two version of R2R are here HEAD master

5 files changed, 1128 insertions, 0 deletions

diff --git a/.venv/lib/python3.12/site-packages/openai/resources/fine_tuning/__init__.py b/.venv/lib/python3.12/site-packages/openai/resources/fine_tuning/__init__.py
new file mode 100644
index 00000000..7765231f
--- /dev/null
+++ b/.venv/lib/python3.12/site-packages/openai/resources/fine_tuning/__init__.py
@@ -0,0 +1,33 @@
+# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
+
+from .jobs import (
+    Jobs,
+    AsyncJobs,
+    JobsWithRawResponse,
+    AsyncJobsWithRawResponse,
+    JobsWithStreamingResponse,
+    AsyncJobsWithStreamingResponse,
+)
+from .fine_tuning import (
+    FineTuning,
+    AsyncFineTuning,
+    FineTuningWithRawResponse,
+    AsyncFineTuningWithRawResponse,
+    FineTuningWithStreamingResponse,
+    AsyncFineTuningWithStreamingResponse,
+)
+
+__all__ = [
+    "Jobs",
+    "AsyncJobs",
+    "JobsWithRawResponse",
+    "AsyncJobsWithRawResponse",
+    "JobsWithStreamingResponse",
+    "AsyncJobsWithStreamingResponse",
+    "FineTuning",
+    "AsyncFineTuning",
+    "FineTuningWithRawResponse",
+    "AsyncFineTuningWithRawResponse",
+    "FineTuningWithStreamingResponse",
+    "AsyncFineTuningWithStreamingResponse",
+]
diff --git a/.venv/lib/python3.12/site-packages/openai/resources/fine_tuning/fine_tuning.py b/.venv/lib/python3.12/site-packages/openai/resources/fine_tuning/fine_tuning.py
new file mode 100644
index 00000000..eebde07d
--- /dev/null
+++ b/.venv/lib/python3.12/site-packages/openai/resources/fine_tuning/fine_tuning.py
@@ -0,0 +1,102 @@
+# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
+
+from __future__ import annotations
+
+from ..._compat import cached_property
+from .jobs.jobs import (
+    Jobs,
+    AsyncJobs,
+    JobsWithRawResponse,
+    AsyncJobsWithRawResponse,
+    JobsWithStreamingResponse,
+    AsyncJobsWithStreamingResponse,
+)
+from ..._resource import SyncAPIResource, AsyncAPIResource
+
+__all__ = ["FineTuning", "AsyncFineTuning"]
+
+
+class FineTuning(SyncAPIResource):
+    @cached_property
+    def jobs(self) -> Jobs:
+        return Jobs(self._client)
+
+    @cached_property
+    def with_raw_response(self) -> FineTuningWithRawResponse:
+        """
+        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 FineTuningWithRawResponse(self)
+
+    @cached_property
+    def with_streaming_response(self) -> FineTuningWithStreamingResponse:
+        """
+        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 FineTuningWithStreamingResponse(self)
+
+
+class AsyncFineTuning(AsyncAPIResource):
+    @cached_property
+    def jobs(self) -> AsyncJobs:
+        return AsyncJobs(self._client)
+
+    @cached_property
+    def with_raw_response(self) -> AsyncFineTuningWithRawResponse:
+        """
+        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 AsyncFineTuningWithRawResponse(self)
+
+    @cached_property
+    def with_streaming_response(self) -> AsyncFineTuningWithStreamingResponse:
+        """
+        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 AsyncFineTuningWithStreamingResponse(self)
+
+
+class FineTuningWithRawResponse:
+    def __init__(self, fine_tuning: FineTuning) -> None:
+        self._fine_tuning = fine_tuning
+
+    @cached_property
+    def jobs(self) -> JobsWithRawResponse:
+        return JobsWithRawResponse(self._fine_tuning.jobs)
+
+
+class AsyncFineTuningWithRawResponse:
+    def __init__(self, fine_tuning: AsyncFineTuning) -> None:
+        self._fine_tuning = fine_tuning
+
+    @cached_property
+    def jobs(self) -> AsyncJobsWithRawResponse:
+        return AsyncJobsWithRawResponse(self._fine_tuning.jobs)
+
+
+class FineTuningWithStreamingResponse:
+    def __init__(self, fine_tuning: FineTuning) -> None:
+        self._fine_tuning = fine_tuning
+
+    @cached_property
+    def jobs(self) -> JobsWithStreamingResponse:
+        return JobsWithStreamingResponse(self._fine_tuning.jobs)
+
+
+class AsyncFineTuningWithStreamingResponse:
+    def __init__(self, fine_tuning: AsyncFineTuning) -> None:
+        self._fine_tuning = fine_tuning
+
+    @cached_property
+    def jobs(self) -> AsyncJobsWithStreamingResponse:
+        return AsyncJobsWithStreamingResponse(self._fine_tuning.jobs)
diff --git a/.venv/lib/python3.12/site-packages/openai/resources/fine_tuning/jobs/__init__.py b/.venv/lib/python3.12/site-packages/openai/resources/fine_tuning/jobs/__init__.py
new file mode 100644
index 00000000..94cd1fb7
--- /dev/null
+++ b/.venv/lib/python3.12/site-packages/openai/resources/fine_tuning/jobs/__init__.py
@@ -0,0 +1,33 @@
+# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
+
+from .jobs import (
+    Jobs,
+    AsyncJobs,
+    JobsWithRawResponse,
+    AsyncJobsWithRawResponse,
+    JobsWithStreamingResponse,
+    AsyncJobsWithStreamingResponse,
+)
+from .checkpoints import (
+    Checkpoints,
+    AsyncCheckpoints,
+    CheckpointsWithRawResponse,
+    AsyncCheckpointsWithRawResponse,
+    CheckpointsWithStreamingResponse,
+    AsyncCheckpointsWithStreamingResponse,
+)
+
+__all__ = [
+    "Checkpoints",
+    "AsyncCheckpoints",
+    "CheckpointsWithRawResponse",
+    "AsyncCheckpointsWithRawResponse",
+    "CheckpointsWithStreamingResponse",
+    "AsyncCheckpointsWithStreamingResponse",
+    "Jobs",
+    "AsyncJobs",
+    "JobsWithRawResponse",
+    "AsyncJobsWithRawResponse",
+    "JobsWithStreamingResponse",
+    "AsyncJobsWithStreamingResponse",
+]
diff --git a/.venv/lib/python3.12/site-packages/openai/resources/fine_tuning/jobs/checkpoints.py b/.venv/lib/python3.12/site-packages/openai/resources/fine_tuning/jobs/checkpoints.py
new file mode 100644
index 00000000..f86462e5
--- /dev/null
+++ b/.venv/lib/python3.12/site-packages/openai/resources/fine_tuning/jobs/checkpoints.py
@@ -0,0 +1,199 @@
+# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
+
+from __future__ import annotations
+
+import httpx
+
+from .... import _legacy_response
+from ...._types import NOT_GIVEN, Body, Query, Headers, NotGiven
+from ...._utils import 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.jobs import checkpoint_list_params
+from ....types.fine_tuning.jobs.fine_tuning_job_checkpoint import FineTuningJobCheckpoint
+
+__all__ = ["Checkpoints", "AsyncCheckpoints"]
+
+
+class Checkpoints(SyncAPIResource):
+    @cached_property
+    def with_raw_response(self) -> CheckpointsWithRawResponse:
+        """
+        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 CheckpointsWithRawResponse(self)
+
+    @cached_property
+    def with_streaming_response(self) -> CheckpointsWithStreamingResponse:
+        """
+        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 CheckpointsWithStreamingResponse(self)
+
+    def list(
+        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[FineTuningJobCheckpoint]:
+        """
+        List checkpoints for a fine-tuning job.
+
+        Args:
+          after: Identifier for the last checkpoint ID from the previous pagination request.
+
+          limit: Number of checkpoints 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}/checkpoints",
+            page=SyncCursorPage[FineTuningJobCheckpoint],
+            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,
+                    },
+                    checkpoint_list_params.CheckpointListParams,
+                ),
+            ),
+            model=FineTuningJobCheckpoint,
+        )
+
+
+class AsyncCheckpoints(AsyncAPIResource):
+    @cached_property
+    def with_raw_response(self) -> AsyncCheckpointsWithRawResponse:
+        """
+        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 AsyncCheckpointsWithRawResponse(self)
+
+    @cached_property
+    def with_streaming_response(self) -> AsyncCheckpointsWithStreamingResponse:
+        """
+        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 AsyncCheckpointsWithStreamingResponse(self)
+
+    def list(
+        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[FineTuningJobCheckpoint, AsyncCursorPage[FineTuningJobCheckpoint]]:
+        """
+        List checkpoints for a fine-tuning job.
+
+        Args:
+          after: Identifier for the last checkpoint ID from the previous pagination request.
+
+          limit: Number of checkpoints 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}/checkpoints",
+            page=AsyncCursorPage[FineTuningJobCheckpoint],
+            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,
+                    },
+                    checkpoint_list_params.CheckpointListParams,
+                ),
+            ),
+            model=FineTuningJobCheckpoint,
+        )
+
+
+class CheckpointsWithRawResponse:
+    def __init__(self, checkpoints: Checkpoints) -> None:
+        self._checkpoints = checkpoints
+
+        self.list = _legacy_response.to_raw_response_wrapper(
+            checkpoints.list,
+        )
+
+
+class AsyncCheckpointsWithRawResponse:
+    def __init__(self, checkpoints: AsyncCheckpoints) -> None:
+        self._checkpoints = checkpoints
+
+        self.list = _legacy_response.async_to_raw_response_wrapper(
+            checkpoints.list,
+        )
+
+
+class CheckpointsWithStreamingResponse:
+    def __init__(self, checkpoints: Checkpoints) -> None:
+        self._checkpoints = checkpoints
+
+        self.list = to_streamed_response_wrapper(
+            checkpoints.list,
+        )
+
+
+class AsyncCheckpointsWithStreamingResponse:
+    def __init__(self, checkpoints: AsyncCheckpoints) -> None:
+        self._checkpoints = checkpoints
+
+        self.list = async_to_streamed_response_wrapper(
+            checkpoints.list,
+        )
diff --git a/.venv/lib/python3.12/site-packages/openai/resources/fine_tuning/jobs/jobs.py b/.venv/lib/python3.12/site-packages/openai/resources/fine_tuning/jobs/jobs.py
new file mode 100644
index 00000000..bbeff60b
--- /dev/null
+++ b/.venv/lib/python3.12/site-packages/openai/resources/fine_tuning/jobs/jobs.py
@@ -0,0 +1,761 @@
+# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
+
+from __future__ import annotations
+
+from typing import Dict, Union, Iterable, 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 .checkpoints import (
+    Checkpoints,
+    AsyncCheckpoints,
+    CheckpointsWithRawResponse,
+    AsyncCheckpointsWithRawResponse,
+    CheckpointsWithStreamingResponse,
+    AsyncCheckpointsWithStreamingResponse,
+)
+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 job_list_params, job_create_params, job_list_events_params
+from ....types.shared_params.metadata import Metadata
+from ....types.fine_tuning.fine_tuning_job import FineTuningJob
+from ....types.fine_tuning.fine_tuning_job_event import FineTuningJobEvent
+
+__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,
+        *,
+        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)