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/**
* The status of a fine-tuning job.
*/
export enum FineTuningJobStatus {
VALIDATING_FILES = 'validating_files',
QUEUED = 'queued',
RUNNING = 'running',
SUCCEEDED = 'succeeded',
FAILED = 'failed',
CANCELLED = 'cancelled',
}
/**
* Error information for a fine-tuning job.
*/
export const FineTuningJobError = z.object({
/** Machine-readable error code. */
code: z.string(),
/** Human-readable error message. */
message: z.string(),
/** The parameter that caused the error, if applicable. */
param: z.string().nullable().optional(),
});
export type FineTuningJobError = z.infer<typeof FineTuningJobError>;
/**
* The hyperparameters used for the fine-tuning job.
*/
export const FineTuningJobHyperparameters = z.object({
/** Number of epochs to train the model for. */
n_epochs: z.union([z.number().int(), z.literal('auto')]),
/** Batch size used for training. */
batch_size: z.union([z.number().int(), z.literal('auto')]).optional(),
/** Learning rate multiplier used for training. */
learning_rate_multiplier: z.union([z.number(), z.literal('auto')]).optional(),
});
export type FineTuningJobHyperparameters = z.infer<
typeof FineTuningJobHyperparameters
>;
/**
* Integration configuration for fine-tuning job.
*/
export const FineTuningJobIntegration = z.object({
/** The type of integration. */
type: z.literal('wandb'),
/** The Weights and Biases integration configuration. */
wandb: z.object({
/** The name of the project that the new run will be created under. */
project: z.string(),
/** A display name to set for the run. */
name: z.string().optional(),
/** The entity to use for the run. */
entity: z.string().optional(),
/** A list of tags to be attached to the newly created run. */
tags: z.array(z.string()).optional(),
}),
});
export type FineTuningJobIntegration = z.infer<typeof FineTuningJobIntegration>;
/**
* A fine-tuning job object.
*/
export const FineTuningJob = z.object({
/** The object identifier, which can be referenced in the API endpoints. */
id: z.string(),
/** The object type, which is always "fine_tuning.job". */
object: z.literal('fine_tuning.job'),
/** The Unix timestamp (in seconds) for when the fine-tuning job was created. */
created_at: z.number().transform((v) => {
if (v.toString().length === 10) {
return v * 1000;
}
return v;
}),
/** For fine-tuning jobs that have failed, this will contain more information on the cause of the failure. */
error: FineTuningJobError.nullable().optional(),
/** The name of the fine-tuned model that is being created. The value will be null if the fine-tuning job is still running. */
fine_tuned_model: z.string().nullable().optional(),
/** 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 running. */
finished_at: z.number().nullable().optional(),
/** The hyperparameters used for the fine-tuning job. */
hyperparameters: FineTuningJobHyperparameters,
/** The base model that is being fine-tuned. */
model: z.string(),
/** The organization that owns the fine-tuning job. */
organization_id: z.string().optional(),
/** The compiled results file ID(s) for the fine-tuning job. You can retrieve the results with the Files API. */
result_files: z.array(z.string()).optional(),
/** The current status of the fine-tuning job. */
status: z.enum(FineTuningJobStatus),
/** 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. */
trained_tokens: z.number().nullable().optional(),
/** The file ID used for training. You can retrieve the training data with the Files API. */
training_file: z.string(),
/** The file ID used for validation. You can retrieve the validation results with the Files API. */
validation_file: z.string().nullable().optional(),
/** A list of integrations to enable for your fine-tuning job. */
integrations: z.array(FineTuningJobIntegration).optional(),
/** The seed used for the fine-tuning job. */
seed: z.number().optional(),
/** 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 not running. */
estimated_finish: z.number().nullable().optional(),
/** Set of 16 key-value pairs that can be attached to an object. */
metadata: z.record(z.string(), z.string()).optional(),
});
export type FineTuningJob = z.infer<typeof FineTuningJob>;
/**
* The type of fine-tuning event.
*/
export const FineTuningEventLevel = z.enum(['info', 'warn', 'error']);
export type FineTuningEventLevel = z.infer<typeof FineTuningEventLevel>;
/**
* The type of fine-tuning event.
*/
export const FineTuningEventType = z.enum(['message', 'metrics']);
export type FineTuningEventType = z.infer<typeof FineTuningEventType>;
/**
* Fine-tuning job event object.
*/
export const FineTuningEvent = z.object({
/** The object identifier. */
id: z.string(),
/** The object type, which is always "fine_tuning.job.event". */
object: z.literal('fine_tuning.job.event'),
/** The Unix timestamp (in seconds) for when the event was created. */
created_at: z.number(),
/** The level of the event. */
level: FineTuningEventLevel,
/** The message of the event. */
message: z.string(),
/** The type of event. */
type: FineTuningEventType,
/** Metrics at the step number during the fine-tuning job. Use these numbers to understand if your training is going smoothly (loss should decrease, token accuracy should increase). */
data: z.record(z.string(), z.unknown()).optional(),
});
export type FineTuningEvent = z.infer<typeof FineTuningEvent>;
/**
* Metrics at a step during the fine-tuning job.
*/
export const FineTuningStepMetrics = z.object({
/** The step number. */
step: z.number(),
/** The training loss at this step. */
train_loss: z.number().optional(),
/** The training token accuracy at this step. */
train_mean_token_accuracy: z.number().optional(),
/** The valid loss at this step. */
valid_loss: z.number().optional(),
/** The valid mean token accuracy at this step. */
valid_mean_token_accuracy: z.number().optional(),
/** The full valid loss at this step. */
full_valid_loss: z.number().optional(),
/** The full valid mean token accuracy at this step. */
full_valid_mean_token_accuracy: z.number().optional(),
});
export type FineTuningStepMetrics = z.infer<typeof FineTuningStepMetrics>;
/**
* Fine-tuning job checkpoint object.
*/
export const FineTuningCheckpoint = z.object({
/** The checkpoint identifier, which can be referenced in the API endpoints. */
id: z.string(),
/** The object type, which is always "fine_tuning.job.checkpoint". */
object: z.literal('fine_tuning.job.checkpoint'),
/** The Unix timestamp (in seconds) for when the checkpoint was created. */
created_at: z.number(),
/** The name of the fine-tuned checkpoint model that is created. */
fine_tuned_model_checkpoint: z.string(),
/** The step number that the checkpoint was created at. */
step_number: z.number(),
/** Metrics at the step number during the fine-tuning job. */
metrics: FineTuningStepMetrics,
/** The name of the fine-tuning job that this checkpoint was created from. */
fine_tuning_job_id: z.string(),
});
export type FineTuningCheckpoint = z.infer<typeof FineTuningCheckpoint>;
/**
* List of fine-tuning job objects.
*/
export const FineTuningJobList = z.object({
/** The object type, which is always "list". */
object: z.literal('list'),
/** Array of fine-tuning job objects. */
data: z.array(FineTuningJob),
/** The first_id if pagination is needed. */
first_id: z.string().optional(),
/** The last_id if pagination is needed. */
last_id: z.string().optional(),
/** True if there are more fine-tuning jobs available. */
has_more: z.boolean(),
});
export type FineTuningJobList = z.infer<typeof FineTuningJobList>;
/**
* List of fine-tuning event objects.
*/
export const FineTuningEventList = z.object({
/** The object type, which is always "list". */
object: z.literal('list'),
/** Array of fine-tuning event objects. */
data: z.array(FineTuningEvent),
/** The first_id if pagination is needed. */
first_id: z.string().optional(),
/** The last_id if pagination is needed. */
last_id: z.string().optional(),
/** True if there are more fine-tuning events available. */
has_more: z.boolean(),
});
export type FineTuningEventList = z.infer<typeof FineTuningEventList>;
/**
* List of fine-tuning checkpoint objects.
*/
export const FineTuningCheckpointList = z.object({
/** The object type, which is always "list". */
object: z.literal('list'),
/** Array of fine-tuning checkpoint objects. */
data: z.array(FineTuningCheckpoint),
/** The first_id if pagination is needed. */
first_id: z.string().optional(),
/** The last_id if pagination is needed. */
last_id: z.string().optional(),
/** True if there are more checkpoints available. */
has_more: z.boolean(),
});
export type FineTuningCheckpointList = z.infer<typeof FineTuningCheckpointList>;
/**
* Response for creating a fine-tuning job.
*/
export const CreateFineTuningJobResponseBody = FineTuningJob;
export type CreateFineTuningJobResponseBody = z.infer<
typeof CreateFineTuningJobResponseBody
>;
/**
* Response for retrieving a fine-tuning job.
*/
export const RetrieveFineTuningJobResponseBody = FineTuningJob;
export type RetrieveFineTuningJobResponseBody = z.infer<
typeof RetrieveFineTuningJobResponseBody
>;
/**
* Response for listing fine-tuning jobs.
*/
export const ListFineTuningJobsResponseBody = FineTuningJobList;
export type ListFineTuningJobsResponseBody = z.infer<
typeof ListFineTuningJobsResponseBody
>;
/**
* Response for cancelling a fine-tuning job.
*/
export const CancelFineTuningJobResponseBody = FineTuningJob;
export type CancelFineTuningJobResponseBody = z.infer<
typeof CancelFineTuningJobResponseBody
>;
/**
* Response for listing fine-tuning events.
*/
export const ListFineTuningEventsResponseBody = FineTuningEventList;
export type ListFineTuningEventsResponseBody = z.infer<
typeof ListFineTuningEventsResponseBody
>;
/**
* Response for listing fine-tuning checkpoints.
*/
export const ListFineTuningCheckpointsResponseBody = FineTuningCheckpointList;
export type ListFineTuningCheckpointsResponseBody = z.infer<
typeof ListFineTuningCheckpointsResponseBody
>;
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