Create app.py

app.py

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+import gradio as gr
+
+import hopsworks
+import joblib
+import datetime
+import yfinance as yf
+from pandas_datareader import data as pdr
+
+project = hopsworks.login()
+fs = project.get_feature_store()
+
+mr = project.get_model_registry()
+model = mr.get_model("btc_model", version=1)
+model_dir = model.download()
+model = joblib.load(model_dir + "/btc_model.pkl")
+
+
+def predict():
+    today = get_date()
+
+    yf.pdr_override()
+    btc_df = pdr.get_data_yahoo('BTC-USD', start=today)
+    btc_df.drop(columns=['Adj Close'], inplace=True)
+
+    btc_df['Dayofyear'] = btc_df.index.dayofyear
+    btc_df['Month'] = btc_df.index.month
+    btc_df['Year'] = btc_df.index.year
+    # btc_df['Date'] = btc_df.index.strftime('%Y-%m-%d %H:%M:%S')
+
+    price = model.predict(btc_df.drop(columns=['close']))[0]
+    return [today, price]
+
+
+def get_date():
+    today = datetime.datetime.today()
+    return today.date()
+
+
+demo = gr.Interface(
+    fn=predict,
+    title="Bitcoin Closing Price Prediction",
+    description="Daily Bitcoin closing price prediction",
+    allow_flagging="never",
+    inputs=[],
+    outputs=[
+        gr.Textbox(label="Date"),
+        gr.Textbox(label="Predicted Closing price"),
+    ]
+)
+
+demo.launch()