Update app.py

app.py

@@ -28,27 +28,36 @@ class ProgressTracker:
         self.message = "Ready"
         self.is_processing = False
         self.lock = threading.Lock()
+        self.gradio_progress = None  # Store Gradio progress object
     
     def update(self, progress, message="Processing..."):
         with self.lock:
             self.progress = progress
             self.message = message
+            # Update Gradio progress bar if available
+            if self.gradio_progress is not None:
+                try:
+                    self.gradio_progress(progress / 100, desc=message)
+                except:
+                    pass  # Ignore errors if progress object is not valid
     
     def get_status(self):
         with self.lock:
             return f"{self.message} ({self.progress:.1f}%)"
     
-    def start_processing(self):
+    def start_processing(self, gradio_progress=None):
         with self.lock:
             self.is_processing = True
             self.progress = 0
             self.message = "Starting..."
+            self.gradio_progress = gradio_progress
     
     def end_processing(self):
         with self.lock:
             self.is_processing = False
             self.progress = 100
             self.message = "Complete"
+            self.gradio_progress = None
 
 # Create a global instance
 progress_tracker = ProgressTracker()
@@ -745,10 +754,13 @@ def process_multiple_dashboards(api_key, files, language_code="it", goal_descrip
     
     return combined_content, output_files, "✅ Analysis completed successfully!"
 
-# FIXED: Improved wrapper function for Gradio interface
-def process_dashboard(api_key, files, language_name, goal_description=None, num_sections=4, model_name=DEFAULT_MODEL, custom_model=None):
+# FIXED: Improved wrapper function for Gradio interface with progress bar integration
+def process_dashboard(api_key, files, language_name, goal_description=None, num_sections=4, model_name=DEFAULT_MODEL, custom_model=None, progress=gr.Progress()):
     """Process dashboard files (PDF/images) and generate reports (wrapper function for Gradio interface)."""
-    # Start a thread to update progress
+    # Start progress tracking with Gradio progress integration
+    progress_tracker.start_processing(progress)
+    
+    # Start a thread to update text-based progress
     progress_thread = threading.Thread(target=update_progress)
     progress_thread.daemon = True
     progress_thread.start()
@@ -893,7 +905,7 @@ def refresh_models(api_key):
         print(f"Error refreshing models: {str(e)}")
         return gr.Dropdown(choices=["custom"] + OPENROUTER_MODELS, value=DEFAULT_MODEL)
 
-# Define the Gradio interface with improved error handling
+# Define the Gradio interface with improved error handling and progress bar
 with gr.Blocks(title="Dashboard Narrator - Powered by OpenRouter.ai", theme=gr.themes.Soft()) as demo:
     gr.Markdown("""
     # 📊 Dashboard Narrator - Powered by OpenRouter.ai
@@ -906,7 +918,8 @@ with gr.Blocks(title="Dashboard Narrator - Powered by OpenRouter.ai", theme=gr.t
     - Support for PNG and JPG image analysis
     - Enhanced with Claude Sonnet 4 and Gemini 2.5 Flash models
     - Multi-format dashboard analysis capabilities
-    - Improved file download functionality<br><br>
+    - Improved file download functionality
+    - **Real-time progress tracking with visual progress bar**<br><br>
     **Instructions:**
     1. Enter your OpenRouter API key (get one at OpenRouter.ai)
     2. Choose an AI model for analysis
@@ -991,7 +1004,7 @@ with gr.Blocks(title="Dashboard Narrator - Powered by OpenRouter.ai", theme=gr.t
         outputs=model_choice,
     )
     
-    # Handle analyze button with improved error handling
+    # Handle analyze button with improved error handling and progress bar
     analyze_btn.click(
         fn=process_dashboard,
         inputs=[api_key, files, language, goal, num_sections, model_choice, custom_model],