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batches.py
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batches.py
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# 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,
)