fix(proxy/batches): resolve managed unified input_file_id to storage_url with ownership check before dispatch

litellm/proxy/batches_endpoints/endpoints.py

@@ -38,11 +38,44 @@
     update_batch_in_database,
 )
 from litellm.proxy.utils import handle_exception_on_proxy, is_known_model
+from litellm.repositories.table_repositories import ManagedFileRepository
 from litellm.types.llms.openai import LiteLLMBatchCreateRequest
 
 router = APIRouter()
 
 
+async def _resolve_managed_input_file_storage_url(input_file_id: str) -> "str | None":
+    """Resolve a managed (unified) input_file_id to its backend storage_url.
+
+    Provider batch handlers (e.g. Vertex AI, which parses a `publishers/`
+    segment out of the file URI) need a real storage location; the opaque
+    unified token crashes them. Returns None only when there is no database or
+    the row has no storage_url yet, so callers fall back to the original id
+    (which the managed-files deployment hook can still map). Fails closed
+    rather than dispatch a token that cannot be resolved: 404 when no
+    managed-file row exists, 503 when the lookup itself errors so the caller
+    can retry.
+    """
+    from litellm.proxy.proxy_server import prisma_client
+
+    if prisma_client is None:
+        return None
+    try:
+        db_file = await ManagedFileRepository(prisma_client).table.find_first(where={"unified_file_id": input_file_id})
+    except Exception as e:
+        verbose_proxy_logger.warning("create_batch: managed file lookup failed for %s: %s", input_file_id, e)
+        raise HTTPException(
+            status_code=503,
+            detail={"error": "Could not resolve managed file; please retry"},
+        )
+    if db_file is None:
+        raise HTTPException(
+            status_code=404,
+            detail={"error": f"Managed file not found: {input_file_id}"},
+        )
+    return db_file.storage_url or None
+
+
 @router.post(
     "/{provider}/v1/batches",
     dependencies=[Depends(user_api_key_auth)],
@@ -224,6 +257,11 @@ async def create_batch(
                 )
             model = target_model_names[0]
             _create_batch_data["model"] = model
+
+            resolved_storage_url = await _resolve_managed_input_file_storage_url(input_file_id)
+            if resolved_storage_url is not None:
+                _create_batch_data["input_file_id"] = resolved_storage_url
+
             if llm_router is None:
                 raise HTTPException(
                     status_code=500,