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# File generated from our OpenAPI spec by Stainless.

from __future__ import annotations

from typing import Union, Optional
from typing_extensions import Literal

import httpx

from ... import _legacy_response
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 ..._base_client import (
    AsyncPaginator,
    make_request_options,
)
from ...types.fine_tuning import (
    FineTuningJob,
    FineTuningJobEvent,
    job_list_params,
    job_create_params,
    job_list_events_params,
)

__all__ = ["Jobs", "AsyncJobs"]

class Jobs(SyncAPIResource):
    @cached_property
    def with_raw_response(self) -> JobsWithRawResponse:
        return JobsWithRawResponse(self)

@cached_property
    def with_streaming_response(self) -> JobsWithStreamingResponse:
        return JobsWithStreamingResponse(self)

def create(
        self,
        *,
        model: Union[str, Literal["babbage-002", "davinci-002", "gpt-3.5-turbo"]],
        training_file: str,
        hyperparameters: job_create_params.Hyperparameters | 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/what-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/upload)
              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`.

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.

suffix: A string of up to 18 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-3.5-turbo: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,
                    "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

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[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.

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,
                    },
                    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

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 with_raw_response(self) -> AsyncJobsWithRawResponse:
        return AsyncJobsWithRawResponse(self)

@cached_property
    def with_streaming_response(self) -> AsyncJobsWithStreamingResponse:
        return AsyncJobsWithStreamingResponse(self)

async def create(
        self,
        *,
        model: Union[str, Literal["babbage-002", "davinci-002", "gpt-3.5-turbo"]],
        training_file: str,
        hyperparameters: job_create_params.Hyperparameters | 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.