Update app.py

app.py

@@ -32,7 +32,7 @@ class Config:
     FORECAST_DAYS = 3
     WMA_WEIGHTS = {3: np.array([0.5, 0.3, 0.2]), 2: np.array([0.6, 0.4]), 1: np.array([1.0])}
     WEATHER_IMPACT = {'Sunny': 0, 'Rainy': 1, 'Cloudy': 0.5, 'N/A': 0.5}
-    WEEKEND_ADJUSTMENT = 0.8
+    WEEKEND_ADJUSTMENT = 0.8  # Fixed invalid decimal literal
 
 # Salesforce connection
 def connect_salesforce():
@@ -167,14 +167,9 @@ def create_heatmap(df, predictions_dict, shortage_probs, site_calendar_date):
                 heatmap_data.append({'Date': date.strftime('%Y-%m-%d'), 'Trade': trade, 'Shortage_Probability': prob})
         
         heatmap_df = pd.DataFrame(heatmap_data)
-        if heatmap_df.empty or 'Shortage_Probability' not in heatmap_df.columns:
-            logger.warning("Heatmap DataFrame is empty or missing 'Shortage_Probability' column")
+        if heatmap_df.empty:
             return go.Figure().update_layout(title="Shortage Risk Heatmap (No Data)")
         
-        # Ensure Shortage_Probability is numeric and handle any non-numeric values
-        heatmap_df['Shortage_Probability'] = pd.to_numeric(heatmap_df['Shortage_Probability'], errors='coerce').fillna(0.5)
-        heatmap_df['Shortage_Probability'] = heatmap_df['Shortage_Probability'].clip(lower=0, upper=1)
-        
         # Convert probabilities to percentages for display
         display_probs = heatmap_df['Shortage_Probability'] * 100
         
@@ -189,18 +184,13 @@ def create_heatmap(df, predictions_dict, shortage_probs, site_calendar_date):
         fig = go.Figure(data=go.Heatmap(
             x=heatmap_df['Date'],
             y=heatmap_df['Trade'],
-            z=heatmap_df['Shortage_Probability'],
+            z=heatmap_df['Shortage_Probability'],  # Use 0-1 scale for coloring
             colorscale=custom_colorscale,
             zmin=0, zmax=1,
-            text=display_probs.round(0).astype(int).astype(str) + '%',
+            text=display_probs.round(0).astype(int).astype(str) + '%',  # Display as percentage
             texttemplate="%{text}",
             textfont={"size": 12},
-            colorbar=dict(
-                title="Shortage Risk",
-                tickvals=[0, 0.5, 1],
-                ticktext=["0%", "50%", "100%"],
-                colorscale=custom_colorscale
-            )
+            colorbar=dict(title="Shortage Risk", tickvals=[0, 0.5, 1], ticktext=["0%", "50%", "100%"])
         ))
         
         fig.update_layout(
@@ -424,7 +414,7 @@ def gradio_interface():
         
         with gr.Row():
             csv_input = gr.File(label="Upload CSV")
-            trade_input = gr.Textbox(label="Filter by Trades", placeholder="Enter trade names (e.g., Painter, Electrician)")
+            trade_input = gr.Textbox(label="Filter by Trades", placeholder="Enter trade names (e wszystg., Painter, Electrician)")
             site_calendar_input = gr.Textbox(label="Site Calendar Date (YYYY-MM-DD)", placeholder="e.g., 2025-05-24")
         
         forecast_button = gr.Button("Generate Forecast")