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Install and use ruff format instead of black for code formatting. (#12585)

Browse Source 
Best to review one commit at a time, since two of the commits are 100%
autogenerated changes from running `ruff format`:
- Install and use `ruff format` instead of black for code formatting.
- Output of `ruff format .` in the `langchain` package.
- Use `ruff format` in experimental package.
- Format changes in experimental package by `ruff format`.
- Manual formatting fixes to make `ruff .` pass.
This commit is contained in:
Predrag Gruevski 2023-10-31 10:53:12 -04:00 committed by GitHub
parent bfd719f9d8
commit f94e24dfd7
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
61 changed files with 246 additions and 399 deletions
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8
.github/CONTRIBUTING.md vendored
View File

@ -134,7 +134,7 @@ Run these locally before submitting a PR; the CI system will check also.
#### Code Formatting #### Code Formatting
Formatting for this project is done via a combination of [Black](https://black.readthedocs.io/en/stable/) and [ruff](https://docs.astral.sh/ruff/rules/). Formatting for this project is done via [ruff](https://docs.astral.sh/ruff/rules/).
To run formatting for docs, cookbook and templates: To run formatting for docs, cookbook and templates:
@ -159,7 +159,7 @@ This is especially useful when you have made changes to a subset of the project
#### Linting #### Linting
Linting for this project is done via a combination of [Black](https://black.readthedocs.io/en/stable/), [ruff](https://docs.astral.sh/ruff/rules/), and [mypy](http://mypy-lang.org/). Linting for this project is done via a combination of [ruff](https://docs.astral.sh/ruff/rules/) and [mypy](http://mypy-lang.org/).
To run linting for docs, cookbook and templates: To run linting for docs, cookbook and templates:
@ -302,8 +302,8 @@ make api_docs_linkcheck
### Verify Documentation changes ### Verify Documentation changes
After pushing documentation changes to the repository, you can preview and verify that the changes are After pushing documentation changes to the repository, you can preview and verify that the changes are
what you wanted by clicking the `View deployment` or `Visit Preview` buttons on the pull request `Conversation` page. what you wanted by clicking the `View deployment` or `Visit Preview` buttons on the pull request `Conversation` page.
This will take you to a preview of the documentation changes. This will take you to a preview of the documentation changes.
This preview is created by [Vercel](https://vercel.com/docs/getting-started-with-vercel). This preview is created by [Vercel](https://vercel.com/docs/getting-started-with-vercel).

4
Makefile
View File

@ -43,10 +43,10 @@ spell_fix:
lint: lint:
poetry run ruff docs templates cookbook poetry run ruff docs templates cookbook
poetry run black docs templates cookbook --check poetry run ruff format docs templates cookbook --diff
format format_diff: format format_diff:
poetry run black docs templates cookbook poetry run ruff format docs templates cookbook
poetry run ruff --select I --fix docs templates cookbook poetry run ruff --select I --fix docs templates cookbook
###################### ######################

6
libs/experimental/Makefile
View File

@ -9,7 +9,7 @@ TEST_FILE ?= tests/unit_tests/
test: test:
poetry run pytest $(TEST_FILE) poetry run pytest $(TEST_FILE)
tests: tests:
poetry run pytest $(TEST_FILE) poetry run pytest $(TEST_FILE)
test_watch: test_watch:
@ -33,11 +33,11 @@ lint_diff format_diff: PYTHON_FILES=$(shell git diff --relative=libs/experimenta
lint lint_diff: lint lint_diff:
poetry run mypy $(PYTHON_FILES) poetry run mypy $(PYTHON_FILES)
poetry run black $(PYTHON_FILES) --check poetry run ruff format $(PYTHON_FILES) --diff
poetry run ruff . poetry run ruff .
format format_diff: format format_diff:
poetry run black $(PYTHON_FILES) poetry run ruff format $(PYTHON_FILES)
poetry run ruff --select I --fix $(PYTHON_FILES) poetry run ruff --select I --fix $(PYTHON_FILES)
spell_check: spell_check:

2
libs/experimental/langchain_experimental/tabular_synthetic_data/openai.py
View File

@ -16,7 +16,7 @@ def create_openai_data_generator(
llm: ChatOpenAI, llm: ChatOpenAI,
prompt: BasePromptTemplate, prompt: BasePromptTemplate,
output_parser: Optional[BaseLLMOutputParser] = None, output_parser: Optional[BaseLLMOutputParser] = None,
**kwargs: Any **kwargs: Any,
) -> SyntheticDataGenerator: ) -> SyntheticDataGenerator:
""" """
Create an instance of SyntheticDataGenerator tailored for OpenAI models. Create an instance of SyntheticDataGenerator tailored for OpenAI models.

8
libs/experimental/langchain_experimental/tot/thought_generation.py
View File

@ -29,7 +29,7 @@ class BaseThoughtGenerationStrategy(LLMChain):
self, self,
problem_description: str, problem_description: str,
thoughts_path: Tuple[str, ...] = (), thoughts_path: Tuple[str, ...] = (),
**kwargs: Any **kwargs: Any,
) -> str: ) -> str:
""" """
Generate the next thought given the problem description and the thoughts Generate the next thought given the problem description and the thoughts
@ -52,7 +52,7 @@ class SampleCoTStrategy(BaseThoughtGenerationStrategy):
self, self,
problem_description: str, problem_description: str,
thoughts_path: Tuple[str, ...] = (), thoughts_path: Tuple[str, ...] = (),
**kwargs: Any **kwargs: Any,
) -> str: ) -> str:
response_text = self.predict_and_parse( response_text = self.predict_and_parse(
problem_description=problem_description, thoughts=thoughts_path, **kwargs problem_description=problem_description, thoughts=thoughts_path, **kwargs
@ -76,14 +76,14 @@ class ProposePromptStrategy(BaseThoughtGenerationStrategy):
self, self,
problem_description: str, problem_description: str,
thoughts_path: Tuple[str, ...] = (), thoughts_path: Tuple[str, ...] = (),
**kwargs: Any **kwargs: Any,
) -> str: ) -> str:
if thoughts_path not in self.tot_memory or not self.tot_memory[thoughts_path]: if thoughts_path not in self.tot_memory or not self.tot_memory[thoughts_path]:
new_thoughts = self.predict_and_parse( new_thoughts = self.predict_and_parse(
problem_description=problem_description, problem_description=problem_description,
thoughts=thoughts_path, thoughts=thoughts_path,
n=self.c, n=self.c,
**kwargs **kwargs,
) )
if not new_thoughts: if not new_thoughts:
return "" return ""

122
libs/experimental/poetry.lock generated
View File

@ -350,48 +350,6 @@ soupsieve = ">1.2"
html5lib = ["html5lib"] html5lib = ["html5lib"]
lxml = ["lxml"] lxml = ["lxml"]
[[package]]
name = "black"
version = "23.10.0"
description = "The uncompromising code formatter."
optional = false
python-versions = ">=3.8"
files = [
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]
[package.dependencies]
click = ">=8.0.0"
mypy-extensions = ">=0.4.3"
packaging = ">=22.0"
pathspec = ">=0.9.0"
platformdirs = ">=2"
tomli = {version = ">=1.1.0", markers = "python_version < \"3.11\""}
typing-extensions = {version = ">=4.0.1", markers = "python_version < \"3.11\""}
[package.extras]
colorama = ["colorama (>=0.4.3)"]
d = ["aiohttp (>=3.7.4)"]
jupyter = ["ipython (>=7.8.0)", "tokenize-rt (>=3.2.0)"]
uvloop = ["uvloop (>=0.15.2)"]
[[package]] [[package]]
name = "bleach" name = "bleach"
version = "6.1.0" version = "6.1.0"
@ -648,7 +606,7 @@ files = [
name = "click" name = "click"
version = "8.1.7" version = "8.1.7"
description = "Composable command line interface toolkit" description = "Composable command line interface toolkit"
optional = false optional = true
python-versions = ">=3.7" python-versions = ">=3.7"
files = [ files = [
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@ -1044,7 +1002,7 @@ files = [
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@ -1054,6 +1012,7 @@ files = [
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] ]
[package.extras] [package.extras]
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] ]
[[package]] [[package]]
@ -3609,11 +3536,6 @@ files = [
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@ -4957,4 +4879,4 @@ extended-testing = ["faker", "presidio-analyzer", "presidio-anonymizer", "senten
[metadata] [metadata]
lock-version = "2.0" lock-version = "2.0"
python-versions = ">=3.8.1,<4.0" python-versions = ">=3.8.1,<4.0"
content-hash = "f23fcff0e5ab8f172578b4f4da8dd204375357c7a5ad10c97bb77de7208bc889" content-hash = "f038878d61e8970fa9062263822db5757face25be16a2de7fda24732df86c6f0"

3
libs/experimental/pyproject.toml
View File

@ -18,8 +18,7 @@ vowpal-wabbit-next = {version = "0.6.0", optional = true}
sentence-transformers = {version = "^2", optional = true} sentence-transformers = {version = "^2", optional = true}
[tool.poetry.group.lint.dependencies] [tool.poetry.group.lint.dependencies]
ruff = "^0.1" ruff = "^0.1.3"
black = "^23.10.0"
[tool.poetry.group.typing.dependencies] [tool.poetry.group.typing.dependencies]
mypy = "^0.991" mypy = "^0.991"

7
libs/experimental/tests/unit_tests/rl_chain/test_pick_best_chain_call.py
View File

@ -95,7 +95,8 @@ def test_update_with_delayed_score_with_auto_validator_throws() -> None:
assert selection_metadata.selected.score == 3.0 # type: ignore assert selection_metadata.selected.score == 3.0 # type: ignore
with pytest.raises(RuntimeError): with pytest.raises(RuntimeError):
chain.update_with_delayed_score( chain.update_with_delayed_score(
chain_response=response, score=100 # type: ignore chain_response=response,
score=100, # type: ignore
) )
@ -121,7 +122,9 @@ def test_update_with_delayed_score_force() -> None:
selection_metadata = response["selection_metadata"] # type: ignore selection_metadata = response["selection_metadata"] # type: ignore
assert selection_metadata.selected.score == 3.0 # type: ignore assert selection_metadata.selected.score == 3.0 # type: ignore
chain.update_with_delayed_score( chain.update_with_delayed_score(
chain_response=response, score=100, force_score=True # type: ignore chain_response=response,
score=100,
force_score=True, # type: ignore
) )
assert selection_metadata.selected.score == 100.0 # type: ignore assert selection_metadata.selected.score == 100.0 # type: ignore

4
libs/langchain/Makefile
View File

@ -50,11 +50,11 @@ lint lint_diff:
./scripts/check_pydantic.sh . ./scripts/check_pydantic.sh .
./scripts/check_imports.sh ./scripts/check_imports.sh
poetry run ruff . poetry run ruff .
[ "$(PYTHON_FILES)" = "" ] || poetry run black $(PYTHON_FILES) --check [ "$(PYTHON_FILES)" = "" ] || poetry run ruff format $(PYTHON_FILES) --diff
[ "$(PYTHON_FILES)" = "" ] || poetry run mypy $(PYTHON_FILES) [ "$(PYTHON_FILES)" = "" ] || poetry run mypy $(PYTHON_FILES)
format format_diff: format format_diff:
[ "$(PYTHON_FILES)" = "" ] || poetry run black $(PYTHON_FILES) [ "$(PYTHON_FILES)" = "" ] || poetry run ruff format $(PYTHON_FILES)
[ "$(PYTHON_FILES)" = "" ] || poetry run ruff --select I --fix $(PYTHON_FILES) [ "$(PYTHON_FILES)" = "" ] || poetry run ruff --select I --fix $(PYTHON_FILES)
spell_check: spell_check:

2
libs/langchain/langchain/_api/path.py
View File

@ -22,7 +22,7 @@ def as_import_path(
file: Union[Path, str], file: Union[Path, str],
*, *,
suffix: Optional[str] = None, suffix: Optional[str] = None,
relative_to: Path = PACKAGE_DIR relative_to: Path = PACKAGE_DIR,
) -> str: ) -> str:
"""Path of the file as a LangChain import exclude langchain top namespace.""" """Path of the file as a LangChain import exclude langchain top namespace."""
if isinstance(file, str): if isinstance(file, str):

4
libs/langchain/langchain/agents/agent_toolkits/conversational_retrieval/openai_functions.py
View File

@ -32,7 +32,7 @@ def create_conversational_retrieval_agent(
system_message: Optional[SystemMessage] = None, system_message: Optional[SystemMessage] = None,
verbose: bool = False, verbose: bool = False,
max_token_limit: int = 2000, max_token_limit: int = 2000,
**kwargs: Any **kwargs: Any,
) -> AgentExecutor: ) -> AgentExecutor:
"""A convenience method for creating a conversational retrieval agent. """A convenience method for creating a conversational retrieval agent.
@ -83,5 +83,5 @@ def create_conversational_retrieval_agent(
memory=memory, memory=memory,
verbose=verbose, verbose=verbose,
return_intermediate_steps=remember_intermediate_steps, return_intermediate_steps=remember_intermediate_steps,
**kwargs **kwargs,
) )

3
libs/langchain/langchain/callbacks/argilla_callback.py
View File

@ -284,7 +284,8 @@ class ArgillaCallbackHandler(BaseCallbackHandler):
}, },
} }
for prompt, output in zip( for prompt, output in zip(
prompts, chain_output_val # type: ignore prompts, # type: ignore
chain_output_val,
) )
] ]
) )

4
libs/langchain/langchain/callbacks/flyte_callback.py
View File

@ -195,7 +195,9 @@ class FlyteCallbackHandler(BaseMetadataCallbackHandler, BaseCallbackHandler):
) )
) )
complexity_metrics: Dict[str, float] = generation_resp.pop("text_complexity_metrics") # type: ignore # noqa: E501 complexity_metrics: Dict[str, float] = generation_resp.pop(
"text_complexity_metrics"
) # type: ignore # noqa: E501
self.deck.append( self.deck.append(
self.markdown_renderer().to_html("#### Text Complexity Metrics") self.markdown_renderer().to_html("#### Text Complexity Metrics")
) )

12
libs/langchain/langchain/callbacks/manager.py
View File

@ -64,20 +64,14 @@ logger = logging.getLogger(__name__)
openai_callback_var: ContextVar[Optional[OpenAICallbackHandler]] = ContextVar( openai_callback_var: ContextVar[Optional[OpenAICallbackHandler]] = ContextVar(
"openai_callback", default=None "openai_callback", default=None
) )
tracing_callback_var: ContextVar[ tracing_callback_var: ContextVar[Optional[LangChainTracerV1]] = ContextVar( # noqa: E501
Optional[LangChainTracerV1]
] = ContextVar( # noqa: E501
"tracing_callback", default=None "tracing_callback", default=None
) )
wandb_tracing_callback_var: ContextVar[ wandb_tracing_callback_var: ContextVar[Optional[WandbTracer]] = ContextVar( # noqa: E501
Optional[WandbTracer]
] = ContextVar( # noqa: E501
"tracing_wandb_callback", default=None "tracing_wandb_callback", default=None
) )
tracing_v2_callback_var: ContextVar[ tracing_v2_callback_var: ContextVar[Optional[LangChainTracer]] = ContextVar( # noqa: E501
Optional[LangChainTracer]
] = ContextVar( # noqa: E501
"tracing_callback_v2", default=None "tracing_callback_v2", default=None
) )
run_collector_var: ContextVar[ run_collector_var: ContextVar[

4
libs/langchain/langchain/callbacks/mlflow_callback.py
View File

@ -371,7 +371,9 @@ class MlflowCallbackHandler(BaseMetadataCallbackHandler, BaseCallbackHandler):
nlp=self.nlp, nlp=self.nlp,
) )
) )
complexity_metrics: Dict[str, float] = generation_resp.pop("text_complexity_metrics") # type: ignore # noqa: E501 complexity_metrics: Dict[str, float] = generation_resp.pop(
"text_complexity_metrics"
) # type: ignore # noqa: E501
self.mlflg.metrics( self.mlflg.metrics(
complexity_metrics, complexity_metrics,
step=self.metrics["step"], step=self.metrics["step"],

2
libs/langchain/langchain/callbacks/streaming_stdout.py
View File

@ -19,7 +19,7 @@ class StreamingStdOutCallbackHandler(BaseCallbackHandler):
self, self,
serialized: Dict[str, Any], serialized: Dict[str, Any],
messages: List[List[BaseMessage]], messages: List[List[BaseMessage]],
**kwargs: Any **kwargs: Any,
) -> None: ) -> None:
"""Run when LLM starts running.""" """Run when LLM starts running."""

2
libs/langchain/langchain/callbacks/streaming_stdout_final_only.py
View File

@ -32,7 +32,7 @@ class FinalStreamingStdOutCallbackHandler(StreamingStdOutCallbackHandler):
*, *,
answer_prefix_tokens: Optional[List[str]] = None, answer_prefix_tokens: Optional[List[str]] = None,
strip_tokens: bool = True, strip_tokens: bool = True,
stream_prefix: bool = False stream_prefix: bool = False,
) -> None: ) -> None:
"""Instantiate FinalStreamingStdOutCallbackHandler. """Instantiate FinalStreamingStdOutCallbackHandler.

2
libs/langchain/langchain/callbacks/tracers/root_listeners.py
View File

@ -11,7 +11,7 @@ class RootListenersTracer(BaseTracer):
*, *,
on_start: Optional[Callable[[Run], None]], on_start: Optional[Callable[[Run], None]],
on_end: Optional[Callable[[Run], None]], on_end: Optional[Callable[[Run], None]],
on_error: Optional[Callable[[Run], None]] on_error: Optional[Callable[[Run], None]],
) -> None: ) -> None:
super().__init__() super().__init__()

4
libs/langchain/langchain/chains/api/openapi/chain.py
View File

@ -171,7 +171,7 @@ class OpenAPIEndpointChain(Chain, BaseModel):
llm: BaseLanguageModel, llm: BaseLanguageModel,
requests: Optional[Requests] = None, requests: Optional[Requests] = None,
return_intermediate_steps: bool = False, return_intermediate_steps: bool = False,
**kwargs: Any **kwargs: Any,
# TODO: Handle async # TODO: Handle async
) -> "OpenAPIEndpointChain": ) -> "OpenAPIEndpointChain":
"""Create an OpenAPIEndpoint from a spec at the specified url.""" """Create an OpenAPIEndpoint from a spec at the specified url."""
@ -194,7 +194,7 @@ class OpenAPIEndpointChain(Chain, BaseModel):
return_intermediate_steps: bool = False, return_intermediate_steps: bool = False,
raw_response: bool = False, raw_response: bool = False,
callbacks: Callbacks = None, callbacks: Callbacks = None,
**kwargs: Any **kwargs: Any,
# TODO: Handle async # TODO: Handle async
) -> "OpenAPIEndpointChain": ) -> "OpenAPIEndpointChain":
"""Create an OpenAPIEndpointChain from an operation and a spec.""" """Create an OpenAPIEndpointChain from an operation and a spec."""

4
libs/langchain/langchain/chains/openai_functions/tagging.py
View File

@ -32,7 +32,7 @@ def create_tagging_chain(
schema: dict, schema: dict,
llm: BaseLanguageModel, llm: BaseLanguageModel,
prompt: Optional[ChatPromptTemplate] = None, prompt: Optional[ChatPromptTemplate] = None,
**kwargs: Any **kwargs: Any,
) -> Chain: ) -> Chain:
"""Creates a chain that extracts information from a passage """Creates a chain that extracts information from a passage
based on a schema. based on a schema.
@ -62,7 +62,7 @@ def create_tagging_chain_pydantic(
pydantic_schema: Any, pydantic_schema: Any,
llm: BaseLanguageModel, llm: BaseLanguageModel,
prompt: Optional[ChatPromptTemplate] = None, prompt: Optional[ChatPromptTemplate] = None,
**kwargs: Any **kwargs: Any,
) -> Chain: ) -> Chain:
"""Creates a chain that extracts information from a passage """Creates a chain that extracts information from a passage
based on a pydantic schema. based on a pydantic schema.

4
libs/langchain/langchain/chat_models/promptlayer_openai.py
View File

@ -44,7 +44,7 @@ class PromptLayerChatOpenAI(ChatOpenAI):
stop: Optional[List[str]] = None, stop: Optional[List[str]] = None,
run_manager: Optional[CallbackManagerForLLMRun] = None, run_manager: Optional[CallbackManagerForLLMRun] = None,
stream: Optional[bool] = None, stream: Optional[bool] = None,
**kwargs: Any **kwargs: Any,
) -> ChatResult: ) -> ChatResult:
"""Call ChatOpenAI generate and then call PromptLayer API to log the request.""" """Call ChatOpenAI generate and then call PromptLayer API to log the request."""
from promptlayer.utils import get_api_key, promptlayer_api_request from promptlayer.utils import get_api_key, promptlayer_api_request
@ -86,7 +86,7 @@ class PromptLayerChatOpenAI(ChatOpenAI):
stop: Optional[List[str]] = None, stop: Optional[List[str]] = None,
run_manager: Optional[AsyncCallbackManagerForLLMRun] = None, run_manager: Optional[AsyncCallbackManagerForLLMRun] = None,
stream: Optional[bool] = None, stream: Optional[bool] = None,
**kwargs: Any **kwargs: Any,
) -> ChatResult: ) -> ChatResult:
"""Call ChatOpenAI agenerate and then call PromptLayer to log.""" """Call ChatOpenAI agenerate and then call PromptLayer to log."""
from promptlayer.utils import get_api_key, promptlayer_api_request_async from promptlayer.utils import get_api_key, promptlayer_api_request_async

4
libs/langchain/langchain/document_loaders/azure_blob_storage_container.py
View File

@ -36,7 +36,9 @@ class AzureBlobStorageContainerLoader(BaseLoader):
blob_list = container.list_blobs(name_starts_with=self.prefix) blob_list = container.list_blobs(name_starts_with=self.prefix)
for blob in blob_list: for blob in blob_list:
loader = AzureBlobStorageFileLoader( loader = AzureBlobStorageFileLoader(
self.conn_str, self.container, blob.name # type: ignore self.conn_str,
self.container,
blob.name, # type: ignore
) )
docs.extend(loader.load()) docs.extend(loader.load())
return docs return docs

4
libs/langchain/langchain/document_loaders/blackboard.py
View File

@ -211,7 +211,9 @@ class BlackboardLoader(WebBaseLoader):
""" """
# Create the document loader # Create the document loader
loader = DirectoryLoader( loader = DirectoryLoader(
path=self.folder_path, glob="*.pdf", loader_cls=PyPDFLoader # type: ignore path=self.folder_path,
glob="*.pdf",
loader_cls=PyPDFLoader, # type: ignore
) )
# Load the documents # Load the documents
documents = loader.load() documents = loader.load()

2
libs/langchain/langchain/embeddings/johnsnowlabs.py
View File

@ -25,7 +25,7 @@ class JohnSnowLabsEmbeddings(BaseModel, Embeddings):
self, self,
model: Any = "embed_sentence.bert", model: Any = "embed_sentence.bert",
hardware_target: str = "cpu", hardware_target: str = "cpu",
**kwargs: Any **kwargs: Any,
): ):
"""Initialize the johnsnowlabs model.""" """Initialize the johnsnowlabs model."""
super().__init__(**kwargs) super().__init__(**kwargs)

4
libs/langchain/langchain/embeddings/localai.py
View File

@ -269,9 +269,7 @@ class LocalAIEmbeddings(BaseModel, Embeddings):
self, self,
input=[text], input=[text],
**self._invocation_params, **self._invocation_params,
)["data"][ )["data"][0]["embedding"]
0
]["embedding"]
async def _aembedding_func(self, text: str, *, engine: str) -> List[float]: async def _aembedding_func(self, text: str, *, engine: str) -> List[float]:
"""Call out to LocalAI's embedding endpoint.""" """Call out to LocalAI's embedding endpoint."""

2
libs/langchain/langchain/embeddings/nlpcloud.py
View File

@ -26,7 +26,7 @@ class NLPCloudEmbeddings(BaseModel, Embeddings):
self, self,
model_name: str = "paraphrase-multilingual-mpnet-base-v2", model_name: str = "paraphrase-multilingual-mpnet-base-v2",
gpu: bool = False, gpu: bool = False,
**kwargs: Any **kwargs: Any,
) -> None: ) -> None:
super().__init__(model_name=model_name, gpu=gpu, **kwargs) super().__init__(model_name=model_name, gpu=gpu, **kwargs)

4
libs/langchain/langchain/embeddings/openai.py
View File

@ -393,9 +393,7 @@ class OpenAIEmbeddings(BaseModel, Embeddings):
self, self,
input="", input="",
**self._invocation_params, **self._invocation_params,
)[ )["data"][0]["embedding"]
"data"
][0]["embedding"]
else: else:
average = np.average(_result, axis=0, weights=num_tokens_in_batch[i]) average = np.average(_result, axis=0, weights=num_tokens_in_batch[i])
embeddings[i] = (average / np.linalg.norm(average)).tolist() embeddings[i] = (average / np.linalg.norm(average)).tolist()

4
libs/langchain/langchain/indexes/vectorstore.py
View File

@ -34,7 +34,7 @@ class VectorStoreIndexWrapper(BaseModel):
question: str, question: str,
llm: Optional[BaseLanguageModel] = None, llm: Optional[BaseLanguageModel] = None,
retriever_kwargs: Optional[Dict[str, Any]] = None, retriever_kwargs: Optional[Dict[str, Any]] = None,
**kwargs: Any **kwargs: Any,
) -> str: ) -> str:
"""Query the vectorstore.""" """Query the vectorstore."""
llm = llm or OpenAI(temperature=0) llm = llm or OpenAI(temperature=0)
@ -49,7 +49,7 @@ class VectorStoreIndexWrapper(BaseModel):
question: str, question: str,
llm: Optional[BaseLanguageModel] = None, llm: Optional[BaseLanguageModel] = None,
retriever_kwargs: Optional[Dict[str, Any]] = None, retriever_kwargs: Optional[Dict[str, Any]] = None,
**kwargs: Any **kwargs: Any,
) -> dict: ) -> dict:
"""Query the vectorstore and get back sources.""" """Query the vectorstore and get back sources."""
llm = llm or OpenAI(temperature=0) llm = llm or OpenAI(temperature=0)

2
libs/langchain/langchain/llms/predibase.py
View File

@ -25,7 +25,7 @@ class Predibase(LLM):
prompt: str, prompt: str,
stop: Optional[List[str]] = None, stop: Optional[List[str]] = None,
run_manager: Optional[CallbackManagerForLLMRun] = None, run_manager: Optional[CallbackManagerForLLMRun] = None,
**kwargs: Any **kwargs: Any,
) -> str: ) -> str:
try: try:
from predibase import PredibaseClient from predibase import PredibaseClient

2
libs/langchain/langchain/retrievers/document_compressors/chain_filter.py
View File

@ -58,7 +58,7 @@ class LLMChainFilter(BaseDocumentCompressor):
cls, cls,
llm: BaseLanguageModel, llm: BaseLanguageModel,
prompt: Optional[BasePromptTemplate] = None, prompt: Optional[BasePromptTemplate] = None,
**kwargs: Any **kwargs: Any,
) -> "LLMChainFilter": ) -> "LLMChainFilter":
"""Create a LLMChainFilter from a language model. """Create a LLMChainFilter from a language model.

2
libs/langchain/langchain/retrievers/tavily_search_api.py
View File

@ -49,7 +49,7 @@ class TavilySearchAPIRetriever(BaseRetriever):
exclude_domains=self.exclude_domains, exclude_domains=self.exclude_domains,
include_raw_content=self.include_raw_content, include_raw_content=self.include_raw_content,
include_images=self.include_images, include_images=self.include_images,
**self.kwargs **self.kwargs,
) )
docs = [ docs = [
Document( Document(

4
libs/langchain/langchain/schema/messages.py
View File

@ -241,9 +241,7 @@ class FunctionMessageChunk(FunctionMessage, BaseMessageChunk):
# Ignoring mypy re-assignment here since we're overriding the value # Ignoring mypy re-assignment here since we're overriding the value
# to make sure that the chunk variant can be discriminated from the # to make sure that the chunk variant can be discriminated from the
# non-chunk variant. # non-chunk variant.
type: Literal[ type: Literal["FunctionMessageChunk"] = "FunctionMessageChunk" # type: ignore[assignment]
"FunctionMessageChunk"
] = "FunctionMessageChunk" # type: ignore[assignment]
def __add__(self, other: Any) -> BaseMessageChunk: # type: ignore def __add__(self, other: Any) -> BaseMessageChunk: # type: ignore
if isinstance(other, FunctionMessageChunk): if isinstance(other, FunctionMessageChunk):

8
libs/langchain/langchain/schema/runnable/base.py
View File

@ -933,9 +933,7 @@ class Runnable(Generic[Input, Output], ABC):
) )
if accepts_run_manager(transformer): if accepts_run_manager(transformer):
kwargs["run_manager"] = run_manager kwargs["run_manager"] = run_manager
iterator = transformer( iterator = transformer(input_for_transform, **kwargs) # type: ignore[call-arg]
input_for_transform, **kwargs
) # type: ignore[call-arg]
for chunk in iterator: for chunk in iterator:
yield chunk yield chunk
if final_output_supported: if final_output_supported:
@ -1011,9 +1009,7 @@ class Runnable(Generic[Input, Output], ABC):
) )
if accepts_run_manager(transformer): if accepts_run_manager(transformer):
kwargs["run_manager"] = run_manager kwargs["run_manager"] = run_manager
iterator = transformer( iterator = transformer(input_for_transform, **kwargs) # type: ignore[call-arg]
input_for_transform, **kwargs
) # type: ignore[call-arg]
async for chunk in iterator: async for chunk in iterator:
yield chunk yield chunk
if final_output_supported: if final_output_supported:

3
libs/langchain/langchain/schema/runnable/branch.py
View File

@ -86,7 +86,8 @@ class RunnableBranch(RunnableSerializable[Input, Output]):
default = branches[-1] default = branches[-1]
if not isinstance( if not isinstance(
default, (Runnable, Callable, Mapping) # type: ignore[arg-type] default,
(Runnable, Callable, Mapping), # type: ignore[arg-type]
): ):
raise TypeError( raise TypeError(
"RunnableBranch default must be runnable, callable or mapping." "RunnableBranch default must be runnable, callable or mapping."

12
libs/langchain/langchain/schema/runnable/retry.py
View File

@ -89,7 +89,7 @@ class RunnableRetry(RunnableBinding[Input, Output]):
input: Input, input: Input,
run_manager: "CallbackManagerForChainRun", run_manager: "CallbackManagerForChainRun",
config: RunnableConfig, config: RunnableConfig,
**kwargs: Any **kwargs: Any,
) -> Output: ) -> Output:
for attempt in self._sync_retrying(reraise=True): for attempt in self._sync_retrying(reraise=True):
with attempt: with attempt:
@ -112,7 +112,7 @@ class RunnableRetry(RunnableBinding[Input, Output]):
input: Input, input: Input,
run_manager: "AsyncCallbackManagerForChainRun", run_manager: "AsyncCallbackManagerForChainRun",
config: RunnableConfig, config: RunnableConfig,
**kwargs: Any **kwargs: Any,
) -> Output: ) -> Output:
async for attempt in self._async_retrying(reraise=True): async for attempt in self._async_retrying(reraise=True):
with attempt: with attempt:
@ -135,7 +135,7 @@ class RunnableRetry(RunnableBinding[Input, Output]):
inputs: List[Input], inputs: List[Input],
run_manager: List["CallbackManagerForChainRun"], run_manager: List["CallbackManagerForChainRun"],
config: List[RunnableConfig], config: List[RunnableConfig],
**kwargs: Any **kwargs: Any,
) -> List[Union[Output, Exception]]: ) -> List[Union[Output, Exception]]:
results_map: Dict[int, Output] = {} results_map: Dict[int, Output] = {}
@ -190,7 +190,7 @@ class RunnableRetry(RunnableBinding[Input, Output]):
config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None,
*, *,
return_exceptions: bool = False, return_exceptions: bool = False,
**kwargs: Any **kwargs: Any,
) -> List[Output]: ) -> List[Output]:
return self._batch_with_config( return self._batch_with_config(
self._batch, inputs, config, return_exceptions=return_exceptions, **kwargs self._batch, inputs, config, return_exceptions=return_exceptions, **kwargs
@ -201,7 +201,7 @@ class RunnableRetry(RunnableBinding[Input, Output]):
inputs: List[Input], inputs: List[Input],
run_manager: List["AsyncCallbackManagerForChainRun"], run_manager: List["AsyncCallbackManagerForChainRun"],
config: List[RunnableConfig], config: List[RunnableConfig],
**kwargs: Any **kwargs: Any,
) -> List[Union[Output, Exception]]: ) -> List[Union[Output, Exception]]:
results_map: Dict[int, Output] = {} results_map: Dict[int, Output] = {}
@ -256,7 +256,7 @@ class RunnableRetry(RunnableBinding[Input, Output]):
config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None,
*, *,
return_exceptions: bool = False, return_exceptions: bool = False,
**kwargs: Any **kwargs: Any,
) -> List[Output]: ) -> List[Output]:
return await self._abatch_with_config( return await self._abatch_with_config(
self._abatch, inputs, config, return_exceptions=return_exceptions, **kwargs self._abatch, inputs, config, return_exceptions=return_exceptions, **kwargs

2
libs/langchain/langchain/smith/evaluation/config.py
View File

@ -322,7 +322,7 @@ class RunEvalConfig(BaseModel):
self, self,
criteria: Optional[CRITERIA_TYPE] = None, criteria: Optional[CRITERIA_TYPE] = None,
normalize_by: Optional[float] = None, normalize_by: Optional[float] = None,
**kwargs: Any **kwargs: Any,
) -> None: ) -> None:
super().__init__(criteria=criteria, normalize_by=normalize_by, **kwargs) super().__init__(criteria=criteria, normalize_by=normalize_by, **kwargs)

3
libs/langchain/langchain/text_splitter.py
View File

@ -412,8 +412,7 @@ class MarkdownHeaderTextSplitter:
if stripped_line.startswith(sep) and ( if stripped_line.startswith(sep) and (
# Header with no text OR header is followed by space # Header with no text OR header is followed by space
# Both are valid conditions that sep is being used a header # Both are valid conditions that sep is being used a header
len(stripped_line) == len(sep) len(stripped_line) == len(sep) or stripped_line[len(sep)] == " "
or stripped_line[len(sep)] == " "
): ):
# Ensure we are tracking the header as metadata # Ensure we are tracking the header as metadata
if name is not None: if name is not None:

2
libs/langchain/langchain/tools/e2b_data_analysis/unparse.py
View File

@ -683,7 +683,7 @@ class Unparser:
first = False first = False
else: else:
self.write(", ") self.write(", ")
self.dispatch(a), (self.dispatch(a),)
if d: if d:
self.write("=") self.write("=")
self.dispatch(d) self.dispatch(d)

4
libs/langchain/langchain/utilities/bing_search.py
View File

@ -36,7 +36,9 @@ class BingSearchAPIWrapper(BaseModel):
"textFormat": "HTML", "textFormat": "HTML",
} }
response = requests.get( response = requests.get(
self.bing_search_url, headers=headers, params=params # type: ignore self.bing_search_url,
headers=headers,
params=params, # type: ignore
) )
response.raise_for_status() response.raise_for_status()
search_results = response.json() search_results = response.json()

2
libs/langchain/langchain/utils/openai_functions.py
View File

@ -19,7 +19,7 @@ def convert_pydantic_to_openai_function(
model: Type[BaseModel], model: Type[BaseModel],
*, *,
name: Optional[str] = None, name: Optional[str] = None,
description: Optional[str] = None description: Optional[str] = None,
) -> FunctionDescription: ) -> FunctionDescription:
"""Converts a Pydantic model to a function description for the OpenAI API.""" """Converts a Pydantic model to a function description for the OpenAI API."""
schema = dereference_refs(model.schema()) schema = dereference_refs(model.schema())

15
libs/langchain/langchain/vectorstores/azuresearch.py
View File

@ -116,12 +116,15 @@ def _get_search_client(
- set(fields_types.items()) - set(fields_types.items())
} }
if len(missing_fields) > 0: if len(missing_fields) > 0:
fmt_err = lambda x: ( # noqa: E731 # Helper for formatting field information for each missing field.
f"{x} current type: '{fields_types.get(x, 'MISSING')}'. It has to " def fmt_err(x: str) -> str:
f"be '{mandatory_fields.get(x)}' or you can point to a different " return (
f"'{mandatory_fields.get(x)}' field name by using the env variable " f"{x} current type: '{fields_types.get(x, 'MISSING')}'. "
f"'AZURESEARCH_FIELDS_{x.upper()}'" f"It has to be '{mandatory_fields.get(x)}' or you can point "
) f"to a different '{mandatory_fields.get(x)}' field name by "
f"using the env variable 'AZURESEARCH_FIELDS_{x.upper()}'"
)
error = "\n".join([fmt_err(x) for x in missing_fields]) error = "\n".join([fmt_err(x) for x in missing_fields])
raise ValueError( raise ValueError(
f"You need to specify at least the following fields " f"You need to specify at least the following fields "

8
libs/langchain/langchain/vectorstores/qdrant.py
View File

@ -1592,9 +1592,7 @@ class Qdrant(VectorStore):
f"If you want to recreate the collection, set `force_recreate` " f"If you want to recreate the collection, set `force_recreate` "
f"parameter to `True`." f"parameter to `True`."
) )
current_vector_config = current_vector_config.get( current_vector_config = current_vector_config.get(vector_name) # type: ignore[assignment]
vector_name
) # type: ignore[assignment]
elif isinstance(current_vector_config, dict) and vector_name is None: elif isinstance(current_vector_config, dict) and vector_name is None:
raise QdrantException( raise QdrantException(
f"Existing Qdrant collection {collection_name} uses named vectors. " f"Existing Qdrant collection {collection_name} uses named vectors. "
@ -1758,9 +1756,7 @@ class Qdrant(VectorStore):
f"If you want to recreate the collection, set `force_recreate` " f"If you want to recreate the collection, set `force_recreate` "
f"parameter to `True`." f"parameter to `True`."
) )
current_vector_config = current_vector_config.get( current_vector_config = current_vector_config.get(vector_name) # type: ignore[assignment]
vector_name
) # type: ignore[assignment]
elif isinstance(current_vector_config, dict) and vector_name is None: elif isinstance(current_vector_config, dict) and vector_name is None:
raise QdrantException( raise QdrantException(
f"Existing Qdrant collection {collection_name} uses named vectors. " f"Existing Qdrant collection {collection_name} uses named vectors. "

20
libs/langchain/langchain/vectorstores/rocksetdb.py
View File

@ -268,20 +268,16 @@ class Rockset(VectorStore):
) )
for k, v in document.items(): for k, v in document.items():
if k == self._text_key: if k == self._text_key:
assert isinstance( assert isinstance(v, str), (
v, str "page content stored in column `{}` must be of type `str`. "
), "page content stored in column `{}` must be of type `str`. \ "But found: `{}`"
But found: `{}`".format( ).format(self._text_key, type(v))
self._text_key, type(v)
)
page_content = v page_content = v
elif k == "dist": elif k == "dist":
assert isinstance( assert isinstance(v, float), (
v, float "Computed distance between vectors must of type `float`. "
), "Computed distance between vectors must of type `float`. \ "But found {}"
But found {}".format( ).format(type(v))
type(v)
)
score = v score = v
elif k not in ["_id", "_event_time", "_meta"]: elif k not in ["_id", "_event_time", "_meta"]:
# These columns are populated by Rockset when documents are # These columns are populated by Rockset when documents are

2
libs/langchain/langchain/vectorstores/utils.py
View File

@ -57,7 +57,7 @@ def maximal_marginal_relevance(
def filter_complex_metadata( def filter_complex_metadata(
documents: List[Document], documents: List[Document],
*, *,
allowed_types: Tuple[Type, ...] = (str, bool, int, float) allowed_types: Tuple[Type, ...] = (str, bool, int, float),
) -> List[Document]: ) -> List[Document]:
"""Filter out metadata types that are not supported for a vector store.""" """Filter out metadata types that are not supported for a vector store."""
updated_documents = [] updated_documents = []

79
libs/langchain/poetry.lock generated
View File

@ -895,48 +895,6 @@ files = [
[package.dependencies] [package.dependencies]
pyparsing = ">=2.0.3" pyparsing = ">=2.0.3"
[[package]]
name = "black"
version = "23.10.1"
description = "The uncompromising code formatter."
optional = false
python-versions = ">=3.8"
files = [
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[package.dependencies]
click = ">=8.0.0"
mypy-extensions = ">=0.4.3"
packaging = ">=22.0"
pathspec = ">=0.9.0"
platformdirs = ">=2"
tomli = {version = ">=1.1.0", markers = "python_version < \"3.11\""}
typing-extensions = {version = ">=4.0.1", markers = "python_version < \"3.11\""}
[package.extras]
colorama = ["colorama (>=0.4.3)"]
d = ["aiohttp (>=3.7.4)"]
jupyter = ["ipython (>=7.8.0)", "tokenize-rt (>=3.2.0)"]
uvloop = ["uvloop (>=0.15.2)"]
[[package]] [[package]]
name = "bleach" name = "bleach"
version = "6.1.0" version = "6.1.0"
@ -2934,7 +2892,7 @@ files = [
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{file = "PyYAML-6.0.1.tar.gz", hash = "sha256:bfdf460b1736c775f2ba9f6a92bca30bc2095067b8a9d77876d1fad6cc3b4a43"}, {file = "PyYAML-6.0.1.tar.gz", hash = "sha256:bfdf460b1736c775f2ba9f6a92bca30bc2095067b8a9d77876d1fad6cc3b4a43"},
@ -11080,4 +11007,4 @@ text-helpers = ["chardet"]
[metadata] [metadata]
lock-version = "2.0" lock-version = "2.0"
python-versions = ">=3.8.1,<4.0" python-versions = ">=3.8.1,<4.0"
content-hash = "d9f38367a43153fda9eaea5e8fd03acfc0a06006dfecc3693dffb212249197bc" content-hash = "1c796fb6c531ed9803594973b7296fba64a22605f602f9646677bc07c5a39a85"

3
libs/langchain/pyproject.toml
View File

@ -193,11 +193,10 @@ tiktoken = "^0.3.2"
anthropic = "^0.3.11" anthropic = "^0.3.11"
[tool.poetry.group.lint.dependencies] [tool.poetry.group.lint.dependencies]
ruff = "^0.1" ruff = "^0.1.3"
types-toml = "^0.10.8.1" types-toml = "^0.10.8.1"
types-redis = "^4.3.21.6" types-redis = "^4.3.21.6"
types-pytz = "^2023.3.0.0" types-pytz = "^2023.3.0.0"
black = "^23.10.0"
types-chardet = "^5.0.4.6" types-chardet = "^5.0.4.6"
mypy-protobuf = "^3.0.0" mypy-protobuf = "^3.0.0"

2
libs/langchain/tests/integration_tests/chat_models/test_vertexai.py
View File

@ -186,7 +186,7 @@ def test_vertexai_args_passed(stop: Optional[str]) -> None:
context=None, context=None,
message_history=[], message_history=[],
**prompt_params, **prompt_params,
stop_sequences=expected_stop_sequence stop_sequences=expected_stop_sequence,
) )

8
libs/langchain/tests/integration_tests/retrievers/test_zep.py
View File

@ -101,14 +101,10 @@ def _test_documents(
assert document.page_content == search_results[i].message.get( # type: ignore assert document.page_content == search_results[i].message.get( # type: ignore
"content" "content"
) )
assert document.metadata.get("uuid") == search_results[ assert document.metadata.get("uuid") == search_results[i].message.get( # type: ignore
i
].message.get( # type: ignore
"uuid" "uuid"
) )
assert document.metadata.get("role") == search_results[ assert document.metadata.get("role") == search_results[i].message.get( # type: ignore
i
].message.get( # type: ignore
"role" "role"
) )
assert document.metadata.get("score") == search_results[i].dist assert document.metadata.get("score") == search_results[i].dist

5
libs/langchain/tests/integration_tests/vectorstores/test_elasticsearch.py
View File

@ -436,7 +436,10 @@ class TestElasticsearch:
assert mmr_output[1].page_content == texts[1] assert mmr_output[1].page_content == texts[1]
mmr_output = docsearch.max_marginal_relevance_search( mmr_output = docsearch.max_marginal_relevance_search(
texts[0], k=2, fetch_k=3, lambda_mult=0.1 # more diversity texts[0],
k=2,
fetch_k=3,
lambda_mult=0.1, # more diversity
) )
assert len(mmr_output) == 2 assert len(mmr_output) == 2
assert mmr_output[0].page_content == texts[0] assert mmr_output[0].page_content == texts[0]

5
libs/langchain/tests/integration_tests/vectorstores/test_redis.py
View File

@ -368,7 +368,10 @@ def test_max_marginal_relevance_search(texts: List[str]) -> None:
assert mmr_output[1].page_content == texts[1] assert mmr_output[1].page_content == texts[1]
mmr_output = docsearch.max_marginal_relevance_search( mmr_output = docsearch.max_marginal_relevance_search(
texts[0], k=2, fetch_k=3, lambda_mult=0.1 # more diversity texts[0],
k=2,
fetch_k=3,
lambda_mult=0.1, # more diversity
) )
assert len(mmr_output) == 2 assert len(mmr_output) == 2
assert mmr_output[0].page_content == texts[0] assert mmr_output[0].page_content == texts[0]

5
libs/langchain/tests/integration_tests/vectorstores/test_vearch.py
View File

@ -57,7 +57,10 @@ def test_vearch() -> None:
def test_vearch_add_texts() -> None: def test_vearch_add_texts() -> None:
"""Test end to end adding of texts.""" """Test end to end adding of texts."""
texts = [ texts = [
("Vearch 是一款存储大语言模型数据的向量数据库，用于存储和快速搜索模型embedding后的向量，" "可用于基于个人知识库的大模型应用"), (
"Vearch 是一款存储大语言模型数据的向量数据库，用于存储和快速搜索模型embedding后的向量，"
"可用于基于个人知识库的大模型应用"
),
"Vearch 支持OpenAI, Llama, ChatGLM等模型，以及LangChain库", "Vearch 支持OpenAI, Llama, ChatGLM等模型，以及LangChain库",
"vearch 是基于C语言,go语言开发的，并提供python接口，可以直接通过pip安装", "vearch 是基于C语言,go语言开发的，并提供python接口，可以直接通过pip安装",
] ]

2
libs/langchain/tests/integration_tests/vectorstores/test_zep.py
View File

@ -168,7 +168,7 @@ def test_from_texts(
vs = zep_vectorstore.from_texts( vs = zep_vectorstore.from_texts(
**texts_metadatas, **texts_metadatas,
collection_name=mock_collection_config.name, collection_name=mock_collection_config.name,
api_url="http://localhost:8000" api_url="http://localhost:8000",
) )
vs._collection.add_documents.assert_called_once_with( # type: ignore vs._collection.add_documents.assert_called_once_with( # type: ignore

4
libs/langchain/tests/unit_tests/agents/test_initialize.py
View File

@ -16,7 +16,9 @@ def test_initialize_agent_with_str_agent_type() -> None:
"""Test initialize_agent with a string.""" """Test initialize_agent with a string."""
fake_llm = FakeLLM() fake_llm = FakeLLM()
agent_executor = initialize_agent( agent_executor = initialize_agent(
[my_tool], fake_llm, "zero-shot-react-description" # type: ignore [my_tool], # type: ignore[list-item]
fake_llm,
"zero-shot-react-description", # type: ignore[arg-type]
) )
assert agent_executor.agent._agent_type == AgentType.ZERO_SHOT_REACT_DESCRIPTION assert agent_executor.agent._agent_type == AgentType.ZERO_SHOT_REACT_DESCRIPTION
assert isinstance(agent_executor.tags, list) assert isinstance(agent_executor.tags, list)

4
libs/langchain/tests/unit_tests/document_loaders/test_detect_encoding.py
View File

@ -47,7 +47,9 @@ def test_loader_detect_encoding_csv() -> None:
row_count -= 1 row_count -= 1
loader = DirectoryLoader( loader = DirectoryLoader(
str(path), glob="**/*.csv", loader_cls=CSVLoader # type: ignore str(path),
glob="**/*.csv",
loader_cls=CSVLoader, # type: ignore
) )
loader_detect_encoding = DirectoryLoader( loader_detect_encoding = DirectoryLoader(
str(path), str(path),

6
libs/langchain/tests/unit_tests/prompts/test_chat.py
View File

@ -168,9 +168,9 @@ def test_chat_prompt_template_from_messages_using_role_strings() -> None:
def test_chat_prompt_template_with_messages() -> None: def test_chat_prompt_template_with_messages() -> None:
messages: List[ messages: List[Union[BaseMessagePromptTemplate, BaseMessage]] = (
Union[BaseMessagePromptTemplate, BaseMessage] create_messages() + [HumanMessage(content="foo")]
] = create_messages() + [HumanMessage(content="foo")] )
chat_prompt_template = ChatPromptTemplate.from_messages(messages) chat_prompt_template = ChatPromptTemplate.from_messages(messages)
assert sorted(chat_prompt_template.input_variables) == sorted( assert sorted(chat_prompt_template.input_variables) == sorted(
["context", "foo", "bar"] ["context", "foo", "bar"]

42
libs/langchain/tests/unit_tests/schema/runnable/test_runnable.py
View File

@ -617,21 +617,27 @@ def test_lambda_schemas() -> None:
"byebye": input["yo"], "byebye": input["yo"],
} }
assert RunnableLambda(aget_values_typed).input_schema.schema() == { # type: ignore[arg-type] assert (
"title": "RunnableLambdaInput", RunnableLambda(aget_values_typed).input_schema.schema() # type: ignore[arg-type]
"$ref": "#/definitions/InputType", == {
"definitions": { "title": "RunnableLambdaInput",
"InputType": { "$ref": "#/definitions/InputType",
"properties": { "definitions": {
"variable_name": {"title": "Variable " "Name", "type": "string"}, "InputType": {
"yo": {"title": "Yo", "type": "integer"}, "properties": {
}, "variable_name": {
"required": ["variable_name", "yo"], "title": "Variable " "Name",
"title": "InputType", "type": "string",
"type": "object", },
} "yo": {"title": "Yo", "type": "integer"},
}, },
} "required": ["variable_name", "yo"],
"title": "InputType",
"type": "object",
}
},
}
)
assert RunnableLambda(aget_values_typed).output_schema.schema() == { # type: ignore[arg-type] assert RunnableLambda(aget_values_typed).output_schema.schema() == { # type: ignore[arg-type]
"title": "RunnableLambdaOutput", "title": "RunnableLambdaOutput",
@ -660,10 +666,12 @@ def test_with_types_with_type_generics() -> None:
# Try specifying some # Try specifying some
RunnableLambda(foo).with_types( RunnableLambda(foo).with_types(
output_type=List[int], input_type=List[int] # type: ignore output_type=List[int], # type: ignore[arg-type]
input_type=List[int], # type: ignore[arg-type]
) )
RunnableLambda(foo).with_types( RunnableLambda(foo).with_types(
output_type=Sequence[int], input_type=Sequence[int] # type: ignore[arg-type] output_type=Sequence[int], # type: ignore[arg-type]
input_type=Sequence[int], # type: ignore[arg-type]
) )

60
libs/langchain/tests/unit_tests/schema/test_messages.py
View File

@ -15,33 +15,39 @@ def test_message_chunks() -> None:
content="I am indeed." content="I am indeed."
), "MessageChunk + MessageChunk should be a MessageChunk" ), "MessageChunk + MessageChunk should be a MessageChunk"
assert AIMessageChunk(content="I am") + HumanMessageChunk( assert (
content=" indeed." AIMessageChunk(content="I am") + HumanMessageChunk(content=" indeed.")
) == AIMessageChunk( == AIMessageChunk(content="I am indeed.")
content="I am indeed."
), "MessageChunk + MessageChunk should be a MessageChunk of same class as the left side" # noqa: E501 ), "MessageChunk + MessageChunk should be a MessageChunk of same class as the left side" # noqa: E501
assert AIMessageChunk( assert (
content="", additional_kwargs={"foo": "bar"} AIMessageChunk(content="", additional_kwargs={"foo": "bar"})
) + AIMessageChunk(content="", additional_kwargs={"baz": "foo"}) == AIMessageChunk( + AIMessageChunk(content="", additional_kwargs={"baz": "foo"})
content="", additional_kwargs={"foo": "bar", "baz": "foo"} == AIMessageChunk(content="", additional_kwargs={"foo": "bar", "baz": "foo"})
), "MessageChunk + MessageChunk should be a MessageChunk with merged additional_kwargs" # noqa: E501 ), "MessageChunk + MessageChunk should be a MessageChunk with merged additional_kwargs" # noqa: E501
assert AIMessageChunk( assert (
content="", additional_kwargs={"function_call": {"name": "web_search"}} AIMessageChunk(
) + AIMessageChunk( content="", additional_kwargs={"function_call": {"name": "web_search"}}
content="", additional_kwargs={"function_call": {"arguments": "{\n"}} )
) + AIMessageChunk( + AIMessageChunk(
content="", content="", additional_kwargs={"function_call": {"arguments": "{\n"}}
additional_kwargs={"function_call": {"arguments": ' "query": "turtles"\n}'}}, )
) == AIMessageChunk( + AIMessageChunk(
content="", content="",
additional_kwargs={ additional_kwargs={
"function_call": { "function_call": {"arguments": ' "query": "turtles"\n}'}
"name": "web_search", },
"arguments": '{\n "query": "turtles"\n}', )
} == AIMessageChunk(
}, content="",
additional_kwargs={
"function_call": {
"name": "web_search",
"arguments": '{\n "query": "turtles"\n}',
}
},
)
), "MessageChunk + MessageChunk should be a MessageChunk with merged additional_kwargs" # noqa: E501 ), "MessageChunk + MessageChunk should be a MessageChunk with merged additional_kwargs" # noqa: E501
@ -57,10 +63,10 @@ def test_chat_message_chunks() -> None:
role="Assistant", content=" indeed." role="Assistant", content=" indeed."
) )
assert ChatMessageChunk(role="User", content="I am") + AIMessageChunk( assert (
content=" indeed." ChatMessageChunk(role="User", content="I am")
) == ChatMessageChunk( + AIMessageChunk(content=" indeed.")
role="User", content="I am indeed." == ChatMessageChunk(role="User", content="I am indeed.")
), "ChatMessageChunk + other MessageChunk should be a ChatMessageChunk with the left side's role" # noqa: E501 ), "ChatMessageChunk + other MessageChunk should be a ChatMessageChunk with the left side's role" # noqa: E501
assert AIMessageChunk(content="I am") + ChatMessageChunk( assert AIMessageChunk(content="I am") + ChatMessageChunk(

56
libs/langchain/tests/unit_tests/schema/test_output.py
View File

@ -9,16 +9,19 @@ def test_generation_chunk() -> None:
text="Hello, world!" text="Hello, world!"
), "GenerationChunk + GenerationChunk should be a GenerationChunk" ), "GenerationChunk + GenerationChunk should be a GenerationChunk"
assert GenerationChunk(text="Hello, ") + GenerationChunk( assert (
text="world!", generation_info={"foo": "bar"} GenerationChunk(text="Hello, ")
) == GenerationChunk( + GenerationChunk(text="world!", generation_info={"foo": "bar"})
text="Hello, world!", generation_info={"foo": "bar"} == GenerationChunk(text="Hello, world!", generation_info={"foo": "bar"})
), "GenerationChunk + GenerationChunk should be a GenerationChunk with merged generation_info" # noqa: E501 ), "GenerationChunk + GenerationChunk should be a GenerationChunk with merged generation_info" # noqa: E501
assert GenerationChunk(text="Hello, ") + GenerationChunk( assert (
text="world!", generation_info={"foo": "bar"} GenerationChunk(text="Hello, ")
) + GenerationChunk(text="!", generation_info={"baz": "foo"}) == GenerationChunk( + GenerationChunk(text="world!", generation_info={"foo": "bar"})
text="Hello, world!!", generation_info={"foo": "bar", "baz": "foo"} + GenerationChunk(text="!", generation_info={"baz": "foo"})
== GenerationChunk(
text="Hello, world!!", generation_info={"foo": "bar", "baz": "foo"}
)
), "GenerationChunk + GenerationChunk should be a GenerationChunk with merged generation_info" # noqa: E501 ), "GenerationChunk + GenerationChunk should be a GenerationChunk with merged generation_info" # noqa: E501
@ -31,22 +34,27 @@ def test_chat_generation_chunk() -> None:
message=HumanMessageChunk(content="Hello, world!") message=HumanMessageChunk(content="Hello, world!")
), "ChatGenerationChunk + ChatGenerationChunk should be a ChatGenerationChunk" ), "ChatGenerationChunk + ChatGenerationChunk should be a ChatGenerationChunk"
assert ChatGenerationChunk( assert (
message=HumanMessageChunk(content="Hello, ") ChatGenerationChunk(message=HumanMessageChunk(content="Hello, "))
) + ChatGenerationChunk( + ChatGenerationChunk(
message=HumanMessageChunk(content="world!"), generation_info={"foo": "bar"} message=HumanMessageChunk(content="world!"), generation_info={"foo": "bar"}
) == ChatGenerationChunk( )
message=HumanMessageChunk(content="Hello, world!"), == ChatGenerationChunk(
generation_info={"foo": "bar"}, message=HumanMessageChunk(content="Hello, world!"),
generation_info={"foo": "bar"},
)
), "GenerationChunk + GenerationChunk should be a GenerationChunk with merged generation_info" # noqa: E501 ), "GenerationChunk + GenerationChunk should be a GenerationChunk with merged generation_info" # noqa: E501
assert ChatGenerationChunk( assert (
message=HumanMessageChunk(content="Hello, ") ChatGenerationChunk(message=HumanMessageChunk(content="Hello, "))
) + ChatGenerationChunk( + ChatGenerationChunk(
message=HumanMessageChunk(content="world!"), generation_info={"foo": "bar"} message=HumanMessageChunk(content="world!"), generation_info={"foo": "bar"}
) + ChatGenerationChunk( )
message=HumanMessageChunk(content="!"), generation_info={"baz": "foo"} + ChatGenerationChunk(
) == ChatGenerationChunk( message=HumanMessageChunk(content="!"), generation_info={"baz": "foo"}
message=HumanMessageChunk(content="Hello, world!!"), )
generation_info={"foo": "bar", "baz": "foo"}, == ChatGenerationChunk(
message=HumanMessageChunk(content="Hello, world!!"),
generation_info={"foo": "bar", "baz": "foo"},
)
), "GenerationChunk + GenerationChunk should be a GenerationChunk with merged generation_info" # noqa: E501 ), "GenerationChunk + GenerationChunk should be a GenerationChunk with merged generation_info" # noqa: E501

4
libs/langchain/tests/unit_tests/smith/evaluation/test_runner_utils.py
View File

@ -318,9 +318,7 @@ async def test_arun_on_dataset(monkeypatch: pytest.MonkeyPatch) -> None:
), mock.patch.object(Client, "list_examples", new=mock_list_examples), mock.patch( ), mock.patch.object(Client, "list_examples", new=mock_list_examples), mock.patch(
"langchain.smith.evaluation.runner_utils._arun_llm_or_chain", "langchain.smith.evaluation.runner_utils._arun_llm_or_chain",
new=mock_arun_chain, new=mock_arun_chain,
), mock.patch.object( ), mock.patch.object(Client, "create_project", new=mock_create_project):
Client, "create_project", new=mock_create_project
):
client = Client(api_url="http://localhost:1984", api_key="123") client = Client(api_url="http://localhost:1984", api_key="123")
chain = mock.MagicMock() chain = mock.MagicMock()
chain.input_keys = ["foothing"] chain.input_keys = ["foothing"]

30
poetry.lock generated
View File

@ -987,7 +987,7 @@ files = [
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{file = "greenlet-3.0.0-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:527cd90ba3d8d7ae7dceb06fda619895768a46a1b4e423bdb24c1969823b8362"}, {file = "greenlet-3.0.0-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:527cd90ba3d8d7ae7dceb06fda619895768a46a1b4e423bdb24c1969823b8362"},
{file = "greenlet-3.0.0-cp311-cp311-win_amd64.whl", hash = "sha256:37f60b3a42d8b5499be910d1267b24355c495064f271cfe74bf28b17b099133c"}, {file = "greenlet-3.0.0-cp311-cp311-win_amd64.whl", hash = "sha256:37f60b3a42d8b5499be910d1267b24355c495064f271cfe74bf28b17b099133c"},
{file = "greenlet-3.0.0-cp312-cp312-macosx_10_9_universal2.whl", hash = "sha256:1482fba7fbed96ea7842b5a7fc11d61727e8be75a077e603e8ab49d24e234383"}, {file = "greenlet-3.0.0-cp311-universal2-macosx_10_9_universal2.whl", hash = "sha256:c3692ecf3fe754c8c0f2c95ff19626584459eab110eaab66413b1e7425cd84e9"},
{file = "greenlet-3.0.0-cp312-cp312-macosx_13_0_arm64.whl", hash = "sha256:be557119bf467d37a8099d91fbf11b2de5eb1fd5fc5b91598407574848dc910f"}, {file = "greenlet-3.0.0-cp312-cp312-macosx_13_0_arm64.whl", hash = "sha256:be557119bf467d37a8099d91fbf11b2de5eb1fd5fc5b91598407574848dc910f"},
{file = "greenlet-3.0.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:73b2f1922a39d5d59cc0e597987300df3396b148a9bd10b76a058a2f2772fc04"}, {file = "greenlet-3.0.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:73b2f1922a39d5d59cc0e597987300df3396b148a9bd10b76a058a2f2772fc04"},
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@ -997,6 +997,7 @@ files = [
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[metadata] [metadata]
lock-version = "2.0" lock-version = "2.0"
python-versions = ">=3.8.1,<4.0" python-versions = ">=3.8.1,<4.0"
content-hash = "47b6bed43d64a2d4690d4554c78481485822b4b226a6e7f8a456dddb4ce8dd20" content-hash = "e5c7a1f126afec578c3cd010d3d2131b96f5283a3402af5bb5084408cc7f7444"

4
pyproject.toml
View File

@ -29,9 +29,7 @@ sphinx-copybutton = "^0.5.1"
nbdoc = "^0.0.82" nbdoc = "^0.0.82"
[tool.poetry.group.lint.dependencies] [tool.poetry.group.lint.dependencies]
ruff = "^0.1" ruff = "^0.1.3"
black = "^23.10.0"
[tool.poetry.group.codespell.dependencies] [tool.poetry.group.codespell.dependencies]
codespell = "^2.2.0" codespell = "^2.2.0"