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

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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.
pull/12594/head^2
Predrag Gruevski 7 months ago 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
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@ -134,7 +134,7 @@ Run these locally before submitting a PR; the CI system will check also.
#### 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:
@ -159,7 +159,7 @@ This is especially useful when you have made changes to a subset of the project
#### 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:
@ -302,8 +302,8 @@ make api_docs_linkcheck
### Verify Documentation changes
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.
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.
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).

4
Makefile
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@ -43,10 +43,10 @@ spell_fix:
lint:
poetry run ruff docs templates cookbook
poetry run black docs templates cookbook --check
poetry run ruff format docs templates cookbook --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
######################

6
libs/experimental/Makefile
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@ -9,7 +9,7 @@ TEST_FILE ?= tests/unit_tests/
test:
poetry run pytest $(TEST_FILE)
tests:
tests:
poetry run pytest $(TEST_FILE)
test_watch:
@ -33,11 +33,11 @@ lint_diff format_diff: PYTHON_FILES=$(shell git diff --relative=libs/experimenta
lint lint_diff:
poetry run mypy $(PYTHON_FILES)
poetry run black $(PYTHON_FILES) --check
poetry run ruff format $(PYTHON_FILES) --diff
poetry run ruff .
format format_diff:
poetry run black $(PYTHON_FILES)
poetry run ruff format $(PYTHON_FILES)
poetry run ruff --select I --fix $(PYTHON_FILES)
spell_check:

2
libs/experimental/langchain_experimental/tabular_synthetic_data/openai.py
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@ -16,7 +16,7 @@ def create_openai_data_generator(
llm: ChatOpenAI,
prompt: BasePromptTemplate,
output_parser: Optional[BaseLLMOutputParser] = None,
**kwargs: Any
**kwargs: Any,
) -> SyntheticDataGenerator:
"""
Create an instance of SyntheticDataGenerator tailored for OpenAI models.

8
libs/experimental/langchain_experimental/tot/thought_generation.py
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@ -29,7 +29,7 @@ class BaseThoughtGenerationStrategy(LLMChain):
self,
problem_description: str,
thoughts_path: Tuple[str, ...] = (),
**kwargs: Any
**kwargs: Any,
) -> str:
"""
Generate the next thought given the problem description and the thoughts
@ -52,7 +52,7 @@ class SampleCoTStrategy(BaseThoughtGenerationStrategy):
self,
problem_description: str,
thoughts_path: Tuple[str, ...] = (),
**kwargs: Any
**kwargs: Any,
) -> str:
response_text = self.predict_and_parse(
problem_description=problem_description, thoughts=thoughts_path, **kwargs
@ -76,14 +76,14 @@ class ProposePromptStrategy(BaseThoughtGenerationStrategy):
self,
problem_description: str,
thoughts_path: Tuple[str, ...] = (),
**kwargs: Any
**kwargs: Any,
) -> str:
if thoughts_path not in self.tot_memory or not self.tot_memory[thoughts_path]:
new_thoughts = self.predict_and_parse(
problem_description=problem_description,
thoughts=thoughts_path,
n=self.c,
**kwargs
**kwargs,
)
if not new_thoughts:
return ""

122
libs/experimental/poetry.lock generated
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@ -350,48 +350,6 @@ soupsieve = ">1.2"
html5lib = ["html5lib"]
lxml = ["lxml"]
[[package]]
name = "black"
version = "23.10.0"
description = "The uncompromising code formatter."
optional = false
python-versions = ">=3.8"
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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]]
name = "bleach"
version = "6.1.0"
@ -648,7 +606,7 @@ files = [
name = "click"
version = "8.1.7"
description = "Composable command line interface toolkit"
optional = false
optional = true
python-versions = ">=3.7"
files = [
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@ -1044,7 +1002,7 @@ files = [
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@ -2344,17 +2292,6 @@ files = [
qa = ["flake8 (==3.8.3)", "mypy (==0.782)"]
testing = ["docopt", "pytest (<6.0.0)"]
[[package]]
name = "pathspec"
version = "0.11.2"
description = "Utility library for gitignore style pattern matching of file paths."
optional = false
python-versions = ">=3.7"
files = [
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]
[[package]]
name = "pexpect"
version = "4.8.0"
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@ -3448,28 +3375,28 @@ files = [
[[package]]
name = "ruff"
version = "0.1.0"
version = "0.1.3"
description = "An extremely fast Python linter, written in Rust."
optional = false
python-versions = ">=3.7"
files = [
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]
[[package]]
@ -3609,11 +3536,6 @@ files = [
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{file = "scikit_learn-1.3.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c6448c37741145b241eeac617028ba6ec2119e1339b1385c9720dae31367f2be"},
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@ -4957,4 +4879,4 @@ extended-testing = ["faker", "presidio-analyzer", "presidio-anonymizer", "senten
[metadata]
lock-version = "2.0"
python-versions = ">=3.8.1,<4.0"
content-hash = "f23fcff0e5ab8f172578b4f4da8dd204375357c7a5ad10c97bb77de7208bc889"
content-hash = "f038878d61e8970fa9062263822db5757face25be16a2de7fda24732df86c6f0"

3
libs/experimental/pyproject.toml
Unescape Escape View File

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

7
libs/experimental/tests/unit_tests/rl_chain/test_pick_best_chain_call.py
Unescape Escape 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
with pytest.raises(RuntimeError):
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
assert selection_metadata.selected.score == 3.0 # type: ignore
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

4
libs/langchain/Makefile
Unescape Escape View File

@ -50,11 +50,11 @@ lint lint_diff:
./scripts/check_pydantic.sh .
./scripts/check_imports.sh
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 $(PYTHON_FILES)
format format_diff:
[ "$(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)
spell_check:

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

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

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

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

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

@ -284,7 +284,8 @@ class ArgillaCallbackHandler(BaseCallbackHandler):
},
}
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
Unescape Escape 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.markdown_renderer().to_html("#### Text Complexity Metrics")
)

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

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

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

@ -371,7 +371,9 @@ class MlflowCallbackHandler(BaseMetadataCallbackHandler, BaseCallbackHandler):
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(
complexity_metrics,
step=self.metrics["step"],

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

@ -211,7 +211,9 @@ class BlackboardLoader(WebBaseLoader):
"""
# Create the document loader
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
documents = loader.load()

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

@ -36,7 +36,9 @@ class BingSearchAPIWrapper(BaseModel):
"textFormat": "HTML",
}
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()
search_results = response.json()

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

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

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

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

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

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

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

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

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

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

79
libs/langchain/poetry.lock generated
Unescape Escape View File

@ -895,48 +895,6 @@ files = [
[package.dependencies]
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]]
name = "bleach"
version = "6.1.0"
@ -2934,7 +2892,7 @@ files = [
{file = "greenlet-3.0.0-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:0b72b802496cccbd9b31acea72b6f87e7771ccfd7f7927437d592e5c92ed703c"},
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@ -2944,6 +2902,7 @@ files = [
{file = "greenlet-3.0.0-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:952256c2bc5b4ee8df8dfc54fc4de330970bf5d79253c863fb5e6761f00dda35"},
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@ -2976,7 +2935,6 @@ files = [
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]
[package.extras]
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@ -6083,17 +6031,6 @@ multiprocess = ">=0.70.15"
pox = ">=0.3.3"
ppft = ">=1.7.6.7"
[[package]]
name = "pathspec"
version = "0.11.2"
description = "Utility library for gitignore style pattern matching of file paths."
optional = false
python-versions = ">=3.7"
files = [
{file = "pathspec-0.11.2-py3-none-any.whl", hash = "sha256:1d6ed233af05e679efb96b1851550ea95bbb64b7c490b0f5aa52996c11e92a20"},
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]
[[package]]
name = "pdfminer-six"
version = "20221105"
@ -7711,7 +7648,6 @@ files = [
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@ -7719,15 +7655,8 @@ files = [
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{file = "PyYAML-6.0.1-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1fe35611261b29bd1de0070f0b2f47cb6ff71fa6595c077e42bd0c419fa27b98"},
{file = "PyYAML-6.0.1-cp36-cp36m-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:704219a11b772aea0d8ecd7058d0082713c3562b4e271b849ad7dc4a5c90c13c"},
@ -7744,7 +7673,6 @@ files = [
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@ -7752,7 +7680,6 @@ files = [
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{file = "PyYAML-6.0.1-cp39-cp39-win_amd64.whl", hash = "sha256:510c9deebc5c0225e8c96813043e62b680ba2f9c50a08d3724c7f28a747d1486"},
{file = "PyYAML-6.0.1.tar.gz", hash = "sha256:bfdf460b1736c775f2ba9f6a92bca30bc2095067b8a9d77876d1fad6cc3b4a43"},
@ -11080,4 +11007,4 @@ text-helpers = ["chardet"]
[metadata]
lock-version = "2.0"
python-versions = ">=3.8.1,<4.0"
content-hash = "d9f38367a43153fda9eaea5e8fd03acfc0a06006dfecc3693dffb212249197bc"
content-hash = "1c796fb6c531ed9803594973b7296fba64a22605f602f9646677bc07c5a39a85"

3
libs/langchain/pyproject.toml
Unescape Escape View File

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

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

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

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

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

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

@ -436,7 +436,10 @@ class TestElasticsearch:
assert mmr_output[1].page_content == texts[1]
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 mmr_output[0].page_content == texts[0]

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

@ -368,7 +368,10 @@ def test_max_marginal_relevance_search(texts: List[str]) -> None:
assert mmr_output[1].page_content == texts[1]
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 mmr_output[0].page_content == texts[0]

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

@ -57,7 +57,10 @@ def test_vearch() -> None:
def test_vearch_add_texts() -> None:
"""Test end to end adding of 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 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
Unescape Escape View File

@ -168,7 +168,7 @@ def test_from_texts(
vs = zep_vectorstore.from_texts(
**texts_metadatas,
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

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

@ -16,7 +16,9 @@ def test_initialize_agent_with_str_agent_type() -> None:
"""Test initialize_agent with a string."""
fake_llm = FakeLLM()
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 isinstance(agent_executor.tags, list)

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

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

6
libs/langchain/tests/unit_tests/prompts/test_chat.py
Unescape Escape 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:
messages: List[
Union[BaseMessagePromptTemplate, BaseMessage]
] = create_messages() + [HumanMessage(content="foo")]
messages: List[Union[BaseMessagePromptTemplate, BaseMessage]] = (
create_messages() + [HumanMessage(content="foo")]
)
chat_prompt_template = ChatPromptTemplate.from_messages(messages)
assert sorted(chat_prompt_template.input_variables) == sorted(
["context", "foo", "bar"]

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

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

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

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

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

4
libs/langchain/tests/unit_tests/smith/evaluation/test_runner_utils.py
Unescape Escape 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(
"langchain.smith.evaluation.runner_utils._arun_llm_or_chain",
new=mock_arun_chain,
), mock.patch.object(
Client, "create_project", new=mock_create_project
):
), mock.patch.object(Client, "create_project", new=mock_create_project):
client = Client(api_url="http://localhost:1984", api_key="123")
chain = mock.MagicMock()
chain.input_keys = ["foothing"]

30
poetry.lock generated
Unescape Escape 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-win_amd64.whl", hash = "sha256:37f60b3a42d8b5499be910d1267b24355c495064f271cfe74bf28b17b099133c"},
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{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_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d1e22c22f7826096ad503e9bb681b05b8c1f5a8138469b255eb91f26a76634f2"},
@ -997,6 +997,7 @@ files = [
{file = "greenlet-3.0.0-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:952256c2bc5b4ee8df8dfc54fc4de330970bf5d79253c863fb5e6761f00dda35"},
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{file = "greenlet-3.0.0-cp312-cp312-win_amd64.whl", hash = "sha256:9adbd8ecf097e34ada8efde9b6fec4dd2a903b1e98037adf72d12993a1c80b51"},
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{file = "greenlet-3.0.0-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:ecf94aa539e97a8411b5ea52fc6ccd8371be9550c4041011a091eb8b3ca1d810"},
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@ -1029,7 +1030,6 @@ files = [
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{file = "greenlet-3.0.0.tar.gz", hash = "sha256:19834e3f91f485442adc1ee440171ec5d9a4840a1f7bd5ed97833544719ce10b"},
]
[package.extras]
@ -1627,7 +1627,7 @@ files = [
[[package]]
name = "langchain"
version = "0.0.325"
version = "0.0.326"
description = "Building applications with LLMs through composability"
optional = false
python-versions = ">=3.8.1,<4.0"
@ -1649,7 +1649,7 @@ SQLAlchemy = ">=1.4,<3"
tenacity = "^8.1.0"
[package.extras]
all = ["O365 (>=2.0.26,<3.0.0)", "aleph-alpha-client (>=2.15.0,<3.0.0)", "amadeus (>=8.1.0)", "arxiv (>=1.4,<2.0)", "atlassian-python-api (>=3.36.0,<4.0.0)", "awadb (>=0.3.9,<0.4.0)", "azure-ai-formrecognizer (>=3.2.1,<4.0.0)", "azure-ai-vision (>=0.11.1b1,<0.12.0)", "azure-cognitiveservices-speech (>=1.28.0,<2.0.0)", "azure-cosmos (>=4.4.0b1,<5.0.0)", "azure-identity (>=1.12.0,<2.0.0)", "beautifulsoup4 (>=4,<5)", "clarifai (>=9.1.0)", "clickhouse-connect (>=0.5.14,<0.6.0)", "cohere (>=4,<5)", "deeplake (>=3.6.8,<4.0.0)", "docarray[hnswlib] (>=0.32.0,<0.33.0)", "duckduckgo-search (>=3.8.3,<4.0.0)", "elasticsearch (>=8,<9)", "esprima (>=4.0.1,<5.0.0)", "faiss-cpu (>=1,<2)", "google-api-python-client (==2.70.0)", "google-auth (>=2.18.1,<3.0.0)", "google-search-results (>=2,<3)", "gptcache (>=0.1.7)", "html2text (>=2020.1.16,<2021.0.0)", "huggingface_hub (>=0,<1)", "jinja2 (>=3,<4)", "jq (>=1.4.1,<2.0.0)", "lancedb (>=0.1,<0.2)", "langkit (>=0.0.6,<0.1.0)", "lark (>=1.1.5,<2.0.0)", "libdeeplake (>=0.0.60,<0.0.61)", "librosa (>=0.10.0.post2,<0.11.0)", "lxml (>=4.9.2,<5.0.0)", "manifest-ml (>=0.0.1,<0.0.2)", "marqo (>=1.2.4,<2.0.0)", "momento (>=1.10.1,<2.0.0)", "nebula3-python (>=3.4.0,<4.0.0)", "neo4j (>=5.8.1,<6.0.0)", "networkx (>=2.6.3,<4)", "nlpcloud (>=1,<2)", "nltk (>=3,<4)", "nomic (>=1.0.43,<2.0.0)", "openai (>=0,<1)", "openlm (>=0.0.5,<0.0.6)", "opensearch-py (>=2.0.0,<3.0.0)", "pdfminer-six (>=20221105,<20221106)", "pexpect (>=4.8.0,<5.0.0)", "pgvector (>=0.1.6,<0.2.0)", "pinecone-client (>=2,<3)", "pinecone-text (>=0.4.2,<0.5.0)", "psycopg2-binary (>=2.9.5,<3.0.0)", "pymongo (>=4.3.3,<5.0.0)", "pyowm (>=3.3.0,<4.0.0)", "pypdf (>=3.4.0,<4.0.0)", "pytesseract (>=0.3.10,<0.4.0)", "python-arango (>=7.5.9,<8.0.0)", "pyvespa (>=0.33.0,<0.34.0)", "qdrant-client (>=1.3.1,<2.0.0)", "rdflib (>=6.3.2,<7.0.0)", "redis (>=4,<5)", "requests-toolbelt (>=1.0.0,<2.0.0)", "sentence-transformers (>=2,<3)", "singlestoredb (>=0.7.1,<0.8.0)", "tensorflow-text (>=2.11.0,<3.0.0)", "tigrisdb (>=1.0.0b6,<2.0.0)", "tiktoken (>=0.3.2,<0.6.0)", "torch (>=1,<3)", "transformers (>=4,<5)", "weaviate-client (>=3,<4)", "wikipedia (>=1,<2)", "wolframalpha (==5.0.0)"]
all = ["O365 (>=2.0.26,<3.0.0)", "aleph-alpha-client (>=2.15.0,<3.0.0)", "amadeus (>=8.1.0)", "arxiv (>=1.4,<2.0)", "atlassian-python-api (>=3.36.0,<4.0.0)", "awadb (>=0.3.9,<0.4.0)", "azure-ai-formrecognizer (>=3.2.1,<4.0.0)", "azure-ai-vision (>=0.11.1b1,<0.12.0)", "azure-cognitiveservices-speech (>=1.28.0,<2.0.0)", "azure-cosmos (>=4.4.0b1,<5.0.0)", "azure-identity (>=1.12.0,<2.0.0)", "beautifulsoup4 (>=4,<5)", "clarifai (>=9.1.0)", "clickhouse-connect (>=0.5.14,<0.6.0)", "cohere (>=4,<5)", "deeplake (>=3.8.3,<4.0.0)", "docarray[hnswlib] (>=0.32.0,<0.33.0)", "duckduckgo-search (>=3.8.3,<4.0.0)", "elasticsearch (>=8,<9)", "esprima (>=4.0.1,<5.0.0)", "faiss-cpu (>=1,<2)", "google-api-python-client (==2.70.0)", "google-auth (>=2.18.1,<3.0.0)", "google-search-results (>=2,<3)", "gptcache (>=0.1.7)", "html2text (>=2020.1.16,<2021.0.0)", "huggingface_hub (>=0,<1)", "jinja2 (>=3,<4)", "jq (>=1.4.1,<2.0.0)", "lancedb (>=0.1,<0.2)", "langkit (>=0.0.6,<0.1.0)", "lark (>=1.1.5,<2.0.0)", "librosa (>=0.10.0.post2,<0.11.0)", "lxml (>=4.9.2,<5.0.0)", "manifest-ml (>=0.0.1,<0.0.2)", "marqo (>=1.2.4,<2.0.0)", "momento (>=1.10.1,<2.0.0)", "nebula3-python (>=3.4.0,<4.0.0)", "neo4j (>=5.8.1,<6.0.0)", "networkx (>=2.6.3,<4)", "nlpcloud (>=1,<2)", "nltk (>=3,<4)", "nomic (>=1.0.43,<2.0.0)", "openai (>=0,<1)", "openlm (>=0.0.5,<0.0.6)", "opensearch-py (>=2.0.0,<3.0.0)", "pdfminer-six (>=20221105,<20221106)", "pexpect (>=4.8.0,<5.0.0)", "pgvector (>=0.1.6,<0.2.0)", "pinecone-client (>=2,<3)", "pinecone-text (>=0.4.2,<0.5.0)", "psycopg2-binary (>=2.9.5,<3.0.0)", "pymongo (>=4.3.3,<5.0.0)", "pyowm (>=3.3.0,<4.0.0)", "pypdf (>=3.4.0,<4.0.0)", "pytesseract (>=0.3.10,<0.4.0)", "python-arango (>=7.5.9,<8.0.0)", "pyvespa (>=0.33.0,<0.34.0)", "qdrant-client (>=1.3.1,<2.0.0)", "rdflib (>=6.3.2,<7.0.0)", "redis (>=4,<5)", "requests-toolbelt (>=1.0.0,<2.0.0)", "sentence-transformers (>=2,<3)", "singlestoredb (>=0.7.1,<0.8.0)", "tensorflow-text (>=2.11.0,<3.0.0)", "tigrisdb (>=1.0.0b6,<2.0.0)", "tiktoken (>=0.3.2,<0.6.0)", "torch (>=1,<3)", "transformers (>=4,<5)", "weaviate-client (>=3,<4)", "wikipedia (>=1,<2)", "wolframalpha (==5.0.0)"]
azure = ["azure-ai-formrecognizer (>=3.2.1,<4.0.0)", "azure-ai-vision (>=0.11.1b1,<0.12.0)", "azure-cognitiveservices-speech (>=1.28.0,<2.0.0)", "azure-core (>=1.26.4,<2.0.0)", "azure-cosmos (>=4.4.0b1,<5.0.0)", "azure-identity (>=1.12.0,<2.0.0)", "azure-search-documents (==11.4.0b8)", "openai (>=0,<1)"]
clarifai = ["clarifai (>=9.1.0)"]
cli = ["typer (>=0.9.0,<0.10.0)"]
@ -1764,16 +1764,6 @@ files = [
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{file = "MarkupSafe-2.1.3-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:cb0932dc158471523c9637e807d9bfb93e06a95cbf010f1a38b98623b929ef2b"},
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@ -2749,7 +2739,6 @@ files = [
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@ -3915,4 +3895,4 @@ testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "p
[metadata]
lock-version = "2.0"
python-versions = ">=3.8.1,<4.0"
content-hash = "47b6bed43d64a2d4690d4554c78481485822b4b226a6e7f8a456dddb4ce8dd20"
content-hash = "e5c7a1f126afec578c3cd010d3d2131b96f5283a3402af5bb5084408cc7f7444"

4
pyproject.toml
Unescape Escape View File

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

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