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core: Improve mypy config (#30737)

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* Cleanup mypy config
* Add mypy `strict` rules except `disallow_any_generics`,
`warn_return_any` and `strict_equality` (TODO)
* Add mypy `strict_byte` rule
* Add mypy support for PEP702 `@deprecated` decorator
* Bump mypy version to 1.15

---------

Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
This commit is contained in:
Christophe Bornet 2025-04-11 22:35:13 +02:00 committed by GitHub
parent bb2c2fd885
commit 42944f3499
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
60 changed files with 222 additions and 237 deletions
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6
libs/core/langchain_core/_api/beta_decorator.py
View File

@ -225,10 +225,8 @@ def beta(
new_doc = f".. beta::\n {details}\n\n{old_doc}\n"
if inspect.iscoroutinefunction(obj):
finalized = finalize(awarning_emitting_wrapper, new_doc)
else:
finalized = finalize(warning_emitting_wrapper, new_doc)
return cast("T", finalized)
return finalize(awarning_emitting_wrapper, new_doc)
return finalize(warning_emitting_wrapper, new_doc)
return beta

11
libs/core/langchain_core/_api/deprecation.py
View File

@ -152,7 +152,10 @@ def deprecated(
_package: str = package,
) -> T:
"""Implementation of the decorator returned by `deprecated`."""
from langchain_core.utils.pydantic import FieldInfoV1, FieldInfoV2
from langchain_core.utils.pydantic import ( # type: ignore[attr-defined]
FieldInfoV1,
FieldInfoV2,
)
def emit_warning() -> None:
"""Emit the warning."""
@ -395,10 +398,8 @@ def deprecated(
"""
if inspect.iscoroutinefunction(obj):
finalized = finalize(awarning_emitting_wrapper, new_doc)
else:
finalized = finalize(warning_emitting_wrapper, new_doc)
return cast("T", finalized)
return finalize(awarning_emitting_wrapper, new_doc)
return finalize(warning_emitting_wrapper, new_doc)
return deprecate

2
libs/core/langchain_core/callbacks/manager.py
View File

@ -2408,7 +2408,7 @@ def _configure(
run_tree.trace_id,
run_tree.dotted_order,
)
handler.run_map[str(run_tree.id)] = cast("Run", run_tree)
handler.run_map[str(run_tree.id)] = run_tree
for var, inheritable, handler_class, env_var in _configure_hooks:
create_one = (
env_var is not None

2
libs/core/langchain_core/document_loaders/base.py
View File

@ -80,7 +80,7 @@ class BaseLoader(ABC): # noqa: B024
iterator = await run_in_executor(None, self.lazy_load)
done = object()
while True:
doc = await run_in_executor(None, next, iterator, done) # type: ignore[call-arg, arg-type]
doc = await run_in_executor(None, next, iterator, done)
if doc is done:
break
yield doc # type: ignore[misc]

4
libs/core/langchain_core/embeddings/fake.py
View File

@ -52,7 +52,7 @@ class FakeEmbeddings(Embeddings, BaseModel):
"""The size of the embedding vector."""
def _get_embedding(self) -> list[float]:
import numpy as np # type: ignore[import-not-found, import-untyped]
import numpy as np
return list(np.random.default_rng().normal(size=self.size))
@ -109,7 +109,7 @@ class DeterministicFakeEmbedding(Embeddings, BaseModel):
"""The size of the embedding vector."""
def _get_embedding(self, seed: int) -> list[float]:
import numpy as np # type: ignore[import-not-found, import-untyped]
import numpy as np
# set the seed for the random generator
rng = np.random.default_rng(seed)

12
libs/core/langchain_core/globals.py
View File

@ -23,7 +23,7 @@ def set_verbose(value: bool) -> None: # noqa: FBT001
value: The new value for the `verbose` global setting.
"""
try:
import langchain # type: ignore[import]
import langchain # type: ignore[import-not-found]
# We're about to run some deprecated code, don't report warnings from it.
# The user called the correct (non-deprecated) code path and shouldn't get
@ -57,7 +57,7 @@ def get_verbose() -> bool:
The value of the `verbose` global setting.
"""
try:
import langchain # type: ignore[import]
import langchain
# We're about to run some deprecated code, don't report warnings from it.
# The user called the correct (non-deprecated) code path and shouldn't get
@ -96,7 +96,7 @@ def set_debug(value: bool) -> None: # noqa: FBT001
value: The new value for the `debug` global setting.
"""
try:
import langchain # type: ignore[import]
import langchain
# We're about to run some deprecated code, don't report warnings from it.
# The user called the correct (non-deprecated) code path and shouldn't get
@ -128,7 +128,7 @@ def get_debug() -> bool:
The value of the `debug` global setting.
"""
try:
import langchain # type: ignore[import]
import langchain
# We're about to run some deprecated code, don't report warnings from it.
# The user called the correct (non-deprecated) code path and shouldn't get
@ -164,7 +164,7 @@ def set_llm_cache(value: Optional["BaseCache"]) -> None:
value: The new LLM cache to use. If `None`, the LLM cache is disabled.
"""
try:
import langchain # type: ignore[import]
import langchain
# We're about to run some deprecated code, don't report warnings from it.
# The user called the correct (non-deprecated) code path and shouldn't get
@ -198,7 +198,7 @@ def get_llm_cache() -> "BaseCache":
The value of the `llm_cache` global setting.
"""
try:
import langchain # type: ignore[import]
import langchain
# We're about to run some deprecated code, don't report warnings from it.
# The user called the correct (non-deprecated) code path and shouldn't get

2
libs/core/langchain_core/indexing/api.py
View File

@ -394,7 +394,7 @@ def index(
if cleanup == "scoped_full":
scoped_full_cleanup_source_ids.add(source_id)
# source ids cannot be None after for loop above.
source_ids = cast("Sequence[str]", source_ids) # type: ignore[assignment]
source_ids = cast("Sequence[str]", source_ids)
exists_batch = record_manager.exists([doc.uid for doc in hashed_docs])

2
libs/core/langchain_core/language_models/base.py
View File

@ -61,7 +61,7 @@ def get_tokenizer() -> Any:
every time it is called.
"""
try:
from transformers import GPT2TokenizerFast # type: ignore[import]
from transformers import GPT2TokenizerFast # type: ignore[import-not-found]
except ImportError as e:
msg = (
"Could not import transformers python package. "

4
libs/core/langchain_core/language_models/chat_models.py
View File

@ -853,7 +853,7 @@ class BaseChatModel(BaseLanguageModel[BaseMessage], ABC):
run_manager.on_llm_end(
LLMResult(
generations=[res.generations], # type: ignore[list-item, union-attr]
llm_output=res.llm_output, # type: ignore[list-item, union-attr]
llm_output=res.llm_output, # type: ignore[union-attr]
)
)
for run_manager, res in zip(run_managers, results)
@ -1107,7 +1107,7 @@ class BaseChatModel(BaseLanguageModel[BaseMessage], ABC):
None,
next,
iterator,
done, # type: ignore[call-arg, arg-type]
done,
)
if item is done:
break

10
libs/core/langchain_core/language_models/llms.py
View File

@ -455,7 +455,7 @@ class BaseLLM(BaseLanguageModel[str], ABC):
inputs[i : i + max_concurrency]
for i in range(0, len(inputs), max_concurrency)
]
config = [{**c, "max_concurrency": None} for c in config] # type: ignore[misc]
config = [{**c, "max_concurrency": None} for c in config]
return [
output
for i, batch in enumerate(batches)
@ -501,7 +501,7 @@ class BaseLLM(BaseLanguageModel[str], ABC):
inputs[i : i + max_concurrency]
for i in range(0, len(inputs), max_concurrency)
]
config = [{**c, "max_concurrency": None} for c in config] # type: ignore[misc]
config = [{**c, "max_concurrency": None} for c in config]
return [
output
for i, batch in enumerate(batches)
@ -746,7 +746,7 @@ class BaseLLM(BaseLanguageModel[str], ABC):
None,
next,
iterator,
done, # type: ignore[call-arg, arg-type]
done,
)
if item is done:
break
@ -1231,7 +1231,7 @@ class BaseLLM(BaseLanguageModel[str], ABC):
stop,
run_managers, # type: ignore[arg-type]
new_arg_supported=bool(new_arg_supported),
**kwargs, # type: ignore[arg-type]
**kwargs,
)
if len(missing_prompts) > 0:
run_managers = await asyncio.gather(
@ -1253,7 +1253,7 @@ class BaseLLM(BaseLanguageModel[str], ABC):
stop,
run_managers, # type: ignore[arg-type]
new_arg_supported=bool(new_arg_supported),
**kwargs, # type: ignore[arg-type]
**kwargs,
)
llm_output = await aupdate_cache(
self.cache,

6
libs/core/langchain_core/messages/base.py
View File

@ -119,7 +119,7 @@ class BaseMessage(Serializable):
"""Concatenate this message with another message."""
from langchain_core.prompts.chat import ChatPromptTemplate
prompt = ChatPromptTemplate(messages=[self]) # type: ignore[call-arg]
prompt = ChatPromptTemplate(messages=[self])
return prompt + other
def pretty_repr(
@ -165,7 +165,7 @@ def merge_content(
if isinstance(merged, str):
# If the next chunk is also a string, then merge them naively
if isinstance(content, str):
merged = cast("str", merged) + content
merged += content
# If the next chunk is a list, add the current to the start of the list
else:
merged = [merged] + content # type: ignore[assignment,operator]
@ -215,7 +215,7 @@ class BaseMessageChunk(BaseMessage):
# If both are (subclasses of) BaseMessageChunk,
# concat into a single BaseMessageChunk
return self.__class__( # type: ignore[call-arg]
return self.__class__(
id=self.id,
type=self.type,
content=merge_content(self.content, other.content),

4
libs/core/langchain_core/messages/utils.py
View File

@ -237,7 +237,7 @@ def _create_message_from_message_type(
if additional_kwargs:
if response_metadata := additional_kwargs.pop("response_metadata", None):
kwargs["response_metadata"] = response_metadata
kwargs["additional_kwargs"] = additional_kwargs # type: ignore[assignment]
kwargs["additional_kwargs"] = additional_kwargs
additional_kwargs.update(additional_kwargs.pop("additional_kwargs", {}))
if id is not None:
kwargs["id"] = id
@ -889,7 +889,7 @@ def trim_messages(
return sum(token_counter(msg) for msg in messages) # type: ignore[arg-type, misc]
else:
list_token_counter = token_counter # type: ignore[assignment]
list_token_counter = token_counter
else:
msg = (
f"'token_counter' expected to be a model that implements "

2
libs/core/langchain_core/output_parsers/json.py
View File

@ -6,7 +6,7 @@ import json
from json import JSONDecodeError
from typing import Annotated, Any, Optional, TypeVar, Union
import jsonpatch # type: ignore[import]
import jsonpatch # type: ignore[import-untyped]
import pydantic
from pydantic import SkipValidation

2
libs/core/langchain_core/output_parsers/openai_functions.py
View File

@ -5,7 +5,7 @@ import json
from types import GenericAlias
from typing import Any, Optional, Union
import jsonpatch # type: ignore[import]
import jsonpatch # type: ignore[import-untyped]
from pydantic import BaseModel, model_validator
from typing_extensions import override

2
libs/core/langchain_core/outputs/llm_result.py
View File

@ -50,7 +50,7 @@ class LLMResult(BaseModel):
run: Optional[list[RunInfo]] = None
"""List of metadata info for model call for each input."""
type: Literal["LLMResult"] = "LLMResult" # type: ignore[assignment]
type: Literal["LLMResult"] = "LLMResult"
"""Type is used exclusively for serialization purposes."""
def flatten(self) -> list[LLMResult]:

12
libs/core/langchain_core/prompts/chat.py
View File

@ -129,7 +129,7 @@ class BaseMessagePromptTemplate(Serializable, ABC):
Returns:
Combined prompt template.
"""
prompt = ChatPromptTemplate(messages=[self]) # type: ignore[call-arg]
prompt = ChatPromptTemplate(messages=[self])
return prompt + other
@ -1033,23 +1033,23 @@ class ChatPromptTemplate(BaseChatPromptTemplate):
if isinstance(other, ChatPromptTemplate):
return ChatPromptTemplate(messages=self.messages + other.messages).partial(
**partials
) # type: ignore[call-arg]
)
if isinstance(
other, (BaseMessagePromptTemplate, BaseMessage, BaseChatPromptTemplate)
):
return ChatPromptTemplate(messages=self.messages + [other]).partial(
**partials
) # type: ignore[call-arg]
)
if isinstance(other, (list, tuple)):
_other = ChatPromptTemplate.from_messages(other)
return ChatPromptTemplate(messages=self.messages + _other.messages).partial(
**partials
) # type: ignore[call-arg]
)
if isinstance(other, str):
prompt = HumanMessagePromptTemplate.from_template(other)
return ChatPromptTemplate(messages=self.messages + [prompt]).partial(
**partials
) # type: ignore[call-arg]
)
msg = f"Unsupported operand type for +: {type(other)}"
raise NotImplementedError(msg)
@ -1138,7 +1138,7 @@ class ChatPromptTemplate(BaseChatPromptTemplate):
Returns:
a chat prompt template.
"""
return cls( # type: ignore[call-arg]
return cls(
messages=[
ChatMessagePromptTemplate.from_template(template, role=role)
for role, template in string_messages

2
libs/core/langchain_core/prompts/image.py
View File

@ -116,7 +116,7 @@ class ImagePromptTemplate(BasePromptTemplate[ImageURL]):
output: ImageURL = {"url": url}
if detail:
# Don't check literal values here: let the API check them
output["detail"] = detail # type: ignore[typeddict-item]
output["detail"] = detail
return output
async def aformat(self, **kwargs: Any) -> ImageURL:

2
libs/core/langchain_core/prompts/prompt.py
View File

@ -297,7 +297,7 @@ class PromptTemplate(StringPromptTemplate):
return cls(
input_variables=input_variables,
template=template,
template_format=template_format, # type: ignore[arg-type]
template_format=template_format,
partial_variables=_partial_variables,
**kwargs,
)

2
libs/core/langchain_core/pydantic_v1/__init__.py
View File

@ -18,7 +18,7 @@ from langchain_core._api.deprecation import warn_deprecated
try:
from pydantic.v1 import * # noqa: F403
except ImportError:
from pydantic import * # noqa: F403
from pydantic import * # type: ignore[assignment,no-redef] # noqa: F403
try:

2
libs/core/langchain_core/pydantic_v1/dataclasses.py
View File

@ -5,7 +5,7 @@ from langchain_core._api import warn_deprecated
try:
from pydantic.v1.dataclasses import * # noqa: F403
except ImportError:
from pydantic.dataclasses import * # noqa: F403
from pydantic.dataclasses import * # type: ignore[no-redef] # noqa: F403
warn_deprecated(
"0.3.0",

2
libs/core/langchain_core/pydantic_v1/main.py
View File

@ -5,7 +5,7 @@ from langchain_core._api import warn_deprecated
try:
from pydantic.v1.main import * # noqa: F403
except ImportError:
from pydantic.main import * # noqa: F403
from pydantic.main import * # type: ignore[assignment,no-redef] # noqa: F403
warn_deprecated(
"0.3.0",

10
libs/core/langchain_core/retrievers.py
View File

@ -30,6 +30,7 @@ from pydantic import ConfigDict
from typing_extensions import Self, TypedDict, override
from langchain_core._api import deprecated
from langchain_core.callbacks import Callbacks
from langchain_core.documents import Document
from langchain_core.runnables import (
Runnable,
@ -43,7 +44,6 @@ if TYPE_CHECKING:
from langchain_core.callbacks.manager import (
AsyncCallbackManagerForRetrieverRun,
CallbackManagerForRetrieverRun,
Callbacks,
)
RetrieverInput = str
@ -160,10 +160,10 @@ class BaseRetriever(RunnableSerializable[RetrieverInput, RetrieverOutput], ABC):
stacklevel=4,
)
swap = cls.get_relevant_documents
cls.get_relevant_documents = ( # type: ignore[assignment]
cls.get_relevant_documents = ( # type: ignore[method-assign]
BaseRetriever.get_relevant_documents
)
cls._get_relevant_documents = swap # type: ignore[assignment]
cls._get_relevant_documents = swap # type: ignore[method-assign]
if (
hasattr(cls, "aget_relevant_documents")
and cls.aget_relevant_documents != BaseRetriever.aget_relevant_documents
@ -175,10 +175,10 @@ class BaseRetriever(RunnableSerializable[RetrieverInput, RetrieverOutput], ABC):
stacklevel=4,
)
aswap = cls.aget_relevant_documents
cls.aget_relevant_documents = ( # type: ignore[assignment]
cls.aget_relevant_documents = ( # type: ignore[method-assign]
BaseRetriever.aget_relevant_documents
)
cls._aget_relevant_documents = aswap # type: ignore[assignment]
cls._aget_relevant_documents = aswap # type: ignore[method-assign]
parameters = signature(cls._get_relevant_documents).parameters
cls._new_arg_supported = parameters.get("run_manager") is not None
if (

40
libs/core/langchain_core/runnables/base.py
View File

@ -489,7 +489,7 @@ class Runnable(Generic[Input, Output], ABC):
include = include or []
config_specs = self.config_specs
configurable = (
create_model_v2( # type: ignore[call-overload]
create_model_v2(
"Configurable",
field_definitions={
spec.id: (
@ -514,9 +514,7 @@ class Runnable(Generic[Input, Output], ABC):
if field_name in [i for i in include if i != "configurable"]
},
}
return create_model_v2( # type: ignore[call-overload]
self.get_name("Config"), field_definitions=all_fields
)
return create_model_v2(self.get_name("Config"), field_definitions=all_fields)
def get_config_jsonschema(
self, *, include: Optional[Sequence[str]] = None
@ -1543,7 +1541,7 @@ class Runnable(Generic[Input, Output], ABC):
config=cast(
"RunnableConfig",
{**(config or {}), **kwargs},
), # type: ignore[misc]
),
kwargs={},
)
@ -1931,8 +1929,8 @@ class Runnable(Generic[Input, Output], ABC):
"Output",
context.run(
call_func_with_variable_args, # type: ignore[arg-type]
func, # type: ignore[arg-type]
input, # type: ignore[arg-type]
func,
input,
config,
run_manager,
**kwargs,
@ -2194,7 +2192,7 @@ class Runnable(Generic[Input, Output], ABC):
cast("_StreamingCallbackHandler", h)
for h in run_manager.handlers
# instance check OK here, it's a mixin
if isinstance(h, _StreamingCallbackHandler) # type: ignore[misc]
if isinstance(h, _StreamingCallbackHandler)
),
None,
):
@ -2299,7 +2297,7 @@ class Runnable(Generic[Input, Output], ABC):
cast("_StreamingCallbackHandler", h)
for h in run_manager.handlers
# instance check OK here, it's a mixin
if isinstance(h, _StreamingCallbackHandler) # type: ignore[misc]
if isinstance(h, _StreamingCallbackHandler)
),
None,
):
@ -2318,7 +2316,7 @@ class Runnable(Generic[Input, Output], ABC):
final_output = chunk
else:
try:
final_output = final_output + chunk # type: ignore[operator]
final_output = final_output + chunk
except TypeError:
final_output = chunk
final_output_supported = False
@ -2601,7 +2599,7 @@ def _seq_input_schema(
next_input_schema = _seq_input_schema(steps[1:], config)
if not issubclass(next_input_schema, RootModel):
# it's a dict as expected
return create_model_v2( # type: ignore[call-overload]
return create_model_v2(
"RunnableSequenceInput",
field_definitions={
k: (v.annotation, v.default)
@ -2628,7 +2626,7 @@ def _seq_output_schema(
prev_output_schema = _seq_output_schema(steps[:-1], config)
if not issubclass(prev_output_schema, RootModel):
# it's a dict as expected
return create_model_v2( # type: ignore[call-overload]
return create_model_v2(
"RunnableSequenceOutput",
field_definitions={
**{
@ -2646,7 +2644,7 @@ def _seq_output_schema(
if not issubclass(prev_output_schema, RootModel):
# it's a dict as expected
if isinstance(last.keys, list):
return create_model_v2( # type: ignore[call-overload]
return create_model_v2(
"RunnableSequenceOutput",
field_definitions={
k: (v.annotation, v.default)
@ -2655,7 +2653,7 @@ def _seq_output_schema(
},
)
field = prev_output_schema.model_fields[last.keys]
return create_model_v2( # type: ignore[call-overload]
return create_model_v2(
"RunnableSequenceOutput", root=(field.annotation, field.default)
)
@ -3625,7 +3623,7 @@ class RunnableParallel(RunnableSerializable[Input, dict[str, Any]]):
for s in self.steps__.values()
):
# This is correct, but pydantic typings/mypy don't think so.
return create_model_v2( # type: ignore[call-overload]
return create_model_v2(
self.get_name("Input"),
field_definitions={
k: (v.annotation, v.default)
@ -4084,7 +4082,7 @@ class RunnableGenerator(Runnable[Input, Output]):
func_for_name: Callable = atransform
if is_async_generator(transform):
self._atransform = transform # type: ignore[assignment]
self._atransform = transform
func_for_name = transform
elif inspect.isgeneratorfunction(transform):
self._transform = transform
@ -4211,7 +4209,7 @@ class RunnableGenerator(Runnable[Input, Output]):
input,
self._transform, # type: ignore[arg-type]
config,
**kwargs, # type: ignore[arg-type]
**kwargs,
)
@override
@ -4815,7 +4813,7 @@ class RunnableLambda(Runnable[Input, Output]):
if inspect.isgeneratorfunction(self.func):
output: Optional[Output] = None
for chunk in call_func_with_variable_args(
self.func, cast("Input", final), config, run_manager, **kwargs
self.func, final, config, run_manager, **kwargs
):
yield chunk
if output is None:
@ -4827,7 +4825,7 @@ class RunnableLambda(Runnable[Input, Output]):
output = chunk
else:
output = call_func_with_variable_args(
self.func, cast("Input", final), config, run_manager, **kwargs
self.func, final, config, run_manager, **kwargs
)
# If the output is a Runnable, use its stream output
@ -4936,7 +4934,7 @@ class RunnableLambda(Runnable[Input, Output]):
"AsyncIterator[Output]",
acall_func_with_variable_args(
cast("Callable", afunc),
cast("Input", final),
final,
config,
run_manager,
**kwargs,
@ -4953,7 +4951,7 @@ class RunnableLambda(Runnable[Input, Output]):
else:
output = await acall_func_with_variable_args(
cast("Callable", afunc),
cast("Input", final),
final,
config,
run_manager,
**kwargs,

2
libs/core/langchain_core/runnables/branch.py
View File

@ -114,7 +114,7 @@ class RunnableBranch(RunnableSerializable[Input, Output]):
_branches = []
for branch in branches[:-1]:
if not isinstance(branch, (tuple, list)): # type: ignore[arg-type]
if not isinstance(branch, (tuple, list)):
msg = (
f"RunnableBranch branches must be "
f"tuples or lists, not {type(branch)}"

19
libs/core/langchain_core/runnables/fallbacks.py
View File

@ -10,7 +10,6 @@ from typing import (
Any,
Optional,
Union,
cast,
)
from pydantic import BaseModel, ConfigDict
@ -183,7 +182,7 @@ class RunnableWithFallbacks(RunnableSerializable[Input, Output]):
for runnable in self.runnables:
try:
if self.exception_key and last_error is not None:
input[self.exception_key] = last_error
input[self.exception_key] = last_error # type: ignore[index]
child_config = patch_config(config, callbacks=run_manager.get_child())
with set_config_context(child_config) as context:
output = context.run(
@ -237,7 +236,7 @@ class RunnableWithFallbacks(RunnableSerializable[Input, Output]):
for runnable in self.runnables:
try:
if self.exception_key and last_error is not None:
input[self.exception_key] = last_error
input[self.exception_key] = last_error # type: ignore[index]
child_config = patch_config(config, callbacks=run_manager.get_child())
with set_config_context(child_config) as context:
coro = context.run(runnable.ainvoke, input, config, **kwargs)
@ -328,12 +327,12 @@ class RunnableWithFallbacks(RunnableSerializable[Input, Output]):
if not return_exceptions:
first_to_raise = first_to_raise or output
else:
handled_exceptions[i] = cast("BaseException", output)
handled_exceptions[i] = output
run_again.pop(i)
elif isinstance(output, self.exceptions_to_handle):
if self.exception_key:
input[self.exception_key] = output # type: ignore[index]
handled_exceptions[i] = cast("BaseException", output)
handled_exceptions[i] = output
else:
run_managers[i].on_chain_end(output)
to_return[i] = output
@ -425,12 +424,12 @@ class RunnableWithFallbacks(RunnableSerializable[Input, Output]):
if not return_exceptions:
first_to_raise = first_to_raise or output
else:
handled_exceptions[i] = cast("BaseException", output)
handled_exceptions[i] = output
run_again.pop(i)
elif isinstance(output, self.exceptions_to_handle):
if self.exception_key:
input[self.exception_key] = output # type: ignore[index]
handled_exceptions[i] = cast("BaseException", output)
handled_exceptions[i] = output
else:
to_return[i] = output
await run_managers[i].on_chain_end(output)
@ -482,7 +481,7 @@ class RunnableWithFallbacks(RunnableSerializable[Input, Output]):
for runnable in self.runnables:
try:
if self.exception_key and last_error is not None:
input[self.exception_key] = last_error
input[self.exception_key] = last_error # type: ignore[index]
child_config = patch_config(config, callbacks=run_manager.get_child())
with set_config_context(child_config) as context:
stream = context.run(
@ -546,7 +545,7 @@ class RunnableWithFallbacks(RunnableSerializable[Input, Output]):
for runnable in self.runnables:
try:
if self.exception_key and last_error is not None:
input[self.exception_key] = last_error
input[self.exception_key] = last_error # type: ignore[index]
child_config = patch_config(config, callbacks=run_manager.get_child())
with set_config_context(child_config) as context:
stream = runnable.astream(
@ -574,7 +573,7 @@ class RunnableWithFallbacks(RunnableSerializable[Input, Output]):
async for chunk in stream:
yield chunk
try:
output = output + chunk # type: ignore[operator]
output = output + chunk
except TypeError:
output = None
except BaseException as e:

2
libs/core/langchain_core/runnables/graph.py
View File

@ -288,7 +288,7 @@ class Graph:
"target": stable_node_ids[edge.target],
}
if edge.data is not None:
edge_dict["data"] = edge.data
edge_dict["data"] = edge.data # type: ignore[assignment]
if edge.conditional:
edge_dict["conditional"] = True
edges.append(edge_dict)

6
libs/core/langchain_core/runnables/graph_ascii.py
View File

@ -167,9 +167,9 @@ def _build_sugiyama_layout(
vertices: Mapping[str, str], edges: Sequence[LangEdge]
) -> Any:
try:
from grandalf.graphs import Edge, Graph, Vertex # type: ignore[import]
from grandalf.layouts import SugiyamaLayout # type: ignore[import]
from grandalf.routing import ( # type: ignore[import]
from grandalf.graphs import Edge, Graph, Vertex # type: ignore[import-untyped]
from grandalf.layouts import SugiyamaLayout # type: ignore[import-untyped]
from grandalf.routing import ( # type: ignore[import-untyped]
EdgeViewer,
route_with_lines,
)

4
libs/core/langchain_core/runnables/graph_mermaid.py
View File

@ -305,7 +305,7 @@ async def _render_mermaid_using_pyppeteer(
) -> bytes:
"""Renders Mermaid graph using Pyppeteer."""
try:
from pyppeteer import launch # type: ignore[import]
from pyppeteer import launch # type: ignore[import-not-found]
except ImportError as e:
msg = "Install Pyppeteer to use the Pyppeteer method: `pip install pyppeteer`."
raise ImportError(msg) from e
@ -377,7 +377,7 @@ def _render_mermaid_using_api(
) -> bytes:
"""Renders Mermaid graph using the Mermaid.INK API."""
try:
import requests # type: ignore[import]
import requests
except ImportError as e:
msg = (
"Install the `requests` module to use the Mermaid.INK API: "

2
libs/core/langchain_core/runnables/graph_png.py
View File

@ -135,7 +135,7 @@ class PngDrawer:
:param output_path: The path to save the PNG. If None, PNG bytes are returned.
"""
try:
import pygraphviz as pgv # type: ignore[import]
import pygraphviz as pgv # type: ignore[import-not-found]
except ImportError as exc:
msg = "Install pygraphviz to draw graphs: `pip install pygraphviz`."
raise ImportError(msg) from exc

2
libs/core/langchain_core/runnables/history.py
View File

@ -388,7 +388,7 @@ class RunnableWithMessageHistory(RunnableBindingBase):
module_name=self.__class__.__module__,
root=(Sequence[BaseMessage], ...),
)
return create_model_v2( # type: ignore[call-overload]
return create_model_v2(
"RunnableWithChatHistoryInput",
field_definitions=fields,
module_name=self.__class__.__module__,

4
libs/core/langchain_core/runnables/passthrough.py
View File

@ -455,9 +455,7 @@ class RunnableAssign(RunnableSerializable[dict[str, Any], dict[str, Any]]):
for name, field_info in map_output_schema.model_fields.items():
fields[name] = (field_info.annotation, field_info.default)
return create_model_v2( # type: ignore[call-overload]
"RunnableAssignOutput", field_definitions=fields
)
return create_model_v2("RunnableAssignOutput", field_definitions=fields)
if not issubclass(map_output_schema, RootModel):
# ie. only map output is a dict
# ie. input type is either unknown or inferred incorrectly

3
libs/core/langchain_core/runnables/retry.py
View File

@ -20,8 +20,9 @@ from tenacity import (
)
from typing_extensions import TypedDict, override
from langchain_core.runnables.base import Input, Output, RunnableBindingBase
from langchain_core.runnables.base import RunnableBindingBase
from langchain_core.runnables.config import RunnableConfig, patch_config
from langchain_core.runnables.utils import Input, Output
if TYPE_CHECKING:
from langchain_core.callbacks.manager import (

4
libs/core/langchain_core/runnables/router.py
View File

@ -17,8 +17,6 @@ from pydantic import ConfigDict
from typing_extensions import TypedDict, override
from langchain_core.runnables.base import (
Input,
Output,
Runnable,
RunnableSerializable,
coerce_to_runnable,
@ -30,6 +28,8 @@ from langchain_core.runnables.config import (
)
from langchain_core.runnables.utils import (
ConfigurableFieldSpec,
Input,
Output,
gather_with_concurrency,
get_unique_config_specs,
)

2
libs/core/langchain_core/runnables/utils.py
View File

@ -141,7 +141,7 @@ def coro_with_context(
The coroutine with the context.
"""
if asyncio_accepts_context():
return asyncio.create_task(coro, context=context) # type: ignore[arg-type,call-arg]
return asyncio.create_task(coro, context=context) # type: ignore[arg-type,call-arg,unused-ignore]
if create_task:
return asyncio.create_task(coro) # type: ignore[arg-type]
return coro

4
libs/core/langchain_core/tools/simple.py
View File

@ -132,9 +132,7 @@ class Tool(BaseTool):
self, name: str, func: Optional[Callable], description: str, **kwargs: Any
) -> None:
"""Initialize tool."""
super().__init__( # type: ignore[call-arg]
name=name, func=func, description=description, **kwargs
)
super().__init__(name=name, func=func, description=description, **kwargs)
@classmethod
def from_function(

2
libs/core/langchain_core/tracers/evaluation.py
View File

@ -162,7 +162,7 @@ class EvaluatorCallbackHandler(BaseTracer):
if isinstance(results, EvaluationResult):
results_ = [results]
elif isinstance(results, dict) and "results" in results:
results_ = cast("list[EvaluationResult]", results["results"])
results_ = results["results"]
else:
msg = (
f"Invalid evaluation result type {type(results)}."

2
libs/core/langchain_core/tracers/event_stream.py
View File

@ -787,8 +787,6 @@ async def _astream_events_implementation_v1(
root_metadata = config.get("metadata", {})
root_name = config.get("run_name", runnable.get_name())
# Ignoring mypy complaint about too many different union combinations
# This arises because many of the argument types are unions
async for log in _astream_log_implementation(
runnable,
input,

4
libs/core/langchain_core/tracers/log_stream.py
View File

@ -17,7 +17,7 @@ from typing import (
overload,
)
import jsonpatch # type: ignore[import]
import jsonpatch # type: ignore[import-untyped]
from typing_extensions import NotRequired, TypedDict, override
from langchain_core.load import dumps
@ -618,7 +618,7 @@ async def _astream_log_implementation(
The implementation has been factored out (at least temporarily) as both
astream_log and astream_events relies on it.
"""
import jsonpatch # type: ignore[import]
import jsonpatch
from langchain_core.callbacks.base import BaseCallbackManager
from langchain_core.tracers.log_stream import (

2
libs/core/langchain_core/utils/function_calling.py
View File

@ -313,7 +313,7 @@ def _convert_any_typed_dicts_to_pydantic(
subscriptable_origin = _py_38_safe_origin(origin)
type_args = tuple(
_convert_any_typed_dicts_to_pydantic(arg, depth=depth + 1, visited=visited)
for arg in type_args # type: ignore[index]
for arg in type_args
)
return subscriptable_origin[type_args] # type: ignore[index]
return type_

6
libs/core/langchain_core/utils/pydantic.py
View File

@ -383,7 +383,7 @@ if IS_PYDANTIC_V2:
) -> Union[dict[str, FieldInfoV2], dict[str, FieldInfoV1]]:
"""Get the field names of a Pydantic model."""
if hasattr(model, "model_fields"):
return model.model_fields # type: ignore[call-overload,arg-type]
return model.model_fields
if hasattr(model, "__fields__"):
return model.__fields__ # type: ignore[return-value]
@ -597,7 +597,7 @@ def create_model_v2(
Returns:
Type[BaseModel]: The created model.
"""
field_definitions = cast("dict[str, Any]", field_definitions or {}) # type: ignore[no-redef]
field_definitions = field_definitions or {}
if root:
if field_definitions:
@ -635,7 +635,7 @@ def create_model_v2(
if name.startswith("model"):
capture_warnings = True
with warnings.catch_warnings() if capture_warnings else nullcontext(): # type: ignore[attr-defined]
with warnings.catch_warnings() if capture_warnings else nullcontext():
if capture_warnings:
warnings.filterwarnings(action="ignore")
try:

18
libs/core/pyproject.toml
View File

@ -31,10 +31,9 @@ lint = [
"ruff<0.12.0,>=0.11.2",
]
typing = [
"mypy<1.11,>=1.10",
"mypy<1.16,>=1.15",
"types-pyyaml<7.0.0.0,>=6.0.12.2",
"types-requests<3.0.0.0,>=2.28.11.5",
"types-jinja2<3.0.0,>=2.11.9",
"langchain-text-splitters",
]
dev = [
@ -68,11 +67,16 @@ langchain-text-splitters = { path = "../text-splitters" }
[tool.mypy]
exclude = [ "notebooks", "examples", "example_data", "langchain_core/pydantic", "tests/unit_tests/utils/test_function_calling.py",]
disallow_untyped_defs = "True"
[[tool.mypy.overrides]]
module = [ "numpy", "pytest",]
ignore_missing_imports = true
strict = "True"
strict_bytes = "True"
enable_error_code = "deprecated"
report_deprecated_as_note = "True"
# TODO: activate for 'strict' checking
disallow_any_generics = "False"
warn_return_any = "False"
strict_equality = "False"
[tool.ruff]
target-version = "py39"

2
libs/core/tests/benchmarks/test_async_callbacks.py
View File

@ -49,7 +49,7 @@ async def test_async_callbacks_in_sync(benchmark: BenchmarkFixture) -> None:
infinite_cycle = cycle([AIMessage(content=" ".join(["hello", "goodbye"] * 500))])
model = GenericFakeChatModel(messages=infinite_cycle)
@benchmark
@benchmark # type: ignore[misc]
def sync_callbacks() -> None:
for _ in range(5):
for _ in model.stream("meow", {"callbacks": [MyCustomAsyncHandler()]}):

2
libs/core/tests/benchmarks/test_imports.py
View File

@ -49,6 +49,6 @@ from pytest_benchmark.fixture import BenchmarkFixture # type: ignore[import-unt
)
@pytest.mark.benchmark
def test_import_time(benchmark: BenchmarkFixture, import_path: str) -> None:
@benchmark
@benchmark # type: ignore[misc]
def import_in_subprocess() -> None:
subprocess.run([sys.executable, "-c", import_path], check=False)

3
libs/core/tests/unit_tests/callbacks/test_sync_callback_manager.py
View File

@ -1,5 +1,4 @@
from langchain_core.callbacks.base import BaseCallbackHandler
from langchain_core.callbacks.manager import BaseCallbackManager
from langchain_core.callbacks.base import BaseCallbackHandler, BaseCallbackManager
def test_remove_handler() -> None:

10
libs/core/tests/unit_tests/example_selectors/test_similarity.py
View File

@ -1,5 +1,5 @@
from collections.abc import Iterable
from typing import Any, Optional, cast
from typing import Any, Optional
from typing_extensions import override
@ -132,7 +132,7 @@ def test_from_examples() -> None:
assert selector.vectorstore_kwargs == {"vs_foo": "vs_bar"}
assert isinstance(selector.vectorstore, DummyVectorStore)
vector_store = cast("DummyVectorStore", selector.vectorstore)
vector_store = selector.vectorstore
assert vector_store.embeddings is embeddings
assert vector_store.init_arg == "some_init_arg"
assert vector_store.texts == ["bar"]
@ -158,7 +158,7 @@ async def test_afrom_examples() -> None:
assert selector.vectorstore_kwargs == {"vs_foo": "vs_bar"}
assert isinstance(selector.vectorstore, DummyVectorStore)
vector_store = cast("DummyVectorStore", selector.vectorstore)
vector_store = selector.vectorstore
assert vector_store.embeddings is embeddings
assert vector_store.init_arg == "some_init_arg"
assert vector_store.texts == ["bar"]
@ -212,7 +212,7 @@ def test_mmr_from_examples() -> None:
assert selector.vectorstore_kwargs == {"vs_foo": "vs_bar"}
assert isinstance(selector.vectorstore, DummyVectorStore)
vector_store = cast("DummyVectorStore", selector.vectorstore)
vector_store = selector.vectorstore
assert vector_store.embeddings is embeddings
assert vector_store.init_arg == "some_init_arg"
assert vector_store.texts == ["bar"]
@ -240,7 +240,7 @@ async def test_mmr_afrom_examples() -> None:
assert selector.vectorstore_kwargs == {"vs_foo": "vs_bar"}
assert isinstance(selector.vectorstore, DummyVectorStore)
vector_store = cast("DummyVectorStore", selector.vectorstore)
vector_store = selector.vectorstore
assert vector_store.embeddings is embeddings
assert vector_store.init_arg == "some_init_arg"
assert vector_store.texts == ["bar"]

10
libs/core/tests/unit_tests/output_parsers/test_list_parser.py
View File

@ -1,5 +1,5 @@
from collections.abc import AsyncIterator, Iterable
from typing import TypeVar, cast
from typing import TypeVar
from langchain_core.output_parsers.list import (
CommaSeparatedListOutputParser,
@ -101,7 +101,7 @@ def test_numbered_list() -> None:
(text2, ["apple", "banana", "cherry"]),
(text3, []),
]:
expectedlist = [[a] for a in cast("list[str]", expected)]
expectedlist = [[a] for a in expected]
assert parser.parse(text) == expected
assert add(parser.transform(t for t in text)) == (expected or None)
assert list(parser.transform(t for t in text)) == expectedlist
@ -137,7 +137,7 @@ def test_markdown_list() -> None:
(text2, ["apple", "banana", "cherry"]),
(text3, []),
]:
expectedlist = [[a] for a in cast("list[str]", expected)]
expectedlist = [[a] for a in expected]
assert parser.parse(text) == expected
assert add(parser.transform(t for t in text)) == (expected or None)
assert list(parser.transform(t for t in text)) == expectedlist
@ -240,7 +240,7 @@ async def test_numbered_list_async() -> None:
(text2, ["apple", "banana", "cherry"]),
(text3, []),
]:
expectedlist = [[a] for a in cast("list[str]", expected)]
expectedlist = [[a] for a in expected]
assert await parser.aparse(text) == expected
assert await aadd(parser.atransform(aiter_from_iter(t for t in text))) == (
expected or None
@ -283,7 +283,7 @@ async def test_markdown_list_async() -> None:
(text2, ["apple", "banana", "cherry"]),
(text3, []),
]:
expectedlist = [[a] for a in cast("list[str]", expected)]
expectedlist = [[a] for a in expected]
assert await parser.aparse(text) == expected
assert await aadd(parser.atransform(aiter_from_iter(t for t in text))) == (
expected or None

4
libs/core/tests/unit_tests/output_parsers/test_openai_tools.py
View File

@ -578,7 +578,7 @@ def test_parse_with_different_pydantic_2_proper() -> None:
# Can't get pydantic to work here due to the odd typing of tryig to support
# both v1 and v2 in the same codebase.
parser = PydanticToolsParser(tools=[Forecast]) # type: ignore[list-item]
parser = PydanticToolsParser(tools=[Forecast])
message = AIMessage(
content="",
tool_calls=[
@ -613,7 +613,7 @@ def test_parse_with_different_pydantic_1_proper() -> None:
# Can't get pydantic to work here due to the odd typing of tryig to support
# both v1 and v2 in the same codebase.
parser = PydanticToolsParser(tools=[Forecast]) # type: ignore[list-item]
parser = PydanticToolsParser(tools=[Forecast])
message = AIMessage(
content="",
tool_calls=[

30
libs/core/tests/unit_tests/prompts/test_chat.py
View File

@ -6,7 +6,7 @@ from typing import Any, Union, cast
import pytest
from packaging import version
from pydantic import ValidationError
from syrupy import SnapshotAssertion
from syrupy.assertion import SnapshotAssertion
from langchain_core._api.deprecation import (
LangChainPendingDeprecationWarning,
@ -15,6 +15,7 @@ from langchain_core.load import dumpd, load
from langchain_core.messages import (
AIMessage,
BaseMessage,
ChatMessage,
HumanMessage,
SystemMessage,
get_buffer_string,
@ -24,7 +25,6 @@ from langchain_core.prompts import PromptTemplate
from langchain_core.prompts.chat import (
AIMessagePromptTemplate,
BaseMessagePromptTemplate,
ChatMessage,
ChatMessagePromptTemplate,
ChatPromptTemplate,
HumanMessagePromptTemplate,
@ -82,7 +82,7 @@ def chat_prompt_template(
"""Create a chat prompt template."""
return ChatPromptTemplate(
input_variables=["foo", "bar", "context"],
messages=messages, # type: ignore[arg-type]
messages=messages,
)
@ -403,12 +403,12 @@ def test_chat_invalid_input_variables_extra() -> None:
),
):
ChatPromptTemplate(
messages=messages, # type: ignore[arg-type]
messages=messages,
input_variables=["foo"],
validate_template=True, # type: ignore[arg-type]
validate_template=True,
)
assert (
ChatPromptTemplate(messages=messages, input_variables=["foo"]).input_variables # type: ignore[arg-type]
ChatPromptTemplate(messages=messages, input_variables=["foo"]).input_variables
== []
)
@ -420,19 +420,19 @@ def test_chat_invalid_input_variables_missing() -> None:
match=re.escape("Got mismatched input_variables. Expected: {'foo'}. Got: []"),
):
ChatPromptTemplate(
messages=messages, # type: ignore[arg-type]
messages=messages,
input_variables=[],
validate_template=True, # type: ignore[arg-type]
validate_template=True,
)
assert ChatPromptTemplate(
messages=messages, # type: ignore[arg-type]
input_variables=[], # type: ignore[arg-type]
messages=messages,
input_variables=[],
).input_variables == ["foo"]
def test_infer_variables() -> None:
messages = [HumanMessagePromptTemplate.from_template("{foo}")]
prompt = ChatPromptTemplate(messages=messages) # type: ignore[arg-type, call-arg]
prompt = ChatPromptTemplate(messages=messages)
assert prompt.input_variables == ["foo"]
@ -443,7 +443,7 @@ def test_chat_valid_with_partial_variables() -> None:
)
]
prompt = ChatPromptTemplate(
messages=messages, # type: ignore[arg-type]
messages=messages,
input_variables=["question", "context"],
partial_variables={"formatins": "some structure"},
)
@ -457,9 +457,9 @@ def test_chat_valid_infer_variables() -> None:
"Do something with {question} using {context} giving it like {formatins}"
)
]
prompt = ChatPromptTemplate( # type: ignore[call-arg]
messages=messages, # type: ignore[arg-type]
partial_variables={"formatins": "some structure"}, # type: ignore[arg-type]
prompt = ChatPromptTemplate(
messages=messages,
partial_variables={"formatins": "some structure"},
)
assert set(prompt.input_variables) == {"question", "context"}
assert prompt.partial_variables == {"formatins": "some structure"}

2
libs/core/tests/unit_tests/prompts/test_prompt.py
View File

@ -6,7 +6,7 @@ from unittest import mock
import pytest
from packaging import version
from syrupy import SnapshotAssertion
from syrupy.assertion import SnapshotAssertion
from langchain_core.prompts.prompt import PromptTemplate
from langchain_core.prompts.string import PromptTemplateFormat

2
libs/core/tests/unit_tests/runnables/test_fallbacks.py
View File

@ -8,7 +8,7 @@ from typing import (
import pytest
from pydantic import BaseModel
from syrupy import SnapshotAssertion
from syrupy.assertion import SnapshotAssertion
from typing_extensions import override
from langchain_core.callbacks import CallbackManagerForLLMRun

5
libs/core/tests/unit_tests/runnables/test_graph.py
View File

@ -2,7 +2,7 @@ from typing import Any, Optional
from packaging import version
from pydantic import BaseModel
from syrupy import SnapshotAssertion
from syrupy.assertion import SnapshotAssertion
from typing_extensions import override
from langchain_core.language_models import FakeListLLM
@ -10,7 +10,8 @@ from langchain_core.output_parsers.list import CommaSeparatedListOutputParser
from langchain_core.output_parsers.string import StrOutputParser
from langchain_core.output_parsers.xml import XMLOutputParser
from langchain_core.prompts.prompt import PromptTemplate
from langchain_core.runnables.base import Runnable, RunnableConfig
from langchain_core.runnables import RunnableConfig
from langchain_core.runnables.base import Runnable
from langchain_core.runnables.graph import Edge, Graph, Node
from langchain_core.runnables.graph_mermaid import _escape_node_label
from langchain_core.utils.pydantic import (

4
libs/core/tests/unit_tests/runnables/test_imports.py
View File

@ -40,4 +40,6 @@ def test_all_imports() -> None:
def test_imports_for_specific_funcs() -> None:
"""Test that a few specific imports in more internal namespaces."""
# create_model implementation has been moved to langchain_core.utils.pydantic
from langchain_core.runnables.utils import create_model # noqa: F401
from langchain_core.runnables.utils import ( # type: ignore[attr-defined] # noqa: F401
create_model,
)

8
libs/core/tests/unit_tests/runnables/test_runnable.py
View File

@ -20,7 +20,7 @@ from freezegun import freeze_time
from packaging import version
from pydantic import BaseModel, Field
from pytest_mock import MockerFixture
from syrupy import SnapshotAssertion
from syrupy.assertion import SnapshotAssertion
from typing_extensions import TypedDict, override
from langchain_core.callbacks.manager import (
@ -557,7 +557,7 @@ def test_lambda_schemas(snapshot: SnapshotAssertion) -> None:
}
second_lambda = lambda x, y: (x["hello"], x["bye"], y["bah"]) # noqa: E731
assert RunnableLambda(second_lambda).get_input_jsonschema() == { # type: ignore[arg-type]
assert RunnableLambda(second_lambda).get_input_jsonschema() == {
"title": "RunnableLambdaInput",
"type": "object",
"properties": {"hello": {"title": "Hello"}, "bye": {"title": "Bye"}},
@ -1012,7 +1012,7 @@ def test_passthrough_tap(mocker: MockerFixture) -> None:
seq: Runnable = RunnablePassthrough(mock) | fake | RunnablePassthrough(mock)
assert seq.invoke("hello", my_kwarg="value") == 5 # type: ignore[call-arg]
assert seq.invoke("hello", my_kwarg="value") == 5
assert mock.call_args_list == [
mocker.call("hello", my_kwarg="value"),
mocker.call(5),
@ -4488,7 +4488,7 @@ def test_runnable_branch_invoke() -> None:
branch = RunnableBranch[int, int](
(lambda x: x > 100, raise_value_error),
# mypy cannot infer types from the lambda
(lambda x: x > 0 and x < 5, lambda x: x + 1), # type: ignore[misc]
(lambda x: x > 0 and x < 5, lambda x: x + 1),
(lambda x: x > 5, lambda x: x * 10),
lambda x: x - 1,
)

4
libs/core/tests/unit_tests/runnables/test_runnable_events_v2.py
View File

@ -2759,9 +2759,7 @@ async def test_custom_event_root_dispatch_with_in_tool() -> None:
return x + 1
# Ignoring type due to @tool not returning correct type annotations
events = await _collect_events(
foo.astream_events({"x": 2}, version="v2") # type: ignore[attr-defined]
)
events = await _collect_events(foo.astream_events({"x": 2}, version="v2"))
_assert_events_equal_allow_superset_metadata(
events,
[

6
libs/core/tests/unit_tests/runnables/test_tracing_interops.py
View File

@ -163,13 +163,13 @@ async def test_config_traceable_async_handoff() -> None:
def my_great_grandchild_function(a: int) -> int:
return my_great_great_grandchild_function(a)
@RunnableLambda # type: ignore[arg-type,attr-defined]
@RunnableLambda # type: ignore[arg-type]
async def my_grandchild_function(a: int) -> int:
return my_great_grandchild_function.invoke(a)
@traceable
async def my_child_function(a: int) -> int:
return await my_grandchild_function.ainvoke(a) * 3 # type: ignore[arg-type,attr-defined]
return await my_grandchild_function.ainvoke(a) * 3 # type: ignore[arg-type]
@traceable()
async def my_function(a: int) -> int:
@ -337,7 +337,7 @@ class TestRunnableSequenceParallelTraceNesting:
assert posts[i]["name"] == name
dotted_order = posts[i]["dotted_order"]
if prev_dotted_order is not None and not str(
expected_parents[name]
expected_parents[name] # type: ignore[index]
).startswith("RunnableParallel"):
assert dotted_order > prev_dotted_order, (
f"{name} not after {name_order[i - 1]}"

4
libs/core/tests/unit_tests/test_messages.py
View File

@ -435,8 +435,8 @@ def test_message_chunk_to_message() -> None:
expected = AIMessage(
content="I am",
tool_calls=[
create_tool_call(name="tool1", args={"a": 1}, id="1"), # type: ignore[arg-type]
create_tool_call(name="tool2", args={}, id="2"), # type: ignore[arg-type]
create_tool_call(name="tool1", args={"a": 1}, id="1"),
create_tool_call(name="tool2", args={}, id="2"),
],
invalid_tool_calls=[
create_invalid_tool_call(name="tool3", args=None, id="3", error=None),

8
libs/core/tests/unit_tests/test_tools.py
View File

@ -907,7 +907,7 @@ def test_validation_error_handling_non_validation_error(
async def _arun(self) -> str:
return "dummy"
_tool = _RaiseNonValidationErrorTool(handle_validation_error=handler) # type: ignore[call-arg]
_tool = _RaiseNonValidationErrorTool(handle_validation_error=handler)
with pytest.raises(NotImplementedError):
_tool.run({})
@ -972,7 +972,7 @@ async def test_async_validation_error_handling_non_validation_error(
async def _arun(self) -> str:
return "dummy"
_tool = _RaiseNonValidationErrorTool(handle_validation_error=handler) # type: ignore[call-arg]
_tool = _RaiseNonValidationErrorTool(handle_validation_error=handler)
with pytest.raises(NotImplementedError):
await _tool.arun({})
@ -1901,7 +1901,7 @@ def test_args_schema_explicitly_typed() -> None:
# type ignoring here since we're allowing overriding a type
# signature of pydantic.v1.BaseModel with pydantic.BaseModel
# for pydantic 2!
args_schema: type[BaseModel] = Foo # type: ignore[assignment]
args_schema: type[BaseModel] = Foo
def _run(self, *args: Any, **kwargs: Any) -> str:
return "foo"
@ -2157,7 +2157,7 @@ def test_tool_annotations_preserved() -> None:
"""Tool docstring."""
return "foo"
schema = my_tool.get_input_schema() # type: ignore[attr-defined]
schema = my_tool.get_input_schema()
func = my_tool.func # type: ignore[attr-defined]

40
libs/core/tests/unit_tests/utils/test_function_calling.py
View File

@ -1,4 +1,3 @@
# mypy: disable-error-code="annotation-unchecked"
import sys
import typing
from collections.abc import Iterable, Mapping, MutableMapping, Sequence
@ -15,12 +14,11 @@ from typing import TypedDict as TypingTypedDict
import pytest
from pydantic import BaseModel as BaseModelV2Maybe # pydantic: ignore
from pydantic import Field as FieldV2Maybe # pydantic: ignore
from typing_extensions import (
TypedDict as ExtensionsTypedDict,
)
from typing_extensions import TypeAlias
from typing_extensions import TypedDict as ExtensionsTypedDict
try:
from typing import Annotated as TypingAnnotated # type: ignore[attr-defined]
from typing import Annotated as TypingAnnotated
except ImportError:
TypingAnnotated = ExtensionsAnnotated
@ -387,8 +385,8 @@ def test_convert_to_openai_function(
assert actual == runnable_expected
# Test simple Tool
def my_function(input_string: str) -> str:
pass
def my_function(_: str) -> str:
return ""
tool = Tool(
name="dummy_function",
@ -738,20 +736,25 @@ def test_tool_outputs() -> None:
assert not response.tool_calls
@pytest.mark.parametrize("use_extension_typed_dict", [True, False])
@pytest.mark.parametrize("use_extension_annotated", [True, False])
@pytest.mark.parametrize(
"typed_dict",
[ExtensionsTypedDict, TypingTypedDict],
ids=["typing_extensions.TypedDict", "typing.TypedDict"],
)
@pytest.mark.parametrize(
"annotated",
[ExtensionsAnnotated, TypingAnnotated],
ids=["typing_extensions.Annotated", "typing.Annotated"],
)
def test__convert_typed_dict_to_openai_function(
*, use_extension_typed_dict: bool, use_extension_annotated: bool
typed_dict: TypeAlias, annotated: TypeAlias
) -> None:
typed_dict = ExtensionsTypedDict if use_extension_typed_dict else TypingTypedDict
annotated = TypingAnnotated if use_extension_annotated else TypingAnnotated
class SubTool(typed_dict):
class SubTool(typed_dict): # type: ignore[misc]
"""Subtool docstring."""
args: annotated[dict[str, Any], {}, "this does bar"] # noqa: F722
class Tool(typed_dict):
class Tool(typed_dict): # type: ignore[misc]
"""Docstring.
Args:
@ -981,7 +984,7 @@ def test__convert_typed_dict_to_openai_function(
@pytest.mark.parametrize("typed_dict", [ExtensionsTypedDict, TypingTypedDict])
def test__convert_typed_dict_to_openai_function_fail(typed_dict: type) -> None:
class Tool(typed_dict):
class Tool(typed_dict): # type: ignore[misc]
arg1: typing.MutableSet # Pydantic 2 supports this, but pydantic v1 does not.
# Error should be raised since we're using v1 code path here
@ -994,11 +997,12 @@ def test__convert_typed_dict_to_openai_function_fail(typed_dict: type) -> None:
)
def test_convert_union_type_py_39() -> None:
@tool
def magic_function(input: int | str) -> str: # noqa: FA102
def magic_function(value: int | str) -> str: # type: ignore[syntax,unused-ignore] # noqa: ARG001,FA102
"""Compute a magic function."""
return ""
result = convert_to_openai_function(magic_function)
assert result["parameters"]["properties"]["input"] == {
assert result["parameters"]["properties"]["value"] == {
"anyOf": [{"type": "integer"}, {"type": "string"}]
}

3
libs/core/tests/unit_tests/utils/test_pydantic.py
View File

@ -56,7 +56,6 @@ def test_pre_init_decorator_with_more_defaults() -> None:
return v
# Try to create an instance of Foo
# nothing is required, but mypy can't track the default for `c`
Foo()
@ -177,7 +176,7 @@ def test_fields_pydantic_v1() -> None:
x: int
fields = get_fields(Foo)
assert fields == {"x": Foo.model_fields["x"]} # type: ignore[index]
assert fields == {"x": Foo.model_fields["x"]}
@pytest.mark.skipif(not IS_PYDANTIC_V2, reason="Only tests Pydantic v2")

81
libs/core/uv.lock
View File

@ -980,7 +980,6 @@ test = [
typing = [
{ name = "langchain-text-splitters" },
{ name = "mypy" },
{ name = "types-jinja2" },
{ name = "types-pyyaml" },
{ name = "types-requests" },
]
@ -1025,8 +1024,7 @@ test = [
test-integration = []
typing = [
{ name = "langchain-text-splitters", directory = "../text-splitters" },
{ name = "mypy", specifier = ">=1.10,<1.11" },
{ name = "types-jinja2", specifier = ">=2.11.9,<3.0.0" },
{ name = "mypy", specifier = ">=1.15,<1.16" },
{ name = "types-pyyaml", specifier = ">=6.0.12.2,<7.0.0.0" },
{ name = "types-requests", specifier = ">=2.28.11.5,<3.0.0.0" },
]
@ -1244,36 +1242,46 @@ wheels = [
[[package]]
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version = "1.15.0"
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{ name = "mypy-extensions" },
{ name = "tomli", marker = "python_full_version < '3.11'" },
{ name = "typing-extensions" },
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