Update app.py

app.py

@@ -1,27 +1,38 @@
 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
-"""
+# Initialize the InferenceClient
 client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
 
-
 def respond(
-    message,
+    message: str,
     history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
+    system_message: str,
+    max_tokens: int,
+    temperature: float,
+    top_p: float,
+) -> str:
+    """
+    Generate a response based on the user's message and chat history.
+
+    Args:
+        message (str): The user's message.
+        history (list[tuple[str, str]]): The chat history.
+        system_message (str): The system message.
+        max_tokens (int): The maximum number of tokens in the response.
+        temperature (float): The temperature for sampling.
+        top_p (float): The top-p (nucleus) sampling value.
+
+    Returns:
+        str: The generated response.
+    """
     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})
 
@@ -35,13 +46,10 @@ def respond(
         top_p=top_p,
     ):
         token = message.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
-"""
+# Create the Gradio ChatInterface
 demo = gr.ChatInterface(
     respond,
     additional_inputs=[
@@ -56,8 +64,9 @@ demo = gr.ChatInterface(
             label="Top-p (nucleus sampling)",
         ),
     ],
+    theme="default",  # Apply the default theme
+    css=".gradio-container {background-color: #E0F7FA;}"  # Set a light blue background
 )
 
-
 if __name__ == "__main__":
     demo.launch()