Add SEO fields to Tasks model, improve content generation response handling, and enhance progress bar animation
- Added primary_keyword, secondary_keywords, tags, and categories fields to Tasks model - Updated generate_content function to handle full JSON response with all SEO fields - Improved progress bar animation: smooth 1% increments every 300ms - Enhanced step detection for content generation vs clustering vs ideas - Fixed progress modal to show correct messages for each function type - Added comprehensive logging to Keywords and Tasks pages for AI functions - Fixed error handling to show meaningful error messages instead of generic failures
This commit is contained in:
Gitea Deploy
@@ -7,6 +7,8 @@ from typing import List
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from django.db import transaction
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from igny8_core.modules.planner.models import Keywords, Clusters, ContentIdeas
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from igny8_core.utils.ai_processor import ai_processor
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from igny8_core.ai.functions.generate_ideas import generate_ideas_core
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from igny8_core.ai.tracker import ConsoleStepTracker
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logger = logging.getLogger(__name__)
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@@ -23,9 +25,19 @@ except ImportError:
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return decorator
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# ============================================================================
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# DEPRECATED: This function is deprecated. Use the new AI framework instead.
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# New path: views.py -> run_ai_task -> AIEngine -> AutoClusterFunction
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# This function is kept for backward compatibility but should not be used.
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# ============================================================================
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def _auto_cluster_keywords_core(keyword_ids: List[int], sector_id: int = None, account_id: int = None, progress_callback=None):
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"""
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Core logic for clustering keywords. Can be called with or without Celery.
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[DEPRECATED] Core logic for clustering keywords. Can be called with or without Celery.
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⚠️ WARNING: This function is deprecated. Use the new AI framework instead:
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- New path: views.py -> run_ai_task -> AIEngine -> AutoClusterFunction
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- This function uses the old AIProcessor and does not use PromptRegistry
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- Console logging may not work correctly in this path
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Args:
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keyword_ids: List of keyword IDs to cluster
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@@ -33,7 +45,11 @@ def _auto_cluster_keywords_core(keyword_ids: List[int], sector_id: int = None, a
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account_id: Account ID for account isolation
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progress_callback: Optional function to call for progress updates (for Celery tasks)
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"""
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# Track request and response steps
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# Initialize console step tracker for logging
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tracker = ConsoleStepTracker('auto_cluster')
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tracker.init(f"Starting keyword clustering for {len(keyword_ids)} keywords")
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# Track request and response steps (for Celery progress callbacks)
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request_steps = []
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response_steps = []
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@@ -56,6 +72,7 @@ def _auto_cluster_keywords_core(keyword_ids: List[int], sector_id: int = None, a
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)
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# Step 4: Keyword Loading & Validation
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tracker.prep(f"Loading {len(keyword_ids)} keywords from database")
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step_start = time.time()
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keywords_queryset = Keywords.objects.filter(id__in=keyword_ids)
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if account_id:
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@@ -66,7 +83,9 @@ def _auto_cluster_keywords_core(keyword_ids: List[int], sector_id: int = None, a
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keywords = list(keywords_queryset.select_related('account', 'site', 'site__account', 'sector', 'sector__site'))
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if not keywords:
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logger.warning(f"No keywords found for clustering: {keyword_ids}")
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error_msg = f"No keywords found for clustering: {keyword_ids}"
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logger.warning(error_msg)
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tracker.error('Validation', error_msg)
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request_steps.append({
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'stepNumber': 4,
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'stepName': 'Keyword Loading & Validation',
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@@ -83,6 +102,7 @@ def _auto_cluster_keywords_core(keyword_ids: List[int], sector_id: int = None, a
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)
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return {'success': False, 'error': 'No keywords found', 'request_steps': request_steps, 'response_steps': response_steps}
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tracker.prep(f"Loaded {len(keywords)} keywords successfully")
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request_steps.append({
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'stepNumber': 4,
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'stepName': 'Keyword Loading & Validation',
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@@ -329,10 +349,20 @@ def _auto_cluster_keywords_core(keyword_ids: List[int], sector_id: int = None, a
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return {'success': False, 'error': f'Error preparing AI call: {str(e)}', 'request_steps': request_steps, 'response_steps': response_steps}
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# Call AI with step tracking
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result = processor.cluster_keywords(keyword_data, sector_name=sector_name, account=account, response_steps=response_steps, progress_callback=progress_callback)
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tracker.ai_call(f"Sending {len(keyword_data)} keywords to AI for clustering")
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result = processor.cluster_keywords(
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keyword_data,
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sector_name=sector_name,
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account=account,
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response_steps=response_steps,
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progress_callback=progress_callback,
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tracker=tracker # Pass tracker for console logging
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)
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if result.get('error'):
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logger.error(f"AI clustering error: {result['error']}")
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error_msg = f"AI clustering error: {result['error']}"
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logger.error(error_msg)
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tracker.error('AI_CALL', error_msg)
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if progress_callback:
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progress_callback(
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state='FAILURE',
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@@ -345,6 +375,9 @@ def _auto_cluster_keywords_core(keyword_ids: List[int], sector_id: int = None, a
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)
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return {'success': False, 'error': result['error'], 'request_steps': request_steps, 'response_steps': response_steps}
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# Parse response
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tracker.parse("Parsing AI response into cluster data")
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# Update response_steps from result if available
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if result.get('response_steps'):
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response_steps.extend(result.get('response_steps', []))
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@@ -369,6 +402,7 @@ def _auto_cluster_keywords_core(keyword_ids: List[int], sector_id: int = None, a
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keywords_updated = 0
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# Step 13: Database Transaction Start
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tracker.save(f"Creating {len(clusters_data)} clusters in database")
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step_start = time.time()
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# Create/update clusters and assign keywords
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# Note: account and sector are already extracted above to avoid database queries inside transaction
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@@ -566,6 +600,7 @@ def _auto_cluster_keywords_core(keyword_ids: List[int], sector_id: int = None, a
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# Final progress update
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final_message = f"Clustering complete: {clusters_created} clusters created, {keywords_updated} keywords updated"
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logger.info(final_message)
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tracker.done(final_message)
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if progress_callback:
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progress_callback(
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@@ -587,7 +622,9 @@ def _auto_cluster_keywords_core(keyword_ids: List[int], sector_id: int = None, a
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}
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except Exception as e:
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logger.error(f"Error in auto_cluster_keywords_core: {str(e)}", exc_info=True)
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error_msg = f"Error in auto_cluster_keywords_core: {str(e)}"
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logger.error(error_msg, exc_info=True)
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tracker.error('Exception', error_msg, exception=e)
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if progress_callback:
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progress_callback(
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state='FAILURE',
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@@ -607,10 +644,18 @@ def _auto_cluster_keywords_core(keyword_ids: List[int], sector_id: int = None, a
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@shared_task(bind=True, max_retries=3)
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# ============================================================================
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# DEPRECATED: This Celery task is deprecated. Use run_ai_task instead.
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# New path: views.py -> run_ai_task -> AIEngine -> AutoClusterFunction
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# ============================================================================
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def auto_cluster_keywords_task(self, keyword_ids: List[int], sector_id: int = None, account_id: int = None):
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"""
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Celery task wrapper for clustering keywords using AI.
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Calls the core function with progress callback.
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[DEPRECATED] Celery task wrapper for clustering keywords using AI.
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⚠️ WARNING: This task is deprecated. Use the new AI framework instead:
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- New path: views.py -> run_ai_task -> AIEngine -> AutoClusterFunction
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- This task uses the old _auto_cluster_keywords_core function
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- Console logging may not work correctly in this path
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Args:
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keyword_ids: List of keyword IDs to cluster
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@@ -716,96 +716,99 @@ class ClusterViewSet(SiteSectorModelViewSet):
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@action(detail=False, methods=['post'], url_path='auto_generate_ideas', url_name='auto_generate_ideas')
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def auto_generate_ideas(self, request):
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"""Generate content ideas for clusters using AI"""
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ids = request.data.get('ids', [])
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"""Generate content ideas for clusters using AI - New unified framework"""
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import logging
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from igny8_core.ai.tasks import run_ai_task
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from kombu.exceptions import OperationalError as KombuOperationalError
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if not ids:
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return Response({'error': 'No cluster IDs provided'}, status=status.HTTP_400_BAD_REQUEST)
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logger = logging.getLogger(__name__)
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if len(ids) > 5:
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return Response({'error': 'Maximum 5 clusters allowed for idea generation'}, status=status.HTTP_400_BAD_REQUEST)
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# Get account - handle RelatedObjectDoesNotExist
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account = None
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account_id = None
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try:
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# Get account
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account = getattr(request, 'account', None)
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if account:
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# Access pk directly instead of id to avoid potential relationship access
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account_id = getattr(account, 'pk', None) or getattr(account, 'id', None)
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except Exception as e:
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import logging
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logger = logging.getLogger(__name__)
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logger.error(f"Error getting account: {type(e).__name__}: {e}", exc_info=True)
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account_id = None
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# Try to queue Celery task, fall back to synchronous if Celery not available
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try:
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import logging
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logger = logging.getLogger(__name__)
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logger.info(f"auto_generate_ideas called with ids={ids}, account_id={account_id}")
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account_id = account.id if account else None
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from .tasks import auto_generate_ideas_task
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from kombu.exceptions import OperationalError as KombuOperationalError
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# Prepare payload
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payload = {
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'ids': request.data.get('ids', [])
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}
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if hasattr(auto_generate_ideas_task, 'delay'):
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try:
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# Celery is available - queue async task
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logger.info("Queuing Celery task...")
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task = auto_generate_ideas_task.delay(ids, account_id=account_id)
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logger.info(f"Task queued successfully: {task.id}")
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logger.info(f"auto_generate_ideas called with ids={payload['ids']}, account_id={account_id}")
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# Validate basic input
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if not payload['ids']:
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return Response({
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'success': False,
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'error': 'No cluster IDs provided'
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}, status=status.HTTP_400_BAD_REQUEST)
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if len(payload['ids']) > 10:
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return Response({
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'success': False,
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'error': 'Maximum 10 clusters allowed for idea generation'
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}, status=status.HTTP_400_BAD_REQUEST)
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# Try to queue Celery task
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try:
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if hasattr(run_ai_task, 'delay'):
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task = run_ai_task.delay(
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function_name='generate_ideas',
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payload=payload,
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account_id=account_id
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)
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logger.info(f"Task queued: {task.id}")
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return Response({
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'success': True,
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'task_id': str(task.id),
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'message': 'Idea generation started'
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}, status=status.HTTP_200_OK)
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except (KombuOperationalError, ConnectionError) as e:
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# Celery connection failed - execute synchronously
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logger.warning(f"Celery connection failed, executing synchronously: {e}")
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result = auto_generate_ideas_task(ids, account_id=account_id)
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else:
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# Celery not available - execute synchronously
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logger.warning("Celery not available, executing synchronously")
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result = run_ai_task(
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function_name='generate_ideas',
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payload=payload,
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account_id=account_id
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)
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if result.get('success'):
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return Response({
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'success': True,
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'ideas_created': result.get('ideas_created', 0),
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'message': 'Ideas generated successfully'
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**result
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}, status=status.HTTP_200_OK)
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else:
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return Response({
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'success': False,
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'error': result.get('error', 'Idea generation failed')
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}, status=status.HTTP_500_INTERNAL_SERVER_ERROR)
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else:
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# Celery not available - execute synchronously
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logger.info("Celery not available, executing synchronously")
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result = auto_generate_ideas_task(ids, account_id=account_id)
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except (KombuOperationalError, ConnectionError) as e:
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# Broker connection failed - fall back to synchronous execution
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logger.warning(f"Celery broker unavailable, falling back to synchronous execution: {str(e)}")
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result = run_ai_task(
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function_name='generate_ideas',
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payload=payload,
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account_id=account_id
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)
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if result.get('success'):
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return Response({
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'success': True,
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'ideas_created': result.get('ideas_created', 0),
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'message': 'Ideas generated successfully'
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**result
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}, status=status.HTTP_200_OK)
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else:
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return Response({
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'success': False,
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'error': result.get('error', 'Idea generation failed')
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}, status=status.HTTP_500_INTERNAL_SERVER_ERROR)
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except ImportError as e:
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import logging
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logger = logging.getLogger(__name__)
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logger.error(f"ImportError in auto_generate_ideas: {e}", exc_info=True)
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return Response({
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'success': False,
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'error': 'AI tasks module not available'
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}, status=status.HTTP_500_INTERNAL_SERVER_ERROR)
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except Exception as e:
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logger.error(f"Error in auto_generate_ideas: {str(e)}", exc_info=True)
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return Response({
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'success': False,
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'error': str(e)
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}, status=status.HTTP_500_INTERNAL_SERVER_ERROR)
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except Exception as e:
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import logging
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logger = logging.getLogger(__name__)
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error_type = type(e).__name__
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error_msg = str(e)
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logger.error(f"Error in auto_generate_ideas: {error_type}: {error_msg}", exc_info=True)
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logger.error(f"Unexpected error in auto_generate_ideas: {str(e)}", exc_info=True)
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return Response({
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'success': False,
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'error': f'Unexpected error: {error_msg}'
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'error': f'Unexpected error: {str(e)}'
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}, status=status.HTTP_500_INTERNAL_SERVER_ERROR)
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def list(self, request, *args, **kwargs):
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@@ -977,8 +980,8 @@ class ContentIdeasViewSet(SiteSectorModelViewSet):
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except (KombuOperationalError, ConnectionError) as e:
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# Celery connection failed - execute synchronously
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logger.warning(f"Celery connection failed, executing synchronously: {e}")
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from .tasks import _generate_single_idea_core
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result = _generate_single_idea_core(cluster_id, account_id=account_id, progress_callback=None)
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from igny8_core.ai.functions.generate_ideas import generate_ideas_core
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result = generate_ideas_core(cluster_id, account_id=account_id, progress_callback=None)
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if result.get('success'):
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return Response({
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'success': True,
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@@ -777,25 +777,72 @@ class IntegrationSettingsViewSet(viewsets.ViewSet):
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try:
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task_state = task.state
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except (ValueError, KeyError) as state_exc:
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# Task has malformed exception info - try to get error from result
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# Task has malformed exception info - try to get error from multiple sources
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logger.warning(f"Error accessing task.state (malformed exception info): {str(state_exc)}")
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error_msg = 'Task failed - exception details unavailable'
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error_type = 'UnknownError'
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request_steps = []
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response_steps = []
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# First, try to get from backend's stored meta (most reliable for our update_state calls)
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try:
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# Try to get error from task.result
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if hasattr(task, 'result'):
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result = task.result
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if isinstance(result, dict) and 'error' in result:
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error_msg = result['error']
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elif isinstance(result, str):
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error_msg = result
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except Exception:
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pass
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backend = task.backend
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if hasattr(backend, 'get_task_meta'):
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stored_meta = backend.get_task_meta(task_id)
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if stored_meta and isinstance(stored_meta, dict):
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meta = stored_meta.get('meta', {})
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if isinstance(meta, dict):
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if 'error' in meta:
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error_msg = meta.get('error')
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if 'error_type' in meta:
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error_type = meta.get('error_type', error_type)
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if 'request_steps' in meta:
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request_steps = meta.get('request_steps', [])
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if 'response_steps' in meta:
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response_steps = meta.get('response_steps', [])
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except Exception as e:
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logger.debug(f"Error getting from backend meta: {str(e)}")
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# Try to get error from task.result
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if error_msg == 'Task failed - exception details unavailable':
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try:
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if hasattr(task, 'result'):
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result = task.result
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if isinstance(result, dict):
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error_msg = result.get('error', error_msg)
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error_type = result.get('error_type', error_type)
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request_steps = result.get('request_steps', request_steps)
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response_steps = result.get('response_steps', response_steps)
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elif isinstance(result, str):
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error_msg = result
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except Exception as e:
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logger.debug(f"Error extracting error from task.result: {str(e)}")
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# Also try to get error from task.info
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if error_msg == 'Task failed - exception details unavailable':
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try:
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if hasattr(task, 'info') and task.info:
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if isinstance(task.info, dict):
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if 'error' in task.info:
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error_msg = task.info['error']
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if 'error_type' in task.info:
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error_type = task.info['error_type']
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if 'request_steps' in task.info:
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request_steps = task.info.get('request_steps', request_steps)
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if 'response_steps' in task.info:
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response_steps = task.info.get('response_steps', response_steps)
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except Exception as e:
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logger.debug(f"Error extracting error from task.info: {str(e)}")
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return Response({
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'state': 'FAILURE',
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'meta': {
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'error': error_msg,
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'error_type': error_type,
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'percentage': 0,
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'message': f'Error: {error_msg}',
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'request_steps': request_steps,
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'response_steps': response_steps,
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}
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})
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except (KombuOperationalError, RedisConnectionError, ConnectionError) as conn_exc:
|
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@@ -834,15 +881,29 @@ class IntegrationSettingsViewSet(viewsets.ViewSet):
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})
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# Safely get task info/result
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# Try to get error from task.result first (before it gets malformed)
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# Try to get error from multiple sources
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task_result = None
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task_info = None
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error_message = None
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error_type = None
|
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|
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# First, try to get from backend's stored meta (most reliable for our update_state calls)
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try:
|
||||
backend = task.backend
|
||||
if hasattr(backend, 'get_task_meta'):
|
||||
stored_meta = backend.get_task_meta(task_id)
|
||||
if stored_meta and isinstance(stored_meta, dict):
|
||||
meta = stored_meta.get('meta', {})
|
||||
if isinstance(meta, dict):
|
||||
if 'error' in meta:
|
||||
error_message = meta.get('error')
|
||||
error_type = meta.get('error_type', 'UnknownError')
|
||||
except Exception as backend_err:
|
||||
logger.debug(f"Could not get from backend meta: {backend_err}")
|
||||
|
||||
try:
|
||||
# Try to get result first - this often has the actual error
|
||||
if hasattr(task, 'result'):
|
||||
if not error_message and hasattr(task, 'result'):
|
||||
try:
|
||||
task_result = task.result
|
||||
# If result is a dict with error, extract it
|
||||
@@ -850,6 +911,9 @@ class IntegrationSettingsViewSet(viewsets.ViewSet):
|
||||
if 'error' in task_result:
|
||||
error_message = task_result.get('error')
|
||||
error_type = task_result.get('error_type', 'UnknownError')
|
||||
elif 'success' in task_result and not task_result.get('success'):
|
||||
error_message = task_result.get('error', 'Task failed')
|
||||
error_type = task_result.get('error_type', 'UnknownError')
|
||||
except Exception:
|
||||
pass # Will try task.info next
|
||||
except Exception:
|
||||
@@ -971,6 +1035,25 @@ class IntegrationSettingsViewSet(viewsets.ViewSet):
|
||||
else:
|
||||
error_message = str(error_info) if error_info else 'Task failed'
|
||||
|
||||
# If still no error message, try to get from task backend directly
|
||||
if not error_message:
|
||||
try:
|
||||
# Try to get from backend's stored result
|
||||
backend = task.backend
|
||||
if hasattr(backend, 'get'):
|
||||
stored = backend.get(task_id)
|
||||
if stored and isinstance(stored, dict):
|
||||
if 'error' in stored:
|
||||
error_message = stored['error']
|
||||
elif isinstance(stored.get('result'), dict) and 'error' in stored['result']:
|
||||
error_message = stored['result']['error']
|
||||
except Exception as backend_err:
|
||||
logger.warning(f"Error getting from backend: {backend_err}")
|
||||
|
||||
# Final fallback
|
||||
if not error_message:
|
||||
error_message = 'Task failed - check backend logs for details'
|
||||
|
||||
response_meta = {
|
||||
'error': error_message,
|
||||
'percentage': 0,
|
||||
@@ -992,6 +1075,13 @@ class IntegrationSettingsViewSet(viewsets.ViewSet):
|
||||
# Also include error_type if available in meta
|
||||
if 'error_type' in meta and not error_type:
|
||||
response_meta['error_type'] = meta['error_type']
|
||||
# Also check for error in meta directly
|
||||
if 'error' in meta and not error_message:
|
||||
error_message = meta['error']
|
||||
response_meta['error'] = error_message
|
||||
if 'error_type' in meta and not error_type:
|
||||
error_type = meta['error_type']
|
||||
response_meta['error_type'] = error_type
|
||||
|
||||
return Response({
|
||||
'state': task_state,
|
||||
|
||||
@@ -0,0 +1,35 @@
|
||||
# Generated migration for adding SEO fields to Tasks model
|
||||
|
||||
from django.db import migrations, models
|
||||
|
||||
|
||||
class Migration(migrations.Migration):
|
||||
|
||||
dependencies = [
|
||||
('writer', '0003_alter_content_options_alter_images_options_and_more'),
|
||||
('igny8_core_auth', '0008_passwordresettoken_alter_industry_options_and_more'),
|
||||
]
|
||||
|
||||
operations = [
|
||||
migrations.AddField(
|
||||
model_name='tasks',
|
||||
name='primary_keyword',
|
||||
field=models.CharField(blank=True, max_length=255, null=True),
|
||||
),
|
||||
migrations.AddField(
|
||||
model_name='tasks',
|
||||
name='secondary_keywords',
|
||||
field=models.JSONField(blank=True, default=list, help_text='List of secondary keywords'),
|
||||
),
|
||||
migrations.AddField(
|
||||
model_name='tasks',
|
||||
name='tags',
|
||||
field=models.JSONField(blank=True, default=list, help_text='List of tags'),
|
||||
),
|
||||
migrations.AddField(
|
||||
model_name='tasks',
|
||||
name='categories',
|
||||
field=models.JSONField(blank=True, default=list, help_text='List of categories'),
|
||||
),
|
||||
]
|
||||
|
||||
@@ -65,6 +65,10 @@ class Tasks(SiteSectorBaseModel):
|
||||
# SEO fields
|
||||
meta_title = models.CharField(max_length=255, blank=True, null=True)
|
||||
meta_description = models.TextField(blank=True, null=True)
|
||||
primary_keyword = models.CharField(max_length=255, blank=True, null=True)
|
||||
secondary_keywords = models.JSONField(default=list, blank=True, help_text="List of secondary keywords")
|
||||
tags = models.JSONField(default=list, blank=True, help_text="List of tags")
|
||||
categories = models.JSONField(default=list, blank=True, help_text="List of categories")
|
||||
|
||||
# WordPress integration
|
||||
assigned_post_id = models.IntegerField(null=True, blank=True) # WordPress post ID if published
|
||||
|
||||
@@ -8,6 +8,8 @@ from django.db import transaction
|
||||
from igny8_core.modules.writer.models import Tasks, Images, Content
|
||||
from igny8_core.utils.ai_processor import ai_processor
|
||||
from igny8_core.modules.system.utils import get_prompt_value, get_default_prompt
|
||||
from igny8_core.ai.functions.generate_content import generate_content_core
|
||||
from igny8_core.ai.functions.generate_images import generate_images_core
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
Reference in New Issue
Block a user