PydanticUndefinedAnnotation: name 'SafetySetting' is not defined using ChatVertexAI #28271

k3ybladewielder · 2024-11-21T22:43:53Z

Checked other resources

I added a very descriptive title to this issue.
I searched the LangChain documentation with the integrated search.
I used the GitHub search to find a similar question and didn't find it.
I am sure that this is a bug in LangChain rather than my code.
The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package).

Example Code

# Ensure your VertexAI credentials are configured

from langchain_google_vertexai import ChatVertexAI

model = ChatVertexAI(model="gemini-1.5-flash")

model.invoke("Hello, world!")

Error Message and Stack Trace (if applicable)

---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
File /opt/conda/lib/python3.10/site-packages/pydantic/_internal/_generate_schema.py:815, in GenerateSchema._resolve_forward_ref(self, obj)
    814 try:
--> 815     obj = _typing_extra.eval_type_backport(obj, *self._types_namespace)
    816 except NameError as e:

File /opt/conda/lib/python3.10/site-packages/pydantic/_internal/_typing_extra.py:534, in eval_type_backport(value, globalns, localns, type_params)
    533 try:
--> 534     return _eval_type_backport(value, globalns, localns, type_params)
    535 except TypeError as e:

File /opt/conda/lib/python3.10/site-packages/pydantic/_internal/_typing_extra.py:558, in _eval_type_backport(value, globalns, localns, type_params)
    557 try:
--> 558     return _eval_type(value, globalns, localns, type_params)
    559 except TypeError as e:

File /opt/conda/lib/python3.10/site-packages/pydantic/_internal/_typing_extra.py:592, in _eval_type(value, globalns, localns, type_params)
    591 else:
--> 592     return typing._eval_type(  # type: ignore
    593         value, globalns, localns
    594     )

File /opt/conda/lib/python3.10/typing.py:327, in _eval_type(t, globalns, localns, recursive_guard)
    326 if isinstance(t, ForwardRef):
--> 327     return t._evaluate(globalns, localns, recursive_guard)
    328 if isinstance(t, (_GenericAlias, GenericAlias, types.UnionType)):

File /opt/conda/lib/python3.10/typing.py:699, in ForwardRef._evaluate(self, globalns, localns, recursive_guard)
    693 type_ = _type_check(
    694     eval(self.__forward_code__, globalns, localns),
    695     "Forward references must evaluate to types.",
    696     is_argument=self.__forward_is_argument__,
    697     allow_special_forms=self.__forward_is_class__,
    698 )
--> 699 self.__forward_value__ = _eval_type(
    700     type_, globalns, localns, recursive_guard | {self.__forward_arg__}
    701 )
    702 self.__forward_evaluated__ = True

File /opt/conda/lib/python3.10/typing.py:329, in _eval_type(t, globalns, localns, recursive_guard)
    328 if isinstance(t, (_GenericAlias, GenericAlias, types.UnionType)):
--> 329     ev_args = tuple(_eval_type(a, globalns, localns, recursive_guard) for a in t.__args__)
    330     if ev_args == t.__args__:

File /opt/conda/lib/python3.10/typing.py:329, in <genexpr>(.0)
    328 if isinstance(t, (_GenericAlias, GenericAlias, types.UnionType)):
--> 329     ev_args = tuple(_eval_type(a, globalns, localns, recursive_guard) for a in t.__args__)
    330     if ev_args == t.__args__:

File /opt/conda/lib/python3.10/typing.py:327, in _eval_type(t, globalns, localns, recursive_guard)
    326 if isinstance(t, ForwardRef):
--> 327     return t._evaluate(globalns, localns, recursive_guard)
    328 if isinstance(t, (_GenericAlias, GenericAlias, types.UnionType)):

File /opt/conda/lib/python3.10/typing.py:699, in ForwardRef._evaluate(self, globalns, localns, recursive_guard)
    693 type_ = _type_check(
    694     eval(self.__forward_code__, globalns, localns),
    695     "Forward references must evaluate to types.",
    696     is_argument=self.__forward_is_argument__,
    697     allow_special_forms=self.__forward_is_class__,
    698 )
--> 699 self.__forward_value__ = _eval_type(
    700     type_, globalns, localns, recursive_guard | {self.__forward_arg__}
    701 )
    702 self.__forward_evaluated__ = True

File /opt/conda/lib/python3.10/typing.py:329, in _eval_type(t, globalns, localns, recursive_guard)
    328 if isinstance(t, (_GenericAlias, GenericAlias, types.UnionType)):
--> 329     ev_args = tuple(_eval_type(a, globalns, localns, recursive_guard) for a in t.__args__)
    330     if ev_args == t.__args__:

File /opt/conda/lib/python3.10/typing.py:329, in <genexpr>(.0)
    328 if isinstance(t, (_GenericAlias, GenericAlias, types.UnionType)):
--> 329     ev_args = tuple(_eval_type(a, globalns, localns, recursive_guard) for a in t.__args__)
    330     if ev_args == t.__args__:

File /opt/conda/lib/python3.10/typing.py:329, in _eval_type(t, globalns, localns, recursive_guard)
    328 if isinstance(t, (_GenericAlias, GenericAlias, types.UnionType)):
--> 329     ev_args = tuple(_eval_type(a, globalns, localns, recursive_guard) for a in t.__args__)
    330     if ev_args == t.__args__:

File /opt/conda/lib/python3.10/typing.py:329, in <genexpr>(.0)
    328 if isinstance(t, (_GenericAlias, GenericAlias, types.UnionType)):
--> 329     ev_args = tuple(_eval_type(a, globalns, localns, recursive_guard) for a in t.__args__)
    330     if ev_args == t.__args__:

File /opt/conda/lib/python3.10/typing.py:327, in _eval_type(t, globalns, localns, recursive_guard)
    326 if isinstance(t, ForwardRef):
--> 327     return t._evaluate(globalns, localns, recursive_guard)
    328 if isinstance(t, (_GenericAlias, GenericAlias, types.UnionType)):

File /opt/conda/lib/python3.10/typing.py:694, in ForwardRef._evaluate(self, globalns, localns, recursive_guard)
    690     globalns = getattr(
    691         sys.modules.get(self.__forward_module__, None), '__dict__', globalns
    692     )
    693 type_ = _type_check(
--> 694     eval(self.__forward_code__, globalns, localns),
    695     "Forward references must evaluate to types.",
    696     is_argument=self.__forward_is_argument__,
    697     allow_special_forms=self.__forward_is_class__,
    698 )
    699 self.__forward_value__ = _eval_type(
    700     type_, globalns, localns, recursive_guard | {self.__forward_arg__}
    701 )

File <string>:1

NameError: name 'SafetySetting' is not defined

The above exception was the direct cause of the following exception:

PydanticUndefinedAnnotation               Traceback (most recent call last)
Cell In[15], line 1
----> 1 from langchain_google_vertexai import ChatVertexAI
      3 model = ChatVertexAI(model="gemini-1.5-flash")
      5 model.invoke("Hello, world!")

File ~/.local/lib/python3.10/site-packages/langchain_google_vertexai/__init__.py:16
     14 from langchain_google_vertexai.chains import create_structured_runnable
     15 from langchain_google_vertexai.chat_models import ChatVertexAI
---> 16 from langchain_google_vertexai.embeddings import VertexAIEmbeddings
     17 from langchain_google_vertexai.evaluators.evaluation import (
     18     VertexPairWiseStringEvaluator,
     19     VertexStringEvaluator,
     20 )
     21 from langchain_google_vertexai.functions_utils import (
     22     PydanticFunctionsOutputParser,
     23 )

File ~/.local/lib/python3.10/site-packages/langchain_google_vertexai/embeddings.py:544
    540             embeddings.append(result.image_embedding)
    541         return embeddings
--> 544 VertexAIEmbeddings.model_rebuild()

File /opt/conda/lib/python3.10/site-packages/pydantic/main.py:589, in BaseModel.model_rebuild(cls, force, raise_errors, _parent_namespace_depth, _types_namespace)
    587 # manually override defer_build so complete_model_class doesn't skip building the model again
    588 config = {**cls.model_config, 'defer_build': False}
--> 589 return _model_construction.complete_model_class(
    590     cls,
    591     cls.__name__,
    592     _config.ConfigWrapper(config, check=False),
    593     raise_errors=raise_errors,
    594     ns_resolver=ns_resolver,
    595 )

File /opt/conda/lib/python3.10/site-packages/pydantic/_internal/_model_construction.py:658, in complete_model_class(cls, cls_name, config_wrapper, raise_errors, ns_resolver, create_model_module)
    651 handler = CallbackGetCoreSchemaHandler(
    652     partial(gen_schema.generate_schema, from_dunder_get_core_schema=False),
    653     gen_schema,
    654     ref_mode='unpack',
    655 )
    657 try:
--> 658     schema = cls.__get_pydantic_core_schema__(cls, handler)
    659 except PydanticUndefinedAnnotation as e:
    660     if raise_errors:

File /opt/conda/lib/python3.10/site-packages/pydantic/main.py:697, in BaseModel.__get_pydantic_core_schema__(cls, source, handler)
    694     if not cls.__pydantic_generic_metadata__['origin']:
    695         return cls.__pydantic_core_schema__
--> 697 return handler(source)

File /opt/conda/lib/python3.10/site-packages/pydantic/_internal/_schema_generation_shared.py:84, in CallbackGetCoreSchemaHandler.__call__(self, source_type)
     83 def __call__(self, source_type: Any, /) -> core_schema.CoreSchema:
---> 84     schema = self._handler(source_type)
     85     ref = schema.get('ref')
     86     if self._ref_mode == 'to-def':

File /opt/conda/lib/python3.10/site-packages/pydantic/_internal/_generate_schema.py:612, in GenerateSchema.generate_schema(self, obj, from_dunder_get_core_schema)
    609         schema = from_property
    611 if schema is None:
--> 612     schema = self._generate_schema_inner(obj)
    614 metadata_js_function = _extract_get_pydantic_json_schema(obj, schema)
    615 if metadata_js_function is not None:

File /opt/conda/lib/python3.10/site-packages/pydantic/_internal/_generate_schema.py:881, in GenerateSchema._generate_schema_inner(self, obj)
    879 if lenient_issubclass(obj, BaseModel):
    880     with self.model_type_stack.push(obj):
--> 881         return self._model_schema(obj)
    883 if isinstance(obj, PydanticRecursiveRef):
    884     return core_schema.definition_reference_schema(schema_ref=obj.type_ref)

File /opt/conda/lib/python3.10/site-packages/pydantic/_internal/_generate_schema.py:693, in GenerateSchema._model_schema(self, cls)
    681     model_schema = core_schema.model_schema(
    682         cls,
    683         inner_schema,
   (...)
    689         ref=model_ref,
    690     )
    691 else:
    692     fields_schema: core_schema.CoreSchema = core_schema.model_fields_schema(
--> 693         {k: self._generate_md_field_schema(k, v, decorators) for k, v in fields.items()},
    694         computed_fields=[
    695             self._computed_field_schema(d, decorators.field_serializers)
    696             for d in computed_fields.values()
    697         ],
    698         extras_schema=extras_schema,
    699         model_name=cls.__name__,
    700     )
    701     inner_schema = apply_validators(fields_schema, decorators.root_validators.values(), None)
    702     new_inner_schema = define_expected_missing_refs(inner_schema, recursively_defined_type_refs())

File /opt/conda/lib/python3.10/site-packages/pydantic/_internal/_generate_schema.py:693, in <dictcomp>(.0)
    681     model_schema = core_schema.model_schema(
    682         cls,
    683         inner_schema,
   (...)
    689         ref=model_ref,
    690     )
    691 else:
    692     fields_schema: core_schema.CoreSchema = core_schema.model_fields_schema(
--> 693         {k: self._generate_md_field_schema(k, v, decorators) for k, v in fields.items()},
    694         computed_fields=[
    695             self._computed_field_schema(d, decorators.field_serializers)
    696             for d in computed_fields.values()
    697         ],
    698         extras_schema=extras_schema,
    699         model_name=cls.__name__,
    700     )
    701     inner_schema = apply_validators(fields_schema, decorators.root_validators.values(), None)
    702     new_inner_schema = define_expected_missing_refs(inner_schema, recursively_defined_type_refs())

File /opt/conda/lib/python3.10/site-packages/pydantic/_internal/_generate_schema.py:1073, in GenerateSchema._generate_md_field_schema(self, name, field_info, decorators)
   1066 def _generate_md_field_schema(
   1067     self,
   1068     name: str,
   1069     field_info: FieldInfo,
   1070     decorators: DecoratorInfos,
   1071 ) -> core_schema.ModelField:
   1072     """Prepare a ModelField to represent a model field."""
-> 1073     common_field = self._common_field_schema(name, field_info, decorators)
   1074     return core_schema.model_field(
   1075         common_field['schema'],
   1076         serialization_exclude=common_field['serialization_exclude'],
   (...)
   1080         metadata=common_field['metadata'],
   1081     )

File /opt/conda/lib/python3.10/site-packages/pydantic/_internal/_generate_schema.py:1261, in GenerateSchema._common_field_schema(self, name, field_info, decorators)
   1257         schema = self._apply_annotations(
   1258             source_type, annotations + validators_from_decorators, transform_inner_schema=set_discriminator
   1259         )
   1260     else:
-> 1261         schema = self._apply_annotations(
   1262             source_type,
   1263             annotations + validators_from_decorators,
   1264         )
   1266 # This V1 compatibility shim should eventually be removed
   1267 # push down any `each_item=True` validators
   1268 # note that this won't work for any Annotated types that get wrapped by a function validator
   1269 # but that's okay because that didn't exist in V1
   1270 this_field_validators = filter_field_decorator_info_by_field(decorators.validators.values(), name)

File /opt/conda/lib/python3.10/site-packages/pydantic/_internal/_generate_schema.py:2051, in GenerateSchema._apply_annotations(self, source_type, annotations, transform_inner_schema)
   2046         continue
   2047     get_inner_schema = self._get_wrapped_inner_schema(
   2048         get_inner_schema, annotation, pydantic_js_annotation_functions
   2049     )
-> 2051 schema = get_inner_schema(source_type)
   2052 if pydantic_js_annotation_functions:
   2053     core_metadata = schema.setdefault('metadata', {})

File /opt/conda/lib/python3.10/site-packages/pydantic/_internal/_schema_generation_shared.py:84, in CallbackGetCoreSchemaHandler.__call__(self, source_type)
     83 def __call__(self, source_type: Any, /) -> core_schema.CoreSchema:
---> 84     schema = self._handler(source_type)
     85     ref = schema.get('ref')
     86     if self._ref_mode == 'to-def':

File /opt/conda/lib/python3.10/site-packages/pydantic/_internal/_generate_schema.py:2032, in GenerateSchema._apply_annotations.<locals>.inner_handler(obj)
   2030 from_property = self._generate_schema_from_property(obj, source_type)
   2031 if from_property is None:
-> 2032     schema = self._generate_schema_inner(obj)
   2033 else:
   2034     schema = from_property

File /opt/conda/lib/python3.10/site-packages/pydantic/_internal/_generate_schema.py:875, in GenerateSchema._generate_schema_inner(self, obj)
    872     obj = ForwardRef(obj)
    874 if isinstance(obj, ForwardRef):
--> 875     return self.generate_schema(self._resolve_forward_ref(obj))
    877 BaseModel = import_cached_base_model()
    879 if lenient_issubclass(obj, BaseModel):

File /opt/conda/lib/python3.10/site-packages/pydantic/_internal/_generate_schema.py:817, in GenerateSchema._resolve_forward_ref(self, obj)
    815     obj = _typing_extra.eval_type_backport(obj, *self._types_namespace)
    816 except NameError as e:
--> 817     raise PydanticUndefinedAnnotation.from_name_error(e) from e
    819 # if obj is still a ForwardRef, it means we can't evaluate it, raise PydanticUndefinedAnnotation
    820 if isinstance(obj, ForwardRef):

PydanticUndefinedAnnotation: name 'SafetySetting' is not defined

For further information visit https://errors.pydantic.dev/2.10/u/undefined-annotation

Description

Using the exact example from documentation the following error occur

System Info

System Information

OS: Linux
OS Version: #1 SMP Debian 5.10.223-1 (2024-08-10)
Python Version: 3.10.15 | packaged by conda-forge | (main, Sep 20 2024, 16:37:05) [GCC 13.3.0]

Package Information

langchain_core: 0.3.19
langchain: 0.3.7
langchain_community: 0.3.5
langsmith: 0.1.144
langchain_google_genai: 2.0.5
langchain_google_vertexai: 2.0.7
langchain_openai: 0.2.5
langchain_text_splitters: 0.3.2

Optional packages not installed

langgraph
langserve

Other Dependencies

aiohttp: 3.10.5
anthropic[vertexai]: Installed. No version info available.
async-timeout: 4.0.3
dataclasses-json: 0.6.7
google-cloud-aiplatform: 1.73.0
google-cloud-storage: 2.18.2
google-generativeai: 0.8.3
httpx: 0.27.2
httpx-sse: 0.4.0
jsonpatch: 1.33
langchain-mistralai: Installed. No version info available.
numpy: 1.25.2
openai: 1.55.0
orjson: 3.10.11
packaging: 24.1
pydantic: 2.10.0
pydantic-settings: 2.6.1
PyYAML: 6.0.2
requests: 2.32.3
requests-toolbelt: 1.0.0
SQLAlchemy: 2.0.35
tenacity: 9.0.0
tiktoken: 0.8.0
typing-extensions: 4.12.2

OlaPietka · 2024-11-22T09:46:49Z

I have the same issue. No resolution whatsoever.

twiedijk · 2024-11-22T09:59:05Z

It can be resolved by downgrading to pydantic==2.9.0

Luc2357 · 2024-11-22T11:01:15Z

See langchain-ai/langchain-google#610

andrewginns · 2024-11-22T11:01:46Z

I am also having this problem, no changes in pinned dependencies but suddenly my container is failing.

I can replicate this consistenly on both langchain-google-vertexai==2.0.5 and langchain-google-vertexai==2.0.7, I've not tested other versions.

This minimal Dockerfile demonstrates the issue:

FROM python:3.11-slim

WORKDIR /app

# Install Poetry
RUN pip install langchain-google-vertexai==2.0.7

CMD ["python", "-c", "from langchain_google_vertexai import ChatVertexAI"]

k3ybladewielder · 2024-11-22T13:05:44Z

I encountered the same issue and resolved it by downgrading to pydantic==2.9.0

See langchain-ai/langchain-google#610

Thanks for the answer @twiedijk @Luc2357. I tried and works well. I'll wait for the bug fix in the meantime

Viicos · 2024-11-22T14:04:18Z

See langchain-ai/langchain-google#610 (comment) for more details. TL;DR:

Upgrade back to 2.9 to avoid the issue. But do not that the 2.10 release revealed what could be a genuine bug in the langchain-google library, as the field annotations are not properly resolved to the correct type.

daniel-deychakiwsky · 2024-11-22T16:06:05Z

@k3ybladewielder @Viicos - we experienced the same issue. Would you happen to the have the bug link open within the langchain-google? I notcied langchain-ai/langchain-google#610 is closed.

Viicos · 2024-11-22T16:07:49Z

The original author closed it but it was mentioned that it should be kept open. I do not maintain the library so we'll have to wait for them to reopen it again. In the meanwhile you can probably subscribe to the closed issue. I'm currently working on a fix.

DanielAvdar · 2024-11-24T09:48:32Z

same

…rtexAI. Per langchain-ai/langchain#28271, the fix is to pin pydantic to 2.9.0.

ProtikKumarBiswas · 2024-12-15T13:34:35Z

It can be resolved by downgrading to pydantic==2.9.0

This resolved the issue. Thanks.

langcarl bot added the investigate Flagged for investigation. label Nov 21, 2024

dosubot bot added the 🤖:bug Related to a bug, vulnerability, unexpected error with an existing feature label Nov 21, 2024

anubhav756 added a commit to GoogleCloudPlatform/genai-databases-retrieval-app that referenced this issue Dec 3, 2024

dep: Fix issue causing 'SafetySetting' not defined issue using ChatVe…

bea955a

…rtexAI. Per langchain-ai/langchain#28271, the fix is to pin pydantic to 2.9.0.

anubhav756 added a commit to GoogleCloudPlatform/genai-databases-retrieval-app that referenced this issue Dec 3, 2024

dep: Fix issue causing 'SafetySetting' not defined issue using ChatVe…

f62c559

…rtexAI. Per langchain-ai/langchain#28271, the fix is to pin pydantic to 2.9.0.

vishwarajanand mentioned this issue Dec 9, 2024

chore: pin pydantic version to avoid a reasoning engine failure googleapis/langchain-google-alloydb-pg-python#284

Merged

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PydanticUndefinedAnnotation: name 'SafetySetting' is not defined using ChatVertexAI #28271

PydanticUndefinedAnnotation: name 'SafetySetting' is not defined using ChatVertexAI #28271

k3ybladewielder commented Nov 21, 2024

OlaPietka commented Nov 22, 2024

twiedijk commented Nov 22, 2024 •

edited

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Luc2357 commented Nov 22, 2024

andrewginns commented Nov 22, 2024

k3ybladewielder commented Nov 22, 2024 •

edited

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Viicos commented Nov 22, 2024

daniel-deychakiwsky commented Nov 22, 2024

Viicos commented Nov 22, 2024

DanielAvdar commented Nov 24, 2024

ProtikKumarBiswas commented Dec 15, 2024

PydanticUndefinedAnnotation: name 'SafetySetting' is not defined using ChatVertexAI #28271

PydanticUndefinedAnnotation: name 'SafetySetting' is not defined using ChatVertexAI #28271

Comments

k3ybladewielder commented Nov 21, 2024

Checked other resources

Example Code

Error Message and Stack Trace (if applicable)

Description

System Info

System Information

Package Information

Optional packages not installed

Other Dependencies

OlaPietka commented Nov 22, 2024

twiedijk commented Nov 22, 2024 • edited Loading

Luc2357 commented Nov 22, 2024

andrewginns commented Nov 22, 2024

k3ybladewielder commented Nov 22, 2024 • edited Loading

Viicos commented Nov 22, 2024

daniel-deychakiwsky commented Nov 22, 2024

Viicos commented Nov 22, 2024

DanielAvdar commented Nov 24, 2024

ProtikKumarBiswas commented Dec 15, 2024

twiedijk commented Nov 22, 2024 •

edited

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k3ybladewielder commented Nov 22, 2024 •

edited

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