commit

app.py

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+import gradio as gr
+from huggingface_hub import HfApi
+from datetime import datetime, timedelta
+import pandas as pd
+
+# Initialize the Hugging Face API
+api = HfApi()
+
+def get_recent_models(min_likes, days_ago):
+    # Get the current date and date from `days_ago` days ago
+    today = datetime.utcnow().replace(tzinfo=None)
+    start_date = (today - timedelta(days=days_ago)).replace(tzinfo=None)
+    
+    # Initialize an empty list to store the filtered models
+    recent_models = []
+    
+    # Use a generator to fetch models in batches, sorted by likes in descending order
+    for model in api.list_models(sort="likes", direction=-1):
+        if model.likes > 10:
+            if hasattr(model, "created_at") and model.created_at:
+                # Ensure created_at is offset-naive
+                created_at_date = model.created_at.replace(tzinfo=None)
+                if created_at_date >= start_date and model.likes >= min_likes:
+                    recent_models.append({
+                        "Model ID": f'<a href="https://huggingface.co/{model.modelId}" target="_blank">{model.modelId}</a>',
+                        "Likes": model.likes,
+                        "Creation Date": model.created_at.strftime("%Y-%m-%d %H:%M")
+                    })
+        else:
+            # Since the models are sorted by likes in descending order,
+            # we can stop once we hit a model with 10 or fewer likes
+            break
+    
+    # Convert the list of dictionaries to a pandas DataFrame
+    df = pd.DataFrame(recent_models)
+    
+    return df
+
+# Define the Gradio interface
+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.")
+    with gr.Row():
+        likes_slider = gr.Slider(minimum=0, maximum=100, step=10, value=10, label="Minimum Likes")
+        days_slider = gr.Slider(minimum=1, maximum=7, step=1, value=1, label="Days Ago")
+    
+    btn = gr.Button("Run")
+    
+    with gr.Column():
+        df = gr.DataFrame(
+            headers=["Model ID", "Likes", "Creation Date"],
+            wrap=True,
+            datatype=["html", "number", "str"],
+        )
+    
+    btn.click(fn=get_recent_models, inputs=[likes_slider, days_slider], outputs=df)
+
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

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+gradio
+huggingface_hub
+pytz
+pandas