grddlmZddlmZmZmZddlmZddlZddl m Z ddl m Z m Z mZmZmZddlmZmZdd lmZd d lmZmZmZmZmZmZdd lmZmZdd 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.ddl/m0Z0ddgZ1GddeZ2GddeZ3GddZ4GddZ5GddZ6GddZ7dS)) annotations)UnionIterableOptional)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) FineTuningJob)FineTuningJobEventJobs AsyncJobsc eZdZed0dZed1dZed2dZeeeeeeddded d3d"Zddded#d4d%Z eeddded&d5d,Z ddded#d4d-Z eeddded&d6d/Z dS)7r&returnrc*t|jSN)r_clientselfs d/var/www/html/mpstechhub/venv/lib/python3.11/site-packages/openai/resources/fine_tuning/jobs/jobs.py checkpointszJobs.checkpoints(s4<(((JobsWithRawResponsec t|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. For more information, see https://www.github.com/openai/openai-python#accessing-raw-response-data-eg-headers )r2r-s r/with_raw_responsezJobs.with_raw_response,s#4(((r1JobsWithStreamingResponsec t|Sz 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 )r6r-s r/with_streaming_responsezJobs.with_streaming_response6s)...r1N hyperparameters integrationsmethodseedsuffixvalidation_file extra_headers extra_query extra_bodytimeoutmodelQUnion[str, Literal['babbage-002', 'davinci-002', 'gpt-3.5-turbo', 'gpt-4o-mini']] training_filestrr;,job_create_params.Hyperparameters | NotGivenr<Optional[int] | NotGivenr?Optional[str] | NotGivenr@rAHeaders | NonerB Query | NonerC Body | NonerD'float | httpx.Timeout | None | NotGivenr$c |dt||||||||dtjt | | | | t S) 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. 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 /fine_tuning/jobsrErGr;r<r=r>r?r@rArBrCrDbodyoptionscast_to)_postrr"JobCreateParamsr r$ r.rErGr;r<r=r>r?r@rArBrCrDs r/createz Jobs.create?s~nzz  "%2'6$0$ $'6  "1  )+Q[el"%   r1rVfine_tuning_job_idc |std||d|t||||tS) Get info about a fine-tuning job. 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