feat: Implement WordPress publishing and unpublishing actions
- Added conditional visibility for table actions based on content state (published/draft). - Introduced `publishContent` and `unpublishContent` API functions for handling WordPress integration. - Updated `Content` component to manage publish/unpublish actions with appropriate error handling and success notifications. - Refactored `PostEditor` to remove deprecated SEO fields and consolidate taxonomy management. - Enhanced `TablePageTemplate` to filter row actions based on visibility conditions. - Updated backend API to support publishing and unpublishing content with proper status updates and external references.
This commit is contained in:
alorig
@@ -1,13 +1,13 @@
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"""
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Generate Content AI Function
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Extracted from modules/writer/tasks.py
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STAGE 3: Updated to use final Stage 1 Content schema
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"""
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import logging
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import re
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from typing import Dict, List, Any
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from django.db import transaction
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from igny8_core.ai.base import BaseAIFunction
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from igny8_core.modules.writer.models import Tasks, Content as TaskContent
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from igny8_core.modules.writer.models import Tasks, Content
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from igny8_core.ai.ai_core import AICore
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from igny8_core.ai.validators import validate_tasks_exist
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from igny8_core.ai.prompts import PromptRegistry
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@@ -62,11 +62,10 @@ class GenerateContentFunction(BaseAIFunction):
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if account:
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queryset = queryset.filter(account=account)
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# Preload all relationships to avoid N+1 queries
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# Stage 3: Include taxonomy and keyword_objects for metadata
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# STAGE 3: Preload relationships - taxonomy_term instead of taxonomy
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tasks = list(queryset.select_related(
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'account', 'site', 'sector', 'cluster', 'idea', 'taxonomy'
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).prefetch_related('keyword_objects'))
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'account', 'site', 'sector', 'cluster', 'taxonomy_term'
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).prefetch_related('keywords'))
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if not tasks:
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raise ValueError("No tasks found")
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@@ -74,9 +73,8 @@ class GenerateContentFunction(BaseAIFunction):
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return tasks
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def build_prompt(self, data: Any, account=None) -> str:
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"""Build content generation prompt for a single task using registry"""
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"""STAGE 3: Build content generation prompt using final Task schema"""
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if isinstance(data, list):
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# For now, handle single task (will be called per task)
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if not data:
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raise ValueError("No tasks provided")
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task = data[0]
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@@ -90,33 +88,9 @@ class GenerateContentFunction(BaseAIFunction):
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if task.description:
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idea_data += f"Description: {task.description}\n"
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# Handle idea description (might be JSON or plain text)
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if task.idea and task.idea.description:
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description = task.idea.description
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try:
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import json
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parsed_desc = json.loads(description)
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if isinstance(parsed_desc, dict):
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formatted_desc = "Content Outline:\n\n"
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if 'H2' in parsed_desc:
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for h2_section in parsed_desc['H2']:
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formatted_desc += f"## {h2_section.get('heading', '')}\n"
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if 'subsections' in h2_section:
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for h3_section in h2_section['subsections']:
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formatted_desc += f"### {h3_section.get('subheading', '')}\n"
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formatted_desc += f"Content Type: {h3_section.get('content_type', '')}\n"
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formatted_desc += f"Details: {h3_section.get('details', '')}\n\n"
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description = formatted_desc
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except (json.JSONDecodeError, TypeError):
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pass # Use as plain text
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idea_data += f"Outline: {description}\n"
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if task.idea:
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idea_data += f"Structure: {task.idea.content_structure or task.content_structure or 'blog_post'}\n"
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idea_data += f"Type: {task.idea.content_type or task.content_type or 'blog_post'}\n"
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if task.idea.estimated_word_count:
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idea_data += f"Estimated Word Count: {task.idea.estimated_word_count}\n"
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# Add content type and structure from task
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idea_data += f"Content Type: {task.content_type or 'post'}\n"
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idea_data += f"Content Structure: {task.content_structure or 'article'}\n"
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# Build cluster data string
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cluster_data = ''
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@@ -124,56 +98,21 @@ class GenerateContentFunction(BaseAIFunction):
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cluster_data = f"Cluster Name: {task.cluster.name or ''}\n"
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if task.cluster.description:
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cluster_data += f"Description: {task.cluster.description}\n"
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cluster_data += f"Status: {task.cluster.status or 'active'}\n"
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# Stage 3: Build cluster role context
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cluster_role_data = ''
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if hasattr(task, 'cluster_role') and task.cluster_role:
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role_descriptions = {
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'hub': 'Hub Page - Main authoritative resource for this topic cluster. Should be comprehensive, overview-focused, and link to supporting content.',
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'supporting': 'Supporting Page - Detailed content that supports the hub page. Focus on specific aspects, use cases, or subtopics.',
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'attribute': 'Attribute Page - Content focused on specific attributes, features, or specifications. Include detailed comparisons and specifications.',
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}
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role_desc = role_descriptions.get(task.cluster_role, f'Role: {task.cluster_role}')
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cluster_role_data = f"Cluster Role: {role_desc}\n"
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# Stage 3: Build taxonomy context
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# STAGE 3: Build taxonomy context (from taxonomy_term FK)
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taxonomy_data = ''
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if hasattr(task, 'taxonomy') and task.taxonomy:
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taxonomy_data = f"Taxonomy: {task.taxonomy.name or ''}\n"
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if task.taxonomy.taxonomy_type:
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taxonomy_data += f"Taxonomy Type: {task.taxonomy.get_taxonomy_type_display() or task.taxonomy.taxonomy_type}\n"
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if task.taxonomy.description:
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taxonomy_data += f"Description: {task.taxonomy.description}\n"
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if task.taxonomy_term:
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taxonomy_data = f"Taxonomy: {task.taxonomy_term.name or ''}\n"
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if task.taxonomy_term.taxonomy_type:
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taxonomy_data += f"Type: {task.taxonomy_term.get_taxonomy_type_display()}\n"
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# Stage 3: Build attributes context from keywords
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attributes_data = ''
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if hasattr(task, 'keyword_objects') and task.keyword_objects.exists():
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attribute_list = []
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for keyword in task.keyword_objects.all():
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if hasattr(keyword, 'attribute_values') and keyword.attribute_values:
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if isinstance(keyword.attribute_values, dict):
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for attr_name, attr_value in keyword.attribute_values.items():
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attribute_list.append(f"{attr_name}: {attr_value}")
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elif isinstance(keyword.attribute_values, list):
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for attr_item in keyword.attribute_values:
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if isinstance(attr_item, dict):
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for attr_name, attr_value in attr_item.items():
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attribute_list.append(f"{attr_name}: {attr_value}")
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else:
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attribute_list.append(str(attr_item))
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if attribute_list:
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attributes_data = "Product/Service Attributes:\n"
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attributes_data += "\n".join(f"- {attr}" for attr in attribute_list) + "\n"
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# Build keywords string
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keywords_data = task.keywords or ''
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if not keywords_data and task.idea:
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keywords_data = task.idea.target_keywords or ''
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# STAGE 3: Build keywords context (from keywords M2M)
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keywords_data = ''
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if task.keywords.exists():
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keyword_list = [kw.keyword for kw in task.keywords.all()]
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keywords_data = "Keywords: " + ", ".join(keyword_list) + "\n"
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# Get prompt from registry with context
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# Stage 3: Include cluster_role, taxonomy, and attributes in context
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prompt = PromptRegistry.get_prompt(
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function_name='generate_content',
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account=account,
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@@ -181,9 +120,7 @@ class GenerateContentFunction(BaseAIFunction):
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context={
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'IDEA': idea_data,
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'CLUSTER': cluster_data,
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'CLUSTER_ROLE': cluster_role_data,
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'TAXONOMY': taxonomy_data,
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'ATTRIBUTES': attributes_data,
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'KEYWORDS': keywords_data,
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}
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)
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@@ -222,7 +159,10 @@ class GenerateContentFunction(BaseAIFunction):
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progress_tracker=None,
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step_tracker=None
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) -> Dict:
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"""Save content to task - handles both JSON and plain text responses"""
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"""
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STAGE 3: Save content using final Stage 1 Content model schema.
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Creates independent Content record (no OneToOne to Task).
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"""
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if isinstance(original_data, list):
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task = original_data[0] if original_data else None
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else:
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@@ -236,113 +176,50 @@ class GenerateContentFunction(BaseAIFunction):
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# JSON response with structured fields
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content_html = parsed.get('content', '')
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title = parsed.get('title') or task.title
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meta_title = parsed.get('meta_title') or title or task.title
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meta_description = parsed.get('meta_description', '')
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word_count = parsed.get('word_count', 0)
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primary_keyword = parsed.get('primary_keyword', '')
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secondary_keywords = parsed.get('secondary_keywords', [])
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tags = parsed.get('tags', [])
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categories = parsed.get('categories', [])
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# Content status should always be 'draft' for newly generated content
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# Status can only be changed manually to 'review' or 'publish'
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content_status = 'draft'
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else:
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# Plain text response (legacy)
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# Plain text response
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content_html = str(parsed)
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title = task.title
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meta_title = task.meta_title or task.title
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meta_description = task.meta_description or (task.description or '')[:160] if task.description else ''
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word_count = 0
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primary_keyword = ''
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secondary_keywords = []
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tags = []
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categories = []
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content_status = 'draft'
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# Calculate word count if not provided
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if not word_count and content_html:
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# Calculate word count
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word_count = 0
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if content_html:
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text_for_counting = re.sub(r'<[^>]+>', '', content_html)
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word_count = len(text_for_counting.split())
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# Ensure related content record exists
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content_record, _created = TaskContent.objects.get_or_create(
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task=task,
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defaults={
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'account': task.account,
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'site': task.site,
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'sector': task.sector,
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'html_content': content_html or '',
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'word_count': word_count or 0,
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'status': 'draft',
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},
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# STAGE 3: Create independent Content record using final schema
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content_record = Content.objects.create(
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# Core fields
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title=title,
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content_html=content_html or '',
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cluster=task.cluster,
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content_type=task.content_type,
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content_structure=task.content_structure,
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# Source and status
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source='igny8',
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status='draft',
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# Site/Sector/Account
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account=task.account,
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site=task.site,
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sector=task.sector,
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)
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# Update content fields
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if content_html:
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content_record.html_content = content_html
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content_record.word_count = word_count or content_record.word_count or 0
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content_record.title = title
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content_record.meta_title = meta_title
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content_record.meta_description = meta_description
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content_record.primary_keyword = primary_keyword or ''
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if isinstance(secondary_keywords, list):
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content_record.secondary_keywords = secondary_keywords
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elif secondary_keywords:
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content_record.secondary_keywords = [secondary_keywords]
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else:
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content_record.secondary_keywords = []
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if isinstance(tags, list):
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content_record.tags = tags
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elif tags:
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content_record.tags = [tags]
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else:
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content_record.tags = []
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if isinstance(categories, list):
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content_record.categories = categories
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elif categories:
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content_record.categories = [categories]
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else:
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content_record.categories = []
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# Always set status to 'draft' for newly generated content
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# Status can only be: draft, review, published (changed manually)
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content_record.status = 'draft'
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# Merge any extra fields into metadata (non-standard keys)
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if isinstance(parsed, dict):
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excluded_keys = {
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'content',
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'title',
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'meta_title',
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'meta_description',
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'primary_keyword',
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'secondary_keywords',
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'tags',
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'categories',
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'word_count',
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'status',
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}
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extra_meta = {k: v for k, v in parsed.items() if k not in excluded_keys}
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existing_meta = content_record.metadata or {}
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existing_meta.update(extra_meta)
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content_record.metadata = existing_meta
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# Align foreign keys to ensure consistency
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content_record.account = task.account
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content_record.site = task.site
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content_record.sector = task.sector
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content_record.task = task
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content_record.save()
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# Update task status - keep task data intact but mark as completed
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# Link taxonomy terms from task if available
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if task.taxonomy_term:
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content_record.taxonomy_terms.add(task.taxonomy_term)
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# Link all keywords from task as taxonomy terms (if they have taxonomy mappings)
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# This is optional - keywords are M2M on Task, not directly on Content
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# STAGE 3: Update task status to completed
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task.status = 'completed'
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task.save(update_fields=['status', 'updated_at'])
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return {
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'count': 1,
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'tasks_updated': 1,
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'word_count': content_record.word_count,
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'content_id': content_record.id,
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'task_id': task.id,
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'word_count': word_count,
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}
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