o i%8@sddlZddlmZmZddlmZddlmZddlm Z ddl m Z ddl m Z dd lmZd d lmZmZd d lmZeejd ZGdddZGdddZdS)N)AsyncClientWrapperSyncClientWrapper)RequestOptions)CreateEmbedJobResponse)EmbedInputType)EmbedJob) EmbeddingType)ListEmbedJobResponse)AsyncRawEmbedJobsClientRawEmbedJobsClient)CreateEmbedJobRequestTruncate.c@eZdZdefddZedefddZddd ej e de fd d Z e e e dd d edededej edej ejedej ed ej e defddZddded ej e defddZddded ej e ddfddZdS)EmbedJobsClientclient_wrappercCt|d|_dSN)r)r _raw_clientselfrr^/var/www/html/karishye-ai-python/venv/lib/python3.10/site-packages/cohere/embed_jobs/client.py__init__zEmbedJobsClient.__init__returncC|jS)z Retrieves a raw implementation of this client that returns raw responses. Returns ------- RawEmbedJobsClient rrrrrwith_raw_response z!EmbedJobsClient.with_raw_responseNrequest_optionsr"cCs|jj|d}|jS)a! The list embed job endpoint allows users to view all embed jobs history for that specific user. Parameters ---------- request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- ListEmbedJobResponse OK Examples -------- from cohere import Client client = Client( client_name="YOUR_CLIENT_NAME", token="YOUR_TOKEN", ) client.embed_jobs.list() r!rlistdatarr" _responserrrr$"szEmbedJobsClient.listnameembedding_typestruncater"model dataset_id input_typer)r*r+c Cs |jj|||||||d}|jS)a This API launches an async Embed job for a [Dataset](https://docs.cohere.com/docs/datasets) of type `embed-input`. The result of a completed embed job is new Dataset of type `embed-output`, which contains the original text entries and the corresponding embeddings. Parameters ---------- model : str ID of the embedding model. Available models and corresponding embedding dimensions: - `embed-english-v3.0` : 1024 - `embed-multilingual-v3.0` : 1024 - `embed-english-light-v3.0` : 384 - `embed-multilingual-light-v3.0` : 384 dataset_id : str ID of a [Dataset](https://docs.cohere.com/docs/datasets). The Dataset must be of type `embed-input` and must have a validation status `Validated` input_type : EmbedInputType name : typing.Optional[str] The name of the embed job. embedding_types : typing.Optional[typing.Sequence[EmbeddingType]] Specifies the types of embeddings you want to get back. Not required and default is None, which returns the Embed Floats response type. Can be one or more of the following types. * `"float"`: Use this when you want to get back the default float embeddings. Valid for all models. * `"int8"`: Use this when you want to get back signed int8 embeddings. Valid for v3 and newer model versions. * `"uint8"`: Use this when you want to get back unsigned int8 embeddings. Valid for v3 and newer model versions. * `"binary"`: Use this when you want to get back signed binary embeddings. Valid for v3 and newer model versions. * `"ubinary"`: Use this when you want to get back unsigned binary embeddings. Valid for v3 and newer model versions. truncate : typing.Optional[CreateEmbedJobRequestTruncate] One of `START|END` to specify how the API will handle inputs longer than the maximum token length. Passing `START` will discard the start of the input. `END` will discard the end of the input. In both cases, input is discarded until the remaining input is exactly the maximum input token length for the model. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- CreateEmbedJobResponse OK Examples -------- from cohere import Client client = Client( client_name="YOUR_CLIENT_NAME", token="YOUR_TOKEN", ) client.embed_jobs.create( model="model", dataset_id="dataset_id", input_type="search_document", ) r,r-r.r)r*r+r"rcreater% rr,r-r.r)r*r+r"r'rrrr1=sF zEmbedJobsClient.createidcC|jj||d}|jS)aa This API retrieves the details about an embed job started by the same user. Parameters ---------- id : str The ID of the embed job to retrieve. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- EmbedJob OK Examples -------- from cohere import Client client = Client( client_name="YOUR_CLIENT_NAME", token="YOUR_TOKEN", ) client.embed_jobs.get( id="id", ) r!rgetr%rr3r"r'rrrr6szEmbedJobsClient.getcCr4)a$ This API allows users to cancel an active embed job. Once invoked, the embedding process will be terminated, and users will be charged for the embeddings processed up to the cancellation point. It's important to note that partial results will not be available to users after cancellation. Parameters ---------- id : str The ID of the embed job to cancel. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- None Examples -------- from cohere import Client client = Client( client_name="YOUR_CLIENT_NAME", token="YOUR_TOKEN", ) client.embed_jobs.cancel( id="id", ) r!rcancelr%r7rrrr9szEmbedJobsClient.cancel)__name__ __module__ __qualname__rrpropertyr rtypingOptionalrr r$OMITstrrSequencer rrr1rr6r9rrrrrs8 !  "Q& rc@r)AsyncEmbedJobsClientrcCrr)r rrrrrrrzAsyncEmbedJobsClient.__init__rcCr)z Retrieves a raw implementation of this client that returns raw responses. Returns ------- AsyncRawEmbedJobsClient rrrrrrr z&AsyncEmbedJobsClient.with_raw_responseNr!r"cs|jj|dIdH}|jS)a The list embed job endpoint allows users to view all embed jobs history for that specific user. Parameters ---------- request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- ListEmbedJobResponse OK Examples -------- import asyncio from cohere import AsyncClient client = AsyncClient( client_name="YOUR_CLIENT_NAME", token="YOUR_TOKEN", ) async def main() -> None: await client.embed_jobs.list() asyncio.run(main()) r!Nr#r&rrrr$s zAsyncEmbedJobsClient.listr(r,r-r.r)r*r+c s(|jj|||||||dIdH}|jS)a* This API launches an async Embed job for a [Dataset](https://docs.cohere.com/docs/datasets) of type `embed-input`. The result of a completed embed job is new Dataset of type `embed-output`, which contains the original text entries and the corresponding embeddings. Parameters ---------- model : str ID of the embedding model. Available models and corresponding embedding dimensions: - `embed-english-v3.0` : 1024 - `embed-multilingual-v3.0` : 1024 - `embed-english-light-v3.0` : 384 - `embed-multilingual-light-v3.0` : 384 dataset_id : str ID of a [Dataset](https://docs.cohere.com/docs/datasets). The Dataset must be of type `embed-input` and must have a validation status `Validated` input_type : EmbedInputType name : typing.Optional[str] The name of the embed job. embedding_types : typing.Optional[typing.Sequence[EmbeddingType]] Specifies the types of embeddings you want to get back. Not required and default is None, which returns the Embed Floats response type. Can be one or more of the following types. * `"float"`: Use this when you want to get back the default float embeddings. Valid for all models. * `"int8"`: Use this when you want to get back signed int8 embeddings. Valid for v3 and newer model versions. * `"uint8"`: Use this when you want to get back unsigned int8 embeddings. Valid for v3 and newer model versions. * `"binary"`: Use this when you want to get back signed binary embeddings. Valid for v3 and newer model versions. * `"ubinary"`: Use this when you want to get back unsigned binary embeddings. Valid for v3 and newer model versions. truncate : typing.Optional[CreateEmbedJobRequestTruncate] One of `START|END` to specify how the API will handle inputs longer than the maximum token length. Passing `START` will discard the start of the input. `END` will discard the end of the input. In both cases, input is discarded until the remaining input is exactly the maximum input token length for the model. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- CreateEmbedJobResponse OK Examples -------- import asyncio from cohere import AsyncClient client = AsyncClient( client_name="YOUR_CLIENT_NAME", token="YOUR_TOKEN", ) async def main() -> None: await client.embed_jobs.create( model="model", dataset_id="dataset_id", input_type="search_document", ) asyncio.run(main()) r/Nr0r2rrrr1sN  zAsyncEmbedJobsClient.creater3c|jj||dIdH}|jS)a This API retrieves the details about an embed job started by the same user. Parameters ---------- id : str The ID of the embed job to retrieve. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- EmbedJob OK Examples -------- import asyncio from cohere import AsyncClient client = AsyncClient( client_name="YOUR_CLIENT_NAME", token="YOUR_TOKEN", ) async def main() -> None: await client.embed_jobs.get( id="id", ) asyncio.run(main()) r!Nr5r7rrrr6Ys%zAsyncEmbedJobsClient.getcrD)a This API allows users to cancel an active embed job. Once invoked, the embedding process will be terminated, and users will be charged for the embeddings processed up to the cancellation point. It's important to note that partial results will not be available to users after cancellation. Parameters ---------- id : str The ID of the embed job to cancel. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- None Examples -------- import asyncio from cohere import AsyncClient client = AsyncClient( client_name="YOUR_CLIENT_NAME", token="YOUR_TOKEN", ) async def main() -> None: await client.embed_jobs.cancel( id="id", ) asyncio.run(main()) r!Nr8r7rrrr9s$zAsyncEmbedJobsClient.cancel)r:r;r<rrr=r rr>r?rr r$r@rArrBr rrr1rr6r9rrrrrCs8 )  "Y&(rC)r>core.client_wrapperrrcore.request_optionsrtypes.create_embed_job_responsertypes.embed_input_typertypes.embed_jobrtypes.embedding_typer types.list_embed_job_responser raw_clientr r 'types.create_embed_job_request_truncatercastAnyr@rrCrrrrs       <