Update app.py

app.py

@@ -1,52 +1,10 @@
 import gradio as gr
-import json
 
-# Function to query the model
-def query_model(prompt):
-    # Simulate the response (replace with actual model logic)
-    response = f"Python function for {prompt}"
-    
-    # Format for Chatbot component
-    chatbot_messages = [
-        ["user", prompt],
-        ["assistant", response]
-    ]
-    
-    return chatbot_messages, json.dumps({
-        "status": "success",
-        "prompt": prompt,
-        "response": response,
-        "model": "open-r1/OlympicCoder-7B"
-    })
-
-# Create the Gradio interface
-with gr.Blocks() as demo:
-    with gr.Row():
-        with gr.Column(scale=3):
-            chatbot = gr.Chatbot(height=500)
-            with gr.Row():
-                with gr.Column(scale=8):
-                    msg = gr.Textbox(label="Message", placeholder="Type your message here", container=False)
-                with gr.Column(scale=1, min_width=50):
-                    submit = gr.Button("Send")
-            clear = gr.Button("Clear")
-        
-        with gr.Column(scale=1, visible=False) as api_column:
-            # Hidden API interface
-            api_input = gr.Textbox(label="API Input")
-            api_output = gr.Textbox(label="API Output")
-            api_button = gr.Button("API Call")
-    
-    # Set up event handlers
-    submit.click(fn=query_model, inputs=[msg], outputs=[chatbot], queue=True)
-    msg.submit(fn=query_model, inputs=[msg], outputs=[chatbot], queue=True)
-    clear.click(lambda: None, None, chatbot, queue=False)
-    
-    # API endpoint
-    api_button.click(fn=lambda x: query_model(x)[1], inputs=[api_input], outputs=[api_output])
-
-# Launch with debug info
-demo.launch(
-    debug=True,
-    show_api=True  # This exposes the API docs
-)
+with gr.Blocks(fill_height=True) as demo:
+    with gr.Sidebar():
+        gr.Markdown("# Inference Provider")
+        gr.Markdown("This Space showcases the open-r1/OlympicCoder-7B model, served by the featherless-ai API. Sign in with your Hugging Face account to use this API.")
+        button = gr.LoginButton("Sign in")
+    gr.load("models/open-r1/OlympicCoder-7B", accept_token=button, provider="featherless-ai")
+    
+demo.launch()