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IGNY8 VPS (Salman)
2025-12-04 09:10:51 +00:00
parent c36b70f31f
commit a8c572a996
2 changed files with 240 additions and 133 deletions
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367
backend/igny8_core/business/automation/services/automation_service.py
View File

@@ -159,35 +159,47 @@ class AutomationService:
keyword_ids = list(pending_keywords.values_list('id', flat=True))
for i in range(0, len(keyword_ids), actual_batch_size):
batch = keyword_ids[i:i + actual_batch_size]
batch_num = (i // actual_batch_size) + 1
total_batches = (len(keyword_ids) + actual_batch_size - 1) // actual_batch_size
self.logger.log_stage_progress(
self.run.run_id, self.account.id, self.site.id,
stage_number, f"Processing batch {batch_num}/{total_batches} ({len(batch)} keywords)"
)
# Call AI function via AIEngine
engine = AIEngine(account=self.account)
result = engine.execute(
fn=AutoClusterFunction(),
payload={'ids': batch}
)
# Monitor task
task_id = result.get('task_id')
if task_id:
self._wait_for_task(task_id, stage_number, f"Batch {batch_num}")
keywords_processed += len(batch)
batches_run += 1
# Log progress
self.logger.log_stage_progress(
self.run.run_id, self.account.id, self.site.id,
stage_number, f"Batch {batch_num} complete"
)
try:
batch = keyword_ids[i:i + actual_batch_size]
batch_num = (i // actual_batch_size) + 1
total_batches = (len(keyword_ids) + actual_batch_size - 1) // actual_batch_size
self.logger.log_stage_progress(
self.run.run_id, self.account.id, self.site.id,
stage_number, f"Processing batch {batch_num}/{total_batches} ({len(batch)} keywords)"
)
# Call AI function via AIEngine
engine = AIEngine(account=self.account)
result = engine.execute(
fn=AutoClusterFunction(),
payload={'ids': batch}
)
# Monitor task
task_id = result.get('task_id')
if task_id:
# FIXED: Pass continue_on_error=True to keep processing other batches on failure
self._wait_for_task(task_id, stage_number, f"Batch {batch_num}", continue_on_error=True)
keywords_processed += len(batch)
batches_run += 1
# Log progress
self.logger.log_stage_progress(
self.run.run_id, self.account.id, self.site.id,
stage_number, f"Batch {batch_num} complete"
)
except Exception as e:
# FIXED: Log error but continue processing remaining batches
error_msg = f"Failed to process batch {batch_num}: {str(e)}"
logger.error(f"[AutomationService] {error_msg}", exc_info=True)
self.logger.log_stage_error(
self.run.run_id, self.account.id, self.site.id,
stage_number, error_msg
)
# Continue to next batch
continue
# ADDED: Within-stage delay (between batches)
if i + actual_batch_size < len(keyword_ids): # Not the last batch
@@ -315,29 +327,41 @@ class AutomationService:
credits_before = self._get_credits_used()
for cluster in pending_clusters:
self.logger.log_stage_progress(
self.run.run_id, self.account.id, self.site.id,
stage_number, f"Generating ideas for cluster: {cluster.name}"
)
# Call AI function via AIEngine
engine = AIEngine(account=self.account)
result = engine.execute(
fn=GenerateIdeasFunction(),
payload={'ids': [cluster.id]}
)
# Monitor task
task_id = result.get('task_id')
if task_id:
self._wait_for_task(task_id, stage_number, f"Cluster '{cluster.name}'")
clusters_processed += 1
self.logger.log_stage_progress(
self.run.run_id, self.account.id, self.site.id,
stage_number, f"Cluster '{cluster.name}' complete"
)
try:
self.logger.log_stage_progress(
self.run.run_id, self.account.id, self.site.id,
stage_number, f"Generating ideas for cluster: {cluster.name}"
)
# Call AI function via AIEngine
engine = AIEngine(account=self.account)
result = engine.execute(
fn=GenerateIdeasFunction(),
payload={'ids': [cluster.id]}
)
# Monitor task
task_id = result.get('task_id')
if task_id:
# FIXED: Pass continue_on_error=True to keep processing other clusters on failure
self._wait_for_task(task_id, stage_number, f"Cluster '{cluster.name}'", continue_on_error=True)
clusters_processed += 1
self.logger.log_stage_progress(
self.run.run_id, self.account.id, self.site.id,
stage_number, f"Cluster '{cluster.name}' complete"
)
except Exception as e:
# FIXED: Log error but continue processing remaining clusters
error_msg = f"Failed to generate ideas for cluster '{cluster.name}': {str(e)}"
logger.error(f"[AutomationService] {error_msg}", exc_info=True)
self.logger.log_stage_error(
self.run.run_id, self.account.id, self.site.id,
stage_number, error_msg
)
# Continue to next cluster
continue
# Get ideas created count
ideas_created = ContentIdeas.objects.filter(
@@ -575,30 +599,42 @@ class AutomationService:
total_tasks = len(task_list)
for idx, task in enumerate(task_list, 1):
self.logger.log_stage_progress(
self.run.run_id, self.account.id, self.site.id,
stage_number, f"Generating content for task {idx}/{total_tasks}: {task.title}"
)
# Call AI function via AIEngine
engine = AIEngine(account=self.account)
result = engine.execute(
fn=GenerateContentFunction(),
payload={'ids': [task.id]}
)
# Monitor task
task_id = result.get('task_id')
if task_id:
self._wait_for_task(task_id, stage_number, f"Task '{task.title}'")
tasks_processed += 1
# Log progress
self.logger.log_stage_progress(
self.run.run_id, self.account.id, self.site.id,
stage_number, f"Task '{task.title}' complete ({tasks_processed}/{total_tasks})"
)
try:
self.logger.log_stage_progress(
self.run.run_id, self.account.id, self.site.id,
stage_number, f"Generating content for task {idx}/{total_tasks}: {task.title}"
)
# Call AI function via AIEngine
engine = AIEngine(account=self.account)
result = engine.execute(
fn=GenerateContentFunction(),
payload={'ids': [task.id]}
)
# Monitor task
task_id = result.get('task_id')
if task_id:
# FIXED: Pass continue_on_error=True to keep processing other tasks on failure
self._wait_for_task(task_id, stage_number, f"Task '{task.title}'", continue_on_error=True)
tasks_processed += 1
# Log progress
self.logger.log_stage_progress(
self.run.run_id, self.account.id, self.site.id,
stage_number, f"Task '{task.title}' complete ({tasks_processed}/{total_tasks})"
)
except Exception as e:
# FIXED: Log error but continue processing remaining tasks
error_msg = f"Failed to process task '{task.title}': {str(e)}"
logger.error(f"[AutomationService] {error_msg}", exc_info=True)
self.logger.log_stage_error(
self.run.run_id, self.account.id, self.site.id,
stage_number, error_msg
)
# Continue to next task
continue
# ADDED: Within-stage delay between tasks (if not last task)
if idx < total_tasks:
@@ -739,29 +775,41 @@ class AutomationService:
total_content = len(content_list)
for idx, content in enumerate(content_list, 1):
self.logger.log_stage_progress(
self.run.run_id, self.account.id, self.site.id,
stage_number, f"Extracting prompts {idx}/{total_content}: {content.title}"
)
# Call AI function via AIEngine
engine = AIEngine(account=self.account)
result = engine.execute(
fn=GenerateImagePromptsFunction(),
payload={'ids': [content.id]}
)
# Monitor task
task_id = result.get('task_id')
if task_id:
self._wait_for_task(task_id, stage_number, f"Content '{content.title}'")
content_processed += 1
self.logger.log_stage_progress(
self.run.run_id, self.account.id, self.site.id,
stage_number, f"Content '{content.title}' complete ({content_processed}/{total_content})"
)
try:
self.logger.log_stage_progress(
self.run.run_id, self.account.id, self.site.id,
stage_number, f"Extracting prompts {idx}/{total_content}: {content.title}"
)
# Call AI function via AIEngine
engine = AIEngine(account=self.account)
result = engine.execute(
fn=GenerateImagePromptsFunction(),
payload={'ids': [content.id]}
)
# Monitor task
task_id = result.get('task_id')
if task_id:
# FIXED: Pass continue_on_error=True to keep processing other content on failure
self._wait_for_task(task_id, stage_number, f"Content '{content.title}'", continue_on_error=True)
content_processed += 1
self.logger.log_stage_progress(
self.run.run_id, self.account.id, self.site.id,
stage_number, f"Content '{content.title}' complete ({content_processed}/{total_content})"
)
except Exception as e:
# FIXED: Log error but continue processing remaining content
error_msg = f"Failed to extract prompts for content '{content.title}': {str(e)}"
logger.error(f"[AutomationService] {error_msg}", exc_info=True)
self.logger.log_stage_error(
self.run.run_id, self.account.id, self.site.id,
stage_number, error_msg
)
# Continue to next content
continue
# ADDED: Within-stage delay between content pieces
if idx < total_content:
@@ -874,30 +922,43 @@ class AutomationService:
total_images = len(image_list)
for idx, image in enumerate(image_list, 1):
content_title = image.content.title if image.content else 'Unknown'
self.logger.log_stage_progress(
self.run.run_id, self.account.id, self.site.id,
stage_number, f"Generating image {idx}/{total_images}: {image.image_type} for '{content_title}'"
)
# Call AI function via AIEngine
engine = AIEngine(account=self.account)
result = engine.execute(
fn=GenerateImagesFunction(),
payload={'image_ids': [image.id]}
)
# Monitor task
task_id = result.get('task_id')
if task_id:
self._wait_for_task(task_id, stage_number, f"Image for '{content_title}'")
images_processed += 1
self.logger.log_stage_progress(
self.run.run_id, self.account.id, self.site.id,
stage_number, f"Image generated for '{content_title}' ({images_processed}/{total_images})"
)
try:
content_title = image.content.title if image.content else 'Unknown'
self.logger.log_stage_progress(
self.run.run_id, self.account.id, self.site.id,
stage_number, f"Generating image {idx}/{total_images}: {image.image_type} for '{content_title}'"
)
# Call AI function via AIEngine
engine = AIEngine(account=self.account)
result = engine.execute(
fn=GenerateImagesFunction(),
payload={'image_ids': [image.id]}
)
# Monitor task
task_id = result.get('task_id')
if task_id:
# FIXED: Pass continue_on_error=True to keep processing other images on failure
self._wait_for_task(task_id, stage_number, f"Image for '{content_title}'", continue_on_error=True)
images_processed += 1
self.logger.log_stage_progress(
self.run.run_id, self.account.id, self.site.id,
stage_number, f"Image generated for '{content_title}' ({images_processed}/{total_images})"
)
except Exception as e:
# FIXED: Log error but continue processing remaining images
content_title = image.content.title if image.content else 'Unknown'
error_msg = f"Failed to generate image for content '{content_title}': {str(e)}"
logger.error(f"[AutomationService] {error_msg}", exc_info=True)
self.logger.log_stage_error(
self.run.run_id, self.account.id, self.site.id,
stage_number, error_msg
)
# Continue to next image
continue
# ADDED: Within-stage delay between images
if idx < total_images:
@@ -1042,12 +1103,42 @@ class AutomationService:
# Helper methods
def _wait_for_task(self, task_id: str, stage_number: int, item_name: str):
"""Wait for Celery task to complete"""
def _wait_for_task(self, task_id: str, stage_number: int, item_name: str, continue_on_error: bool = True):
"""Wait for Celery task to complete
Args:
task_id: Celery task ID
stage_number: Current stage number
item_name: Name of item being processed
continue_on_error: If True, log error but don't raise exception (default: True)
"""
result = AsyncResult(task_id)
while not result.ready():
# FIXED: Wrap result.ready() in try-catch to handle Celery backend errors
max_retries = 100 # Maximum polling attempts (100 * 3s = 5 minutes)
retry_count = 0
while retry_count < max_retries:
try:
is_ready = result.ready()
if is_ready:
break
except (TypeError, ValueError, Exception) as e:
# FIXED: Handle Celery backend errors (e.g., Redis key serialization issues)
logger.warning(f"[AutomationService] Celery backend error while checking task {task_id}: {e}")
# Wait a bit longer and try to get result directly
time.sleep(5)
try:
# Try to get the result status from database/backend
if result.state in ['SUCCESS', 'FAILURE']:
break
except Exception:
# If still failing, assume task is done and break
logger.warning(f"[AutomationService] Cannot determine task state, assuming complete")
break
time.sleep(3) # Poll every 3 seconds
retry_count += 1
# Check for pause
self.run.refresh_from_db()
@@ -1058,13 +1149,23 @@ class AutomationService:
time.sleep(5)
self.run.refresh_from_db()
if result.failed():
error_msg = f"Task failed for {item_name}"
self.logger.log_stage_error(
self.run.run_id, self.account.id, self.site.id,
stage_number, error_msg
)
raise Exception(error_msg)
# Check if task failed
try:
if result.failed():
error_msg = f"Task failed for {item_name}"
self.logger.log_stage_error(
self.run.run_id, self.account.id, self.site.id,
stage_number, error_msg
)
if not continue_on_error:
raise Exception(error_msg)
else:
logger.warning(f"[AutomationService] {error_msg} - continuing with next item")
except (TypeError, ValueError, Exception) as e:
# FIXED: If we can't determine task status due to backend error, log and continue
logger.warning(f"[AutomationService] Cannot determine task failure state for {item_name}: {e}")
if not continue_on_error:
raise
def _get_credits_used(self) -> int:
"""Get total credits used by this run so far"""

6
backend/igny8_core/settings.py
View File

@@ -501,6 +501,7 @@ JWT_ACCESS_TOKEN_EXPIRY = timedelta(minutes=15)
JWT_REFRESH_TOKEN_EXPIRY = timedelta(days=30) # Extended to 30 days for persistent login
# Celery Configuration
# FIXED: Use redis:// URL with explicit string parameters to avoid Celery backend key serialization issues
CELERY_BROKER_URL = os.getenv('CELERY_BROKER_URL', f"redis://{os.getenv('REDIS_HOST', 'redis')}:{os.getenv('REDIS_PORT', '6379')}/0")
CELERY_RESULT_BACKEND = os.getenv('CELERY_RESULT_BACKEND', f"redis://{os.getenv('REDIS_HOST', 'redis')}:{os.getenv('REDIS_PORT', '6379')}/0")
CELERY_ACCEPT_CONTENT = ['json']
@@ -513,6 +514,11 @@ CELERY_TASK_TIME_LIMIT = 30 * 60 # 30 minutes
CELERY_TASK_SOFT_TIME_LIMIT = 25 * 60 # 25 minutes
CELERY_WORKER_PREFETCH_MULTIPLIER = 1
CELERY_WORKER_MAX_TASKS_PER_CHILD = 1000
# FIXED: Add explicit backend options to prevent key serialization issues
CELERY_RESULT_BACKEND_TRANSPORT_OPTIONS = {
'master_name': 'mymaster'
} if os.getenv('REDIS_SENTINEL_ENABLED', 'false').lower() == 'true' else {}
CELERY_REDIS_BACKEND_USE_SSL = os.getenv('REDIS_SSL_ENABLED', 'false').lower() == 'true'
# Publish/Sync Logging Configuration
PUBLISH_SYNC_LOG_DIR = os.path.join(BASE_DIR, 'logs', 'publish-sync-logs')