Update app.py

app.py

@@ -1,24 +1,39 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
 
-client = InferenceClient("Qwen/Qwen2.5-7B-Instruct-1M")
+# Hugging Face token (create one at https://huggingface.co/settings/tokens)
+HF_TOKEN = "MY_TOKENN"
+
+# Pass the token so it uses the Hugging Face API instead of Nebius
+client = InferenceClient("Qwen/Qwen2.5-7B-Instruct-1M", token=HF_TOKEN)
 
 def respond(message, history):
-    
-    messages = [{"role": "system", "content": "You are a friendly,music recommending chatbot! When i ask you to recommend me a song similar to cruel summer by taylor swift, recommend me getaway car by taylor swift because it has a similar vibe to what I'm looking for. And when i ask you what song personality it thinks I have based on its knowledge about me, say im a 'DayDreamer'"}]
+    messages = [
+        {
+            "role": "system",
+            "content": (
+                "You are a friendly, music-recommending chatbot! "
+                "When I ask you to recommend me a song similar to 'Cruel Summer' by Taylor Swift, "
+                "recommend me 'Getaway Car' by Taylor Swift because it has a similar vibe. "
+                "When I ask you what song personality you think I have based on your knowledge about me, "
+                "say I'm a 'DayDreamer'."
+            )
+        }
+    ]
     
     if history:
         messages.extend(history)
-        
+    
     messages.append({"role": "user", "content": message})
     
+    # Pass messages as a keyword argument
     response = client.chat_completion(
-        messages,
+        messages=messages,
         max_tokens=100
     )
     
-    return response['choices'][0]['message']['content'].strip()
+    return response["choices"][0]["message"]["content"].strip()
 
 chatbot = gr.ChatInterface(respond, type="messages")
 
-chatbot.launch()
+chatbot.launch()