Update app.py

app.py

@@ -324,9 +324,6 @@ def query_ai(model, stats, question, df=None):
 def save_plotly_as_image(fig, filename):
     """Convert Plotly figure to PNG for PDF"""
     try:
-        # Check if kaleido is available
-        import kaleido
-        
         temp_dir = tempfile.gettempdir()
         filepath = os.path.join(temp_dir, filename)
         
@@ -338,44 +335,66 @@ def save_plotly_as_image(fig, filename):
             margin=dict(t=50, b=40, l=40, r=40)
         )
         
-        pio.write_image(fig, filepath, format='png', width=800, height=400, scale=2)
-        return filepath if os.path.exists(filepath) else None
+        # Debug info
+        print(f"Attempting to save chart to: {filepath}")
         
-    except ImportError:
-        st.warning("📸 Kaleido not installed. Charts will not appear in PDF. Run: pip install kaleido")
-        return None
+        # Use kaleido explicitly
+        pio.write_image(fig, filepath, format='png', width=800, height=400, scale=2, engine='kaleido')
+        
+        # Check if file was created
+        if os.path.exists(filepath):
+            file_size = os.path.getsize(filepath)
+            print(f"Chart saved successfully: {filepath} ({file_size} bytes)")
+            return filepath
+        else:
+            print("Chart file was not created")
+            return None
+            
     except Exception as e:
-        st.warning(f"Chart save error: {e}")
+        print(f"Chart save error: {str(e)}")
+        st.error(f"Chart save error: {str(e)}")
         return None
 
 def create_pdf_charts(df, stats):
     """Generate charts for PDF report"""
     charts = {}
     
-    # Production distribution pie chart
-    materials = [k for k in stats.keys() if k != '_total_']
-    values = [stats[mat]['total'] for mat in materials]
-    labels = [mat.replace('_', ' ').title() for mat in materials]
-    
-    fig_pie = px.pie(values=values, names=labels, title="Production Distribution by Material")
-    charts['pie'] = save_plotly_as_image(fig_pie, "distribution.png")
-    
-    # Daily production trend
-    daily_data = df.groupby('date')['weight_kg'].sum().reset_index()
-    fig_trend = px.line(daily_data, x='date', y='weight_kg', title="Daily Production Trend")
-    fig_trend.update_layout(xaxis_title="Date", yaxis_title="Weight (kg)")
-    charts['trend'] = save_plotly_as_image(fig_trend, "trend.png")
-    
-    # Material comparison bar chart
-    fig_bar = px.bar(x=labels, y=values, title="Production by Material Type")
-    fig_bar.update_layout(xaxis_title="Material Type", yaxis_title="Weight (kg)")
-    charts['bar'] = save_plotly_as_image(fig_bar, "materials.png")
-    
-    # Shift analysis if available
-    if 'shift' in df.columns:
-        shift_data = df.groupby('shift')['weight_kg'].sum().reset_index()
-        fig_shift = px.pie(shift_data, values='weight_kg', names='shift', title="Production by Shift")
-        charts['shift'] = save_plotly_as_image(fig_shift, "shifts.png")
+    try:
+        # Production distribution pie chart
+        materials = [k for k in stats.keys() if k != '_total_']
+        values = [stats[mat]['total'] for mat in materials]
+        labels = [mat.replace('_', ' ').title() for mat in materials]
+        
+        if len(materials) > 0 and len(values) > 0:
+            fig_pie = px.pie(values=values, names=labels, title="Production Distribution by Material")
+            charts['pie'] = save_plotly_as_image(fig_pie, "distribution.png")
+        
+        # Daily production trend
+        if len(df) > 0:
+            daily_data = df.groupby('date')['weight_kg'].sum().reset_index()
+            if len(daily_data) > 0:
+                fig_trend = px.line(daily_data, x='date', y='weight_kg', title="Daily Production Trend")
+                fig_trend.update_layout(xaxis_title="Date", yaxis_title="Weight (kg)")
+                charts['trend'] = save_plotly_as_image(fig_trend, "trend.png")
+        
+        # Material comparison bar chart
+        if len(materials) > 0 and len(values) > 0:
+            fig_bar = px.bar(x=labels, y=values, title="Production by Material Type")
+            fig_bar.update_layout(xaxis_title="Material Type", yaxis_title="Weight (kg)")
+            charts['bar'] = save_plotly_as_image(fig_bar, "materials.png")
+        
+        # Shift analysis if available
+        if 'shift' in df.columns and len(df) > 0:
+            shift_data = df.groupby('shift')['weight_kg'].sum().reset_index()
+            if len(shift_data) > 0 and shift_data['weight_kg'].sum() > 0:
+                fig_shift = px.pie(shift_data, values='weight_kg', names='shift', title="Production by Shift")
+                charts['shift'] = save_plotly_as_image(fig_shift, "shifts.png")
+        
+        print(f"Charts created: {list(charts.keys())}")
+        
+    except Exception as e:
+        print(f"Error creating charts: {str(e)}")
+        st.error(f"Error creating charts: {str(e)}")
     
     return charts
 
@@ -477,53 +496,40 @@ def create_enhanced_pdf_report(df, stats, outliers):
     # Generate and add charts
     elements.append(Paragraph("Production Analysis Charts", subtitle_style))
     
-    try:
-        # Check if kaleido is available
-        import kaleido
-        
-        with st.spinner("Generating charts for PDF..."):
-            charts = create_pdf_charts(df, stats)
-        
-        # Add charts to PDF
-        charts_added = False
-        
-        if charts.get('pie') and charts['pie'] and os.path.exists(charts['pie']):
-            elements.append(Paragraph("Production Distribution", styles['Heading3']))
-            elements.append(Image(charts['pie'], width=6*inch, height=3*inch))
-            elements.append(Spacer(1, 20))
-            charts_added = True
-        
-        if charts.get('trend') and charts['trend'] and os.path.exists(charts['trend']):
-            elements.append(Paragraph("Production Trend", styles['Heading3']))
-            elements.append(Image(charts['trend'], width=6*inch, height=3*inch))
-            elements.append(Spacer(1, 20))
-            charts_added = True
-        
-        if charts.get('bar') and charts['bar'] and os.path.exists(charts['bar']):
-            elements.append(Paragraph("Material Comparison", styles['Heading3']))
-            elements.append(Image(charts['bar'], width=6*inch, height=3*inch))
-            elements.append(Spacer(1, 20))
-            charts_added = True
-        
-        if charts.get('shift') and charts['shift'] and os.path.exists(charts['shift']):
-            elements.append(Paragraph("Shift Analysis", styles['Heading3']))
-            elements.append(Image(charts['shift'], width=6*inch, height=3*inch))
-            elements.append(Spacer(1, 20))
-            charts_added = True
-        
-        if not charts_added:
-            elements.append(Paragraph("Charts could not be generated. Please install kaleido: pip install kaleido", styles['Normal']))
-            elements.append(Spacer(1, 20))
-            
-    except ImportError:
-        # Kaleido not available - add text summary instead
-        elements.append(Paragraph("Charts Not Available", styles['Heading3']))
-        elements.append(Paragraph("To enable charts in PDF reports, please install kaleido:", styles['Normal']))
-        elements.append(Paragraph("<b>pip install kaleido</b>", styles['Normal']))
+    with st.spinner("Generating charts for PDF..."):
+        charts = create_pdf_charts(df, stats)
+    
+    # Add charts to PDF with better error checking
+    charts_added = False
+    
+    for chart_type, chart_titles in [
+        ('pie', "Production Distribution"),
+        ('trend', "Production Trend"), 
+        ('bar', "Material Comparison"),
+        ('shift', "Shift Analysis")
+    ]:
+        chart_path = charts.get(chart_type)
+        if chart_path and os.path.exists(chart_path):
+            try:
+                elements.append(Paragraph(chart_titles, styles['Heading3']))
+                elements.append(Image(chart_path, width=6*inch, height=3*inch))
+                elements.append(Spacer(1, 20))
+                charts_added = True
+                print(f"Added chart: {chart_type}")
+            except Exception as e:
+                print(f"Error adding chart {chart_type}: {str(e)}")
+                st.warning(f"Could not add {chart_type} chart to PDF: {str(e)}")
+    
+    if not charts_added:
+        elements.append(Paragraph("Charts Generation Failed", styles['Heading3']))
+        elements.append(Paragraph("Possible issues:", styles['Normal']))
+        elements.append(Paragraph("1. Kaleido installation problem", styles['Normal']))
+        elements.append(Paragraph("2. File permissions issue", styles['Normal']))
+        elements.append(Paragraph("3. Data format problem", styles['Normal']))
         elements.append(Spacer(1, 10))
         
-        # Add text-based data summary instead
-        elements.append(Paragraph("Production Summary (Text Format):", styles['Normal']))
+        # Add text-based summary instead
+        elements.append(Paragraph("Production Data Summary:", styles['Normal']))
         for material, info in stats.items():
             if material != '_total_':
                 summary_text = f"• {material.replace('_', ' ').title()}: {info['total']:,.0f} kg ({info['percentage']:.1f}%)"