Update app.py

app.py

@@ -75,24 +75,26 @@ def get_recent_models(min_likes, days_ago, filter_string, search_string):
     return df
 
 # Define the Gradio interface
-def launch_interface():
-    iface = gr.Interface(
-        fn=get_recent_models,
-        inputs=[
-            gr.Slider(minimum=1, maximum=100, step=1, value=5, label="Minimum Likes"),
-            gr.Slider(minimum=1, maximum=30, step=1, value=3, label="Days Ago"),
-            gr.Text(label="Filter", max_lines=1),
-            gr.Text(label="Search", max_lines=1)
-        ],
-        outputs=gr.DataFrame(
+with gr.Blocks() as demo:
+    gr.Markdown("# Model Drops Tracker 🚀")
+    gr.Markdown("Overwhelmed by the rapid pace of model releases? 😅 You're not alone! That's exactly why I built this tool. Easily filter recent models from the Hub by setting a minimum number of likes and the number of days since their release. Click on a model to see its card. Use `;` to split filter and search")
+    with gr.Row():
+        likes_slider = gr.Slider(minimum=1, maximum=100, step=1, value=5, label="Minimum Likes")
+        days_slider = gr.Slider(minimum=1, maximum=30, step=1, value=3, label="Days Ago")
+    with gr.Row():
+        filter_text = gr.Text(label="Filter", max_lines=1)
+        search_text = gr.Text(label="Search", max_lines=1)
+    
+    btn = gr.Button("Run")
+    
+    with gr.Column():
+        df = gr.DataFrame(
             headers=["Model ID", "Likes", "Creation Date", "Task"],
             wrap=True,
             datatype=["html", "number", "str"],
-        ),
-        title="Model Drops Tracker 🚀",
-        description="Overwhelmed by the rapid pace of model releases? 😅 You're not alone! That's exactly why I built this tool. Easily filter recent models from the Hub by setting a minimum number of likes and the number of days since their release. Click on a model to see its card. Use `;` to split filter and search"
-    )
-    iface.launch()
+        )
+    
+    btn.click(fn=get_recent_models, inputs=[likes_slider, days_slider, filter_text, search_text], outputs=df)
 
 if __name__ == "__main__":
-    launch_interface()
+    demo.launch()