fix: resolve AttributeError by supporting both Pydantic and Protobuf AgentCard serialization

tests/unit/vertex_langchain/test_agent_engines.py

@@ -1061,6 +1061,130 @@ def test_create_agent_engine(
             retry=_TEST_RETRY,
         )
 
+    def test_create_agent_engine_with_protobuf_agent_card(
+        self,
+        create_agent_engine_mock,
+        cloud_storage_create_bucket_mock,
+        tarfile_open_mock,
+        cloudpickle_dump_mock,
+        cloudpickle_load_mock,
+        importlib_metadata_version_mock,
+        get_agent_engine_mock,
+        get_gca_resource_mock,
+    ):
+        class CapitalizeEngineWithCard(CapitalizeEngine):
+            def __init__(self, card):
+                self.agent_card = card
+
+        from google.protobuf import struct_pb2
+
+        card = struct_pb2.Struct()
+        card["name"] = "test_agent_card"
+        agent = CapitalizeEngineWithCard(card)
+
+        agent_engines.create(
+            agent,
+            display_name=_TEST_AGENT_ENGINE_DISPLAY_NAME,
+            requirements=_TEST_AGENT_ENGINE_REQUIREMENTS,
+            extra_packages=[_TEST_AGENT_ENGINE_EXTRA_PACKAGE_PATH],
+        )
+
+        expected_reasoning_engine = types.ReasoningEngine(
+            display_name=_TEST_AGENT_ENGINE_DISPLAY_NAME,
+            spec=types.ReasoningEngineSpec(
+                package_spec=_TEST_AGENT_ENGINE_PACKAGE_SPEC,
+                agent_framework=_agent_engines._DEFAULT_AGENT_FRAMEWORK,
+            ),
+        )
+        from google.protobuf import json_format
+
+        expected_class_method = struct_pb2.Struct()
+        expected_class_method.CopyFrom(_TEST_AGENT_ENGINE_QUERY_SCHEMA)
+        expected_class_method["a2a_agent_card"] = json_format.MessageToJson(card)
+        expected_reasoning_engine.spec.class_methods.append(expected_class_method)
+
+        create_agent_engine_mock.assert_called_with(
+            parent=_TEST_PARENT,
+            reasoning_engine=expected_reasoning_engine,
+        )
+
+    def test_create_agent_engine_with_pydantic_agent_card(
+        self,
+        create_agent_engine_mock,
+        cloud_storage_create_bucket_mock,
+        tarfile_open_mock,
+        cloudpickle_dump_mock,
+        cloudpickle_load_mock,
+        importlib_metadata_version_mock,
+        get_agent_engine_mock,
+        get_gca_resource_mock,
+    ):
+        class CapitalizeEngineWithCard(CapitalizeEngine):
+            def __init__(self, card):
+                self.agent_card = card
+
+        import pydantic
+
+        class DummyPydanticCard(pydantic.BaseModel):
+            name: str = "test_pydantic_card"
+
+        card = DummyPydanticCard()
+        agent = CapitalizeEngineWithCard(card)
+
+        agent_engines.create(
+            agent,
+            display_name=_TEST_AGENT_ENGINE_DISPLAY_NAME,
+            requirements=_TEST_AGENT_ENGINE_REQUIREMENTS,
+            extra_packages=[_TEST_AGENT_ENGINE_EXTRA_PACKAGE_PATH],
+        )
+
+        expected_reasoning_engine = types.ReasoningEngine(
+            display_name=_TEST_AGENT_ENGINE_DISPLAY_NAME,
+            spec=types.ReasoningEngineSpec(
+                package_spec=_TEST_AGENT_ENGINE_PACKAGE_SPEC,
+                agent_framework=_agent_engines._DEFAULT_AGENT_FRAMEWORK,
+            ),
+        )
+        from google.protobuf import struct_pb2
+
+        expected_class_method = struct_pb2.Struct()
+        expected_class_method.CopyFrom(_TEST_AGENT_ENGINE_QUERY_SCHEMA)
+        expected_class_method["a2a_agent_card"] = card.model_dump_json()
+        expected_reasoning_engine.spec.class_methods.append(expected_class_method)
+
+        create_agent_engine_mock.assert_called_with(
+            parent=_TEST_PARENT,
+            reasoning_engine=expected_reasoning_engine,
+        )
+
+    def test_create_agent_engine_with_invalid_agent_card(
+        self,
+        create_agent_engine_mock,
+        cloud_storage_create_bucket_mock,
+        tarfile_open_mock,
+        cloudpickle_dump_mock,
+        cloudpickle_load_mock,
+        importlib_metadata_version_mock,
+        get_agent_engine_mock,
+        get_gca_resource_mock,
+    ):
+        class CapitalizeEngineWithCard(CapitalizeEngine):
+            def __init__(self, card):
+                self.agent_card = card
+
+        agent = CapitalizeEngineWithCard(card="invalid_card_type_string")
+
+        with pytest.raises(
+            TypeError,
+            match="Unsupported AgentCard type",
+        ):
+            agent_engines.create(
+                agent,
+                display_name=_TEST_AGENT_ENGINE_DISPLAY_NAME,
+                requirements=_TEST_AGENT_ENGINE_REQUIREMENTS,
+                extra_packages=[_TEST_AGENT_ENGINE_EXTRA_PACKAGE_PATH],
+            )
+
     def test_create_agent_engine_requirements_from_file(
         self,
         create_agent_engine_mock,

vertexai/_genai/_agent_engines_utils.py

@@ -652,10 +652,9 @@ def _generate_class_methods_spec_or_raise(
 
             class_method = _to_proto(schema_dict)
             class_method[_MODE_KEY_IN_SCHEMA] = mode
-            if hasattr(agent, "agent_card"):
-                class_method[_A2A_AGENT_CARD] = json_format.MessageToJson(
-                    getattr(agent, "agent_card")
-                )
+            card = getattr(agent, "agent_card", None)
+            if card is not None:
+                class_method[_A2A_AGENT_CARD] = _serialize_agent_card_to_json(card)
             class_methods_spec.append(class_method)
 
     return class_methods_spec
@@ -2148,3 +2147,59 @@ def _add_telemetry_enablement_env(
         return env_vars
 
     return env_vars | env_to_add
+
+
+def _serialize_agent_card_to_dict(card: Any) -> Optional[Dict[str, Any]]:
+    """Validates and serializes an AgentCard to a dictionary representation.
+
+    Args:
+        card: The AgentCard instance (Pydantic model or Protobuf Message).
+
+    Returns:
+        The serialized card as a dictionary.
+
+    Raises:
+        TypeError: If the card type is not supported.
+    """
+    if card is None:
+        return None
+
+    if hasattr(card, "model_dump"):
+        return typing.cast(dict[str, Any], card.model_dump(exclude_none=True))
+    elif hasattr(card, "DESCRIPTOR"):
+        from google.protobuf import json_format
+
+        return typing.cast(dict[str, Any], json_format.MessageToDict(card))
+    else:
+        raise TypeError(
+            f"Unsupported AgentCard type: {type(card)}. "
+            "Only Pydantic models and Protobuf Messages are supported."
+        )
+
+
+def _serialize_agent_card_to_json(card: Any) -> Optional[str]:
+    """Validates and serializes an AgentCard to a JSON string representation.
+
+    Args:
+        card: The AgentCard instance (Pydantic model or Protobuf Message).
+
+    Returns:
+        The serialized card as a JSON string.
+
+    Raises:
+        TypeError: If the card type is not supported.
+    """
+    if card is None:
+        return None
+
+    if hasattr(card, "model_dump_json"):
+        return typing.cast(str, card.model_dump_json())
+    elif hasattr(card, "DESCRIPTOR"):
+        from google.protobuf import json_format
+
+        return typing.cast(str, json_format.MessageToJson(card))
+    else:
+        raise TypeError(
+            f"Unsupported AgentCard type: {type(card)}. "
+            "Only Pydantic models and Protobuf Messages are supported."
+        )

vertexai/_genai/agent_engines.py

@@ -2498,12 +2498,12 @@ def _create_config(
 
             if hasattr(agent, "agent_card"):
                 agent_card = getattr(agent, "agent_card")
-                if agent_card:
+                if agent_card is not None:
                     try:
-                        from google.protobuf import json_format
-
-                        agent_engine_spec["agent_card"] = json_format.MessageToDict(
-                            agent_card
+                        agent_engine_spec["agent_card"] = (
+                            _agent_engines_utils._serialize_agent_card_to_dict(
+                                agent_card
+                            )
                         )
                     except Exception as e:
                         raise ValueError(

vertexai/agent_engines/_agent_engines.py

@@ -46,6 +46,7 @@
 from google.cloud.aiplatform_v1 import types as aip_types
 from google.cloud.aiplatform_v1.types import reasoning_engine_service
 from vertexai.agent_engines import _utils
+from vertexai._genai import _agent_engines_utils
 import httpx
 import proto
 
@@ -1997,11 +1998,11 @@ def _generate_class_methods_spec_or_raise(
             class_method[_MODE_KEY_IN_SCHEMA] = mode
             # A2A agent card is a special case, when running in A2A mode,
             if hasattr(agent_engine, "agent_card"):
-                from google.protobuf import json_format
-
-                class_method[_A2A_AGENT_CARD] = json_format.MessageToJson(
-                    getattr(agent_engine, "agent_card")
-                )
+                card = getattr(agent_engine, "agent_card")
+                if card is not None:
+                    class_method[_A2A_AGENT_CARD] = (
+                        _agent_engines_utils._serialize_agent_card_to_json(card)
+                    )
             class_methods_spec.append(class_method)
 
     return class_methods_spec