
+        with gr.Column():
+            system_message = gr.Textbox(
+                value="You are a friendly Chatbot.",
+                label="Initial Behavior (System Message)",
+                lines=3,
+                placeholder="Describe how the assistant should behave..."
+            )
+            max_tokens = gr.Slider(
+                minimum=1, maximum=2048, value=512, step=1,
+                label="Max new tokens"
+            )
+            temperature = gr.Slider(
+                minimum=0.1, maximum=4.0, value=0.7, step=0.1,
+                label="Temperature"
+            )
+            top_p = gr.Slider(
+                minimum=0.1, maximum=1.0, value=0.95, step=0.05,
+                label="Top-p (nucleus sampling)"
+            )
+
+        # Create the chat interface using tuple format
+        # Note: `type='tuple'` preserves the (user, assistant) tuple format.
+        chat = gr.ChatInterface(
+            fn=respond,
+            additional_inputs=[system_message, max_tokens, temperature, top_p],
+            type='tuples'
+        )
 
 if __name__ == "__main__":
     demo.launch()