- adding usage to specialist execution

- Correcting implementation of usage
- Removed some obsolete debug statements

eveai_entitlements/tasks.py

@@ -30,6 +30,8 @@ def update_usages():
     error_list = []
 
     for tenant_id in tenant_ids:
+        if tenant_id == 1:
+            continue
         try:
             Database(tenant_id).switch_schema()
             check_and_create_license_usage_for_tenant(tenant_id)
@@ -65,6 +67,50 @@ def update_usages():
     return "Update Usages taks completed successfully"
 
 
+@current_celery.task(name='persist_business_events', queue='entitlements')
+def persist_business_events(log_entries):
+    """
+    Persist multiple business event logs to the database in a single transaction
+
+    Args:
+        log_entries: List of log event dictionaries to persist
+    """
+    try:
+        db_entries = []
+        for entry in log_entries:
+            event_log = BusinessEventLog(
+                timestamp=entry.pop('timestamp'),
+                event_type=entry.pop('event_type'),
+                tenant_id=entry.pop('tenant_id'),
+                trace_id=entry.pop('trace_id'),
+                span_id=entry.pop('span_id', None),
+                span_name=entry.pop('span_name', None),
+                parent_span_id=entry.pop('parent_span_id', None),
+                document_version_id=entry.pop('document_version_id', None),
+                document_version_file_size=entry.pop('document_version_file_size', None),
+                chat_session_id=entry.pop('chat_session_id', None),
+                interaction_id=entry.pop('interaction_id', None),
+                environment=entry.pop('environment', None),
+                llm_metrics_total_tokens=entry.pop('llm_metrics_total_tokens', None),
+                llm_metrics_prompt_tokens=entry.pop('llm_metrics_prompt_tokens', None),
+                llm_metrics_completion_tokens=entry.pop('llm_metrics_completion_tokens', None),
+                llm_metrics_total_time=entry.pop('llm_metrics_total_time', None),
+                llm_metrics_call_count=entry.pop('llm_metrics_call_count', None),
+                llm_interaction_type=entry.pop('llm_interaction_type', None),
+                message=entry.pop('message', None)
+            )
+            db_entries.append(event_log)
+
+        # Perform a bulk insert of all entries
+        db.session.bulk_save_objects(db_entries)
+        db.session.commit()
+        current_app.logger.info(f"Successfully persisted {len(db_entries)} business event logs")
+
+    except Exception as e:
+        current_app.logger.error(f"Failed to persist business event logs: {e}")
+        db.session.rollback()
+
+
 def get_all_tenant_ids():
     tenant_ids = db.session.query(Tenant.id).all()
     return [tenant_id[0] for tenant_id in tenant_ids]  # Extract tenant_id from tuples
@@ -193,6 +239,18 @@ def process_logs_for_license_usage(tenant_id, license_usage_id, logs):
                 interaction_completion_tokens_used += log.llm_metrics_completion_tokens
                 interaction_total_tokens_used += log.llm_metrics_total_tokens
 
+        # Case for 'Specialist Execution' event
+        elif log.event_type == 'Execute Specialist':
+            if log.message == 'Final LLM Metrics':
+                if log.span_name == 'Specialist Retrieval':     # This is embedding
+                    embedding_prompt_tokens_used += log.llm_metrics_prompt_tokens
+                    embedding_completion_tokens_used += log.llm_metrics_completion_tokens
+                    embedding_total_tokens_used += log.llm_metrics_total_tokens
+                else:   # This is an interaction
+                    interaction_prompt_tokens_used += log.llm_metrics_prompt_tokens
+                    interaction_completion_tokens_used += log.llm_metrics_completion_tokens
+                    interaction_total_tokens_used += log.llm_metrics_total_tokens
+
         # Mark the log as processed by setting the license_usage_id
         log.license_usage_id = license_usage_id