Update app.py

app.py

@@ -3,16 +3,14 @@ import sambanova_gradio
 
 # Function to load the selected model
 def load_model(model_choice):
-    model = gr.load(
-        name=model_choice,
-        src=sambanova_gradio.registry
-    )
+    # Directly load the model without using the ChatInterface
+    model = sambanova_gradio.registry(model_choice)
     return model
 
-# Define a function to handle the user input and return a response
+# Function to generate response
 def generate_response(model_choice, user_input):
     model = load_model(model_choice)
-    output = model.predict(user_input)
+    output = model(user_input)  # Assuming model is callable like a function
     return output
 
 # Available model choices
@@ -24,40 +22,39 @@ model_choices = [
     "Meta-Llama-3.1-70B-lnstruct"
 ]
 
-# Create Gradio interface
+# Gradio interface
 with gr.Blocks() as demo:
     gr.Markdown("# Meta-Llama Model Selector")
-    
-    # Dropdown for selecting the model
+
+    # Dropdown for model selection
     model_choice = gr.Dropdown(
-        choices=model_choices, 
+        choices=model_choices,
         label="Choose a Meta-Llama Model",
-        value="Meta-Llama-3.2-3B-Instruct"  # default value
+        value="Meta-Llama-3.2-3B-Instruct"  # Default selected model
     )
-    
+
     # Textbox for user input
     input_box = gr.Textbox(
         label="Input",
         placeholder="Ask a question..."
     )
-    
-    # Output for the model's response
+
+    # Output textbox for displaying the response
     output_box = gr.Textbox(label="Output")
-    
-    # Button to generate the output
+
+    # Button to generate a response
     generate_button = gr.Button("Generate Response")
-    
-    # Add example inputs
+
+    # Example inputs
     examples = gr.Examples(
-        examples=["Explain quantum gravity to a 5-year old.", 
-                  "How many R are there in the word Strawberry?"],
+        examples=["Explain quantum gravity to a 5-year-old.", "How many R are there in the word Strawberry?"],
         inputs=input_box
     )
-    
-    # Action when button is clicked
+
+    # Define button click action
     generate_button.click(
-        fn=generate_response, 
-        inputs=[model_choice, input_box], 
+        fn=generate_response,
+        inputs=[model_choice, input_box],
         outputs=output_box
     )