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michal.zyga
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add create fine-tuning and list fine-tuning to sync client
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5 files changed

+147
-21
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5 files changed

+147
-21
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‎core/src/main/scala/sttp/openai/OpenAI.scala

+33
Original file line numberDiff line numberDiff line change
@@ -24,6 +24,8 @@ import sttp.openai.requests.completions.chat.ChatRequestResponseData.ChatRespons
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import sttp.openai.requests.embeddings.EmbeddingsRequestBody.EmbeddingsBody
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import sttp.openai.requests.embeddings.EmbeddingsResponseBody.EmbeddingResponse
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import sttp.openai.requests.files.FilesResponseData._
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import sttp.openai.requests.finetuning
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import sttp.openai.requests.finetuning._
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import sttp.openai.requests.images.ImageResponseData.ImageResponse
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import sttp.openai.requests.images.creation.ImageCreationRequestBody.ImageCreationBody
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import sttp.openai.requests.images.edit.ImageEditsConfig
@@ -541,6 +543,36 @@ class OpenAI(authToken: String, baseUri: Uri = OpenAIUris.OpenAIBaseUri) {
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}
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.response(asJson_parseErrors[AudioResponse])
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/** Creates a fine-tuning job which begins the process of creating a new model from a given dataset.
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*
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* Response includes details of the enqueued job including job status and the name of the fine-tuned models once complete.
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*
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* [[https://platform.openai.com/docs/api-reference/fine-tuning/create]]
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*
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* @param fineTuningRequestBody
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* Request body that will be used to create a fine-tuning job.
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*/
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def createFineTuningJob(fineTuningRequestBody: FineTuningRequestBody): Request[Either[OpenAIException, FineTuningResponse]] =
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openAIAuthRequest
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.post(openAIUris.FineTuning)
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.body(fineTuningRequestBody)
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.response(asJson_parseErrors[FineTuningResponse])
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/** List your organization's fine-tuning jobs
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*
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* [[https://platform.openai.com/docs/api-reference/fine-tuning/list]]
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*/
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def listFineTuningJobs(
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queryParameters: finetuning.QueryParameters = finetuning.QueryParameters.empty
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): Request[Either[OpenAIException, ListFineTuningResponse]] = {
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val uri = openAIUris.FineTuning
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.withParams(queryParameters.toMap)
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openAIAuthRequest
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.get(uri)
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.response(asJson_parseErrors[ListFineTuningResponse])
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}
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/** Gets info about the fine-tune job.
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*
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* [[https://platform.openai.com/docs/api-reference/embeddings/create]]
@@ -1036,6 +1068,7 @@ private class OpenAIUris(val baseUri: Uri) {
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val Files: Uri = uri"$baseUri/files"
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val Models: Uri = uri"$baseUri/models"
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val Moderations: Uri = uri"$baseUri/moderations"
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val FineTuning: Uri = uri"$baseUri/fine_tuning/jobs"
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val Transcriptions: Uri = audioBase.addPath("transcriptions")
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val Translations: Uri = audioBase.addPath("translations")
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val VariationsImage: Uri = imageBase.addPath("variations")

‎core/src/main/scala/sttp/openai/OpenAISyncClient.scala

+21
Original file line numberDiff line numberDiff line change
@@ -16,6 +16,8 @@ import sttp.openai.requests.completions.chat.ChatRequestResponseData.ChatRespons
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import sttp.openai.requests.embeddings.EmbeddingsRequestBody.EmbeddingsBody
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import sttp.openai.requests.embeddings.EmbeddingsResponseBody.EmbeddingResponse
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import sttp.openai.requests.files.FilesResponseData.{DeletedFileData, FileData, FilesResponse}
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import sttp.openai.requests.finetuning
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import sttp.openai.requests.finetuning.{FineTuningRequestBody, FineTuningResponse, ListFineTuningResponse}
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import sttp.openai.requests.images.ImageResponseData.ImageResponse
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import sttp.openai.requests.images.creation.ImageCreationRequestBody.ImageCreationBody
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import sttp.openai.requests.images.edit.ImageEditsConfig
@@ -348,6 +350,25 @@ class OpenAISyncClient private (
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def createTranscription(transcriptionConfig: TranscriptionConfig): AudioResponse =
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sendOrThrow(openAI.createTranscription(transcriptionConfig))
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/** Creates a fine-tuning job which begins the process of creating a new model from a given dataset.
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*
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* Response includes details of the enqueued job including job status and the name of the fine-tuned models once complete.
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*
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* [[https://platform.openai.com/docs/api-reference/fine-tuning/create]]
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*
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* @param fineTuningRequestBody
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* Request body that will be used to create a fine-tuning job.
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*/
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def createFineTuningJob(fineTuningRequestBody: FineTuningRequestBody): FineTuningResponse =
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sendOrThrow(openAI.createFineTuningJob(fineTuningRequestBody))
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/** List your organization's fine-tuning jobs
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*
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* [[https://platform.openai.com/docs/api-reference/fine-tuning/list]]
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*/
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def listFineTuningJobs(queryParameters: finetuning.QueryParameters = finetuning.QueryParameters.empty): ListFineTuningResponse =
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sendOrThrow(openAI.listFineTuningJobs(queryParameters))
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/** Gets info about the fine-tune job.
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*
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* [[https://platform.openai.com/docs/api-reference/embeddings/create]]

‎core/src/main/scala/sttp/openai/requests/finetuning/FineTuningResponse.scala

+54-6
Original file line numberDiff line numberDiff line change
@@ -4,6 +4,45 @@ import sttp.openai.OpenAIExceptions.OpenAIException.DeserializationOpenAIExcepti
44
import sttp.openai.json.SnakePickle
55
import ujson.Str
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/** @param id
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* The object identifier, which can be referenced in the API endpoints.
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* @param createdAt
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* The Unix timestamp (in seconds) for when the fine-tuning job was created.
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* @param error
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* For fine-tuning jobs that have failed, this will contain more information on the cause of the failure.
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* @param fineTunedModel
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* The name of the fine-tuned model that is being created. The value will be null if the fine-tuning job is still running.
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* @param finishedAt
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* The Unix timestamp (in seconds) for when the fine-tuning job was finished. The value will be null if the fine-tuning job is still
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* running.
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* @param hyperparameters
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* The hyperparameters used for the fine-tuning job. This value will only be returned when running supervised jobs.
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* @param model
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* The base model that is being fine-tuned.
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* @param `object`
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* The object type, which is always "fine_tuning.job".
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* @param organizationId
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* The organization that owns the fine-tuning job.
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* @param resultFiles
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* The compiled results file ID(s) for the fine-tuning job. You can retrieve the results with the Files API.
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* @param status
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* The current status of the fine-tuning job, which can be either validating_files, queued, running, succeeded, failed, or cancelled.
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* @param trainedTokens
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* The total number of billable tokens processed by this fine-tuning job. The value will be null if the fine-tuning job is still running.
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* @param trainingFile
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* The file ID used for training. You can retrieve the training data with the Files API.
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* @param validationFile
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* The file ID used for validation. You can retrieve the validation results with the Files API.
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* @param integrations
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* A list of integrations to enable for this fine-tuning job.
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* @param seed
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* The seed used for the fine-tuning job.
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* @param estimatedFinish
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* The Unix timestamp (in seconds) for when the fine-tuning job is estimated to finish. The value will be null if the fine-tuning job is
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* not running.
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* @param method
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* The method used for fine-tuning.
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*/
746
case class FineTuningResponse(
847
id: String,
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createdAt: Int,
@@ -53,12 +92,11 @@ object Status {
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5493
implicit val statusRW: SnakePickle.Reader[Status] = SnakePickle
5594
.reader[ujson.Value]
56-
.map[Status](
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jsonValue =>
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SnakePickle.read[ujson.Value](jsonValue) match {
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case Str(value) => byStatusValue.getOrElse(value, CustomStatus(value))
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case e => throw DeserializationOpenAIException(new Exception(s"Could not deserialize: $e"))
61-
}
95+
.map[Status](jsonValue =>
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SnakePickle.read[ujson.Value](jsonValue) match {
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case Str(value) => byStatusValue.getOrElse(value, CustomStatus(value))
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case e => throw DeserializationOpenAIException(new Exception(s"Could not deserialize: $e"))
99+
}
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)
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64102
case object ValidatingFiles extends Status("validating_files")
@@ -80,3 +118,13 @@ object Status {
80118
private val byStatusValue = values.map(status => status.value -> status).toMap
81119

82120
}
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case class ListFineTuningResponse(
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`object`: String = "list",
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data: Seq[FineTuningResponse],
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hasMore: Boolean
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)
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object ListFineTuningResponse {
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implicit val listFineTuningResponseR: SnakePickle.Reader[ListFineTuningResponse] = SnakePickle.macroR[ListFineTuningResponse]
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}

‎core/src/main/scala/sttp/openai/requests/finetuning/Integration.scala

+15-15
Original file line numberDiff line numberDiff line change
@@ -27,22 +27,22 @@ object Integration {
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}
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/** @param project
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* The name of the project that the new run will be created under.
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* @param name
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* A display name to set for the run. If not set, we will use the Job ID as the name.
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* @param entity
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* The entity to use for the run. This allows you to set the team or username of the WandB user that you would like associated with the
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* run. If not set, the default entity for the registered WandB API key is used.
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* @param tags
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* A list of tags to be attached to the newly created run. These tags are passed through directly to WandB. Some default tags are
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* generated by OpenAI: "openai/finetune", "openai/{base-model}", "openai/{ftjob-abcdef}".
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*/
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* The name of the project that the new run will be created under.
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* @param name
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* A display name to set for the run. If not set, we will use the Job ID as the name.
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* @param entity
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* The entity to use for the run. This allows you to set the team or username of the WandB user that you would like associated with the
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* run. If not set, the default entity for the registered WandB API key is used.
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* @param tags
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* A list of tags to be attached to the newly created run. These tags are passed through directly to WandB. Some default tags are
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* generated by OpenAI: "openai/finetune", "openai/{base-model}", "openai/{ftjob-abcdef}".
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*/
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case class Wandb(
41-
project: String,
42-
name: Option[String] = None,
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entity: Option[String] = None,
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tags: Option[Seq[String]]
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)
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project: String,
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name: Option[String] = None,
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entity: Option[String] = None,
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tags: Option[Seq[String]]
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)
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object Wandb {
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implicit val wandbRW: SnakePickle.ReadWriter[Wandb] = SnakePickle.macroRW[Wandb]

‎core/src/main/scala/sttp/openai/requests/finetuning/QueryParameters.scala

+24
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,24 @@
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package sttp.openai.requests.finetuning
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/** @param after
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* A cursor for use in pagination. after is an object ID that defines your place in the list. For instance, if you make a list request
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* and receive 100 objects, ending with obj_foo, your subsequent call can include after=obj_foo in order to fetch the next page of the
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* list
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* @param limit
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* Defaults to 20 A limit on the number of objects to be returned. Limit can range between 1 and 100, and the default is 20.
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*/
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case class QueryParameters(
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after: Option[String] = None,
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limit: Option[Int] = None
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) {
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def toMap: Map[String, String] = {
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val queryParams = after.map("after" -> _) ++
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limit.map(_.toString).map("order" -> _)
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queryParams.toMap
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}
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}
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object QueryParameters {
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val empty: QueryParameters = QueryParameters(None, None)
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}

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