Update app.py

app.py

@@ -1,10 +1,6 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
 
-# Initialize the client for a HF-hosted model
-# No token needed when running inside a Space owned by a Team org
-client = InferenceClient(model="meta-llama/Llama-3.1-8B-Instruct")
-
 
 def respond(
     message,
@@ -13,32 +9,40 @@ def respond(
     max_tokens,
     temperature,
     top_p,
+    hf_token: gr.OAuthToken,
 ):
     """
-    Generate responses using HF-hosted Llama 3.1 model.
-    This version avoids Novita/Groq routing and does not require tokens.
+    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(token=hf_token.token, model="openai/gpt-oss-20b")
+
     messages = [{"role": "system", "content": system_message}]
+
     messages.extend(history)
+
     messages.append({"role": "user", "content": message})
 
     response = ""
-    # Stream responses using the new chat.completions API
-    for message_chunk in client.chat.completions.create(
-        messages=messages,
+
+    for message in client.chat_completion(
+        messages,
         max_tokens=max_tokens,
+        stream=True,
         temperature=temperature,
         top_p=top_p,
-        stream=True
     ):
-        delta = message_chunk.choices[0].delta
-        if delta and delta.content:
-            token = delta.content
-            response += token
-            yield response
+        choices = message.choices
+        token = ""
+        if len(choices) and choices[0].delta.content:
+            token = choices[0].delta.content
+
+        response += token
+        yield response
 
 
-# Define the Gradio Chat Interface
+"""
+For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
+"""
 chatbot = gr.ChatInterface(
     respond,
     type="messages",
@@ -56,11 +60,11 @@ chatbot = gr.ChatInterface(
     ],
 )
 
-# Build the Gradio Blocks interface with optional login button
 with gr.Blocks() as demo:
     with gr.Sidebar():
         gr.LoginButton()
     chatbot.render()
 
+
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()