Update app.py

app.py

@@ -1,3 +1,6 @@
+"""
+LabOps Log Analyzer Dashboard with CSV file upload and optional PDF generation
+"""
 import gradio as gr
 import pandas as pd
 from datetime import datetime
@@ -6,9 +9,17 @@ import plotly.express as px
 from sklearn.ensemble import IsolationForest
 from transformers import pipeline
 import torch
-from reportlab.lib.pagesizes import letter
-from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer
-from reportlab.lib.styles import getSampleStyleSheet
+
+# Try to import reportlab for PDF generation
+try:
+    from reportlab.lib.pagesizes import letter
+    from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer
+    from reportlab.lib.styles import getSampleStyleSheet
+    reportlab_available = True
+    logging.info("reportlab module successfully imported")
+except ImportError:
+    logging.warning("reportlab module not found. PDF generation will be disabled. Install with: pip install reportlab")
+    reportlab_available = False
 
 # Configure logging for debugging
 logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
@@ -130,8 +141,11 @@ def create_usage_chart(df, progress=gr.Progress()):
         logging.error(f"Failed to create usage chart: {str(e)}")
         return None
 
-# Generate PDF content using reportlab
+# Generate PDF content using reportlab if available
 def generate_pdf_content(summary, preview, anomalies, amc_reminders, insights):
+    if not reportlab_available:
+        logging.warning("Skipping PDF generation: reportlab not installed")
+        return None
     try:
         pdf_path = "analysis_report.pdf"
         doc = SimpleDocTemplate(pdf_path, pagesize=letter)
@@ -195,7 +209,6 @@ async def process_logs(file_obj, progress=gr.Progress()):
             logging.error("Unsupported file format")
             return "Unsupported file format. Please upload a CSV file.", "", None, "", "", "", None
 
-        progress(0.05, "Loading CSV file...")
         try:
             required_columns = ["device_id", "log_type", "status", "timestamp", "usage_hours", "downtime", "amc_date"]
             dtypes = {
@@ -207,17 +220,16 @@ async def process_logs(file_obj, progress=gr.Progress()):
                 "amc_date": "string"
             }
             df = pd.read_csv(file_obj, dtype=dtypes)
-            # Validate required columns
+            # Check for required columns
             missing_columns = [col for col in required_columns if col not in df.columns]
             if missing_columns:
-                logging.error(f"Missing required columns: {missing_columns}")
+                logging.error(f"Missing columns: {missing_columns}")
                 return f"Missing required columns: {missing_columns}", None, None, None, None, None, None
             logging.info(f"File loaded successfully with {len(df)} rows")
         except Exception as e:
             logging.error(f"Failed to load CSV: {str(e)}")
             return f"Failed to load CSV: {str(e)}", None, None, None, None, None, None
 
-        progress(0.1, "Converting timestamps...")
         try:
             df["timestamp"] = pd.to_datetime(df["timestamp"], errors='coerce')
         except Exception as e:
@@ -226,46 +238,52 @@ async def process_logs(file_obj, progress=gr.Progress()):
 
         if df.empty:
             logging.warning("No data provided in the file")
-            return "No data available in provided.", "No data to preview.", None, "No anomalies detected.", "No AMC reminders.", "No insights generated.", None
+            return "No data available in provided.", None, None, None, None, None, None
 
         # Step 1: Summary
-        progress(0.2, "Generating summary...")
-        summary = f"Step 1: Summary Report\n{summarize_logs(df, progress)}"
+        progress(0.2, "Summary...")
+        summary = f"Step 1: Summary Report\n{summarize_logs(df)}"
 
         # Step 2: Log Preview
-        progress(0.3, "Previewing logs...")
+        progress(0.3, "Previewing...")
         if not df.empty:
             preview_lines = ["Step 2: Log Preview (First 5 Rows)"]
-            for idx, row in df.head().iterrows():
-                preview_lines.append(f"Row {idx + 1}: Device ID: {row['device_id']}, Log Type: {row['log_type']}, Status: {row['status']}, Timestamp: {row['timestamp']}, Usage Hours: {row['usage_hours']}, Downtime: {row['downtime']}, AMC Date: {row['amc_date']}")
+            for idx, row in df.head(5).iterrows():
+                preview_lines.append(
+                    f"Row {idx + 1}: Device ID: {row['device_id']}, "
+                    f"Log Type: {row['log_type']}, Status: {row['status']}, "
+                    f"Timestamp: {row['timestamp']}, Usage Hours: {row['usage_hours']}, "
+                    f"Downtime: {row['downtime']}, AMC Date: {row['amc_date']}"
+                )
             preview = "\n".join(preview_lines)
         else:
             preview = "Step 2: Log Preview\nNo data available."
 
         # Step 3: Usage Chart
-        progress(0.5, "Creating usage chart...")
-        chart = create_usage_chart(df, progress)
+        progress(0.5, "Chart...")
+        chart = create_usage_chart(df)
 
         # Step 4: Anomaly Detection
-        progress(0.7, "Detecting anomalies...")
-        anomalies = f"Step 4: Anomaly Detection\n{detect_anomalies(df, progress)}"
+        progress(0.7, "Anomalies...")
+        anomalies = f"Anomaly Detection\n{detect_anomalies(df)}"
 
         # Step 5: AMC Reminders
-        progress(0.8, "Checking AMC reminders...")
-        amc_reminders = f"Step 5: AMC Reminders\n{check_amc_reminders(df, datetime.now(), progress)}"
-
-        # Step 6: Dashboard Insights
-        progress(0.9, "Generating insights...")
-        insights = f"Step 6: Dashboard Insights (AI)\n{generate_dashboard_insights(df, progress)}"
-
-        # Generate PDF
-        progress(0.95, "Generating PDF report...")
-        pdf_file = generate_pdf_content(summary, preview, anomalies, amc_reminders, insights)
-        if pdf_file is None:
-            logging.error("PDF generation failed")
-            return "PDF generation failed. Please check logs.", preview, chart, anomalies, amc_reminders, insights, None
-
-        progress(1.0, "Processing complete!")
+        progress(0.8, "AMC...")
+        amc_reminders = f"AMC Reminders\n{check_amc_reminders(df, datetime.now())}"
+
+        # Step 6: Insights
+        progress(0.9, "Insights...")
+        insights = f"Dashboard Insights (AI)\n{generate_dashboard_insights(df)}"
+
+        # Generate PDF if available
+        progress(0.95, "PDF...")
+        pdf_file = generate_pdf_content(summary, preview, anomalies, amc_reminders, insights) if reportlab_available else None
+        if pdf_file is None and reportlab_available:
+            logging.warning("PDF generation failed")
+        elif pdf_file is None:
+            logging.info("PDF skipped: no reportlab")
+
+        progress(1.0, "Done!")
         return summary, preview, chart, anomalies, amc_reminders, insights, pdf_file
     except Exception as e:
         logging.error(f"Failed to process file: {str(e)}")
@@ -273,11 +291,11 @@ async def process_logs(file_obj, progress=gr.Progress()):
 
 # Gradio Interface
 try:
-    logging.info("Initializing Gradio Blocks interface...")
+    logging.info("Initializing Gradio interface...")
     with gr.Blocks(css="""
-        .dashboard-container {border: 1px solid #e0e0e0; padding: 10px; border-radius: 5px; background-color: #f9f9f9;}
+        .dashboard-container {border: 1px solid #e0e0e0; padding: 10px; border-radius: 5px;}
         .dashboard-title {font-size: 24px; font-weight: bold; margin-bottom: 5px;}
-        .dashboard-section {margin-bottom: 5px;}
+        .dashboard-section {margin-bottom: 20px;}
         .dashboard-section h3 {font-size: 18px; margin-bottom: 2px;}
         .dashboard-section p {margin: 1px 0; line-height: 1.2;}
         .dashboard-section ul {margin: 2px 0; padding-left: 20px;}
@@ -289,7 +307,7 @@ try:
             with gr.Column(scale=1):
                 file_input = gr.File(label="Upload Logs (CSV)", file_types=[".csv"])
                 submit_button = gr.Button("Analyze", variant="primary")
-            
+
             with gr.Column(scale=2):
                 with gr.Group(elem_classes="dashboard-container"):
                     gr.Markdown("<div class='dashboard-title'>Analysis Results (Step-by-Step)</div>")
@@ -303,27 +321,27 @@ try:
                     with gr.Group(elem_classes="dashboard-section"):
                         gr.Markdown("### Step 2: Log Preview")
                         preview_output = gr.Markdown()
-                    
+                        
                     # Step 3: Usage Chart
                     with gr.Group(elem_classes="dashboard-section"):
                         gr.Markdown("### Step 3: Usage Chart")
                         chart_output = gr.Plot()
-                    
+                        
                     # Step 4: Anomaly Detection
                     with gr.Group(elem_classes="dashboard-section"):
                         gr.Markdown("### Step 4: Anomaly Detection")
                         anomaly_output = gr.Markdown()
-                    
+                        
                     # Step 5: AMC Reminders
                     with gr.Group(elem_classes="dashboard-section"):
                         gr.Markdown("### Step 5: AMC Reminders")
                         amc_output = gr.Markdown()
-                    
+                        
                     # Step 6: Dashboard Insights
                     with gr.Group(elem_classes="dashboard-section"):
-                        gr.Markdown("### Step 6: Dashboard Insights (AI)")
+                        gr.Markdown("### Step 6: Insights (AI)")
                         insights_output = gr.Markdown()
-                    
+                        
                     # PDF Download
                     with gr.Group(elem_classes="dashboard-section"):
                         gr.Markdown("### Download Report")