credits adn tokens final correct setup

backend/igny8_core/management/commands/backfill_tokens.py

@@ -0,0 +1,62 @@
+"""
+Backfill token data from AITaskLog to CreditUsageLog
+"""
+from django.core.management.base import BaseCommand
+from igny8_core.ai.models import AITaskLog
+from igny8_core.modules.billing.models import CreditUsageLog
+from datetime import timedelta
+
+
+class Command(BaseCommand):
+    help = 'Backfill token data from AITaskLog to CreditUsageLog'
+
+    def handle(self, *args, **options):
+        self.stdout.write("=== Token Data Backfill ===\n")
+        
+        # Get AITaskLog entries with token data
+        ai_logs = AITaskLog.objects.filter(
+            tokens__gt=0,
+            status='success'
+        ).select_related('account').order_by('created_at')
+        
+        self.stdout.write(f"Found {ai_logs.count()} AITaskLog entries with tokens\n")
+        
+        updated_count = 0
+        skipped_count = 0
+        no_match_count = 0
+        
+        for ai_log in ai_logs:
+            # Find matching CreditUsageLog within 10 second window
+            time_start = ai_log.created_at - timedelta(seconds=10)
+            time_end = ai_log.created_at + timedelta(seconds=10)
+            
+            # Try to find exact match
+            credit_log = CreditUsageLog.objects.filter(
+                account=ai_log.account,
+                created_at__gte=time_start,
+                created_at__lte=time_end,
+                tokens_input=0,
+                tokens_output=0
+            ).order_by('created_at').first()
+            
+            if credit_log:
+                # AITaskLog has total tokens, estimate 40/60 split for input/output
+                # This is approximate but better than 0
+                total_tokens = ai_log.tokens
+                estimated_input = int(total_tokens * 0.4)
+                estimated_output = total_tokens - estimated_input
+                
+                credit_log.tokens_input = estimated_input
+                credit_log.tokens_output = estimated_output
+                credit_log.save(update_fields=['tokens_input', 'tokens_output'])
+                
+                updated_count += 1
+                if updated_count % 50 == 0:
+                    self.stdout.write(f"  Updated {updated_count} records...")
+            else:
+                no_match_count += 1
+        
+        self.stdout.write(self.style.SUCCESS(f"\n✅ Backfill complete!"))
+        self.stdout.write(f"  Updated: {updated_count}")
+        self.stdout.write(f"  No match: {no_match_count}")
+        self.stdout.write(f"  Total processed: {ai_logs.count()}")