init

app.py

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+import gradio as gr
+from train import WeatherPredictor
+
+# Initialize the predictor
+predictor = WeatherPredictor('basel-weather.csv')
+predictor.load_model('weather_predictor.pth')
+
+@spaces.GPU
+def predict_weather(input_date):
+    result = predictor.predict(input_date)
+    return result['temp'], result['precip'], result['snow'], result['windspeed']
+
+# Create Gradio interface
+app = gr.Interface(
+    fn=predict_weather,
+    inputs=gr.Textbox(label="Enter Date (dd/mm/yy)"),
+    outputs=[
+        gr.Textbox(label="Temperature"),
+        gr.Textbox(label="Precipitation"),
+        gr.Textbox(label="Snow"),
+        gr.Textbox(label="Windspeed")
+    ],
+    title="Weather Predictor",
+    description="Enter a date to get weather predictions."
+)
+
+# Launch the interface
+if __name__ == "__main__":
+    app.launch()

requirements.txt

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+pandas==2.1.4
+scikit-learn==1.3.2
+numpy==1.26.2
+gradio
+torch==2.1.2

weather_predictor.pth

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+version https://git-lfs.github.com/spec/v1
+oid sha256:c67235436c311635e3c066447935a1b1a7cb3904628f5a8299eb82d24dc298d2
+size 3756