Update app.py

app.py

@@ -133,7 +133,7 @@ demo = gr.ChatInterface(
         ),
         gr.Slider(
             minimum=-1,
-            maximum=65535,  # Arbitrary upper limit for demonstration
+            maximum=65535,
             value=-1,
             step=1,
             label="Seed (-1 for random)"
@@ -150,6 +150,51 @@ demo = gr.ChatInterface(
 )
 print("Gradio interface initialized.")
 
+# --------------------------------------------------------
+# NEW FEATURE: "Featured Models" Accordion with Filtering
+# Adapted from Serverless-ImgGen-Hub's approach
+# --------------------------------------------------------
+with demo:
+    with gr.Accordion("Featured Models", open=False):
+        # Textbox to search/filter models
+        model_search = gr.Textbox(
+            label="Filter Models",
+            placeholder="Search for a featured model...",
+            lines=1
+        )
+        
+        # For demonstration purposes, here is a sample list of possible text-generation models
+        models_list = [
+            "meta-llama/Llama-3.3-70B-Instruct",
+            "bigscience/bloomz-7b1",
+            "OpenAssistant/oasst-sft-1-pythia-12b",
+            "OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5",
+            "tiiuae/falcon-7b-instruct",
+            "OpenAI/gpt-3.5-turbo",
+            "OpenAI/gpt-4-32k",
+            "meta-llama/Llama-2-13B-chat-hf",
+            "meta-llama/Llama-2-70B-chat-hf",
+        ]
+        
+        # Radio buttons to display and select from the featured models
+        # This won't directly override the "Custom Model" field, but you can copy it from here
+        featured_model = gr.Radio(
+            label="Select a model below",
+            choices=models_list,
+            value="meta-llama/Llama-3.3-70B-Instruct",
+            interactive=True
+        )
+
+        # Filtering function to update model list based on search input
+        def filter_models(search_term):
+            # Filter the list by checking if the search term is in each model name
+            filtered = [m for m in models_list if search_term.lower() in m.lower()]
+            return gr.update(choices=filtered)
+
+        # When the user types in the search box, we update the featured_model radio choices
+        model_search.change(filter_models, inputs=model_search, outputs=featured_model)
+
+
 if __name__ == "__main__":
     print("Launching the demo application.")
     demo.launch()