langchain_community.utilities.apify.ApifyWrapper

class langchain_community.utilities.apify.ApifyWrapper[source]

Bases: BaseModel

封装了Apify。 要使用，应安装``apify-client`` python包， 并设置环境变量``APIFY_API_TOKEN``为您的API密钥，或将 `apify_api_token`作为构造函数的一个命名参数传递。

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 apify_client: Any = None
param apify_client_async: Any = None
async acall_actor(actor_id: str, run_input: Dict, dataset_mapping_function: Callable[[Dict], Document], *, build: Optional[str] = None, memory_mbytes: Optional[int] = None, timeout_secs: Optional[int] = None) → ApifyDatasetLoader[source]

在Apify平台上运行一个Actor，并等待结果准备就绪。 参数:

actor_id (str): Apify平台上Actor的ID或名称。 run_input (Dict): 您要运行的Actor的输入对象。 dataset_mapping_function (Callable): 一个函数，接受一个字典（一个Apify数据集项）并将其转换为Document类的实例。 build (str, optional): 可选参数，指定要运行的actor构建。可以是构建标签或构建编号。 memory_mbytes (int, optional): 运行的可选内存限制，以兆字节为单位。 timeout_secs (int, optional): 运行的可选超时时间，以秒为单位。

返回:

ApifyDatasetLoader: 一个加载器，将从Actor运行的默认数据集中获取记录。

Parameters

  • actor_id (str) –

  • run_input (Dict) –

  • dataset_mapping_function (Callable[[Dict], Document]) –

  • build (Optional[str]) –

  • memory_mbytes (Optional[int]) –

  • timeout_secs (Optional[int]) –

Return type

ApifyDatasetLoader

async acall_actor_task(task_id: str, task_input: Dict, dataset_mapping_function: Callable[[Dict], Document], *, build: Optional[str] = None, memory_mbytes: Optional[int] = None, timeout_secs: Optional[int] = None) → ApifyDatasetLoader[source]

在Apify上运行保存的Actor任务，并等待结果准备就绪。 参数：

task_id (str): Apify平台上任务的ID或名称。 task_input (Dict): 您要运行的任务的输入对象。覆盖任务的保存输入。 dataset_mapping_function (Callable): 一个接受单个字典（Apify数据集项）并将其转换为Document类实例的函数。 build (str, optional): 可选指定要运行的actor构建。可以是构建标签或构建编号。 memory_mbytes (int, optional): 运行的可选内存限制，以兆字节为单位。 timeout_secs (int, optional): 运行的可选超时时间，以秒为单位。

返回：

ApifyDatasetLoader: 一个加载器，将从任务运行的默认数据集中获取记录。

Parameters

  • task_id (str) –

  • task_input (Dict) –

  • dataset_mapping_function (Callable[[Dict], Document]) –

  • build (Optional[str]) –

  • memory_mbytes (Optional[int]) –

  • timeout_secs (Optional[int]) –

Return type

ApifyDatasetLoader

call_actor(actor_id: str, run_input: Dict, dataset_mapping_function: Callable[[Dict], Document], *, build: Optional[str] = None, memory_mbytes: Optional[int] = None, timeout_secs: Optional[int] = None) → ApifyDatasetLoader[source]

在Apify平台上运行一个Actor，并等待结果准备就绪。 参数：

actor_id（str）：Apify平台上Actor的ID或名称。 run_input（Dict）：您要运行的Actor的输入对象。 dataset_mapping_function（Callable）：一个函数，接受一个字典（Apify数据集项）并将其转换为Document类的实例。 build（str，可选）：可选指定要运行的actor构建。可以是构建标签或构建编号。 memory_mbytes（int，可选）：运行的可选内存限制，以兆字节为单位。 timeout_secs（int，可选）：运行的可选超时时间，以秒为单位。

返回：

ApifyDatasetLoader：一个加载器，将从Actor运行的默认数据集中获取记录。

Parameters

  • actor_id (str) –

  • run_input (Dict) –

  • dataset_mapping_function (Callable[[Dict], Document]) –

  • build (Optional[str]) –

  • memory_mbytes (Optional[int]) –

  • timeout_secs (Optional[int]) –

Return type

ApifyDatasetLoader

call_actor_task(task_id: str, task_input: Dict, dataset_mapping_function: Callable[[Dict], Document], *, build: Optional[str] = None, memory_mbytes: Optional[int] = None, timeout_secs: Optional[int] = None) → ApifyDatasetLoader[source]

在Apify上运行保存的Actor任务，并等待结果准备就绪。 参数：

task_id (str): Apify平台上任务的ID或名称。 task_input (Dict): 您要运行的任务的输入对象。覆盖任务的保存输入。 dataset_mapping_function (Callable): 一个接受单个字典（Apify数据集项）并将其转换为Document类实例的函数。 build (str, optional): 可选指定要运行的actor构建。可以是构建标签或构建编号。 memory_mbytes (int, optional): 运行的可选内存限制，以兆字节为单位。 timeout_secs (int, optional): 运行的可选超时时间，以秒为单位。

返回：

ApifyDatasetLoader: 一个加载器，将从任务运行的默认数据集中获取记录。

Parameters

  • task_id (str) –

  • task_input (Dict) –

  • dataset_mapping_function (Callable[[Dict], Document]) –

  • build (Optional[str]) –

  • memory_mbytes (Optional[int]) –

  • timeout_secs (Optional[int]) –

Return type

ApifyDatasetLoader

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().

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) –

  • 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 ApifyWrapper