Implement V2 AI functions and enhance progress handling
- Added support for new V2 functions: `auto_cluster_v2` and `generate_ideas_v2`, including backend logic and API endpoints. - Updated model configuration to ensure V2 functions validate the presence of models before execution. - Enhanced progress modal to provide better feedback during asynchronous tasks, including task IDs for debugging. - Updated frontend components to integrate new V2 functionalities and improve user experience with clustering and idea generation.
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"""
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Auto Cluster Keywords V2 - Workflow Function
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Uses helpers folder imports and dynamic model loading
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Max 50 keywords for bulk actions
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"""
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import logging
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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.helpers.base import BaseAIFunction
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from igny8_core.modules.planner.models import Keywords, Clusters
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from igny8_core.ai.helpers.ai_core import AICore
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from igny8_core.ai.prompts import PromptRegistry
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from igny8_core.ai.helpers.settings import get_model_config
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logger = logging.getLogger(__name__)
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class AutoClusterV2Function(BaseAIFunction):
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"""Auto-cluster keywords using AI - V2 with dynamic model"""
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def get_name(self) -> str:
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return 'auto_cluster_v2'
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def get_metadata(self) -> Dict:
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return {
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'display_name': 'Keywords Clustering',
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'description': 'Group related keywords into semantic clusters',
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'phases': {
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'INIT': 'Validating keywords...',
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'PREP': 'Loading keyword data...',
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'AI_CALL': 'Analyzing relationships with AI...',
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'PARSE': 'Processing cluster results...',
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'SAVE': 'Creating clusters...',
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'DONE': 'Clustering completed successfully'
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}
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}
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def get_max_items(self) -> int:
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return 50 # Max 50 keywords
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def validate(self, payload: dict, account=None) -> Dict:
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"""Validate input with max 50 keywords"""
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ids = payload.get('ids', [])
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if not ids:
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return {'valid': False, 'error': 'No keywords selected'}
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if len(ids) > 50:
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return {'valid': False, 'error': 'Maximum 50 keywords allowed for clustering'}
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# Check keywords exist
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queryset = Keywords.objects.filter(id__in=ids)
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if account:
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queryset = queryset.filter(account=account)
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keywords = queryset
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if keywords.count() != len(ids):
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return {'valid': False, 'error': 'Some selected keywords not found'}
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return {'valid': True}
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def prepare(self, payload: dict, account=None) -> Dict:
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"""Load keywords with relationships"""
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ids = payload.get('ids', [])
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sector_id = payload.get('sector_id')
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queryset = Keywords.objects.filter(id__in=ids)
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if account:
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queryset = queryset.filter(account=account)
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if sector_id:
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queryset = queryset.filter(sector_id=sector_id)
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keywords = list(queryset.select_related('seed_keyword', 'cluster', 'account', 'site', 'sector'))
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if not keywords:
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raise ValueError("No keywords found")
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keyword_data = []
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for kw in keywords:
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keyword_data.append({
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'id': kw.id,
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'keyword': kw.keyword,
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'volume': kw.volume,
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'difficulty': kw.difficulty,
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'intent': kw.seed_keyword.intent if kw.seed_keyword else None,
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})
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return {
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'keywords': keywords, # Store original objects
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'keyword_data': keyword_data,
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'sector_id': sector_id
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}
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def build_prompt(self, data: Dict, account=None) -> str:
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"""Build clustering prompt"""
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keyword_data = data.get('keyword_data', [])
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sector_id = data.get('sector_id')
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# Format keywords
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keywords_text = '\n'.join([
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f"- {kw['keyword']} (Volume: {kw['volume']}, Difficulty: {kw['difficulty']}, Intent: {kw.get('intent', 'N/A')})"
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for kw in keyword_data
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])
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# Build context
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context = {'KEYWORDS': keywords_text}
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# Add sector context if available
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if sector_id:
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try:
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from igny8_core.auth.models import Sector
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sector = Sector.objects.get(id=sector_id)
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if sector:
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context['SECTOR'] = sector.name
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except Exception:
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pass
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# Get prompt from registry
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prompt = PromptRegistry.get_prompt(
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function_name='auto_cluster',
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account=account,
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context=context
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)
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# Ensure JSON format instruction
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prompt_lower = prompt.lower()
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has_json_request = (
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'json' in prompt_lower and
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('format' in prompt_lower or 'respond' in prompt_lower or 'return' in prompt_lower or 'output' in prompt_lower)
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)
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if not has_json_request:
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prompt += "\n\nIMPORTANT: You must respond with valid JSON only. The response must be a JSON object with a 'clusters' array."
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return prompt
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def parse_response(self, response: str, step_tracker=None) -> List[Dict]:
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"""Parse AI response into cluster data"""
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if not response or not response.strip():
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raise ValueError("Empty response from AI")
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ai_core = AICore(account=getattr(self, 'account', None))
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json_data = ai_core.extract_json(response)
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if not json_data or 'clusters' not in json_data:
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raise ValueError("Invalid response format: missing 'clusters' array")
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return json_data['clusters']
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def save_output(self, parsed: List[Dict], original_data: Any, account=None, step_tracker=None) -> Dict:
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"""Save clusters and update keywords"""
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keywords = original_data.get('keywords', [])
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keyword_map = {kw.id: kw for kw in keywords}
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clusters_created = 0
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keywords_updated = 0
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with transaction.atomic():
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for cluster_data in parsed:
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cluster_name = cluster_data.get('name', 'Unnamed Cluster')
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cluster_keywords = cluster_data.get('keywords', [])
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if not cluster_keywords:
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continue
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# Create cluster
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cluster = Clusters.objects.create(
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name=cluster_name,
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description=f"Auto-clustered from {len(cluster_keywords)} keywords",
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account=account,
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status='active'
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)
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clusters_created += 1
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# Update keywords
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for keyword_text in cluster_keywords:
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for kw in keywords:
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if kw.keyword.lower() == keyword_text.lower():
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kw.cluster = cluster
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kw.save()
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keywords_updated += 1
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break
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return {
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'clusters_created': clusters_created,
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'keywords_updated': keywords_updated,
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'count': clusters_created
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}
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@@ -0,0 +1,152 @@
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"""
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Generate Ideas V2 - Workflow Function
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Single cluster only, uses helpers folder imports
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"""
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import logging
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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.helpers.base import BaseAIFunction
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from igny8_core.modules.planner.models import Clusters, ContentIdeas, Keywords
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from igny8_core.ai.helpers.ai_core import AICore
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from igny8_core.ai.prompts import PromptRegistry
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from igny8_core.ai.helpers.settings import get_model_config
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logger = logging.getLogger(__name__)
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class GenerateIdeasV2Function(BaseAIFunction):
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"""Generate content ideas from cluster - V2 with dynamic model"""
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def get_name(self) -> str:
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return 'generate_ideas_v2'
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def get_metadata(self) -> Dict:
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return {
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'display_name': 'Generate Ideas',
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'description': 'Generate SEO-optimized content ideas from keyword cluster',
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'phases': {
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'INIT': 'Validating cluster...',
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'PREP': 'Loading cluster data...',
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'AI_CALL': 'Generating ideas with AI...',
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'PARSE': 'Processing idea results...',
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'SAVE': 'Saving ideas...',
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'DONE': 'Ideas generated successfully'
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}
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}
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def get_max_items(self) -> int:
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return 1 # Single cluster only
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def validate(self, payload: dict, account=None) -> Dict:
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"""Validate single cluster"""
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ids = payload.get('ids', [])
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if not ids:
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return {'valid': False, 'error': 'No cluster selected'}
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if len(ids) > 1:
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return {'valid': False, 'error': 'Only one cluster can be processed at a time'}
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queryset = Clusters.objects.filter(id=ids[0])
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if account:
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queryset = queryset.filter(account=account)
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cluster = queryset.first()
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if not cluster:
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return {'valid': False, 'error': 'Cluster not found'}
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return {'valid': True}
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def prepare(self, payload: dict, account=None) -> Dict:
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"""Load cluster with keywords"""
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cluster_id = payload.get('ids', [])[0]
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queryset = Clusters.objects.filter(id=cluster_id)
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if account:
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queryset = queryset.filter(account=account)
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cluster = queryset.prefetch_related('keywords__seed_keyword').first()
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if not cluster:
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raise ValueError("Cluster not found")
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# Get keywords
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keyword_objects = Keywords.objects.filter(cluster=cluster).select_related('seed_keyword')
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keywords = []
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for kw in keyword_objects:
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keywords.append({
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'keyword': kw.seed_keyword.keyword if kw.seed_keyword else kw.keyword,
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'volume': kw.volume,
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'difficulty': kw.difficulty,
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})
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return {
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'cluster': cluster, # Store original object
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'cluster_data': {
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'id': cluster.id,
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'name': cluster.name,
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'description': cluster.description or '',
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'keywords': keywords,
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}
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}
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def build_prompt(self, data: Dict, account=None) -> str:
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"""Build idea generation prompt"""
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cluster_data = data.get('cluster_data', {})
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keywords = cluster_data.get('keywords', [])
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keyword_list = [kw['keyword'] for kw in keywords]
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# Format clusters text
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clusters_text = f"Cluster ID: {cluster_data.get('id', '')} | Name: {cluster_data.get('name', '')} | Description: {cluster_data.get('description', '')}"
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# Format cluster keywords
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cluster_keywords_text = f"Cluster ID: {cluster_data.get('id', '')} | Name: {cluster_data.get('name', '')} | Keywords: {', '.join(keyword_list)}"
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# Get prompt from registry
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prompt = PromptRegistry.get_prompt(
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function_name='generate_ideas',
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account=account,
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context={
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'CLUSTERS': clusters_text,
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'CLUSTER_KEYWORDS': cluster_keywords_text,
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}
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)
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return prompt
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def parse_response(self, response: str, step_tracker=None) -> List[Dict]:
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"""Parse AI response into idea data"""
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if not response or not response.strip():
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raise ValueError("Empty response from AI")
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ai_core = AICore(account=getattr(self, 'account', None))
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json_data = ai_core.extract_json(response)
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if not json_data or 'ideas' not in json_data:
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raise ValueError("Invalid response format: missing 'ideas' array")
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return json_data.get('ideas', [])
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def save_output(self, parsed: List[Dict], original_data: Any, account=None, step_tracker=None) -> Dict:
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"""Save ideas to database"""
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cluster = original_data.get('cluster')
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if not cluster:
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raise ValueError("Cluster not found in original data")
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ideas_created = 0
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with transaction.atomic():
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for idea_data in parsed:
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ContentIdeas.objects.create(
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cluster=cluster,
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title=idea_data.get('title', 'Untitled Idea'),
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description=idea_data.get('description', ''),
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structure=idea_data.get('structure', 'article'),
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account=account,
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status='new'
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)
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ideas_created += 1
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return {
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'ideas_created': ideas_created,
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'count': ideas_created
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}
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