# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details. from __future__ import annotations from typing import Dict, Optional from typing_extensions import Literal import httpx from .. import _legacy_response from ..types import batch_list_params, batch_create_params from .._types import NOT_GIVEN, Body, Query, Headers, NotGiven from .._utils import ( maybe_transform, async_maybe_transform, ) from .._compat import cached_property from .._resource import SyncAPIResource, AsyncAPIResource from .._response import to_streamed_response_wrapper, async_to_streamed_response_wrapper from ..pagination import SyncCursorPage, AsyncCursorPage from ..types.batch import Batch from .._base_client import ( AsyncPaginator, make_request_options, ) __all__ = ["Batches", "AsyncBatches"] class Batches(SyncAPIResource): @cached_property def with_raw_response(self) -> BatchesWithRawResponse: """ This property can be used as a prefix for any HTTP method call to return the the raw response object instead of the parsed content. For more information, see https://www.github.com/openai/openai-python#accessing-raw-response-data-eg-headers """ return BatchesWithRawResponse(self) @cached_property def with_streaming_response(self) -> BatchesWithStreamingResponse: """ An alternative to `.with_raw_response` that doesn't eagerly read the response body. For more information, see https://www.github.com/openai/openai-python#with_streaming_response """ return BatchesWithStreamingResponse(self) def create( self, *, completion_window: Literal["24h"], endpoint: Literal["/v1/chat/completions", "/v1/embeddings", "/v1/completions"], input_file_id: str, metadata: Optional[Dict[str, str]] | NotGiven = NOT_GIVEN, # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs. # The extra values given here take precedence over values defined on the client or passed to this method. extra_headers: Headers | None = None, extra_query: Query | None = None, extra_body: Body | None = None, timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN, ) -> Batch: """ Creates and executes a batch from an uploaded file of requests Args: completion_window: The time frame within which the batch should be processed. Currently only `24h` is supported. endpoint: The endpoint to be used for all requests in the batch. Currently `/v1/chat/completions`, `/v1/embeddings`, and `/v1/completions` are supported. Note that `/v1/embeddings` batches are also restricted to a maximum of 50,000 embedding inputs across all requests in the batch. input_file_id: The ID of an uploaded file that contains requests for the new batch. See [upload file](https://platform.openai.com/docs/api-reference/files/create) for how to upload a file. Your input file must be formatted as a [JSONL file](https://platform.openai.com/docs/api-reference/batch/request-input), and must be uploaded with the purpose `batch`. The file can contain up to 50,000 requests, and can be up to 100 MB in size. metadata: Optional custom metadata for the batch. extra_headers: Send extra headers extra_query: Add additional query parameters to the request extra_body: Add additional JSON properties to the request timeout: Override the client-level default timeout for this request, in seconds """ return self._post( "/batches", body=maybe_transform( { "completion_window": completion_window, "endpoint": endpoint, "input_file_id": input_file_id, "metadata": metadata, }, batch_create_params.BatchCreateParams, ), options=make_request_options( extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout ), cast_to=Batch, ) def retrieve( self, batch_id: str, *, # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs. # The extra values given here take precedence over values defined on the client or passed to this method. extra_headers: Headers | None = None, extra_query: Query | None = None, extra_body: Body | None = None, timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN, ) -> Batch: """ Retrieves a batch. Args: extra_headers: Send extra headers extra_query: Add additional query parameters to the request extra_body: Add additional JSON properties to the request timeout: Override the client-level default timeout for this request, in seconds """ if not batch_id: raise ValueError(f"Expected a non-empty value for `batch_id` but received {batch_id!r}") return self._get( f"/batches/{batch_id}", options=make_request_options( extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout ), cast_to=Batch, ) def list( self, *, after: str | NotGiven = NOT_GIVEN, limit: int | NotGiven = NOT_GIVEN, # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs. # The extra values given here take precedence over values defined on the client or passed to this method. extra_headers: Headers | None = None, extra_query: Query | None = None, extra_body: Body | None = None, timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN, ) -> SyncCursorPage[Batch]: """List your organization's batches. Args: after: A cursor for use in pagination. `after` is an object ID that defines your place in the list. For instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent call can include after=obj_foo in order to fetch the next page of the list. limit: A limit on the number of objects to be returned. Limit can range between 1 and 100, and the default is 20. extra_headers: Send extra headers extra_query: Add additional query parameters to the request extra_body: Add additional JSON properties to the request timeout: Override the client-level default timeout for this request, in seconds """ return self._get_api_list( "/batches", page=SyncCursorPage[Batch], options=make_request_options( extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout, query=maybe_transform( { "after": after, "limit": limit, }, batch_list_params.BatchListParams, ), ), model=Batch, ) def cancel( self, batch_id: str, *, # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs. # The extra values given here take precedence over values defined on the client or passed to this method. extra_headers: Headers | None = None, extra_query: Query | None = None, extra_body: Body | None = None, timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN, ) -> Batch: """Cancels an in-progress batch. The batch will be in status `cancelling` for up to 10 minutes, before changing to `cancelled`, where it will have partial results (if any) available in the output file. Args: extra_headers: Send extra headers extra_query: Add additional query parameters to the request extra_body: Add additional JSON properties to the request timeout: Override the client-level default timeout for this request, in seconds """ if not batch_id: raise ValueError(f"Expected a non-empty value for `batch_id` but received {batch_id!r}") return self._post( f"/batches/{batch_id}/cancel", options=make_request_options( extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout ), cast_to=Batch, ) class AsyncBatches(AsyncAPIResource): @cached_property def with_raw_response(self) -> AsyncBatchesWithRawResponse: """ This property can be used as a prefix for any HTTP method call to return the the raw response object instead of the parsed content. For more information, see https://www.github.com/openai/openai-python#accessing-raw-response-data-eg-headers """ return AsyncBatchesWithRawResponse(self) @cached_property def with_streaming_response(self) -> AsyncBatchesWithStreamingResponse: """ An alternative to `.with_raw_response` that doesn't eagerly read the response body. For more information, see https://www.github.com/openai/openai-python#with_streaming_response """ return AsyncBatchesWithStreamingResponse(self) async def create( self, *, completion_window: Literal["24h"], endpoint: Literal["/v1/chat/completions", "/v1/embeddings", "/v1/completions"], input_file_id: str, metadata: Optional[Dict[str, str]] | NotGiven = NOT_GIVEN, # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs. # The extra values given here take precedence over values defined on the client or passed to this method. extra_headers: Headers | None = None, extra_query: Query | None = None, extra_body: Body | None = None, timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN, ) -> Batch: """ Creates and executes a batch from an uploaded file of requests Args: completion_window: The time frame within which the batch should be processed. Currently only `24h` is supported. endpoint: The endpoint to be used for all requests in the batch. Currently `/v1/chat/completions`, `/v1/embeddings`, and `/v1/completions` are supported. Note that `/v1/embeddings` batches are also restricted to a maximum of 50,000 embedding inputs across all requests in the batch. input_file_id: The ID of an uploaded file that contains requests for the new batch. See [upload file](https://platform.openai.com/docs/api-reference/files/create) for how to upload a file. Your input file must be formatted as a [JSONL file](https://platform.openai.com/docs/api-reference/batch/request-input), and must be uploaded with the purpose `batch`. The file can contain up to 50,000 requests, and can be up to 100 MB in size. metadata: Optional custom metadata for the batch. extra_headers: Send extra headers extra_query: Add additional query parameters to the request extra_body: Add additional JSON properties to the request timeout: Override the client-level default timeout for this request, in seconds """ return await self._post( "/batches", body=await async_maybe_transform( { "completion_window": completion_window, "endpoint": endpoint, "input_file_id": input_file_id, "metadata": metadata, }, batch_create_params.BatchCreateParams, ), options=make_request_options( extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout ), cast_to=Batch, ) async def retrieve( self, batch_id: str, *, # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs. # The extra values given here take precedence over values defined on the client or passed to this method. extra_headers: Headers | None = None, extra_query: Query | None = None, extra_body: Body | None = None, timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN, ) -> Batch: """ Retrieves a batch. Args: extra_headers: Send extra headers extra_query: Add additional query parameters to the request extra_body: Add additional JSON properties to the request timeout: Override the client-level default timeout for this request, in seconds """ if not batch_id: raise ValueError(f"Expected a non-empty value for `batch_id` but received {batch_id!r}") return await self._get( f"/batches/{batch_id}", options=make_request_options( extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout ), cast_to=Batch, ) def list( self, *, after: str | NotGiven = NOT_GIVEN, limit: int | NotGiven = NOT_GIVEN, # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs. # The extra values given here take precedence over values defined on the client or passed to this method. extra_headers: Headers | None = None, extra_query: Query | None = None, extra_body: Body | None = None, timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN, ) -> AsyncPaginator[Batch, AsyncCursorPage[Batch]]: """List your organization's batches. Args: after: A cursor for use in pagination. `after` is an object ID that defines your place in the list. For instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent call can include after=obj_foo in order to fetch the next page of the list. limit: A limit on the number of objects to be returned. Limit can range between 1 and 100, and the default is 20. extra_headers: Send extra headers extra_query: Add additional query parameters to the request extra_body: Add additional JSON properties to the request timeout: Override the client-level default timeout for this request, in seconds """ return self._get_api_list( "/batches", page=AsyncCursorPage[Batch], options=make_request_options( extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout, query=maybe_transform( { "after": after, "limit": limit, }, batch_list_params.BatchListParams, ), ), model=Batch, ) async def cancel( self, batch_id: str, *, # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs. # The extra values given here take precedence over values defined on the client or passed to this method. extra_headers: Headers | None = None, extra_query: Query | None = None, extra_body: Body | None = None, timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN, ) -> Batch: """Cancels an in-progress batch. The batch will be in status `cancelling` for up to 10 minutes, before changing to `cancelled`, where it will have partial results (if any) available in the output file. Args: extra_headers: Send extra headers extra_query: Add additional query parameters to the request extra_body: Add additional JSON properties to the request timeout: Override the client-level default timeout for this request, in seconds """ if not batch_id: raise ValueError(f"Expected a non-empty value for `batch_id` but received {batch_id!r}") return await self._post( f"/batches/{batch_id}/cancel", options=make_request_options( extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout ), cast_to=Batch, ) class BatchesWithRawResponse: def __init__(self, batches: Batches) -> None: self._batches = batches self.create = _legacy_response.to_raw_response_wrapper( batches.create, ) self.retrieve = _legacy_response.to_raw_response_wrapper( batches.retrieve, ) self.list = _legacy_response.to_raw_response_wrapper( batches.list, ) self.cancel = _legacy_response.to_raw_response_wrapper( batches.cancel, ) class AsyncBatchesWithRawResponse: def __init__(self, batches: AsyncBatches) -> None: self._batches = batches self.create = _legacy_response.async_to_raw_response_wrapper( batches.create, ) self.retrieve = _legacy_response.async_to_raw_response_wrapper( batches.retrieve, ) self.list = _legacy_response.async_to_raw_response_wrapper( batches.list, ) self.cancel = _legacy_response.async_to_raw_response_wrapper( batches.cancel, ) class BatchesWithStreamingResponse: def __init__(self, batches: Batches) -> None: self._batches = batches self.create = to_streamed_response_wrapper( batches.create, ) self.retrieve = to_streamed_response_wrapper( batches.retrieve, ) self.list = to_streamed_response_wrapper( batches.list, ) self.cancel = to_streamed_response_wrapper( batches.cancel, ) class AsyncBatchesWithStreamingResponse: def __init__(self, batches: AsyncBatches) -> None: self._batches = batches self.create = async_to_streamed_response_wrapper( batches.create, ) self.retrieve = async_to_streamed_response_wrapper( batches.retrieve, ) self.list = async_to_streamed_response_wrapper( batches.list, ) self.cancel = async_to_streamed_response_wrapper( batches.cancel, )