chore: automatic commit 2025-04-30 12:48
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# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
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from .jobs import (
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Jobs,
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AsyncJobs,
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JobsWithRawResponse,
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AsyncJobsWithRawResponse,
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JobsWithStreamingResponse,
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AsyncJobsWithStreamingResponse,
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)
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from .checkpoints import (
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Checkpoints,
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AsyncCheckpoints,
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CheckpointsWithRawResponse,
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AsyncCheckpointsWithRawResponse,
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CheckpointsWithStreamingResponse,
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AsyncCheckpointsWithStreamingResponse,
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)
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__all__ = [
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"Checkpoints",
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"AsyncCheckpoints",
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"CheckpointsWithRawResponse",
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"AsyncCheckpointsWithRawResponse",
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"CheckpointsWithStreamingResponse",
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"AsyncCheckpointsWithStreamingResponse",
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"Jobs",
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"AsyncJobs",
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"JobsWithRawResponse",
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"AsyncJobsWithRawResponse",
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"JobsWithStreamingResponse",
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"AsyncJobsWithStreamingResponse",
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]
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# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
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from __future__ import annotations
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import httpx
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from .... import _legacy_response
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from ...._types import NOT_GIVEN, Body, Query, Headers, NotGiven
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from ...._utils import maybe_transform
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from ...._compat import cached_property
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from ...._resource import SyncAPIResource, AsyncAPIResource
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from ...._response import to_streamed_response_wrapper, async_to_streamed_response_wrapper
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from ....pagination import SyncCursorPage, AsyncCursorPage
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from ...._base_client import (
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AsyncPaginator,
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make_request_options,
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)
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from ....types.fine_tuning.jobs import checkpoint_list_params
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from ....types.fine_tuning.jobs.fine_tuning_job_checkpoint import FineTuningJobCheckpoint
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__all__ = ["Checkpoints", "AsyncCheckpoints"]
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class Checkpoints(SyncAPIResource):
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@cached_property
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def with_raw_response(self) -> CheckpointsWithRawResponse:
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"""
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This property can be used as a prefix for any HTTP method call to return
|
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the raw response object instead of the parsed content.
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|
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For more information, see https://www.github.com/openai/openai-python#accessing-raw-response-data-eg-headers
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"""
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return CheckpointsWithRawResponse(self)
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@cached_property
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def with_streaming_response(self) -> CheckpointsWithStreamingResponse:
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"""
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An alternative to `.with_raw_response` that doesn't eagerly read the response body.
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|
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For more information, see https://www.github.com/openai/openai-python#with_streaming_response
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"""
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return CheckpointsWithStreamingResponse(self)
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def list(
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self,
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fine_tuning_job_id: str,
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*,
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after: str | NotGiven = NOT_GIVEN,
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limit: int | NotGiven = NOT_GIVEN,
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# 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,
|
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extra_query: Query | None = None,
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extra_body: Body | None = None,
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||||
timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
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||||
) -> SyncCursorPage[FineTuningJobCheckpoint]:
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"""
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List checkpoints for a fine-tuning job.
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Args:
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after: Identifier for the last checkpoint ID from the previous pagination request.
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|
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limit: Number of checkpoints to retrieve.
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|
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extra_headers: Send extra headers
|
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|
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extra_query: Add additional query parameters to the request
|
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|
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extra_body: Add additional JSON properties to the request
|
||||
|
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timeout: Override the client-level default timeout for this request, in seconds
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"""
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if not fine_tuning_job_id:
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raise ValueError(f"Expected a non-empty value for `fine_tuning_job_id` but received {fine_tuning_job_id!r}")
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return self._get_api_list(
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f"/fine_tuning/jobs/{fine_tuning_job_id}/checkpoints",
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page=SyncCursorPage[FineTuningJobCheckpoint],
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options=make_request_options(
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extra_headers=extra_headers,
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extra_query=extra_query,
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extra_body=extra_body,
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timeout=timeout,
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query=maybe_transform(
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{
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"after": after,
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"limit": limit,
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},
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checkpoint_list_params.CheckpointListParams,
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),
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),
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model=FineTuningJobCheckpoint,
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)
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class AsyncCheckpoints(AsyncAPIResource):
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@cached_property
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def with_raw_response(self) -> AsyncCheckpointsWithRawResponse:
|
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"""
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||||
This property can be used as a prefix for any HTTP method call to return
|
||||
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
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"""
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return AsyncCheckpointsWithRawResponse(self)
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@cached_property
|
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def with_streaming_response(self) -> AsyncCheckpointsWithStreamingResponse:
|
||||
"""
|
||||
An alternative to `.with_raw_response` that doesn't eagerly read the response body.
|
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|
||||
For more information, see https://www.github.com/openai/openai-python#with_streaming_response
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"""
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return AsyncCheckpointsWithStreamingResponse(self)
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|
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def list(
|
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self,
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fine_tuning_job_id: str,
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*,
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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,
|
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extra_query: Query | None = None,
|
||||
extra_body: Body | None = None,
|
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timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
|
||||
) -> AsyncPaginator[FineTuningJobCheckpoint, AsyncCursorPage[FineTuningJobCheckpoint]]:
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"""
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List checkpoints for a fine-tuning job.
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|
||||
Args:
|
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after: Identifier for the last checkpoint ID from the previous pagination request.
|
||||
|
||||
limit: Number of checkpoints to retrieve.
|
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|
||||
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
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||||
"""
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if not fine_tuning_job_id:
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raise ValueError(f"Expected a non-empty value for `fine_tuning_job_id` but received {fine_tuning_job_id!r}")
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return self._get_api_list(
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f"/fine_tuning/jobs/{fine_tuning_job_id}/checkpoints",
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page=AsyncCursorPage[FineTuningJobCheckpoint],
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options=make_request_options(
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extra_headers=extra_headers,
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extra_query=extra_query,
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extra_body=extra_body,
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timeout=timeout,
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query=maybe_transform(
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{
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"after": after,
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"limit": limit,
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||||
},
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checkpoint_list_params.CheckpointListParams,
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||||
),
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),
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model=FineTuningJobCheckpoint,
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)
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||||
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class CheckpointsWithRawResponse:
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def __init__(self, checkpoints: Checkpoints) -> None:
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self._checkpoints = checkpoints
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self.list = _legacy_response.to_raw_response_wrapper(
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checkpoints.list,
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)
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class AsyncCheckpointsWithRawResponse:
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def __init__(self, checkpoints: AsyncCheckpoints) -> None:
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self._checkpoints = checkpoints
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self.list = _legacy_response.async_to_raw_response_wrapper(
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checkpoints.list,
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)
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class CheckpointsWithStreamingResponse:
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||||
def __init__(self, checkpoints: Checkpoints) -> None:
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self._checkpoints = checkpoints
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self.list = to_streamed_response_wrapper(
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checkpoints.list,
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)
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class AsyncCheckpointsWithStreamingResponse:
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def __init__(self, checkpoints: AsyncCheckpoints) -> None:
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self._checkpoints = checkpoints
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self.list = async_to_streamed_response_wrapper(
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checkpoints.list,
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)
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@@ -0,0 +1,758 @@
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# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
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from __future__ import annotations
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||||
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from typing import Dict, Union, Iterable, Optional
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from typing_extensions import Literal
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import httpx
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from .... import _legacy_response
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from ...._types import NOT_GIVEN, Body, Query, Headers, NotGiven
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from ...._utils import maybe_transform, async_maybe_transform
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from ...._compat import cached_property
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||||
from .checkpoints import (
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Checkpoints,
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||||
AsyncCheckpoints,
|
||||
CheckpointsWithRawResponse,
|
||||
AsyncCheckpointsWithRawResponse,
|
||||
CheckpointsWithStreamingResponse,
|
||||
AsyncCheckpointsWithStreamingResponse,
|
||||
)
|
||||
from ...._resource import SyncAPIResource, AsyncAPIResource
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||||
from ...._response import to_streamed_response_wrapper, async_to_streamed_response_wrapper
|
||||
from ....pagination import SyncCursorPage, AsyncCursorPage
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||||
from ...._base_client import (
|
||||
AsyncPaginator,
|
||||
make_request_options,
|
||||
)
|
||||
from ....types.fine_tuning import job_list_params, job_create_params, job_list_events_params
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||||
from ....types.shared_params.metadata import Metadata
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||||
from ....types.fine_tuning.fine_tuning_job import FineTuningJob
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||||
from ....types.fine_tuning.fine_tuning_job_event import FineTuningJobEvent
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||||
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||||
__all__ = ["Jobs", "AsyncJobs"]
|
||||
|
||||
|
||||
class Jobs(SyncAPIResource):
|
||||
@cached_property
|
||||
def checkpoints(self) -> Checkpoints:
|
||||
return Checkpoints(self._client)
|
||||
|
||||
@cached_property
|
||||
def with_raw_response(self) -> JobsWithRawResponse:
|
||||
"""
|
||||
This property can be used as a prefix for any HTTP method call to return
|
||||
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 JobsWithRawResponse(self)
|
||||
|
||||
@cached_property
|
||||
def with_streaming_response(self) -> JobsWithStreamingResponse:
|
||||
"""
|
||||
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 JobsWithStreamingResponse(self)
|
||||
|
||||
def create(
|
||||
self,
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||||
*,
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||||
model: Union[str, Literal["babbage-002", "davinci-002", "gpt-3.5-turbo", "gpt-4o-mini"]],
|
||||
training_file: str,
|
||||
hyperparameters: job_create_params.Hyperparameters | NotGiven = NOT_GIVEN,
|
||||
integrations: Optional[Iterable[job_create_params.Integration]] | NotGiven = NOT_GIVEN,
|
||||
metadata: Optional[Metadata] | NotGiven = NOT_GIVEN,
|
||||
method: job_create_params.Method | NotGiven = NOT_GIVEN,
|
||||
seed: Optional[int] | NotGiven = NOT_GIVEN,
|
||||
suffix: Optional[str] | NotGiven = NOT_GIVEN,
|
||||
validation_file: Optional[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,
|
||||
) -> FineTuningJob:
|
||||
"""
|
||||
Creates a fine-tuning job which begins the process of creating a new model from
|
||||
a given dataset.
|
||||
|
||||
Response includes details of the enqueued job including job status and the name
|
||||
of the fine-tuned models once complete.
|
||||
|
||||
[Learn more about fine-tuning](https://platform.openai.com/docs/guides/fine-tuning)
|
||||
|
||||
Args:
|
||||
model: The name of the model to fine-tune. You can select one of the
|
||||
[supported models](https://platform.openai.com/docs/guides/fine-tuning#which-models-can-be-fine-tuned).
|
||||
|
||||
training_file: The ID of an uploaded file that contains training data.
|
||||
|
||||
See [upload file](https://platform.openai.com/docs/api-reference/files/create)
|
||||
for how to upload a file.
|
||||
|
||||
Your dataset must be formatted as a JSONL file. Additionally, you must upload
|
||||
your file with the purpose `fine-tune`.
|
||||
|
||||
The contents of the file should differ depending on if the model uses the
|
||||
[chat](https://platform.openai.com/docs/api-reference/fine-tuning/chat-input),
|
||||
[completions](https://platform.openai.com/docs/api-reference/fine-tuning/completions-input)
|
||||
format, or if the fine-tuning method uses the
|
||||
[preference](https://platform.openai.com/docs/api-reference/fine-tuning/preference-input)
|
||||
format.
|
||||
|
||||
See the [fine-tuning guide](https://platform.openai.com/docs/guides/fine-tuning)
|
||||
for more details.
|
||||
|
||||
hyperparameters: The hyperparameters used for the fine-tuning job. This value is now deprecated
|
||||
in favor of `method`, and should be passed in under the `method` parameter.
|
||||
|
||||
integrations: A list of integrations to enable for your fine-tuning job.
|
||||
|
||||
metadata: Set of 16 key-value pairs that can be attached to an object. This can be useful
|
||||
for storing additional information about the object in a structured format, and
|
||||
querying for objects via API or the dashboard.
|
||||
|
||||
Keys are strings with a maximum length of 64 characters. Values are strings with
|
||||
a maximum length of 512 characters.
|
||||
|
||||
method: The method used for fine-tuning.
|
||||
|
||||
seed: The seed controls the reproducibility of the job. Passing in the same seed and
|
||||
job parameters should produce the same results, but may differ in rare cases. If
|
||||
a seed is not specified, one will be generated for you.
|
||||
|
||||
suffix: A string of up to 64 characters that will be added to your fine-tuned model
|
||||
name.
|
||||
|
||||
For example, a `suffix` of "custom-model-name" would produce a model name like
|
||||
`ft:gpt-4o-mini:openai:custom-model-name:7p4lURel`.
|
||||
|
||||
validation_file: The ID of an uploaded file that contains validation data.
|
||||
|
||||
If you provide this file, the data is used to generate validation metrics
|
||||
periodically during fine-tuning. These metrics can be viewed in the fine-tuning
|
||||
results file. The same data should not be present in both train and validation
|
||||
files.
|
||||
|
||||
Your dataset must be formatted as a JSONL file. You must upload your file with
|
||||
the purpose `fine-tune`.
|
||||
|
||||
See the [fine-tuning guide](https://platform.openai.com/docs/guides/fine-tuning)
|
||||
for more details.
|
||||
|
||||
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(
|
||||
"/fine_tuning/jobs",
|
||||
body=maybe_transform(
|
||||
{
|
||||
"model": model,
|
||||
"training_file": training_file,
|
||||
"hyperparameters": hyperparameters,
|
||||
"integrations": integrations,
|
||||
"metadata": metadata,
|
||||
"method": method,
|
||||
"seed": seed,
|
||||
"suffix": suffix,
|
||||
"validation_file": validation_file,
|
||||
},
|
||||
job_create_params.JobCreateParams,
|
||||
),
|
||||
options=make_request_options(
|
||||
extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
|
||||
),
|
||||
cast_to=FineTuningJob,
|
||||
)
|
||||
|
||||
def retrieve(
|
||||
self,
|
||||
fine_tuning_job_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,
|
||||
) -> FineTuningJob:
|
||||
"""
|
||||
Get info about a fine-tuning job.
|
||||
|
||||
[Learn more about fine-tuning](https://platform.openai.com/docs/guides/fine-tuning)
|
||||
|
||||
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 fine_tuning_job_id:
|
||||
raise ValueError(f"Expected a non-empty value for `fine_tuning_job_id` but received {fine_tuning_job_id!r}")
|
||||
return self._get(
|
||||
f"/fine_tuning/jobs/{fine_tuning_job_id}",
|
||||
options=make_request_options(
|
||||
extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
|
||||
),
|
||||
cast_to=FineTuningJob,
|
||||
)
|
||||
|
||||
def list(
|
||||
self,
|
||||
*,
|
||||
after: str | NotGiven = NOT_GIVEN,
|
||||
limit: int | NotGiven = NOT_GIVEN,
|
||||
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,
|
||||
) -> SyncCursorPage[FineTuningJob]:
|
||||
"""
|
||||
List your organization's fine-tuning jobs
|
||||
|
||||
Args:
|
||||
after: Identifier for the last job from the previous pagination request.
|
||||
|
||||
limit: Number of fine-tuning jobs to retrieve.
|
||||
|
||||
metadata: Optional metadata filter. To filter, use the syntax `metadata[k]=v`.
|
||||
Alternatively, set `metadata=null` to indicate no metadata.
|
||||
|
||||
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(
|
||||
"/fine_tuning/jobs",
|
||||
page=SyncCursorPage[FineTuningJob],
|
||||
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,
|
||||
"metadata": metadata,
|
||||
},
|
||||
job_list_params.JobListParams,
|
||||
),
|
||||
),
|
||||
model=FineTuningJob,
|
||||
)
|
||||
|
||||
def cancel(
|
||||
self,
|
||||
fine_tuning_job_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,
|
||||
) -> FineTuningJob:
|
||||
"""
|
||||
Immediately cancel a fine-tune job.
|
||||
|
||||
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 fine_tuning_job_id:
|
||||
raise ValueError(f"Expected a non-empty value for `fine_tuning_job_id` but received {fine_tuning_job_id!r}")
|
||||
return self._post(
|
||||
f"/fine_tuning/jobs/{fine_tuning_job_id}/cancel",
|
||||
options=make_request_options(
|
||||
extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
|
||||
),
|
||||
cast_to=FineTuningJob,
|
||||
)
|
||||
|
||||
def list_events(
|
||||
self,
|
||||
fine_tuning_job_id: str,
|
||||
*,
|
||||
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[FineTuningJobEvent]:
|
||||
"""
|
||||
Get status updates for a fine-tuning job.
|
||||
|
||||
Args:
|
||||
after: Identifier for the last event from the previous pagination request.
|
||||
|
||||
limit: Number of events to retrieve.
|
||||
|
||||
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 fine_tuning_job_id:
|
||||
raise ValueError(f"Expected a non-empty value for `fine_tuning_job_id` but received {fine_tuning_job_id!r}")
|
||||
return self._get_api_list(
|
||||
f"/fine_tuning/jobs/{fine_tuning_job_id}/events",
|
||||
page=SyncCursorPage[FineTuningJobEvent],
|
||||
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,
|
||||
},
|
||||
job_list_events_params.JobListEventsParams,
|
||||
),
|
||||
),
|
||||
model=FineTuningJobEvent,
|
||||
)
|
||||
|
||||
|
||||
class AsyncJobs(AsyncAPIResource):
|
||||
@cached_property
|
||||
def checkpoints(self) -> AsyncCheckpoints:
|
||||
return AsyncCheckpoints(self._client)
|
||||
|
||||
@cached_property
|
||||
def with_raw_response(self) -> AsyncJobsWithRawResponse:
|
||||
"""
|
||||
This property can be used as a prefix for any HTTP method call to return
|
||||
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 AsyncJobsWithRawResponse(self)
|
||||
|
||||
@cached_property
|
||||
def with_streaming_response(self) -> AsyncJobsWithStreamingResponse:
|
||||
"""
|
||||
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 AsyncJobsWithStreamingResponse(self)
|
||||
|
||||
async def create(
|
||||
self,
|
||||
*,
|
||||
model: Union[str, Literal["babbage-002", "davinci-002", "gpt-3.5-turbo", "gpt-4o-mini"]],
|
||||
training_file: str,
|
||||
hyperparameters: job_create_params.Hyperparameters | NotGiven = NOT_GIVEN,
|
||||
integrations: Optional[Iterable[job_create_params.Integration]] | NotGiven = NOT_GIVEN,
|
||||
metadata: Optional[Metadata] | NotGiven = NOT_GIVEN,
|
||||
method: job_create_params.Method | NotGiven = NOT_GIVEN,
|
||||
seed: Optional[int] | NotGiven = NOT_GIVEN,
|
||||
suffix: Optional[str] | NotGiven = NOT_GIVEN,
|
||||
validation_file: Optional[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,
|
||||
) -> FineTuningJob:
|
||||
"""
|
||||
Creates a fine-tuning job which begins the process of creating a new model from
|
||||
a given dataset.
|
||||
|
||||
Response includes details of the enqueued job including job status and the name
|
||||
of the fine-tuned models once complete.
|
||||
|
||||
[Learn more about fine-tuning](https://platform.openai.com/docs/guides/fine-tuning)
|
||||
|
||||
Args:
|
||||
model: The name of the model to fine-tune. You can select one of the
|
||||
[supported models](https://platform.openai.com/docs/guides/fine-tuning#which-models-can-be-fine-tuned).
|
||||
|
||||
training_file: The ID of an uploaded file that contains training data.
|
||||
|
||||
See [upload file](https://platform.openai.com/docs/api-reference/files/create)
|
||||
for how to upload a file.
|
||||
|
||||
Your dataset must be formatted as a JSONL file. Additionally, you must upload
|
||||
your file with the purpose `fine-tune`.
|
||||
|
||||
The contents of the file should differ depending on if the model uses the
|
||||
[chat](https://platform.openai.com/docs/api-reference/fine-tuning/chat-input),
|
||||
[completions](https://platform.openai.com/docs/api-reference/fine-tuning/completions-input)
|
||||
format, or if the fine-tuning method uses the
|
||||
[preference](https://platform.openai.com/docs/api-reference/fine-tuning/preference-input)
|
||||
format.
|
||||
|
||||
See the [fine-tuning guide](https://platform.openai.com/docs/guides/fine-tuning)
|
||||
for more details.
|
||||
|
||||
hyperparameters: The hyperparameters used for the fine-tuning job. This value is now deprecated
|
||||
in favor of `method`, and should be passed in under the `method` parameter.
|
||||
|
||||
integrations: A list of integrations to enable for your fine-tuning job.
|
||||
|
||||
metadata: Set of 16 key-value pairs that can be attached to an object. This can be useful
|
||||
for storing additional information about the object in a structured format, and
|
||||
querying for objects via API or the dashboard.
|
||||
|
||||
Keys are strings with a maximum length of 64 characters. Values are strings with
|
||||
a maximum length of 512 characters.
|
||||
|
||||
method: The method used for fine-tuning.
|
||||
|
||||
seed: The seed controls the reproducibility of the job. Passing in the same seed and
|
||||
job parameters should produce the same results, but may differ in rare cases. If
|
||||
a seed is not specified, one will be generated for you.
|
||||
|
||||
suffix: A string of up to 64 characters that will be added to your fine-tuned model
|
||||
name.
|
||||
|
||||
For example, a `suffix` of "custom-model-name" would produce a model name like
|
||||
`ft:gpt-4o-mini:openai:custom-model-name:7p4lURel`.
|
||||
|
||||
validation_file: The ID of an uploaded file that contains validation data.
|
||||
|
||||
If you provide this file, the data is used to generate validation metrics
|
||||
periodically during fine-tuning. These metrics can be viewed in the fine-tuning
|
||||
results file. The same data should not be present in both train and validation
|
||||
files.
|
||||
|
||||
Your dataset must be formatted as a JSONL file. You must upload your file with
|
||||
the purpose `fine-tune`.
|
||||
|
||||
See the [fine-tuning guide](https://platform.openai.com/docs/guides/fine-tuning)
|
||||
for more details.
|
||||
|
||||
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(
|
||||
"/fine_tuning/jobs",
|
||||
body=await async_maybe_transform(
|
||||
{
|
||||
"model": model,
|
||||
"training_file": training_file,
|
||||
"hyperparameters": hyperparameters,
|
||||
"integrations": integrations,
|
||||
"metadata": metadata,
|
||||
"method": method,
|
||||
"seed": seed,
|
||||
"suffix": suffix,
|
||||
"validation_file": validation_file,
|
||||
},
|
||||
job_create_params.JobCreateParams,
|
||||
),
|
||||
options=make_request_options(
|
||||
extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
|
||||
),
|
||||
cast_to=FineTuningJob,
|
||||
)
|
||||
|
||||
async def retrieve(
|
||||
self,
|
||||
fine_tuning_job_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,
|
||||
) -> FineTuningJob:
|
||||
"""
|
||||
Get info about a fine-tuning job.
|
||||
|
||||
[Learn more about fine-tuning](https://platform.openai.com/docs/guides/fine-tuning)
|
||||
|
||||
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 fine_tuning_job_id:
|
||||
raise ValueError(f"Expected a non-empty value for `fine_tuning_job_id` but received {fine_tuning_job_id!r}")
|
||||
return await self._get(
|
||||
f"/fine_tuning/jobs/{fine_tuning_job_id}",
|
||||
options=make_request_options(
|
||||
extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
|
||||
),
|
||||
cast_to=FineTuningJob,
|
||||
)
|
||||
|
||||
def list(
|
||||
self,
|
||||
*,
|
||||
after: str | NotGiven = NOT_GIVEN,
|
||||
limit: int | NotGiven = NOT_GIVEN,
|
||||
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,
|
||||
) -> AsyncPaginator[FineTuningJob, AsyncCursorPage[FineTuningJob]]:
|
||||
"""
|
||||
List your organization's fine-tuning jobs
|
||||
|
||||
Args:
|
||||
after: Identifier for the last job from the previous pagination request.
|
||||
|
||||
limit: Number of fine-tuning jobs to retrieve.
|
||||
|
||||
metadata: Optional metadata filter. To filter, use the syntax `metadata[k]=v`.
|
||||
Alternatively, set `metadata=null` to indicate no metadata.
|
||||
|
||||
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(
|
||||
"/fine_tuning/jobs",
|
||||
page=AsyncCursorPage[FineTuningJob],
|
||||
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,
|
||||
"metadata": metadata,
|
||||
},
|
||||
job_list_params.JobListParams,
|
||||
),
|
||||
),
|
||||
model=FineTuningJob,
|
||||
)
|
||||
|
||||
async def cancel(
|
||||
self,
|
||||
fine_tuning_job_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,
|
||||
) -> FineTuningJob:
|
||||
"""
|
||||
Immediately cancel a fine-tune job.
|
||||
|
||||
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 fine_tuning_job_id:
|
||||
raise ValueError(f"Expected a non-empty value for `fine_tuning_job_id` but received {fine_tuning_job_id!r}")
|
||||
return await self._post(
|
||||
f"/fine_tuning/jobs/{fine_tuning_job_id}/cancel",
|
||||
options=make_request_options(
|
||||
extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
|
||||
),
|
||||
cast_to=FineTuningJob,
|
||||
)
|
||||
|
||||
def list_events(
|
||||
self,
|
||||
fine_tuning_job_id: str,
|
||||
*,
|
||||
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[FineTuningJobEvent, AsyncCursorPage[FineTuningJobEvent]]:
|
||||
"""
|
||||
Get status updates for a fine-tuning job.
|
||||
|
||||
Args:
|
||||
after: Identifier for the last event from the previous pagination request.
|
||||
|
||||
limit: Number of events to retrieve.
|
||||
|
||||
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 fine_tuning_job_id:
|
||||
raise ValueError(f"Expected a non-empty value for `fine_tuning_job_id` but received {fine_tuning_job_id!r}")
|
||||
return self._get_api_list(
|
||||
f"/fine_tuning/jobs/{fine_tuning_job_id}/events",
|
||||
page=AsyncCursorPage[FineTuningJobEvent],
|
||||
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,
|
||||
},
|
||||
job_list_events_params.JobListEventsParams,
|
||||
),
|
||||
),
|
||||
model=FineTuningJobEvent,
|
||||
)
|
||||
|
||||
|
||||
class JobsWithRawResponse:
|
||||
def __init__(self, jobs: Jobs) -> None:
|
||||
self._jobs = jobs
|
||||
|
||||
self.create = _legacy_response.to_raw_response_wrapper(
|
||||
jobs.create,
|
||||
)
|
||||
self.retrieve = _legacy_response.to_raw_response_wrapper(
|
||||
jobs.retrieve,
|
||||
)
|
||||
self.list = _legacy_response.to_raw_response_wrapper(
|
||||
jobs.list,
|
||||
)
|
||||
self.cancel = _legacy_response.to_raw_response_wrapper(
|
||||
jobs.cancel,
|
||||
)
|
||||
self.list_events = _legacy_response.to_raw_response_wrapper(
|
||||
jobs.list_events,
|
||||
)
|
||||
|
||||
@cached_property
|
||||
def checkpoints(self) -> CheckpointsWithRawResponse:
|
||||
return CheckpointsWithRawResponse(self._jobs.checkpoints)
|
||||
|
||||
|
||||
class AsyncJobsWithRawResponse:
|
||||
def __init__(self, jobs: AsyncJobs) -> None:
|
||||
self._jobs = jobs
|
||||
|
||||
self.create = _legacy_response.async_to_raw_response_wrapper(
|
||||
jobs.create,
|
||||
)
|
||||
self.retrieve = _legacy_response.async_to_raw_response_wrapper(
|
||||
jobs.retrieve,
|
||||
)
|
||||
self.list = _legacy_response.async_to_raw_response_wrapper(
|
||||
jobs.list,
|
||||
)
|
||||
self.cancel = _legacy_response.async_to_raw_response_wrapper(
|
||||
jobs.cancel,
|
||||
)
|
||||
self.list_events = _legacy_response.async_to_raw_response_wrapper(
|
||||
jobs.list_events,
|
||||
)
|
||||
|
||||
@cached_property
|
||||
def checkpoints(self) -> AsyncCheckpointsWithRawResponse:
|
||||
return AsyncCheckpointsWithRawResponse(self._jobs.checkpoints)
|
||||
|
||||
|
||||
class JobsWithStreamingResponse:
|
||||
def __init__(self, jobs: Jobs) -> None:
|
||||
self._jobs = jobs
|
||||
|
||||
self.create = to_streamed_response_wrapper(
|
||||
jobs.create,
|
||||
)
|
||||
self.retrieve = to_streamed_response_wrapper(
|
||||
jobs.retrieve,
|
||||
)
|
||||
self.list = to_streamed_response_wrapper(
|
||||
jobs.list,
|
||||
)
|
||||
self.cancel = to_streamed_response_wrapper(
|
||||
jobs.cancel,
|
||||
)
|
||||
self.list_events = to_streamed_response_wrapper(
|
||||
jobs.list_events,
|
||||
)
|
||||
|
||||
@cached_property
|
||||
def checkpoints(self) -> CheckpointsWithStreamingResponse:
|
||||
return CheckpointsWithStreamingResponse(self._jobs.checkpoints)
|
||||
|
||||
|
||||
class AsyncJobsWithStreamingResponse:
|
||||
def __init__(self, jobs: AsyncJobs) -> None:
|
||||
self._jobs = jobs
|
||||
|
||||
self.create = async_to_streamed_response_wrapper(
|
||||
jobs.create,
|
||||
)
|
||||
self.retrieve = async_to_streamed_response_wrapper(
|
||||
jobs.retrieve,
|
||||
)
|
||||
self.list = async_to_streamed_response_wrapper(
|
||||
jobs.list,
|
||||
)
|
||||
self.cancel = async_to_streamed_response_wrapper(
|
||||
jobs.cancel,
|
||||
)
|
||||
self.list_events = async_to_streamed_response_wrapper(
|
||||
jobs.list_events,
|
||||
)
|
||||
|
||||
@cached_property
|
||||
def checkpoints(self) -> AsyncCheckpointsWithStreamingResponse:
|
||||
return AsyncCheckpointsWithStreamingResponse(self._jobs.checkpoints)
|
||||
Reference in New Issue
Block a user