Update app.py

app.py

@@ -1,6 +1,6 @@
 import pandas as pd
 import numpy as np
-from datetime import datetime, timedelta
+from datetime import datetime
 from prophet import Prophet
 import matplotlib.pyplot as plt
 import gradio as gr
@@ -8,22 +8,28 @@ import gradio as gr
 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'])
-    df['temperature'] = np.random.normal(loc=70, scale=5, size=(len(date_rng)))
+    df['temperature'] = np.random.normal(loc=70, scale=4, size=(len(date_rng)))
     df['vibration'] = np.random.normal(loc=20, scale=3, size=(len(date_rng)))
-    df['power_usage'] = np.random.normal(loc=120, scale=10, size=(len(date_rng)))
+    df['power_usage'] = np.random.normal(loc=120, scale=8, size=(len(date_rng)))
+    anomaly_indices = np.random.choice(len(df), size=10, replace=False)
+    df.loc[anomaly_indices, 'temperature'] += np.random.uniform(10, 20, size=10)
+    df.loc[anomaly_indices, 'vibration'] += np.random.uniform(5, 10, size=10)
+    df.loc[anomaly_indices, 'power_usage'] += np.random.uniform(30, 50, size=10)
     return df
 
-def forecast_temperature(days):
+def forecast_temperature(hours):
+    periods = int(hours)  # Prophet expects integer periods
     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')
+    future = model.make_future_dataframe(periods=periods, 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')
     ax.fill_between(forecast['ds'], forecast['yhat_lower'], forecast['yhat_upper'], alpha=0.2, label='Confidence')
+    ax.axhspan(85, 100, color='red', alpha=0.1, label='Danger Zone')
     ax.set_title("Machine Temperature Forecast")
     ax.set_xlabel("Time")
     ax.set_ylabel("Temperature (°C)")
@@ -33,10 +39,10 @@ def forecast_temperature(days):
 
 demo = gr.Interface(
     fn=forecast_temperature,
-    inputs=gr.Slider(12, 72, value=48, label="Forecast Hours"),
+    inputs=gr.Slider(12.0, 72.0, value=48.0, step=0.5, label="Forecast Hours"),
     outputs=gr.Plot(label="Forecasted Temperature Chart"),
-    title="Smart Factory AI Pipeline by Aryan",
-    description="Simulated machine temperature forecasting using Prophet. Drag the slider to choose how far to forecast."
+    title="Smart Factory AI Pipeline",
+    description="Forecast machine temperature using Prophet. Red zone shows potential overheating risk."
 )
 
 if __name__ == "__main__":