Ng"vddlmZmZmZmZmZddlmZddlm Z ddl m Z m Z erddl mZGdde ZdS) ) TYPE_CHECKINGAnyCallableDictOptional)Document)get_from_dict_or_env) BaseModelmodel_validatorApifyDatasetLoaderceZdZUdZeed<eed<dZeeed<e de de d efd Z dddd d ed e de e gefdeedeedeed dfdZdddd d ed e de e gefdeedeedeed dfdZdddd dede de e gefdeedeedeed dfdZdddd dede de e gefdeedeedeed dfdZdS) ApifyWrapperzWrapper 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. apify_clientapify_client_asyncNapify_api_tokenbefore)modevaluesreturncft|dd} ddlm}m}||}t |jdx}r|jdxxdz cc<||}t |jdx}r|jdxxdz cc<||d <||d <n#t$rtd wxYw|S) zValidate environment. Validate that an Apify API token is set and the apify-client Python package exists in the current environment. rAPIFY_API_TOKENr) ApifyClientApifyClientAsync httpx_clientz user-agentz; Origin/langchainhttpx_async_clientrrz`Could not import apify-client Python package. Please install it with `pip install apify-client`.)r rrrgetattr http_clientheaders ImportError) clsrrrrclientr async_clientrs _/var/www/html/ai-engine/env/lib/python3.11/site-packages/langchain_community/utilities/apify.pyvalidate_environmentz!ApifyWrapper.validate_environments+/ %'8    B B B B B B B B [11F&v'9>JJJ| K$\2226JJ222++O<&&! Q#*<888 "+7F' ( (   E    s BBB.)build memory_mbytes timeout_secsactor_id run_inputdataset_mapping_functionr&r'r(r cddlm}|j|||||}||d|S)aRun an Actor on the Apify platform and wait for results to be ready. Args: actor_id (str): The ID or name of the Actor on the Apify platform. run_input (Dict): The input object of the Actor that you're trying to run. 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. Returns: ApifyDatasetLoader: A loader that will fetch the records from the Actor run's default dataset. rr r*r&r'r(defaultDatasetId dataset_idr+)$langchain_community.document_loadersr ractorcall selfr)r*r+r&r'r(r actor_calls r$ call_actorzApifyWrapper.call_actor8sv4 LKKKKK&,,X66;;'% <  "!!"45%=    cKddlm}|j|||||d{V}||d|S)aRun an Actor on the Apify platform and wait for results to be ready. Args: actor_id (str): The ID or name of the Actor on the Apify platform. run_input (Dict): The input object of the Actor that you're trying to run. 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. Returns: ApifyDatasetLoader: A loader that will fetch the records from the Actor run's default dataset. rr r-Nr.r/)r1r rr2r3r4s r$ acall_actorzApifyWrapper.acall_actor`s4 LKKKKK288BBGG'% H        "!!"45%=    r8task_id task_inputcddlm}|j|||||}||d|S)Run a saved Actor task on Apify and wait for results to be ready. Args: task_id (str): The ID or name of the task on the Apify platform. task_input (Dict): The input object of the task that you're trying to run. Overrides the task's saved input. 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. Returns: ApifyDatasetLoader: A loader that will fetch the records from the task run's default dataset. rr r<r&r'r(r.r/)r1r rtaskr3 r5r;r<r+r&r'r(r task_calls r$call_actor_taskzApifyWrapper.call_actor_tasksv6 LKKKKK%**73388!'% 9  "! !34%=    r8cKddlm}|j|||||d{V}||d|S)r>rr r?Nr.r/)r1r rr@r3rAs r$acall_actor_taskzApifyWrapper.acall_actor_tasks6 LKKKKK166w??DD!'% E        "! !34%=    r8)__name__ __module__ __qualname____doc__r__annotations__rrstrr classmethodrr%rrintr7r:rCrEr8r$rr s %)OXc])))_(###$3[$#L $'+&*& & & & & #+D68+;"< & } &  }& sm&  & & & & \ $'+&*& & & & & #+D68+;"< & } &  }& sm&  & & & & \ $'+&*' ' ' ' ' #+D68+;"< ' } '  }' sm'  ' ' ' ' ^ $'+&*' ' ' ' ' #+D68+;"< ' } '  }' sm'  ' ' ' ' ' ' r8rN)typingrrrrrlangchain_core.documentsrlangchain_core.utilsr pydanticr r r1r rrNr8r$rSs??????????????------555555////////HGGGGGGM M M M M 9M M M M M r8