Upload forecast_engine.py

forecast_engine.py

@@ -0,0 +1,21 @@
+import numpy as np
+from joblib import load
+
+model = load("model.pkl")
+
+def forecast_consumables(usage_series, days):
+    forecast = []
+    current_series = usage_series.copy()
+    
+    for _ in range(days):
+        # Prepare the input for prediction (last 60 days)
+        input_series = np.array(current_series[-60:]).reshape(1, -1)
+        # Predict the next day's usage
+        next_usage = model.predict(input_series)[0]
+        next_usage = max(0, int(next_usage))  # Ensure non-negative and integer
+        next_usage = min(next_usage, 100)    # Cap at 100
+        forecast.append(next_usage)
+        # Append the predicted usage for the next iteration
+        current_series.append(next_usage)
+    
+    return forecast