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Automation final fixes

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IGNY8 VPS (Salman)
2025-12-28 20:37:46 +00:00
parent 7f82ef4551
commit 748de099dd
8 changed files with 292 additions and 144 deletions
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152
backend/igny8_core/business/automation/services/automation_service.py
View File

@@ -225,9 +225,21 @@ class AutomationService:
clusters_created = 0
batches_run = 0
credits_before = self._get_credits_used()
keyword_ids = list(pending_keywords.values_list('id', flat=True))
# INITIAL SAVE: Set keywords_total immediately so frontend shows accurate counts from start
self.run.stage_1_result = {
'keywords_processed': 0,
'keywords_total': len(keyword_ids),
'clusters_created': 0,
'batches_run': 0,
'credits_used': 0,
'time_elapsed': '0m 0s',
'in_progress': True
}
self.run.save(update_fields=['stage_1_result'])
for i in range(0, len(keyword_ids), actual_batch_size):
# Check if automation should stop (paused or cancelled)
should_stop, reason = self._check_should_stop()
@@ -262,19 +274,21 @@ class AutomationService:
stage_number, f"Processing batch {batch_num}/{total_batches} ({len(batch)} keywords)"
)
# Call AI function via AIEngine
# Call AI function via AIEngine (runs synchronously - no Celery subtask)
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)
# NOTE: AIEngine.execute() runs synchronously and returns immediately
# No Celery task polling needed
if not result.get('success'):
error_msg = result.get('error', 'Unknown error')
logger.warning(f"[AutomationService] Clustering failed for batch {batch_num}: {error_msg}")
# Continue to next batch
keywords_processed += len(batch)
batches_run += 1
@@ -450,8 +464,21 @@ class AutomationService:
# Process one at a time
clusters_processed = 0
credits_before = self._get_credits_used()
for cluster in pending_clusters:
# INITIAL SAVE: Set clusters_total immediately so frontend shows accurate counts from start
cluster_list = list(pending_clusters)
total_clusters = len(cluster_list)
self.run.stage_2_result = {
'clusters_processed': 0,
'clusters_total': total_clusters,
'ideas_created': 0,
'credits_used': 0,
'time_elapsed': '0m 0s',
'in_progress': True
}
self.run.save(update_fields=['stage_2_result'])
for cluster in cluster_list:
# Check if automation should stop (paused or cancelled)
should_stop, reason = self._check_should_stop()
if should_stop:
@@ -485,19 +512,21 @@ class AutomationService:
stage_number, f"Generating ideas for cluster: {cluster.name}"
)
# Call AI function via AIEngine
# Call AI function via AIEngine (runs synchronously - no Celery subtask)
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)
# NOTE: AIEngine.execute() runs synchronously and returns immediately
# No Celery task polling needed
if not result.get('success'):
error_msg = result.get('error', 'Unknown error')
logger.warning(f"[AutomationService] Idea generation failed for cluster '{cluster.name}': {error_msg}")
# Continue to next cluster
clusters_processed += 1
self.logger.log_stage_progress(
@@ -792,11 +821,22 @@ class AutomationService:
# Process one at a time
tasks_processed = 0
credits_before = self._get_credits_used()
# FIXED: Ensure ALL tasks are processed by iterating over queryset list
task_list = list(pending_tasks)
total_tasks = len(task_list)
# INITIAL SAVE: Set tasks_total immediately so frontend shows accurate counts from start
self.run.stage_4_result = {
'tasks_processed': 0,
'tasks_total': total_tasks,
'content_created': 0,
'credits_used': 0,
'time_elapsed': '0m 0s',
'in_progress': True
}
self.run.save(update_fields=['stage_4_result'])
for idx, task in enumerate(task_list, 1):
# Check if automation should stop (paused or cancelled)
should_stop, reason = self._check_should_stop()
@@ -831,19 +871,22 @@ class AutomationService:
stage_number, f"Generating content for task {idx}/{total_tasks}: {task.title}"
)
# Call AI function via AIEngine
# Call AI function via AIEngine (runs synchronously - no Celery subtask)
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)
# NOTE: AIEngine.execute() runs synchronously and returns immediately
# The result contains 'task_id' which is the DB Task model ID, NOT a Celery task ID
# So we do NOT call _wait_for_task here
if not result.get('success'):
error_msg = result.get('error', 'Unknown error')
logger.warning(f"[AutomationService] Content generation failed for task '{task.title}': {error_msg}")
# Continue to next task
tasks_processed += 1
# Log progress
@@ -1025,10 +1068,21 @@ class AutomationService:
# Process one at a time
content_processed = 0
credits_before = self._get_credits_used()
content_list = list(content_without_images)
total_content = len(content_list)
# INITIAL SAVE: Set content_total immediately so frontend shows accurate counts from start
self.run.stage_5_result = {
'content_processed': 0,
'content_total': total_content,
'prompts_created': 0,
'credits_used': 0,
'time_elapsed': '0m 0s',
'in_progress': True
}
self.run.save(update_fields=['stage_5_result'])
for idx, content in enumerate(content_list, 1):
# Check if automation should stop (paused or cancelled)
should_stop, reason = self._check_should_stop()
@@ -1063,19 +1117,21 @@ class AutomationService:
stage_number, f"Extracting prompts {idx}/{total_content}: {content.title}"
)
# Call AI function via AIEngine
# Call AI function via AIEngine (runs synchronously - no Celery subtask)
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)
# NOTE: AIEngine.execute() runs synchronously and returns immediately
# No Celery task polling needed
if not result.get('success'):
error_msg = result.get('error', 'Unknown error')
logger.warning(f"[AutomationService] Image prompt generation failed for content '{content.title}': {error_msg}")
# Continue to next content
content_processed += 1
self.logger.log_stage_progress(
@@ -1199,10 +1255,22 @@ class AutomationService:
# Process one at a time
images_processed = 0
credits_before = self._get_credits_used()
image_list = list(pending_images)
total_images = len(image_list)
# INITIAL SAVE: Set images_total immediately so frontend shows accurate counts from start
self.run.stage_6_result = {
'images_processed': 0,
'images_total': total_images,
'images_generated': 0,
'content_moved_to_review': 0,
'credits_used': 0,
'time_elapsed': '0m 0s',
'in_progress': True
}
self.run.save(update_fields=['stage_6_result'])
for idx, image in enumerate(image_list, 1):
# Check if automation should stop (paused or cancelled)
should_stop, reason = self._check_should_stop()

11
backend/igny8_core/business/content/models.py
View File

@@ -675,3 +675,14 @@ class ContentAttribute(SiteSectorBaseModel):
# Backward compatibility alias
ContentAttributeMap = ContentAttribute
class ImagePrompts(Images):
"""
Proxy model for Images to provide a separate admin interface focused on prompts.
This allows a dedicated "Image Prompts" view in the admin sidebar.
"""
class Meta:
proxy = True
verbose_name = 'Image Prompt'
verbose_name_plural = 'Image Prompts'
app_label = 'writer'