U Zhu@sxddlmZddlmZmZmZmZddlmZddl Z ddl m Z ddl m Z mZmZmZmZddlmZmZdd lmZd d lmZmZmZmZmZmZdd lmZm Z dd l!m"Z"m#Z#ddl$m%Z%m&Z&ddl'm(Z(m)Z)ddl*m+Z+m,Z,m-Z-ddl.m/Z/ddl0m1Z1ddl2m3Z3ddgZ4GdddeZ5Gddde Z6GdddZ7GdddZ8GdddZ9GdddZ:dS) ) annotations)DictUnionIterableOptional)LiteralN)_legacy_response) NOT_GIVENBodyQueryHeadersNotGiven)maybe_transformasync_maybe_transform)cached_property) CheckpointsAsyncCheckpointsCheckpointsWithRawResponseAsyncCheckpointsWithRawResponse CheckpointsWithStreamingResponse%AsyncCheckpointsWithStreamingResponse)SyncAPIResourceAsyncAPIResource)to_streamed_response_wrapper"async_to_streamed_response_wrapper)SyncCursorPageAsyncCursorPage)AsyncPaginatormake_request_options)job_list_paramsjob_create_paramsjob_list_events_params)Metadata) FineTuningJob)FineTuningJobEventJobs AsyncJobsc@sneZdZeddddZeddddZeddd d Zeeeeeeed d d ed d ddddddddddddddddZd d d edddddddddd Z eeed d d ed!d"d#d$ddddd%d&d'd(Z d d d eddddddddd)d*Z eed d d ed+dd"d#ddddd,d-d.d/Z d d d eddddddddd0d1Z d d d eddddddddd2d3Zd S)4r'rreturncCs t|jSN)r_clientselfr/J/tmp/pip-unpacked-wheel-693nel7n/openai/resources/fine_tuning/jobs/jobs.py checkpoints&szJobs.checkpointsJobsWithRawResponsecCst|Sa This property can be used as a prefix for any HTTP method call to return the raw response object instead of the parsed content. 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[Learn more about fine-tuning](https://platform.openai.com/docs/guides/model-optimization) 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/model-optimization) 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/model-optimization) 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 /fine_tuning/jobs rQrRr9r:r;r<r=r>r?r@rArBrCbodyoptionscast_to)_postrr"JobCreateParamsr r%r.rQrRr9r:r;r<r=r>r?r@rArBrCr/r/r0create=s.a z Jobs.createrVfine_tuning_job_idr@rArBrCr*cCs4|std||jd|t||||dtdS) Get info about a fine-tuning job. 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