diff --git a/en/ruby/resources/fine_tuning/index.md b/en/ruby/resources/fine_tuning/index.md new file mode 100644 index 0000000..00f2830 --- /dev/null +++ b/en/ruby/resources/fine_tuning/index.md @@ -0,0 +1,10903 @@ +# Fine Tuning + +# Methods + +## Domain Types + +### Dpo Hyperparameters + +- `class DpoHyperparameters` + + The hyperparameters used for the DPO fine-tuning job. + + - `batch_size: :auto | Integer` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `BatchSize = :auto` + + - `:auto` + + - `Integer = Integer` + + - `beta: :auto | Float` + + The beta value for the DPO method. A higher beta value will increase the weight of the penalty between the policy and reference model. + + - `Beta = :auto` + + - `:auto` + + - `Float = Float` + + - `learning_rate_multiplier: :auto | Float` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `LearningRateMultiplier = :auto` + + - `:auto` + + - `Float = Float` + + - `n_epochs: :auto | Integer` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `NEpochs = :auto` + + - `:auto` + + - `Integer = Integer` + +### Dpo Method + +- `class DpoMethod` + + Configuration for the DPO fine-tuning method. + + - `hyperparameters: DpoHyperparameters` + + The hyperparameters used for the DPO fine-tuning job. + + - `batch_size: :auto | Integer` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `BatchSize = :auto` + + - `:auto` + + - `Integer = Integer` + + - `beta: :auto | Float` + + The beta value for the DPO method. A higher beta value will increase the weight of the penalty between the policy and reference model. + + - `Beta = :auto` + + - `:auto` + + - `Float = Float` + + - `learning_rate_multiplier: :auto | Float` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `LearningRateMultiplier = :auto` + + - `:auto` + + - `Float = Float` + + - `n_epochs: :auto | Integer` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `NEpochs = :auto` + + - `:auto` + + - `Integer = Integer` + +### Reinforcement Hyperparameters + +- `class ReinforcementHyperparameters` + + The hyperparameters used for the reinforcement fine-tuning job. + + - `batch_size: :auto | Integer` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `BatchSize = :auto` + + - `:auto` + + - `Integer = Integer` + + - `compute_multiplier: :auto | Float` + + Multiplier on amount of compute used for exploring search space during training. + + - `ComputeMultiplier = :auto` + + - `:auto` + + - `Float = Float` + + - `eval_interval: :auto | Integer` + + The number of training steps between evaluation runs. + + - `EvalInterval = :auto` + + - `:auto` + + - `Integer = Integer` + + - `eval_samples: :auto | Integer` + + Number of evaluation samples to generate per training step. + + - `EvalSamples = :auto` + + - `:auto` + + - `Integer = Integer` + + - `learning_rate_multiplier: :auto | Float` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `LearningRateMultiplier = :auto` + + - `:auto` + + - `Float = Float` + + - `n_epochs: :auto | Integer` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `NEpochs = :auto` + + - `:auto` + + - `Integer = Integer` + + - `reasoning_effort: :default | :low | :medium | :high` + + Level of reasoning effort. + + - `:default` + + - `:low` + + - `:medium` + + - `:high` + +### Reinforcement Method + +- `class ReinforcementMethod` + + Configuration for the reinforcement fine-tuning method. + + - `grader: StringCheckGrader | TextSimilarityGrader | PythonGrader | 2 more` + + The grader used for the fine-tuning job. + + - `class StringCheckGrader` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `input: String` + + The input text. This may include template strings. + + - `name: String` + + The name of the grader. + + - `operation: :eq | :ne | :like | :ilike` + + The string check operation to perform. One of `eq`, `ne`, `like`, or `ilike`. + + - `:eq` + + - `:ne` + + - `:like` + + - `:ilike` + + - `reference: String` + + The reference text. This may include template strings. + + - `type: :string_check` + + The object type, which is always `string_check`. + + - `:string_check` + + - `class TextSimilarityGrader` + + A TextSimilarityGrader object which grades text based on similarity metrics. + + - `evaluation_metric: :cosine | :fuzzy_match | :bleu | 8 more` + + The evaluation metric to use. One of `cosine`, `fuzzy_match`, `bleu`, + `gleu`, `meteor`, `rouge_1`, `rouge_2`, `rouge_3`, `rouge_4`, `rouge_5`, + or `rouge_l`. + + - `:cosine` + + - `:fuzzy_match` + + - `:bleu` + + - `:gleu` + + - `:meteor` + + - `:rouge_1` + + - `:rouge_2` + + - `:rouge_3` + + - `:rouge_4` + + - `:rouge_5` + + - `:rouge_l` + + - `input: String` + + The text being graded. + + - `name: String` + + The name of the grader. + + - `reference: String` + + The text being graded against. + + - `type: :text_similarity` + + The type of grader. + + - `:text_similarity` + + - `class PythonGrader` + + A PythonGrader object that runs a python script on the input. + + - `name: String` + + The name of the grader. + + - `source: String` + + The source code of the python script. + + - `type: :python` + + The object type, which is always `python`. + + - `:python` + + - `image_tag: String` + + The image tag to use for the python script. + + - `class ScoreModelGrader` + + A ScoreModelGrader object that uses a model to assign a score to the input. + + - `input: Array[Input{ content, role, type}]` + + The input messages evaluated by the grader. Supports text, output text, input image, and input audio content blocks, and may include template strings. + + - `content: String | ResponseInputText | OutputText{ text, type} | 3 more` + + Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items. + + - `String = String` + + A text input to the model. + + - `class ResponseInputText` + + A text input to the model. + + - `text: String` + + The text input to the model. + + - `type: :input_text` + + The type of the input item. Always `input_text`. + + - `:input_text` + + - `class OutputText` + + A text output from the model. + + - `text: String` + + The text output from the model. + + - `type: :output_text` + + The type of the output text. Always `output_text`. + + - `:output_text` + + - `class InputImage` + + An image input block used within EvalItem content arrays. + + - `image_url: String` + + The URL of the image input. + + - `type: :input_image` + + The type of the image input. Always `input_image`. + + - `:input_image` + + - `detail: String` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `class ResponseInputAudio` + + An audio input to the model. + + - `input_audio: InputAudio{ data, format_}` + + - `data: String` + + Base64-encoded audio data. + + - `format_: :mp3 | :wav` + + The format of the audio data. Currently supported formats are `mp3` and + `wav`. + + - `:mp3` + + - `:wav` + + - `type: :input_audio` + + The type of the input item. Always `input_audio`. + + - `:input_audio` + + - `GraderInputs = Array[GraderInputItem]` + + A list of inputs, each of which may be either an input text, output text, input + image, or input audio object. + + - `String = String` + + A text input to the model. + + - `class ResponseInputText` + + A text input to the model. + + - `class OutputText` + + A text output from the model. + + - `text: String` + + The text output from the model. + + - `type: :output_text` + + The type of the output text. Always `output_text`. + + - `:output_text` + + - `class InputImage` + + An image input block used within EvalItem content arrays. + + - `image_url: String` + + The URL of the image input. + + - `type: :input_image` + + The type of the image input. Always `input_image`. + + - `:input_image` + + - `detail: String` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `class ResponseInputAudio` + + An audio input to the model. + + - `role: :user | :assistant | :system | :developer` + + The role of the message input. One of `user`, `assistant`, `system`, or + `developer`. + + - `:user` + + - `:assistant` + + - `:system` + + - `:developer` + + - `type: :message` + + The type of the message input. Always `message`. + + - `:message` + + - `model: String` + + The model to use for the evaluation. + + - `name: String` + + The name of the grader. + + - `type: :score_model` + + The object type, which is always `score_model`. + + - `:score_model` + + - `range: Array[Float]` + + The range of the score. Defaults to `[0, 1]`. + + - `sampling_params: SamplingParams{ max_completions_tokens, reasoning_effort, seed, 2 more}` + + The sampling parameters for the model. + + - `max_completions_tokens: Integer` + + The maximum number of tokens the grader model may generate in its response. + + - `reasoning_effort: ReasoningEffort` + + Constrains effort on reasoning for + [reasoning models](https://platform.openai.com/docs/guides/reasoning). + Currently supported values are `none`, `minimal`, `low`, `medium`, `high`, and `xhigh`. Reducing + reasoning effort can result in faster responses and fewer tokens used + on reasoning in a response. + + - `gpt-5.1` defaults to `none`, which does not perform reasoning. The supported reasoning values for `gpt-5.1` are `none`, `low`, `medium`, and `high`. Tool calls are supported for all reasoning values in gpt-5.1. + - All models before `gpt-5.1` default to `medium` reasoning effort, and do not support `none`. + - The `gpt-5-pro` model defaults to (and only supports) `high` reasoning effort. + - `xhigh` is supported for all models after `gpt-5.1-codex-max`. + + - `:none` + + - `:minimal` + + - `:low` + + - `:medium` + + - `:high` + + - `:xhigh` + + - `seed: Integer` + + A seed value to initialize the randomness, during sampling. + + - `temperature: Float` + + A higher temperature increases randomness in the outputs. + + - `top_p: Float` + + An alternative to temperature for nucleus sampling; 1.0 includes all tokens. + + - `class MultiGrader` + + A MultiGrader object combines the output of multiple graders to produce a single score. + + - `calculate_output: String` + + A formula to calculate the output based on grader results. + + - `graders: StringCheckGrader | TextSimilarityGrader | PythonGrader | 2 more` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `class StringCheckGrader` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `class TextSimilarityGrader` + + A TextSimilarityGrader object which grades text based on similarity metrics. + + - `class PythonGrader` + + A PythonGrader object that runs a python script on the input. + + - `class ScoreModelGrader` + + A ScoreModelGrader object that uses a model to assign a score to the input. + + - `class LabelModelGrader` + + A LabelModelGrader object which uses a model to assign labels to each item + in the evaluation. + + - `input: Array[Input{ content, role, type}]` + + - `content: String | ResponseInputText | OutputText{ text, type} | 3 more` + + Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items. + + - `String = String` + + A text input to the model. + + - `class ResponseInputText` + + A text input to the model. + + - `class OutputText` + + A text output from the model. + + - `text: String` + + The text output from the model. + + - `type: :output_text` + + The type of the output text. Always `output_text`. + + - `:output_text` + + - `class InputImage` + + An image input block used within EvalItem content arrays. + + - `image_url: String` + + The URL of the image input. + + - `type: :input_image` + + The type of the image input. Always `input_image`. + + - `:input_image` + + - `detail: String` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `class ResponseInputAudio` + + An audio input to the model. + + - `GraderInputs = Array[GraderInputItem]` + + A list of inputs, each of which may be either an input text, output text, input + image, or input audio object. + + - `role: :user | :assistant | :system | :developer` + + The role of the message input. One of `user`, `assistant`, `system`, or + `developer`. + + - `:user` + + - `:assistant` + + - `:system` + + - `:developer` + + - `type: :message` + + The type of the message input. Always `message`. + + - `:message` + + - `labels: Array[String]` + + The labels to assign to each item in the evaluation. + + - `model: String` + + The model to use for the evaluation. Must support structured outputs. + + - `name: String` + + The name of the grader. + + - `passing_labels: Array[String]` + + The labels that indicate a passing result. Must be a subset of labels. + + - `type: :label_model` + + The object type, which is always `label_model`. + + - `:label_model` + + - `name: String` + + The name of the grader. + + - `type: :multi` + + The object type, which is always `multi`. + + - `:multi` + + - `hyperparameters: ReinforcementHyperparameters` + + The hyperparameters used for the reinforcement fine-tuning job. + + - `batch_size: :auto | Integer` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `BatchSize = :auto` + + - `:auto` + + - `Integer = Integer` + + - `compute_multiplier: :auto | Float` + + Multiplier on amount of compute used for exploring search space during training. + + - `ComputeMultiplier = :auto` + + - `:auto` + + - `Float = Float` + + - `eval_interval: :auto | Integer` + + The number of training steps between evaluation runs. + + - `EvalInterval = :auto` + + - `:auto` + + - `Integer = Integer` + + - `eval_samples: :auto | Integer` + + Number of evaluation samples to generate per training step. + + - `EvalSamples = :auto` + + - `:auto` + + - `Integer = Integer` + + - `learning_rate_multiplier: :auto | Float` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `LearningRateMultiplier = :auto` + + - `:auto` + + - `Float = Float` + + - `n_epochs: :auto | Integer` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `NEpochs = :auto` + + - `:auto` + + - `Integer = Integer` + + - `reasoning_effort: :default | :low | :medium | :high` + + Level of reasoning effort. + + - `:default` + + - `:low` + + - `:medium` + + - `:high` + +### Supervised Hyperparameters + +- `class SupervisedHyperparameters` + + The hyperparameters used for the fine-tuning job. + + - `batch_size: :auto | Integer` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `BatchSize = :auto` + + - `:auto` + + - `Integer = Integer` + + - `learning_rate_multiplier: :auto | Float` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `LearningRateMultiplier = :auto` + + - `:auto` + + - `Float = Float` + + - `n_epochs: :auto | Integer` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `NEpochs = :auto` + + - `:auto` + + - `Integer = Integer` + +### Supervised Method + +- `class SupervisedMethod` + + Configuration for the supervised fine-tuning method. + + - `hyperparameters: SupervisedHyperparameters` + + The hyperparameters used for the fine-tuning job. + + - `batch_size: :auto | Integer` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `BatchSize = :auto` + + - `:auto` + + - `Integer = Integer` + + - `learning_rate_multiplier: :auto | Float` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `LearningRateMultiplier = :auto` + + - `:auto` + + - `Float = Float` + + - `n_epochs: :auto | Integer` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `NEpochs = :auto` + + - `:auto` + + - `Integer = Integer` + +# Jobs + +## Create fine-tuning job + +`fine_tuning.jobs.create(**kwargs) -> FineTuningJob` + +**post** `/fine_tuning/jobs` + +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) + +### Parameters + +- `model: String | :"babbage-002" | :"davinci-002" | :"gpt-3.5-turbo" | :"gpt-4o-mini"` + + 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). + + - `String = String` + + - `Model = :"babbage-002" | :"davinci-002" | :"gpt-3.5-turbo" | :"gpt-4o-mini"` + + 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). + + - `:"babbage-002"` + + - `:"davinci-002"` + + - `:"gpt-3.5-turbo"` + + - `:"gpt-4o-mini"` + +- `training_file: String` + + 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: Hyperparameters{ batch_size, learning_rate_multiplier, n_epochs}` + + 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. + + - `batch_size: :auto | Integer` + + Number of examples in each batch. A larger batch size means that model parameters + are updated less frequently, but with lower variance. + + - `BatchSize = :auto` + + - `:auto` + + - `Integer = Integer` + + - `learning_rate_multiplier: :auto | Float` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid + overfitting. + + - `LearningRateMultiplier = :auto` + + - `:auto` + + - `Float = Float` + + - `n_epochs: :auto | Integer` + + The number of epochs to train the model for. An epoch refers to one full cycle + through the training dataset. + + - `NEpochs = :auto` + + - `:auto` + + - `Integer = Integer` + +- `integrations: Array[Integration{ type, wandb}]` + + A list of integrations to enable for your fine-tuning job. + + - `type: :wandb` + + The type of integration to enable. Currently, only "wandb" (Weights and Biases) is supported. + + - `:wandb` + + - `wandb: Wandb{ project, entity, name, tags}` + + The settings for your integration with Weights and Biases. This payload specifies the project that + metrics will be sent to. Optionally, you can set an explicit display name for your run, add tags + to your run, and set a default entity (team, username, etc) to be associated with your run. + + - `project: String` + + The name of the project that the new run will be created under. + + - `entity: String` + + 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 run. If not set, the default entity for the registered WandB API key is used. + + - `name: String` + + A display name to set for the run. If not set, we will use the Job ID as the name. + + - `tags: Array[String]` + + A list of tags to be attached to the newly created run. These tags are passed through directly to WandB. Some + default tags are generated by OpenAI: "openai/finetune", "openai/{base-model}", "openai/{ftjob-abcdef}". + +- `metadata: 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_: Method{ type, dpo, reinforcement, supervised}` + + The method used for fine-tuning. + + - `type: :supervised | :dpo | :reinforcement` + + The type of method. Is either `supervised`, `dpo`, or `reinforcement`. + + - `:supervised` + + - `:dpo` + + - `:reinforcement` + + - `dpo: DpoMethod` + + Configuration for the DPO fine-tuning method. + + - `hyperparameters: DpoHyperparameters` + + The hyperparameters used for the DPO fine-tuning job. + + - `batch_size: :auto | Integer` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `BatchSize = :auto` + + - `:auto` + + - `Integer = Integer` + + - `beta: :auto | Float` + + The beta value for the DPO method. A higher beta value will increase the weight of the penalty between the policy and reference model. + + - `Beta = :auto` + + - `:auto` + + - `Float = Float` + + - `learning_rate_multiplier: :auto | Float` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `LearningRateMultiplier = :auto` + + - `:auto` + + - `Float = Float` + + - `n_epochs: :auto | Integer` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `NEpochs = :auto` + + - `:auto` + + - `Integer = Integer` + + - `reinforcement: ReinforcementMethod` + + Configuration for the reinforcement fine-tuning method. + + - `grader: StringCheckGrader | TextSimilarityGrader | PythonGrader | 2 more` + + The grader used for the fine-tuning job. + + - `class StringCheckGrader` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `input: String` + + The input text. This may include template strings. + + - `name: String` + + The name of the grader. + + - `operation: :eq | :ne | :like | :ilike` + + The string check operation to perform. One of `eq`, `ne`, `like`, or `ilike`. + + - `:eq` + + - `:ne` + + - `:like` + + - `:ilike` + + - `reference: String` + + The reference text. This may include template strings. + + - `type: :string_check` + + The object type, which is always `string_check`. + + - `:string_check` + + - `class TextSimilarityGrader` + + A TextSimilarityGrader object which grades text based on similarity metrics. + + - `evaluation_metric: :cosine | :fuzzy_match | :bleu | 8 more` + + The evaluation metric to use. One of `cosine`, `fuzzy_match`, `bleu`, + `gleu`, `meteor`, `rouge_1`, `rouge_2`, `rouge_3`, `rouge_4`, `rouge_5`, + or `rouge_l`. + + - `:cosine` + + - `:fuzzy_match` + + - `:bleu` + + - `:gleu` + + - `:meteor` + + - `:rouge_1` + + - `:rouge_2` + + - `:rouge_3` + + - `:rouge_4` + + - `:rouge_5` + + - `:rouge_l` + + - `input: String` + + The text being graded. + + - `name: String` + + The name of the grader. + + - `reference: String` + + The text being graded against. + + - `type: :text_similarity` + + The type of grader. + + - `:text_similarity` + + - `class PythonGrader` + + A PythonGrader object that runs a python script on the input. + + - `name: String` + + The name of the grader. + + - `source: String` + + The source code of the python script. + + - `type: :python` + + The object type, which is always `python`. + + - `:python` + + - `image_tag: String` + + The image tag to use for the python script. + + - `class ScoreModelGrader` + + A ScoreModelGrader object that uses a model to assign a score to the input. + + - `input: Array[Input{ content, role, type}]` + + The input messages evaluated by the grader. Supports text, output text, input image, and input audio content blocks, and may include template strings. + + - `content: String | ResponseInputText | OutputText{ text, type} | 3 more` + + Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items. + + - `String = String` + + A text input to the model. + + - `class ResponseInputText` + + A text input to the model. + + - `text: String` + + The text input to the model. + + - `type: :input_text` + + The type of the input item. Always `input_text`. + + - `:input_text` + + - `class OutputText` + + A text output from the model. + + - `text: String` + + The text output from the model. + + - `type: :output_text` + + The type of the output text. Always `output_text`. + + - `:output_text` + + - `class InputImage` + + An image input block used within EvalItem content arrays. + + - `image_url: String` + + The URL of the image input. + + - `type: :input_image` + + The type of the image input. Always `input_image`. + + - `:input_image` + + - `detail: String` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `class ResponseInputAudio` + + An audio input to the model. + + - `input_audio: InputAudio{ data, format_}` + + - `data: String` + + Base64-encoded audio data. + + - `format_: :mp3 | :wav` + + The format of the audio data. Currently supported formats are `mp3` and + `wav`. + + - `:mp3` + + - `:wav` + + - `type: :input_audio` + + The type of the input item. Always `input_audio`. + + - `:input_audio` + + - `GraderInputs = Array[GraderInputItem]` + + A list of inputs, each of which may be either an input text, output text, input + image, or input audio object. + + - `String = String` + + A text input to the model. + + - `class ResponseInputText` + + A text input to the model. + + - `class OutputText` + + A text output from the model. + + - `text: String` + + The text output from the model. + + - `type: :output_text` + + The type of the output text. Always `output_text`. + + - `:output_text` + + - `class InputImage` + + An image input block used within EvalItem content arrays. + + - `image_url: String` + + The URL of the image input. + + - `type: :input_image` + + The type of the image input. Always `input_image`. + + - `:input_image` + + - `detail: String` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `class ResponseInputAudio` + + An audio input to the model. + + - `role: :user | :assistant | :system | :developer` + + The role of the message input. One of `user`, `assistant`, `system`, or + `developer`. + + - `:user` + + - `:assistant` + + - `:system` + + - `:developer` + + - `type: :message` + + The type of the message input. Always `message`. + + - `:message` + + - `model: String` + + The model to use for the evaluation. + + - `name: String` + + The name of the grader. + + - `type: :score_model` + + The object type, which is always `score_model`. + + - `:score_model` + + - `range: Array[Float]` + + The range of the score. Defaults to `[0, 1]`. + + - `sampling_params: SamplingParams{ max_completions_tokens, reasoning_effort, seed, 2 more}` + + The sampling parameters for the model. + + - `max_completions_tokens: Integer` + + The maximum number of tokens the grader model may generate in its response. + + - `reasoning_effort: ReasoningEffort` + + Constrains effort on reasoning for + [reasoning models](https://platform.openai.com/docs/guides/reasoning). + Currently supported values are `none`, `minimal`, `low`, `medium`, `high`, and `xhigh`. Reducing + reasoning effort can result in faster responses and fewer tokens used + on reasoning in a response. + + - `gpt-5.1` defaults to `none`, which does not perform reasoning. The supported reasoning values for `gpt-5.1` are `none`, `low`, `medium`, and `high`. Tool calls are supported for all reasoning values in gpt-5.1. + - All models before `gpt-5.1` default to `medium` reasoning effort, and do not support `none`. + - The `gpt-5-pro` model defaults to (and only supports) `high` reasoning effort. + - `xhigh` is supported for all models after `gpt-5.1-codex-max`. + + - `:none` + + - `:minimal` + + - `:low` + + - `:medium` + + - `:high` + + - `:xhigh` + + - `seed: Integer` + + A seed value to initialize the randomness, during sampling. + + - `temperature: Float` + + A higher temperature increases randomness in the outputs. + + - `top_p: Float` + + An alternative to temperature for nucleus sampling; 1.0 includes all tokens. + + - `class MultiGrader` + + A MultiGrader object combines the output of multiple graders to produce a single score. + + - `calculate_output: String` + + A formula to calculate the output based on grader results. + + - `graders: StringCheckGrader | TextSimilarityGrader | PythonGrader | 2 more` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `class StringCheckGrader` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `class TextSimilarityGrader` + + A TextSimilarityGrader object which grades text based on similarity metrics. + + - `class PythonGrader` + + A PythonGrader object that runs a python script on the input. + + - `class ScoreModelGrader` + + A ScoreModelGrader object that uses a model to assign a score to the input. + + - `class LabelModelGrader` + + A LabelModelGrader object which uses a model to assign labels to each item + in the evaluation. + + - `input: Array[Input{ content, role, type}]` + + - `content: String | ResponseInputText | OutputText{ text, type} | 3 more` + + Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items. + + - `String = String` + + A text input to the model. + + - `class ResponseInputText` + + A text input to the model. + + - `class OutputText` + + A text output from the model. + + - `text: String` + + The text output from the model. + + - `type: :output_text` + + The type of the output text. Always `output_text`. + + - `:output_text` + + - `class InputImage` + + An image input block used within EvalItem content arrays. + + - `image_url: String` + + The URL of the image input. + + - `type: :input_image` + + The type of the image input. Always `input_image`. + + - `:input_image` + + - `detail: String` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `class ResponseInputAudio` + + An audio input to the model. + + - `GraderInputs = Array[GraderInputItem]` + + A list of inputs, each of which may be either an input text, output text, input + image, or input audio object. + + - `role: :user | :assistant | :system | :developer` + + The role of the message input. One of `user`, `assistant`, `system`, or + `developer`. + + - `:user` + + - `:assistant` + + - `:system` + + - `:developer` + + - `type: :message` + + The type of the message input. Always `message`. + + - `:message` + + - `labels: Array[String]` + + The labels to assign to each item in the evaluation. + + - `model: String` + + The model to use for the evaluation. Must support structured outputs. + + - `name: String` + + The name of the grader. + + - `passing_labels: Array[String]` + + The labels that indicate a passing result. Must be a subset of labels. + + - `type: :label_model` + + The object type, which is always `label_model`. + + - `:label_model` + + - `name: String` + + The name of the grader. + + - `type: :multi` + + The object type, which is always `multi`. + + - `:multi` + + - `hyperparameters: ReinforcementHyperparameters` + + The hyperparameters used for the reinforcement fine-tuning job. + + - `batch_size: :auto | Integer` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `BatchSize = :auto` + + - `:auto` + + - `Integer = Integer` + + - `compute_multiplier: :auto | Float` + + Multiplier on amount of compute used for exploring search space during training. + + - `ComputeMultiplier = :auto` + + - `:auto` + + - `Float = Float` + + - `eval_interval: :auto | Integer` + + The number of training steps between evaluation runs. + + - `EvalInterval = :auto` + + - `:auto` + + - `Integer = Integer` + + - `eval_samples: :auto | Integer` + + Number of evaluation samples to generate per training step. + + - `EvalSamples = :auto` + + - `:auto` + + - `Integer = Integer` + + - `learning_rate_multiplier: :auto | Float` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `LearningRateMultiplier = :auto` + + - `:auto` + + - `Float = Float` + + - `n_epochs: :auto | Integer` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `NEpochs = :auto` + + - `:auto` + + - `Integer = Integer` + + - `reasoning_effort: :default | :low | :medium | :high` + + Level of reasoning effort. + + - `:default` + + - `:low` + + - `:medium` + + - `:high` + + - `supervised: SupervisedMethod` + + Configuration for the supervised fine-tuning method. + + - `hyperparameters: SupervisedHyperparameters` + + The hyperparameters used for the fine-tuning job. + + - `batch_size: :auto | Integer` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `BatchSize = :auto` + + - `:auto` + + - `Integer = Integer` + + - `learning_rate_multiplier: :auto | Float` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `LearningRateMultiplier = :auto` + + - `:auto` + + - `Float = Float` + + - `n_epochs: :auto | Integer` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `NEpochs = :auto` + + - `:auto` + + - `Integer = Integer` + +- `seed: Integer` + + 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: String` + + 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: String` + + 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. + +### Returns + +- `class FineTuningJob` + + The `fine_tuning.job` object represents a fine-tuning job that has been created through the API. + + - `id: String` + + The object identifier, which can be referenced in the API endpoints. + + - `created_at: Integer` + + The Unix timestamp (in seconds) for when the fine-tuning job was created. + + - `error: Error{ code, message, param}` + + For fine-tuning jobs that have `failed`, this will contain more information on the cause of the failure. + + - `code: String` + + A machine-readable error code. + + - `message: String` + + A human-readable error message. + + - `param: String` + + The parameter that was invalid, usually `training_file` or `validation_file`. This field will be null if the failure was not parameter-specific. + + - `fine_tuned_model: String` + + The name of the fine-tuned model that is being created. The value will be null if the fine-tuning job is still running. + + - `finished_at: Integer` + + 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. + + - `hyperparameters: Hyperparameters{ batch_size, learning_rate_multiplier, n_epochs}` + + The hyperparameters used for the fine-tuning job. This value will only be returned when running `supervised` jobs. + + - `batch_size: :auto | Integer` + + Number of examples in each batch. A larger batch size means that model parameters + are updated less frequently, but with lower variance. + + - `BatchSize = :auto` + + - `:auto` + + - `Integer = Integer` + + - `learning_rate_multiplier: :auto | Float` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid + overfitting. + + - `LearningRateMultiplier = :auto` + + - `:auto` + + - `Float = Float` + + - `n_epochs: :auto | Integer` + + The number of epochs to train the model for. An epoch refers to one full cycle + through the training dataset. + + - `NEpochs = :auto` + + - `:auto` + + - `Integer = Integer` + + - `model: String` + + The base model that is being fine-tuned. + + - `object: :"fine_tuning.job"` + + The object type, which is always "fine_tuning.job". + + - `:"fine_tuning.job"` + + - `organization_id: String` + + The organization that owns the fine-tuning job. + + - `result_files: Array[String]` + + The compiled results file ID(s) for the fine-tuning job. You can retrieve the results with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents). + + - `seed: Integer` + + The seed used for the fine-tuning job. + + - `status: :validating_files | :queued | :running | 3 more` + + The current status of the fine-tuning job, which can be either `validating_files`, `queued`, `running`, `succeeded`, `failed`, or `cancelled`. + + - `:validating_files` + + - `:queued` + + - `:running` + + - `:succeeded` + + - `:failed` + + - `:cancelled` + + - `trained_tokens: Integer` + + 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. + + - `training_file: String` + + The file ID used for training. You can retrieve the training data with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents). + + - `validation_file: String` + + The file ID used for validation. You can retrieve the validation results with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents). + + - `estimated_finish: Integer` + + 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. + + - `integrations: Array[FineTuningJobWandbIntegrationObject]` + + A list of integrations to enable for this fine-tuning job. + + - `type: :wandb` + + The type of the integration being enabled for the fine-tuning job + + - `:wandb` + + - `wandb: FineTuningJobWandbIntegration` + + The settings for your integration with Weights and Biases. This payload specifies the project that + metrics will be sent to. Optionally, you can set an explicit display name for your run, add tags + to your run, and set a default entity (team, username, etc) to be associated with your run. + + - `project: String` + + The name of the project that the new run will be created under. + + - `entity: String` + + 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 run. If not set, the default entity for the registered WandB API key is used. + + - `name: String` + + A display name to set for the run. If not set, we will use the Job ID as the name. + + - `tags: Array[String]` + + A list of tags to be attached to the newly created run. These tags are passed through directly to WandB. Some + default tags are generated by OpenAI: "openai/finetune", "openai/{base-model}", "openai/{ftjob-abcdef}". + + - `metadata: 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_: Method{ type, dpo, reinforcement, supervised}` + + The method used for fine-tuning. + + - `type: :supervised | :dpo | :reinforcement` + + The type of method. Is either `supervised`, `dpo`, or `reinforcement`. + + - `:supervised` + + - `:dpo` + + - `:reinforcement` + + - `dpo: DpoMethod` + + Configuration for the DPO fine-tuning method. + + - `hyperparameters: DpoHyperparameters` + + The hyperparameters used for the DPO fine-tuning job. + + - `batch_size: :auto | Integer` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `BatchSize = :auto` + + - `:auto` + + - `Integer = Integer` + + - `beta: :auto | Float` + + The beta value for the DPO method. A higher beta value will increase the weight of the penalty between the policy and reference model. + + - `Beta = :auto` + + - `:auto` + + - `Float = Float` + + - `learning_rate_multiplier: :auto | Float` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `LearningRateMultiplier = :auto` + + - `:auto` + + - `Float = Float` + + - `n_epochs: :auto | Integer` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `NEpochs = :auto` + + - `:auto` + + - `Integer = Integer` + + - `reinforcement: ReinforcementMethod` + + Configuration for the reinforcement fine-tuning method. + + - `grader: StringCheckGrader | TextSimilarityGrader | PythonGrader | 2 more` + + The grader used for the fine-tuning job. + + - `class StringCheckGrader` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `input: String` + + The input text. This may include template strings. + + - `name: String` + + The name of the grader. + + - `operation: :eq | :ne | :like | :ilike` + + The string check operation to perform. One of `eq`, `ne`, `like`, or `ilike`. + + - `:eq` + + - `:ne` + + - `:like` + + - `:ilike` + + - `reference: String` + + The reference text. This may include template strings. + + - `type: :string_check` + + The object type, which is always `string_check`. + + - `:string_check` + + - `class TextSimilarityGrader` + + A TextSimilarityGrader object which grades text based on similarity metrics. + + - `evaluation_metric: :cosine | :fuzzy_match | :bleu | 8 more` + + The evaluation metric to use. One of `cosine`, `fuzzy_match`, `bleu`, + `gleu`, `meteor`, `rouge_1`, `rouge_2`, `rouge_3`, `rouge_4`, `rouge_5`, + or `rouge_l`. + + - `:cosine` + + - `:fuzzy_match` + + - `:bleu` + + - `:gleu` + + - `:meteor` + + - `:rouge_1` + + - `:rouge_2` + + - `:rouge_3` + + - `:rouge_4` + + - `:rouge_5` + + - `:rouge_l` + + - `input: String` + + The text being graded. + + - `name: String` + + The name of the grader. + + - `reference: String` + + The text being graded against. + + - `type: :text_similarity` + + The type of grader. + + - `:text_similarity` + + - `class PythonGrader` + + A PythonGrader object that runs a python script on the input. + + - `name: String` + + The name of the grader. + + - `source: String` + + The source code of the python script. + + - `type: :python` + + The object type, which is always `python`. + + - `:python` + + - `image_tag: String` + + The image tag to use for the python script. + + - `class ScoreModelGrader` + + A ScoreModelGrader object that uses a model to assign a score to the input. + + - `input: Array[Input{ content, role, type}]` + + The input messages evaluated by the grader. Supports text, output text, input image, and input audio content blocks, and may include template strings. + + - `content: String | ResponseInputText | OutputText{ text, type} | 3 more` + + Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items. + + - `String = String` + + A text input to the model. + + - `class ResponseInputText` + + A text input to the model. + + - `text: String` + + The text input to the model. + + - `type: :input_text` + + The type of the input item. Always `input_text`. + + - `:input_text` + + - `class OutputText` + + A text output from the model. + + - `text: String` + + The text output from the model. + + - `type: :output_text` + + The type of the output text. Always `output_text`. + + - `:output_text` + + - `class InputImage` + + An image input block used within EvalItem content arrays. + + - `image_url: String` + + The URL of the image input. + + - `type: :input_image` + + The type of the image input. Always `input_image`. + + - `:input_image` + + - `detail: String` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `class ResponseInputAudio` + + An audio input to the model. + + - `input_audio: InputAudio{ data, format_}` + + - `data: String` + + Base64-encoded audio data. + + - `format_: :mp3 | :wav` + + The format of the audio data. Currently supported formats are `mp3` and + `wav`. + + - `:mp3` + + - `:wav` + + - `type: :input_audio` + + The type of the input item. Always `input_audio`. + + - `:input_audio` + + - `GraderInputs = Array[GraderInputItem]` + + A list of inputs, each of which may be either an input text, output text, input + image, or input audio object. + + - `String = String` + + A text input to the model. + + - `class ResponseInputText` + + A text input to the model. + + - `class OutputText` + + A text output from the model. + + - `text: String` + + The text output from the model. + + - `type: :output_text` + + The type of the output text. Always `output_text`. + + - `:output_text` + + - `class InputImage` + + An image input block used within EvalItem content arrays. + + - `image_url: String` + + The URL of the image input. + + - `type: :input_image` + + The type of the image input. Always `input_image`. + + - `:input_image` + + - `detail: String` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `class ResponseInputAudio` + + An audio input to the model. + + - `role: :user | :assistant | :system | :developer` + + The role of the message input. One of `user`, `assistant`, `system`, or + `developer`. + + - `:user` + + - `:assistant` + + - `:system` + + - `:developer` + + - `type: :message` + + The type of the message input. Always `message`. + + - `:message` + + - `model: String` + + The model to use for the evaluation. + + - `name: String` + + The name of the grader. + + - `type: :score_model` + + The object type, which is always `score_model`. + + - `:score_model` + + - `range: Array[Float]` + + The range of the score. Defaults to `[0, 1]`. + + - `sampling_params: SamplingParams{ max_completions_tokens, reasoning_effort, seed, 2 more}` + + The sampling parameters for the model. + + - `max_completions_tokens: Integer` + + The maximum number of tokens the grader model may generate in its response. + + - `reasoning_effort: ReasoningEffort` + + Constrains effort on reasoning for + [reasoning models](https://platform.openai.com/docs/guides/reasoning). + Currently supported values are `none`, `minimal`, `low`, `medium`, `high`, and `xhigh`. Reducing + reasoning effort can result in faster responses and fewer tokens used + on reasoning in a response. + + - `gpt-5.1` defaults to `none`, which does not perform reasoning. The supported reasoning values for `gpt-5.1` are `none`, `low`, `medium`, and `high`. Tool calls are supported for all reasoning values in gpt-5.1. + - All models before `gpt-5.1` default to `medium` reasoning effort, and do not support `none`. + - The `gpt-5-pro` model defaults to (and only supports) `high` reasoning effort. + - `xhigh` is supported for all models after `gpt-5.1-codex-max`. + + - `:none` + + - `:minimal` + + - `:low` + + - `:medium` + + - `:high` + + - `:xhigh` + + - `seed: Integer` + + A seed value to initialize the randomness, during sampling. + + - `temperature: Float` + + A higher temperature increases randomness in the outputs. + + - `top_p: Float` + + An alternative to temperature for nucleus sampling; 1.0 includes all tokens. + + - `class MultiGrader` + + A MultiGrader object combines the output of multiple graders to produce a single score. + + - `calculate_output: String` + + A formula to calculate the output based on grader results. + + - `graders: StringCheckGrader | TextSimilarityGrader | PythonGrader | 2 more` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `class StringCheckGrader` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `class TextSimilarityGrader` + + A TextSimilarityGrader object which grades text based on similarity metrics. + + - `class PythonGrader` + + A PythonGrader object that runs a python script on the input. + + - `class ScoreModelGrader` + + A ScoreModelGrader object that uses a model to assign a score to the input. + + - `class LabelModelGrader` + + A LabelModelGrader object which uses a model to assign labels to each item + in the evaluation. + + - `input: Array[Input{ content, role, type}]` + + - `content: String | ResponseInputText | OutputText{ text, type} | 3 more` + + Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items. + + - `String = String` + + A text input to the model. + + - `class ResponseInputText` + + A text input to the model. + + - `class OutputText` + + A text output from the model. + + - `text: String` + + The text output from the model. + + - `type: :output_text` + + The type of the output text. Always `output_text`. + + - `:output_text` + + - `class InputImage` + + An image input block used within EvalItem content arrays. + + - `image_url: String` + + The URL of the image input. + + - `type: :input_image` + + The type of the image input. Always `input_image`. + + - `:input_image` + + - `detail: String` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `class ResponseInputAudio` + + An audio input to the model. + + - `GraderInputs = Array[GraderInputItem]` + + A list of inputs, each of which may be either an input text, output text, input + image, or input audio object. + + - `role: :user | :assistant | :system | :developer` + + The role of the message input. One of `user`, `assistant`, `system`, or + `developer`. + + - `:user` + + - `:assistant` + + - `:system` + + - `:developer` + + - `type: :message` + + The type of the message input. Always `message`. + + - `:message` + + - `labels: Array[String]` + + The labels to assign to each item in the evaluation. + + - `model: String` + + The model to use for the evaluation. Must support structured outputs. + + - `name: String` + + The name of the grader. + + - `passing_labels: Array[String]` + + The labels that indicate a passing result. Must be a subset of labels. + + - `type: :label_model` + + The object type, which is always `label_model`. + + - `:label_model` + + - `name: String` + + The name of the grader. + + - `type: :multi` + + The object type, which is always `multi`. + + - `:multi` + + - `hyperparameters: ReinforcementHyperparameters` + + The hyperparameters used for the reinforcement fine-tuning job. + + - `batch_size: :auto | Integer` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `BatchSize = :auto` + + - `:auto` + + - `Integer = Integer` + + - `compute_multiplier: :auto | Float` + + Multiplier on amount of compute used for exploring search space during training. + + - `ComputeMultiplier = :auto` + + - `:auto` + + - `Float = Float` + + - `eval_interval: :auto | Integer` + + The number of training steps between evaluation runs. + + - `EvalInterval = :auto` + + - `:auto` + + - `Integer = Integer` + + - `eval_samples: :auto | Integer` + + Number of evaluation samples to generate per training step. + + - `EvalSamples = :auto` + + - `:auto` + + - `Integer = Integer` + + - `learning_rate_multiplier: :auto | Float` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `LearningRateMultiplier = :auto` + + - `:auto` + + - `Float = Float` + + - `n_epochs: :auto | Integer` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `NEpochs = :auto` + + - `:auto` + + - `Integer = Integer` + + - `reasoning_effort: :default | :low | :medium | :high` + + Level of reasoning effort. + + - `:default` + + - `:low` + + - `:medium` + + - `:high` + + - `supervised: SupervisedMethod` + + Configuration for the supervised fine-tuning method. + + - `hyperparameters: SupervisedHyperparameters` + + The hyperparameters used for the fine-tuning job. + + - `batch_size: :auto | Integer` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `BatchSize = :auto` + + - `:auto` + + - `Integer = Integer` + + - `learning_rate_multiplier: :auto | Float` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `LearningRateMultiplier = :auto` + + - `:auto` + + - `Float = Float` + + - `n_epochs: :auto | Integer` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `NEpochs = :auto` + + - `:auto` + + - `Integer = Integer` + +### Example + +```ruby +require "openai" + +openai = OpenAI::Client.new(api_key: "My API Key") + +fine_tuning_job = openai.fine_tuning.jobs.create(model: :"gpt-4o-mini", training_file: "file-abc123") + +puts(fine_tuning_job) +``` + +#### Response + +```json +{ + "id": "id", + "created_at": 0, + "error": { + "code": "code", + "message": "message", + "param": "param" + }, + "fine_tuned_model": "fine_tuned_model", + "finished_at": 0, + "hyperparameters": { + "batch_size": "auto", + "learning_rate_multiplier": "auto", + "n_epochs": "auto" + }, + "model": "model", + "object": "fine_tuning.job", + "organization_id": "organization_id", + "result_files": [ + "file-abc123" + ], + "seed": 0, + "status": "validating_files", + "trained_tokens": 0, + "training_file": "training_file", + "validation_file": "validation_file", + "estimated_finish": 0, + "integrations": [ + { + "type": "wandb", + "wandb": { + "project": "my-wandb-project", + "entity": "entity", + "name": "name", + "tags": [ + "custom-tag" + ] + } + } + ], + "metadata": { + "foo": "string" + }, + "method": { + "type": "supervised", + "dpo": { + "hyperparameters": { + "batch_size": "auto", + "beta": "auto", + "learning_rate_multiplier": "auto", + "n_epochs": "auto" + } + }, + "reinforcement": { + "grader": { + "input": "input", + "name": "name", + "operation": "eq", + "reference": "reference", + "type": "string_check" + }, + "hyperparameters": { + "batch_size": "auto", + "compute_multiplier": "auto", + "eval_interval": "auto", + "eval_samples": "auto", + "learning_rate_multiplier": "auto", + "n_epochs": "auto", + "reasoning_effort": "default" + } + }, + "supervised": { + "hyperparameters": { + "batch_size": "auto", + "learning_rate_multiplier": "auto", + "n_epochs": "auto" + } + } + } +} +``` + +## List fine-tuning jobs + +`fine_tuning.jobs.list(**kwargs) -> CursorPage` + +**get** `/fine_tuning/jobs` + +List your organization's fine-tuning jobs + +### Parameters + +- `after: String` + + Identifier for the last job from the previous pagination request. + +- `limit: Integer` + + Number of fine-tuning jobs to retrieve. + +- `metadata: Hash[Symbol, String]` + + Optional metadata filter. To filter, use the syntax `metadata[k]=v`. Alternatively, set `metadata=null` to indicate no metadata. + +### Returns + +- `class FineTuningJob` + + The `fine_tuning.job` object represents a fine-tuning job that has been created through the API. + + - `id: String` + + The object identifier, which can be referenced in the API endpoints. + + - `created_at: Integer` + + The Unix timestamp (in seconds) for when the fine-tuning job was created. + + - `error: Error{ code, message, param}` + + For fine-tuning jobs that have `failed`, this will contain more information on the cause of the failure. + + - `code: String` + + A machine-readable error code. + + - `message: String` + + A human-readable error message. + + - `param: String` + + The parameter that was invalid, usually `training_file` or `validation_file`. This field will be null if the failure was not parameter-specific. + + - `fine_tuned_model: String` + + The name of the fine-tuned model that is being created. The value will be null if the fine-tuning job is still running. + + - `finished_at: Integer` + + 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. + + - `hyperparameters: Hyperparameters{ batch_size, learning_rate_multiplier, n_epochs}` + + The hyperparameters used for the fine-tuning job. This value will only be returned when running `supervised` jobs. + + - `batch_size: :auto | Integer` + + Number of examples in each batch. A larger batch size means that model parameters + are updated less frequently, but with lower variance. + + - `BatchSize = :auto` + + - `:auto` + + - `Integer = Integer` + + - `learning_rate_multiplier: :auto | Float` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid + overfitting. + + - `LearningRateMultiplier = :auto` + + - `:auto` + + - `Float = Float` + + - `n_epochs: :auto | Integer` + + The number of epochs to train the model for. An epoch refers to one full cycle + through the training dataset. + + - `NEpochs = :auto` + + - `:auto` + + - `Integer = Integer` + + - `model: String` + + The base model that is being fine-tuned. + + - `object: :"fine_tuning.job"` + + The object type, which is always "fine_tuning.job". + + - `:"fine_tuning.job"` + + - `organization_id: String` + + The organization that owns the fine-tuning job. + + - `result_files: Array[String]` + + The compiled results file ID(s) for the fine-tuning job. You can retrieve the results with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents). + + - `seed: Integer` + + The seed used for the fine-tuning job. + + - `status: :validating_files | :queued | :running | 3 more` + + The current status of the fine-tuning job, which can be either `validating_files`, `queued`, `running`, `succeeded`, `failed`, or `cancelled`. + + - `:validating_files` + + - `:queued` + + - `:running` + + - `:succeeded` + + - `:failed` + + - `:cancelled` + + - `trained_tokens: Integer` + + 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. + + - `training_file: String` + + The file ID used for training. You can retrieve the training data with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents). + + - `validation_file: String` + + The file ID used for validation. You can retrieve the validation results with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents). + + - `estimated_finish: Integer` + + 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. + + - `integrations: Array[FineTuningJobWandbIntegrationObject]` + + A list of integrations to enable for this fine-tuning job. + + - `type: :wandb` + + The type of the integration being enabled for the fine-tuning job + + - `:wandb` + + - `wandb: FineTuningJobWandbIntegration` + + The settings for your integration with Weights and Biases. This payload specifies the project that + metrics will be sent to. Optionally, you can set an explicit display name for your run, add tags + to your run, and set a default entity (team, username, etc) to be associated with your run. + + - `project: String` + + The name of the project that the new run will be created under. + + - `entity: String` + + 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 run. If not set, the default entity for the registered WandB API key is used. + + - `name: String` + + A display name to set for the run. If not set, we will use the Job ID as the name. + + - `tags: Array[String]` + + A list of tags to be attached to the newly created run. These tags are passed through directly to WandB. Some + default tags are generated by OpenAI: "openai/finetune", "openai/{base-model}", "openai/{ftjob-abcdef}". + + - `metadata: 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_: Method{ type, dpo, reinforcement, supervised}` + + The method used for fine-tuning. + + - `type: :supervised | :dpo | :reinforcement` + + The type of method. Is either `supervised`, `dpo`, or `reinforcement`. + + - `:supervised` + + - `:dpo` + + - `:reinforcement` + + - `dpo: DpoMethod` + + Configuration for the DPO fine-tuning method. + + - `hyperparameters: DpoHyperparameters` + + The hyperparameters used for the DPO fine-tuning job. + + - `batch_size: :auto | Integer` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `BatchSize = :auto` + + - `:auto` + + - `Integer = Integer` + + - `beta: :auto | Float` + + The beta value for the DPO method. A higher beta value will increase the weight of the penalty between the policy and reference model. + + - `Beta = :auto` + + - `:auto` + + - `Float = Float` + + - `learning_rate_multiplier: :auto | Float` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `LearningRateMultiplier = :auto` + + - `:auto` + + - `Float = Float` + + - `n_epochs: :auto | Integer` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `NEpochs = :auto` + + - `:auto` + + - `Integer = Integer` + + - `reinforcement: ReinforcementMethod` + + Configuration for the reinforcement fine-tuning method. + + - `grader: StringCheckGrader | TextSimilarityGrader | PythonGrader | 2 more` + + The grader used for the fine-tuning job. + + - `class StringCheckGrader` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `input: String` + + The input text. This may include template strings. + + - `name: String` + + The name of the grader. + + - `operation: :eq | :ne | :like | :ilike` + + The string check operation to perform. One of `eq`, `ne`, `like`, or `ilike`. + + - `:eq` + + - `:ne` + + - `:like` + + - `:ilike` + + - `reference: String` + + The reference text. This may include template strings. + + - `type: :string_check` + + The object type, which is always `string_check`. + + - `:string_check` + + - `class TextSimilarityGrader` + + A TextSimilarityGrader object which grades text based on similarity metrics. + + - `evaluation_metric: :cosine | :fuzzy_match | :bleu | 8 more` + + The evaluation metric to use. One of `cosine`, `fuzzy_match`, `bleu`, + `gleu`, `meteor`, `rouge_1`, `rouge_2`, `rouge_3`, `rouge_4`, `rouge_5`, + or `rouge_l`. + + - `:cosine` + + - `:fuzzy_match` + + - `:bleu` + + - `:gleu` + + - `:meteor` + + - `:rouge_1` + + - `:rouge_2` + + - `:rouge_3` + + - `:rouge_4` + + - `:rouge_5` + + - `:rouge_l` + + - `input: String` + + The text being graded. + + - `name: String` + + The name of the grader. + + - `reference: String` + + The text being graded against. + + - `type: :text_similarity` + + The type of grader. + + - `:text_similarity` + + - `class PythonGrader` + + A PythonGrader object that runs a python script on the input. + + - `name: String` + + The name of the grader. + + - `source: String` + + The source code of the python script. + + - `type: :python` + + The object type, which is always `python`. + + - `:python` + + - `image_tag: String` + + The image tag to use for the python script. + + - `class ScoreModelGrader` + + A ScoreModelGrader object that uses a model to assign a score to the input. + + - `input: Array[Input{ content, role, type}]` + + The input messages evaluated by the grader. Supports text, output text, input image, and input audio content blocks, and may include template strings. + + - `content: String | ResponseInputText | OutputText{ text, type} | 3 more` + + Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items. + + - `String = String` + + A text input to the model. + + - `class ResponseInputText` + + A text input to the model. + + - `text: String` + + The text input to the model. + + - `type: :input_text` + + The type of the input item. Always `input_text`. + + - `:input_text` + + - `class OutputText` + + A text output from the model. + + - `text: String` + + The text output from the model. + + - `type: :output_text` + + The type of the output text. Always `output_text`. + + - `:output_text` + + - `class InputImage` + + An image input block used within EvalItem content arrays. + + - `image_url: String` + + The URL of the image input. + + - `type: :input_image` + + The type of the image input. Always `input_image`. + + - `:input_image` + + - `detail: String` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `class ResponseInputAudio` + + An audio input to the model. + + - `input_audio: InputAudio{ data, format_}` + + - `data: String` + + Base64-encoded audio data. + + - `format_: :mp3 | :wav` + + The format of the audio data. Currently supported formats are `mp3` and + `wav`. + + - `:mp3` + + - `:wav` + + - `type: :input_audio` + + The type of the input item. Always `input_audio`. + + - `:input_audio` + + - `GraderInputs = Array[GraderInputItem]` + + A list of inputs, each of which may be either an input text, output text, input + image, or input audio object. + + - `String = String` + + A text input to the model. + + - `class ResponseInputText` + + A text input to the model. + + - `class OutputText` + + A text output from the model. + + - `text: String` + + The text output from the model. + + - `type: :output_text` + + The type of the output text. Always `output_text`. + + - `:output_text` + + - `class InputImage` + + An image input block used within EvalItem content arrays. + + - `image_url: String` + + The URL of the image input. + + - `type: :input_image` + + The type of the image input. Always `input_image`. + + - `:input_image` + + - `detail: String` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `class ResponseInputAudio` + + An audio input to the model. + + - `role: :user | :assistant | :system | :developer` + + The role of the message input. One of `user`, `assistant`, `system`, or + `developer`. + + - `:user` + + - `:assistant` + + - `:system` + + - `:developer` + + - `type: :message` + + The type of the message input. Always `message`. + + - `:message` + + - `model: String` + + The model to use for the evaluation. + + - `name: String` + + The name of the grader. + + - `type: :score_model` + + The object type, which is always `score_model`. + + - `:score_model` + + - `range: Array[Float]` + + The range of the score. Defaults to `[0, 1]`. + + - `sampling_params: SamplingParams{ max_completions_tokens, reasoning_effort, seed, 2 more}` + + The sampling parameters for the model. + + - `max_completions_tokens: Integer` + + The maximum number of tokens the grader model may generate in its response. + + - `reasoning_effort: ReasoningEffort` + + Constrains effort on reasoning for + [reasoning models](https://platform.openai.com/docs/guides/reasoning). + Currently supported values are `none`, `minimal`, `low`, `medium`, `high`, and `xhigh`. Reducing + reasoning effort can result in faster responses and fewer tokens used + on reasoning in a response. + + - `gpt-5.1` defaults to `none`, which does not perform reasoning. The supported reasoning values for `gpt-5.1` are `none`, `low`, `medium`, and `high`. Tool calls are supported for all reasoning values in gpt-5.1. + - All models before `gpt-5.1` default to `medium` reasoning effort, and do not support `none`. + - The `gpt-5-pro` model defaults to (and only supports) `high` reasoning effort. + - `xhigh` is supported for all models after `gpt-5.1-codex-max`. + + - `:none` + + - `:minimal` + + - `:low` + + - `:medium` + + - `:high` + + - `:xhigh` + + - `seed: Integer` + + A seed value to initialize the randomness, during sampling. + + - `temperature: Float` + + A higher temperature increases randomness in the outputs. + + - `top_p: Float` + + An alternative to temperature for nucleus sampling; 1.0 includes all tokens. + + - `class MultiGrader` + + A MultiGrader object combines the output of multiple graders to produce a single score. + + - `calculate_output: String` + + A formula to calculate the output based on grader results. + + - `graders: StringCheckGrader | TextSimilarityGrader | PythonGrader | 2 more` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `class StringCheckGrader` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `class TextSimilarityGrader` + + A TextSimilarityGrader object which grades text based on similarity metrics. + + - `class PythonGrader` + + A PythonGrader object that runs a python script on the input. + + - `class ScoreModelGrader` + + A ScoreModelGrader object that uses a model to assign a score to the input. + + - `class LabelModelGrader` + + A LabelModelGrader object which uses a model to assign labels to each item + in the evaluation. + + - `input: Array[Input{ content, role, type}]` + + - `content: String | ResponseInputText | OutputText{ text, type} | 3 more` + + Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items. + + - `String = String` + + A text input to the model. + + - `class ResponseInputText` + + A text input to the model. + + - `class OutputText` + + A text output from the model. + + - `text: String` + + The text output from the model. + + - `type: :output_text` + + The type of the output text. Always `output_text`. + + - `:output_text` + + - `class InputImage` + + An image input block used within EvalItem content arrays. + + - `image_url: String` + + The URL of the image input. + + - `type: :input_image` + + The type of the image input. Always `input_image`. + + - `:input_image` + + - `detail: String` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `class ResponseInputAudio` + + An audio input to the model. + + - `GraderInputs = Array[GraderInputItem]` + + A list of inputs, each of which may be either an input text, output text, input + image, or input audio object. + + - `role: :user | :assistant | :system | :developer` + + The role of the message input. One of `user`, `assistant`, `system`, or + `developer`. + + - `:user` + + - `:assistant` + + - `:system` + + - `:developer` + + - `type: :message` + + The type of the message input. Always `message`. + + - `:message` + + - `labels: Array[String]` + + The labels to assign to each item in the evaluation. + + - `model: String` + + The model to use for the evaluation. Must support structured outputs. + + - `name: String` + + The name of the grader. + + - `passing_labels: Array[String]` + + The labels that indicate a passing result. Must be a subset of labels. + + - `type: :label_model` + + The object type, which is always `label_model`. + + - `:label_model` + + - `name: String` + + The name of the grader. + + - `type: :multi` + + The object type, which is always `multi`. + + - `:multi` + + - `hyperparameters: ReinforcementHyperparameters` + + The hyperparameters used for the reinforcement fine-tuning job. + + - `batch_size: :auto | Integer` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `BatchSize = :auto` + + - `:auto` + + - `Integer = Integer` + + - `compute_multiplier: :auto | Float` + + Multiplier on amount of compute used for exploring search space during training. + + - `ComputeMultiplier = :auto` + + - `:auto` + + - `Float = Float` + + - `eval_interval: :auto | Integer` + + The number of training steps between evaluation runs. + + - `EvalInterval = :auto` + + - `:auto` + + - `Integer = Integer` + + - `eval_samples: :auto | Integer` + + Number of evaluation samples to generate per training step. + + - `EvalSamples = :auto` + + - `:auto` + + - `Integer = Integer` + + - `learning_rate_multiplier: :auto | Float` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `LearningRateMultiplier = :auto` + + - `:auto` + + - `Float = Float` + + - `n_epochs: :auto | Integer` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `NEpochs = :auto` + + - `:auto` + + - `Integer = Integer` + + - `reasoning_effort: :default | :low | :medium | :high` + + Level of reasoning effort. + + - `:default` + + - `:low` + + - `:medium` + + - `:high` + + - `supervised: SupervisedMethod` + + Configuration for the supervised fine-tuning method. + + - `hyperparameters: SupervisedHyperparameters` + + The hyperparameters used for the fine-tuning job. + + - `batch_size: :auto | Integer` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `BatchSize = :auto` + + - `:auto` + + - `Integer = Integer` + + - `learning_rate_multiplier: :auto | Float` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `LearningRateMultiplier = :auto` + + - `:auto` + + - `Float = Float` + + - `n_epochs: :auto | Integer` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `NEpochs = :auto` + + - `:auto` + + - `Integer = Integer` + +### Example + +```ruby +require "openai" + +openai = OpenAI::Client.new(api_key: "My API Key") + +page = openai.fine_tuning.jobs.list + +puts(page) +``` + +#### Response + +```json +{ + "data": [ + { + "id": "id", + "created_at": 0, + "error": { + "code": "code", + "message": "message", + "param": "param" + }, + "fine_tuned_model": "fine_tuned_model", + "finished_at": 0, + "hyperparameters": { + "batch_size": "auto", + "learning_rate_multiplier": "auto", + "n_epochs": "auto" + }, + "model": "model", + "object": "fine_tuning.job", + "organization_id": "organization_id", + "result_files": [ + "file-abc123" + ], + "seed": 0, + "status": "validating_files", + "trained_tokens": 0, + "training_file": "training_file", + "validation_file": "validation_file", + "estimated_finish": 0, + "integrations": [ + { + "type": "wandb", + "wandb": { + "project": "my-wandb-project", + "entity": "entity", + "name": "name", + "tags": [ + "custom-tag" + ] + } + } + ], + "metadata": { + "foo": "string" + }, + "method": { + "type": "supervised", + "dpo": { + "hyperparameters": { + "batch_size": "auto", + "beta": "auto", + "learning_rate_multiplier": "auto", + "n_epochs": "auto" + } + }, + "reinforcement": { + "grader": { + "input": "input", + "name": "name", + "operation": "eq", + "reference": "reference", + "type": "string_check" + }, + "hyperparameters": { + "batch_size": "auto", + "compute_multiplier": "auto", + "eval_interval": "auto", + "eval_samples": "auto", + "learning_rate_multiplier": "auto", + "n_epochs": "auto", + "reasoning_effort": "default" + } + }, + "supervised": { + "hyperparameters": { + "batch_size": "auto", + "learning_rate_multiplier": "auto", + "n_epochs": "auto" + } + } + } + } + ], + "has_more": true, + "object": "list" +} +``` + +## Retrieve fine-tuning job + +`fine_tuning.jobs.retrieve(fine_tuning_job_id) -> FineTuningJob` + +**get** `/fine_tuning/jobs/{fine_tuning_job_id}` + +Get info about a fine-tuning job. + +[Learn more about fine-tuning](https://platform.openai.com/docs/guides/model-optimization) + +### Parameters + +- `fine_tuning_job_id: String` + +### Returns + +- `class FineTuningJob` + + The `fine_tuning.job` object represents a fine-tuning job that has been created through the API. + + - `id: String` + + The object identifier, which can be referenced in the API endpoints. + + - `created_at: Integer` + + The Unix timestamp (in seconds) for when the fine-tuning job was created. + + - `error: Error{ code, message, param}` + + For fine-tuning jobs that have `failed`, this will contain more information on the cause of the failure. + + - `code: String` + + A machine-readable error code. + + - `message: String` + + A human-readable error message. + + - `param: String` + + The parameter that was invalid, usually `training_file` or `validation_file`. This field will be null if the failure was not parameter-specific. + + - `fine_tuned_model: String` + + The name of the fine-tuned model that is being created. The value will be null if the fine-tuning job is still running. + + - `finished_at: Integer` + + 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. + + - `hyperparameters: Hyperparameters{ batch_size, learning_rate_multiplier, n_epochs}` + + The hyperparameters used for the fine-tuning job. This value will only be returned when running `supervised` jobs. + + - `batch_size: :auto | Integer` + + Number of examples in each batch. A larger batch size means that model parameters + are updated less frequently, but with lower variance. + + - `BatchSize = :auto` + + - `:auto` + + - `Integer = Integer` + + - `learning_rate_multiplier: :auto | Float` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid + overfitting. + + - `LearningRateMultiplier = :auto` + + - `:auto` + + - `Float = Float` + + - `n_epochs: :auto | Integer` + + The number of epochs to train the model for. An epoch refers to one full cycle + through the training dataset. + + - `NEpochs = :auto` + + - `:auto` + + - `Integer = Integer` + + - `model: String` + + The base model that is being fine-tuned. + + - `object: :"fine_tuning.job"` + + The object type, which is always "fine_tuning.job". + + - `:"fine_tuning.job"` + + - `organization_id: String` + + The organization that owns the fine-tuning job. + + - `result_files: Array[String]` + + The compiled results file ID(s) for the fine-tuning job. You can retrieve the results with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents). + + - `seed: Integer` + + The seed used for the fine-tuning job. + + - `status: :validating_files | :queued | :running | 3 more` + + The current status of the fine-tuning job, which can be either `validating_files`, `queued`, `running`, `succeeded`, `failed`, or `cancelled`. + + - `:validating_files` + + - `:queued` + + - `:running` + + - `:succeeded` + + - `:failed` + + - `:cancelled` + + - `trained_tokens: Integer` + + 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. + + - `training_file: String` + + The file ID used for training. You can retrieve the training data with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents). + + - `validation_file: String` + + The file ID used for validation. You can retrieve the validation results with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents). + + - `estimated_finish: Integer` + + 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. + + - `integrations: Array[FineTuningJobWandbIntegrationObject]` + + A list of integrations to enable for this fine-tuning job. + + - `type: :wandb` + + The type of the integration being enabled for the fine-tuning job + + - `:wandb` + + - `wandb: FineTuningJobWandbIntegration` + + The settings for your integration with Weights and Biases. This payload specifies the project that + metrics will be sent to. Optionally, you can set an explicit display name for your run, add tags + to your run, and set a default entity (team, username, etc) to be associated with your run. + + - `project: String` + + The name of the project that the new run will be created under. + + - `entity: String` + + 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 run. If not set, the default entity for the registered WandB API key is used. + + - `name: String` + + A display name to set for the run. If not set, we will use the Job ID as the name. + + - `tags: Array[String]` + + A list of tags to be attached to the newly created run. These tags are passed through directly to WandB. Some + default tags are generated by OpenAI: "openai/finetune", "openai/{base-model}", "openai/{ftjob-abcdef}". + + - `metadata: 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_: Method{ type, dpo, reinforcement, supervised}` + + The method used for fine-tuning. + + - `type: :supervised | :dpo | :reinforcement` + + The type of method. Is either `supervised`, `dpo`, or `reinforcement`. + + - `:supervised` + + - `:dpo` + + - `:reinforcement` + + - `dpo: DpoMethod` + + Configuration for the DPO fine-tuning method. + + - `hyperparameters: DpoHyperparameters` + + The hyperparameters used for the DPO fine-tuning job. + + - `batch_size: :auto | Integer` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `BatchSize = :auto` + + - `:auto` + + - `Integer = Integer` + + - `beta: :auto | Float` + + The beta value for the DPO method. A higher beta value will increase the weight of the penalty between the policy and reference model. + + - `Beta = :auto` + + - `:auto` + + - `Float = Float` + + - `learning_rate_multiplier: :auto | Float` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `LearningRateMultiplier = :auto` + + - `:auto` + + - `Float = Float` + + - `n_epochs: :auto | Integer` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `NEpochs = :auto` + + - `:auto` + + - `Integer = Integer` + + - `reinforcement: ReinforcementMethod` + + Configuration for the reinforcement fine-tuning method. + + - `grader: StringCheckGrader | TextSimilarityGrader | PythonGrader | 2 more` + + The grader used for the fine-tuning job. + + - `class StringCheckGrader` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `input: String` + + The input text. This may include template strings. + + - `name: String` + + The name of the grader. + + - `operation: :eq | :ne | :like | :ilike` + + The string check operation to perform. One of `eq`, `ne`, `like`, or `ilike`. + + - `:eq` + + - `:ne` + + - `:like` + + - `:ilike` + + - `reference: String` + + The reference text. This may include template strings. + + - `type: :string_check` + + The object type, which is always `string_check`. + + - `:string_check` + + - `class TextSimilarityGrader` + + A TextSimilarityGrader object which grades text based on similarity metrics. + + - `evaluation_metric: :cosine | :fuzzy_match | :bleu | 8 more` + + The evaluation metric to use. One of `cosine`, `fuzzy_match`, `bleu`, + `gleu`, `meteor`, `rouge_1`, `rouge_2`, `rouge_3`, `rouge_4`, `rouge_5`, + or `rouge_l`. + + - `:cosine` + + - `:fuzzy_match` + + - `:bleu` + + - `:gleu` + + - `:meteor` + + - `:rouge_1` + + - `:rouge_2` + + - `:rouge_3` + + - `:rouge_4` + + - `:rouge_5` + + - `:rouge_l` + + - `input: String` + + The text being graded. + + - `name: String` + + The name of the grader. + + - `reference: String` + + The text being graded against. + + - `type: :text_similarity` + + The type of grader. + + - `:text_similarity` + + - `class PythonGrader` + + A PythonGrader object that runs a python script on the input. + + - `name: String` + + The name of the grader. + + - `source: String` + + The source code of the python script. + + - `type: :python` + + The object type, which is always `python`. + + - `:python` + + - `image_tag: String` + + The image tag to use for the python script. + + - `class ScoreModelGrader` + + A ScoreModelGrader object that uses a model to assign a score to the input. + + - `input: Array[Input{ content, role, type}]` + + The input messages evaluated by the grader. Supports text, output text, input image, and input audio content blocks, and may include template strings. + + - `content: String | ResponseInputText | OutputText{ text, type} | 3 more` + + Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items. + + - `String = String` + + A text input to the model. + + - `class ResponseInputText` + + A text input to the model. + + - `text: String` + + The text input to the model. + + - `type: :input_text` + + The type of the input item. Always `input_text`. + + - `:input_text` + + - `class OutputText` + + A text output from the model. + + - `text: String` + + The text output from the model. + + - `type: :output_text` + + The type of the output text. Always `output_text`. + + - `:output_text` + + - `class InputImage` + + An image input block used within EvalItem content arrays. + + - `image_url: String` + + The URL of the image input. + + - `type: :input_image` + + The type of the image input. Always `input_image`. + + - `:input_image` + + - `detail: String` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `class ResponseInputAudio` + + An audio input to the model. + + - `input_audio: InputAudio{ data, format_}` + + - `data: String` + + Base64-encoded audio data. + + - `format_: :mp3 | :wav` + + The format of the audio data. Currently supported formats are `mp3` and + `wav`. + + - `:mp3` + + - `:wav` + + - `type: :input_audio` + + The type of the input item. Always `input_audio`. + + - `:input_audio` + + - `GraderInputs = Array[GraderInputItem]` + + A list of inputs, each of which may be either an input text, output text, input + image, or input audio object. + + - `String = String` + + A text input to the model. + + - `class ResponseInputText` + + A text input to the model. + + - `class OutputText` + + A text output from the model. + + - `text: String` + + The text output from the model. + + - `type: :output_text` + + The type of the output text. Always `output_text`. + + - `:output_text` + + - `class InputImage` + + An image input block used within EvalItem content arrays. + + - `image_url: String` + + The URL of the image input. + + - `type: :input_image` + + The type of the image input. Always `input_image`. + + - `:input_image` + + - `detail: String` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `class ResponseInputAudio` + + An audio input to the model. + + - `role: :user | :assistant | :system | :developer` + + The role of the message input. One of `user`, `assistant`, `system`, or + `developer`. + + - `:user` + + - `:assistant` + + - `:system` + + - `:developer` + + - `type: :message` + + The type of the message input. Always `message`. + + - `:message` + + - `model: String` + + The model to use for the evaluation. + + - `name: String` + + The name of the grader. + + - `type: :score_model` + + The object type, which is always `score_model`. + + - `:score_model` + + - `range: Array[Float]` + + The range of the score. Defaults to `[0, 1]`. + + - `sampling_params: SamplingParams{ max_completions_tokens, reasoning_effort, seed, 2 more}` + + The sampling parameters for the model. + + - `max_completions_tokens: Integer` + + The maximum number of tokens the grader model may generate in its response. + + - `reasoning_effort: ReasoningEffort` + + Constrains effort on reasoning for + [reasoning models](https://platform.openai.com/docs/guides/reasoning). + Currently supported values are `none`, `minimal`, `low`, `medium`, `high`, and `xhigh`. Reducing + reasoning effort can result in faster responses and fewer tokens used + on reasoning in a response. + + - `gpt-5.1` defaults to `none`, which does not perform reasoning. The supported reasoning values for `gpt-5.1` are `none`, `low`, `medium`, and `high`. Tool calls are supported for all reasoning values in gpt-5.1. + - All models before `gpt-5.1` default to `medium` reasoning effort, and do not support `none`. + - The `gpt-5-pro` model defaults to (and only supports) `high` reasoning effort. + - `xhigh` is supported for all models after `gpt-5.1-codex-max`. + + - `:none` + + - `:minimal` + + - `:low` + + - `:medium` + + - `:high` + + - `:xhigh` + + - `seed: Integer` + + A seed value to initialize the randomness, during sampling. + + - `temperature: Float` + + A higher temperature increases randomness in the outputs. + + - `top_p: Float` + + An alternative to temperature for nucleus sampling; 1.0 includes all tokens. + + - `class MultiGrader` + + A MultiGrader object combines the output of multiple graders to produce a single score. + + - `calculate_output: String` + + A formula to calculate the output based on grader results. + + - `graders: StringCheckGrader | TextSimilarityGrader | PythonGrader | 2 more` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `class StringCheckGrader` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `class TextSimilarityGrader` + + A TextSimilarityGrader object which grades text based on similarity metrics. + + - `class PythonGrader` + + A PythonGrader object that runs a python script on the input. + + - `class ScoreModelGrader` + + A ScoreModelGrader object that uses a model to assign a score to the input. + + - `class LabelModelGrader` + + A LabelModelGrader object which uses a model to assign labels to each item + in the evaluation. + + - `input: Array[Input{ content, role, type}]` + + - `content: String | ResponseInputText | OutputText{ text, type} | 3 more` + + Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items. + + - `String = String` + + A text input to the model. + + - `class ResponseInputText` + + A text input to the model. + + - `class OutputText` + + A text output from the model. + + - `text: String` + + The text output from the model. + + - `type: :output_text` + + The type of the output text. Always `output_text`. + + - `:output_text` + + - `class InputImage` + + An image input block used within EvalItem content arrays. + + - `image_url: String` + + The URL of the image input. + + - `type: :input_image` + + The type of the image input. Always `input_image`. + + - `:input_image` + + - `detail: String` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `class ResponseInputAudio` + + An audio input to the model. + + - `GraderInputs = Array[GraderInputItem]` + + A list of inputs, each of which may be either an input text, output text, input + image, or input audio object. + + - `role: :user | :assistant | :system | :developer` + + The role of the message input. One of `user`, `assistant`, `system`, or + `developer`. + + - `:user` + + - `:assistant` + + - `:system` + + - `:developer` + + - `type: :message` + + The type of the message input. Always `message`. + + - `:message` + + - `labels: Array[String]` + + The labels to assign to each item in the evaluation. + + - `model: String` + + The model to use for the evaluation. Must support structured outputs. + + - `name: String` + + The name of the grader. + + - `passing_labels: Array[String]` + + The labels that indicate a passing result. Must be a subset of labels. + + - `type: :label_model` + + The object type, which is always `label_model`. + + - `:label_model` + + - `name: String` + + The name of the grader. + + - `type: :multi` + + The object type, which is always `multi`. + + - `:multi` + + - `hyperparameters: ReinforcementHyperparameters` + + The hyperparameters used for the reinforcement fine-tuning job. + + - `batch_size: :auto | Integer` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `BatchSize = :auto` + + - `:auto` + + - `Integer = Integer` + + - `compute_multiplier: :auto | Float` + + Multiplier on amount of compute used for exploring search space during training. + + - `ComputeMultiplier = :auto` + + - `:auto` + + - `Float = Float` + + - `eval_interval: :auto | Integer` + + The number of training steps between evaluation runs. + + - `EvalInterval = :auto` + + - `:auto` + + - `Integer = Integer` + + - `eval_samples: :auto | Integer` + + Number of evaluation samples to generate per training step. + + - `EvalSamples = :auto` + + - `:auto` + + - `Integer = Integer` + + - `learning_rate_multiplier: :auto | Float` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `LearningRateMultiplier = :auto` + + - `:auto` + + - `Float = Float` + + - `n_epochs: :auto | Integer` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `NEpochs = :auto` + + - `:auto` + + - `Integer = Integer` + + - `reasoning_effort: :default | :low | :medium | :high` + + Level of reasoning effort. + + - `:default` + + - `:low` + + - `:medium` + + - `:high` + + - `supervised: SupervisedMethod` + + Configuration for the supervised fine-tuning method. + + - `hyperparameters: SupervisedHyperparameters` + + The hyperparameters used for the fine-tuning job. + + - `batch_size: :auto | Integer` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `BatchSize = :auto` + + - `:auto` + + - `Integer = Integer` + + - `learning_rate_multiplier: :auto | Float` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `LearningRateMultiplier = :auto` + + - `:auto` + + - `Float = Float` + + - `n_epochs: :auto | Integer` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `NEpochs = :auto` + + - `:auto` + + - `Integer = Integer` + +### Example + +```ruby +require "openai" + +openai = OpenAI::Client.new(api_key: "My API Key") + +fine_tuning_job = openai.fine_tuning.jobs.retrieve("ft-AF1WoRqd3aJAHsqc9NY7iL8F") + +puts(fine_tuning_job) +``` + +#### Response + +```json +{ + "id": "id", + "created_at": 0, + "error": { + "code": "code", + "message": "message", + "param": "param" + }, + "fine_tuned_model": "fine_tuned_model", + "finished_at": 0, + "hyperparameters": { + "batch_size": "auto", + "learning_rate_multiplier": "auto", + "n_epochs": "auto" + }, + "model": "model", + "object": "fine_tuning.job", + "organization_id": "organization_id", + "result_files": [ + "file-abc123" + ], + "seed": 0, + "status": "validating_files", + "trained_tokens": 0, + "training_file": "training_file", + "validation_file": "validation_file", + "estimated_finish": 0, + "integrations": [ + { + "type": "wandb", + "wandb": { + "project": "my-wandb-project", + "entity": "entity", + "name": "name", + "tags": [ + "custom-tag" + ] + } + } + ], + "metadata": { + "foo": "string" + }, + "method": { + "type": "supervised", + "dpo": { + "hyperparameters": { + "batch_size": "auto", + "beta": "auto", + "learning_rate_multiplier": "auto", + "n_epochs": "auto" + } + }, + "reinforcement": { + "grader": { + "input": "input", + "name": "name", + "operation": "eq", + "reference": "reference", + "type": "string_check" + }, + "hyperparameters": { + "batch_size": "auto", + "compute_multiplier": "auto", + "eval_interval": "auto", + "eval_samples": "auto", + "learning_rate_multiplier": "auto", + "n_epochs": "auto", + "reasoning_effort": "default" + } + }, + "supervised": { + "hyperparameters": { + "batch_size": "auto", + "learning_rate_multiplier": "auto", + "n_epochs": "auto" + } + } + } +} +``` + +## List fine-tuning events + +`fine_tuning.jobs.list_events(fine_tuning_job_id, **kwargs) -> CursorPage` + +**get** `/fine_tuning/jobs/{fine_tuning_job_id}/events` + +Get status updates for a fine-tuning job. + +### Parameters + +- `fine_tuning_job_id: String` + +- `after: String` + + Identifier for the last event from the previous pagination request. + +- `limit: Integer` + + Number of events to retrieve. + +### Returns + +- `class FineTuningJobEvent` + + Fine-tuning job event object + + - `id: String` + + The object identifier. + + - `created_at: Integer` + + The Unix timestamp (in seconds) for when the fine-tuning job was created. + + - `level: :info | :warn | :error` + + The log level of the event. + + - `:info` + + - `:warn` + + - `:error` + + - `message: String` + + The message of the event. + + - `object: :"fine_tuning.job.event"` + + The object type, which is always "fine_tuning.job.event". + + - `:"fine_tuning.job.event"` + + - `data: untyped` + + The data associated with the event. + + - `type: :message | :metrics` + + The type of event. + + - `:message` + + - `:metrics` + +### Example + +```ruby +require "openai" + +openai = OpenAI::Client.new(api_key: "My API Key") + +page = openai.fine_tuning.jobs.list_events("ft-AF1WoRqd3aJAHsqc9NY7iL8F") + +puts(page) +``` + +#### Response + +```json +{ + "data": [ + { + "id": "id", + "created_at": 0, + "level": "info", + "message": "message", + "object": "fine_tuning.job.event", + "data": {}, + "type": "message" + } + ], + "has_more": true, + "object": "list" +} +``` + +## Cancel fine-tuning + +`fine_tuning.jobs.cancel(fine_tuning_job_id) -> FineTuningJob` + +**post** `/fine_tuning/jobs/{fine_tuning_job_id}/cancel` + +Immediately cancel a fine-tune job. + +### Parameters + +- `fine_tuning_job_id: String` + +### Returns + +- `class FineTuningJob` + + The `fine_tuning.job` object represents a fine-tuning job that has been created through the API. + + - `id: String` + + The object identifier, which can be referenced in the API endpoints. + + - `created_at: Integer` + + The Unix timestamp (in seconds) for when the fine-tuning job was created. + + - `error: Error{ code, message, param}` + + For fine-tuning jobs that have `failed`, this will contain more information on the cause of the failure. + + - `code: String` + + A machine-readable error code. + + - `message: String` + + A human-readable error message. + + - `param: String` + + The parameter that was invalid, usually `training_file` or `validation_file`. This field will be null if the failure was not parameter-specific. + + - `fine_tuned_model: String` + + The name of the fine-tuned model that is being created. The value will be null if the fine-tuning job is still running. + + - `finished_at: Integer` + + 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. + + - `hyperparameters: Hyperparameters{ batch_size, learning_rate_multiplier, n_epochs}` + + The hyperparameters used for the fine-tuning job. This value will only be returned when running `supervised` jobs. + + - `batch_size: :auto | Integer` + + Number of examples in each batch. A larger batch size means that model parameters + are updated less frequently, but with lower variance. + + - `BatchSize = :auto` + + - `:auto` + + - `Integer = Integer` + + - `learning_rate_multiplier: :auto | Float` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid + overfitting. + + - `LearningRateMultiplier = :auto` + + - `:auto` + + - `Float = Float` + + - `n_epochs: :auto | Integer` + + The number of epochs to train the model for. An epoch refers to one full cycle + through the training dataset. + + - `NEpochs = :auto` + + - `:auto` + + - `Integer = Integer` + + - `model: String` + + The base model that is being fine-tuned. + + - `object: :"fine_tuning.job"` + + The object type, which is always "fine_tuning.job". + + - `:"fine_tuning.job"` + + - `organization_id: String` + + The organization that owns the fine-tuning job. + + - `result_files: Array[String]` + + The compiled results file ID(s) for the fine-tuning job. You can retrieve the results with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents). + + - `seed: Integer` + + The seed used for the fine-tuning job. + + - `status: :validating_files | :queued | :running | 3 more` + + The current status of the fine-tuning job, which can be either `validating_files`, `queued`, `running`, `succeeded`, `failed`, or `cancelled`. + + - `:validating_files` + + - `:queued` + + - `:running` + + - `:succeeded` + + - `:failed` + + - `:cancelled` + + - `trained_tokens: Integer` + + 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. + + - `training_file: String` + + The file ID used for training. You can retrieve the training data with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents). + + - `validation_file: String` + + The file ID used for validation. You can retrieve the validation results with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents). + + - `estimated_finish: Integer` + + 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. + + - `integrations: Array[FineTuningJobWandbIntegrationObject]` + + A list of integrations to enable for this fine-tuning job. + + - `type: :wandb` + + The type of the integration being enabled for the fine-tuning job + + - `:wandb` + + - `wandb: FineTuningJobWandbIntegration` + + The settings for your integration with Weights and Biases. This payload specifies the project that + metrics will be sent to. Optionally, you can set an explicit display name for your run, add tags + to your run, and set a default entity (team, username, etc) to be associated with your run. + + - `project: String` + + The name of the project that the new run will be created under. + + - `entity: String` + + 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 run. If not set, the default entity for the registered WandB API key is used. + + - `name: String` + + A display name to set for the run. If not set, we will use the Job ID as the name. + + - `tags: Array[String]` + + A list of tags to be attached to the newly created run. These tags are passed through directly to WandB. Some + default tags are generated by OpenAI: "openai/finetune", "openai/{base-model}", "openai/{ftjob-abcdef}". + + - `metadata: 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_: Method{ type, dpo, reinforcement, supervised}` + + The method used for fine-tuning. + + - `type: :supervised | :dpo | :reinforcement` + + The type of method. Is either `supervised`, `dpo`, or `reinforcement`. + + - `:supervised` + + - `:dpo` + + - `:reinforcement` + + - `dpo: DpoMethod` + + Configuration for the DPO fine-tuning method. + + - `hyperparameters: DpoHyperparameters` + + The hyperparameters used for the DPO fine-tuning job. + + - `batch_size: :auto | Integer` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `BatchSize = :auto` + + - `:auto` + + - `Integer = Integer` + + - `beta: :auto | Float` + + The beta value for the DPO method. A higher beta value will increase the weight of the penalty between the policy and reference model. + + - `Beta = :auto` + + - `:auto` + + - `Float = Float` + + - `learning_rate_multiplier: :auto | Float` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `LearningRateMultiplier = :auto` + + - `:auto` + + - `Float = Float` + + - `n_epochs: :auto | Integer` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `NEpochs = :auto` + + - `:auto` + + - `Integer = Integer` + + - `reinforcement: ReinforcementMethod` + + Configuration for the reinforcement fine-tuning method. + + - `grader: StringCheckGrader | TextSimilarityGrader | PythonGrader | 2 more` + + The grader used for the fine-tuning job. + + - `class StringCheckGrader` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `input: String` + + The input text. This may include template strings. + + - `name: String` + + The name of the grader. + + - `operation: :eq | :ne | :like | :ilike` + + The string check operation to perform. One of `eq`, `ne`, `like`, or `ilike`. + + - `:eq` + + - `:ne` + + - `:like` + + - `:ilike` + + - `reference: String` + + The reference text. This may include template strings. + + - `type: :string_check` + + The object type, which is always `string_check`. + + - `:string_check` + + - `class TextSimilarityGrader` + + A TextSimilarityGrader object which grades text based on similarity metrics. + + - `evaluation_metric: :cosine | :fuzzy_match | :bleu | 8 more` + + The evaluation metric to use. One of `cosine`, `fuzzy_match`, `bleu`, + `gleu`, `meteor`, `rouge_1`, `rouge_2`, `rouge_3`, `rouge_4`, `rouge_5`, + or `rouge_l`. + + - `:cosine` + + - `:fuzzy_match` + + - `:bleu` + + - `:gleu` + + - `:meteor` + + - `:rouge_1` + + - `:rouge_2` + + - `:rouge_3` + + - `:rouge_4` + + - `:rouge_5` + + - `:rouge_l` + + - `input: String` + + The text being graded. + + - `name: String` + + The name of the grader. + + - `reference: String` + + The text being graded against. + + - `type: :text_similarity` + + The type of grader. + + - `:text_similarity` + + - `class PythonGrader` + + A PythonGrader object that runs a python script on the input. + + - `name: String` + + The name of the grader. + + - `source: String` + + The source code of the python script. + + - `type: :python` + + The object type, which is always `python`. + + - `:python` + + - `image_tag: String` + + The image tag to use for the python script. + + - `class ScoreModelGrader` + + A ScoreModelGrader object that uses a model to assign a score to the input. + + - `input: Array[Input{ content, role, type}]` + + The input messages evaluated by the grader. Supports text, output text, input image, and input audio content blocks, and may include template strings. + + - `content: String | ResponseInputText | OutputText{ text, type} | 3 more` + + Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items. + + - `String = String` + + A text input to the model. + + - `class ResponseInputText` + + A text input to the model. + + - `text: String` + + The text input to the model. + + - `type: :input_text` + + The type of the input item. Always `input_text`. + + - `:input_text` + + - `class OutputText` + + A text output from the model. + + - `text: String` + + The text output from the model. + + - `type: :output_text` + + The type of the output text. Always `output_text`. + + - `:output_text` + + - `class InputImage` + + An image input block used within EvalItem content arrays. + + - `image_url: String` + + The URL of the image input. + + - `type: :input_image` + + The type of the image input. Always `input_image`. + + - `:input_image` + + - `detail: String` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `class ResponseInputAudio` + + An audio input to the model. + + - `input_audio: InputAudio{ data, format_}` + + - `data: String` + + Base64-encoded audio data. + + - `format_: :mp3 | :wav` + + The format of the audio data. Currently supported formats are `mp3` and + `wav`. + + - `:mp3` + + - `:wav` + + - `type: :input_audio` + + The type of the input item. Always `input_audio`. + + - `:input_audio` + + - `GraderInputs = Array[GraderInputItem]` + + A list of inputs, each of which may be either an input text, output text, input + image, or input audio object. + + - `String = String` + + A text input to the model. + + - `class ResponseInputText` + + A text input to the model. + + - `class OutputText` + + A text output from the model. + + - `text: String` + + The text output from the model. + + - `type: :output_text` + + The type of the output text. Always `output_text`. + + - `:output_text` + + - `class InputImage` + + An image input block used within EvalItem content arrays. + + - `image_url: String` + + The URL of the image input. + + - `type: :input_image` + + The type of the image input. Always `input_image`. + + - `:input_image` + + - `detail: String` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `class ResponseInputAudio` + + An audio input to the model. + + - `role: :user | :assistant | :system | :developer` + + The role of the message input. One of `user`, `assistant`, `system`, or + `developer`. + + - `:user` + + - `:assistant` + + - `:system` + + - `:developer` + + - `type: :message` + + The type of the message input. Always `message`. + + - `:message` + + - `model: String` + + The model to use for the evaluation. + + - `name: String` + + The name of the grader. + + - `type: :score_model` + + The object type, which is always `score_model`. + + - `:score_model` + + - `range: Array[Float]` + + The range of the score. Defaults to `[0, 1]`. + + - `sampling_params: SamplingParams{ max_completions_tokens, reasoning_effort, seed, 2 more}` + + The sampling parameters for the model. + + - `max_completions_tokens: Integer` + + The maximum number of tokens the grader model may generate in its response. + + - `reasoning_effort: ReasoningEffort` + + Constrains effort on reasoning for + [reasoning models](https://platform.openai.com/docs/guides/reasoning). + Currently supported values are `none`, `minimal`, `low`, `medium`, `high`, and `xhigh`. Reducing + reasoning effort can result in faster responses and fewer tokens used + on reasoning in a response. + + - `gpt-5.1` defaults to `none`, which does not perform reasoning. The supported reasoning values for `gpt-5.1` are `none`, `low`, `medium`, and `high`. Tool calls are supported for all reasoning values in gpt-5.1. + - All models before `gpt-5.1` default to `medium` reasoning effort, and do not support `none`. + - The `gpt-5-pro` model defaults to (and only supports) `high` reasoning effort. + - `xhigh` is supported for all models after `gpt-5.1-codex-max`. + + - `:none` + + - `:minimal` + + - `:low` + + - `:medium` + + - `:high` + + - `:xhigh` + + - `seed: Integer` + + A seed value to initialize the randomness, during sampling. + + - `temperature: Float` + + A higher temperature increases randomness in the outputs. + + - `top_p: Float` + + An alternative to temperature for nucleus sampling; 1.0 includes all tokens. + + - `class MultiGrader` + + A MultiGrader object combines the output of multiple graders to produce a single score. + + - `calculate_output: String` + + A formula to calculate the output based on grader results. + + - `graders: StringCheckGrader | TextSimilarityGrader | PythonGrader | 2 more` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `class StringCheckGrader` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `class TextSimilarityGrader` + + A TextSimilarityGrader object which grades text based on similarity metrics. + + - `class PythonGrader` + + A PythonGrader object that runs a python script on the input. + + - `class ScoreModelGrader` + + A ScoreModelGrader object that uses a model to assign a score to the input. + + - `class LabelModelGrader` + + A LabelModelGrader object which uses a model to assign labels to each item + in the evaluation. + + - `input: Array[Input{ content, role, type}]` + + - `content: String | ResponseInputText | OutputText{ text, type} | 3 more` + + Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items. + + - `String = String` + + A text input to the model. + + - `class ResponseInputText` + + A text input to the model. + + - `class OutputText` + + A text output from the model. + + - `text: String` + + The text output from the model. + + - `type: :output_text` + + The type of the output text. Always `output_text`. + + - `:output_text` + + - `class InputImage` + + An image input block used within EvalItem content arrays. + + - `image_url: String` + + The URL of the image input. + + - `type: :input_image` + + The type of the image input. Always `input_image`. + + - `:input_image` + + - `detail: String` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `class ResponseInputAudio` + + An audio input to the model. + + - `GraderInputs = Array[GraderInputItem]` + + A list of inputs, each of which may be either an input text, output text, input + image, or input audio object. + + - `role: :user | :assistant | :system | :developer` + + The role of the message input. One of `user`, `assistant`, `system`, or + `developer`. + + - `:user` + + - `:assistant` + + - `:system` + + - `:developer` + + - `type: :message` + + The type of the message input. Always `message`. + + - `:message` + + - `labels: Array[String]` + + The labels to assign to each item in the evaluation. + + - `model: String` + + The model to use for the evaluation. Must support structured outputs. + + - `name: String` + + The name of the grader. + + - `passing_labels: Array[String]` + + The labels that indicate a passing result. Must be a subset of labels. + + - `type: :label_model` + + The object type, which is always `label_model`. + + - `:label_model` + + - `name: String` + + The name of the grader. + + - `type: :multi` + + The object type, which is always `multi`. + + - `:multi` + + - `hyperparameters: ReinforcementHyperparameters` + + The hyperparameters used for the reinforcement fine-tuning job. + + - `batch_size: :auto | Integer` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `BatchSize = :auto` + + - `:auto` + + - `Integer = Integer` + + - `compute_multiplier: :auto | Float` + + Multiplier on amount of compute used for exploring search space during training. + + - `ComputeMultiplier = :auto` + + - `:auto` + + - `Float = Float` + + - `eval_interval: :auto | Integer` + + The number of training steps between evaluation runs. + + - `EvalInterval = :auto` + + - `:auto` + + - `Integer = Integer` + + - `eval_samples: :auto | Integer` + + Number of evaluation samples to generate per training step. + + - `EvalSamples = :auto` + + - `:auto` + + - `Integer = Integer` + + - `learning_rate_multiplier: :auto | Float` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `LearningRateMultiplier = :auto` + + - `:auto` + + - `Float = Float` + + - `n_epochs: :auto | Integer` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `NEpochs = :auto` + + - `:auto` + + - `Integer = Integer` + + - `reasoning_effort: :default | :low | :medium | :high` + + Level of reasoning effort. + + - `:default` + + - `:low` + + - `:medium` + + - `:high` + + - `supervised: SupervisedMethod` + + Configuration for the supervised fine-tuning method. + + - `hyperparameters: SupervisedHyperparameters` + + The hyperparameters used for the fine-tuning job. + + - `batch_size: :auto | Integer` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `BatchSize = :auto` + + - `:auto` + + - `Integer = Integer` + + - `learning_rate_multiplier: :auto | Float` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `LearningRateMultiplier = :auto` + + - `:auto` + + - `Float = Float` + + - `n_epochs: :auto | Integer` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `NEpochs = :auto` + + - `:auto` + + - `Integer = Integer` + +### Example + +```ruby +require "openai" + +openai = OpenAI::Client.new(api_key: "My API Key") + +fine_tuning_job = openai.fine_tuning.jobs.cancel("ft-AF1WoRqd3aJAHsqc9NY7iL8F") + +puts(fine_tuning_job) +``` + +#### Response + +```json +{ + "id": "id", + "created_at": 0, + "error": { + "code": "code", + "message": "message", + "param": "param" + }, + "fine_tuned_model": "fine_tuned_model", + "finished_at": 0, + "hyperparameters": { + "batch_size": "auto", + "learning_rate_multiplier": "auto", + "n_epochs": "auto" + }, + "model": "model", + "object": "fine_tuning.job", + "organization_id": "organization_id", + "result_files": [ + "file-abc123" + ], + "seed": 0, + "status": "validating_files", + "trained_tokens": 0, + "training_file": "training_file", + "validation_file": "validation_file", + "estimated_finish": 0, + "integrations": [ + { + "type": "wandb", + "wandb": { + "project": "my-wandb-project", + "entity": "entity", + "name": "name", + "tags": [ + "custom-tag" + ] + } + } + ], + "metadata": { + "foo": "string" + }, + "method": { + "type": "supervised", + "dpo": { + "hyperparameters": { + "batch_size": "auto", + "beta": "auto", + "learning_rate_multiplier": "auto", + "n_epochs": "auto" + } + }, + "reinforcement": { + "grader": { + "input": "input", + "name": "name", + "operation": "eq", + "reference": "reference", + "type": "string_check" + }, + "hyperparameters": { + "batch_size": "auto", + "compute_multiplier": "auto", + "eval_interval": "auto", + "eval_samples": "auto", + "learning_rate_multiplier": "auto", + "n_epochs": "auto", + "reasoning_effort": "default" + } + }, + "supervised": { + "hyperparameters": { + "batch_size": "auto", + "learning_rate_multiplier": "auto", + "n_epochs": "auto" + } + } + } +} +``` + +## Pause fine-tuning + +`fine_tuning.jobs.pause(fine_tuning_job_id) -> FineTuningJob` + +**post** `/fine_tuning/jobs/{fine_tuning_job_id}/pause` + +Pause a fine-tune job. + +### Parameters + +- `fine_tuning_job_id: String` + +### Returns + +- `class FineTuningJob` + + The `fine_tuning.job` object represents a fine-tuning job that has been created through the API. + + - `id: String` + + The object identifier, which can be referenced in the API endpoints. + + - `created_at: Integer` + + The Unix timestamp (in seconds) for when the fine-tuning job was created. + + - `error: Error{ code, message, param}` + + For fine-tuning jobs that have `failed`, this will contain more information on the cause of the failure. + + - `code: String` + + A machine-readable error code. + + - `message: String` + + A human-readable error message. + + - `param: String` + + The parameter that was invalid, usually `training_file` or `validation_file`. This field will be null if the failure was not parameter-specific. + + - `fine_tuned_model: String` + + The name of the fine-tuned model that is being created. The value will be null if the fine-tuning job is still running. + + - `finished_at: Integer` + + 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. + + - `hyperparameters: Hyperparameters{ batch_size, learning_rate_multiplier, n_epochs}` + + The hyperparameters used for the fine-tuning job. This value will only be returned when running `supervised` jobs. + + - `batch_size: :auto | Integer` + + Number of examples in each batch. A larger batch size means that model parameters + are updated less frequently, but with lower variance. + + - `BatchSize = :auto` + + - `:auto` + + - `Integer = Integer` + + - `learning_rate_multiplier: :auto | Float` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid + overfitting. + + - `LearningRateMultiplier = :auto` + + - `:auto` + + - `Float = Float` + + - `n_epochs: :auto | Integer` + + The number of epochs to train the model for. An epoch refers to one full cycle + through the training dataset. + + - `NEpochs = :auto` + + - `:auto` + + - `Integer = Integer` + + - `model: String` + + The base model that is being fine-tuned. + + - `object: :"fine_tuning.job"` + + The object type, which is always "fine_tuning.job". + + - `:"fine_tuning.job"` + + - `organization_id: String` + + The organization that owns the fine-tuning job. + + - `result_files: Array[String]` + + The compiled results file ID(s) for the fine-tuning job. You can retrieve the results with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents). + + - `seed: Integer` + + The seed used for the fine-tuning job. + + - `status: :validating_files | :queued | :running | 3 more` + + The current status of the fine-tuning job, which can be either `validating_files`, `queued`, `running`, `succeeded`, `failed`, or `cancelled`. + + - `:validating_files` + + - `:queued` + + - `:running` + + - `:succeeded` + + - `:failed` + + - `:cancelled` + + - `trained_tokens: Integer` + + 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. + + - `training_file: String` + + The file ID used for training. You can retrieve the training data with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents). + + - `validation_file: String` + + The file ID used for validation. You can retrieve the validation results with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents). + + - `estimated_finish: Integer` + + 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. + + - `integrations: Array[FineTuningJobWandbIntegrationObject]` + + A list of integrations to enable for this fine-tuning job. + + - `type: :wandb` + + The type of the integration being enabled for the fine-tuning job + + - `:wandb` + + - `wandb: FineTuningJobWandbIntegration` + + The settings for your integration with Weights and Biases. This payload specifies the project that + metrics will be sent to. Optionally, you can set an explicit display name for your run, add tags + to your run, and set a default entity (team, username, etc) to be associated with your run. + + - `project: String` + + The name of the project that the new run will be created under. + + - `entity: String` + + 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 run. If not set, the default entity for the registered WandB API key is used. + + - `name: String` + + A display name to set for the run. If not set, we will use the Job ID as the name. + + - `tags: Array[String]` + + A list of tags to be attached to the newly created run. These tags are passed through directly to WandB. Some + default tags are generated by OpenAI: "openai/finetune", "openai/{base-model}", "openai/{ftjob-abcdef}". + + - `metadata: 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_: Method{ type, dpo, reinforcement, supervised}` + + The method used for fine-tuning. + + - `type: :supervised | :dpo | :reinforcement` + + The type of method. Is either `supervised`, `dpo`, or `reinforcement`. + + - `:supervised` + + - `:dpo` + + - `:reinforcement` + + - `dpo: DpoMethod` + + Configuration for the DPO fine-tuning method. + + - `hyperparameters: DpoHyperparameters` + + The hyperparameters used for the DPO fine-tuning job. + + - `batch_size: :auto | Integer` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `BatchSize = :auto` + + - `:auto` + + - `Integer = Integer` + + - `beta: :auto | Float` + + The beta value for the DPO method. A higher beta value will increase the weight of the penalty between the policy and reference model. + + - `Beta = :auto` + + - `:auto` + + - `Float = Float` + + - `learning_rate_multiplier: :auto | Float` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `LearningRateMultiplier = :auto` + + - `:auto` + + - `Float = Float` + + - `n_epochs: :auto | Integer` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `NEpochs = :auto` + + - `:auto` + + - `Integer = Integer` + + - `reinforcement: ReinforcementMethod` + + Configuration for the reinforcement fine-tuning method. + + - `grader: StringCheckGrader | TextSimilarityGrader | PythonGrader | 2 more` + + The grader used for the fine-tuning job. + + - `class StringCheckGrader` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `input: String` + + The input text. This may include template strings. + + - `name: String` + + The name of the grader. + + - `operation: :eq | :ne | :like | :ilike` + + The string check operation to perform. One of `eq`, `ne`, `like`, or `ilike`. + + - `:eq` + + - `:ne` + + - `:like` + + - `:ilike` + + - `reference: String` + + The reference text. This may include template strings. + + - `type: :string_check` + + The object type, which is always `string_check`. + + - `:string_check` + + - `class TextSimilarityGrader` + + A TextSimilarityGrader object which grades text based on similarity metrics. + + - `evaluation_metric: :cosine | :fuzzy_match | :bleu | 8 more` + + The evaluation metric to use. One of `cosine`, `fuzzy_match`, `bleu`, + `gleu`, `meteor`, `rouge_1`, `rouge_2`, `rouge_3`, `rouge_4`, `rouge_5`, + or `rouge_l`. + + - `:cosine` + + - `:fuzzy_match` + + - `:bleu` + + - `:gleu` + + - `:meteor` + + - `:rouge_1` + + - `:rouge_2` + + - `:rouge_3` + + - `:rouge_4` + + - `:rouge_5` + + - `:rouge_l` + + - `input: String` + + The text being graded. + + - `name: String` + + The name of the grader. + + - `reference: String` + + The text being graded against. + + - `type: :text_similarity` + + The type of grader. + + - `:text_similarity` + + - `class PythonGrader` + + A PythonGrader object that runs a python script on the input. + + - `name: String` + + The name of the grader. + + - `source: String` + + The source code of the python script. + + - `type: :python` + + The object type, which is always `python`. + + - `:python` + + - `image_tag: String` + + The image tag to use for the python script. + + - `class ScoreModelGrader` + + A ScoreModelGrader object that uses a model to assign a score to the input. + + - `input: Array[Input{ content, role, type}]` + + The input messages evaluated by the grader. Supports text, output text, input image, and input audio content blocks, and may include template strings. + + - `content: String | ResponseInputText | OutputText{ text, type} | 3 more` + + Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items. + + - `String = String` + + A text input to the model. + + - `class ResponseInputText` + + A text input to the model. + + - `text: String` + + The text input to the model. + + - `type: :input_text` + + The type of the input item. Always `input_text`. + + - `:input_text` + + - `class OutputText` + + A text output from the model. + + - `text: String` + + The text output from the model. + + - `type: :output_text` + + The type of the output text. Always `output_text`. + + - `:output_text` + + - `class InputImage` + + An image input block used within EvalItem content arrays. + + - `image_url: String` + + The URL of the image input. + + - `type: :input_image` + + The type of the image input. Always `input_image`. + + - `:input_image` + + - `detail: String` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `class ResponseInputAudio` + + An audio input to the model. + + - `input_audio: InputAudio{ data, format_}` + + - `data: String` + + Base64-encoded audio data. + + - `format_: :mp3 | :wav` + + The format of the audio data. Currently supported formats are `mp3` and + `wav`. + + - `:mp3` + + - `:wav` + + - `type: :input_audio` + + The type of the input item. Always `input_audio`. + + - `:input_audio` + + - `GraderInputs = Array[GraderInputItem]` + + A list of inputs, each of which may be either an input text, output text, input + image, or input audio object. + + - `String = String` + + A text input to the model. + + - `class ResponseInputText` + + A text input to the model. + + - `class OutputText` + + A text output from the model. + + - `text: String` + + The text output from the model. + + - `type: :output_text` + + The type of the output text. Always `output_text`. + + - `:output_text` + + - `class InputImage` + + An image input block used within EvalItem content arrays. + + - `image_url: String` + + The URL of the image input. + + - `type: :input_image` + + The type of the image input. Always `input_image`. + + - `:input_image` + + - `detail: String` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `class ResponseInputAudio` + + An audio input to the model. + + - `role: :user | :assistant | :system | :developer` + + The role of the message input. One of `user`, `assistant`, `system`, or + `developer`. + + - `:user` + + - `:assistant` + + - `:system` + + - `:developer` + + - `type: :message` + + The type of the message input. Always `message`. + + - `:message` + + - `model: String` + + The model to use for the evaluation. + + - `name: String` + + The name of the grader. + + - `type: :score_model` + + The object type, which is always `score_model`. + + - `:score_model` + + - `range: Array[Float]` + + The range of the score. Defaults to `[0, 1]`. + + - `sampling_params: SamplingParams{ max_completions_tokens, reasoning_effort, seed, 2 more}` + + The sampling parameters for the model. + + - `max_completions_tokens: Integer` + + The maximum number of tokens the grader model may generate in its response. + + - `reasoning_effort: ReasoningEffort` + + Constrains effort on reasoning for + [reasoning models](https://platform.openai.com/docs/guides/reasoning). + Currently supported values are `none`, `minimal`, `low`, `medium`, `high`, and `xhigh`. Reducing + reasoning effort can result in faster responses and fewer tokens used + on reasoning in a response. + + - `gpt-5.1` defaults to `none`, which does not perform reasoning. The supported reasoning values for `gpt-5.1` are `none`, `low`, `medium`, and `high`. Tool calls are supported for all reasoning values in gpt-5.1. + - All models before `gpt-5.1` default to `medium` reasoning effort, and do not support `none`. + - The `gpt-5-pro` model defaults to (and only supports) `high` reasoning effort. + - `xhigh` is supported for all models after `gpt-5.1-codex-max`. + + - `:none` + + - `:minimal` + + - `:low` + + - `:medium` + + - `:high` + + - `:xhigh` + + - `seed: Integer` + + A seed value to initialize the randomness, during sampling. + + - `temperature: Float` + + A higher temperature increases randomness in the outputs. + + - `top_p: Float` + + An alternative to temperature for nucleus sampling; 1.0 includes all tokens. + + - `class MultiGrader` + + A MultiGrader object combines the output of multiple graders to produce a single score. + + - `calculate_output: String` + + A formula to calculate the output based on grader results. + + - `graders: StringCheckGrader | TextSimilarityGrader | PythonGrader | 2 more` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `class StringCheckGrader` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `class TextSimilarityGrader` + + A TextSimilarityGrader object which grades text based on similarity metrics. + + - `class PythonGrader` + + A PythonGrader object that runs a python script on the input. + + - `class ScoreModelGrader` + + A ScoreModelGrader object that uses a model to assign a score to the input. + + - `class LabelModelGrader` + + A LabelModelGrader object which uses a model to assign labels to each item + in the evaluation. + + - `input: Array[Input{ content, role, type}]` + + - `content: String | ResponseInputText | OutputText{ text, type} | 3 more` + + Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items. + + - `String = String` + + A text input to the model. + + - `class ResponseInputText` + + A text input to the model. + + - `class OutputText` + + A text output from the model. + + - `text: String` + + The text output from the model. + + - `type: :output_text` + + The type of the output text. Always `output_text`. + + - `:output_text` + + - `class InputImage` + + An image input block used within EvalItem content arrays. + + - `image_url: String` + + The URL of the image input. + + - `type: :input_image` + + The type of the image input. Always `input_image`. + + - `:input_image` + + - `detail: String` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `class ResponseInputAudio` + + An audio input to the model. + + - `GraderInputs = Array[GraderInputItem]` + + A list of inputs, each of which may be either an input text, output text, input + image, or input audio object. + + - `role: :user | :assistant | :system | :developer` + + The role of the message input. One of `user`, `assistant`, `system`, or + `developer`. + + - `:user` + + - `:assistant` + + - `:system` + + - `:developer` + + - `type: :message` + + The type of the message input. Always `message`. + + - `:message` + + - `labels: Array[String]` + + The labels to assign to each item in the evaluation. + + - `model: String` + + The model to use for the evaluation. Must support structured outputs. + + - `name: String` + + The name of the grader. + + - `passing_labels: Array[String]` + + The labels that indicate a passing result. Must be a subset of labels. + + - `type: :label_model` + + The object type, which is always `label_model`. + + - `:label_model` + + - `name: String` + + The name of the grader. + + - `type: :multi` + + The object type, which is always `multi`. + + - `:multi` + + - `hyperparameters: ReinforcementHyperparameters` + + The hyperparameters used for the reinforcement fine-tuning job. + + - `batch_size: :auto | Integer` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `BatchSize = :auto` + + - `:auto` + + - `Integer = Integer` + + - `compute_multiplier: :auto | Float` + + Multiplier on amount of compute used for exploring search space during training. + + - `ComputeMultiplier = :auto` + + - `:auto` + + - `Float = Float` + + - `eval_interval: :auto | Integer` + + The number of training steps between evaluation runs. + + - `EvalInterval = :auto` + + - `:auto` + + - `Integer = Integer` + + - `eval_samples: :auto | Integer` + + Number of evaluation samples to generate per training step. + + - `EvalSamples = :auto` + + - `:auto` + + - `Integer = Integer` + + - `learning_rate_multiplier: :auto | Float` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `LearningRateMultiplier = :auto` + + - `:auto` + + - `Float = Float` + + - `n_epochs: :auto | Integer` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `NEpochs = :auto` + + - `:auto` + + - `Integer = Integer` + + - `reasoning_effort: :default | :low | :medium | :high` + + Level of reasoning effort. + + - `:default` + + - `:low` + + - `:medium` + + - `:high` + + - `supervised: SupervisedMethod` + + Configuration for the supervised fine-tuning method. + + - `hyperparameters: SupervisedHyperparameters` + + The hyperparameters used for the fine-tuning job. + + - `batch_size: :auto | Integer` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `BatchSize = :auto` + + - `:auto` + + - `Integer = Integer` + + - `learning_rate_multiplier: :auto | Float` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `LearningRateMultiplier = :auto` + + - `:auto` + + - `Float = Float` + + - `n_epochs: :auto | Integer` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `NEpochs = :auto` + + - `:auto` + + - `Integer = Integer` + +### Example + +```ruby +require "openai" + +openai = OpenAI::Client.new(api_key: "My API Key") + +fine_tuning_job = openai.fine_tuning.jobs.pause("ft-AF1WoRqd3aJAHsqc9NY7iL8F") + +puts(fine_tuning_job) +``` + +#### Response + +```json +{ + "id": "id", + "created_at": 0, + "error": { + "code": "code", + "message": "message", + "param": "param" + }, + "fine_tuned_model": "fine_tuned_model", + "finished_at": 0, + "hyperparameters": { + "batch_size": "auto", + "learning_rate_multiplier": "auto", + "n_epochs": "auto" + }, + "model": "model", + "object": "fine_tuning.job", + "organization_id": "organization_id", + "result_files": [ + "file-abc123" + ], + "seed": 0, + "status": "validating_files", + "trained_tokens": 0, + "training_file": "training_file", + "validation_file": "validation_file", + "estimated_finish": 0, + "integrations": [ + { + "type": "wandb", + "wandb": { + "project": "my-wandb-project", + "entity": "entity", + "name": "name", + "tags": [ + "custom-tag" + ] + } + } + ], + "metadata": { + "foo": "string" + }, + "method": { + "type": "supervised", + "dpo": { + "hyperparameters": { + "batch_size": "auto", + "beta": "auto", + "learning_rate_multiplier": "auto", + "n_epochs": "auto" + } + }, + "reinforcement": { + "grader": { + "input": "input", + "name": "name", + "operation": "eq", + "reference": "reference", + "type": "string_check" + }, + "hyperparameters": { + "batch_size": "auto", + "compute_multiplier": "auto", + "eval_interval": "auto", + "eval_samples": "auto", + "learning_rate_multiplier": "auto", + "n_epochs": "auto", + "reasoning_effort": "default" + } + }, + "supervised": { + "hyperparameters": { + "batch_size": "auto", + "learning_rate_multiplier": "auto", + "n_epochs": "auto" + } + } + } +} +``` + +## Resume fine-tuning + +`fine_tuning.jobs.resume(fine_tuning_job_id) -> FineTuningJob` + +**post** `/fine_tuning/jobs/{fine_tuning_job_id}/resume` + +Resume a fine-tune job. + +### Parameters + +- `fine_tuning_job_id: String` + +### Returns + +- `class FineTuningJob` + + The `fine_tuning.job` object represents a fine-tuning job that has been created through the API. + + - `id: String` + + The object identifier, which can be referenced in the API endpoints. + + - `created_at: Integer` + + The Unix timestamp (in seconds) for when the fine-tuning job was created. + + - `error: Error{ code, message, param}` + + For fine-tuning jobs that have `failed`, this will contain more information on the cause of the failure. + + - `code: String` + + A machine-readable error code. + + - `message: String` + + A human-readable error message. + + - `param: String` + + The parameter that was invalid, usually `training_file` or `validation_file`. This field will be null if the failure was not parameter-specific. + + - `fine_tuned_model: String` + + The name of the fine-tuned model that is being created. The value will be null if the fine-tuning job is still running. + + - `finished_at: Integer` + + 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. + + - `hyperparameters: Hyperparameters{ batch_size, learning_rate_multiplier, n_epochs}` + + The hyperparameters used for the fine-tuning job. This value will only be returned when running `supervised` jobs. + + - `batch_size: :auto | Integer` + + Number of examples in each batch. A larger batch size means that model parameters + are updated less frequently, but with lower variance. + + - `BatchSize = :auto` + + - `:auto` + + - `Integer = Integer` + + - `learning_rate_multiplier: :auto | Float` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid + overfitting. + + - `LearningRateMultiplier = :auto` + + - `:auto` + + - `Float = Float` + + - `n_epochs: :auto | Integer` + + The number of epochs to train the model for. An epoch refers to one full cycle + through the training dataset. + + - `NEpochs = :auto` + + - `:auto` + + - `Integer = Integer` + + - `model: String` + + The base model that is being fine-tuned. + + - `object: :"fine_tuning.job"` + + The object type, which is always "fine_tuning.job". + + - `:"fine_tuning.job"` + + - `organization_id: String` + + The organization that owns the fine-tuning job. + + - `result_files: Array[String]` + + The compiled results file ID(s) for the fine-tuning job. You can retrieve the results with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents). + + - `seed: Integer` + + The seed used for the fine-tuning job. + + - `status: :validating_files | :queued | :running | 3 more` + + The current status of the fine-tuning job, which can be either `validating_files`, `queued`, `running`, `succeeded`, `failed`, or `cancelled`. + + - `:validating_files` + + - `:queued` + + - `:running` + + - `:succeeded` + + - `:failed` + + - `:cancelled` + + - `trained_tokens: Integer` + + 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. + + - `training_file: String` + + The file ID used for training. You can retrieve the training data with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents). + + - `validation_file: String` + + The file ID used for validation. You can retrieve the validation results with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents). + + - `estimated_finish: Integer` + + 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. + + - `integrations: Array[FineTuningJobWandbIntegrationObject]` + + A list of integrations to enable for this fine-tuning job. + + - `type: :wandb` + + The type of the integration being enabled for the fine-tuning job + + - `:wandb` + + - `wandb: FineTuningJobWandbIntegration` + + The settings for your integration with Weights and Biases. This payload specifies the project that + metrics will be sent to. Optionally, you can set an explicit display name for your run, add tags + to your run, and set a default entity (team, username, etc) to be associated with your run. + + - `project: String` + + The name of the project that the new run will be created under. + + - `entity: String` + + 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 run. If not set, the default entity for the registered WandB API key is used. + + - `name: String` + + A display name to set for the run. If not set, we will use the Job ID as the name. + + - `tags: Array[String]` + + A list of tags to be attached to the newly created run. These tags are passed through directly to WandB. Some + default tags are generated by OpenAI: "openai/finetune", "openai/{base-model}", "openai/{ftjob-abcdef}". + + - `metadata: 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_: Method{ type, dpo, reinforcement, supervised}` + + The method used for fine-tuning. + + - `type: :supervised | :dpo | :reinforcement` + + The type of method. Is either `supervised`, `dpo`, or `reinforcement`. + + - `:supervised` + + - `:dpo` + + - `:reinforcement` + + - `dpo: DpoMethod` + + Configuration for the DPO fine-tuning method. + + - `hyperparameters: DpoHyperparameters` + + The hyperparameters used for the DPO fine-tuning job. + + - `batch_size: :auto | Integer` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `BatchSize = :auto` + + - `:auto` + + - `Integer = Integer` + + - `beta: :auto | Float` + + The beta value for the DPO method. A higher beta value will increase the weight of the penalty between the policy and reference model. + + - `Beta = :auto` + + - `:auto` + + - `Float = Float` + + - `learning_rate_multiplier: :auto | Float` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `LearningRateMultiplier = :auto` + + - `:auto` + + - `Float = Float` + + - `n_epochs: :auto | Integer` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `NEpochs = :auto` + + - `:auto` + + - `Integer = Integer` + + - `reinforcement: ReinforcementMethod` + + Configuration for the reinforcement fine-tuning method. + + - `grader: StringCheckGrader | TextSimilarityGrader | PythonGrader | 2 more` + + The grader used for the fine-tuning job. + + - `class StringCheckGrader` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `input: String` + + The input text. This may include template strings. + + - `name: String` + + The name of the grader. + + - `operation: :eq | :ne | :like | :ilike` + + The string check operation to perform. One of `eq`, `ne`, `like`, or `ilike`. + + - `:eq` + + - `:ne` + + - `:like` + + - `:ilike` + + - `reference: String` + + The reference text. This may include template strings. + + - `type: :string_check` + + The object type, which is always `string_check`. + + - `:string_check` + + - `class TextSimilarityGrader` + + A TextSimilarityGrader object which grades text based on similarity metrics. + + - `evaluation_metric: :cosine | :fuzzy_match | :bleu | 8 more` + + The evaluation metric to use. One of `cosine`, `fuzzy_match`, `bleu`, + `gleu`, `meteor`, `rouge_1`, `rouge_2`, `rouge_3`, `rouge_4`, `rouge_5`, + or `rouge_l`. + + - `:cosine` + + - `:fuzzy_match` + + - `:bleu` + + - `:gleu` + + - `:meteor` + + - `:rouge_1` + + - `:rouge_2` + + - `:rouge_3` + + - `:rouge_4` + + - `:rouge_5` + + - `:rouge_l` + + - `input: String` + + The text being graded. + + - `name: String` + + The name of the grader. + + - `reference: String` + + The text being graded against. + + - `type: :text_similarity` + + The type of grader. + + - `:text_similarity` + + - `class PythonGrader` + + A PythonGrader object that runs a python script on the input. + + - `name: String` + + The name of the grader. + + - `source: String` + + The source code of the python script. + + - `type: :python` + + The object type, which is always `python`. + + - `:python` + + - `image_tag: String` + + The image tag to use for the python script. + + - `class ScoreModelGrader` + + A ScoreModelGrader object that uses a model to assign a score to the input. + + - `input: Array[Input{ content, role, type}]` + + The input messages evaluated by the grader. Supports text, output text, input image, and input audio content blocks, and may include template strings. + + - `content: String | ResponseInputText | OutputText{ text, type} | 3 more` + + Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items. + + - `String = String` + + A text input to the model. + + - `class ResponseInputText` + + A text input to the model. + + - `text: String` + + The text input to the model. + + - `type: :input_text` + + The type of the input item. Always `input_text`. + + - `:input_text` + + - `class OutputText` + + A text output from the model. + + - `text: String` + + The text output from the model. + + - `type: :output_text` + + The type of the output text. Always `output_text`. + + - `:output_text` + + - `class InputImage` + + An image input block used within EvalItem content arrays. + + - `image_url: String` + + The URL of the image input. + + - `type: :input_image` + + The type of the image input. Always `input_image`. + + - `:input_image` + + - `detail: String` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `class ResponseInputAudio` + + An audio input to the model. + + - `input_audio: InputAudio{ data, format_}` + + - `data: String` + + Base64-encoded audio data. + + - `format_: :mp3 | :wav` + + The format of the audio data. Currently supported formats are `mp3` and + `wav`. + + - `:mp3` + + - `:wav` + + - `type: :input_audio` + + The type of the input item. Always `input_audio`. + + - `:input_audio` + + - `GraderInputs = Array[GraderInputItem]` + + A list of inputs, each of which may be either an input text, output text, input + image, or input audio object. + + - `String = String` + + A text input to the model. + + - `class ResponseInputText` + + A text input to the model. + + - `class OutputText` + + A text output from the model. + + - `text: String` + + The text output from the model. + + - `type: :output_text` + + The type of the output text. Always `output_text`. + + - `:output_text` + + - `class InputImage` + + An image input block used within EvalItem content arrays. + + - `image_url: String` + + The URL of the image input. + + - `type: :input_image` + + The type of the image input. Always `input_image`. + + - `:input_image` + + - `detail: String` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `class ResponseInputAudio` + + An audio input to the model. + + - `role: :user | :assistant | :system | :developer` + + The role of the message input. One of `user`, `assistant`, `system`, or + `developer`. + + - `:user` + + - `:assistant` + + - `:system` + + - `:developer` + + - `type: :message` + + The type of the message input. Always `message`. + + - `:message` + + - `model: String` + + The model to use for the evaluation. + + - `name: String` + + The name of the grader. + + - `type: :score_model` + + The object type, which is always `score_model`. + + - `:score_model` + + - `range: Array[Float]` + + The range of the score. Defaults to `[0, 1]`. + + - `sampling_params: SamplingParams{ max_completions_tokens, reasoning_effort, seed, 2 more}` + + The sampling parameters for the model. + + - `max_completions_tokens: Integer` + + The maximum number of tokens the grader model may generate in its response. + + - `reasoning_effort: ReasoningEffort` + + Constrains effort on reasoning for + [reasoning models](https://platform.openai.com/docs/guides/reasoning). + Currently supported values are `none`, `minimal`, `low`, `medium`, `high`, and `xhigh`. Reducing + reasoning effort can result in faster responses and fewer tokens used + on reasoning in a response. + + - `gpt-5.1` defaults to `none`, which does not perform reasoning. The supported reasoning values for `gpt-5.1` are `none`, `low`, `medium`, and `high`. Tool calls are supported for all reasoning values in gpt-5.1. + - All models before `gpt-5.1` default to `medium` reasoning effort, and do not support `none`. + - The `gpt-5-pro` model defaults to (and only supports) `high` reasoning effort. + - `xhigh` is supported for all models after `gpt-5.1-codex-max`. + + - `:none` + + - `:minimal` + + - `:low` + + - `:medium` + + - `:high` + + - `:xhigh` + + - `seed: Integer` + + A seed value to initialize the randomness, during sampling. + + - `temperature: Float` + + A higher temperature increases randomness in the outputs. + + - `top_p: Float` + + An alternative to temperature for nucleus sampling; 1.0 includes all tokens. + + - `class MultiGrader` + + A MultiGrader object combines the output of multiple graders to produce a single score. + + - `calculate_output: String` + + A formula to calculate the output based on grader results. + + - `graders: StringCheckGrader | TextSimilarityGrader | PythonGrader | 2 more` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `class StringCheckGrader` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `class TextSimilarityGrader` + + A TextSimilarityGrader object which grades text based on similarity metrics. + + - `class PythonGrader` + + A PythonGrader object that runs a python script on the input. + + - `class ScoreModelGrader` + + A ScoreModelGrader object that uses a model to assign a score to the input. + + - `class LabelModelGrader` + + A LabelModelGrader object which uses a model to assign labels to each item + in the evaluation. + + - `input: Array[Input{ content, role, type}]` + + - `content: String | ResponseInputText | OutputText{ text, type} | 3 more` + + Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items. + + - `String = String` + + A text input to the model. + + - `class ResponseInputText` + + A text input to the model. + + - `class OutputText` + + A text output from the model. + + - `text: String` + + The text output from the model. + + - `type: :output_text` + + The type of the output text. Always `output_text`. + + - `:output_text` + + - `class InputImage` + + An image input block used within EvalItem content arrays. + + - `image_url: String` + + The URL of the image input. + + - `type: :input_image` + + The type of the image input. Always `input_image`. + + - `:input_image` + + - `detail: String` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `class ResponseInputAudio` + + An audio input to the model. + + - `GraderInputs = Array[GraderInputItem]` + + A list of inputs, each of which may be either an input text, output text, input + image, or input audio object. + + - `role: :user | :assistant | :system | :developer` + + The role of the message input. One of `user`, `assistant`, `system`, or + `developer`. + + - `:user` + + - `:assistant` + + - `:system` + + - `:developer` + + - `type: :message` + + The type of the message input. Always `message`. + + - `:message` + + - `labels: Array[String]` + + The labels to assign to each item in the evaluation. + + - `model: String` + + The model to use for the evaluation. Must support structured outputs. + + - `name: String` + + The name of the grader. + + - `passing_labels: Array[String]` + + The labels that indicate a passing result. Must be a subset of labels. + + - `type: :label_model` + + The object type, which is always `label_model`. + + - `:label_model` + + - `name: String` + + The name of the grader. + + - `type: :multi` + + The object type, which is always `multi`. + + - `:multi` + + - `hyperparameters: ReinforcementHyperparameters` + + The hyperparameters used for the reinforcement fine-tuning job. + + - `batch_size: :auto | Integer` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `BatchSize = :auto` + + - `:auto` + + - `Integer = Integer` + + - `compute_multiplier: :auto | Float` + + Multiplier on amount of compute used for exploring search space during training. + + - `ComputeMultiplier = :auto` + + - `:auto` + + - `Float = Float` + + - `eval_interval: :auto | Integer` + + The number of training steps between evaluation runs. + + - `EvalInterval = :auto` + + - `:auto` + + - `Integer = Integer` + + - `eval_samples: :auto | Integer` + + Number of evaluation samples to generate per training step. + + - `EvalSamples = :auto` + + - `:auto` + + - `Integer = Integer` + + - `learning_rate_multiplier: :auto | Float` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `LearningRateMultiplier = :auto` + + - `:auto` + + - `Float = Float` + + - `n_epochs: :auto | Integer` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `NEpochs = :auto` + + - `:auto` + + - `Integer = Integer` + + - `reasoning_effort: :default | :low | :medium | :high` + + Level of reasoning effort. + + - `:default` + + - `:low` + + - `:medium` + + - `:high` + + - `supervised: SupervisedMethod` + + Configuration for the supervised fine-tuning method. + + - `hyperparameters: SupervisedHyperparameters` + + The hyperparameters used for the fine-tuning job. + + - `batch_size: :auto | Integer` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `BatchSize = :auto` + + - `:auto` + + - `Integer = Integer` + + - `learning_rate_multiplier: :auto | Float` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `LearningRateMultiplier = :auto` + + - `:auto` + + - `Float = Float` + + - `n_epochs: :auto | Integer` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `NEpochs = :auto` + + - `:auto` + + - `Integer = Integer` + +### Example + +```ruby +require "openai" + +openai = OpenAI::Client.new(api_key: "My API Key") + +fine_tuning_job = openai.fine_tuning.jobs.resume("ft-AF1WoRqd3aJAHsqc9NY7iL8F") + +puts(fine_tuning_job) +``` + +#### Response + +```json +{ + "id": "id", + "created_at": 0, + "error": { + "code": "code", + "message": "message", + "param": "param" + }, + "fine_tuned_model": "fine_tuned_model", + "finished_at": 0, + "hyperparameters": { + "batch_size": "auto", + "learning_rate_multiplier": "auto", + "n_epochs": "auto" + }, + "model": "model", + "object": "fine_tuning.job", + "organization_id": "organization_id", + "result_files": [ + "file-abc123" + ], + "seed": 0, + "status": "validating_files", + "trained_tokens": 0, + "training_file": "training_file", + "validation_file": "validation_file", + "estimated_finish": 0, + "integrations": [ + { + "type": "wandb", + "wandb": { + "project": "my-wandb-project", + "entity": "entity", + "name": "name", + "tags": [ + "custom-tag" + ] + } + } + ], + "metadata": { + "foo": "string" + }, + "method": { + "type": "supervised", + "dpo": { + "hyperparameters": { + "batch_size": "auto", + "beta": "auto", + "learning_rate_multiplier": "auto", + "n_epochs": "auto" + } + }, + "reinforcement": { + "grader": { + "input": "input", + "name": "name", + "operation": "eq", + "reference": "reference", + "type": "string_check" + }, + "hyperparameters": { + "batch_size": "auto", + "compute_multiplier": "auto", + "eval_interval": "auto", + "eval_samples": "auto", + "learning_rate_multiplier": "auto", + "n_epochs": "auto", + "reasoning_effort": "default" + } + }, + "supervised": { + "hyperparameters": { + "batch_size": "auto", + "learning_rate_multiplier": "auto", + "n_epochs": "auto" + } + } + } +} +``` + +## Domain Types + +### Fine Tuning Job + +- `class FineTuningJob` + + The `fine_tuning.job` object represents a fine-tuning job that has been created through the API. + + - `id: String` + + The object identifier, which can be referenced in the API endpoints. + + - `created_at: Integer` + + The Unix timestamp (in seconds) for when the fine-tuning job was created. + + - `error: Error{ code, message, param}` + + For fine-tuning jobs that have `failed`, this will contain more information on the cause of the failure. + + - `code: String` + + A machine-readable error code. + + - `message: String` + + A human-readable error message. + + - `param: String` + + The parameter that was invalid, usually `training_file` or `validation_file`. This field will be null if the failure was not parameter-specific. + + - `fine_tuned_model: String` + + The name of the fine-tuned model that is being created. The value will be null if the fine-tuning job is still running. + + - `finished_at: Integer` + + 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. + + - `hyperparameters: Hyperparameters{ batch_size, learning_rate_multiplier, n_epochs}` + + The hyperparameters used for the fine-tuning job. This value will only be returned when running `supervised` jobs. + + - `batch_size: :auto | Integer` + + Number of examples in each batch. A larger batch size means that model parameters + are updated less frequently, but with lower variance. + + - `BatchSize = :auto` + + - `:auto` + + - `Integer = Integer` + + - `learning_rate_multiplier: :auto | Float` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid + overfitting. + + - `LearningRateMultiplier = :auto` + + - `:auto` + + - `Float = Float` + + - `n_epochs: :auto | Integer` + + The number of epochs to train the model for. An epoch refers to one full cycle + through the training dataset. + + - `NEpochs = :auto` + + - `:auto` + + - `Integer = Integer` + + - `model: String` + + The base model that is being fine-tuned. + + - `object: :"fine_tuning.job"` + + The object type, which is always "fine_tuning.job". + + - `:"fine_tuning.job"` + + - `organization_id: String` + + The organization that owns the fine-tuning job. + + - `result_files: Array[String]` + + The compiled results file ID(s) for the fine-tuning job. You can retrieve the results with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents). + + - `seed: Integer` + + The seed used for the fine-tuning job. + + - `status: :validating_files | :queued | :running | 3 more` + + The current status of the fine-tuning job, which can be either `validating_files`, `queued`, `running`, `succeeded`, `failed`, or `cancelled`. + + - `:validating_files` + + - `:queued` + + - `:running` + + - `:succeeded` + + - `:failed` + + - `:cancelled` + + - `trained_tokens: Integer` + + 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. + + - `training_file: String` + + The file ID used for training. You can retrieve the training data with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents). + + - `validation_file: String` + + The file ID used for validation. You can retrieve the validation results with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents). + + - `estimated_finish: Integer` + + 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. + + - `integrations: Array[FineTuningJobWandbIntegrationObject]` + + A list of integrations to enable for this fine-tuning job. + + - `type: :wandb` + + The type of the integration being enabled for the fine-tuning job + + - `:wandb` + + - `wandb: FineTuningJobWandbIntegration` + + The settings for your integration with Weights and Biases. This payload specifies the project that + metrics will be sent to. Optionally, you can set an explicit display name for your run, add tags + to your run, and set a default entity (team, username, etc) to be associated with your run. + + - `project: String` + + The name of the project that the new run will be created under. + + - `entity: String` + + 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 run. If not set, the default entity for the registered WandB API key is used. + + - `name: String` + + A display name to set for the run. If not set, we will use the Job ID as the name. + + - `tags: Array[String]` + + A list of tags to be attached to the newly created run. These tags are passed through directly to WandB. Some + default tags are generated by OpenAI: "openai/finetune", "openai/{base-model}", "openai/{ftjob-abcdef}". + + - `metadata: 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_: Method{ type, dpo, reinforcement, supervised}` + + The method used for fine-tuning. + + - `type: :supervised | :dpo | :reinforcement` + + The type of method. Is either `supervised`, `dpo`, or `reinforcement`. + + - `:supervised` + + - `:dpo` + + - `:reinforcement` + + - `dpo: DpoMethod` + + Configuration for the DPO fine-tuning method. + + - `hyperparameters: DpoHyperparameters` + + The hyperparameters used for the DPO fine-tuning job. + + - `batch_size: :auto | Integer` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `BatchSize = :auto` + + - `:auto` + + - `Integer = Integer` + + - `beta: :auto | Float` + + The beta value for the DPO method. A higher beta value will increase the weight of the penalty between the policy and reference model. + + - `Beta = :auto` + + - `:auto` + + - `Float = Float` + + - `learning_rate_multiplier: :auto | Float` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `LearningRateMultiplier = :auto` + + - `:auto` + + - `Float = Float` + + - `n_epochs: :auto | Integer` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `NEpochs = :auto` + + - `:auto` + + - `Integer = Integer` + + - `reinforcement: ReinforcementMethod` + + Configuration for the reinforcement fine-tuning method. + + - `grader: StringCheckGrader | TextSimilarityGrader | PythonGrader | 2 more` + + The grader used for the fine-tuning job. + + - `class StringCheckGrader` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `input: String` + + The input text. This may include template strings. + + - `name: String` + + The name of the grader. + + - `operation: :eq | :ne | :like | :ilike` + + The string check operation to perform. One of `eq`, `ne`, `like`, or `ilike`. + + - `:eq` + + - `:ne` + + - `:like` + + - `:ilike` + + - `reference: String` + + The reference text. This may include template strings. + + - `type: :string_check` + + The object type, which is always `string_check`. + + - `:string_check` + + - `class TextSimilarityGrader` + + A TextSimilarityGrader object which grades text based on similarity metrics. + + - `evaluation_metric: :cosine | :fuzzy_match | :bleu | 8 more` + + The evaluation metric to use. One of `cosine`, `fuzzy_match`, `bleu`, + `gleu`, `meteor`, `rouge_1`, `rouge_2`, `rouge_3`, `rouge_4`, `rouge_5`, + or `rouge_l`. + + - `:cosine` + + - `:fuzzy_match` + + - `:bleu` + + - `:gleu` + + - `:meteor` + + - `:rouge_1` + + - `:rouge_2` + + - `:rouge_3` + + - `:rouge_4` + + - `:rouge_5` + + - `:rouge_l` + + - `input: String` + + The text being graded. + + - `name: String` + + The name of the grader. + + - `reference: String` + + The text being graded against. + + - `type: :text_similarity` + + The type of grader. + + - `:text_similarity` + + - `class PythonGrader` + + A PythonGrader object that runs a python script on the input. + + - `name: String` + + The name of the grader. + + - `source: String` + + The source code of the python script. + + - `type: :python` + + The object type, which is always `python`. + + - `:python` + + - `image_tag: String` + + The image tag to use for the python script. + + - `class ScoreModelGrader` + + A ScoreModelGrader object that uses a model to assign a score to the input. + + - `input: Array[Input{ content, role, type}]` + + The input messages evaluated by the grader. Supports text, output text, input image, and input audio content blocks, and may include template strings. + + - `content: String | ResponseInputText | OutputText{ text, type} | 3 more` + + Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items. + + - `String = String` + + A text input to the model. + + - `class ResponseInputText` + + A text input to the model. + + - `text: String` + + The text input to the model. + + - `type: :input_text` + + The type of the input item. Always `input_text`. + + - `:input_text` + + - `class OutputText` + + A text output from the model. + + - `text: String` + + The text output from the model. + + - `type: :output_text` + + The type of the output text. Always `output_text`. + + - `:output_text` + + - `class InputImage` + + An image input block used within EvalItem content arrays. + + - `image_url: String` + + The URL of the image input. + + - `type: :input_image` + + The type of the image input. Always `input_image`. + + - `:input_image` + + - `detail: String` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `class ResponseInputAudio` + + An audio input to the model. + + - `input_audio: InputAudio{ data, format_}` + + - `data: String` + + Base64-encoded audio data. + + - `format_: :mp3 | :wav` + + The format of the audio data. Currently supported formats are `mp3` and + `wav`. + + - `:mp3` + + - `:wav` + + - `type: :input_audio` + + The type of the input item. Always `input_audio`. + + - `:input_audio` + + - `GraderInputs = Array[GraderInputItem]` + + A list of inputs, each of which may be either an input text, output text, input + image, or input audio object. + + - `String = String` + + A text input to the model. + + - `class ResponseInputText` + + A text input to the model. + + - `class OutputText` + + A text output from the model. + + - `text: String` + + The text output from the model. + + - `type: :output_text` + + The type of the output text. Always `output_text`. + + - `:output_text` + + - `class InputImage` + + An image input block used within EvalItem content arrays. + + - `image_url: String` + + The URL of the image input. + + - `type: :input_image` + + The type of the image input. Always `input_image`. + + - `:input_image` + + - `detail: String` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `class ResponseInputAudio` + + An audio input to the model. + + - `role: :user | :assistant | :system | :developer` + + The role of the message input. One of `user`, `assistant`, `system`, or + `developer`. + + - `:user` + + - `:assistant` + + - `:system` + + - `:developer` + + - `type: :message` + + The type of the message input. Always `message`. + + - `:message` + + - `model: String` + + The model to use for the evaluation. + + - `name: String` + + The name of the grader. + + - `type: :score_model` + + The object type, which is always `score_model`. + + - `:score_model` + + - `range: Array[Float]` + + The range of the score. Defaults to `[0, 1]`. + + - `sampling_params: SamplingParams{ max_completions_tokens, reasoning_effort, seed, 2 more}` + + The sampling parameters for the model. + + - `max_completions_tokens: Integer` + + The maximum number of tokens the grader model may generate in its response. + + - `reasoning_effort: ReasoningEffort` + + Constrains effort on reasoning for + [reasoning models](https://platform.openai.com/docs/guides/reasoning). + Currently supported values are `none`, `minimal`, `low`, `medium`, `high`, and `xhigh`. Reducing + reasoning effort can result in faster responses and fewer tokens used + on reasoning in a response. + + - `gpt-5.1` defaults to `none`, which does not perform reasoning. The supported reasoning values for `gpt-5.1` are `none`, `low`, `medium`, and `high`. Tool calls are supported for all reasoning values in gpt-5.1. + - All models before `gpt-5.1` default to `medium` reasoning effort, and do not support `none`. + - The `gpt-5-pro` model defaults to (and only supports) `high` reasoning effort. + - `xhigh` is supported for all models after `gpt-5.1-codex-max`. + + - `:none` + + - `:minimal` + + - `:low` + + - `:medium` + + - `:high` + + - `:xhigh` + + - `seed: Integer` + + A seed value to initialize the randomness, during sampling. + + - `temperature: Float` + + A higher temperature increases randomness in the outputs. + + - `top_p: Float` + + An alternative to temperature for nucleus sampling; 1.0 includes all tokens. + + - `class MultiGrader` + + A MultiGrader object combines the output of multiple graders to produce a single score. + + - `calculate_output: String` + + A formula to calculate the output based on grader results. + + - `graders: StringCheckGrader | TextSimilarityGrader | PythonGrader | 2 more` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `class StringCheckGrader` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `class TextSimilarityGrader` + + A TextSimilarityGrader object which grades text based on similarity metrics. + + - `class PythonGrader` + + A PythonGrader object that runs a python script on the input. + + - `class ScoreModelGrader` + + A ScoreModelGrader object that uses a model to assign a score to the input. + + - `class LabelModelGrader` + + A LabelModelGrader object which uses a model to assign labels to each item + in the evaluation. + + - `input: Array[Input{ content, role, type}]` + + - `content: String | ResponseInputText | OutputText{ text, type} | 3 more` + + Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items. + + - `String = String` + + A text input to the model. + + - `class ResponseInputText` + + A text input to the model. + + - `class OutputText` + + A text output from the model. + + - `text: String` + + The text output from the model. + + - `type: :output_text` + + The type of the output text. Always `output_text`. + + - `:output_text` + + - `class InputImage` + + An image input block used within EvalItem content arrays. + + - `image_url: String` + + The URL of the image input. + + - `type: :input_image` + + The type of the image input. Always `input_image`. + + - `:input_image` + + - `detail: String` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `class ResponseInputAudio` + + An audio input to the model. + + - `GraderInputs = Array[GraderInputItem]` + + A list of inputs, each of which may be either an input text, output text, input + image, or input audio object. + + - `role: :user | :assistant | :system | :developer` + + The role of the message input. One of `user`, `assistant`, `system`, or + `developer`. + + - `:user` + + - `:assistant` + + - `:system` + + - `:developer` + + - `type: :message` + + The type of the message input. Always `message`. + + - `:message` + + - `labels: Array[String]` + + The labels to assign to each item in the evaluation. + + - `model: String` + + The model to use for the evaluation. Must support structured outputs. + + - `name: String` + + The name of the grader. + + - `passing_labels: Array[String]` + + The labels that indicate a passing result. Must be a subset of labels. + + - `type: :label_model` + + The object type, which is always `label_model`. + + - `:label_model` + + - `name: String` + + The name of the grader. + + - `type: :multi` + + The object type, which is always `multi`. + + - `:multi` + + - `hyperparameters: ReinforcementHyperparameters` + + The hyperparameters used for the reinforcement fine-tuning job. + + - `batch_size: :auto | Integer` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `BatchSize = :auto` + + - `:auto` + + - `Integer = Integer` + + - `compute_multiplier: :auto | Float` + + Multiplier on amount of compute used for exploring search space during training. + + - `ComputeMultiplier = :auto` + + - `:auto` + + - `Float = Float` + + - `eval_interval: :auto | Integer` + + The number of training steps between evaluation runs. + + - `EvalInterval = :auto` + + - `:auto` + + - `Integer = Integer` + + - `eval_samples: :auto | Integer` + + Number of evaluation samples to generate per training step. + + - `EvalSamples = :auto` + + - `:auto` + + - `Integer = Integer` + + - `learning_rate_multiplier: :auto | Float` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `LearningRateMultiplier = :auto` + + - `:auto` + + - `Float = Float` + + - `n_epochs: :auto | Integer` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `NEpochs = :auto` + + - `:auto` + + - `Integer = Integer` + + - `reasoning_effort: :default | :low | :medium | :high` + + Level of reasoning effort. + + - `:default` + + - `:low` + + - `:medium` + + - `:high` + + - `supervised: SupervisedMethod` + + Configuration for the supervised fine-tuning method. + + - `hyperparameters: SupervisedHyperparameters` + + The hyperparameters used for the fine-tuning job. + + - `batch_size: :auto | Integer` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `BatchSize = :auto` + + - `:auto` + + - `Integer = Integer` + + - `learning_rate_multiplier: :auto | Float` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `LearningRateMultiplier = :auto` + + - `:auto` + + - `Float = Float` + + - `n_epochs: :auto | Integer` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `NEpochs = :auto` + + - `:auto` + + - `Integer = Integer` + +### Fine Tuning Job Event + +- `class FineTuningJobEvent` + + Fine-tuning job event object + + - `id: String` + + The object identifier. + + - `created_at: Integer` + + The Unix timestamp (in seconds) for when the fine-tuning job was created. + + - `level: :info | :warn | :error` + + The log level of the event. + + - `:info` + + - `:warn` + + - `:error` + + - `message: String` + + The message of the event. + + - `object: :"fine_tuning.job.event"` + + The object type, which is always "fine_tuning.job.event". + + - `:"fine_tuning.job.event"` + + - `data: untyped` + + The data associated with the event. + + - `type: :message | :metrics` + + The type of event. + + - `:message` + + - `:metrics` + +### Fine Tuning Job Wandb Integration + +- `class FineTuningJobWandbIntegration` + + The settings for your integration with Weights and Biases. This payload specifies the project that + metrics will be sent to. Optionally, you can set an explicit display name for your run, add tags + to your run, and set a default entity (team, username, etc) to be associated with your run. + + - `project: String` + + The name of the project that the new run will be created under. + + - `entity: String` + + 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 run. If not set, the default entity for the registered WandB API key is used. + + - `name: String` + + A display name to set for the run. If not set, we will use the Job ID as the name. + + - `tags: Array[String]` + + A list of tags to be attached to the newly created run. These tags are passed through directly to WandB. Some + default tags are generated by OpenAI: "openai/finetune", "openai/{base-model}", "openai/{ftjob-abcdef}". + +### Fine Tuning Job Wandb Integration Object + +- `class FineTuningJobWandbIntegrationObject` + + - `type: :wandb` + + The type of the integration being enabled for the fine-tuning job + + - `:wandb` + + - `wandb: FineTuningJobWandbIntegration` + + The settings for your integration with Weights and Biases. This payload specifies the project that + metrics will be sent to. Optionally, you can set an explicit display name for your run, add tags + to your run, and set a default entity (team, username, etc) to be associated with your run. + + - `project: String` + + The name of the project that the new run will be created under. + + - `entity: String` + + 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 run. If not set, the default entity for the registered WandB API key is used. + + - `name: String` + + A display name to set for the run. If not set, we will use the Job ID as the name. + + - `tags: Array[String]` + + A list of tags to be attached to the newly created run. These tags are passed through directly to WandB. Some + default tags are generated by OpenAI: "openai/finetune", "openai/{base-model}", "openai/{ftjob-abcdef}". + +# Checkpoints + +## List fine-tuning checkpoints + +`fine_tuning.jobs.checkpoints.list(fine_tuning_job_id, **kwargs) -> CursorPage` + +**get** `/fine_tuning/jobs/{fine_tuning_job_id}/checkpoints` + +List checkpoints for a fine-tuning job. + +### Parameters + +- `fine_tuning_job_id: String` + +- `after: String` + + Identifier for the last checkpoint ID from the previous pagination request. + +- `limit: Integer` + + Number of checkpoints to retrieve. + +### Returns + +- `class FineTuningJobCheckpoint` + + The `fine_tuning.job.checkpoint` object represents a model checkpoint for a fine-tuning job that is ready to use. + + - `id: String` + + The checkpoint identifier, which can be referenced in the API endpoints. + + - `created_at: Integer` + + The Unix timestamp (in seconds) for when the checkpoint was created. + + - `fine_tuned_model_checkpoint: String` + + The name of the fine-tuned checkpoint model that is created. + + - `fine_tuning_job_id: String` + + The name of the fine-tuning job that this checkpoint was created from. + + - `metrics: Metrics{ full_valid_loss, full_valid_mean_token_accuracy, step, 4 more}` + + Metrics at the step number during the fine-tuning job. + + - `full_valid_loss: Float` + + - `full_valid_mean_token_accuracy: Float` + + - `step: Float` + + - `train_loss: Float` + + - `train_mean_token_accuracy: Float` + + - `valid_loss: Float` + + - `valid_mean_token_accuracy: Float` + + - `object: :"fine_tuning.job.checkpoint"` + + The object type, which is always "fine_tuning.job.checkpoint". + + - `:"fine_tuning.job.checkpoint"` + + - `step_number: Integer` + + The step number that the checkpoint was created at. + +### Example + +```ruby +require "openai" + +openai = OpenAI::Client.new(api_key: "My API Key") + +page = openai.fine_tuning.jobs.checkpoints.list("ft-AF1WoRqd3aJAHsqc9NY7iL8F") + +puts(page) +``` + +#### Response + +```json +{ + "data": [ + { + "id": "id", + "created_at": 0, + "fine_tuned_model_checkpoint": "fine_tuned_model_checkpoint", + "fine_tuning_job_id": "fine_tuning_job_id", + "metrics": { + "full_valid_loss": 0, + "full_valid_mean_token_accuracy": 0, + "step": 0, + "train_loss": 0, + "train_mean_token_accuracy": 0, + "valid_loss": 0, + "valid_mean_token_accuracy": 0 + }, + "object": "fine_tuning.job.checkpoint", + "step_number": 0 + } + ], + "has_more": true, + "object": "list", + "first_id": "first_id", + "last_id": "last_id" +} +``` + +## Domain Types + +### Fine Tuning Job Checkpoint + +- `class FineTuningJobCheckpoint` + + The `fine_tuning.job.checkpoint` object represents a model checkpoint for a fine-tuning job that is ready to use. + + - `id: String` + + The checkpoint identifier, which can be referenced in the API endpoints. + + - `created_at: Integer` + + The Unix timestamp (in seconds) for when the checkpoint was created. + + - `fine_tuned_model_checkpoint: String` + + The name of the fine-tuned checkpoint model that is created. + + - `fine_tuning_job_id: String` + + The name of the fine-tuning job that this checkpoint was created from. + + - `metrics: Metrics{ full_valid_loss, full_valid_mean_token_accuracy, step, 4 more}` + + Metrics at the step number during the fine-tuning job. + + - `full_valid_loss: Float` + + - `full_valid_mean_token_accuracy: Float` + + - `step: Float` + + - `train_loss: Float` + + - `train_mean_token_accuracy: Float` + + - `valid_loss: Float` + + - `valid_mean_token_accuracy: Float` + + - `object: :"fine_tuning.job.checkpoint"` + + The object type, which is always "fine_tuning.job.checkpoint". + + - `:"fine_tuning.job.checkpoint"` + + - `step_number: Integer` + + The step number that the checkpoint was created at. + +# Checkpoints + +# Permissions + +## List checkpoint permissions + +`fine_tuning.checkpoints.permissions.retrieve(fine_tuned_model_checkpoint, **kwargs) -> PermissionRetrieveResponse` + +**get** `/fine_tuning/checkpoints/{fine_tuned_model_checkpoint}/permissions` + +**NOTE:** This endpoint requires an [admin API key](../admin-api-keys). + +Organization owners can use this endpoint to view all permissions for a fine-tuned model checkpoint. + +### Parameters + +- `fine_tuned_model_checkpoint: String` + +- `after: String` + + Identifier for the last permission ID from the previous pagination request. + +- `limit: Integer` + + Number of permissions to retrieve. + +- `order: :ascending | :descending` + + The order in which to retrieve permissions. + + - `:ascending` + + - `:descending` + +- `project_id: String` + + The ID of the project to get permissions for. + +### Returns + +- `class PermissionRetrieveResponse` + + - `data: Array[Data{ id, created_at, object, project_id}]` + + - `id: String` + + The permission identifier, which can be referenced in the API endpoints. + + - `created_at: Integer` + + The Unix timestamp (in seconds) for when the permission was created. + + - `object: :"checkpoint.permission"` + + The object type, which is always "checkpoint.permission". + + - `:"checkpoint.permission"` + + - `project_id: String` + + The project identifier that the permission is for. + + - `has_more: bool` + + - `object: :list` + + - `:list` + + - `first_id: String` + + - `last_id: String` + +### Example + +```ruby +require "openai" + +openai = OpenAI::Client.new(api_key: "My API Key") + +permission = openai.fine_tuning.checkpoints.permissions.retrieve("ft-AF1WoRqd3aJAHsqc9NY7iL8F") + +puts(permission) +``` + +#### Response + +```json +{ + "data": [ + { + "id": "id", + "created_at": 0, + "object": "checkpoint.permission", + "project_id": "project_id" + } + ], + "has_more": true, + "object": "list", + "first_id": "first_id", + "last_id": "last_id" +} +``` + +## List checkpoint permissions + +`fine_tuning.checkpoints.permissions.list(fine_tuned_model_checkpoint, **kwargs) -> ConversationCursorPage` + +**get** `/fine_tuning/checkpoints/{fine_tuned_model_checkpoint}/permissions` + +**NOTE:** This endpoint requires an [admin API key](../admin-api-keys). + +Organization owners can use this endpoint to view all permissions for a fine-tuned model checkpoint. + +### Parameters + +- `fine_tuned_model_checkpoint: String` + +- `after: String` + + Identifier for the last permission ID from the previous pagination request. + +- `limit: Integer` + + Number of permissions to retrieve. + +- `order: :ascending | :descending` + + The order in which to retrieve permissions. + + - `:ascending` + + - `:descending` + +- `project_id: String` + + The ID of the project to get permissions for. + +### Returns + +- `class PermissionListResponse` + + The `checkpoint.permission` object represents a permission for a fine-tuned model checkpoint. + + - `id: String` + + The permission identifier, which can be referenced in the API endpoints. + + - `created_at: Integer` + + The Unix timestamp (in seconds) for when the permission was created. + + - `object: :"checkpoint.permission"` + + The object type, which is always "checkpoint.permission". + + - `:"checkpoint.permission"` + + - `project_id: String` + + The project identifier that the permission is for. + +### Example + +```ruby +require "openai" + +openai = OpenAI::Client.new(api_key: "My API Key") + +page = openai.fine_tuning.checkpoints.permissions.list("ft-AF1WoRqd3aJAHsqc9NY7iL8F") + +puts(page) +``` + +#### Response + +```json +{ + "data": [ + { + "id": "id", + "created_at": 0, + "object": "checkpoint.permission", + "project_id": "project_id" + } + ], + "has_more": true, + "object": "list", + "first_id": "first_id", + "last_id": "last_id" +} +``` + +## Create checkpoint permissions + +`fine_tuning.checkpoints.permissions.create(fine_tuned_model_checkpoint, **kwargs) -> Page` + +**post** `/fine_tuning/checkpoints/{fine_tuned_model_checkpoint}/permissions` + +**NOTE:** Calling this endpoint requires an [admin API key](../admin-api-keys). + +This enables organization owners to share fine-tuned models with other projects in their organization. + +### Parameters + +- `fine_tuned_model_checkpoint: String` + +- `project_ids: Array[String]` + + The project identifiers to grant access to. + +### Returns + +- `class PermissionCreateResponse` + + The `checkpoint.permission` object represents a permission for a fine-tuned model checkpoint. + + - `id: String` + + The permission identifier, which can be referenced in the API endpoints. + + - `created_at: Integer` + + The Unix timestamp (in seconds) for when the permission was created. + + - `object: :"checkpoint.permission"` + + The object type, which is always "checkpoint.permission". + + - `:"checkpoint.permission"` + + - `project_id: String` + + The project identifier that the permission is for. + +### Example + +```ruby +require "openai" + +openai = OpenAI::Client.new(api_key: "My API Key") + +page = openai.fine_tuning.checkpoints.permissions.create( + "ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd", + project_ids: ["string"] +) + +puts(page) +``` + +#### Response + +```json +{ + "data": [ + { + "id": "id", + "created_at": 0, + "object": "checkpoint.permission", + "project_id": "project_id" + } + ], + "has_more": true, + "object": "list", + "first_id": "first_id", + "last_id": "last_id" +} +``` + +## Delete checkpoint permission + +`fine_tuning.checkpoints.permissions.delete(permission_id, **kwargs) -> PermissionDeleteResponse` + +**delete** `/fine_tuning/checkpoints/{fine_tuned_model_checkpoint}/permissions/{permission_id}` + +**NOTE:** This endpoint requires an [admin API key](../admin-api-keys). + +Organization owners can use this endpoint to delete a permission for a fine-tuned model checkpoint. + +### Parameters + +- `fine_tuned_model_checkpoint: String` + +- `permission_id: String` + +### Returns + +- `class PermissionDeleteResponse` + + - `id: String` + + The ID of the fine-tuned model checkpoint permission that was deleted. + + - `deleted: bool` + + Whether the fine-tuned model checkpoint permission was successfully deleted. + + - `object: :"checkpoint.permission"` + + The object type, which is always "checkpoint.permission". + + - `:"checkpoint.permission"` + +### Example + +```ruby +require "openai" + +openai = OpenAI::Client.new(api_key: "My API Key") + +permission = openai.fine_tuning.checkpoints.permissions.delete( + "cp_zc4Q7MP6XxulcVzj4MZdwsAB", + fine_tuned_model_checkpoint: "ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd" +) + +puts(permission) +``` + +#### Response + +```json +{ + "id": "id", + "deleted": true, + "object": "checkpoint.permission" +} +``` + +## Domain Types + +### Permission Retrieve Response + +- `class PermissionRetrieveResponse` + + - `data: Array[Data{ id, created_at, object, project_id}]` + + - `id: String` + + The permission identifier, which can be referenced in the API endpoints. + + - `created_at: Integer` + + The Unix timestamp (in seconds) for when the permission was created. + + - `object: :"checkpoint.permission"` + + The object type, which is always "checkpoint.permission". + + - `:"checkpoint.permission"` + + - `project_id: String` + + The project identifier that the permission is for. + + - `has_more: bool` + + - `object: :list` + + - `:list` + + - `first_id: String` + + - `last_id: String` + +### Permission List Response + +- `class PermissionListResponse` + + The `checkpoint.permission` object represents a permission for a fine-tuned model checkpoint. + + - `id: String` + + The permission identifier, which can be referenced in the API endpoints. + + - `created_at: Integer` + + The Unix timestamp (in seconds) for when the permission was created. + + - `object: :"checkpoint.permission"` + + The object type, which is always "checkpoint.permission". + + - `:"checkpoint.permission"` + + - `project_id: String` + + The project identifier that the permission is for. + +### Permission Create Response + +- `class PermissionCreateResponse` + + The `checkpoint.permission` object represents a permission for a fine-tuned model checkpoint. + + - `id: String` + + The permission identifier, which can be referenced in the API endpoints. + + - `created_at: Integer` + + The Unix timestamp (in seconds) for when the permission was created. + + - `object: :"checkpoint.permission"` + + The object type, which is always "checkpoint.permission". + + - `:"checkpoint.permission"` + + - `project_id: String` + + The project identifier that the permission is for. + +### Permission Delete Response + +- `class PermissionDeleteResponse` + + - `id: String` + + The ID of the fine-tuned model checkpoint permission that was deleted. + + - `deleted: bool` + + Whether the fine-tuned model checkpoint permission was successfully deleted. + + - `object: :"checkpoint.permission"` + + The object type, which is always "checkpoint.permission". + + - `:"checkpoint.permission"` + +# Alpha + +# Graders + +## Run grader + +`fine_tuning.alpha.graders.run(**kwargs) -> GraderRunResponse` + +**post** `/fine_tuning/alpha/graders/run` + +Run a grader. + +### Parameters + +- `grader: StringCheckGrader | TextSimilarityGrader | PythonGrader | 2 more` + + The grader used for the fine-tuning job. + + - `class StringCheckGrader` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `input: String` + + The input text. This may include template strings. + + - `name: String` + + The name of the grader. + + - `operation: :eq | :ne | :like | :ilike` + + The string check operation to perform. One of `eq`, `ne`, `like`, or `ilike`. + + - `:eq` + + - `:ne` + + - `:like` + + - `:ilike` + + - `reference: String` + + The reference text. This may include template strings. + + - `type: :string_check` + + The object type, which is always `string_check`. + + - `:string_check` + + - `class TextSimilarityGrader` + + A TextSimilarityGrader object which grades text based on similarity metrics. + + - `evaluation_metric: :cosine | :fuzzy_match | :bleu | 8 more` + + The evaluation metric to use. One of `cosine`, `fuzzy_match`, `bleu`, + `gleu`, `meteor`, `rouge_1`, `rouge_2`, `rouge_3`, `rouge_4`, `rouge_5`, + or `rouge_l`. + + - `:cosine` + + - `:fuzzy_match` + + - `:bleu` + + - `:gleu` + + - `:meteor` + + - `:rouge_1` + + - `:rouge_2` + + - `:rouge_3` + + - `:rouge_4` + + - `:rouge_5` + + - `:rouge_l` + + - `input: String` + + The text being graded. + + - `name: String` + + The name of the grader. + + - `reference: String` + + The text being graded against. + + - `type: :text_similarity` + + The type of grader. + + - `:text_similarity` + + - `class PythonGrader` + + A PythonGrader object that runs a python script on the input. + + - `name: String` + + The name of the grader. + + - `source: String` + + The source code of the python script. + + - `type: :python` + + The object type, which is always `python`. + + - `:python` + + - `image_tag: String` + + The image tag to use for the python script. + + - `class ScoreModelGrader` + + A ScoreModelGrader object that uses a model to assign a score to the input. + + - `input: Array[Input{ content, role, type}]` + + The input messages evaluated by the grader. Supports text, output text, input image, and input audio content blocks, and may include template strings. + + - `content: String | ResponseInputText | OutputText{ text, type} | 3 more` + + Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items. + + - `String = String` + + A text input to the model. + + - `class ResponseInputText` + + A text input to the model. + + - `text: String` + + The text input to the model. + + - `type: :input_text` + + The type of the input item. Always `input_text`. + + - `:input_text` + + - `class OutputText` + + A text output from the model. + + - `text: String` + + The text output from the model. + + - `type: :output_text` + + The type of the output text. Always `output_text`. + + - `:output_text` + + - `class InputImage` + + An image input block used within EvalItem content arrays. + + - `image_url: String` + + The URL of the image input. + + - `type: :input_image` + + The type of the image input. Always `input_image`. + + - `:input_image` + + - `detail: String` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `class ResponseInputAudio` + + An audio input to the model. + + - `input_audio: InputAudio{ data, format_}` + + - `data: String` + + Base64-encoded audio data. + + - `format_: :mp3 | :wav` + + The format of the audio data. Currently supported formats are `mp3` and + `wav`. + + - `:mp3` + + - `:wav` + + - `type: :input_audio` + + The type of the input item. Always `input_audio`. + + - `:input_audio` + + - `GraderInputs = Array[GraderInputItem]` + + A list of inputs, each of which may be either an input text, output text, input + image, or input audio object. + + - `String = String` + + A text input to the model. + + - `class ResponseInputText` + + A text input to the model. + + - `class OutputText` + + A text output from the model. + + - `text: String` + + The text output from the model. + + - `type: :output_text` + + The type of the output text. Always `output_text`. + + - `:output_text` + + - `class InputImage` + + An image input block used within EvalItem content arrays. + + - `image_url: String` + + The URL of the image input. + + - `type: :input_image` + + The type of the image input. Always `input_image`. + + - `:input_image` + + - `detail: String` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `class ResponseInputAudio` + + An audio input to the model. + + - `role: :user | :assistant | :system | :developer` + + The role of the message input. One of `user`, `assistant`, `system`, or + `developer`. + + - `:user` + + - `:assistant` + + - `:system` + + - `:developer` + + - `type: :message` + + The type of the message input. Always `message`. + + - `:message` + + - `model: String` + + The model to use for the evaluation. + + - `name: String` + + The name of the grader. + + - `type: :score_model` + + The object type, which is always `score_model`. + + - `:score_model` + + - `range: Array[Float]` + + The range of the score. Defaults to `[0, 1]`. + + - `sampling_params: SamplingParams{ max_completions_tokens, reasoning_effort, seed, 2 more}` + + The sampling parameters for the model. + + - `max_completions_tokens: Integer` + + The maximum number of tokens the grader model may generate in its response. + + - `reasoning_effort: ReasoningEffort` + + Constrains effort on reasoning for + [reasoning models](https://platform.openai.com/docs/guides/reasoning). + Currently supported values are `none`, `minimal`, `low`, `medium`, `high`, and `xhigh`. Reducing + reasoning effort can result in faster responses and fewer tokens used + on reasoning in a response. + + - `gpt-5.1` defaults to `none`, which does not perform reasoning. The supported reasoning values for `gpt-5.1` are `none`, `low`, `medium`, and `high`. Tool calls are supported for all reasoning values in gpt-5.1. + - All models before `gpt-5.1` default to `medium` reasoning effort, and do not support `none`. + - The `gpt-5-pro` model defaults to (and only supports) `high` reasoning effort. + - `xhigh` is supported for all models after `gpt-5.1-codex-max`. + + - `:none` + + - `:minimal` + + - `:low` + + - `:medium` + + - `:high` + + - `:xhigh` + + - `seed: Integer` + + A seed value to initialize the randomness, during sampling. + + - `temperature: Float` + + A higher temperature increases randomness in the outputs. + + - `top_p: Float` + + An alternative to temperature for nucleus sampling; 1.0 includes all tokens. + + - `class MultiGrader` + + A MultiGrader object combines the output of multiple graders to produce a single score. + + - `calculate_output: String` + + A formula to calculate the output based on grader results. + + - `graders: StringCheckGrader | TextSimilarityGrader | PythonGrader | 2 more` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `class StringCheckGrader` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `class TextSimilarityGrader` + + A TextSimilarityGrader object which grades text based on similarity metrics. + + - `class PythonGrader` + + A PythonGrader object that runs a python script on the input. + + - `class ScoreModelGrader` + + A ScoreModelGrader object that uses a model to assign a score to the input. + + - `class LabelModelGrader` + + A LabelModelGrader object which uses a model to assign labels to each item + in the evaluation. + + - `input: Array[Input{ content, role, type}]` + + - `content: String | ResponseInputText | OutputText{ text, type} | 3 more` + + Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items. + + - `String = String` + + A text input to the model. + + - `class ResponseInputText` + + A text input to the model. + + - `class OutputText` + + A text output from the model. + + - `text: String` + + The text output from the model. + + - `type: :output_text` + + The type of the output text. Always `output_text`. + + - `:output_text` + + - `class InputImage` + + An image input block used within EvalItem content arrays. + + - `image_url: String` + + The URL of the image input. + + - `type: :input_image` + + The type of the image input. Always `input_image`. + + - `:input_image` + + - `detail: String` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `class ResponseInputAudio` + + An audio input to the model. + + - `GraderInputs = Array[GraderInputItem]` + + A list of inputs, each of which may be either an input text, output text, input + image, or input audio object. + + - `role: :user | :assistant | :system | :developer` + + The role of the message input. One of `user`, `assistant`, `system`, or + `developer`. + + - `:user` + + - `:assistant` + + - `:system` + + - `:developer` + + - `type: :message` + + The type of the message input. Always `message`. + + - `:message` + + - `labels: Array[String]` + + The labels to assign to each item in the evaluation. + + - `model: String` + + The model to use for the evaluation. Must support structured outputs. + + - `name: String` + + The name of the grader. + + - `passing_labels: Array[String]` + + The labels that indicate a passing result. Must be a subset of labels. + + - `type: :label_model` + + The object type, which is always `label_model`. + + - `:label_model` + + - `name: String` + + The name of the grader. + + - `type: :multi` + + The object type, which is always `multi`. + + - `:multi` + +- `model_sample: String` + + The model sample to be evaluated. This value will be used to populate + the `sample` namespace. See [the guide](https://platform.openai.com/docs/guides/graders) for more details. + The `output_json` variable will be populated if the model sample is a + valid JSON string. + +- `item: untyped` + + The dataset item provided to the grader. This will be used to populate + the `item` namespace. See [the guide](https://platform.openai.com/docs/guides/graders) for more details. + +### Returns + +- `class GraderRunResponse` + + - `metadata: Metadata{ errors, execution_time, name, 4 more}` + + - `errors: Errors{ formula_parse_error, invalid_variable_error, model_grader_parse_error, 11 more}` + + - `formula_parse_error: bool` + + - `invalid_variable_error: bool` + + - `model_grader_parse_error: bool` + + - `model_grader_refusal_error: bool` + + - `model_grader_server_error: bool` + + - `model_grader_server_error_details: String` + + - `other_error: bool` + + - `python_grader_runtime_error: bool` + + - `python_grader_runtime_error_details: String` + + - `python_grader_server_error: bool` + + - `python_grader_server_error_type: String` + + - `sample_parse_error: bool` + + - `truncated_observation_error: bool` + + - `unresponsive_reward_error: bool` + + - `execution_time: Float` + + - `name: String` + + - `sampled_model_name: String` + + - `scores: Hash[Symbol, untyped]` + + - `token_usage: Integer` + + - `type: String` + + - `model_grader_token_usage_per_model: Hash[Symbol, untyped]` + + - `reward: Float` + + - `sub_rewards: Hash[Symbol, untyped]` + +### Example + +```ruby +require "openai" + +openai = OpenAI::Client.new(api_key: "My API Key") + +response = openai.fine_tuning.alpha.graders.run( + grader: {input: "input", name: "name", operation: :eq, reference: "reference", type: :string_check}, + model_sample: "model_sample" +) + +puts(response) +``` + +#### Response + +```json +{ + "metadata": { + "errors": { + "formula_parse_error": true, + "invalid_variable_error": true, + "model_grader_parse_error": true, + "model_grader_refusal_error": true, + "model_grader_server_error": true, + "model_grader_server_error_details": "model_grader_server_error_details", + "other_error": true, + "python_grader_runtime_error": true, + "python_grader_runtime_error_details": "python_grader_runtime_error_details", + "python_grader_server_error": true, + "python_grader_server_error_type": "python_grader_server_error_type", + "sample_parse_error": true, + "truncated_observation_error": true, + "unresponsive_reward_error": true + }, + "execution_time": 0, + "name": "name", + "sampled_model_name": "sampled_model_name", + "scores": { + "foo": "bar" + }, + "token_usage": 0, + "type": "type" + }, + "model_grader_token_usage_per_model": { + "foo": "bar" + }, + "reward": 0, + "sub_rewards": { + "foo": "bar" + } +} +``` + +## Validate grader + +`fine_tuning.alpha.graders.validate(**kwargs) -> GraderValidateResponse` + +**post** `/fine_tuning/alpha/graders/validate` + +Validate a grader. + +### Parameters + +- `grader: StringCheckGrader | TextSimilarityGrader | PythonGrader | 2 more` + + The grader used for the fine-tuning job. + + - `class StringCheckGrader` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `input: String` + + The input text. This may include template strings. + + - `name: String` + + The name of the grader. + + - `operation: :eq | :ne | :like | :ilike` + + The string check operation to perform. One of `eq`, `ne`, `like`, or `ilike`. + + - `:eq` + + - `:ne` + + - `:like` + + - `:ilike` + + - `reference: String` + + The reference text. This may include template strings. + + - `type: :string_check` + + The object type, which is always `string_check`. + + - `:string_check` + + - `class TextSimilarityGrader` + + A TextSimilarityGrader object which grades text based on similarity metrics. + + - `evaluation_metric: :cosine | :fuzzy_match | :bleu | 8 more` + + The evaluation metric to use. One of `cosine`, `fuzzy_match`, `bleu`, + `gleu`, `meteor`, `rouge_1`, `rouge_2`, `rouge_3`, `rouge_4`, `rouge_5`, + or `rouge_l`. + + - `:cosine` + + - `:fuzzy_match` + + - `:bleu` + + - `:gleu` + + - `:meteor` + + - `:rouge_1` + + - `:rouge_2` + + - `:rouge_3` + + - `:rouge_4` + + - `:rouge_5` + + - `:rouge_l` + + - `input: String` + + The text being graded. + + - `name: String` + + The name of the grader. + + - `reference: String` + + The text being graded against. + + - `type: :text_similarity` + + The type of grader. + + - `:text_similarity` + + - `class PythonGrader` + + A PythonGrader object that runs a python script on the input. + + - `name: String` + + The name of the grader. + + - `source: String` + + The source code of the python script. + + - `type: :python` + + The object type, which is always `python`. + + - `:python` + + - `image_tag: String` + + The image tag to use for the python script. + + - `class ScoreModelGrader` + + A ScoreModelGrader object that uses a model to assign a score to the input. + + - `input: Array[Input{ content, role, type}]` + + The input messages evaluated by the grader. Supports text, output text, input image, and input audio content blocks, and may include template strings. + + - `content: String | ResponseInputText | OutputText{ text, type} | 3 more` + + Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items. + + - `String = String` + + A text input to the model. + + - `class ResponseInputText` + + A text input to the model. + + - `text: String` + + The text input to the model. + + - `type: :input_text` + + The type of the input item. Always `input_text`. + + - `:input_text` + + - `class OutputText` + + A text output from the model. + + - `text: String` + + The text output from the model. + + - `type: :output_text` + + The type of the output text. Always `output_text`. + + - `:output_text` + + - `class InputImage` + + An image input block used within EvalItem content arrays. + + - `image_url: String` + + The URL of the image input. + + - `type: :input_image` + + The type of the image input. Always `input_image`. + + - `:input_image` + + - `detail: String` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `class ResponseInputAudio` + + An audio input to the model. + + - `input_audio: InputAudio{ data, format_}` + + - `data: String` + + Base64-encoded audio data. + + - `format_: :mp3 | :wav` + + The format of the audio data. Currently supported formats are `mp3` and + `wav`. + + - `:mp3` + + - `:wav` + + - `type: :input_audio` + + The type of the input item. Always `input_audio`. + + - `:input_audio` + + - `GraderInputs = Array[GraderInputItem]` + + A list of inputs, each of which may be either an input text, output text, input + image, or input audio object. + + - `String = String` + + A text input to the model. + + - `class ResponseInputText` + + A text input to the model. + + - `class OutputText` + + A text output from the model. + + - `text: String` + + The text output from the model. + + - `type: :output_text` + + The type of the output text. Always `output_text`. + + - `:output_text` + + - `class InputImage` + + An image input block used within EvalItem content arrays. + + - `image_url: String` + + The URL of the image input. + + - `type: :input_image` + + The type of the image input. Always `input_image`. + + - `:input_image` + + - `detail: String` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `class ResponseInputAudio` + + An audio input to the model. + + - `role: :user | :assistant | :system | :developer` + + The role of the message input. One of `user`, `assistant`, `system`, or + `developer`. + + - `:user` + + - `:assistant` + + - `:system` + + - `:developer` + + - `type: :message` + + The type of the message input. Always `message`. + + - `:message` + + - `model: String` + + The model to use for the evaluation. + + - `name: String` + + The name of the grader. + + - `type: :score_model` + + The object type, which is always `score_model`. + + - `:score_model` + + - `range: Array[Float]` + + The range of the score. Defaults to `[0, 1]`. + + - `sampling_params: SamplingParams{ max_completions_tokens, reasoning_effort, seed, 2 more}` + + The sampling parameters for the model. + + - `max_completions_tokens: Integer` + + The maximum number of tokens the grader model may generate in its response. + + - `reasoning_effort: ReasoningEffort` + + Constrains effort on reasoning for + [reasoning models](https://platform.openai.com/docs/guides/reasoning). + Currently supported values are `none`, `minimal`, `low`, `medium`, `high`, and `xhigh`. Reducing + reasoning effort can result in faster responses and fewer tokens used + on reasoning in a response. + + - `gpt-5.1` defaults to `none`, which does not perform reasoning. The supported reasoning values for `gpt-5.1` are `none`, `low`, `medium`, and `high`. Tool calls are supported for all reasoning values in gpt-5.1. + - All models before `gpt-5.1` default to `medium` reasoning effort, and do not support `none`. + - The `gpt-5-pro` model defaults to (and only supports) `high` reasoning effort. + - `xhigh` is supported for all models after `gpt-5.1-codex-max`. + + - `:none` + + - `:minimal` + + - `:low` + + - `:medium` + + - `:high` + + - `:xhigh` + + - `seed: Integer` + + A seed value to initialize the randomness, during sampling. + + - `temperature: Float` + + A higher temperature increases randomness in the outputs. + + - `top_p: Float` + + An alternative to temperature for nucleus sampling; 1.0 includes all tokens. + + - `class MultiGrader` + + A MultiGrader object combines the output of multiple graders to produce a single score. + + - `calculate_output: String` + + A formula to calculate the output based on grader results. + + - `graders: StringCheckGrader | TextSimilarityGrader | PythonGrader | 2 more` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `class StringCheckGrader` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `class TextSimilarityGrader` + + A TextSimilarityGrader object which grades text based on similarity metrics. + + - `class PythonGrader` + + A PythonGrader object that runs a python script on the input. + + - `class ScoreModelGrader` + + A ScoreModelGrader object that uses a model to assign a score to the input. + + - `class LabelModelGrader` + + A LabelModelGrader object which uses a model to assign labels to each item + in the evaluation. + + - `input: Array[Input{ content, role, type}]` + + - `content: String | ResponseInputText | OutputText{ text, type} | 3 more` + + Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items. + + - `String = String` + + A text input to the model. + + - `class ResponseInputText` + + A text input to the model. + + - `class OutputText` + + A text output from the model. + + - `text: String` + + The text output from the model. + + - `type: :output_text` + + The type of the output text. Always `output_text`. + + - `:output_text` + + - `class InputImage` + + An image input block used within EvalItem content arrays. + + - `image_url: String` + + The URL of the image input. + + - `type: :input_image` + + The type of the image input. Always `input_image`. + + - `:input_image` + + - `detail: String` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `class ResponseInputAudio` + + An audio input to the model. + + - `GraderInputs = Array[GraderInputItem]` + + A list of inputs, each of which may be either an input text, output text, input + image, or input audio object. + + - `role: :user | :assistant | :system | :developer` + + The role of the message input. One of `user`, `assistant`, `system`, or + `developer`. + + - `:user` + + - `:assistant` + + - `:system` + + - `:developer` + + - `type: :message` + + The type of the message input. Always `message`. + + - `:message` + + - `labels: Array[String]` + + The labels to assign to each item in the evaluation. + + - `model: String` + + The model to use for the evaluation. Must support structured outputs. + + - `name: String` + + The name of the grader. + + - `passing_labels: Array[String]` + + The labels that indicate a passing result. Must be a subset of labels. + + - `type: :label_model` + + The object type, which is always `label_model`. + + - `:label_model` + + - `name: String` + + The name of the grader. + + - `type: :multi` + + The object type, which is always `multi`. + + - `:multi` + +### Returns + +- `class GraderValidateResponse` + + - `grader: StringCheckGrader | TextSimilarityGrader | PythonGrader | 2 more` + + The grader used for the fine-tuning job. + + - `class StringCheckGrader` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `input: String` + + The input text. This may include template strings. + + - `name: String` + + The name of the grader. + + - `operation: :eq | :ne | :like | :ilike` + + The string check operation to perform. One of `eq`, `ne`, `like`, or `ilike`. + + - `:eq` + + - `:ne` + + - `:like` + + - `:ilike` + + - `reference: String` + + The reference text. This may include template strings. + + - `type: :string_check` + + The object type, which is always `string_check`. + + - `:string_check` + + - `class TextSimilarityGrader` + + A TextSimilarityGrader object which grades text based on similarity metrics. + + - `evaluation_metric: :cosine | :fuzzy_match | :bleu | 8 more` + + The evaluation metric to use. One of `cosine`, `fuzzy_match`, `bleu`, + `gleu`, `meteor`, `rouge_1`, `rouge_2`, `rouge_3`, `rouge_4`, `rouge_5`, + or `rouge_l`. + + - `:cosine` + + - `:fuzzy_match` + + - `:bleu` + + - `:gleu` + + - `:meteor` + + - `:rouge_1` + + - `:rouge_2` + + - `:rouge_3` + + - `:rouge_4` + + - `:rouge_5` + + - `:rouge_l` + + - `input: String` + + The text being graded. + + - `name: String` + + The name of the grader. + + - `reference: String` + + The text being graded against. + + - `type: :text_similarity` + + The type of grader. + + - `:text_similarity` + + - `class PythonGrader` + + A PythonGrader object that runs a python script on the input. + + - `name: String` + + The name of the grader. + + - `source: String` + + The source code of the python script. + + - `type: :python` + + The object type, which is always `python`. + + - `:python` + + - `image_tag: String` + + The image tag to use for the python script. + + - `class ScoreModelGrader` + + A ScoreModelGrader object that uses a model to assign a score to the input. + + - `input: Array[Input{ content, role, type}]` + + The input messages evaluated by the grader. Supports text, output text, input image, and input audio content blocks, and may include template strings. + + - `content: String | ResponseInputText | OutputText{ text, type} | 3 more` + + Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items. + + - `String = String` + + A text input to the model. + + - `class ResponseInputText` + + A text input to the model. + + - `text: String` + + The text input to the model. + + - `type: :input_text` + + The type of the input item. Always `input_text`. + + - `:input_text` + + - `class OutputText` + + A text output from the model. + + - `text: String` + + The text output from the model. + + - `type: :output_text` + + The type of the output text. Always `output_text`. + + - `:output_text` + + - `class InputImage` + + An image input block used within EvalItem content arrays. + + - `image_url: String` + + The URL of the image input. + + - `type: :input_image` + + The type of the image input. Always `input_image`. + + - `:input_image` + + - `detail: String` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `class ResponseInputAudio` + + An audio input to the model. + + - `input_audio: InputAudio{ data, format_}` + + - `data: String` + + Base64-encoded audio data. + + - `format_: :mp3 | :wav` + + The format of the audio data. Currently supported formats are `mp3` and + `wav`. + + - `:mp3` + + - `:wav` + + - `type: :input_audio` + + The type of the input item. Always `input_audio`. + + - `:input_audio` + + - `GraderInputs = Array[GraderInputItem]` + + A list of inputs, each of which may be either an input text, output text, input + image, or input audio object. + + - `String = String` + + A text input to the model. + + - `class ResponseInputText` + + A text input to the model. + + - `class OutputText` + + A text output from the model. + + - `text: String` + + The text output from the model. + + - `type: :output_text` + + The type of the output text. Always `output_text`. + + - `:output_text` + + - `class InputImage` + + An image input block used within EvalItem content arrays. + + - `image_url: String` + + The URL of the image input. + + - `type: :input_image` + + The type of the image input. Always `input_image`. + + - `:input_image` + + - `detail: String` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `class ResponseInputAudio` + + An audio input to the model. + + - `role: :user | :assistant | :system | :developer` + + The role of the message input. One of `user`, `assistant`, `system`, or + `developer`. + + - `:user` + + - `:assistant` + + - `:system` + + - `:developer` + + - `type: :message` + + The type of the message input. Always `message`. + + - `:message` + + - `model: String` + + The model to use for the evaluation. + + - `name: String` + + The name of the grader. + + - `type: :score_model` + + The object type, which is always `score_model`. + + - `:score_model` + + - `range: Array[Float]` + + The range of the score. Defaults to `[0, 1]`. + + - `sampling_params: SamplingParams{ max_completions_tokens, reasoning_effort, seed, 2 more}` + + The sampling parameters for the model. + + - `max_completions_tokens: Integer` + + The maximum number of tokens the grader model may generate in its response. + + - `reasoning_effort: ReasoningEffort` + + Constrains effort on reasoning for + [reasoning models](https://platform.openai.com/docs/guides/reasoning). + Currently supported values are `none`, `minimal`, `low`, `medium`, `high`, and `xhigh`. Reducing + reasoning effort can result in faster responses and fewer tokens used + on reasoning in a response. + + - `gpt-5.1` defaults to `none`, which does not perform reasoning. The supported reasoning values for `gpt-5.1` are `none`, `low`, `medium`, and `high`. Tool calls are supported for all reasoning values in gpt-5.1. + - All models before `gpt-5.1` default to `medium` reasoning effort, and do not support `none`. + - The `gpt-5-pro` model defaults to (and only supports) `high` reasoning effort. + - `xhigh` is supported for all models after `gpt-5.1-codex-max`. + + - `:none` + + - `:minimal` + + - `:low` + + - `:medium` + + - `:high` + + - `:xhigh` + + - `seed: Integer` + + A seed value to initialize the randomness, during sampling. + + - `temperature: Float` + + A higher temperature increases randomness in the outputs. + + - `top_p: Float` + + An alternative to temperature for nucleus sampling; 1.0 includes all tokens. + + - `class MultiGrader` + + A MultiGrader object combines the output of multiple graders to produce a single score. + + - `calculate_output: String` + + A formula to calculate the output based on grader results. + + - `graders: StringCheckGrader | TextSimilarityGrader | PythonGrader | 2 more` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `class StringCheckGrader` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `class TextSimilarityGrader` + + A TextSimilarityGrader object which grades text based on similarity metrics. + + - `class PythonGrader` + + A PythonGrader object that runs a python script on the input. + + - `class ScoreModelGrader` + + A ScoreModelGrader object that uses a model to assign a score to the input. + + - `class LabelModelGrader` + + A LabelModelGrader object which uses a model to assign labels to each item + in the evaluation. + + - `input: Array[Input{ content, role, type}]` + + - `content: String | ResponseInputText | OutputText{ text, type} | 3 more` + + Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items. + + - `String = String` + + A text input to the model. + + - `class ResponseInputText` + + A text input to the model. + + - `class OutputText` + + A text output from the model. + + - `text: String` + + The text output from the model. + + - `type: :output_text` + + The type of the output text. Always `output_text`. + + - `:output_text` + + - `class InputImage` + + An image input block used within EvalItem content arrays. + + - `image_url: String` + + The URL of the image input. + + - `type: :input_image` + + The type of the image input. Always `input_image`. + + - `:input_image` + + - `detail: String` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `class ResponseInputAudio` + + An audio input to the model. + + - `GraderInputs = Array[GraderInputItem]` + + A list of inputs, each of which may be either an input text, output text, input + image, or input audio object. + + - `role: :user | :assistant | :system | :developer` + + The role of the message input. One of `user`, `assistant`, `system`, or + `developer`. + + - `:user` + + - `:assistant` + + - `:system` + + - `:developer` + + - `type: :message` + + The type of the message input. Always `message`. + + - `:message` + + - `labels: Array[String]` + + The labels to assign to each item in the evaluation. + + - `model: String` + + The model to use for the evaluation. Must support structured outputs. + + - `name: String` + + The name of the grader. + + - `passing_labels: Array[String]` + + The labels that indicate a passing result. Must be a subset of labels. + + - `type: :label_model` + + The object type, which is always `label_model`. + + - `:label_model` + + - `name: String` + + The name of the grader. + + - `type: :multi` + + The object type, which is always `multi`. + + - `:multi` + +### Example + +```ruby +require "openai" + +openai = OpenAI::Client.new(api_key: "My API Key") + +response = openai.fine_tuning.alpha.graders.validate( + grader: {input: "input", name: "name", operation: :eq, reference: "reference", type: :string_check} +) + +puts(response) +``` + +#### Response + +```json +{ + "grader": { + "input": "input", + "name": "name", + "operation": "eq", + "reference": "reference", + "type": "string_check" + } +} +``` + +## Domain Types + +### Grader Run Response + +- `class GraderRunResponse` + + - `metadata: Metadata{ errors, execution_time, name, 4 more}` + + - `errors: Errors{ formula_parse_error, invalid_variable_error, model_grader_parse_error, 11 more}` + + - `formula_parse_error: bool` + + - `invalid_variable_error: bool` + + - `model_grader_parse_error: bool` + + - `model_grader_refusal_error: bool` + + - `model_grader_server_error: bool` + + - `model_grader_server_error_details: String` + + - `other_error: bool` + + - `python_grader_runtime_error: bool` + + - `python_grader_runtime_error_details: String` + + - `python_grader_server_error: bool` + + - `python_grader_server_error_type: String` + + - `sample_parse_error: bool` + + - `truncated_observation_error: bool` + + - `unresponsive_reward_error: bool` + + - `execution_time: Float` + + - `name: String` + + - `sampled_model_name: String` + + - `scores: Hash[Symbol, untyped]` + + - `token_usage: Integer` + + - `type: String` + + - `model_grader_token_usage_per_model: Hash[Symbol, untyped]` + + - `reward: Float` + + - `sub_rewards: Hash[Symbol, untyped]` + +### Grader Validate Response + +- `class GraderValidateResponse` + + - `grader: StringCheckGrader | TextSimilarityGrader | PythonGrader | 2 more` + + The grader used for the fine-tuning job. + + - `class StringCheckGrader` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `input: String` + + The input text. This may include template strings. + + - `name: String` + + The name of the grader. + + - `operation: :eq | :ne | :like | :ilike` + + The string check operation to perform. One of `eq`, `ne`, `like`, or `ilike`. + + - `:eq` + + - `:ne` + + - `:like` + + - `:ilike` + + - `reference: String` + + The reference text. This may include template strings. + + - `type: :string_check` + + The object type, which is always `string_check`. + + - `:string_check` + + - `class TextSimilarityGrader` + + A TextSimilarityGrader object which grades text based on similarity metrics. + + - `evaluation_metric: :cosine | :fuzzy_match | :bleu | 8 more` + + The evaluation metric to use. One of `cosine`, `fuzzy_match`, `bleu`, + `gleu`, `meteor`, `rouge_1`, `rouge_2`, `rouge_3`, `rouge_4`, `rouge_5`, + or `rouge_l`. + + - `:cosine` + + - `:fuzzy_match` + + - `:bleu` + + - `:gleu` + + - `:meteor` + + - `:rouge_1` + + - `:rouge_2` + + - `:rouge_3` + + - `:rouge_4` + + - `:rouge_5` + + - `:rouge_l` + + - `input: String` + + The text being graded. + + - `name: String` + + The name of the grader. + + - `reference: String` + + The text being graded against. + + - `type: :text_similarity` + + The type of grader. + + - `:text_similarity` + + - `class PythonGrader` + + A PythonGrader object that runs a python script on the input. + + - `name: String` + + The name of the grader. + + - `source: String` + + The source code of the python script. + + - `type: :python` + + The object type, which is always `python`. + + - `:python` + + - `image_tag: String` + + The image tag to use for the python script. + + - `class ScoreModelGrader` + + A ScoreModelGrader object that uses a model to assign a score to the input. + + - `input: Array[Input{ content, role, type}]` + + The input messages evaluated by the grader. Supports text, output text, input image, and input audio content blocks, and may include template strings. + + - `content: String | ResponseInputText | OutputText{ text, type} | 3 more` + + Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items. + + - `String = String` + + A text input to the model. + + - `class ResponseInputText` + + A text input to the model. + + - `text: String` + + The text input to the model. + + - `type: :input_text` + + The type of the input item. Always `input_text`. + + - `:input_text` + + - `class OutputText` + + A text output from the model. + + - `text: String` + + The text output from the model. + + - `type: :output_text` + + The type of the output text. Always `output_text`. + + - `:output_text` + + - `class InputImage` + + An image input block used within EvalItem content arrays. + + - `image_url: String` + + The URL of the image input. + + - `type: :input_image` + + The type of the image input. Always `input_image`. + + - `:input_image` + + - `detail: String` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `class ResponseInputAudio` + + An audio input to the model. + + - `input_audio: InputAudio{ data, format_}` + + - `data: String` + + Base64-encoded audio data. + + - `format_: :mp3 | :wav` + + The format of the audio data. Currently supported formats are `mp3` and + `wav`. + + - `:mp3` + + - `:wav` + + - `type: :input_audio` + + The type of the input item. Always `input_audio`. + + - `:input_audio` + + - `GraderInputs = Array[GraderInputItem]` + + A list of inputs, each of which may be either an input text, output text, input + image, or input audio object. + + - `String = String` + + A text input to the model. + + - `class ResponseInputText` + + A text input to the model. + + - `class OutputText` + + A text output from the model. + + - `text: String` + + The text output from the model. + + - `type: :output_text` + + The type of the output text. Always `output_text`. + + - `:output_text` + + - `class InputImage` + + An image input block used within EvalItem content arrays. + + - `image_url: String` + + The URL of the image input. + + - `type: :input_image` + + The type of the image input. Always `input_image`. + + - `:input_image` + + - `detail: String` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `class ResponseInputAudio` + + An audio input to the model. + + - `role: :user | :assistant | :system | :developer` + + The role of the message input. One of `user`, `assistant`, `system`, or + `developer`. + + - `:user` + + - `:assistant` + + - `:system` + + - `:developer` + + - `type: :message` + + The type of the message input. Always `message`. + + - `:message` + + - `model: String` + + The model to use for the evaluation. + + - `name: String` + + The name of the grader. + + - `type: :score_model` + + The object type, which is always `score_model`. + + - `:score_model` + + - `range: Array[Float]` + + The range of the score. Defaults to `[0, 1]`. + + - `sampling_params: SamplingParams{ max_completions_tokens, reasoning_effort, seed, 2 more}` + + The sampling parameters for the model. + + - `max_completions_tokens: Integer` + + The maximum number of tokens the grader model may generate in its response. + + - `reasoning_effort: ReasoningEffort` + + Constrains effort on reasoning for + [reasoning models](https://platform.openai.com/docs/guides/reasoning). + Currently supported values are `none`, `minimal`, `low`, `medium`, `high`, and `xhigh`. Reducing + reasoning effort can result in faster responses and fewer tokens used + on reasoning in a response. + + - `gpt-5.1` defaults to `none`, which does not perform reasoning. The supported reasoning values for `gpt-5.1` are `none`, `low`, `medium`, and `high`. Tool calls are supported for all reasoning values in gpt-5.1. + - All models before `gpt-5.1` default to `medium` reasoning effort, and do not support `none`. + - The `gpt-5-pro` model defaults to (and only supports) `high` reasoning effort. + - `xhigh` is supported for all models after `gpt-5.1-codex-max`. + + - `:none` + + - `:minimal` + + - `:low` + + - `:medium` + + - `:high` + + - `:xhigh` + + - `seed: Integer` + + A seed value to initialize the randomness, during sampling. + + - `temperature: Float` + + A higher temperature increases randomness in the outputs. + + - `top_p: Float` + + An alternative to temperature for nucleus sampling; 1.0 includes all tokens. + + - `class MultiGrader` + + A MultiGrader object combines the output of multiple graders to produce a single score. + + - `calculate_output: String` + + A formula to calculate the output based on grader results. + + - `graders: StringCheckGrader | TextSimilarityGrader | PythonGrader | 2 more` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `class StringCheckGrader` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `class TextSimilarityGrader` + + A TextSimilarityGrader object which grades text based on similarity metrics. + + - `class PythonGrader` + + A PythonGrader object that runs a python script on the input. + + - `class ScoreModelGrader` + + A ScoreModelGrader object that uses a model to assign a score to the input. + + - `class LabelModelGrader` + + A LabelModelGrader object which uses a model to assign labels to each item + in the evaluation. + + - `input: Array[Input{ content, role, type}]` + + - `content: String | ResponseInputText | OutputText{ text, type} | 3 more` + + Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items. + + - `String = String` + + A text input to the model. + + - `class ResponseInputText` + + A text input to the model. + + - `class OutputText` + + A text output from the model. + + - `text: String` + + The text output from the model. + + - `type: :output_text` + + The type of the output text. Always `output_text`. + + - `:output_text` + + - `class InputImage` + + An image input block used within EvalItem content arrays. + + - `image_url: String` + + The URL of the image input. + + - `type: :input_image` + + The type of the image input. Always `input_image`. + + - `:input_image` + + - `detail: String` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `class ResponseInputAudio` + + An audio input to the model. + + - `GraderInputs = Array[GraderInputItem]` + + A list of inputs, each of which may be either an input text, output text, input + image, or input audio object. + + - `role: :user | :assistant | :system | :developer` + + The role of the message input. One of `user`, `assistant`, `system`, or + `developer`. + + - `:user` + + - `:assistant` + + - `:system` + + - `:developer` + + - `type: :message` + + The type of the message input. Always `message`. + + - `:message` + + - `labels: Array[String]` + + The labels to assign to each item in the evaluation. + + - `model: String` + + The model to use for the evaluation. Must support structured outputs. + + - `name: String` + + The name of the grader. + + - `passing_labels: Array[String]` + + The labels that indicate a passing result. Must be a subset of labels. + + - `type: :label_model` + + The object type, which is always `label_model`. + + - `:label_model` + + - `name: String` + + The name of the grader. + + - `type: :multi` + + The object type, which is always `multi`. + + - `:multi`