Update app.py

app.py

@@ -1,4 +1,3 @@
-# app.py
 import pandas as pd
 import numpy as np
 from datetime import datetime, timedelta
@@ -6,7 +5,6 @@ from prophet import Prophet
 import matplotlib.pyplot as plt
 import gradio as gr
 
-# Simulate factory sensor data
 def simulate_factory_data(days=30, freq='H'):
     date_rng = pd.date_range(end=datetime.now(), periods=24 * days, freq=freq)
     df = pd.DataFrame(date_rng, columns=['ds'])
@@ -15,16 +13,13 @@ def simulate_factory_data(days=30, freq='H'):
     df['power_usage'] = np.random.normal(loc=120, scale=10, size=(len(date_rng)))
     return df
 
-# Forecast temperature using Prophet
 def forecast_temperature(days):
     df = simulate_factory_data()
     model = Prophet()
     df_temp = df[['ds', 'temperature']].rename(columns={"temperature": "y"})
     model.fit(df_temp)
-
     future = model.make_future_dataframe(periods=days, freq='H')
     forecast = model.predict(future)
-
     fig, ax = plt.subplots(figsize=(10, 5))
     ax.plot(df['ds'], df['temperature'], label='Actual')
     ax.plot(forecast['ds'], forecast['yhat'], label='Forecast')
@@ -36,12 +31,11 @@ def forecast_temperature(days):
     plt.tight_layout()
     return fig
 
-# Gradio Interface
 demo = gr.Interface(
     fn=forecast_temperature,
     inputs=gr.Slider(12, 72, value=48, label="Forecast Hours"),
     outputs=gr.Plot(label="Forecasted Temperature Chart"),
-    title="Smart Factory AI Pipeline",
+    title="Smart Factory AI Pipeline by Aryan",
     description="Simulated machine temperature forecasting using Prophet. Drag the slider to choose how far to forecast."
 )