Update app.py

app.py

@@ -1,12 +1,9 @@
 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 with the specified model
 client = InferenceClient("WhiteRabbitNeo/Llama-3.1-WhiteRabbitNeo-2-70B")
 
-
 def respond(
     message,
     history: list[tuple[str, str]],
@@ -27,38 +24,46 @@ def respond(
 
     response = ""
 
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        token = message['choices'][0]['delta']['content']  # check for correct key names
+    try:
+        for message in client.chat_completion(
+            messages,
+            max_tokens=max_tokens,
+            stream=True,
+            temperature=temperature,
+            top_p=top_p,
+        ):
+            token = message['choices'][0]['delta']['content']
+            response += token
+            yield response
+    except Exception as e:
+        yield f"An error occurred: {str(e)}"
 
-        response += token
-        yield response
+# Define the system message with a cybersecurity focus
+system_message = (
+    "You are a cybersecurity expert chatbot, providing assistance on penetration testing, ransomware analysis, and code classification. "
+    "Your responses should be concise, accurate, and tailored to cybersecurity professionals."
+)
 
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
+# Create the Gradio interface with dark/light mode toggle
 demo = gr.Interface(
     fn=respond,
     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.Textbox(value=system_message, 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"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        ),
+        gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (Nucleus Sampling)"),
+        gr.Checkbox(label="Dark Mode", value=False),  # Dark mode toggle
     ],
     outputs=[gr.Textbox()],
+    theme="dark",  # Default theme
 )
 
+def toggle_theme(dark_mode):
+    """Toggle between dark and light themes based on user input."""
+    return "dark" if dark_mode else "light"
+
+# Update the theme based on the checkbox value
+demo.change(fn=toggle_theme, inputs=[demo.inputs[4]], outputs=[demo])
 
 if __name__ == "__main__":
     demo.launch()