Tony20100/langchain_full huggingface dataset:
langchain_core.structured_query.FilterDirective¶
class langchain_core.structured_query.FilterDirective[source]¶
Bases: Expr, ABC
Filtering expression.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
accept(visitor: Visitor) → Any¶
Accept a visitor.
Parameters
visitor (Visitor) – visitor to accept
Returns
result of visiting
Return type
Any
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
Parameters
_fields_set (Optional[SetStr]) – 
values (Any) – 
Return type
Model
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model¶
Duplicate a model, optionally choose which fields to include, exclude and change.
Parameters
include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to include in new model
exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to exclude from new model, as with values this takes precedence over include
update (Optional[DictStrAny]) – values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data
deep (bool) – set to True to make a deep copy of the model
deep (bool) – set to True to make a deep copy of the model
self (Model) – 
Returns
new model instance
Return type
Model
dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) → DictStrAny¶
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
Parameters
include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – 
exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – 
by_alias (bool) – 
skip_defaults (Optional[bool]) – 
exclude_unset (bool) – 
exclude_defaults (bool) – 
exclude_none (bool) – 
Return type
DictStrAny
classmethod from_orm(obj: Any) → Model¶
Parameters
obj (Any) – 
Return type
Model
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) → unicode¶
Generate a JSON representation of the model, include and exclude arguments as per dict().
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
Parameters
include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – 
exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – 
by_alias (bool) – 
skip_defaults (Optional[bool]) – 
exclude_unset (bool) – 
exclude_defaults (bool) – 
exclude_none (bool) – 
encoder (Optional[Callable[[Any], Any]]) – 
models_as_dict (bool) – 
dumps_kwargs (Any) – 
Return type
unicode
classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
Parameters
path (Union[str, Path]) – 
content_type (unicode) – 
encoding (unicode) – 
proto (Protocol) – 
allow_pickle (bool) – 
Return type
Model
classmethod parse_obj(obj: Any) → Model¶
Parameters
obj (Any) – 
Return type
Model
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
Parameters
b (Union[str, bytes]) – 
content_type (unicode) – 
encoding (unicode) – 
proto (Protocol) – 
allow_pickle (bool) – 
Return type
Model
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
Parameters
by_alias (bool) –
Parameters
by_alias (bool) – 
ref_template (unicode) – 
Return type
DictStrAny
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
Parameters
by_alias (bool) – 
ref_template (unicode) – 
dumps_kwargs (Any) – 
Return type
unicode
classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on fields based on this Model, globalns and localns.
Parameters
localns (Any) – 
Return type
None
classmethod validate(value: Any) → Model¶
Parameters
value (Any) – 
Return type
Model
langchain_core.structured_query.Comparator¶
class langchain_core.structured_query.Comparator(value)[source]¶
Enumerator of the comparison operators.
EQ = 'eq'¶
NE = 'ne'¶
GT = 'gt'¶
GTE = 'gte'¶
LT = 'lt'¶
LTE = 'lte'¶
CONTAIN = 'contain'¶
LIKE = 'like'¶
IN = 'in'¶
NIN = 'nin'¶
Examples using Comparator¶
How to construct filters for query analysis
langchain_core.structured_query.Comparison¶
class langchain_core.structured_query.Comparison[source]¶
Bases: FilterDirective
Comparison to a value.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
param attribute: str [Required]¶
param comparator: Comparator [Required]¶
param value: Any = None¶
accept(visitor: Visitor) → Any¶
Accept a visitor.
Parameters
visitor (Visitor) – visitor to accept
Returns
result of visiting
Return type
Any
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
Parameters
_fields_set (Optional[SetStr]) – 
values (Any) – 
Return type
Model
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model¶
Duplicate a model, optionally choose which fields to include, exclude and change.
Parameters
include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to include in new model
exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to exclude from new model, as with values this takes precedence over include
update (Optional[DictStrAny]) – values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data
deep (bool) – set to True to make a deep copy of the model
self (Model) – 
Returns
new model instance
Return type
Model
dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) → DictStrAny¶
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
Parameters
include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – 
exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – 
by_alias (bool) – 
skip_defaults (Optional[bool]) – 
exclude_unset (bool) – 
exclude_defaults (bool) – 
exclude_none (bool) – 
Return type
DictStrAny
classmethod from_orm(obj: Any) → Model¶
Parameters
obj (Any) – 
Return type
Model
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) → unicode¶
Generate a JSON representation of the model, include and exclude arguments as per dict().
Parameters
by_alias (bool) – 
ref_template (unicode) – 
Return type
DictStrAny
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
Parameters
by_alias (bool) – 
ref_template (unicode) – 
dumps_kwargs (Any) – 
Return type
unicode
classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on fields based on this Model, globalns and localns.
Parameters
localns (Any) – 
Return type
None
classmethod validate(value: Any) → Model¶
Parameters
value (Any) – 
Return type
Model
Examples using Comparison¶
How to construct filters for query analysis
langchain_core.structured_query.Expr¶
class langchain_core.structured_query.Expr[source]¶
Bases: BaseModel
Base class for all expressions.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
accept(visitor: Visitor) → Any[source]¶
Accept a visitor.
Parameters
visitor (Visitor) – visitor to accept
Returns
result of visiting
Return type
Any
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
Parameters
_fields_set (Optional[SetStr]) – 
values (Any) – 
Return type
Model
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model¶
Duplicate a model, optionally choose which fields to include, exclude and change.
Parameters
include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to include in new model
exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to exclude from new model, as with values this takes precedence over include
update (Optional[DictStrAny]) – values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data
deep (bool) – set to True to make a deep copy of the model
langchain_core.structured_query.Operation¶
class langchain_core.structured_query.Operation[source]¶
Bases: FilterDirective
Llogical operation over other directives.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
param arguments: List[FilterDirective] [Required]¶
param operator: Operator [Required]¶
accept(visitor: Visitor) → Any¶
Accept a visitor.
Parameters
visitor (Visitor) – visitor to accept
Returns
result of visiting
Return type
Any
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
Parameters
_fields_set (Optional[SetStr]) – 
values (Any) – 
Return type
Model
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model¶
Duplicate a model, optionally choose which fields to include, exclude and change.
Parameters
include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to include in new model
exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to exclude from new model, as with values this takes precedence over include
update (Optional[DictStrAny]) – values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data
Parameters
by_alias (bool) – 
ref_template (unicode) – 
Return type
DictStrAny
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
Parameters
by_alias (bool) – 
ref_template (unicode) – 
dumps_kwargs (Any) – 
Return type
unicode
classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on fields based on this Model, globalns and localns.
Parameters
localns (Any) – 
Return type
None
classmethod validate(value: Any) → Model¶
Parameters
value (Any) – 
Return type
Model
Examples using Operation¶
How to construct filters for query analysis
langchain_core.structured_query.StructuredQuery¶
class langchain_core.structured_query.StructuredQuery[source]¶
Bases: Expr
Structured query.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
param filter: Optional[FilterDirective] = None¶
Filtering expression.
param limit: Optional[int] = None¶
Limit on the number of results.
param query: str [Required]¶
Query string.
accept(visitor: Visitor) → Any¶
Accept a visitor.
Parameters
visitor (Visitor) – visitor to accept
Returns
result of visiting
Return type
Any
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
Parameters
_fields_set (Optional[SetStr]) – 
values (Any) – 
Return type
Model
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model¶
Duplicate a model, optionally choose which fields to include, exclude and change.
Parameters
include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to include in new model
exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to exclude from new model, as with values this takes precedence over include
update (Optional[DictStrAny]) – values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data
deep (bool) – set to True to make a deep copy of the model
self (Model) – 
Returns
new model instance
Return type
Model
dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) → DictStrAny¶
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
Parameters
include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – 
exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – 
by_alias (bool) – 
skip_defaults (Optional[bool]) – 
exclude_unset (bool) – 
exclude_defaults (bool) – 
exclude_none (bool) – 
Return type
DictStrAny
classmethod from_orm(obj: Any) → Model¶
Parameters
obj (Any) – 
Return type
Model
Parameters
obj (Any) – 
Return type
Model
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) → unicode¶
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
Parameters
include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – 
exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – 
by_alias (bool) – 
skip_defaults (Optional[bool]) – 
exclude_unset (bool) – 
exclude_defaults (bool) – 
exclude_none (bool) – 
encoder (Optional[Callable[[Any], Any]]) – 
models_as_dict (bool) – 
dumps_kwargs (Any) – 
Return type
unicode
classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
Parameters
path (Union[str, Path]) – 
content_type (unicode) – 
encoding (unicode) – 
proto (Protocol) – 
allow_pickle (bool) – 
Return type
Model
classmethod parse_obj(obj: Any) → Model¶
Parameters
obj (Any) – 
Return type
Model
Parameters
obj (Any) – 
Return type
Model
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
Parameters
b (Union[str, bytes]) – 
content_type (unicode) – 
encoding (unicode) – 
proto (Protocol) – 
allow_pickle (bool) – 
Return type
Model
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
Parameters
by_alias (bool) – 
ref_template (unicode) – 
Return type
DictStrAny
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
Parameters
by_alias (bool) – 
ref_template (unicode) – 
dumps_kwargs (Any) – 
Return type
unicode
classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on fields based on this Model, globalns and localns.
Parameters
localns (Any) – 
Return type
None
classmethod validate(value: Any) → Model¶
Parameters
value (Any) – 
Return type
Model
Examples using StructuredQuery¶
How to construct filters for query analysis
langchain_ai21.semantic_text_splitter.AI21SemanticTextSplitter¶
class langchain_ai21.semantic_text_splitter.AI21SemanticTextSplitter(chunk_size: int = 0, chunk_overlap: int = 0, client: Optional[Any] = None, api_key: Optional[SecretStr] = None, api_host: Optional[str] = None, timeout_sec: Optional[float] = None, num_retries: Optional[int] = None, **kwargs: Any)[source]¶
Splitting text into coherent and readable units,
based on distinct topics and lines
Create a new TextSplitter.
Methods
__init__([chunk_size, chunk_overlap, ...])
Create a new TextSplitter.
atransform_documents(documents, **kwargs)
Asynchronously transform a list of documents.
create_documents(texts[, metadatas])
Create documents from a list of texts.
from_huggingface_tokenizer(tokenizer, **kwargs)
Text splitter that uses HuggingFace tokenizer to count length.
from_tiktoken_encoder([encoding_name, ...])
Text splitter that uses tiktoken encoder to count length.
split_documents(documents)
Split documents.
split_text(source)
Split text into multiple components.
split_text_to_documents(source)
Split text into multiple documents.
transform_documents(documents, **kwargs)
Transform sequence of documents by splitting them.
Parameters
chunk_size (int) – 
chunk_overlap (int) – 
client (Optional[Any]) – 
api_key (Optional[SecretStr]) – 
api_host (Optional[str]) – 
timeout_sec (Optional[float]) – 
num_retries (Optional[int]) – 
kwargs (Any) –
num_retries (Optional[int]) – 
kwargs (Any) – 
__init__(chunk_size: int = 0, chunk_overlap: int = 0, client: Optional[Any] = None, api_key: Optional[SecretStr] = None, api_host: Optional[str] = None, timeout_sec: Optional[float] = None, num_retries: Optional[int] = None, **kwargs: Any) → None[source]¶
Create a new TextSplitter.
Parameters
chunk_size (int) – 
chunk_overlap (int) – 
client (Optional[Any]) – 
api_key (Optional[SecretStr]) – 
api_host (Optional[str]) – 
timeout_sec (Optional[float]) – 
num_retries (Optional[int]) – 
kwargs (Any) – 
Return type
None
async atransform_documents(documents: Sequence[Document], **kwargs: Any) → Sequence[Document]¶
Asynchronously transform a list of documents.
Parameters
documents (Sequence[Document]) – A sequence of Documents to be transformed.
kwargs (Any) – 
Returns
A list of transformed Documents.
Return type
Sequence[Document]
create_documents(texts: List[str], metadatas: Optional[List[dict]] = None) → List[Document][source]¶
Create documents from a list of texts.
Parameters
texts (List[str]) – 
metadatas (Optional[List[dict]]) – 
Return type
List[Document]
classmethod from_huggingface_tokenizer(tokenizer: Any, **kwargs: Any) → TextSplitter¶
Text splitter that uses HuggingFace tokenizer to count length.
Parameters
tokenizer (Any) – 
kwargs (Any) – 
Return type
TextSplitter
kwargs (Any) – 
Return type
TextSplitter
classmethod from_tiktoken_encoder(encoding_name: str = 'gpt2', model_name: Optional[str] = None, allowed_special: Union[Literal['all'], AbstractSet[str]] = {}, disallowed_special: Union[Literal['all'], Collection[str]] = 'all', **kwargs: Any) → TS¶
Text splitter that uses tiktoken encoder to count length.
Parameters
encoding_name (str) – 
model_name (Optional[str]) – 
allowed_special (Union[Literal['all'], ~typing.AbstractSet[str]]) – 
disallowed_special (Union[Literal['all'], ~typing.Collection[str]]) – 
kwargs (Any) – 
Return type
TS
split_documents(documents: Iterable[Document]) → List[Document]¶
Split documents.
Parameters
documents (Iterable[Document]) – 
Return type
List[Document]
split_text(source: str) → List[str][source]¶
Split text into multiple components.
Parameters
source (str) – Specifies the text input for text segmentation
Return type
List[str]
split_text_to_documents(source: str) → List[Document][source]¶
Split text into multiple documents.
Parameters
source (str) – Specifies the text input for text segmentation
Return type
List[Document]
transform_documents(documents: Sequence[Document], **kwargs: Any) → Sequence[Document]¶
Transform sequence of documents by splitting them.
Parameters
documents (Sequence[Document]) – 
kwargs (Any) – 
Return type
Sequence[Document]
langchain_community.document_transformers.google_translate.GoogleTranslateTransformer¶
class langchain_community.document_transformers.google_translate.GoogleTranslateTransformer(project_id: str, *, location: str = 'global', model_id: Optional[str] = None, glossary_id: Optional[str] = None, api_endpoint: Optional[str] = None)[source]¶
[Deprecated] Translate text documents using Google Cloud Translation.
Notes
Deprecated since version 0.0.32.
Parameters
project_id (str) – Google Cloud Project ID.
location (str) – (Optional) Translate model location.
model_id (Optional[str]) – (Optional) Translate model ID to use.
glossary_id (Optional[str]) – (Optional) Translate glossary ID to use.
api_endpoint (Optional[str]) – (Optional) Regional endpoint to use.
Methods
__init__(project_id, *[, location, ...])
param project_id
Google Cloud Project ID.
atransform_documents(documents, **kwargs)
Asynchronously transform a list of documents.
transform_documents(documents, **kwargs)
Translate text documents using Google Translate.
__init__(project_id: str, *, location: str = 'global', model_id: Optional[str] = None, glossary_id: Optional[str] = None, api_endpoint: Optional[str] = None) → None[source]¶
Parameters
project_id (str) – Google Cloud Project ID.
location (str) – (Optional) Translate model location.
model_id (Optional[str]) – (Optional) Translate model ID to use.
glossary_id (Optional[str]) – (Optional) Translate glossary ID to use.
api_endpoint (Optional[str]) – (Optional) Regional endpoint to use.
Return type
None
async atransform_documents(documents: Sequence[Document], **kwargs: Any) → Sequence[Document]¶