ApifyWrapper#

class langchain_community.utilities.apify.ApifyWrapper[source]#

Bases: BaseModel

Wrapper around Apify. To use, you should have the apify-client python package installed, and the environment variable APIFY_API_TOKEN set with your API key, or pass apify_api_token as a named parameter to the constructor.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

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

Run an Actor on the Apify platform and wait for results to be ready. :param actor_id: The ID or name of the Actor on the Apify platform. :type actor_id: str :param run_input: The input object of the Actor that you’re trying to run. :type run_input: Dict :param dataset_mapping_function: A function that takes a single

dictionary (an Apify dataset item) and converts it to an instance of the Document class.

Parameters:

  • build (str, optional) – Optionally specifies the actor build to run. It can be either a build tag or build number.

  • memory_mbytes (int, optional) – Optional memory limit for the run, in megabytes.

  • timeout_secs (int, optional) – Optional timeout for the run, in seconds.

  • actor_id (str)

  • run_input (Dict)

  • dataset_mapping_function (Callable)

Returns:

A loader that will fetch the records from the

Actor run’s default dataset.

Return type:

ApifyDatasetLoader

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

Run a saved Actor task on Apify and wait for results to be ready. :param task_id: The ID or name of the task on the Apify platform. :type task_id: str :param task_input: The input object of the task that you’re trying to run.

Overrides the task’s saved input.

Parameters:

  • dataset_mapping_function (Callable) – A function that takes a single dictionary (an Apify dataset item) and converts it to an instance of the Document class.

  • build (str, optional) – Optionally specifies the actor build to run. It can be either a build tag or build number.

  • memory_mbytes (int, optional) – Optional memory limit for the run, in megabytes.

  • timeout_secs (int, optional) – Optional timeout for the run, in seconds.

  • task_id (str)

  • task_input (Dict)

Returns:

A loader that will fetch the records from the

task run’s default dataset.

Return type:

ApifyDatasetLoader

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

Run an Actor on the Apify platform and wait for results to be ready. :param actor_id: The ID or name of the Actor on the Apify platform. :type actor_id: str :param run_input: The input object of the Actor that you’re trying to run. :type run_input: Dict :param dataset_mapping_function: A function that takes a single

dictionary (an Apify dataset item) and converts it to an instance of the Document class.

Parameters:

  • build (str, optional) – Optionally specifies the actor build to run. It can be either a build tag or build number.

  • memory_mbytes (int, optional) – Optional memory limit for the run, in megabytes.

  • timeout_secs (int, optional) – Optional timeout for the run, in seconds.

  • actor_id (str)

  • run_input (Dict)

  • dataset_mapping_function (Callable)

Returns:

A loader that will fetch the records from the

Actor run’s default dataset.

Return type:

ApifyDatasetLoader

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

Run a saved Actor task on Apify and wait for results to be ready. :param task_id: The ID or name of the task on the Apify platform. :type task_id: str :param task_input: The input object of the task that you’re trying to run.

Overrides the task’s saved input.

Parameters:

  • dataset_mapping_function (Callable) – A function that takes a single dictionary (an Apify dataset item) and converts it to an instance of the Document class.

  • build (str, optional) – Optionally specifies the actor build to run. It can be either a build tag or build number.

  • memory_mbytes (int, optional) – Optional memory limit for the run, in megabytes.

  • timeout_secs (int, optional) – Optional timeout for the run, in seconds.

  • task_id (str)

  • task_input (Dict)

Returns:

A loader that will fetch the records from the

task run’s default dataset.

Return type:

ApifyDatasetLoader

Examples using ApifyWrapper