Update app.py

app.py

@@ -1,29 +1,34 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
+import os
 
+# 1. Setup the Client 
+# Tip: Add your HF_TOKEN to the Space's "Variables and Secrets" settings 
+# so you don't have to hardcode it!
+HF_TOKEN = os.getenv("HF_TOKEN") 
+client = InferenceClient(model="Qwen/Qwen2.5-7B-Instruct", token=HF_TOKEN)
 
 def respond(
     message,
-    history: list[dict[str, str]],
+    history,
     system_message,
     max_tokens,
     temperature,
     top_p,
-    hf_token: gr.OAuthToken,
 ):
-    """
-    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)
+    
+    # Convert Gradio history to HF format
+    for val in history:
+        if val[0]:
+            messages.append({"role": "user", "content": val[0]})
+        if val[1]:
+            messages.append({"role": "assistant", "content": val[1]})
 
     messages.append({"role": "user", "content": message})
 
     response = ""
-
+    # Call the API
     for message in client.chat_completion(
         messages,
         max_tokens=max_tokens,
@@ -31,39 +36,21 @@ def respond(
         temperature=temperature,
         top_p=top_p,
     ):
-        choices = message.choices
-        token = ""
-        if len(choices) and choices[0].delta.content:
-            token = choices[0].delta.content
-
-        response += token
-        yield response
+        token = message.choices[0].delta.content
+        if token:
+            response += token
+            yield response
 
-
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
-chatbot = gr.ChatInterface(
+# 2. Setup the Interface
+demo = gr.ChatInterface(
     respond,
     additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
+        gr.Textbox(value="You are the CodeIgnite AI tutor. Help students learn coding by being encouraging and clear.", 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"),
     ],
 )
 
-with gr.Blocks() as demo:
-    with gr.Sidebar():
-        gr.LoginButton()
-    chatbot.render()
-
-
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()