o r)ic@sddlmZddlmZmZmZmZddlmZddl Z ddl m Z ddl m Z mZmZmZmZmZmZddlmZmZdd lmZd d lmZmZmZmZmZmZdd l m!Z!m"Z"dd l#m$Z$m%Z%ddl&m'Z'm(Z(ddl)m*Z*m+Z+ddl,m-Z-m.Z.m/Z/ddl0m1Z1ddl2m3Z3ddl4m5Z5ddgZ6Gddde!Z7Gddde"Z8GdddZ9GdddZ:GdddZ;GdddZZd d d e d*dEd?d@Zd S)Hr)IManage fine-tuning jobs to tailor a model to your specific training data.returnrcC t|jSr,)r_clientselfr3j/var/www/html/voicebot/backend/venv/lib/python3.10/site-packages/openai/resources/fine_tuning/jobs/jobs.py checkpoints( zJobs.checkpointsJobsWithRawResponsecCt|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 )r7r1r3r3r4with_raw_response-zJobs.with_raw_responseJobsWithStreamingResponsecCr8z 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 )r<r1r3r3r4with_streaming_response7zJobs.with_streaming_responseN hyperparameters integrationsmetadatamethodseedsuffixvalidation_file extra_headers extra_query extra_bodytimeoutmodelQUnion[str, Literal['babbage-002', 'davinci-002', 'gpt-3.5-turbo', 'gpt-4o-mini']] training_filestrrA(job_create_params.Hyperparameters | OmitrB8Optional[Iterable[job_create_params.Integration]] | OmitrCOptional[Metadata] | OmitrDjob_create_params.Method | OmitrEOptional[int] | OmitrFOptional[str] | OmitrGrHHeaders | NonerI Query | NonerJ Body | NonerK'float | httpx.Timeout | None | NotGivenr'c  Cs:|jdt||||||||| d tjt| | | | dtdS) 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/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 rLrNrArBrCrDrErFrGrHrIrJrKbodyoptionscast_to)_postrr$JobCreateParamsr"r'r2rLrNrArBrCrDrErFrGrHrIrJrKr3r3r4create@s(a z Jobs.creater]fine_tuning_job_idcCs4|s td||jd|t||||dtdS) Get info about a fine-tuning job. [Learn more about fine-tuning](https://platform.openai.com/docs/guides/model-optimization) Args: extra_headers: Send extra headers extra_query: Add additional query parameters to the request extra_body: Add additional JSON properties to the request timeout: Override the client-level default timeout for this request, in seconds AExpected a non-empty value for `fine_tuning_job_id` but received /fine_tuning/jobs/r]r`ra ValueError_getr"r'r2rfrHrIrJrKr3r3r4retrievesz Jobs.retrieveafterlimitrCrHrIrJrKrq str | Omitrr int | OmitOptional[Dict[str, str]] | OmitSyncCursorPage[FineTuningJob]c C4|jdttt||||t|||dtjdtdSa List your organization's fine-tuning jobs Args: after: Identifier for the last job from the previous pagination request. limit: Number of fine-tuning jobs to retrieve. metadata: Optional metadata filter. To filter, use the syntax `metadata[k]=v`. Alternatively, set `metadata=null` to indicate no metadata. extra_headers: Send extra headers extra_query: Add additional query parameters to the request extra_body: Add additional JSON properties to the request timeout: Override the client-level default timeout for this request, in seconds r[)rqrrrCrHrIrJrKquerypager`rL) _get_api_listrr'r"rr# JobListParamsr2rqrrrCrHrIrJrKr3r3r4list$ z Jobs.listcC6|s td||jd|dt||||dtdS)W 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 rhri/cancelr]rjrlrbr"r'rnr3r3r4cancel z Jobs.cancelrqrrrHrIrJrK"SyncCursorPage[FineTuningJobEvent]c CL|s td||jd|dttt||||t||dtjdtdSa 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 rhriz/events)rqrrryr{)rlr}rr(r"rr%JobListEventsParamsr2rfrqrrrHrIrJrKr3r3r4 list_events/&  zJobs.list_eventscCr)J Pause 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 rhri/pauser]rjrrnr3r3r4pausearz Jobs.pausecCr)K Resume 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 rhri/resumer]rjrrnr3r3r4resumerz Jobs.resume)r-r)r-r7)r-r<rLrMrNrOrArPrBrQrCrRrDrSrErTrFrUrGrUrHrVrIrWrJrXrKrYr-r' rfrOrHrVrIrWrJrXrKrYr-r')rqrsrrrtrCrurHrVrIrWrJrXrKrYr-rv)rfrOrqrsrrrtrHrVrIrWrJrXrKrYr-r__name__ __module__ __qualname____doc__rr5r:r>rrrerorrrrrr3r3r3r4r)%n    }&:%8'c @r+)Hr*r,r-rcCr.r/)rr0r1r3r3r4r5r6zAsyncJobs.checkpointsAsyncJobsWithRawResponsecCr8r9)rr1r3r3r4r:r;zAsyncJobs.with_raw_responseAsyncJobsWithStreamingResponsecCr8r=)rr1r3r3r4r>r?z!AsyncJobs.with_streaming_responseNr@rLrMrNrOrArPrBrQrCrRrDrSrErTrFrUrGrHrVrIrWrJrXrKrYr'c  sH|jdt||||||||| d tjIdHt| | | | dtdIdHS)rZr[r\Nr]r^)rbrr$rcr"r'rdr3r3r4res*a  zAsyncJobs.creater]rfcs<|s td||jd|t||||dtdIdHS)rgrhrir]rjNrkrnr3r3r4ro6s zAsyncJobs.retrieverprqrsrrrtru=AsyncPaginator[FineTuningJob, AsyncCursorPage[FineTuningJob]]c Crwrx)r}r r'r"rr#r~rr3r3r4rYrzAsyncJobs.listc>|s td||jd|dt||||dtdIdHS)rrhrirr]rjNrrnr3r3r4r  zAsyncJobs.cancelrGAsyncPaginator[FineTuningJobEvent, AsyncCursorPage[FineTuningJobEvent]]c Crr)rlr}r r(r"rr%rrr3r3r4rrzAsyncJobs.list_eventscr)rrhrirr]rjNrrnr3r3r4rrzAsyncJobs.pausecr)rrhrirr]rjNrrnr3r3r4rrzAsyncJobs.resume)r-r)r-r)r-rrr)rqrsrrrtrCrurHrVrIrWrJrXrKrYr-r)rfrOrqrsrrrtrHrVrIrWrJrXrKrYr-rrr3r3r3r4r*rc@$eZdZd ddZed dd Zd S) r7jobsr)r-NonecCl||_t|j|_t|j|_t|j|_t|j|_t|j|_t|j|_t|j |_ dSN) _jobsr to_raw_response_wrapperrerorrrrrr2rr3r3r4__init__$, zJobsWithRawResponse.__init__rcC t|jjSr/)rrr5r1r3r3r4r5= zJobsWithRawResponse.checkpointsNrr)r-r)r-rrrrrrr5r3r3r3r4r7# r7c@r) rrr*r-rcCrr) rr async_to_raw_response_wrapperrerorrrrrrr3r3r4rDrz!AsyncJobsWithRawResponse.__init__rcCrr/)rrr5r1r3r3r4r5]rz$AsyncJobsWithRawResponse.checkpointsNrr*r-r)r-rrr3r3r3r4rCrrc@r) r<rr)r-rcC^||_t|j|_t|j|_t|j|_t|j|_t|j|_t|j|_t|j|_dSr) rrrerorrrrrrr3r3r4rd, z"JobsWithStreamingResponse.__init__rcCrr/)rrr5r1r3r3r4r5}rz%JobsWithStreamingResponse.checkpointsNr)r-rrr3r3r3r4r<crr<c@r) rrr*r-rcCrr) rrrerorrrrrrr3r3r4rrz'AsyncJobsWithStreamingResponse.__init__rcCrr/)rrr5r1r3r3r4r5rz*AsyncJobsWithStreamingResponse.checkpointsNr)r-rrr3r3r3r4rrr)= __future__rtypingrrrrtyping_extensionsrhttpxr _typesr r r r rrr_utilsrr_compatrr5rrrrrr _resourcerr _responserr paginationrr _base_clientr!r"types.fine_tuningr#r$r%types.shared_params.metadatar&!types.fine_tuning.fine_tuning_jobr''types.fine_tuning.fine_tuning_job_eventr(__all__r)r*r7rr<rr3r3r3r4s<   $