Update app.py

app.py

@@ -2,46 +2,60 @@ import gradio as gr
 from huggingface_hub import InferenceClient
 from typing import List, Tuple
 
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
+# Initialize the InferenceClient
+client = InferenceClient("microsoft/phi-4")
 
+# Define the system message
+system_message = "You're an advanced AI assistant designed to engage in friendly and informative conversations. Your role is to respond to user queries with helpful, clear, and concise answers, while maintaining a conversational tone. You can provide advice, explanations, and solutions based on user input.
+
+"
+
+# Define the response function
 def respond(
     message: str,
     history: List[Tuple[str, str]],
-    system_message: str,
     max_tokens: int,
     temperature: float,
     top_p: float,
 ):
+    # Construct the messages for the model, adding the system prompt at the beginning
     messages = [{"role": "system", "content": system_message}]
-
-    # Add conversation history to the messages
     for val in history:
         if val[0]:
             messages.append({"role": "user", "content": val[0]})
         if val[1]:
             messages.append({"role": "assistant", "content": val[1]})
 
-    # Append the new message to the conversation
+    # Append the new user message
     messages.append({"role": "user", "content": message})
 
-    response = ""
-
-    # Stream the response from the model
-    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
+    try:
+        response = ""
+        # Stream the response from the model
+        for msg in client.chat_completion(
+            messages,
+            max_tokens=max_tokens,
+            stream=True,
+            temperature=temperature,
+            top_p=top_p,
+        ):
+            if 'choices' in msg and len(msg['choices']) > 0:
+                token = msg['choices'][0].get('delta', {}).get('content', '')
+                if token:
+                    response += token
+                    yield response
+            else:
+                print("Error: API response did not contain expected data.")
+                yield "Error: Could not process the request. Please try again."
+    except Exception as e:
+        print(f"An error occurred: {e}")
+        yield "Error: An unexpected error occurred while processing your request."
 
+# Define the Gradio Interface
 demo = gr.Interface(
     fn=respond,
     inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
+        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)"),
@@ -50,5 +64,6 @@ demo = gr.Interface(
     outputs=[gr.Textbox(label="Response")]
 )
 
+# Launch the Gradio interface
 if __name__ == "__main__":
     demo.launch()