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+# Fine Tuning
+
+# Methods
+
+## Domain Types
+
+### Dpo Hyperparameters
+
+- `dpo_hyperparameters: object { batch_size, beta, learning_rate_multiplier, n_epochs }`
+
+  The hyperparameters used for the DPO fine-tuning job.
+
+  - `batch_size: optional "auto" or number`
+
+    Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+    - `union_member_0: "auto"`
+
+    - `union_member_1: number`
+
+  - `beta: optional "auto" or number`
+
+    The beta value for the DPO method. A higher beta value will increase the weight of the penalty between the policy and reference model.
+
+    - `union_member_0: "auto"`
+
+    - `union_member_1: number`
+
+  - `learning_rate_multiplier: optional "auto" or number`
+
+    Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+    - `union_member_0: "auto"`
+
+    - `union_member_1: number`
+
+  - `n_epochs: optional "auto" or number`
+
+    The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+    - `union_member_0: "auto"`
+
+    - `union_member_1: number`
+
+### Dpo Method
+
+- `dpo_method: object { hyperparameters }`
+
+  Configuration for the DPO fine-tuning method.
+
+  - `hyperparameters: optional object { batch_size, beta, learning_rate_multiplier, n_epochs }`
+
+    The hyperparameters used for the DPO fine-tuning job.
+
+    - `batch_size: optional "auto" or number`
+
+      Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+      - `union_member_0: "auto"`
+
+      - `union_member_1: number`
+
+    - `beta: optional "auto" or number`
+
+      The beta value for the DPO method. A higher beta value will increase the weight of the penalty between the policy and reference model.
+
+      - `union_member_0: "auto"`
+
+      - `union_member_1: number`
+
+    - `learning_rate_multiplier: optional "auto" or number`
+
+      Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+      - `union_member_0: "auto"`
+
+      - `union_member_1: number`
+
+    - `n_epochs: optional "auto" or number`
+
+      The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+      - `union_member_0: "auto"`
+
+      - `union_member_1: number`
+
+### Reinforcement Hyperparameters
+
+- `reinforcement_hyperparameters: object { batch_size, compute_multiplier, eval_interval, 4 more }`
+
+  The hyperparameters used for the reinforcement fine-tuning job.
+
+  - `batch_size: optional "auto" or number`
+
+    Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+    - `union_member_0: "auto"`
+
+    - `union_member_1: number`
+
+  - `compute_multiplier: optional "auto" or number`
+
+    Multiplier on amount of compute used for exploring search space during training.
+
+    - `union_member_0: "auto"`
+
+    - `union_member_1: number`
+
+  - `eval_interval: optional "auto" or number`
+
+    The number of training steps between evaluation runs.
+
+    - `union_member_0: "auto"`
+
+    - `union_member_1: number`
+
+  - `eval_samples: optional "auto" or number`
+
+    Number of evaluation samples to generate per training step.
+
+    - `union_member_0: "auto"`
+
+    - `union_member_1: number`
+
+  - `learning_rate_multiplier: optional "auto" or number`
+
+    Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+    - `union_member_0: "auto"`
+
+    - `union_member_1: number`
+
+  - `n_epochs: optional "auto" or number`
+
+    The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+    - `union_member_0: "auto"`
+
+    - `union_member_1: number`
+
+  - `reasoning_effort: optional "default" or "low" or "medium" or "high"`
+
+    Level of reasoning effort.
+
+    - `"default"`
+
+    - `"low"`
+
+    - `"medium"`
+
+    - `"high"`
+
+### Reinforcement Method
+
+- `reinforcement_method: object { grader, hyperparameters }`
+
+  Configuration for the reinforcement fine-tuning method.
+
+  - `grader: StringCheckGrader or TextSimilarityGrader or PythonGrader or 2 more`
+
+    The grader used for the fine-tuning job.
+
+    - `string_check_grader: object { input, name, operation, 2 more }`
+
+      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" or "ne" or "like" or "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`.
+
+    - `text_similarity_grader: object { evaluation_metric, input, name, 2 more }`
+
+      A TextSimilarityGrader object which grades text based on similarity metrics.
+
+      - `evaluation_metric: "cosine" or "fuzzy_match" or "bleu" or 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.
+
+    - `python_grader: object { name, source, type, image_tag }`
+
+      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`.
+
+      - `image_tag: optional string`
+
+        The image tag to use for the python script.
+
+    - `score_model_grader: object { input, model, name, 3 more }`
+
+      A ScoreModelGrader object that uses a model to assign a score to the input.
+
+      - `input: array of object { 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 or ResponseInputText or object { text, type }  or 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.
+
+          - `Text input: string`
+
+            A text input to the model.
+
+          - `response_input_text: object { text, type }`
+
+            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`.
+
+          - `Output text: object { text, type }`
+
+            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`.
+
+          - `Input image: object { image_url, type, detail }`
+
+            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`.
+
+            - `detail: optional string`
+
+              The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+          - `response_input_audio: object { input_audio, type }`
+
+            An audio input to the model.
+
+            - `input_audio: object { data, format }`
+
+              - `data: string`
+
+                Base64-encoded audio data.
+
+              - `format: "mp3" or "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`.
+
+          - `grader_inputs: array of string or ResponseInputText or object { text, type }  or 2 more`
+
+            A list of inputs, each of which may be either an input text, output text, input
+            image, or input audio object.
+
+            - `Text input: string`
+
+              A text input to the model.
+
+            - `response_input_text: object { text, type }`
+
+              A text input to the model.
+
+            - `Output text: object { text, type }`
+
+              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`.
+
+            - `Input image: object { image_url, type, detail }`
+
+              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`.
+
+              - `detail: optional string`
+
+                The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+            - `response_input_audio: object { input_audio, type }`
+
+              An audio input to the model.
+
+        - `role: "user" or "assistant" or "system" or "developer"`
+
+          The role of the message input. One of `user`, `assistant`, `system`, or
+          `developer`.
+
+          - `"user"`
+
+          - `"assistant"`
+
+          - `"system"`
+
+          - `"developer"`
+
+        - `type: optional "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`.
+
+      - `range: optional array of number`
+
+        The range of the score. Defaults to `[0, 1]`.
+
+      - `sampling_params: optional object { max_completions_tokens, reasoning_effort, seed, 2 more }`
+
+        The sampling parameters for the model.
+
+        - `max_completions_tokens: optional number`
+
+          The maximum number of tokens the grader model may generate in its response.
+
+        - `reasoning_effort: optional "none" or "minimal" or "low" or 3 more`
+
+          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: optional number`
+
+          A seed value to initialize the randomness, during sampling.
+
+        - `temperature: optional number`
+
+          A higher temperature increases randomness in the outputs.
+
+        - `top_p: optional number`
+
+          An alternative to temperature for nucleus sampling; 1.0 includes all tokens.
+
+    - `multi_grader: object { calculate_output, graders, name, type }`
+
+      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 or TextSimilarityGrader or PythonGrader or 2 more`
+
+        A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+        - `string_check_grader: object { input, name, operation, 2 more }`
+
+          A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+        - `text_similarity_grader: object { evaluation_metric, input, name, 2 more }`
+
+          A TextSimilarityGrader object which grades text based on similarity metrics.
+
+        - `python_grader: object { name, source, type, image_tag }`
+
+          A PythonGrader object that runs a python script on the input.
+
+        - `score_model_grader: object { input, model, name, 3 more }`
+
+          A ScoreModelGrader object that uses a model to assign a score to the input.
+
+        - `label_model_grader: object { input, labels, model, 3 more }`
+
+          A LabelModelGrader object which uses a model to assign labels to each item
+          in the evaluation.
+
+          - `input: array of object { content, role, type }`
+
+            - `content: string or ResponseInputText or object { text, type }  or 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.
+
+              - `Text input: string`
+
+                A text input to the model.
+
+              - `response_input_text: object { text, type }`
+
+                A text input to the model.
+
+              - `Output text: object { text, type }`
+
+                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`.
+
+              - `Input image: object { image_url, type, detail }`
+
+                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`.
+
+                - `detail: optional string`
+
+                  The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+              - `response_input_audio: object { input_audio, type }`
+
+                An audio input to the model.
+
+              - `grader_inputs: array of string or ResponseInputText or object { text, type }  or 2 more`
+
+                A list of inputs, each of which may be either an input text, output text, input
+                image, or input audio object.
+
+            - `role: "user" or "assistant" or "system" or "developer"`
+
+              The role of the message input. One of `user`, `assistant`, `system`, or
+              `developer`.
+
+              - `"user"`
+
+              - `"assistant"`
+
+              - `"system"`
+
+              - `"developer"`
+
+            - `type: optional "message"`
+
+              The type of the message input. Always `message`.
+
+              - `"message"`
+
+          - `labels: array of 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 of 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`.
+
+      - `name: string`
+
+        The name of the grader.
+
+      - `type: "multi"`
+
+        The object type, which is always `multi`.
+
+  - `hyperparameters: optional object { batch_size, compute_multiplier, eval_interval, 4 more }`
+
+    The hyperparameters used for the reinforcement fine-tuning job.
+
+    - `batch_size: optional "auto" or number`
+
+      Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+      - `union_member_0: "auto"`
+
+      - `union_member_1: number`
+
+    - `compute_multiplier: optional "auto" or number`
+
+      Multiplier on amount of compute used for exploring search space during training.
+
+      - `union_member_0: "auto"`
+
+      - `union_member_1: number`
+
+    - `eval_interval: optional "auto" or number`
+
+      The number of training steps between evaluation runs.
+
+      - `union_member_0: "auto"`
+
+      - `union_member_1: number`
+
+    - `eval_samples: optional "auto" or number`
+
+      Number of evaluation samples to generate per training step.
+
+      - `union_member_0: "auto"`
+
+      - `union_member_1: number`
+
+    - `learning_rate_multiplier: optional "auto" or number`
+
+      Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+      - `union_member_0: "auto"`
+
+      - `union_member_1: number`
+
+    - `n_epochs: optional "auto" or number`
+
+      The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+      - `union_member_0: "auto"`
+
+      - `union_member_1: number`
+
+    - `reasoning_effort: optional "default" or "low" or "medium" or "high"`
+
+      Level of reasoning effort.
+
+      - `"default"`
+
+      - `"low"`
+
+      - `"medium"`
+
+      - `"high"`
+
+### Supervised Hyperparameters
+
+- `supervised_hyperparameters: object { batch_size, learning_rate_multiplier, n_epochs }`
+
+  The hyperparameters used for the fine-tuning job.
+
+  - `batch_size: optional "auto" or number`
+
+    Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+    - `union_member_0: "auto"`
+
+    - `union_member_1: number`
+
+  - `learning_rate_multiplier: optional "auto" or number`
+
+    Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+    - `union_member_0: "auto"`
+
+    - `union_member_1: number`
+
+  - `n_epochs: optional "auto" or number`
+
+    The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+    - `union_member_0: "auto"`
+
+    - `union_member_1: number`
+
+### Supervised Method
+
+- `supervised_method: object { hyperparameters }`
+
+  Configuration for the supervised fine-tuning method.
+
+  - `hyperparameters: optional object { batch_size, learning_rate_multiplier, n_epochs }`
+
+    The hyperparameters used for the fine-tuning job.
+
+    - `batch_size: optional "auto" or number`
+
+      Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+      - `union_member_0: "auto"`
+
+      - `union_member_1: number`
+
+    - `learning_rate_multiplier: optional "auto" or number`
+
+      Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+      - `union_member_0: "auto"`
+
+      - `union_member_1: number`
+
+    - `n_epochs: optional "auto" or number`
+
+      The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+      - `union_member_0: "auto"`
+
+      - `union_member_1: number`
+
+# Jobs
+
+## Create fine-tuning job
+
+`$ openai fine-tuning:jobs create`
+
+**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 or "babbage-002" or "davinci-002" or "gpt-3.5-turbo" or "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).
+
+- `--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: optional object { 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.
+
+- `--integration: optional array of object { type, wandb }`
+
+  A list of integrations to enable for your fine-tuning job.
+
+- `--metadata: optional map[string]`
+
+  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: optional object { type, dpo, reinforcement, supervised }`
+
+  The method used for fine-tuning.
+
+- `--seed: optional number`
+
+  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: optional 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: optional 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
+
+- `fine_tuning_job: object { id, created_at, error, 16 more }`
+
+  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: number`
+
+    The Unix timestamp (in seconds) for when the fine-tuning job was created.
+
+  - `error: object { 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: number`
+
+    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: object { 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: optional "auto" or number`
+
+      Number of examples in each batch. A larger batch size means that model parameters
+      are updated less frequently, but with lower variance.
+
+      - `union_member_0: "auto"`
+
+      - `union_member_1: number`
+
+    - `learning_rate_multiplier: optional "auto" or number`
+
+      Scaling factor for the learning rate. A smaller learning rate may be useful to avoid
+      overfitting.
+
+      - `Auto: "auto"`
+
+      - `union_member_1: number`
+
+    - `n_epochs: optional "auto" or number`
+
+      The number of epochs to train the model for. An epoch refers to one full cycle
+      through the training dataset.
+
+      - `Auto: "auto"`
+
+      - `union_member_1: number`
+
+  - `model: string`
+
+    The base model that is being fine-tuned.
+
+  - `object: "fine_tuning.job"`
+
+    The object type, which is always "fine_tuning.job".
+
+  - `organization_id: string`
+
+    The organization that owns the fine-tuning job.
+
+  - `result_files: array of 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: number`
+
+    The seed used for the fine-tuning job.
+
+  - `status: "validating_files" or "queued" or "running" or 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: number`
+
+    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: optional number`
+
+    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: optional array of 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: object { 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: optional 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: optional string`
+
+        A display name to set for the run. If not set, we will use the Job ID as the name.
+
+      - `tags: optional array of 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: optional map[string]`
+
+    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: optional object { type, dpo, reinforcement, supervised }`
+
+    The method used for fine-tuning.
+
+    - `type: "supervised" or "dpo" or "reinforcement"`
+
+      The type of method. Is either `supervised`, `dpo`, or `reinforcement`.
+
+      - `"supervised"`
+
+      - `"dpo"`
+
+      - `"reinforcement"`
+
+    - `dpo: optional object { hyperparameters }`
+
+      Configuration for the DPO fine-tuning method.
+
+      - `hyperparameters: optional object { batch_size, beta, learning_rate_multiplier, n_epochs }`
+
+        The hyperparameters used for the DPO fine-tuning job.
+
+        - `batch_size: optional "auto" or number`
+
+          Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `beta: optional "auto" or number`
+
+          The beta value for the DPO method. A higher beta value will increase the weight of the penalty between the policy and reference model.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `learning_rate_multiplier: optional "auto" or number`
+
+          Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `n_epochs: optional "auto" or number`
+
+          The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+    - `reinforcement: optional object { grader, hyperparameters }`
+
+      Configuration for the reinforcement fine-tuning method.
+
+      - `grader: StringCheckGrader or TextSimilarityGrader or PythonGrader or 2 more`
+
+        The grader used for the fine-tuning job.
+
+        - `string_check_grader: object { input, name, operation, 2 more }`
+
+          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" or "ne" or "like" or "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`.
+
+        - `text_similarity_grader: object { evaluation_metric, input, name, 2 more }`
+
+          A TextSimilarityGrader object which grades text based on similarity metrics.
+
+          - `evaluation_metric: "cosine" or "fuzzy_match" or "bleu" or 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.
+
+        - `python_grader: object { name, source, type, image_tag }`
+
+          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`.
+
+          - `image_tag: optional string`
+
+            The image tag to use for the python script.
+
+        - `score_model_grader: object { input, model, name, 3 more }`
+
+          A ScoreModelGrader object that uses a model to assign a score to the input.
+
+          - `input: array of object { 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 or ResponseInputText or object { text, type }  or 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.
+
+              - `Text input: string`
+
+                A text input to the model.
+
+              - `response_input_text: object { text, type }`
+
+                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`.
+
+              - `Output text: object { text, type }`
+
+                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`.
+
+              - `Input image: object { image_url, type, detail }`
+
+                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`.
+
+                - `detail: optional string`
+
+                  The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+              - `response_input_audio: object { input_audio, type }`
+
+                An audio input to the model.
+
+                - `input_audio: object { data, format }`
+
+                  - `data: string`
+
+                    Base64-encoded audio data.
+
+                  - `format: "mp3" or "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`.
+
+              - `grader_inputs: array of string or ResponseInputText or object { text, type }  or 2 more`
+
+                A list of inputs, each of which may be either an input text, output text, input
+                image, or input audio object.
+
+                - `Text input: string`
+
+                  A text input to the model.
+
+                - `response_input_text: object { text, type }`
+
+                  A text input to the model.
+
+                - `Output text: object { text, type }`
+
+                  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`.
+
+                - `Input image: object { image_url, type, detail }`
+
+                  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`.
+
+                  - `detail: optional string`
+
+                    The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+                - `response_input_audio: object { input_audio, type }`
+
+                  An audio input to the model.
+
+            - `role: "user" or "assistant" or "system" or "developer"`
+
+              The role of the message input. One of `user`, `assistant`, `system`, or
+              `developer`.
+
+              - `"user"`
+
+              - `"assistant"`
+
+              - `"system"`
+
+              - `"developer"`
+
+            - `type: optional "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`.
+
+          - `range: optional array of number`
+
+            The range of the score. Defaults to `[0, 1]`.
+
+          - `sampling_params: optional object { max_completions_tokens, reasoning_effort, seed, 2 more }`
+
+            The sampling parameters for the model.
+
+            - `max_completions_tokens: optional number`
+
+              The maximum number of tokens the grader model may generate in its response.
+
+            - `reasoning_effort: optional "none" or "minimal" or "low" or 3 more`
+
+              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: optional number`
+
+              A seed value to initialize the randomness, during sampling.
+
+            - `temperature: optional number`
+
+              A higher temperature increases randomness in the outputs.
+
+            - `top_p: optional number`
+
+              An alternative to temperature for nucleus sampling; 1.0 includes all tokens.
+
+        - `multi_grader: object { calculate_output, graders, name, type }`
+
+          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 or TextSimilarityGrader or PythonGrader or 2 more`
+
+            A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+            - `string_check_grader: object { input, name, operation, 2 more }`
+
+              A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+            - `text_similarity_grader: object { evaluation_metric, input, name, 2 more }`
+
+              A TextSimilarityGrader object which grades text based on similarity metrics.
+
+            - `python_grader: object { name, source, type, image_tag }`
+
+              A PythonGrader object that runs a python script on the input.
+
+            - `score_model_grader: object { input, model, name, 3 more }`
+
+              A ScoreModelGrader object that uses a model to assign a score to the input.
+
+            - `label_model_grader: object { input, labels, model, 3 more }`
+
+              A LabelModelGrader object which uses a model to assign labels to each item
+              in the evaluation.
+
+              - `input: array of object { content, role, type }`
+
+                - `content: string or ResponseInputText or object { text, type }  or 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.
+
+                  - `Text input: string`
+
+                    A text input to the model.
+
+                  - `response_input_text: object { text, type }`
+
+                    A text input to the model.
+
+                  - `Output text: object { text, type }`
+
+                    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`.
+
+                  - `Input image: object { image_url, type, detail }`
+
+                    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`.
+
+                    - `detail: optional string`
+
+                      The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+                  - `response_input_audio: object { input_audio, type }`
+
+                    An audio input to the model.
+
+                  - `grader_inputs: array of string or ResponseInputText or object { text, type }  or 2 more`
+
+                    A list of inputs, each of which may be either an input text, output text, input
+                    image, or input audio object.
+
+                - `role: "user" or "assistant" or "system" or "developer"`
+
+                  The role of the message input. One of `user`, `assistant`, `system`, or
+                  `developer`.
+
+                  - `"user"`
+
+                  - `"assistant"`
+
+                  - `"system"`
+
+                  - `"developer"`
+
+                - `type: optional "message"`
+
+                  The type of the message input. Always `message`.
+
+                  - `"message"`
+
+              - `labels: array of 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 of 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`.
+
+          - `name: string`
+
+            The name of the grader.
+
+          - `type: "multi"`
+
+            The object type, which is always `multi`.
+
+      - `hyperparameters: optional object { batch_size, compute_multiplier, eval_interval, 4 more }`
+
+        The hyperparameters used for the reinforcement fine-tuning job.
+
+        - `batch_size: optional "auto" or number`
+
+          Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `compute_multiplier: optional "auto" or number`
+
+          Multiplier on amount of compute used for exploring search space during training.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `eval_interval: optional "auto" or number`
+
+          The number of training steps between evaluation runs.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `eval_samples: optional "auto" or number`
+
+          Number of evaluation samples to generate per training step.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `learning_rate_multiplier: optional "auto" or number`
+
+          Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `n_epochs: optional "auto" or number`
+
+          The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `reasoning_effort: optional "default" or "low" or "medium" or "high"`
+
+          Level of reasoning effort.
+
+          - `"default"`
+
+          - `"low"`
+
+          - `"medium"`
+
+          - `"high"`
+
+    - `supervised: optional object { hyperparameters }`
+
+      Configuration for the supervised fine-tuning method.
+
+      - `hyperparameters: optional object { batch_size, learning_rate_multiplier, n_epochs }`
+
+        The hyperparameters used for the fine-tuning job.
+
+        - `batch_size: optional "auto" or number`
+
+          Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `learning_rate_multiplier: optional "auto" or number`
+
+          Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `n_epochs: optional "auto" or number`
+
+          The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+### Example
+
+```cli
+openai fine-tuning:jobs create \
+  --api-key 'My API Key' \
+  --model gpt-4o-mini \
+  --training-file file-abc123
+```
+
+#### 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
+
+`$ openai fine-tuning:jobs list`
+
+**get** `/fine_tuning/jobs`
+
+List your organization's fine-tuning jobs
+
+### Parameters
+
+- `--after: optional string`
+
+  Identifier for the last job from the previous pagination request.
+
+- `--limit: optional number`
+
+  Number of fine-tuning jobs to retrieve.
+
+- `--metadata: optional map[string]`
+
+  Optional metadata filter. To filter, use the syntax `metadata[k]=v`. Alternatively, set `metadata=null` to indicate no metadata.
+
+### Returns
+
+- `ListPaginatedFineTuningJobsResponse: object { data, has_more, object }`
+
+  - `data: array of FineTuningJob`
+
+    - `id: string`
+
+      The object identifier, which can be referenced in the API endpoints.
+
+    - `created_at: number`
+
+      The Unix timestamp (in seconds) for when the fine-tuning job was created.
+
+    - `error: object { 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: number`
+
+      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: object { 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: optional "auto" or number`
+
+        Number of examples in each batch. A larger batch size means that model parameters
+        are updated less frequently, but with lower variance.
+
+        - `union_member_0: "auto"`
+
+        - `union_member_1: number`
+
+      - `learning_rate_multiplier: optional "auto" or number`
+
+        Scaling factor for the learning rate. A smaller learning rate may be useful to avoid
+        overfitting.
+
+        - `Auto: "auto"`
+
+        - `union_member_1: number`
+
+      - `n_epochs: optional "auto" or number`
+
+        The number of epochs to train the model for. An epoch refers to one full cycle
+        through the training dataset.
+
+        - `Auto: "auto"`
+
+        - `union_member_1: number`
+
+    - `model: string`
+
+      The base model that is being fine-tuned.
+
+    - `object: "fine_tuning.job"`
+
+      The object type, which is always "fine_tuning.job".
+
+    - `organization_id: string`
+
+      The organization that owns the fine-tuning job.
+
+    - `result_files: array of 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: number`
+
+      The seed used for the fine-tuning job.
+
+    - `status: "validating_files" or "queued" or "running" or 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: number`
+
+      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: optional number`
+
+      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: optional array of 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: object { 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: optional 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: optional string`
+
+          A display name to set for the run. If not set, we will use the Job ID as the name.
+
+        - `tags: optional array of 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: optional map[string]`
+
+      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: optional object { type, dpo, reinforcement, supervised }`
+
+      The method used for fine-tuning.
+
+      - `type: "supervised" or "dpo" or "reinforcement"`
+
+        The type of method. Is either `supervised`, `dpo`, or `reinforcement`.
+
+        - `"supervised"`
+
+        - `"dpo"`
+
+        - `"reinforcement"`
+
+      - `dpo: optional object { hyperparameters }`
+
+        Configuration for the DPO fine-tuning method.
+
+        - `hyperparameters: optional object { batch_size, beta, learning_rate_multiplier, n_epochs }`
+
+          The hyperparameters used for the DPO fine-tuning job.
+
+          - `batch_size: optional "auto" or number`
+
+            Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+            - `union_member_0: "auto"`
+
+            - `union_member_1: number`
+
+          - `beta: optional "auto" or number`
+
+            The beta value for the DPO method. A higher beta value will increase the weight of the penalty between the policy and reference model.
+
+            - `union_member_0: "auto"`
+
+            - `union_member_1: number`
+
+          - `learning_rate_multiplier: optional "auto" or number`
+
+            Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+            - `union_member_0: "auto"`
+
+            - `union_member_1: number`
+
+          - `n_epochs: optional "auto" or number`
+
+            The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+            - `union_member_0: "auto"`
+
+            - `union_member_1: number`
+
+      - `reinforcement: optional object { grader, hyperparameters }`
+
+        Configuration for the reinforcement fine-tuning method.
+
+        - `grader: StringCheckGrader or TextSimilarityGrader or PythonGrader or 2 more`
+
+          The grader used for the fine-tuning job.
+
+          - `string_check_grader: object { input, name, operation, 2 more }`
+
+            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" or "ne" or "like" or "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`.
+
+          - `text_similarity_grader: object { evaluation_metric, input, name, 2 more }`
+
+            A TextSimilarityGrader object which grades text based on similarity metrics.
+
+            - `evaluation_metric: "cosine" or "fuzzy_match" or "bleu" or 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.
+
+          - `python_grader: object { name, source, type, image_tag }`
+
+            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`.
+
+            - `image_tag: optional string`
+
+              The image tag to use for the python script.
+
+          - `score_model_grader: object { input, model, name, 3 more }`
+
+            A ScoreModelGrader object that uses a model to assign a score to the input.
+
+            - `input: array of object { 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 or ResponseInputText or object { text, type }  or 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.
+
+                - `Text input: string`
+
+                  A text input to the model.
+
+                - `response_input_text: object { text, type }`
+
+                  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`.
+
+                - `Output text: object { text, type }`
+
+                  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`.
+
+                - `Input image: object { image_url, type, detail }`
+
+                  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`.
+
+                  - `detail: optional string`
+
+                    The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+                - `response_input_audio: object { input_audio, type }`
+
+                  An audio input to the model.
+
+                  - `input_audio: object { data, format }`
+
+                    - `data: string`
+
+                      Base64-encoded audio data.
+
+                    - `format: "mp3" or "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`.
+
+                - `grader_inputs: array of string or ResponseInputText or object { text, type }  or 2 more`
+
+                  A list of inputs, each of which may be either an input text, output text, input
+                  image, or input audio object.
+
+                  - `Text input: string`
+
+                    A text input to the model.
+
+                  - `response_input_text: object { text, type }`
+
+                    A text input to the model.
+
+                  - `Output text: object { text, type }`
+
+                    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`.
+
+                  - `Input image: object { image_url, type, detail }`
+
+                    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`.
+
+                    - `detail: optional string`
+
+                      The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+                  - `response_input_audio: object { input_audio, type }`
+
+                    An audio input to the model.
+
+              - `role: "user" or "assistant" or "system" or "developer"`
+
+                The role of the message input. One of `user`, `assistant`, `system`, or
+                `developer`.
+
+                - `"user"`
+
+                - `"assistant"`
+
+                - `"system"`
+
+                - `"developer"`
+
+              - `type: optional "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`.
+
+            - `range: optional array of number`
+
+              The range of the score. Defaults to `[0, 1]`.
+
+            - `sampling_params: optional object { max_completions_tokens, reasoning_effort, seed, 2 more }`
+
+              The sampling parameters for the model.
+
+              - `max_completions_tokens: optional number`
+
+                The maximum number of tokens the grader model may generate in its response.
+
+              - `reasoning_effort: optional "none" or "minimal" or "low" or 3 more`
+
+                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: optional number`
+
+                A seed value to initialize the randomness, during sampling.
+
+              - `temperature: optional number`
+
+                A higher temperature increases randomness in the outputs.
+
+              - `top_p: optional number`
+
+                An alternative to temperature for nucleus sampling; 1.0 includes all tokens.
+
+          - `multi_grader: object { calculate_output, graders, name, type }`
+
+            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 or TextSimilarityGrader or PythonGrader or 2 more`
+
+              A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+              - `string_check_grader: object { input, name, operation, 2 more }`
+
+                A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+              - `text_similarity_grader: object { evaluation_metric, input, name, 2 more }`
+
+                A TextSimilarityGrader object which grades text based on similarity metrics.
+
+              - `python_grader: object { name, source, type, image_tag }`
+
+                A PythonGrader object that runs a python script on the input.
+
+              - `score_model_grader: object { input, model, name, 3 more }`
+
+                A ScoreModelGrader object that uses a model to assign a score to the input.
+
+              - `label_model_grader: object { input, labels, model, 3 more }`
+
+                A LabelModelGrader object which uses a model to assign labels to each item
+                in the evaluation.
+
+                - `input: array of object { content, role, type }`
+
+                  - `content: string or ResponseInputText or object { text, type }  or 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.
+
+                    - `Text input: string`
+
+                      A text input to the model.
+
+                    - `response_input_text: object { text, type }`
+
+                      A text input to the model.
+
+                    - `Output text: object { text, type }`
+
+                      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`.
+
+                    - `Input image: object { image_url, type, detail }`
+
+                      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`.
+
+                      - `detail: optional string`
+
+                        The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+                    - `response_input_audio: object { input_audio, type }`
+
+                      An audio input to the model.
+
+                    - `grader_inputs: array of string or ResponseInputText or object { text, type }  or 2 more`
+
+                      A list of inputs, each of which may be either an input text, output text, input
+                      image, or input audio object.
+
+                  - `role: "user" or "assistant" or "system" or "developer"`
+
+                    The role of the message input. One of `user`, `assistant`, `system`, or
+                    `developer`.
+
+                    - `"user"`
+
+                    - `"assistant"`
+
+                    - `"system"`
+
+                    - `"developer"`
+
+                  - `type: optional "message"`
+
+                    The type of the message input. Always `message`.
+
+                    - `"message"`
+
+                - `labels: array of 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 of 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`.
+
+            - `name: string`
+
+              The name of the grader.
+
+            - `type: "multi"`
+
+              The object type, which is always `multi`.
+
+        - `hyperparameters: optional object { batch_size, compute_multiplier, eval_interval, 4 more }`
+
+          The hyperparameters used for the reinforcement fine-tuning job.
+
+          - `batch_size: optional "auto" or number`
+
+            Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+            - `union_member_0: "auto"`
+
+            - `union_member_1: number`
+
+          - `compute_multiplier: optional "auto" or number`
+
+            Multiplier on amount of compute used for exploring search space during training.
+
+            - `union_member_0: "auto"`
+
+            - `union_member_1: number`
+
+          - `eval_interval: optional "auto" or number`
+
+            The number of training steps between evaluation runs.
+
+            - `union_member_0: "auto"`
+
+            - `union_member_1: number`
+
+          - `eval_samples: optional "auto" or number`
+
+            Number of evaluation samples to generate per training step.
+
+            - `union_member_0: "auto"`
+
+            - `union_member_1: number`
+
+          - `learning_rate_multiplier: optional "auto" or number`
+
+            Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+            - `union_member_0: "auto"`
+
+            - `union_member_1: number`
+
+          - `n_epochs: optional "auto" or number`
+
+            The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+            - `union_member_0: "auto"`
+
+            - `union_member_1: number`
+
+          - `reasoning_effort: optional "default" or "low" or "medium" or "high"`
+
+            Level of reasoning effort.
+
+            - `"default"`
+
+            - `"low"`
+
+            - `"medium"`
+
+            - `"high"`
+
+      - `supervised: optional object { hyperparameters }`
+
+        Configuration for the supervised fine-tuning method.
+
+        - `hyperparameters: optional object { batch_size, learning_rate_multiplier, n_epochs }`
+
+          The hyperparameters used for the fine-tuning job.
+
+          - `batch_size: optional "auto" or number`
+
+            Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+            - `union_member_0: "auto"`
+
+            - `union_member_1: number`
+
+          - `learning_rate_multiplier: optional "auto" or number`
+
+            Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+            - `union_member_0: "auto"`
+
+            - `union_member_1: number`
+
+          - `n_epochs: optional "auto" or number`
+
+            The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+            - `union_member_0: "auto"`
+
+            - `union_member_1: number`
+
+  - `has_more: boolean`
+
+  - `object: "list"`
+
+### Example
+
+```cli
+openai fine-tuning:jobs list \
+  --api-key 'My API Key'
+```
+
+#### 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
+
+`$ openai fine-tuning:jobs retrieve`
+
+**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`
+
+  The ID of the fine-tuning job.
+
+### Returns
+
+- `fine_tuning_job: object { id, created_at, error, 16 more }`
+
+  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: number`
+
+    The Unix timestamp (in seconds) for when the fine-tuning job was created.
+
+  - `error: object { 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: number`
+
+    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: object { 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: optional "auto" or number`
+
+      Number of examples in each batch. A larger batch size means that model parameters
+      are updated less frequently, but with lower variance.
+
+      - `union_member_0: "auto"`
+
+      - `union_member_1: number`
+
+    - `learning_rate_multiplier: optional "auto" or number`
+
+      Scaling factor for the learning rate. A smaller learning rate may be useful to avoid
+      overfitting.
+
+      - `Auto: "auto"`
+
+      - `union_member_1: number`
+
+    - `n_epochs: optional "auto" or number`
+
+      The number of epochs to train the model for. An epoch refers to one full cycle
+      through the training dataset.
+
+      - `Auto: "auto"`
+
+      - `union_member_1: number`
+
+  - `model: string`
+
+    The base model that is being fine-tuned.
+
+  - `object: "fine_tuning.job"`
+
+    The object type, which is always "fine_tuning.job".
+
+  - `organization_id: string`
+
+    The organization that owns the fine-tuning job.
+
+  - `result_files: array of 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: number`
+
+    The seed used for the fine-tuning job.
+
+  - `status: "validating_files" or "queued" or "running" or 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: number`
+
+    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: optional number`
+
+    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: optional array of 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: object { 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: optional 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: optional string`
+
+        A display name to set for the run. If not set, we will use the Job ID as the name.
+
+      - `tags: optional array of 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: optional map[string]`
+
+    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: optional object { type, dpo, reinforcement, supervised }`
+
+    The method used for fine-tuning.
+
+    - `type: "supervised" or "dpo" or "reinforcement"`
+
+      The type of method. Is either `supervised`, `dpo`, or `reinforcement`.
+
+      - `"supervised"`
+
+      - `"dpo"`
+
+      - `"reinforcement"`
+
+    - `dpo: optional object { hyperparameters }`
+
+      Configuration for the DPO fine-tuning method.
+
+      - `hyperparameters: optional object { batch_size, beta, learning_rate_multiplier, n_epochs }`
+
+        The hyperparameters used for the DPO fine-tuning job.
+
+        - `batch_size: optional "auto" or number`
+
+          Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `beta: optional "auto" or number`
+
+          The beta value for the DPO method. A higher beta value will increase the weight of the penalty between the policy and reference model.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `learning_rate_multiplier: optional "auto" or number`
+
+          Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `n_epochs: optional "auto" or number`
+
+          The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+    - `reinforcement: optional object { grader, hyperparameters }`
+
+      Configuration for the reinforcement fine-tuning method.
+
+      - `grader: StringCheckGrader or TextSimilarityGrader or PythonGrader or 2 more`
+
+        The grader used for the fine-tuning job.
+
+        - `string_check_grader: object { input, name, operation, 2 more }`
+
+          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" or "ne" or "like" or "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`.
+
+        - `text_similarity_grader: object { evaluation_metric, input, name, 2 more }`
+
+          A TextSimilarityGrader object which grades text based on similarity metrics.
+
+          - `evaluation_metric: "cosine" or "fuzzy_match" or "bleu" or 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.
+
+        - `python_grader: object { name, source, type, image_tag }`
+
+          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`.
+
+          - `image_tag: optional string`
+
+            The image tag to use for the python script.
+
+        - `score_model_grader: object { input, model, name, 3 more }`
+
+          A ScoreModelGrader object that uses a model to assign a score to the input.
+
+          - `input: array of object { 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 or ResponseInputText or object { text, type }  or 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.
+
+              - `Text input: string`
+
+                A text input to the model.
+
+              - `response_input_text: object { text, type }`
+
+                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`.
+
+              - `Output text: object { text, type }`
+
+                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`.
+
+              - `Input image: object { image_url, type, detail }`
+
+                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`.
+
+                - `detail: optional string`
+
+                  The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+              - `response_input_audio: object { input_audio, type }`
+
+                An audio input to the model.
+
+                - `input_audio: object { data, format }`
+
+                  - `data: string`
+
+                    Base64-encoded audio data.
+
+                  - `format: "mp3" or "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`.
+
+              - `grader_inputs: array of string or ResponseInputText or object { text, type }  or 2 more`
+
+                A list of inputs, each of which may be either an input text, output text, input
+                image, or input audio object.
+
+                - `Text input: string`
+
+                  A text input to the model.
+
+                - `response_input_text: object { text, type }`
+
+                  A text input to the model.
+
+                - `Output text: object { text, type }`
+
+                  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`.
+
+                - `Input image: object { image_url, type, detail }`
+
+                  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`.
+
+                  - `detail: optional string`
+
+                    The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+                - `response_input_audio: object { input_audio, type }`
+
+                  An audio input to the model.
+
+            - `role: "user" or "assistant" or "system" or "developer"`
+
+              The role of the message input. One of `user`, `assistant`, `system`, or
+              `developer`.
+
+              - `"user"`
+
+              - `"assistant"`
+
+              - `"system"`
+
+              - `"developer"`
+
+            - `type: optional "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`.
+
+          - `range: optional array of number`
+
+            The range of the score. Defaults to `[0, 1]`.
+
+          - `sampling_params: optional object { max_completions_tokens, reasoning_effort, seed, 2 more }`
+
+            The sampling parameters for the model.
+
+            - `max_completions_tokens: optional number`
+
+              The maximum number of tokens the grader model may generate in its response.
+
+            - `reasoning_effort: optional "none" or "minimal" or "low" or 3 more`
+
+              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: optional number`
+
+              A seed value to initialize the randomness, during sampling.
+
+            - `temperature: optional number`
+
+              A higher temperature increases randomness in the outputs.
+
+            - `top_p: optional number`
+
+              An alternative to temperature for nucleus sampling; 1.0 includes all tokens.
+
+        - `multi_grader: object { calculate_output, graders, name, type }`
+
+          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 or TextSimilarityGrader or PythonGrader or 2 more`
+
+            A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+            - `string_check_grader: object { input, name, operation, 2 more }`
+
+              A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+            - `text_similarity_grader: object { evaluation_metric, input, name, 2 more }`
+
+              A TextSimilarityGrader object which grades text based on similarity metrics.
+
+            - `python_grader: object { name, source, type, image_tag }`
+
+              A PythonGrader object that runs a python script on the input.
+
+            - `score_model_grader: object { input, model, name, 3 more }`
+
+              A ScoreModelGrader object that uses a model to assign a score to the input.
+
+            - `label_model_grader: object { input, labels, model, 3 more }`
+
+              A LabelModelGrader object which uses a model to assign labels to each item
+              in the evaluation.
+
+              - `input: array of object { content, role, type }`
+
+                - `content: string or ResponseInputText or object { text, type }  or 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.
+
+                  - `Text input: string`
+
+                    A text input to the model.
+
+                  - `response_input_text: object { text, type }`
+
+                    A text input to the model.
+
+                  - `Output text: object { text, type }`
+
+                    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`.
+
+                  - `Input image: object { image_url, type, detail }`
+
+                    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`.
+
+                    - `detail: optional string`
+
+                      The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+                  - `response_input_audio: object { input_audio, type }`
+
+                    An audio input to the model.
+
+                  - `grader_inputs: array of string or ResponseInputText or object { text, type }  or 2 more`
+
+                    A list of inputs, each of which may be either an input text, output text, input
+                    image, or input audio object.
+
+                - `role: "user" or "assistant" or "system" or "developer"`
+
+                  The role of the message input. One of `user`, `assistant`, `system`, or
+                  `developer`.
+
+                  - `"user"`
+
+                  - `"assistant"`
+
+                  - `"system"`
+
+                  - `"developer"`
+
+                - `type: optional "message"`
+
+                  The type of the message input. Always `message`.
+
+                  - `"message"`
+
+              - `labels: array of 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 of 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`.
+
+          - `name: string`
+
+            The name of the grader.
+
+          - `type: "multi"`
+
+            The object type, which is always `multi`.
+
+      - `hyperparameters: optional object { batch_size, compute_multiplier, eval_interval, 4 more }`
+
+        The hyperparameters used for the reinforcement fine-tuning job.
+
+        - `batch_size: optional "auto" or number`
+
+          Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `compute_multiplier: optional "auto" or number`
+
+          Multiplier on amount of compute used for exploring search space during training.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `eval_interval: optional "auto" or number`
+
+          The number of training steps between evaluation runs.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `eval_samples: optional "auto" or number`
+
+          Number of evaluation samples to generate per training step.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `learning_rate_multiplier: optional "auto" or number`
+
+          Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `n_epochs: optional "auto" or number`
+
+          The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `reasoning_effort: optional "default" or "low" or "medium" or "high"`
+
+          Level of reasoning effort.
+
+          - `"default"`
+
+          - `"low"`
+
+          - `"medium"`
+
+          - `"high"`
+
+    - `supervised: optional object { hyperparameters }`
+
+      Configuration for the supervised fine-tuning method.
+
+      - `hyperparameters: optional object { batch_size, learning_rate_multiplier, n_epochs }`
+
+        The hyperparameters used for the fine-tuning job.
+
+        - `batch_size: optional "auto" or number`
+
+          Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `learning_rate_multiplier: optional "auto" or number`
+
+          Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `n_epochs: optional "auto" or number`
+
+          The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+### Example
+
+```cli
+openai fine-tuning:jobs retrieve \
+  --api-key 'My API Key' \
+  --fine-tuning-job-id ft-AF1WoRqd3aJAHsqc9NY7iL8F
+```
+
+#### 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
+
+`$ openai fine-tuning:jobs list-events`
+
+**get** `/fine_tuning/jobs/{fine_tuning_job_id}/events`
+
+Get status updates for a fine-tuning job.
+
+### Parameters
+
+- `--fine-tuning-job-id: string`
+
+  The ID of the fine-tuning job to get events for.
+
+- `--after: optional string`
+
+  Identifier for the last event from the previous pagination request.
+
+- `--limit: optional number`
+
+  Number of events to retrieve.
+
+### Returns
+
+- `ListFineTuningJobEventsResponse: object { data, has_more, object }`
+
+  - `data: array of FineTuningJobEvent`
+
+    - `id: string`
+
+      The object identifier.
+
+    - `created_at: number`
+
+      The Unix timestamp (in seconds) for when the fine-tuning job was created.
+
+    - `level: "info" or "warn" or "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".
+
+    - `data: optional unknown`
+
+      The data associated with the event.
+
+    - `type: optional "message" or "metrics"`
+
+      The type of event.
+
+      - `"message"`
+
+      - `"metrics"`
+
+  - `has_more: boolean`
+
+  - `object: "list"`
+
+### Example
+
+```cli
+openai fine-tuning:jobs list-events \
+  --api-key 'My API Key' \
+  --fine-tuning-job-id ft-AF1WoRqd3aJAHsqc9NY7iL8F
+```
+
+#### 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
+
+`$ openai fine-tuning:jobs cancel`
+
+**post** `/fine_tuning/jobs/{fine_tuning_job_id}/cancel`
+
+Immediately cancel a fine-tune job.
+
+### Parameters
+
+- `--fine-tuning-job-id: string`
+
+  The ID of the fine-tuning job to cancel.
+
+### Returns
+
+- `fine_tuning_job: object { id, created_at, error, 16 more }`
+
+  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: number`
+
+    The Unix timestamp (in seconds) for when the fine-tuning job was created.
+
+  - `error: object { 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: number`
+
+    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: object { 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: optional "auto" or number`
+
+      Number of examples in each batch. A larger batch size means that model parameters
+      are updated less frequently, but with lower variance.
+
+      - `union_member_0: "auto"`
+
+      - `union_member_1: number`
+
+    - `learning_rate_multiplier: optional "auto" or number`
+
+      Scaling factor for the learning rate. A smaller learning rate may be useful to avoid
+      overfitting.
+
+      - `Auto: "auto"`
+
+      - `union_member_1: number`
+
+    - `n_epochs: optional "auto" or number`
+
+      The number of epochs to train the model for. An epoch refers to one full cycle
+      through the training dataset.
+
+      - `Auto: "auto"`
+
+      - `union_member_1: number`
+
+  - `model: string`
+
+    The base model that is being fine-tuned.
+
+  - `object: "fine_tuning.job"`
+
+    The object type, which is always "fine_tuning.job".
+
+  - `organization_id: string`
+
+    The organization that owns the fine-tuning job.
+
+  - `result_files: array of 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: number`
+
+    The seed used for the fine-tuning job.
+
+  - `status: "validating_files" or "queued" or "running" or 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: number`
+
+    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: optional number`
+
+    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: optional array of 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: object { 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: optional 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: optional string`
+
+        A display name to set for the run. If not set, we will use the Job ID as the name.
+
+      - `tags: optional array of 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: optional map[string]`
+
+    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: optional object { type, dpo, reinforcement, supervised }`
+
+    The method used for fine-tuning.
+
+    - `type: "supervised" or "dpo" or "reinforcement"`
+
+      The type of method. Is either `supervised`, `dpo`, or `reinforcement`.
+
+      - `"supervised"`
+
+      - `"dpo"`
+
+      - `"reinforcement"`
+
+    - `dpo: optional object { hyperparameters }`
+
+      Configuration for the DPO fine-tuning method.
+
+      - `hyperparameters: optional object { batch_size, beta, learning_rate_multiplier, n_epochs }`
+
+        The hyperparameters used for the DPO fine-tuning job.
+
+        - `batch_size: optional "auto" or number`
+
+          Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `beta: optional "auto" or number`
+
+          The beta value for the DPO method. A higher beta value will increase the weight of the penalty between the policy and reference model.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `learning_rate_multiplier: optional "auto" or number`
+
+          Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `n_epochs: optional "auto" or number`
+
+          The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+    - `reinforcement: optional object { grader, hyperparameters }`
+
+      Configuration for the reinforcement fine-tuning method.
+
+      - `grader: StringCheckGrader or TextSimilarityGrader or PythonGrader or 2 more`
+
+        The grader used for the fine-tuning job.
+
+        - `string_check_grader: object { input, name, operation, 2 more }`
+
+          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" or "ne" or "like" or "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`.
+
+        - `text_similarity_grader: object { evaluation_metric, input, name, 2 more }`
+
+          A TextSimilarityGrader object which grades text based on similarity metrics.
+
+          - `evaluation_metric: "cosine" or "fuzzy_match" or "bleu" or 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.
+
+        - `python_grader: object { name, source, type, image_tag }`
+
+          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`.
+
+          - `image_tag: optional string`
+
+            The image tag to use for the python script.
+
+        - `score_model_grader: object { input, model, name, 3 more }`
+
+          A ScoreModelGrader object that uses a model to assign a score to the input.
+
+          - `input: array of object { 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 or ResponseInputText or object { text, type }  or 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.
+
+              - `Text input: string`
+
+                A text input to the model.
+
+              - `response_input_text: object { text, type }`
+
+                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`.
+
+              - `Output text: object { text, type }`
+
+                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`.
+
+              - `Input image: object { image_url, type, detail }`
+
+                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`.
+
+                - `detail: optional string`
+
+                  The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+              - `response_input_audio: object { input_audio, type }`
+
+                An audio input to the model.
+
+                - `input_audio: object { data, format }`
+
+                  - `data: string`
+
+                    Base64-encoded audio data.
+
+                  - `format: "mp3" or "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`.
+
+              - `grader_inputs: array of string or ResponseInputText or object { text, type }  or 2 more`
+
+                A list of inputs, each of which may be either an input text, output text, input
+                image, or input audio object.
+
+                - `Text input: string`
+
+                  A text input to the model.
+
+                - `response_input_text: object { text, type }`
+
+                  A text input to the model.
+
+                - `Output text: object { text, type }`
+
+                  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`.
+
+                - `Input image: object { image_url, type, detail }`
+
+                  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`.
+
+                  - `detail: optional string`
+
+                    The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+                - `response_input_audio: object { input_audio, type }`
+
+                  An audio input to the model.
+
+            - `role: "user" or "assistant" or "system" or "developer"`
+
+              The role of the message input. One of `user`, `assistant`, `system`, or
+              `developer`.
+
+              - `"user"`
+
+              - `"assistant"`
+
+              - `"system"`
+
+              - `"developer"`
+
+            - `type: optional "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`.
+
+          - `range: optional array of number`
+
+            The range of the score. Defaults to `[0, 1]`.
+
+          - `sampling_params: optional object { max_completions_tokens, reasoning_effort, seed, 2 more }`
+
+            The sampling parameters for the model.
+
+            - `max_completions_tokens: optional number`
+
+              The maximum number of tokens the grader model may generate in its response.
+
+            - `reasoning_effort: optional "none" or "minimal" or "low" or 3 more`
+
+              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: optional number`
+
+              A seed value to initialize the randomness, during sampling.
+
+            - `temperature: optional number`
+
+              A higher temperature increases randomness in the outputs.
+
+            - `top_p: optional number`
+
+              An alternative to temperature for nucleus sampling; 1.0 includes all tokens.
+
+        - `multi_grader: object { calculate_output, graders, name, type }`
+
+          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 or TextSimilarityGrader or PythonGrader or 2 more`
+
+            A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+            - `string_check_grader: object { input, name, operation, 2 more }`
+
+              A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+            - `text_similarity_grader: object { evaluation_metric, input, name, 2 more }`
+
+              A TextSimilarityGrader object which grades text based on similarity metrics.
+
+            - `python_grader: object { name, source, type, image_tag }`
+
+              A PythonGrader object that runs a python script on the input.
+
+            - `score_model_grader: object { input, model, name, 3 more }`
+
+              A ScoreModelGrader object that uses a model to assign a score to the input.
+
+            - `label_model_grader: object { input, labels, model, 3 more }`
+
+              A LabelModelGrader object which uses a model to assign labels to each item
+              in the evaluation.
+
+              - `input: array of object { content, role, type }`
+
+                - `content: string or ResponseInputText or object { text, type }  or 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.
+
+                  - `Text input: string`
+
+                    A text input to the model.
+
+                  - `response_input_text: object { text, type }`
+
+                    A text input to the model.
+
+                  - `Output text: object { text, type }`
+
+                    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`.
+
+                  - `Input image: object { image_url, type, detail }`
+
+                    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`.
+
+                    - `detail: optional string`
+
+                      The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+                  - `response_input_audio: object { input_audio, type }`
+
+                    An audio input to the model.
+
+                  - `grader_inputs: array of string or ResponseInputText or object { text, type }  or 2 more`
+
+                    A list of inputs, each of which may be either an input text, output text, input
+                    image, or input audio object.
+
+                - `role: "user" or "assistant" or "system" or "developer"`
+
+                  The role of the message input. One of `user`, `assistant`, `system`, or
+                  `developer`.
+
+                  - `"user"`
+
+                  - `"assistant"`
+
+                  - `"system"`
+
+                  - `"developer"`
+
+                - `type: optional "message"`
+
+                  The type of the message input. Always `message`.
+
+                  - `"message"`
+
+              - `labels: array of 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 of 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`.
+
+          - `name: string`
+
+            The name of the grader.
+
+          - `type: "multi"`
+
+            The object type, which is always `multi`.
+
+      - `hyperparameters: optional object { batch_size, compute_multiplier, eval_interval, 4 more }`
+
+        The hyperparameters used for the reinforcement fine-tuning job.
+
+        - `batch_size: optional "auto" or number`
+
+          Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `compute_multiplier: optional "auto" or number`
+
+          Multiplier on amount of compute used for exploring search space during training.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `eval_interval: optional "auto" or number`
+
+          The number of training steps between evaluation runs.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `eval_samples: optional "auto" or number`
+
+          Number of evaluation samples to generate per training step.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `learning_rate_multiplier: optional "auto" or number`
+
+          Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `n_epochs: optional "auto" or number`
+
+          The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `reasoning_effort: optional "default" or "low" or "medium" or "high"`
+
+          Level of reasoning effort.
+
+          - `"default"`
+
+          - `"low"`
+
+          - `"medium"`
+
+          - `"high"`
+
+    - `supervised: optional object { hyperparameters }`
+
+      Configuration for the supervised fine-tuning method.
+
+      - `hyperparameters: optional object { batch_size, learning_rate_multiplier, n_epochs }`
+
+        The hyperparameters used for the fine-tuning job.
+
+        - `batch_size: optional "auto" or number`
+
+          Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `learning_rate_multiplier: optional "auto" or number`
+
+          Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `n_epochs: optional "auto" or number`
+
+          The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+### Example
+
+```cli
+openai fine-tuning:jobs cancel \
+  --api-key 'My API Key' \
+  --fine-tuning-job-id ft-AF1WoRqd3aJAHsqc9NY7iL8F
+```
+
+#### 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
+
+`$ openai fine-tuning:jobs pause`
+
+**post** `/fine_tuning/jobs/{fine_tuning_job_id}/pause`
+
+Pause a fine-tune job.
+
+### Parameters
+
+- `--fine-tuning-job-id: string`
+
+  The ID of the fine-tuning job to pause.
+
+### Returns
+
+- `fine_tuning_job: object { id, created_at, error, 16 more }`
+
+  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: number`
+
+    The Unix timestamp (in seconds) for when the fine-tuning job was created.
+
+  - `error: object { 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: number`
+
+    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: object { 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: optional "auto" or number`
+
+      Number of examples in each batch. A larger batch size means that model parameters
+      are updated less frequently, but with lower variance.
+
+      - `union_member_0: "auto"`
+
+      - `union_member_1: number`
+
+    - `learning_rate_multiplier: optional "auto" or number`
+
+      Scaling factor for the learning rate. A smaller learning rate may be useful to avoid
+      overfitting.
+
+      - `Auto: "auto"`
+
+      - `union_member_1: number`
+
+    - `n_epochs: optional "auto" or number`
+
+      The number of epochs to train the model for. An epoch refers to one full cycle
+      through the training dataset.
+
+      - `Auto: "auto"`
+
+      - `union_member_1: number`
+
+  - `model: string`
+
+    The base model that is being fine-tuned.
+
+  - `object: "fine_tuning.job"`
+
+    The object type, which is always "fine_tuning.job".
+
+  - `organization_id: string`
+
+    The organization that owns the fine-tuning job.
+
+  - `result_files: array of 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: number`
+
+    The seed used for the fine-tuning job.
+
+  - `status: "validating_files" or "queued" or "running" or 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: number`
+
+    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: optional number`
+
+    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: optional array of 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: object { 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: optional 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: optional string`
+
+        A display name to set for the run. If not set, we will use the Job ID as the name.
+
+      - `tags: optional array of 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: optional map[string]`
+
+    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: optional object { type, dpo, reinforcement, supervised }`
+
+    The method used for fine-tuning.
+
+    - `type: "supervised" or "dpo" or "reinforcement"`
+
+      The type of method. Is either `supervised`, `dpo`, or `reinforcement`.
+
+      - `"supervised"`
+
+      - `"dpo"`
+
+      - `"reinforcement"`
+
+    - `dpo: optional object { hyperparameters }`
+
+      Configuration for the DPO fine-tuning method.
+
+      - `hyperparameters: optional object { batch_size, beta, learning_rate_multiplier, n_epochs }`
+
+        The hyperparameters used for the DPO fine-tuning job.
+
+        - `batch_size: optional "auto" or number`
+
+          Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `beta: optional "auto" or number`
+
+          The beta value for the DPO method. A higher beta value will increase the weight of the penalty between the policy and reference model.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `learning_rate_multiplier: optional "auto" or number`
+
+          Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `n_epochs: optional "auto" or number`
+
+          The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+    - `reinforcement: optional object { grader, hyperparameters }`
+
+      Configuration for the reinforcement fine-tuning method.
+
+      - `grader: StringCheckGrader or TextSimilarityGrader or PythonGrader or 2 more`
+
+        The grader used for the fine-tuning job.
+
+        - `string_check_grader: object { input, name, operation, 2 more }`
+
+          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" or "ne" or "like" or "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`.
+
+        - `text_similarity_grader: object { evaluation_metric, input, name, 2 more }`
+
+          A TextSimilarityGrader object which grades text based on similarity metrics.
+
+          - `evaluation_metric: "cosine" or "fuzzy_match" or "bleu" or 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.
+
+        - `python_grader: object { name, source, type, image_tag }`
+
+          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`.
+
+          - `image_tag: optional string`
+
+            The image tag to use for the python script.
+
+        - `score_model_grader: object { input, model, name, 3 more }`
+
+          A ScoreModelGrader object that uses a model to assign a score to the input.
+
+          - `input: array of object { 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 or ResponseInputText or object { text, type }  or 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.
+
+              - `Text input: string`
+
+                A text input to the model.
+
+              - `response_input_text: object { text, type }`
+
+                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`.
+
+              - `Output text: object { text, type }`
+
+                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`.
+
+              - `Input image: object { image_url, type, detail }`
+
+                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`.
+
+                - `detail: optional string`
+
+                  The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+              - `response_input_audio: object { input_audio, type }`
+
+                An audio input to the model.
+
+                - `input_audio: object { data, format }`
+
+                  - `data: string`
+
+                    Base64-encoded audio data.
+
+                  - `format: "mp3" or "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`.
+
+              - `grader_inputs: array of string or ResponseInputText or object { text, type }  or 2 more`
+
+                A list of inputs, each of which may be either an input text, output text, input
+                image, or input audio object.
+
+                - `Text input: string`
+
+                  A text input to the model.
+
+                - `response_input_text: object { text, type }`
+
+                  A text input to the model.
+
+                - `Output text: object { text, type }`
+
+                  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`.
+
+                - `Input image: object { image_url, type, detail }`
+
+                  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`.
+
+                  - `detail: optional string`
+
+                    The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+                - `response_input_audio: object { input_audio, type }`
+
+                  An audio input to the model.
+
+            - `role: "user" or "assistant" or "system" or "developer"`
+
+              The role of the message input. One of `user`, `assistant`, `system`, or
+              `developer`.
+
+              - `"user"`
+
+              - `"assistant"`
+
+              - `"system"`
+
+              - `"developer"`
+
+            - `type: optional "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`.
+
+          - `range: optional array of number`
+
+            The range of the score. Defaults to `[0, 1]`.
+
+          - `sampling_params: optional object { max_completions_tokens, reasoning_effort, seed, 2 more }`
+
+            The sampling parameters for the model.
+
+            - `max_completions_tokens: optional number`
+
+              The maximum number of tokens the grader model may generate in its response.
+
+            - `reasoning_effort: optional "none" or "minimal" or "low" or 3 more`
+
+              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: optional number`
+
+              A seed value to initialize the randomness, during sampling.
+
+            - `temperature: optional number`
+
+              A higher temperature increases randomness in the outputs.
+
+            - `top_p: optional number`
+
+              An alternative to temperature for nucleus sampling; 1.0 includes all tokens.
+
+        - `multi_grader: object { calculate_output, graders, name, type }`
+
+          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 or TextSimilarityGrader or PythonGrader or 2 more`
+
+            A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+            - `string_check_grader: object { input, name, operation, 2 more }`
+
+              A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+            - `text_similarity_grader: object { evaluation_metric, input, name, 2 more }`
+
+              A TextSimilarityGrader object which grades text based on similarity metrics.
+
+            - `python_grader: object { name, source, type, image_tag }`
+
+              A PythonGrader object that runs a python script on the input.
+
+            - `score_model_grader: object { input, model, name, 3 more }`
+
+              A ScoreModelGrader object that uses a model to assign a score to the input.
+
+            - `label_model_grader: object { input, labels, model, 3 more }`
+
+              A LabelModelGrader object which uses a model to assign labels to each item
+              in the evaluation.
+
+              - `input: array of object { content, role, type }`
+
+                - `content: string or ResponseInputText or object { text, type }  or 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.
+
+                  - `Text input: string`
+
+                    A text input to the model.
+
+                  - `response_input_text: object { text, type }`
+
+                    A text input to the model.
+
+                  - `Output text: object { text, type }`
+
+                    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`.
+
+                  - `Input image: object { image_url, type, detail }`
+
+                    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`.
+
+                    - `detail: optional string`
+
+                      The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+                  - `response_input_audio: object { input_audio, type }`
+
+                    An audio input to the model.
+
+                  - `grader_inputs: array of string or ResponseInputText or object { text, type }  or 2 more`
+
+                    A list of inputs, each of which may be either an input text, output text, input
+                    image, or input audio object.
+
+                - `role: "user" or "assistant" or "system" or "developer"`
+
+                  The role of the message input. One of `user`, `assistant`, `system`, or
+                  `developer`.
+
+                  - `"user"`
+
+                  - `"assistant"`
+
+                  - `"system"`
+
+                  - `"developer"`
+
+                - `type: optional "message"`
+
+                  The type of the message input. Always `message`.
+
+                  - `"message"`
+
+              - `labels: array of 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 of 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`.
+
+          - `name: string`
+
+            The name of the grader.
+
+          - `type: "multi"`
+
+            The object type, which is always `multi`.
+
+      - `hyperparameters: optional object { batch_size, compute_multiplier, eval_interval, 4 more }`
+
+        The hyperparameters used for the reinforcement fine-tuning job.
+
+        - `batch_size: optional "auto" or number`
+
+          Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `compute_multiplier: optional "auto" or number`
+
+          Multiplier on amount of compute used for exploring search space during training.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `eval_interval: optional "auto" or number`
+
+          The number of training steps between evaluation runs.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `eval_samples: optional "auto" or number`
+
+          Number of evaluation samples to generate per training step.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `learning_rate_multiplier: optional "auto" or number`
+
+          Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `n_epochs: optional "auto" or number`
+
+          The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `reasoning_effort: optional "default" or "low" or "medium" or "high"`
+
+          Level of reasoning effort.
+
+          - `"default"`
+
+          - `"low"`
+
+          - `"medium"`
+
+          - `"high"`
+
+    - `supervised: optional object { hyperparameters }`
+
+      Configuration for the supervised fine-tuning method.
+
+      - `hyperparameters: optional object { batch_size, learning_rate_multiplier, n_epochs }`
+
+        The hyperparameters used for the fine-tuning job.
+
+        - `batch_size: optional "auto" or number`
+
+          Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `learning_rate_multiplier: optional "auto" or number`
+
+          Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `n_epochs: optional "auto" or number`
+
+          The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+### Example
+
+```cli
+openai fine-tuning:jobs pause \
+  --api-key 'My API Key' \
+  --fine-tuning-job-id ft-AF1WoRqd3aJAHsqc9NY7iL8F
+```
+
+#### 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
+
+`$ openai fine-tuning:jobs resume`
+
+**post** `/fine_tuning/jobs/{fine_tuning_job_id}/resume`
+
+Resume a fine-tune job.
+
+### Parameters
+
+- `--fine-tuning-job-id: string`
+
+  The ID of the fine-tuning job to resume.
+
+### Returns
+
+- `fine_tuning_job: object { id, created_at, error, 16 more }`
+
+  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: number`
+
+    The Unix timestamp (in seconds) for when the fine-tuning job was created.
+
+  - `error: object { 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: number`
+
+    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: object { 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: optional "auto" or number`
+
+      Number of examples in each batch. A larger batch size means that model parameters
+      are updated less frequently, but with lower variance.
+
+      - `union_member_0: "auto"`
+
+      - `union_member_1: number`
+
+    - `learning_rate_multiplier: optional "auto" or number`
+
+      Scaling factor for the learning rate. A smaller learning rate may be useful to avoid
+      overfitting.
+
+      - `Auto: "auto"`
+
+      - `union_member_1: number`
+
+    - `n_epochs: optional "auto" or number`
+
+      The number of epochs to train the model for. An epoch refers to one full cycle
+      through the training dataset.
+
+      - `Auto: "auto"`
+
+      - `union_member_1: number`
+
+  - `model: string`
+
+    The base model that is being fine-tuned.
+
+  - `object: "fine_tuning.job"`
+
+    The object type, which is always "fine_tuning.job".
+
+  - `organization_id: string`
+
+    The organization that owns the fine-tuning job.
+
+  - `result_files: array of 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: number`
+
+    The seed used for the fine-tuning job.
+
+  - `status: "validating_files" or "queued" or "running" or 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: number`
+
+    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: optional number`
+
+    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: optional array of 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: object { 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: optional 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: optional string`
+
+        A display name to set for the run. If not set, we will use the Job ID as the name.
+
+      - `tags: optional array of 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: optional map[string]`
+
+    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: optional object { type, dpo, reinforcement, supervised }`
+
+    The method used for fine-tuning.
+
+    - `type: "supervised" or "dpo" or "reinforcement"`
+
+      The type of method. Is either `supervised`, `dpo`, or `reinforcement`.
+
+      - `"supervised"`
+
+      - `"dpo"`
+
+      - `"reinforcement"`
+
+    - `dpo: optional object { hyperparameters }`
+
+      Configuration for the DPO fine-tuning method.
+
+      - `hyperparameters: optional object { batch_size, beta, learning_rate_multiplier, n_epochs }`
+
+        The hyperparameters used for the DPO fine-tuning job.
+
+        - `batch_size: optional "auto" or number`
+
+          Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `beta: optional "auto" or number`
+
+          The beta value for the DPO method. A higher beta value will increase the weight of the penalty between the policy and reference model.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `learning_rate_multiplier: optional "auto" or number`
+
+          Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `n_epochs: optional "auto" or number`
+
+          The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+    - `reinforcement: optional object { grader, hyperparameters }`
+
+      Configuration for the reinforcement fine-tuning method.
+
+      - `grader: StringCheckGrader or TextSimilarityGrader or PythonGrader or 2 more`
+
+        The grader used for the fine-tuning job.
+
+        - `string_check_grader: object { input, name, operation, 2 more }`
+
+          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" or "ne" or "like" or "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`.
+
+        - `text_similarity_grader: object { evaluation_metric, input, name, 2 more }`
+
+          A TextSimilarityGrader object which grades text based on similarity metrics.
+
+          - `evaluation_metric: "cosine" or "fuzzy_match" or "bleu" or 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.
+
+        - `python_grader: object { name, source, type, image_tag }`
+
+          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`.
+
+          - `image_tag: optional string`
+
+            The image tag to use for the python script.
+
+        - `score_model_grader: object { input, model, name, 3 more }`
+
+          A ScoreModelGrader object that uses a model to assign a score to the input.
+
+          - `input: array of object { 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 or ResponseInputText or object { text, type }  or 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.
+
+              - `Text input: string`
+
+                A text input to the model.
+
+              - `response_input_text: object { text, type }`
+
+                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`.
+
+              - `Output text: object { text, type }`
+
+                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`.
+
+              - `Input image: object { image_url, type, detail }`
+
+                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`.
+
+                - `detail: optional string`
+
+                  The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+              - `response_input_audio: object { input_audio, type }`
+
+                An audio input to the model.
+
+                - `input_audio: object { data, format }`
+
+                  - `data: string`
+
+                    Base64-encoded audio data.
+
+                  - `format: "mp3" or "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`.
+
+              - `grader_inputs: array of string or ResponseInputText or object { text, type }  or 2 more`
+
+                A list of inputs, each of which may be either an input text, output text, input
+                image, or input audio object.
+
+                - `Text input: string`
+
+                  A text input to the model.
+
+                - `response_input_text: object { text, type }`
+
+                  A text input to the model.
+
+                - `Output text: object { text, type }`
+
+                  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`.
+
+                - `Input image: object { image_url, type, detail }`
+
+                  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`.
+
+                  - `detail: optional string`
+
+                    The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+                - `response_input_audio: object { input_audio, type }`
+
+                  An audio input to the model.
+
+            - `role: "user" or "assistant" or "system" or "developer"`
+
+              The role of the message input. One of `user`, `assistant`, `system`, or
+              `developer`.
+
+              - `"user"`
+
+              - `"assistant"`
+
+              - `"system"`
+
+              - `"developer"`
+
+            - `type: optional "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`.
+
+          - `range: optional array of number`
+
+            The range of the score. Defaults to `[0, 1]`.
+
+          - `sampling_params: optional object { max_completions_tokens, reasoning_effort, seed, 2 more }`
+
+            The sampling parameters for the model.
+
+            - `max_completions_tokens: optional number`
+
+              The maximum number of tokens the grader model may generate in its response.
+
+            - `reasoning_effort: optional "none" or "minimal" or "low" or 3 more`
+
+              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: optional number`
+
+              A seed value to initialize the randomness, during sampling.
+
+            - `temperature: optional number`
+
+              A higher temperature increases randomness in the outputs.
+
+            - `top_p: optional number`
+
+              An alternative to temperature for nucleus sampling; 1.0 includes all tokens.
+
+        - `multi_grader: object { calculate_output, graders, name, type }`
+
+          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 or TextSimilarityGrader or PythonGrader or 2 more`
+
+            A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+            - `string_check_grader: object { input, name, operation, 2 more }`
+
+              A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+            - `text_similarity_grader: object { evaluation_metric, input, name, 2 more }`
+
+              A TextSimilarityGrader object which grades text based on similarity metrics.
+
+            - `python_grader: object { name, source, type, image_tag }`
+
+              A PythonGrader object that runs a python script on the input.
+
+            - `score_model_grader: object { input, model, name, 3 more }`
+
+              A ScoreModelGrader object that uses a model to assign a score to the input.
+
+            - `label_model_grader: object { input, labels, model, 3 more }`
+
+              A LabelModelGrader object which uses a model to assign labels to each item
+              in the evaluation.
+
+              - `input: array of object { content, role, type }`
+
+                - `content: string or ResponseInputText or object { text, type }  or 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.
+
+                  - `Text input: string`
+
+                    A text input to the model.
+
+                  - `response_input_text: object { text, type }`
+
+                    A text input to the model.
+
+                  - `Output text: object { text, type }`
+
+                    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`.
+
+                  - `Input image: object { image_url, type, detail }`
+
+                    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`.
+
+                    - `detail: optional string`
+
+                      The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+                  - `response_input_audio: object { input_audio, type }`
+
+                    An audio input to the model.
+
+                  - `grader_inputs: array of string or ResponseInputText or object { text, type }  or 2 more`
+
+                    A list of inputs, each of which may be either an input text, output text, input
+                    image, or input audio object.
+
+                - `role: "user" or "assistant" or "system" or "developer"`
+
+                  The role of the message input. One of `user`, `assistant`, `system`, or
+                  `developer`.
+
+                  - `"user"`
+
+                  - `"assistant"`
+
+                  - `"system"`
+
+                  - `"developer"`
+
+                - `type: optional "message"`
+
+                  The type of the message input. Always `message`.
+
+                  - `"message"`
+
+              - `labels: array of 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 of 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`.
+
+          - `name: string`
+
+            The name of the grader.
+
+          - `type: "multi"`
+
+            The object type, which is always `multi`.
+
+      - `hyperparameters: optional object { batch_size, compute_multiplier, eval_interval, 4 more }`
+
+        The hyperparameters used for the reinforcement fine-tuning job.
+
+        - `batch_size: optional "auto" or number`
+
+          Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `compute_multiplier: optional "auto" or number`
+
+          Multiplier on amount of compute used for exploring search space during training.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `eval_interval: optional "auto" or number`
+
+          The number of training steps between evaluation runs.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `eval_samples: optional "auto" or number`
+
+          Number of evaluation samples to generate per training step.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `learning_rate_multiplier: optional "auto" or number`
+
+          Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `n_epochs: optional "auto" or number`
+
+          The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `reasoning_effort: optional "default" or "low" or "medium" or "high"`
+
+          Level of reasoning effort.
+
+          - `"default"`
+
+          - `"low"`
+
+          - `"medium"`
+
+          - `"high"`
+
+    - `supervised: optional object { hyperparameters }`
+
+      Configuration for the supervised fine-tuning method.
+
+      - `hyperparameters: optional object { batch_size, learning_rate_multiplier, n_epochs }`
+
+        The hyperparameters used for the fine-tuning job.
+
+        - `batch_size: optional "auto" or number`
+
+          Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `learning_rate_multiplier: optional "auto" or number`
+
+          Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `n_epochs: optional "auto" or number`
+
+          The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+### Example
+
+```cli
+openai fine-tuning:jobs resume \
+  --api-key 'My API Key' \
+  --fine-tuning-job-id ft-AF1WoRqd3aJAHsqc9NY7iL8F
+```
+
+#### 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
+
+- `fine_tuning_job: object { id, created_at, error, 16 more }`
+
+  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: number`
+
+    The Unix timestamp (in seconds) for when the fine-tuning job was created.
+
+  - `error: object { 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: number`
+
+    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: object { 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: optional "auto" or number`
+
+      Number of examples in each batch. A larger batch size means that model parameters
+      are updated less frequently, but with lower variance.
+
+      - `union_member_0: "auto"`
+
+      - `union_member_1: number`
+
+    - `learning_rate_multiplier: optional "auto" or number`
+
+      Scaling factor for the learning rate. A smaller learning rate may be useful to avoid
+      overfitting.
+
+      - `Auto: "auto"`
+
+      - `union_member_1: number`
+
+    - `n_epochs: optional "auto" or number`
+
+      The number of epochs to train the model for. An epoch refers to one full cycle
+      through the training dataset.
+
+      - `Auto: "auto"`
+
+      - `union_member_1: number`
+
+  - `model: string`
+
+    The base model that is being fine-tuned.
+
+  - `object: "fine_tuning.job"`
+
+    The object type, which is always "fine_tuning.job".
+
+  - `organization_id: string`
+
+    The organization that owns the fine-tuning job.
+
+  - `result_files: array of 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: number`
+
+    The seed used for the fine-tuning job.
+
+  - `status: "validating_files" or "queued" or "running" or 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: number`
+
+    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: optional number`
+
+    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: optional array of 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: object { 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: optional 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: optional string`
+
+        A display name to set for the run. If not set, we will use the Job ID as the name.
+
+      - `tags: optional array of 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: optional map[string]`
+
+    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: optional object { type, dpo, reinforcement, supervised }`
+
+    The method used for fine-tuning.
+
+    - `type: "supervised" or "dpo" or "reinforcement"`
+
+      The type of method. Is either `supervised`, `dpo`, or `reinforcement`.
+
+      - `"supervised"`
+
+      - `"dpo"`
+
+      - `"reinforcement"`
+
+    - `dpo: optional object { hyperparameters }`
+
+      Configuration for the DPO fine-tuning method.
+
+      - `hyperparameters: optional object { batch_size, beta, learning_rate_multiplier, n_epochs }`
+
+        The hyperparameters used for the DPO fine-tuning job.
+
+        - `batch_size: optional "auto" or number`
+
+          Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `beta: optional "auto" or number`
+
+          The beta value for the DPO method. A higher beta value will increase the weight of the penalty between the policy and reference model.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `learning_rate_multiplier: optional "auto" or number`
+
+          Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `n_epochs: optional "auto" or number`
+
+          The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+    - `reinforcement: optional object { grader, hyperparameters }`
+
+      Configuration for the reinforcement fine-tuning method.
+
+      - `grader: StringCheckGrader or TextSimilarityGrader or PythonGrader or 2 more`
+
+        The grader used for the fine-tuning job.
+
+        - `string_check_grader: object { input, name, operation, 2 more }`
+
+          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" or "ne" or "like" or "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`.
+
+        - `text_similarity_grader: object { evaluation_metric, input, name, 2 more }`
+
+          A TextSimilarityGrader object which grades text based on similarity metrics.
+
+          - `evaluation_metric: "cosine" or "fuzzy_match" or "bleu" or 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.
+
+        - `python_grader: object { name, source, type, image_tag }`
+
+          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`.
+
+          - `image_tag: optional string`
+
+            The image tag to use for the python script.
+
+        - `score_model_grader: object { input, model, name, 3 more }`
+
+          A ScoreModelGrader object that uses a model to assign a score to the input.
+
+          - `input: array of object { 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 or ResponseInputText or object { text, type }  or 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.
+
+              - `Text input: string`
+
+                A text input to the model.
+
+              - `response_input_text: object { text, type }`
+
+                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`.
+
+              - `Output text: object { text, type }`
+
+                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`.
+
+              - `Input image: object { image_url, type, detail }`
+
+                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`.
+
+                - `detail: optional string`
+
+                  The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+              - `response_input_audio: object { input_audio, type }`
+
+                An audio input to the model.
+
+                - `input_audio: object { data, format }`
+
+                  - `data: string`
+
+                    Base64-encoded audio data.
+
+                  - `format: "mp3" or "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`.
+
+              - `grader_inputs: array of string or ResponseInputText or object { text, type }  or 2 more`
+
+                A list of inputs, each of which may be either an input text, output text, input
+                image, or input audio object.
+
+                - `Text input: string`
+
+                  A text input to the model.
+
+                - `response_input_text: object { text, type }`
+
+                  A text input to the model.
+
+                - `Output text: object { text, type }`
+
+                  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`.
+
+                - `Input image: object { image_url, type, detail }`
+
+                  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`.
+
+                  - `detail: optional string`
+
+                    The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+                - `response_input_audio: object { input_audio, type }`
+
+                  An audio input to the model.
+
+            - `role: "user" or "assistant" or "system" or "developer"`
+
+              The role of the message input. One of `user`, `assistant`, `system`, or
+              `developer`.
+
+              - `"user"`
+
+              - `"assistant"`
+
+              - `"system"`
+
+              - `"developer"`
+
+            - `type: optional "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`.
+
+          - `range: optional array of number`
+
+            The range of the score. Defaults to `[0, 1]`.
+
+          - `sampling_params: optional object { max_completions_tokens, reasoning_effort, seed, 2 more }`
+
+            The sampling parameters for the model.
+
+            - `max_completions_tokens: optional number`
+
+              The maximum number of tokens the grader model may generate in its response.
+
+            - `reasoning_effort: optional "none" or "minimal" or "low" or 3 more`
+
+              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: optional number`
+
+              A seed value to initialize the randomness, during sampling.
+
+            - `temperature: optional number`
+
+              A higher temperature increases randomness in the outputs.
+
+            - `top_p: optional number`
+
+              An alternative to temperature for nucleus sampling; 1.0 includes all tokens.
+
+        - `multi_grader: object { calculate_output, graders, name, type }`
+
+          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 or TextSimilarityGrader or PythonGrader or 2 more`
+
+            A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+            - `string_check_grader: object { input, name, operation, 2 more }`
+
+              A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+            - `text_similarity_grader: object { evaluation_metric, input, name, 2 more }`
+
+              A TextSimilarityGrader object which grades text based on similarity metrics.
+
+            - `python_grader: object { name, source, type, image_tag }`
+
+              A PythonGrader object that runs a python script on the input.
+
+            - `score_model_grader: object { input, model, name, 3 more }`
+
+              A ScoreModelGrader object that uses a model to assign a score to the input.
+
+            - `label_model_grader: object { input, labels, model, 3 more }`
+
+              A LabelModelGrader object which uses a model to assign labels to each item
+              in the evaluation.
+
+              - `input: array of object { content, role, type }`
+
+                - `content: string or ResponseInputText or object { text, type }  or 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.
+
+                  - `Text input: string`
+
+                    A text input to the model.
+
+                  - `response_input_text: object { text, type }`
+
+                    A text input to the model.
+
+                  - `Output text: object { text, type }`
+
+                    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`.
+
+                  - `Input image: object { image_url, type, detail }`
+
+                    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`.
+
+                    - `detail: optional string`
+
+                      The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+                  - `response_input_audio: object { input_audio, type }`
+
+                    An audio input to the model.
+
+                  - `grader_inputs: array of string or ResponseInputText or object { text, type }  or 2 more`
+
+                    A list of inputs, each of which may be either an input text, output text, input
+                    image, or input audio object.
+
+                - `role: "user" or "assistant" or "system" or "developer"`
+
+                  The role of the message input. One of `user`, `assistant`, `system`, or
+                  `developer`.
+
+                  - `"user"`
+
+                  - `"assistant"`
+
+                  - `"system"`
+
+                  - `"developer"`
+
+                - `type: optional "message"`
+
+                  The type of the message input. Always `message`.
+
+                  - `"message"`
+
+              - `labels: array of 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 of 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`.
+
+          - `name: string`
+
+            The name of the grader.
+
+          - `type: "multi"`
+
+            The object type, which is always `multi`.
+
+      - `hyperparameters: optional object { batch_size, compute_multiplier, eval_interval, 4 more }`
+
+        The hyperparameters used for the reinforcement fine-tuning job.
+
+        - `batch_size: optional "auto" or number`
+
+          Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `compute_multiplier: optional "auto" or number`
+
+          Multiplier on amount of compute used for exploring search space during training.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `eval_interval: optional "auto" or number`
+
+          The number of training steps between evaluation runs.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `eval_samples: optional "auto" or number`
+
+          Number of evaluation samples to generate per training step.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `learning_rate_multiplier: optional "auto" or number`
+
+          Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `n_epochs: optional "auto" or number`
+
+          The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `reasoning_effort: optional "default" or "low" or "medium" or "high"`
+
+          Level of reasoning effort.
+
+          - `"default"`
+
+          - `"low"`
+
+          - `"medium"`
+
+          - `"high"`
+
+    - `supervised: optional object { hyperparameters }`
+
+      Configuration for the supervised fine-tuning method.
+
+      - `hyperparameters: optional object { batch_size, learning_rate_multiplier, n_epochs }`
+
+        The hyperparameters used for the fine-tuning job.
+
+        - `batch_size: optional "auto" or number`
+
+          Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `learning_rate_multiplier: optional "auto" or number`
+
+          Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+        - `n_epochs: optional "auto" or number`
+
+          The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+          - `union_member_0: "auto"`
+
+          - `union_member_1: number`
+
+### Fine Tuning Job Event
+
+- `fine_tuning_job_event: object { id, created_at, level, 4 more }`
+
+  Fine-tuning job event object
+
+  - `id: string`
+
+    The object identifier.
+
+  - `created_at: number`
+
+    The Unix timestamp (in seconds) for when the fine-tuning job was created.
+
+  - `level: "info" or "warn" or "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".
+
+  - `data: optional unknown`
+
+    The data associated with the event.
+
+  - `type: optional "message" or "metrics"`
+
+    The type of event.
+
+    - `"message"`
+
+    - `"metrics"`
+
+### Fine Tuning Job Wandb Integration
+
+- `fine_tuning_job_wandb_integration: object { 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: optional 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: optional string`
+
+    A display name to set for the run. If not set, we will use the Job ID as the name.
+
+  - `tags: optional array of 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
+
+- `fine_tuning_job_wandb_integration_object: object { type, wandb }`
+
+  - `type: "wandb"`
+
+    The type of the integration being enabled for the fine-tuning job
+
+  - `wandb: object { 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: optional 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: optional string`
+
+      A display name to set for the run. If not set, we will use the Job ID as the name.
+
+    - `tags: optional array of 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
+
+`$ openai fine-tuning:jobs:checkpoints list`
+
+**get** `/fine_tuning/jobs/{fine_tuning_job_id}/checkpoints`
+
+List checkpoints for a fine-tuning job.
+
+### Parameters
+
+- `--fine-tuning-job-id: string`
+
+  The ID of the fine-tuning job to get checkpoints for.
+
+- `--after: optional string`
+
+  Identifier for the last checkpoint ID from the previous pagination request.
+
+- `--limit: optional number`
+
+  Number of checkpoints to retrieve.
+
+### Returns
+
+- `ListFineTuningJobCheckpointsResponse: object { data, has_more, object, 2 more }`
+
+  - `data: array of FineTuningJobCheckpoint`
+
+    - `id: string`
+
+      The checkpoint identifier, which can be referenced in the API endpoints.
+
+    - `created_at: number`
+
+      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: object { full_valid_loss, full_valid_mean_token_accuracy, step, 4 more }`
+
+      Metrics at the step number during the fine-tuning job.
+
+      - `full_valid_loss: optional number`
+
+      - `full_valid_mean_token_accuracy: optional number`
+
+      - `step: optional number`
+
+      - `train_loss: optional number`
+
+      - `train_mean_token_accuracy: optional number`
+
+      - `valid_loss: optional number`
+
+      - `valid_mean_token_accuracy: optional number`
+
+    - `object: "fine_tuning.job.checkpoint"`
+
+      The object type, which is always "fine_tuning.job.checkpoint".
+
+    - `step_number: number`
+
+      The step number that the checkpoint was created at.
+
+  - `has_more: boolean`
+
+  - `object: "list"`
+
+  - `first_id: optional string`
+
+  - `last_id: optional string`
+
+### Example
+
+```cli
+openai fine-tuning:jobs:checkpoints list \
+  --api-key 'My API Key' \
+  --fine-tuning-job-id ft-AF1WoRqd3aJAHsqc9NY7iL8F
+```
+
+#### 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
+
+- `fine_tuning_job_checkpoint: object { id, created_at, fine_tuned_model_checkpoint, 4 more }`
+
+  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: number`
+
+    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: object { full_valid_loss, full_valid_mean_token_accuracy, step, 4 more }`
+
+    Metrics at the step number during the fine-tuning job.
+
+    - `full_valid_loss: optional number`
+
+    - `full_valid_mean_token_accuracy: optional number`
+
+    - `step: optional number`
+
+    - `train_loss: optional number`
+
+    - `train_mean_token_accuracy: optional number`
+
+    - `valid_loss: optional number`
+
+    - `valid_mean_token_accuracy: optional number`
+
+  - `object: "fine_tuning.job.checkpoint"`
+
+    The object type, which is always "fine_tuning.job.checkpoint".
+
+  - `step_number: number`
+
+    The step number that the checkpoint was created at.
+
+# Checkpoints
+
+# Permissions
+
+## List checkpoint permissions
+
+`$ openai fine-tuning:checkpoints:permissions retrieve`
+
+**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`
+
+  The ID of the fine-tuned model checkpoint to get permissions for.
+
+- `--after: optional string`
+
+  Identifier for the last permission ID from the previous pagination request.
+
+- `--limit: optional number`
+
+  Number of permissions to retrieve.
+
+- `--order: optional "ascending" or "descending"`
+
+  The order in which to retrieve permissions.
+
+- `--project-id: optional string`
+
+  The ID of the project to get permissions for.
+
+### Returns
+
+- `FineTuningCheckpointPermissionGetResponse: object { data, has_more, object, 2 more }`
+
+  - `data: array of object { id, created_at, object, project_id }`
+
+    - `id: string`
+
+      The permission identifier, which can be referenced in the API endpoints.
+
+    - `created_at: number`
+
+      The Unix timestamp (in seconds) for when the permission was created.
+
+    - `object: "checkpoint.permission"`
+
+      The object type, which is always "checkpoint.permission".
+
+    - `project_id: string`
+
+      The project identifier that the permission is for.
+
+  - `has_more: boolean`
+
+  - `object: "list"`
+
+  - `first_id: optional string`
+
+  - `last_id: optional string`
+
+### Example
+
+```cli
+openai fine-tuning:checkpoints:permissions retrieve \
+  --api-key 'My API Key' \
+  --fine-tuned-model-checkpoint ft-AF1WoRqd3aJAHsqc9NY7iL8F
+```
+
+#### 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
+
+`$ openai fine-tuning:checkpoints:permissions list`
+
+**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`
+
+  The ID of the fine-tuned model checkpoint to get permissions for.
+
+- `--after: optional string`
+
+  Identifier for the last permission ID from the previous pagination request.
+
+- `--limit: optional number`
+
+  Number of permissions to retrieve.
+
+- `--order: optional "ascending" or "descending"`
+
+  The order in which to retrieve permissions.
+
+- `--project-id: optional string`
+
+  The ID of the project to get permissions for.
+
+### Returns
+
+- `ListFineTuningCheckpointPermissionResponse: object { data, has_more, object, 2 more }`
+
+  - `data: array of object { id, created_at, object, project_id }`
+
+    - `id: string`
+
+      The permission identifier, which can be referenced in the API endpoints.
+
+    - `created_at: number`
+
+      The Unix timestamp (in seconds) for when the permission was created.
+
+    - `object: "checkpoint.permission"`
+
+      The object type, which is always "checkpoint.permission".
+
+    - `project_id: string`
+
+      The project identifier that the permission is for.
+
+  - `has_more: boolean`
+
+  - `object: "list"`
+
+  - `first_id: optional string`
+
+  - `last_id: optional string`
+
+### Example
+
+```cli
+openai fine-tuning:checkpoints:permissions list \
+  --api-key 'My API Key' \
+  --fine-tuned-model-checkpoint ft-AF1WoRqd3aJAHsqc9NY7iL8F
+```
+
+#### 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
+
+`$ openai fine-tuning:checkpoints:permissions create`
+
+**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`
+
+  The ID of the fine-tuned model checkpoint to create a permission for.
+
+- `--project-id: array of string`
+
+  The project identifiers to grant access to.
+
+### Returns
+
+- `ListFineTuningCheckpointPermissionResponse: object { data, has_more, object, 2 more }`
+
+  - `data: array of object { id, created_at, object, project_id }`
+
+    - `id: string`
+
+      The permission identifier, which can be referenced in the API endpoints.
+
+    - `created_at: number`
+
+      The Unix timestamp (in seconds) for when the permission was created.
+
+    - `object: "checkpoint.permission"`
+
+      The object type, which is always "checkpoint.permission".
+
+    - `project_id: string`
+
+      The project identifier that the permission is for.
+
+  - `has_more: boolean`
+
+  - `object: "list"`
+
+  - `first_id: optional string`
+
+  - `last_id: optional string`
+
+### Example
+
+```cli
+openai fine-tuning:checkpoints:permissions create \
+  --api-key 'My API Key' \
+  --fine-tuned-model-checkpoint ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd \
+  --project-id string
+```
+
+#### 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
+
+`$ openai fine-tuning:checkpoints:permissions delete`
+
+**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`
+
+  The ID of the fine-tuned model checkpoint to delete a permission for.
+
+- `--permission-id: string`
+
+  The ID of the fine-tuned model checkpoint permission to delete.
+
+### Returns
+
+- `FineTuningCheckpointPermissionDeleteResponse: object { id, deleted, object }`
+
+  - `id: string`
+
+    The ID of the fine-tuned model checkpoint permission that was deleted.
+
+  - `deleted: boolean`
+
+    Whether the fine-tuned model checkpoint permission was successfully deleted.
+
+  - `object: "checkpoint.permission"`
+
+    The object type, which is always "checkpoint.permission".
+
+### Example
+
+```cli
+openai fine-tuning:checkpoints:permissions delete \
+  --api-key 'My API Key' \
+  --fine-tuned-model-checkpoint ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd \
+  --permission-id cp_zc4Q7MP6XxulcVzj4MZdwsAB
+```
+
+#### Response
+
+```json
+{
+  "id": "id",
+  "deleted": true,
+  "object": "checkpoint.permission"
+}
+```
+
+# Alpha
+
+# Graders
+
+## Run grader
+
+`$ openai fine-tuning:alpha:graders run`
+
+**post** `/fine_tuning/alpha/graders/run`
+
+Run a grader.
+
+### Parameters
+
+- `--grader: StringCheckGrader or TextSimilarityGrader or PythonGrader or 2 more`
+
+  The grader used for the fine-tuning job.
+
+- `--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: optional unknown`
+
+  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
+
+- `FineTuningAlphaGraderRunResponse: object { metadata, model_grader_token_usage_per_model, reward, sub_rewards }`
+
+  - `metadata: object { errors, execution_time, name, 4 more }`
+
+    - `errors: object { formula_parse_error, invalid_variable_error, model_grader_parse_error, 11 more }`
+
+      - `formula_parse_error: boolean`
+
+      - `invalid_variable_error: boolean`
+
+      - `model_grader_parse_error: boolean`
+
+      - `model_grader_refusal_error: boolean`
+
+      - `model_grader_server_error: boolean`
+
+      - `model_grader_server_error_details: string`
+
+      - `other_error: boolean`
+
+      - `python_grader_runtime_error: boolean`
+
+      - `python_grader_runtime_error_details: string`
+
+      - `python_grader_server_error: boolean`
+
+      - `python_grader_server_error_type: string`
+
+      - `sample_parse_error: boolean`
+
+      - `truncated_observation_error: boolean`
+
+      - `unresponsive_reward_error: boolean`
+
+    - `execution_time: number`
+
+    - `name: string`
+
+    - `sampled_model_name: string`
+
+    - `scores: map[unknown]`
+
+    - `token_usage: number`
+
+    - `type: string`
+
+  - `model_grader_token_usage_per_model: map[unknown]`
+
+  - `reward: number`
+
+  - `sub_rewards: map[unknown]`
+
+### Example
+
+```cli
+openai fine-tuning:alpha:graders run \
+  --api-key 'My API Key' \
+  --grader '{input: input, name: name, operation: eq, reference: reference, type: string_check}' \
+  --model-sample model_sample
+```
+
+#### 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
+
+`$ openai fine-tuning:alpha:graders validate`
+
+**post** `/fine_tuning/alpha/graders/validate`
+
+Validate a grader.
+
+### Parameters
+
+- `--grader: StringCheckGrader or TextSimilarityGrader or PythonGrader or 2 more`
+
+  The grader used for the fine-tuning job.
+
+### Returns
+
+- `FineTuningAlphaGraderValidateResponse: object { grader }`
+
+  - `grader: optional StringCheckGrader or TextSimilarityGrader or PythonGrader or 2 more`
+
+    The grader used for the fine-tuning job.
+
+    - `string_check_grader: object { input, name, operation, 2 more }`
+
+      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" or "ne" or "like" or "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`.
+
+    - `text_similarity_grader: object { evaluation_metric, input, name, 2 more }`
+
+      A TextSimilarityGrader object which grades text based on similarity metrics.
+
+      - `evaluation_metric: "cosine" or "fuzzy_match" or "bleu" or 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.
+
+    - `python_grader: object { name, source, type, image_tag }`
+
+      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`.
+
+      - `image_tag: optional string`
+
+        The image tag to use for the python script.
+
+    - `score_model_grader: object { input, model, name, 3 more }`
+
+      A ScoreModelGrader object that uses a model to assign a score to the input.
+
+      - `input: array of object { 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 or ResponseInputText or object { text, type }  or 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.
+
+          - `Text input: string`
+
+            A text input to the model.
+
+          - `response_input_text: object { text, type }`
+
+            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`.
+
+          - `Output text: object { text, type }`
+
+            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`.
+
+          - `Input image: object { image_url, type, detail }`
+
+            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`.
+
+            - `detail: optional string`
+
+              The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+          - `response_input_audio: object { input_audio, type }`
+
+            An audio input to the model.
+
+            - `input_audio: object { data, format }`
+
+              - `data: string`
+
+                Base64-encoded audio data.
+
+              - `format: "mp3" or "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`.
+
+          - `grader_inputs: array of string or ResponseInputText or object { text, type }  or 2 more`
+
+            A list of inputs, each of which may be either an input text, output text, input
+            image, or input audio object.
+
+            - `Text input: string`
+
+              A text input to the model.
+
+            - `response_input_text: object { text, type }`
+
+              A text input to the model.
+
+            - `Output text: object { text, type }`
+
+              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`.
+
+            - `Input image: object { image_url, type, detail }`
+
+              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`.
+
+              - `detail: optional string`
+
+                The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+            - `response_input_audio: object { input_audio, type }`
+
+              An audio input to the model.
+
+        - `role: "user" or "assistant" or "system" or "developer"`
+
+          The role of the message input. One of `user`, `assistant`, `system`, or
+          `developer`.
+
+          - `"user"`
+
+          - `"assistant"`
+
+          - `"system"`
+
+          - `"developer"`
+
+        - `type: optional "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`.
+
+      - `range: optional array of number`
+
+        The range of the score. Defaults to `[0, 1]`.
+
+      - `sampling_params: optional object { max_completions_tokens, reasoning_effort, seed, 2 more }`
+
+        The sampling parameters for the model.
+
+        - `max_completions_tokens: optional number`
+
+          The maximum number of tokens the grader model may generate in its response.
+
+        - `reasoning_effort: optional "none" or "minimal" or "low" or 3 more`
+
+          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: optional number`
+
+          A seed value to initialize the randomness, during sampling.
+
+        - `temperature: optional number`
+
+          A higher temperature increases randomness in the outputs.
+
+        - `top_p: optional number`
+
+          An alternative to temperature for nucleus sampling; 1.0 includes all tokens.
+
+    - `multi_grader: object { calculate_output, graders, name, type }`
+
+      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 or TextSimilarityGrader or PythonGrader or 2 more`
+
+        A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+        - `string_check_grader: object { input, name, operation, 2 more }`
+
+          A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+        - `text_similarity_grader: object { evaluation_metric, input, name, 2 more }`
+
+          A TextSimilarityGrader object which grades text based on similarity metrics.
+
+        - `python_grader: object { name, source, type, image_tag }`
+
+          A PythonGrader object that runs a python script on the input.
+
+        - `score_model_grader: object { input, model, name, 3 more }`
+
+          A ScoreModelGrader object that uses a model to assign a score to the input.
+
+        - `label_model_grader: object { input, labels, model, 3 more }`
+
+          A LabelModelGrader object which uses a model to assign labels to each item
+          in the evaluation.
+
+          - `input: array of object { content, role, type }`
+
+            - `content: string or ResponseInputText or object { text, type }  or 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.
+
+              - `Text input: string`
+
+                A text input to the model.
+
+              - `response_input_text: object { text, type }`
+
+                A text input to the model.
+
+              - `Output text: object { text, type }`
+
+                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`.
+
+              - `Input image: object { image_url, type, detail }`
+
+                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`.
+
+                - `detail: optional string`
+
+                  The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+              - `response_input_audio: object { input_audio, type }`
+
+                An audio input to the model.
+
+              - `grader_inputs: array of string or ResponseInputText or object { text, type }  or 2 more`
+
+                A list of inputs, each of which may be either an input text, output text, input
+                image, or input audio object.
+
+            - `role: "user" or "assistant" or "system" or "developer"`
+
+              The role of the message input. One of `user`, `assistant`, `system`, or
+              `developer`.
+
+              - `"user"`
+
+              - `"assistant"`
+
+              - `"system"`
+
+              - `"developer"`
+
+            - `type: optional "message"`
+
+              The type of the message input. Always `message`.
+
+              - `"message"`
+
+          - `labels: array of 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 of 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`.
+
+      - `name: string`
+
+        The name of the grader.
+
+      - `type: "multi"`
+
+        The object type, which is always `multi`.
+
+### Example
+
+```cli
+openai fine-tuning:alpha:graders validate \
+  --api-key 'My API Key' \
+  --grader '{input: input, name: name, operation: eq, reference: reference, type: string_check}'
+```
+
+#### Response
+
+```json
+{
+  "grader": {
+    "input": "input",
+    "name": "name",
+    "operation": "eq",
+    "reference": "reference",
+    "type": "string_check"
+  }
+}
+```