Update features/insight_and_tasks/orchestrators/linkedin_analytics_orchestrator.py

features/insight_and_tasks/orchestrators/linkedin_analytics_orchestrator.py

@@ -16,7 +16,7 @@ from features.insight_and_tasks.coordinators.employer_branding_coordinator impor
 from features.insight_and_tasks.agents.task_extraction_agent import TaskExtractionAgent
 from features.insight_and_tasks.data_models.metrics import AgentMetrics # For type hinting
 from features.insight_and_tasks.data_models.tasks import TaskExtractionOutput # For type hinting
-from features.insight_and_tasks.agents.task_extraction_model import extract_tasks_from_text
+from features.insight_and_tasks.agents.task_extraction_model_groq import extract_tasks_from_text_groq
 
 # Configure logger for this module
 logger = logging.getLogger(__name__)
@@ -105,7 +105,7 @@ class EnhancedLinkedInAnalyticsOrchestrator:
 
         # Step 3: TaskExtractionAgent extracts actionable tasks (OKRs) from the comprehensive text.
         logger.info("Running task extraction...")
-        actionable_tasks_okrs, quarter, year, days_remaining = extract_tasks_from_text(comprehensive_analysis_text, GOOGLE_API_KEY)
+        actionable_tasks_okrs, quarter, year, days_remaining = extract_tasks_from_text_groq(comprehensive_analysis_text, GOOGLE_API_KEY)
         logger.info(f"Task extraction complete. Number of OKRs: {len(actionable_tasks_okrs.okrs) if actionable_tasks_okrs else 'Error'}.")
 
         # Step 4: Compile and return all results.