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Add fine tuning api (#283)
Co-authored-by: michal.zyga <michal.zyga@softwaremill.com>
1 parent 4744078 commit 57419ad

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

+103-1
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
@@ -82,7 +84,7 @@ class OpenAI(authToken: String, baseUri: Uri = OpenAIUris.OpenAIBaseUri) {
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* @param completionBody
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* Create completion request body.
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* @deprecated
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* This is marked as Legacy in OpenAI API and might be removed in the future. Please use createChatCompletion instead.
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* This is marked as Legacy in OpenAI API and might be removed in the future. Please use [[createChatCompletion]] instead.
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*/
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def createCompletion(completionBody: CompletionsBody): Request[Either[OpenAIException, CompletionsResponse]] =
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openAIAuthRequest
@@ -541,6 +543,100 @@ 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: FineTuningJobRequestBody): Request[Either[OpenAIException, FineTuningJobResponse]] =
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openAIAuthRequest
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.post(openAIUris.FineTuningJobs)
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.body(fineTuningRequestBody)
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.response(asJson_parseErrors[FineTuningJobResponse])
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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, ListFineTuningJobResponse]] = {
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val uri = openAIUris.FineTuningJobs
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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[ListFineTuningJobResponse])
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}
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/** Get status updates for a fine-tuning job.
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*
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* [[https://platform.openai.com/docs/api-reference/fine-tuning/list-events]]
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*
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* @param fineTuningJobId
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* The ID of the fine-tuning job to get checkpoints for.
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*/
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def listFineTuningJobEvents(
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fineTuningJobId: String,
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queryParameters: finetuning.QueryParameters = finetuning.QueryParameters.empty
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): Request[Either[OpenAIException, ListFineTuningJobEventResponse]] = {
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val uri = openAIUris
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.fineTuningJobEvents(fineTuningJobId)
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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[ListFineTuningJobEventResponse])
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}
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/** List checkpoints for a fine-tuning job.
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*
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* [[https://platform.openai.com/docs/api-reference/fine-tuning/list-checkpoints]]
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*
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* @param fineTuningJobId
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* The ID of the fine-tuning job to get checkpoints for.
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*/
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def listFineTuningJobCheckpoints(
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fineTuningJobId: String,
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queryParameters: finetuning.QueryParameters = finetuning.QueryParameters.empty
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): Request[Either[OpenAIException, ListFineTuningJobCheckpointResponse]] = {
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val uri = openAIUris
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.fineTuningJobCheckpoints(fineTuningJobId)
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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[ListFineTuningJobCheckpointResponse])
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}
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/** Get info about a fine-tuning job.
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*
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* [[https://platform.openai.com/docs/api-reference/fine-tuning/retrieve]]
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*
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* @param fineTuningJobId
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* The ID of the fine-tuning job.
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*/
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def retrieveFineTuningJob(fineTuningJobId: String): Request[Either[OpenAIException, FineTuningJobResponse]] =
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openAIAuthRequest
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.get(openAIUris.fineTuningJob(fineTuningJobId))
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.response(asJson_parseErrors[FineTuningJobResponse])
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/** Immediately cancel a fine-tune job.
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*
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* [[https://platform.openai.com/docs/api-reference/fine-tuning/cancel]]
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*
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* @param fineTuningJobId
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* The ID of the fine-tuning job to cancel.
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*/
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def cancelFineTuningJob(fineTuningJobId: String): Request[Either[OpenAIException, FineTuningJobResponse]] =
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openAIAuthRequest
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.post(openAIUris.cancelFineTuningJob(fineTuningJobId))
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.response(asJson_parseErrors[FineTuningJobResponse])
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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 +1132,7 @@ 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"$baseUri/moderations"
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val FineTuningJobs: Uri = uri"$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")
@@ -1045,6 +1142,11 @@ private class OpenAIUris(val baseUri: Uri) {
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val ThreadsRuns: Uri = uri"$baseUri/threads/runs"
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val VectorStores: Uri = uri"$baseUri/vector_stores"
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def fineTuningJob(fineTuningJobId: String): Uri = FineTuningJobs.addPath(fineTuningJobId)
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def fineTuningJobEvents(fineTuningJobId: String): Uri = fineTuningJob(fineTuningJobId).addPath("events")
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def fineTuningJobCheckpoints(fineTuningJobId: String): Uri = fineTuningJob(fineTuningJobId).addPath("checkpoints")
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def cancelFineTuningJob(fineTuningJobId: String): Uri = fineTuningJob(fineTuningJobId).addPath("cancel")
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def file(fileId: String): Uri = Files.addPath(fileId)
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def fileContent(fileId: String): Uri = Files.addPath(fileId, "content")
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def model(modelId: String): Uri = Models.addPath(modelId)

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

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@@ -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._
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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 +350,71 @@ 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: FineTuningJobRequestBody): FineTuningJobResponse =
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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): ListFineTuningJobResponse =
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sendOrThrow(openAI.listFineTuningJobs(queryParameters))
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/** Get status updates for a fine-tuning job.
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*
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* [[https://platform.openai.com/docs/api-reference/fine-tuning/list-events]]
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*
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* @param fineTuningJobId
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* The ID of the fine-tuning job to get checkpoints for.
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*/
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def listFineTuningJobEvents(
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fineTuningJobId: String,
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queryParameters: finetuning.QueryParameters = finetuning.QueryParameters.empty
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): ListFineTuningJobEventResponse =
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sendOrThrow(openAI.listFineTuningJobEvents(fineTuningJobId, queryParameters))
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/** List checkpoints for a fine-tuning job.
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*
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* [[https://platform.openai.com/docs/api-reference/fine-tuning/list-checkpoints]]
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*
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* @param fineTuningJobId
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* The ID of the fine-tuning job to get checkpoints for.
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*/
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def listFineTuningJobCheckpoints(
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fineTuningJobId: String,
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queryParameters: finetuning.QueryParameters = finetuning.QueryParameters.empty
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): ListFineTuningJobCheckpointResponse =
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sendOrThrow(openAI.listFineTuningJobCheckpoints(fineTuningJobId, queryParameters))
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/** Get info about a fine-tuning job.
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*
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* [[https://platform.openai.com/docs/api-reference/fine-tuning/retrieve]]
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*
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* @param fineTuningJobId
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* The ID of the fine-tuning job.
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*/
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def retrieveFineTuningJob(fineTuningJobId: String): FineTuningJobResponse =
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sendOrThrow(openAI.retrieveFineTuningJob(fineTuningJobId))
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/** Immediately cancel a fine-tune job.
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*
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* [[https://platform.openai.com/docs/api-reference/fine-tuning/cancel]]
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*
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* @param fineTuningJobId
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* The ID of the fine-tuning job to cancel.
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*/
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def cancelFineTuningJob(fineTuningJobId: String): FineTuningJobResponse =
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sendOrThrow(openAI.cancelFineTuningJob(fineTuningJobId))
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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/FineTuningJobRequestBody.scala

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@@ -0,0 +1,78 @@
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package sttp.openai.requests.finetuning
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import sttp.openai.OpenAIExceptions.OpenAIException.DeserializationOpenAIException
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import sttp.openai.json.SnakePickle
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import ujson.Str
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/** @param model
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* The name of the model to fine-tune. You can select one of the supported models
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* [[https://platform.openai.com/docs/guides/fine-tuning#which-models-can-be-fine-tuned]].
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* @param trainingFile
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* The ID of an uploaded file that contains training data. See upload file for how to upload a file. Your dataset must be formatted as a
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* JSONL file. Additionally, you must upload your file with the purpose fine-tune. The contents of the file should differ depending on if
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* the model uses the chat, completions format, or if the fine-tuning method uses the preference format. See the fine-tuning guide for
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* more details.
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* @param suffix
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* 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
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* produce a model name like ft:gpt-4o-mini:openai:custom-model-name:7p4lURel.
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* @param validationFile
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* The ID of an uploaded file that contains validation data. If you provide this file, the data is used to generate validation metrics
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* periodically during fine-tuning. These metrics can be viewed in the fine-tuning results file. The same data should not be present in
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* both train and validation files. Your dataset must be formatted as a JSONL file. You must upload your file with the purpose fine-tune.
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* See the fine-tuning guide for more details.
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* @param integrations
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* A list of integrations to enable for your fine-tuning job.
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* @param seed
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* The seed controls the reproducibility of the job. Passing in the same seed and job parameters should produce the same results, but may
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* differ in rare cases. If a seed is not specified, one will be generated for you.
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* @param method
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* The method used for fine-tuning.
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*/
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case class FineTuningJobRequestBody(
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model: FineTuningModel,
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trainingFile: String,
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suffix: Option[String] = None,
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validationFile: Option[String] = None,
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integrations: Option[Seq[Integration]] = None,
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seed: Option[Int] = None,
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method: Option[Method] = None
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)
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object FineTuningJobRequestBody {
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implicit val fineTuningRequestBodyWriter: SnakePickle.Writer[FineTuningJobRequestBody] = SnakePickle.macroW[FineTuningJobRequestBody]
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}
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sealed abstract class FineTuningModel(val value: String)
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object FineTuningModel {
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implicit val fineTuningModelRW: SnakePickle.ReadWriter[FineTuningModel] = SnakePickle
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.readwriter[ujson.Value]
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.bimap[FineTuningModel](
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model => SnakePickle.writeJs(model.value),
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jsonValue =>
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SnakePickle.read[ujson.Value](jsonValue) match {
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case Str(value) =>
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byFineTuningModelValue.getOrElse(value, CustomFineTuningModel(value))
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case e => throw DeserializationOpenAIException(new Exception(s"Could not deserialize: $e"))
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}
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)
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case object GPT4o20240806 extends FineTuningModel("gpt-4o-2024-08-06")
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case object GPT4oMini20240718 extends FineTuningModel("gpt-4o-mini-2024-07-18")
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case object GPT40613 extends FineTuningModel("gpt-4-0613")
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case object GPT35Turbo0125 extends FineTuningModel("gpt-3.5-turbo-0125")
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case object GPT35Turbo1106 extends FineTuningModel("gpt-3.5-turbo-1106")
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case object GPT35Turbo0613 extends FineTuningModel("gpt-3.5-turbo-0613")
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case class CustomFineTuningModel(customFineTuningModel: String) extends FineTuningModel(customFineTuningModel)
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val values: Set[FineTuningModel] = Set(GPT4o20240806, GPT4oMini20240718, GPT40613, GPT35Turbo0125, GPT35Turbo1106, GPT35Turbo0613)
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private val byFineTuningModelValue = values.map(model => model.value -> model).toMap
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}

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