Update app.py

app.py

@@ -2,6 +2,7 @@ import streamlit as st
 import pandas as pd
 from prophet import Prophet
 from datetime import datetime, timedelta
+import numpy as np
 
 # Prepare data for Prophet
 def prepare_prophet_data(usage_series):
@@ -12,35 +13,33 @@ def prepare_prophet_data(usage_series):
         'ds': dates,
         'y': usage_series
     })
-    prophet_df['cap'] = 30  # Lowered to 30
+    prophet_df['cap'] = 60  # Max observed usage
     prophet_df['floor'] = 0
     return prophet_df
 
-# Train or update Prophet model
+# Train Prophet model
 def train_model_with_usage(usage_series):
-    print("Training with changepoint_prior_scale=0.001, usage:", usage_series)  # Debug to logs
     prophet_df = prepare_prophet_data(usage_series)
     model = Prophet(
         yearly_seasonality=False,
         weekly_seasonality=True,
         daily_seasonality=True,
-        changepoint_prior_scale=0.001,  # Lowered to 0.001
+        changepoint_prior_scale=0.002,
         growth='logistic'
     )
     model.fit(prophet_df)
     return model
 
-# Function to make forecasts
+# Forecast function
 def make_forecast(model, periods):
     future = model.make_future_dataframe(periods=periods)
-    future['cap'] = 30
+    future['cap'] = 60
     future['floor'] = 0
     forecast = model.predict(future)
     daily_forecasts = forecast['yhat'].tail(periods).tolist()
-    print(f"Daily forecasts for {periods} days:", [round(y) for y in daily_forecasts])  # Debug to logs
-    return round(sum(max(0, y) for y in daily_forecasts))  # Clip negative values
+    return round(sum(max(0, y) for y in daily_forecasts))  # Clip negatives
 
-# Function to validate input
+# Input validation
 def validate_usage_series(usage_str):
     try:
         usage_list = [float(x) for x in usage_str.split(',')]
@@ -55,10 +54,7 @@ def validate_usage_series(usage_str):
 # Main Streamlit app
 def main():
     st.title("SmartLab Consumables Forecast")
-    if st.button("Clear Cache"):
-        st.cache_resource.clear()
-        st.write("Cache cleared!")
-    
+
     st.header("Input Parameters")
     consumable_type = st.selectbox("Consumable Type", ['Filters', 'Reagents', 'Vials'])
     usage_series = st.text_input("Last 60 Days Usage (comma-separated)", "")
@@ -69,7 +65,6 @@ def main():
         if error:
             st.error(error)
             return
-        print("Input usage series:", usage_list)  # Debug to logs
         
         try:
             model = train_model_with_usage(usage_list)
@@ -110,4 +105,4 @@ def main():
         st.write(f"**For 30 Days**: Order {order_30} additional units.")
 
 if __name__ == "__main__":
-    main()
+    main()