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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()
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