Update app.py

app.py

@@ -599,8 +599,11 @@ def generate_pdf_content(summary, preview, anomalies, amc_reminders, insights, d
 def validate_and_generate_pdf(summary, preview, anomalies, amc_reminders, insights, device_cards, daily_log_chart, weekly_uptime_chart, anomaly_alerts_chart, downtime_chart, df, month_filter):
     if not all([summary, preview, anomalies, amc_reminders, insights, device_cards, df is not None]):
         logging.error("One or more required inputs for PDF generation are missing.")
-        return None
-    return generate_pdf_content(summary, preview, anomalies, amc_reminders, insights, device_cards, daily_log_chart, weekly_uptime_chart, anomaly_alerts_chart, downtime_chart, df, month_filter)
+        return None, "Please click 'Analyze' to process the data before generating a PDF."
+    pdf_path = generate_pdf_content(summary, preview, anomalies, amc_reminders, insights, device_cards, daily_log_chart, weekly_uptime_chart, anomaly_alerts_chart, downtime_chart, df, month_filter)
+    if pdf_path is None:
+        return None, "Failed to generate PDF. Check logs for details."
+    return pdf_path, "PDF generated successfully."
 
 # Main Gradio function
 async def process_logs(file_obj, lab_site_filter, equipment_type_filter, date_range, month_filter, last_modified_state):
@@ -608,18 +611,18 @@ async def process_logs(file_obj, lab_site_filter, equipment_type_filter, date_ra
         start_time = datetime.now()
 
         if not file_obj:
-            return "No file uploaded.", "No data to preview.", None, '<p>No device cards available.</p>', None, None, None, None, "No anomalies detected.", "No AMC reminders.", "No insights generated.", None, last_modified_state, None, None, None, None, None, None
+            return "No file uploaded.", "No data to preview.", None, '<p>No device cards available.</p>', None, None, None, None, "No anomalies detected.", "No AMC reminders.", "No insights generated.", None, last_modified_state, None, None, None, None, None, None, False, "Please upload a CSV file to analyze."
         
         file_path = file_obj.name
         current_modified_time = os.path.getmtime(file_path)
         
         if last_modified_state and current_modified_time == last_modified_state:
-            return None, None, None, None, None, None, None, None, None, None, None, None, last_modified_state, None, None, None, None, None, None
+            return None, None, None, None, None, None, None, None, None, None, None, None, last_modified_state, None, None, None, None, None, None, False, "No changes detected in the file."
 
         logging.info(f"Processing file: {file_path}, last modified: {current_modified_time}")
         
         if not file_path.endswith(".csv"):
-            return "Please upload a CSV file.", "", None, '<p>No device cards available.</p>', None, None, None, None, "", "", "", None, last_modified_state, None, None, None, None, None, None
+            return "Please upload a CSV file.", "", None, '<p>No device cards available.</p>', None, None, None, None, "", "", "", None, last_modified_state, None, None, None, None, None, None, False, "Invalid file format. Please upload a CSV file."
 
         required_columns = ["device_id", "log_type", "status", "timestamp", "usage_hours", "downtime", "amc_date"]
         dtypes = {
@@ -633,7 +636,7 @@ async def process_logs(file_obj, lab_site_filter, equipment_type_filter, date_ra
         df = pd.read_csv(file_path, dtype=dtypes)
         missing_columns = [col for col in required_columns if col not in df.columns]
         if missing_columns:
-            return f"Missing columns: {missing_columns}", None, None, '<p>No device cards available.</p>', None, None, None, None, None, None, None, None, last_modified_state, None, None, None, None, None, None
+            return f"Missing columns: {missing_columns}", None, None, '<p>No device cards available.</p>', None, None, None, None, None, None, None, None, last_modified_state, None, None, None, None, None, None, False, f"Missing required columns: {missing_columns}"
         
         df["timestamp"] = pd.to_datetime(df["timestamp"], errors='coerce')
         df["amc_date"] = pd.to_datetime(df["amc_date"], errors='coerce')
@@ -641,7 +644,7 @@ async def process_logs(file_obj, lab_site_filter, equipment_type_filter, date_ra
             logging.info("Localizing naive timestamps to IST")
             df["timestamp"] = df["timestamp"].dt.tz_localize('UTC').dt.tz_convert('Asia/Kolkata')
         if df.empty:
-            return "No data available.", None, None, '<p>No device cards available.</p>', None, None, None, None, None, None, None, None, last_modified_state, None, None, None, None, None, None
+            return "No data available.", None, None, '<p>No device cards available.</p>', None, None, None, None, None, None, None, None, last_modified_state, None, None, None, None, None, None, False, "No data available in the uploaded file."
 
         logging.info(f"DataFrame before filtering:\n{df.head().to_string()}")
 
@@ -676,7 +679,7 @@ async def process_logs(file_obj, lab_site_filter, equipment_type_filter, date_ra
 
         if filtered_df.empty:
             logging.warning("Filtered DataFrame is empty after applying filters.")
-            return "No data after applying filters.", None, None, '<p>No device cards available.</p>', None, None, None, None, None, None, None, None, last_modified_state, None, None, None, None, None, None
+            return "No data after applying filters.", None, None, '<p>No device cards available.</p>', None, None, None, None, None, None, None, None, last_modified_state, None, None, None, None, None, None, False, "No data available after applying filters."
 
         logging.info(f"Filtered DataFrame:\n{filtered_df.head().to_string()}")
 
@@ -796,10 +799,13 @@ async def process_logs(file_obj, lab_site_filter, equipment_type_filter, date_ra
         if elapsed_time > 10:
             logging.warning(f"Processing time exceeded 10 seconds: {elapsed_time:.2f} seconds")
 
-        return (summary, preview_html, usage_chart, device_cards, daily_log_chart, weekly_uptime_chart, anomaly_alerts_chart, downtime_chart, anomalies, amc_reminders, insights, pdf_file, last_modified_state, summary, preview_text, anomalies, amc_reminders, insights, device_cards, filtered_df)
+        # Log state variable assignments for debugging
+        logging.info(f"Setting state variables: summary={summary}, preview={preview_text}, anomalies={anomalies}, amc_reminders={amc_reminders}, insights={insights}, device_cards={device_cards[:50]}..., df={'set' if df is not None else 'None'}")
+
+        return (summary, preview_html, usage_chart, device_cards, daily_log_chart, weekly_uptime_chart, anomaly_alerts_chart, downtime_chart, anomalies, amc_reminders, insights, pdf_file, current_modified_time, summary, preview_text, anomalies, amc_reminders, insights, device_cards, filtered_df, True, "Analysis completed successfully. You can now generate the PDF report.")
     except Exception as e:
         logging.error(f"Failed to process file: {str(e)}")
-        return f"Error: {str(e)}", None, None, '<p>Error processing data.</p>', None, None, None, None, None, None, None, None, last_modified_state, None, None, None, None, None, None
+        return f"Error: {str(e)}", None, None, '<p>Error processing data.</p>', None, None, None, None, None, None, None, None, last_modified_state, None, None, None, None, None, None, False, f"Failed to process file: {str(e)}"
 
 # Update filter options
 def update_filters(file_obj):
@@ -867,6 +873,7 @@ try:
         insights_state = gr.State()
         device_cards_state = gr.State()
         df_state = gr.State()
+        is_analyzed_state = gr.State(value=False)
 
         with gr.Row():
             with gr.Column(scale=1):
@@ -907,6 +914,10 @@ try:
                 with gr.Group(elem_classes="dashboard-container"):
                     gr.Markdown("<div class='dashboard-title'>Analysis Results</div>")
                     
+                    with gr.Group(elem_classes="dashboard-section"):
+                        gr.Markdown("### Status Message")
+                        status_message = gr.Markdown("Please upload a CSV file and click 'Analyze' to begin.")
+
                     with gr.Group(elem_classes="dashboard-section"):
                         gr.Markdown("### Step 1: Summary Report")
                         summary_output = gr.Markdown()
@@ -946,7 +957,7 @@ try:
                         
                     with gr.Group(elem_classes="dashboard-section"):
                         gr.Markdown("### Export Report")
-                        pdf_button = gr.Button("Generate PDF Report")
+                        pdf_button = gr.Button("Generate PDF Report", interactive=False)  # Disabled by default
                         pdf_output = gr.File(label="Download Monthly Status Report as PDF")
 
         file_input.change(
@@ -986,10 +997,22 @@ try:
                 amc_reminders_state,
                 insights_state,
                 device_cards_state,
-                df_state
+                df_state,
+                is_analyzed_state,
+                status_message
             ]
         )
 
+        def update_pdf_button_interactivity(is_analyzed):
+            return gr.update(interactive=is_analyzed)
+
+        is_analyzed_state.change(
+            fn=update_pdf_button_interactivity,
+            inputs=[is_analyzed_state],
+            outputs=[pdf_button],
+            queue=False
+        )
+
         pdf_button.click(
             fn=validate_and_generate_pdf,
             inputs=[
@@ -1006,7 +1029,7 @@ try:
                 df_state,
                 month_filter
             ],
-            outputs=[pdf_output]
+            outputs=[pdf_output, status_message]
         )
 
     logging.info("Gradio interface initialized successfully")