Enhance image generation functionality: Add console tracking to monitor progress and errors during image processing, and include image queue in response metadata for better integration.

backend/igny8_core/ai/base.py

@@ -84,7 +84,8 @@ class BaseAIFunction(ABC):
         original_data: Any,
         account=None,
         progress_tracker=None,
-        step_tracker=None
+        step_tracker=None,
+        console_tracker=None
     ) -> Dict:
         """
         Save parsed results to database.

backend/igny8_core/ai/engine.py

@@ -348,8 +348,8 @@ class AIEngine:
                     return self._handle_error(error_msg, fn)
             
             # Phase 5: SAVE - Database Operations (85-98%)
-            # Pass step_tracker to save_output so it can add validation steps
-            save_result = fn.save_output(parsed, data, self.account, self.tracker, step_tracker=self.step_tracker)
+            # Pass step_tracker and console_tracker to save_output so it can add validation steps and log
+            save_result = fn.save_output(parsed, data, self.account, self.tracker, step_tracker=self.step_tracker, console_tracker=self.console_tracker)
             clusters_created = save_result.get('clusters_created', 0)
             keywords_updated = save_result.get('keywords_updated', 0)
             count = save_result.get('count', 0)

backend/igny8_core/ai/functions/generate_images_from_prompts.py

@@ -146,15 +146,24 @@ class GenerateImagesFromPromptsFunction(BaseAIFunction):
         original_data: Dict,
         account=None,
         progress_tracker=None,
-        step_tracker=None
+        step_tracker=None,
+        console_tracker=None
     ) -> Dict:
         """
         Process all images sequentially and generate them.
         This method handles the loop and makes AI calls directly.
         """
+        function_name = self.get_name()
+        
+        if console_tracker:
+            console_tracker.save(f"[{function_name}] Starting image generation queue")
+        
         images = original_data.get('images', [])
         if not images:
-            raise ValueError("No images to process")
+            error_msg = "[{function_name}] No images to process"
+            if console_tracker:
+                console_tracker.error('ValidationError', error_msg)
+            raise ValueError(error_msg)
         
         provider = original_data.get('provider', 'openai')
         model = original_data.get('model', 'dall-e-3')
@@ -169,6 +178,9 @@ class GenerateImagesFromPromptsFunction(BaseAIFunction):
         images_failed = 0
         errors = []
         
+        if console_tracker:
+            console_tracker.prep(f"[{function_name}] Preparing {total_images} image{'s' if total_images != 1 else ''} for generation")
+        
         # Initialize image queue in meta for frontend
         image_queue = []
         for idx, img in enumerate(images, 1):
@@ -198,6 +210,9 @@ class GenerateImagesFromPromptsFunction(BaseAIFunction):
             initial_meta['image_queue'] = image_queue
             progress_tracker.update("PREP", 10, f"Preparing to generate {total_images} image{'s' if total_images != 1 else ''}", meta=initial_meta)
         
+        if console_tracker:
+            console_tracker.prep(f"[{function_name}] Image queue initialized with {total_images} image{'s' if total_images != 1 else ''}")
+        
         # Process each image sequentially
         for index, image in enumerate(images, 1):
             queue_item = image_queue[index - 1]
@@ -216,6 +231,9 @@ class GenerateImagesFromPromptsFunction(BaseAIFunction):
                 else:
                     content_title = content.title or content.meta_title or "Content"
                 
+                if console_tracker:
+                    console_tracker.prep(f"[{function_name}] Processing image {index}/{total_images}: {image.image_type} for '{content_title}'")
+                
                 # Format prompt using template
                 if image_prompt_template:
                     try:
@@ -224,12 +242,18 @@ class GenerateImagesFromPromptsFunction(BaseAIFunction):
                             image_prompt=image.prompt,
                             image_type=image_type
                         )
+                        if console_tracker:
+                            console_tracker.prep(f"[{function_name}] Formatted prompt using template (length: {len(formatted_prompt)})")
                     except KeyError as e:
                         logger.warning(f"Template formatting error: {e}, using simple format")
                         formatted_prompt = f"Create a high-quality {image_type} image: {image.prompt}"
+                        if console_tracker:
+                            console_tracker.prep(f"[{function_name}] Template formatting error, using fallback prompt")
                 else:
                     # Fallback template
                     formatted_prompt = f"Create a high-quality {image_type} image: {image.prompt}"
+                    if console_tracker:
+                        console_tracker.prep(f"[{function_name}] Using fallback prompt template")
                 
                 # Update progress: PREP phase for this image
                 if progress_tracker and step_tracker:
@@ -261,6 +285,9 @@ class GenerateImagesFromPromptsFunction(BaseAIFunction):
                 
                 # Generate image (this is the actual API call)
                 # Frontend will simulate smooth progress from 50% to 95% while waiting
+                if console_tracker:
+                    console_tracker.ai_call(f"[{function_name}] Calling {provider}/{model} API for image {index}/{total_images}")
+                
                 result = ai_core.generate_image(
                     prompt=formatted_prompt,
                     provider=provider,
@@ -286,11 +313,14 @@ class GenerateImagesFromPromptsFunction(BaseAIFunction):
                         image.status = 'failed'
                         image.save(update_fields=['status', 'updated_at'])
                     
-                    error_msg = f"Image {index} failed: {result['error']}"
+                    error_msg = f"[{function_name}] Image {index}/{total_images} failed: {result['error']}"
                     errors.append(error_msg)
                     images_failed += 1
                     logger.error(f"Image generation failed for image {image.id}: {result['error']}")
                     
+                    if console_tracker:
+                        console_tracker.error('ImageGenerationError', error_msg)
+                    
                     if progress_tracker and step_tracker:
                         parse_msg = f"Image {index} failed: {result['error']}"
                         step_tracker.add_response_step("PARSE", "error", parse_msg)
@@ -311,11 +341,14 @@ class GenerateImagesFromPromptsFunction(BaseAIFunction):
                         image.status = 'failed'
                         image.save(update_fields=['status', 'updated_at'])
                     
-                    error_msg = f"Image {index} failed: No URL returned"
+                    error_msg = f"[{function_name}] Image {index}/{total_images} failed: No URL returned"
                     errors.append(error_msg)
                     images_failed += 1
                     logger.error(f"No image URL returned for image {image.id}")
                     
+                    if console_tracker:
+                        console_tracker.error('ImageGenerationError', error_msg)
+                    
                     if progress_tracker and step_tracker:
                         parse_msg = f"Image {index} failed: No URL returned"
                         step_tracker.add_response_step("PARSE", "error", parse_msg)
@@ -336,6 +369,9 @@ class GenerateImagesFromPromptsFunction(BaseAIFunction):
                     progress_pct = 70 + int((index - 1) / total_images * 15)  # 70-85% for PARSE
                     progress_tracker.update("PARSE", progress_pct, parse_msg, meta=meta)
                 
+                if console_tracker:
+                    console_tracker.parse(f"[{function_name}] Image {index}/{total_images} generated successfully: {image_url[:50]}...")
+                
                 # Update image record
                 with transaction.atomic():
                     image.image_url = image_url
@@ -349,6 +385,9 @@ class GenerateImagesFromPromptsFunction(BaseAIFunction):
                 images_generated += 1
                 logger.info(f"Image {image.id} ({image.image_type}) generated successfully: {image_url}")
                 
+                if console_tracker:
+                    console_tracker.save(f"[{function_name}] Saved image {index}/{total_images} to database (ID: {image.id})")
+                
                 # Update progress: SAVE phase
                 if progress_tracker and step_tracker:
                     save_msg = f"Saved image {index} of {total_images}"
@@ -360,21 +399,40 @@ class GenerateImagesFromPromptsFunction(BaseAIFunction):
                 
             except Exception as e:
                 # Mark as failed
+                queue_item['status'] = 'failed'
+                queue_item['progress'] = 100
+                queue_item['error'] = str(e)
                 with transaction.atomic():
                     image.status = 'failed'
                     image.save(update_fields=['status', 'updated_at'])
                 
-                error_msg = f"Image {index} failed: {str(e)}"
+                error_msg = f"[{function_name}] Image {index}/{total_images} exception: {str(e)}"
                 errors.append(error_msg)
                 images_failed += 1
                 logger.error(f"Exception generating image {image.id}: {str(e)}", exc_info=True)
+                
+                if console_tracker:
+                    console_tracker.error('Exception', error_msg)
+                
                 continue
         
         # Final progress update
         if progress_tracker and step_tracker:
             final_msg = f"Generated {images_generated} of {total_images} images"
             step_tracker.add_request_step("SAVE", "success", final_msg)
-            progress_tracker.update("SAVE", 98, final_msg, meta=step_tracker.get_meta())
+            meta = step_tracker.get_meta()
+            meta['image_queue'] = image_queue
+            progress_tracker.update("SAVE", 98, final_msg, meta=meta)
+        
+        if console_tracker:
+            if images_generated > 0:
+                console_tracker.save(f"[{function_name}] SUCCESS: Generated {images_generated}/{total_images} image{'s' if images_generated != 1 else ''} successfully")
+            if images_failed > 0:
+                console_tracker.error('ImageGenerationError', f"[{function_name}] FAILED: {images_failed}/{total_images} image{'s' if images_failed != 1 else ''} failed")
+            if images_generated == total_images:
+                console_tracker.done(f"[{function_name}] All {total_images} image{'s' if total_images != 1 else ''} generated successfully")
+            else:
+                console_tracker.done(f"[{function_name}] Completed: {images_generated} succeeded, {images_failed} failed out of {total_images} total")
         
         return {
             'count': images_generated,

backend/igny8_core/modules/system/integration_views.py

@@ -1001,6 +1001,9 @@ class IntegrationSettingsViewSet(viewsets.ViewSet):
                             response_meta['request_steps'] = meta['request_steps']
                         if 'response_steps' in meta:
                             response_meta['response_steps'] = meta['response_steps']
+                        # Include image_queue if available (for image generation)
+                        if 'image_queue' in meta:
+                            response_meta['image_queue'] = meta['image_queue']
                     return Response({
                         'state': task_state,
                         'meta': response_meta