Update app.py

app.py

@@ -1,86 +1,68 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
 
-"""
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-"""
 client = InferenceClient("Grandediw/lora_model")
 
-def respond(message, history: list[tuple[str, str]], system_message, max_tokens, temperature, top_p):
+def respond(message, history, system_message, max_tokens, temperature, top_p):
+    # Convert tuple-based history to messages if needed
     messages = [{"role": "system", "content": system_message}]
-
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
-
+    for user_msg, assistant_msg in history:
+        if user_msg:
+            messages.append({"role": "user", "content": user_msg})
+        if assistant_msg:
+            messages.append({"role": "assistant", "content": assistant_msg})
     messages.append({"role": "user", "content": message})
 
     response = ""
-
-    for message in client.chat_completion(
+    for partial in client.chat_completion(
         messages,
         max_tokens=max_tokens,
         stream=True,
         temperature=temperature,
         top_p=top_p,
     ):
-        token = message.choices[0].delta.content
+        token = partial.choices[0].delta.content
         response += token
         yield response
 
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
 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 in the chat box below.
+        Start by entering your prompt below.
         """
     )
 
     with gr.Row():
-        # Left column: Chat interface
-        with gr.Column():
-            chat = gr.ChatInterface(
-                fn=respond,
-                additional_inputs=[]
-            )
-        
-        # Right column: Settings and System Message
+        # System message and other parameters
         with gr.Column():
-            gr.Markdown("### Configuration")
             system_message = gr.Textbox(
                 value="You are a friendly Chatbot.",
                 label="Initial Behavior (System Message)",
                 lines=3,
                 placeholder="Describe how the assistant should behave..."
             )
-
-            with gr.Accordion("Advanced Settings", open=False):
-                max_tokens = gr.Slider(
-                    minimum=1, maximum=2048, value=512, step=1,
-                    label="Max new tokens",
-                    info="Controls the maximum number of tokens in the response."
-                )
-                temperature = gr.Slider(
-                    minimum=0.1, maximum=4.0, value=0.7, step=0.1,
-                    label="Temperature",
-                    info="Higher values produce more random outputs."
-                )
-                top_p = gr.Slider(
-                    minimum=0.1, maximum=1.0, value=0.95, step=0.05,
-                    label="Top-p (nucleus sampling)",
-                    info="Limits the tokens considered to the top portion by cumulative probability."
-                )
-
-            # Link parameters to the chat interface's function
-            chat.configure(
-                additional_inputs=[system_message, max_tokens, temperature, top_p]
+            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='tuple'
+        )
 
 if __name__ == "__main__":
     demo.launch()