Integrate DataEnrichmentManager into lead_scoring_agent - enrich profiles before scoring

lead_scoring_agent.py

@@ -12,12 +12,25 @@ Integrates with enrichment, research, outreach, analytics, validation agents. Se
 
 from transformers import pipeline
 import numpy as np
+from data_enrichment import DataEnrichmentManager
 
 class LeadScoringAgent:
-    def __init__(self, model_name: str = 'distilbert-base-uncased'):
+    def __init__(self, username: str = 'default', model_name: str = 'distilbert-base-uncased'):        self.classifier = pipeline('text-classification', model=model_name)
         self.classifier = pipeline('text-classification', model=model_name)
-
+        self.username = username
+        self.enrichment_manager = DataEnrichmentManager(username)
     def score_lead(self, profile: dict) -> dict:
+                # ENRICHMENT STEP: Optionally enrich profile before scoring for better accuracy
+        try:
+            enriched_data = self.enrichment_manager.enrich_contact_full(profile)
+            if enriched_data:
+                # Merge enriched data into profile for richer scoring
+                for key, value in enriched_data.items():
+                    if key not in profile or not profile.get(key):
+                        profile[key] = value
+        except Exception:
+            pass  # Continue with available data if enrichment fails
+        
         text = self.profile_to_text(profile)
         model_result = self.classifier(text)[0]
         intent_score = float(model_result['score'])