Update app.py

app.py

@@ -15,8 +15,8 @@ def respond(
     top_p,
     frequency_penalty,
     seed,
-    provider,  # Provider selection (moved up)
-    custom_model,  # Custom Model (moved down)
+    custom_model,
+    provider,
     model_search_term,
     selected_model
 ):
@@ -149,7 +149,15 @@ seed_slider = gr.Slider(
     label="Seed (-1 for random)"
 )
 
-# Provider selection with model links
+# Custom model box
+custom_model_box = gr.Textbox(
+    value="",
+    label="Custom Model",
+    info="(Optional) Provide a custom Hugging Face model path. Overrides any selected featured model.",
+    placeholder="meta-llama/Llama-3.3-70B-Instruct"
+)
+
+# Provider selection
 providers_list = [
     "hf-inference",  # Default Hugging Face Inference
     "cerebras",      # Cerebras provider
@@ -163,7 +171,6 @@ providers_list = [
     "openai"         # OpenAI compatible endpoints
 ]
 
-# Define provider selection with markdown links
 provider_radio = gr.Radio(
     choices=providers_list,
     value="hf-inference",
@@ -171,31 +178,6 @@ provider_radio = gr.Radio(
     info="Select which inference provider to use. Uses your Hugging Face PRO credits."
 )
 
-# Create markdown links for each provider
-provider_links = {
-    "hf-inference": "View all models hosted by [Hugging Face](https://huggingface.co/models?inference_provider=hf-inference&pipeline_tag=text-generation&sort=trending)",
-    "cerebras": "View all models hosted by [Cerebras](https://huggingface.co/models?inference_provider=cerebras&pipeline_tag=text-generation&sort=trending)",
-    "together": "View all models hosted by [Together AI](https://huggingface.co/models?inference_provider=together&pipeline_tag=text-generation&sort=trending)",
-    "sambanova": "View all models hosted by [SambaNova](https://huggingface.co/models?inference_provider=sambanova&pipeline_tag=text-generation&sort=trending)",
-    "novita": "View all models hosted by [Novita AI](https://huggingface.co/models?inference_provider=novita&pipeline_tag=text-generation&sort=trending)",
-    "cohere": "View all models hosted by [Cohere](https://huggingface.co/models?inference_provider=cohere&pipeline_tag=text-generation&sort=trending)",
-    "fireworks-ai": "View all models hosted by [Fireworks AI](https://huggingface.co/models?inference_provider=fireworks-ai&pipeline_tag=text-generation&sort=trending)",
-    "hyperbolic": "View all models hosted by [Hyperbolic](https://huggingface.co/models?inference_provider=hyperbolic&pipeline_tag=text-generation&sort=trending)",
-    "nebius": "View all models hosted by [Nebius](https://huggingface.co/models?inference_provider=nebius&pipeline_tag=text-generation&sort=trending)",
-    "openai": "View all models hosted by [OpenAI compatible endpoints](https://huggingface.co/models?inference_provider=openai&pipeline_tag=text-generation&sort=trending)",
-}
-
-# Provider links markdown
-provider_links_md = gr.Markdown(provider_links["hf-inference"])
-
-# Custom model box (moved down)
-custom_model_box = gr.Textbox(
-    value="",
-    label="Custom Model",
-    info="(Optional) Provide a custom Hugging Face model path. Overrides any selected featured model.",
-    placeholder="meta-llama/Llama-3.3-70B-Instruct"
-)
-
 # Model selection components
 model_search_box = gr.Textbox(
     label="Filter Models",
@@ -255,162 +237,43 @@ def set_custom_model_from_radio(selected):
     print(f"Featured model selected: {selected}")
     return selected
 
-# Update provider links when provider selection changes
-def update_provider_info(provider):
-    return provider_links[provider]
+# Create the Gradio interface
+demo = gr.ChatInterface(
+    fn=respond,
+    additional_inputs=[
+        system_message_box,
+        max_tokens_slider,
+        temperature_slider,
+        top_p_slider,
+        frequency_penalty_slider,
+        seed_slider,
+        provider_radio,     # Provider selection (moved up)
+        custom_model_box,   # Custom Model (moved down)
+        model_search_box,   # Model search box
+        featured_model_radio # Featured model radio
+    ],
+    fill_height=True,
+    chatbot=chatbot,
+    theme="Nymbo/Nymbo_Theme",
+)
+print("ChatInterface object created.")
 
-# Custom layout with Blocks
-with gr.Blocks(theme="Nymbo/Nymbo_Theme") as demo:
-    chatbot_ui = gr.Chatbot(height=600, show_copy_button=True, placeholder="Select a model and begin chatting", layout="panel")
-    
-    with gr.Row():
-        with gr.Column():
-            msg = gr.Textbox(
-                scale=4,
-                show_label=False,
-                placeholder="Enter text and press enter",
-                container=False,
-            )
-            submit_btn = gr.Button("Submit", variant="primary")
-    
-    with gr.Accordion("Additional Inputs", open=False):
-        system_message_box = gr.Textbox(value="", placeholder="You are a helpful assistant.", label="System Prompt")
-        
-        with gr.Row():
-            with gr.Column():
-                max_tokens_slider = gr.Slider(
-                    minimum=1,
-                    maximum=4096,
-                    value=512,
-                    step=1,
-                    label="Max tokens"
-                )
-                temperature_slider = gr.Slider(
-                    minimum=0.1,
-                    maximum=4.0,
-                    value=0.7,
-                    step=0.1,
-                    label="Temperature"
-                )
-                top_p_slider = gr.Slider(
-                    minimum=0.1,
-                    maximum=1.0,
-                    value=0.95,
-                    step=0.05,
-                    label="Top-P"
-                )
-            
-            with gr.Column():
-                frequency_penalty_slider = gr.Slider(
-                    minimum=-2.0,
-                    maximum=2.0,
-                    value=0.0,
-                    step=0.1,
-                    label="Frequency Penalty"
-                )
-                seed_slider = gr.Slider(
-                    minimum=-1,
-                    maximum=65535,
-                    value=-1,
-                    step=1,
-                    label="Seed (-1 for random)"
-                )
-        
-        # Provider selection section with markdown links
-        with gr.Group():
-            provider_radio = gr.Radio(
-                choices=providers_list,
-                value="hf-inference",
-                label="Inference Provider",
-                info="Select which inference provider to use. Uses your Hugging Face PRO credits."
-            )
-            provider_links_md = gr.Markdown(provider_links["hf-inference"])
-            
-            # Connect provider radio to update markdown links
-            provider_radio.change(
-                fn=update_provider_info,
-                inputs=provider_radio,
-                outputs=provider_links_md
-            )
-        
-        # Custom model box (moved below provider selection)
-        custom_model_box = gr.Textbox(
-            value="",
-            label="Custom Model",
-            info="(Optional) Provide a custom Hugging Face model path. Overrides any selected featured model.",
-            placeholder="meta-llama/Llama-3.3-70B-Instruct"
-        )
-        
-        # Model filter and selection
-        model_search_box = gr.Textbox(
-            label="Filter Models",
-            placeholder="Search for a featured model...",
-            lines=1
-        )
-        
-        featured_model_radio = gr.Radio(
-            label="Select a model below",
-            choices=models_list,
-            value="meta-llama/Llama-3.3-70B-Instruct",
-            interactive=True
-        )
-    
-    # Connect model filter and selection events
+with demo:
+    # Connect the model filter to update the radio choices
     model_search_box.change(
         fn=filter_models,
         inputs=model_search_box,
         outputs=featured_model_radio
     )
-    
+    print("Model search box change event linked.")
+
+    # Connect the featured model radio to update the custom model box
     featured_model_radio.change(
         fn=set_custom_model_from_radio,
         inputs=featured_model_radio,
         outputs=custom_model_box
     )
-    
-    # Chat history state
-    history_state = gr.State([])
-    
-    # Connect chat functionality
-    submit_btn.click(
-        fn=respond,
-        inputs=[
-            msg,
-            history_state,
-            system_message_box,
-            max_tokens_slider,
-            temperature_slider,
-            top_p_slider,
-            frequency_penalty_slider,
-            seed_slider,
-            provider_radio,     # Provider selection (moved up)
-            custom_model_box,   # Custom Model (moved down)
-            model_search_box,
-            featured_model_radio
-        ],
-        outputs=[chatbot_ui, history_state],
-        show_progress=True,
-    )
-    
-    msg.submit(
-        fn=respond,
-        inputs=[
-            msg,
-            history_state,
-            system_message_box,
-            max_tokens_slider,
-            temperature_slider,
-            top_p_slider,
-            frequency_penalty_slider,
-            seed_slider,
-            provider_radio,     # Provider selection (moved up)
-            custom_model_box,   # Custom Model (moved down)
-            model_search_box,
-            featured_model_radio
-        ],
-        outputs=[chatbot_ui, history_state],
-        show_progress=True,
-    )
+    print("Featured model radio button change event linked.")
 
 print("Gradio interface initialized.")