BitsofPaper/Risk_Thinking

1#from unicodedata import numeric2import gradio as gr3import pandas as pd4import numpy as np5from joblib import load6 7def predict_price(vol_moving_avg, adj_close_rolling_med):8    9    try:10        vol_moving_avg = float(vol_moving_avg)11        adj_close_rolling_med = float(adj_close_rolling_med)12    except Exception:13        return "Invalid input format. Please provide a numeric value."14    15    # Load the ML model and scaler16    model = load("model.joblib")17    scaler = load('scaler.joblib')18 19    # Create dict array from parameters20    data={21       "vol_moving_avg":[vol_moving_avg],22       "adj_close_rolling_med":[adj_close_rolling_med]23    }24 25    xin=pd.DataFrame(data)26    X = scaler.transform(xin)27    price=model.predict(X)28    return int(price[0])29 30ui=gr.Interface(31    fn=predict_price,32    inputs=[ 33        gr.components.Textbox(placeholder="vol_moving_avg", label="Volume Moving Avg"),34        gr.components.Textbox(placeholder="adj_close_rolling_med", label="Adj Close Rolling Mean")35    ],36    title="Risk Thinking Volume Predictor",37    outputs=[gr.components.Textbox(label="Volume")]38)39 40if __name__=="__main__":41    ui.launch()