Fix dry-run summary alignment, token logging, and upload error handling

- Align dry-run summary to use pre-transform columns (spend, total_tokens,
  team_id, model) matching FocusExportEngine internals
- Reduce token exposure in debug logs to first 4 chars
- Wrap raise_for_status in try/except to log httpx errors before re-raising

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

litellm/integrations/focus/destinations/vantage_destination.py

@@ -88,7 +88,15 @@ class FocusVantageDestination(FocusDestination):
             headers=headers,
             files={"file": (filename, csv_bytes, "text/csv")},
         )
-        response.raise_for_status()
+        try:
+            response.raise_for_status()
+        except httpx.HTTPStatusError as e:
+            verbose_logger.error(
+                "Vantage destination: upload failed for %s — %s",
+                filename,
+                e,
+            )
+            raise
 
         verbose_logger.debug(
             "Vantage destination: uploaded %d bytes (%s)",

litellm/integrations/vantage/vantage_logger.py

@@ -83,7 +83,7 @@ class VantageLogger(FocusLogger):
 
         verbose_logger.debug(
             "VantageLogger initialized (integration_token=%s)",
-            resolved_token[:8] + "..." if resolved_token else "None",
+            resolved_token[:4] + "***" if resolved_token and len(resolved_token) > 4 else "***",
         )
 
     @staticmethod

litellm/proxy/spend_tracking/vantage_endpoints.py

@@ -392,13 +392,14 @@ async def vantage_dry_run_export(
         usage_sample = data.head(min(50, len(data))).to_dicts() if not data.is_empty() else []
         normalized_sample = normalized.head(min(50, len(normalized))).to_dicts() if not normalized.is_empty() else []
 
-        # Compute summary from the FOCUS-normalized DataFrame.
-        # These use post-transform column names specific to this endpoint.
+        # Use the same pre-transform column names as
+        # FocusExportEngine.dry_run_export_usage_data for consistency.
         summary = {
             "total_records": len(normalized),
-            "total_spend": FocusExportEngine._sum_column(normalized, "BilledCost"),
-            "unique_teams": FocusExportEngine._count_unique(normalized, "SubAccountId"),
-            "unique_models": FocusExportEngine._count_unique(normalized, "ResourceType"),
+            "total_spend": FocusExportEngine._sum_column(data, "spend"),
+            "total_tokens": FocusExportEngine._sum_column(data, "total_tokens"),
+            "unique_teams": FocusExportEngine._count_unique(data, "team_id"),
+            "unique_models": FocusExportEngine._count_unique(data, "model"),
         }
 
         dry_run_result = {