fix: stop deserializing the staged agent from Cloud Storage during Agent Engine deployment

agentplatform/_genai/_runtimes_utils.py

@@ -1294,11 +1294,6 @@ def _upload_runtime(
                     "`from a2a import types`."
                 )
             raise TypeError(error_msg) from e
-    with blob.open("rb") as f:
-        try:
-            _ = cloudpickle.load(f)
-        except Exception as e:
-            raise TypeError("agent runtime serialized to an invalid format") from e
     dir_name = f"gs://{gcs_bucket.name}/{gcs_dir_name}"
     logger.info(f"Wrote to {dir_name}/{_BLOB_FILENAME}")
 

tests/unit/agentplatform/genai/replays/test_create_agent_engine_a2a.py

@@ -14,9 +14,7 @@
 #
 # pylint: disable=protected-access,bad-continuation,missing-function-docstring
 
-import contextlib
 import os
-from unittest import mock
 from tests.unit.agentplatform.genai.replays import pytest_helper
 from agentplatform._genai import types
 from agentplatform.frameworks.a2a import default_a2a_agent
@@ -30,7 +28,7 @@
 from a2a.utils.constants import TransportProtocol
 
 
-def test_create_a2a_agent(client, is_replay_mode):
+def test_create_a2a_agent(client):
     my_agent = default_a2a_agent()
 
     my_agent.agent_card.supported_interfaces.append(
@@ -44,30 +42,20 @@ def test_create_a2a_agent(client, is_replay_mode):
 
     staging_bucket = os.environ["GCS_BUCKET"]
 
-    # In replay mode, GCS operations are mocked and blob.open("rb") returns a mock
-    # that fails when cloudpickle.load expects bytes. We mock _upload_runtime
-    # to skip this verification step, which is not needed when replaying API calls.
-    upload_patch = (
-        mock.patch("agentplatform._genai._runtimes_utils._upload_runtime")
-        if is_replay_mode
-        else contextlib.nullcontext()
+    runtime = client.runtimes.create(
+        agent=my_agent,
+        config={
+            "staging_bucket": staging_bucket,
+            "display_name": "test-a2a-agent",
+            "http_options": {"api_version": "v1beta1"},
+            "requirements": [
+                "google-cloud-aiplatform[agent_engines]",
+                "a2a-sdk",
+                "sse-starlette",
+            ],
+        },
     )
 
-    with upload_patch:
-        runtime = client.runtimes.create(
-            agent=my_agent,
-            config={
-                "staging_bucket": staging_bucket,
-                "display_name": "test-a2a-agent",
-                "http_options": {"api_version": "v1beta1"},
-                "requirements": [
-                    "google-cloud-aiplatform[agent_engines]",
-                    "a2a-sdk",
-                    "sse-starlette",
-                ],
-            },
-        )
-
 
     assert isinstance(runtime, types.Runtime)
     assert runtime.api_resource.display_name == "test-a2a-agent"

vertexai/_genai/_agent_engines_utils.py

@@ -1281,11 +1281,6 @@ def _upload_agent_engine(
                     "`from a2a import types`."
                 )
             raise TypeError(error_msg) from e
-    with blob.open("rb") as f:
-        try:
-            _ = cloudpickle.load(f)
-        except Exception as e:
-            raise TypeError("Agent engine serialized to an invalid format") from e
     dir_name = f"gs://{gcs_bucket.name}/{gcs_dir_name}"
     logger.info(f"Wrote to {dir_name}/{_BLOB_FILENAME}")
 

vertexai/agent_engines/_agent_engines.py

@@ -1302,11 +1302,6 @@ def _upload_agent_engine(
                     "`from a2a import types as a2a_types`."
                 )
             raise TypeError(error_msg) from e
-    with blob.open("rb") as f:
-        try:
-            _ = cloudpickle.load(f)
-        except Exception as e:
-            raise TypeError("Agent engine serialized to an invalid format") from e
     dir_name = f"gs://{gcs_bucket.name}/{gcs_dir_name}"
     logger.info(f"Wrote to {dir_name}/{_BLOB_FILENAME}")