diff --git a/en/ruby/resources/fine_tuning/index.md b/en/ruby/resources/fine_tuning/index.md deleted file mode 100644 index 00f2830..0000000 --- a/en/ruby/resources/fine_tuning/index.md +++ /dev/null @@ -1,10903 +0,0 @@ -# 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`