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+# Fine Tuning
+
+# Methods
+
+## Domain Types
+
+### Dpo Hyperparameters
+
+- `class DpoHyperparameters:`
+
+  The hyperparameters used for the DPO fine-tuning job.
+
+  - `Optional<BatchSize> batchSize`
+
+    Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+    - `JsonValue;`
+
+      - `AUTO("auto")`
+
+    - `long`
+
+  - `Optional<Beta> beta`
+
+    The beta value for the DPO method. A higher beta value will increase the weight of the penalty between the policy and reference model.
+
+    - `JsonValue;`
+
+      - `AUTO("auto")`
+
+    - `double`
+
+  - `Optional<LearningRateMultiplier> learningRateMultiplier`
+
+    Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+    - `JsonValue;`
+
+      - `AUTO("auto")`
+
+    - `double`
+
+  - `Optional<NEpochs> nEpochs`
+
+    The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+    - `JsonValue;`
+
+      - `AUTO("auto")`
+
+    - `long`
+
+### Dpo Method
+
+- `class DpoMethod:`
+
+  Configuration for the DPO fine-tuning method.
+
+  - `Optional<DpoHyperparameters> hyperparameters`
+
+    The hyperparameters used for the DPO fine-tuning job.
+
+    - `Optional<BatchSize> batchSize`
+
+      Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+      - `JsonValue;`
+
+        - `AUTO("auto")`
+
+      - `long`
+
+    - `Optional<Beta> beta`
+
+      The beta value for the DPO method. A higher beta value will increase the weight of the penalty between the policy and reference model.
+
+      - `JsonValue;`
+
+        - `AUTO("auto")`
+
+      - `double`
+
+    - `Optional<LearningRateMultiplier> learningRateMultiplier`
+
+      Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+      - `JsonValue;`
+
+        - `AUTO("auto")`
+
+      - `double`
+
+    - `Optional<NEpochs> nEpochs`
+
+      The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+      - `JsonValue;`
+
+        - `AUTO("auto")`
+
+      - `long`
+
+### Reinforcement Hyperparameters
+
+- `class ReinforcementHyperparameters:`
+
+  The hyperparameters used for the reinforcement fine-tuning job.
+
+  - `Optional<BatchSize> batchSize`
+
+    Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+    - `JsonValue;`
+
+      - `AUTO("auto")`
+
+    - `long`
+
+  - `Optional<ComputeMultiplier> computeMultiplier`
+
+    Multiplier on amount of compute used for exploring search space during training.
+
+    - `JsonValue;`
+
+      - `AUTO("auto")`
+
+    - `double`
+
+  - `Optional<EvalInterval> evalInterval`
+
+    The number of training steps between evaluation runs.
+
+    - `JsonValue;`
+
+      - `AUTO("auto")`
+
+    - `long`
+
+  - `Optional<EvalSamples> evalSamples`
+
+    Number of evaluation samples to generate per training step.
+
+    - `JsonValue;`
+
+      - `AUTO("auto")`
+
+    - `long`
+
+  - `Optional<LearningRateMultiplier> learningRateMultiplier`
+
+    Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+    - `JsonValue;`
+
+      - `AUTO("auto")`
+
+    - `double`
+
+  - `Optional<NEpochs> nEpochs`
+
+    The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+    - `JsonValue;`
+
+      - `AUTO("auto")`
+
+    - `long`
+
+  - `Optional<ReasoningEffort> reasoningEffort`
+
+    Level of reasoning effort.
+
+    - `DEFAULT("default")`
+
+    - `LOW("low")`
+
+    - `MEDIUM("medium")`
+
+    - `HIGH("high")`
+
+### Reinforcement Method
+
+- `class ReinforcementMethod:`
+
+  Configuration for the reinforcement fine-tuning method.
+
+  - `Grader grader`
+
+    The grader used for the fine-tuning job.
+
+    - `class StringCheckGrader:`
+
+      A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+      - `String input`
+
+        The input text. This may include template strings.
+
+      - `String name`
+
+        The name of the grader.
+
+      - `Operation operation`
+
+        The string check operation to perform. One of `eq`, `ne`, `like`, or `ilike`.
+
+        - `EQ("eq")`
+
+        - `NE("ne")`
+
+        - `LIKE("like")`
+
+        - `ILIKE("ilike")`
+
+      - `String reference`
+
+        The reference text. This may include template strings.
+
+      - `JsonValue; type "string_check"constant`
+
+        The object type, which is always `string_check`.
+
+        - `STRING_CHECK("string_check")`
+
+    - `class TextSimilarityGrader:`
+
+      A TextSimilarityGrader object which grades text based on similarity metrics.
+
+      - `EvaluationMetric evaluationMetric`
+
+        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("cosine")`
+
+        - `FUZZY_MATCH("fuzzy_match")`
+
+        - `BLEU("bleu")`
+
+        - `GLEU("gleu")`
+
+        - `METEOR("meteor")`
+
+        - `ROUGE_1("rouge_1")`
+
+        - `ROUGE_2("rouge_2")`
+
+        - `ROUGE_3("rouge_3")`
+
+        - `ROUGE_4("rouge_4")`
+
+        - `ROUGE_5("rouge_5")`
+
+        - `ROUGE_L("rouge_l")`
+
+      - `String input`
+
+        The text being graded.
+
+      - `String name`
+
+        The name of the grader.
+
+      - `String reference`
+
+        The text being graded against.
+
+      - `JsonValue; type "text_similarity"constant`
+
+        The type of grader.
+
+        - `TEXT_SIMILARITY("text_similarity")`
+
+    - `class PythonGrader:`
+
+      A PythonGrader object that runs a python script on the input.
+
+      - `String name`
+
+        The name of the grader.
+
+      - `String source`
+
+        The source code of the python script.
+
+      - `JsonValue; type "python"constant`
+
+        The object type, which is always `python`.
+
+        - `PYTHON("python")`
+
+      - `Optional<String> imageTag`
+
+        The image tag to use for the python script.
+
+    - `class ScoreModelGrader:`
+
+      A ScoreModelGrader object that uses a model to assign a score to the input.
+
+      - `List<Input> input`
+
+        The input messages evaluated by the grader. Supports text, output text, input image, and input audio content blocks, and may include template strings.
+
+        - `Content content`
+
+          Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items.
+
+          - `String`
+
+          - `class ResponseInputText:`
+
+            A text input to the model.
+
+            - `String text`
+
+              The text input to the model.
+
+            - `JsonValue; type "input_text"constant`
+
+              The type of the input item. Always `input_text`.
+
+              - `INPUT_TEXT("input_text")`
+
+            - `Optional<PromptCacheBreakpoint> promptCacheBreakpoint`
+
+              Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's `prompt_cache_options.ttl`; the boundary is not rounded to a token block.
+
+              - `JsonValue; mode "explicit"constant`
+
+                The breakpoint mode. Always `explicit`.
+
+                - `EXPLICIT("explicit")`
+
+          - `class OutputText:`
+
+            A text output from the model.
+
+            - `String text`
+
+              The text output from the model.
+
+            - `JsonValue; type "output_text"constant`
+
+              The type of the output text. Always `output_text`.
+
+              - `OUTPUT_TEXT("output_text")`
+
+          - `class InputImage:`
+
+            An image input block used within EvalItem content arrays.
+
+            - `String imageUrl`
+
+              The URL of the image input.
+
+            - `JsonValue; type "input_image"constant`
+
+              The type of the image input. Always `input_image`.
+
+              - `INPUT_IMAGE("input_image")`
+
+            - `Optional<String> detail`
+
+              The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+          - `class ResponseInputAudio:`
+
+            An audio input to the model.
+
+            - `InputAudio inputAudio`
+
+              - `String data`
+
+                Base64-encoded audio data.
+
+              - `Format format`
+
+                The format of the audio data. Currently supported formats are `mp3` and
+                `wav`.
+
+                - `MP3("mp3")`
+
+                - `WAV("wav")`
+
+            - `JsonValue; type "input_audio"constant`
+
+              The type of the input item. Always `input_audio`.
+
+              - `INPUT_AUDIO("input_audio")`
+
+          - `List<EvalContentItem>`
+
+            - `String`
+
+            - `class ResponseInputText:`
+
+              A text input to the model.
+
+            - `OutputText`
+
+              - `String text`
+
+                The text output from the model.
+
+              - `JsonValue; type "output_text"constant`
+
+                The type of the output text. Always `output_text`.
+
+                - `OUTPUT_TEXT("output_text")`
+
+            - `InputImage`
+
+              - `String imageUrl`
+
+                The URL of the image input.
+
+              - `JsonValue; type "input_image"constant`
+
+                The type of the image input. Always `input_image`.
+
+                - `INPUT_IMAGE("input_image")`
+
+              - `Optional<String> detail`
+
+                The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+            - `class ResponseInputAudio:`
+
+              An audio input to the model.
+
+        - `Role role`
+
+          The role of the message input. One of `user`, `assistant`, `system`, or
+          `developer`.
+
+          - `USER("user")`
+
+          - `ASSISTANT("assistant")`
+
+          - `SYSTEM("system")`
+
+          - `DEVELOPER("developer")`
+
+        - `Optional<Type> type`
+
+          The type of the message input. Always `message`.
+
+          - `MESSAGE("message")`
+
+      - `String model`
+
+        The model to use for the evaluation.
+
+      - `String name`
+
+        The name of the grader.
+
+      - `JsonValue; type "score_model"constant`
+
+        The object type, which is always `score_model`.
+
+        - `SCORE_MODEL("score_model")`
+
+      - `Optional<List<Double>> range`
+
+        The range of the score. Defaults to `[0, 1]`.
+
+      - `Optional<SamplingParams> samplingParams`
+
+        The sampling parameters for the model.
+
+        - `Optional<Long> maxCompletionsTokens`
+
+          The maximum number of tokens the grader model may generate in its response.
+
+        - `Optional<ReasoningEffort> reasoningEffort`
+
+          Constrains effort on reasoning for reasoning models. Currently supported
+          values are `none`, `minimal`, `low`, `medium`, `high`, `xhigh`, and `max`.
+          Reducing reasoning effort can result in faster responses and fewer tokens
+          used on reasoning in a response. Not all reasoning models support every
+          value. See the
+          [reasoning guide](https://platform.openai.com/docs/guides/reasoning)
+          for model-specific support.
+
+          - `NONE("none")`
+
+          - `MINIMAL("minimal")`
+
+          - `LOW("low")`
+
+          - `MEDIUM("medium")`
+
+          - `HIGH("high")`
+
+          - `XHIGH("xhigh")`
+
+          - `MAX("max")`
+
+        - `Optional<Long> seed`
+
+          A seed value to initialize the randomness, during sampling.
+
+        - `Optional<Double> temperature`
+
+          A higher temperature increases randomness in the outputs.
+
+        - `Optional<Double> topP`
+
+          An alternative to temperature for nucleus sampling; 1.0 includes all tokens.
+
+    - `class MultiGrader:`
+
+      A MultiGrader object combines the output of multiple graders to produce a single score.
+
+      - `String calculateOutput`
+
+        A formula to calculate the output based on grader results.
+
+      - `Graders graders`
+
+        A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+        - `class StringCheckGrader:`
+
+          A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+        - `class TextSimilarityGrader:`
+
+          A TextSimilarityGrader object which grades text based on similarity metrics.
+
+        - `class PythonGrader:`
+
+          A PythonGrader object that runs a python script on the input.
+
+        - `class ScoreModelGrader:`
+
+          A ScoreModelGrader object that uses a model to assign a score to the input.
+
+        - `class LabelModelGrader:`
+
+          A LabelModelGrader object which uses a model to assign labels to each item
+          in the evaluation.
+
+          - `List<Input> input`
+
+            - `Content content`
+
+              Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items.
+
+              - `String`
+
+              - `class ResponseInputText:`
+
+                A text input to the model.
+
+              - `class OutputText:`
+
+                A text output from the model.
+
+                - `String text`
+
+                  The text output from the model.
+
+                - `JsonValue; type "output_text"constant`
+
+                  The type of the output text. Always `output_text`.
+
+                  - `OUTPUT_TEXT("output_text")`
+
+              - `class InputImage:`
+
+                An image input block used within EvalItem content arrays.
+
+                - `String imageUrl`
+
+                  The URL of the image input.
+
+                - `JsonValue; type "input_image"constant`
+
+                  The type of the image input. Always `input_image`.
+
+                  - `INPUT_IMAGE("input_image")`
+
+                - `Optional<String> detail`
+
+                  The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+              - `class ResponseInputAudio:`
+
+                An audio input to the model.
+
+              - `List<EvalContentItem>`
+
+                - `String`
+
+                - `class ResponseInputText:`
+
+                  A text input to the model.
+
+                - `OutputText`
+
+                - `InputImage`
+
+                - `class ResponseInputAudio:`
+
+                  An audio input to the model.
+
+            - `Role role`
+
+              The role of the message input. One of `user`, `assistant`, `system`, or
+              `developer`.
+
+              - `USER("user")`
+
+              - `ASSISTANT("assistant")`
+
+              - `SYSTEM("system")`
+
+              - `DEVELOPER("developer")`
+
+            - `Optional<Type> type`
+
+              The type of the message input. Always `message`.
+
+              - `MESSAGE("message")`
+
+          - `List<String> labels`
+
+            The labels to assign to each item in the evaluation.
+
+          - `String model`
+
+            The model to use for the evaluation. Must support structured outputs.
+
+          - `String name`
+
+            The name of the grader.
+
+          - `List<String> passingLabels`
+
+            The labels that indicate a passing result. Must be a subset of labels.
+
+          - `JsonValue; type "label_model"constant`
+
+            The object type, which is always `label_model`.
+
+            - `LABEL_MODEL("label_model")`
+
+      - `String name`
+
+        The name of the grader.
+
+      - `JsonValue; type "multi"constant`
+
+        The object type, which is always `multi`.
+
+        - `MULTI("multi")`
+
+  - `Optional<ReinforcementHyperparameters> hyperparameters`
+
+    The hyperparameters used for the reinforcement fine-tuning job.
+
+    - `Optional<BatchSize> batchSize`
+
+      Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+      - `JsonValue;`
+
+        - `AUTO("auto")`
+
+      - `long`
+
+    - `Optional<ComputeMultiplier> computeMultiplier`
+
+      Multiplier on amount of compute used for exploring search space during training.
+
+      - `JsonValue;`
+
+        - `AUTO("auto")`
+
+      - `double`
+
+    - `Optional<EvalInterval> evalInterval`
+
+      The number of training steps between evaluation runs.
+
+      - `JsonValue;`
+
+        - `AUTO("auto")`
+
+      - `long`
+
+    - `Optional<EvalSamples> evalSamples`
+
+      Number of evaluation samples to generate per training step.
+
+      - `JsonValue;`
+
+        - `AUTO("auto")`
+
+      - `long`
+
+    - `Optional<LearningRateMultiplier> learningRateMultiplier`
+
+      Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+      - `JsonValue;`
+
+        - `AUTO("auto")`
+
+      - `double`
+
+    - `Optional<NEpochs> nEpochs`
+
+      The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+      - `JsonValue;`
+
+        - `AUTO("auto")`
+
+      - `long`
+
+    - `Optional<ReasoningEffort> reasoningEffort`
+
+      Level of reasoning effort.
+
+      - `DEFAULT("default")`
+
+      - `LOW("low")`
+
+      - `MEDIUM("medium")`
+
+      - `HIGH("high")`
+
+### Supervised Hyperparameters
+
+- `class SupervisedHyperparameters:`
+
+  The hyperparameters used for the fine-tuning job.
+
+  - `Optional<BatchSize> batchSize`
+
+    Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+    - `JsonValue;`
+
+      - `AUTO("auto")`
+
+    - `long`
+
+  - `Optional<LearningRateMultiplier> learningRateMultiplier`
+
+    Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+    - `JsonValue;`
+
+      - `AUTO("auto")`
+
+    - `double`
+
+  - `Optional<NEpochs> nEpochs`
+
+    The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+    - `JsonValue;`
+
+      - `AUTO("auto")`
+
+    - `long`
+
+### Supervised Method
+
+- `class SupervisedMethod:`
+
+  Configuration for the supervised fine-tuning method.
+
+  - `Optional<SupervisedHyperparameters> hyperparameters`
+
+    The hyperparameters used for the fine-tuning job.
+
+    - `Optional<BatchSize> batchSize`
+
+      Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+      - `JsonValue;`
+
+        - `AUTO("auto")`
+
+      - `long`
+
+    - `Optional<LearningRateMultiplier> learningRateMultiplier`
+
+      Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+      - `JsonValue;`
+
+        - `AUTO("auto")`
+
+      - `double`
+
+    - `Optional<NEpochs> nEpochs`
+
+      The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+      - `JsonValue;`
+
+        - `AUTO("auto")`
+
+      - `long`
+
+# Jobs
+
+## Create fine-tuning job
+
+`FineTuningJob fineTuning().jobs().create(JobCreateParamsparams, RequestOptionsrequestOptions = RequestOptions.none())`
+
+**post** `/fine_tuning/jobs`
+
+Create fine-tuning job
+
+### Parameters
+
+- `JobCreateParams params`
+
+  - `Model model`
+
+    The name of the model to fine-tune. You can select one of the
+    [supported models](https://platform.openai.com/docs/guides/fine-tuning#which-models-can-be-fine-tuned).
+
+    - `BABBAGE_002("babbage-002")`
+
+    - `DAVINCI_002("davinci-002")`
+
+    - `GPT_3_5_TURBO("gpt-3.5-turbo")`
+
+    - `GPT_4O_MINI("gpt-4o-mini")`
+
+  - `String trainingFile`
+
+    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.
+
+  - `Optional<Hyperparameters> hyperparameters`
+
+    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.
+
+    - `Optional<BatchSize> batchSize`
+
+      Number of examples in each batch. A larger batch size means that model parameters
+      are updated less frequently, but with lower variance.
+
+      - `JsonValue;`
+
+        - `AUTO("auto")`
+
+      - `long`
+
+    - `Optional<LearningRateMultiplier> learningRateMultiplier`
+
+      Scaling factor for the learning rate. A smaller learning rate may be useful to avoid
+      overfitting.
+
+      - `JsonValue;`
+
+        - `AUTO("auto")`
+
+      - `double`
+
+    - `Optional<NEpochs> nEpochs`
+
+      The number of epochs to train the model for. An epoch refers to one full cycle
+      through the training dataset.
+
+      - `JsonValue;`
+
+        - `AUTO("auto")`
+
+      - `long`
+
+  - `Optional<List<Integration>> integrations`
+
+    A list of integrations to enable for your fine-tuning job.
+
+    - `JsonValue; type "wandb"constant`
+
+      The type of integration to enable. Currently, only "wandb" (Weights and Biases) is supported.
+
+      - `WANDB("wandb")`
+
+    - `Wandb wandb`
+
+      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.
+
+      - `String project`
+
+        The name of the project that the new run will be created under.
+
+      - `Optional<String> entity`
+
+        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.
+
+      - `Optional<String> name`
+
+        A display name to set for the run. If not set, we will use the Job ID as the name.
+
+      - `Optional<List<String>> tags`
+
+        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}".
+
+  - `Optional<Metadata> metadata`
+
+    Set of 16 key-value pairs that can be attached to an object. This can be
+    useful for storing additional information about the object in a structured
+    format, and querying for objects via API or the dashboard.
+
+    Keys are strings with a maximum length of 64 characters. Values are strings
+    with a maximum length of 512 characters.
+
+  - `Optional<Method> method`
+
+    The method used for fine-tuning.
+
+    - `Type type`
+
+      The type of method. Is either `supervised`, `dpo`, or `reinforcement`.
+
+      - `SUPERVISED("supervised")`
+
+      - `DPO("dpo")`
+
+      - `REINFORCEMENT("reinforcement")`
+
+    - `Optional<DpoMethod> dpo`
+
+      Configuration for the DPO fine-tuning method.
+
+      - `Optional<DpoHyperparameters> hyperparameters`
+
+        The hyperparameters used for the DPO fine-tuning job.
+
+        - `Optional<BatchSize> batchSize`
+
+          Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+        - `Optional<Beta> beta`
+
+          The beta value for the DPO method. A higher beta value will increase the weight of the penalty between the policy and reference model.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `double`
+
+        - `Optional<LearningRateMultiplier> learningRateMultiplier`
+
+          Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `double`
+
+        - `Optional<NEpochs> nEpochs`
+
+          The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+    - `Optional<ReinforcementMethod> reinforcement`
+
+      Configuration for the reinforcement fine-tuning method.
+
+      - `Grader grader`
+
+        The grader used for the fine-tuning job.
+
+        - `class StringCheckGrader:`
+
+          A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+          - `String input`
+
+            The input text. This may include template strings.
+
+          - `String name`
+
+            The name of the grader.
+
+          - `Operation operation`
+
+            The string check operation to perform. One of `eq`, `ne`, `like`, or `ilike`.
+
+            - `EQ("eq")`
+
+            - `NE("ne")`
+
+            - `LIKE("like")`
+
+            - `ILIKE("ilike")`
+
+          - `String reference`
+
+            The reference text. This may include template strings.
+
+          - `JsonValue; type "string_check"constant`
+
+            The object type, which is always `string_check`.
+
+            - `STRING_CHECK("string_check")`
+
+        - `class TextSimilarityGrader:`
+
+          A TextSimilarityGrader object which grades text based on similarity metrics.
+
+          - `EvaluationMetric evaluationMetric`
+
+            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("cosine")`
+
+            - `FUZZY_MATCH("fuzzy_match")`
+
+            - `BLEU("bleu")`
+
+            - `GLEU("gleu")`
+
+            - `METEOR("meteor")`
+
+            - `ROUGE_1("rouge_1")`
+
+            - `ROUGE_2("rouge_2")`
+
+            - `ROUGE_3("rouge_3")`
+
+            - `ROUGE_4("rouge_4")`
+
+            - `ROUGE_5("rouge_5")`
+
+            - `ROUGE_L("rouge_l")`
+
+          - `String input`
+
+            The text being graded.
+
+          - `String name`
+
+            The name of the grader.
+
+          - `String reference`
+
+            The text being graded against.
+
+          - `JsonValue; type "text_similarity"constant`
+
+            The type of grader.
+
+            - `TEXT_SIMILARITY("text_similarity")`
+
+        - `class PythonGrader:`
+
+          A PythonGrader object that runs a python script on the input.
+
+          - `String name`
+
+            The name of the grader.
+
+          - `String source`
+
+            The source code of the python script.
+
+          - `JsonValue; type "python"constant`
+
+            The object type, which is always `python`.
+
+            - `PYTHON("python")`
+
+          - `Optional<String> imageTag`
+
+            The image tag to use for the python script.
+
+        - `class ScoreModelGrader:`
+
+          A ScoreModelGrader object that uses a model to assign a score to the input.
+
+          - `List<Input> input`
+
+            The input messages evaluated by the grader. Supports text, output text, input image, and input audio content blocks, and may include template strings.
+
+            - `Content content`
+
+              Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items.
+
+              - `String`
+
+              - `class ResponseInputText:`
+
+                A text input to the model.
+
+                - `String text`
+
+                  The text input to the model.
+
+                - `JsonValue; type "input_text"constant`
+
+                  The type of the input item. Always `input_text`.
+
+                  - `INPUT_TEXT("input_text")`
+
+                - `Optional<PromptCacheBreakpoint> promptCacheBreakpoint`
+
+                  Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's `prompt_cache_options.ttl`; the boundary is not rounded to a token block.
+
+                  - `JsonValue; mode "explicit"constant`
+
+                    The breakpoint mode. Always `explicit`.
+
+                    - `EXPLICIT("explicit")`
+
+              - `class OutputText:`
+
+                A text output from the model.
+
+                - `String text`
+
+                  The text output from the model.
+
+                - `JsonValue; type "output_text"constant`
+
+                  The type of the output text. Always `output_text`.
+
+                  - `OUTPUT_TEXT("output_text")`
+
+              - `class InputImage:`
+
+                An image input block used within EvalItem content arrays.
+
+                - `String imageUrl`
+
+                  The URL of the image input.
+
+                - `JsonValue; type "input_image"constant`
+
+                  The type of the image input. Always `input_image`.
+
+                  - `INPUT_IMAGE("input_image")`
+
+                - `Optional<String> detail`
+
+                  The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+              - `class ResponseInputAudio:`
+
+                An audio input to the model.
+
+                - `InputAudio inputAudio`
+
+                  - `String data`
+
+                    Base64-encoded audio data.
+
+                  - `Format format`
+
+                    The format of the audio data. Currently supported formats are `mp3` and
+                    `wav`.
+
+                    - `MP3("mp3")`
+
+                    - `WAV("wav")`
+
+                - `JsonValue; type "input_audio"constant`
+
+                  The type of the input item. Always `input_audio`.
+
+                  - `INPUT_AUDIO("input_audio")`
+
+              - `List<EvalContentItem>`
+
+                - `String`
+
+                - `class ResponseInputText:`
+
+                  A text input to the model.
+
+                - `OutputText`
+
+                  - `String text`
+
+                    The text output from the model.
+
+                  - `JsonValue; type "output_text"constant`
+
+                    The type of the output text. Always `output_text`.
+
+                    - `OUTPUT_TEXT("output_text")`
+
+                - `InputImage`
+
+                  - `String imageUrl`
+
+                    The URL of the image input.
+
+                  - `JsonValue; type "input_image"constant`
+
+                    The type of the image input. Always `input_image`.
+
+                    - `INPUT_IMAGE("input_image")`
+
+                  - `Optional<String> detail`
+
+                    The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+                - `class ResponseInputAudio:`
+
+                  An audio input to the model.
+
+            - `Role role`
+
+              The role of the message input. One of `user`, `assistant`, `system`, or
+              `developer`.
+
+              - `USER("user")`
+
+              - `ASSISTANT("assistant")`
+
+              - `SYSTEM("system")`
+
+              - `DEVELOPER("developer")`
+
+            - `Optional<Type> type`
+
+              The type of the message input. Always `message`.
+
+              - `MESSAGE("message")`
+
+          - `String model`
+
+            The model to use for the evaluation.
+
+          - `String name`
+
+            The name of the grader.
+
+          - `JsonValue; type "score_model"constant`
+
+            The object type, which is always `score_model`.
+
+            - `SCORE_MODEL("score_model")`
+
+          - `Optional<List<Double>> range`
+
+            The range of the score. Defaults to `[0, 1]`.
+
+          - `Optional<SamplingParams> samplingParams`
+
+            The sampling parameters for the model.
+
+            - `Optional<Long> maxCompletionsTokens`
+
+              The maximum number of tokens the grader model may generate in its response.
+
+            - `Optional<ReasoningEffort> reasoningEffort`
+
+              Constrains effort on reasoning for reasoning models. Currently supported
+              values are `none`, `minimal`, `low`, `medium`, `high`, `xhigh`, and `max`.
+              Reducing reasoning effort can result in faster responses and fewer tokens
+              used on reasoning in a response. Not all reasoning models support every
+              value. See the
+              [reasoning guide](https://platform.openai.com/docs/guides/reasoning)
+              for model-specific support.
+
+              - `NONE("none")`
+
+              - `MINIMAL("minimal")`
+
+              - `LOW("low")`
+
+              - `MEDIUM("medium")`
+
+              - `HIGH("high")`
+
+              - `XHIGH("xhigh")`
+
+              - `MAX("max")`
+
+            - `Optional<Long> seed`
+
+              A seed value to initialize the randomness, during sampling.
+
+            - `Optional<Double> temperature`
+
+              A higher temperature increases randomness in the outputs.
+
+            - `Optional<Double> topP`
+
+              An alternative to temperature for nucleus sampling; 1.0 includes all tokens.
+
+        - `class MultiGrader:`
+
+          A MultiGrader object combines the output of multiple graders to produce a single score.
+
+          - `String calculateOutput`
+
+            A formula to calculate the output based on grader results.
+
+          - `Graders graders`
+
+            A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+            - `class StringCheckGrader:`
+
+              A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+            - `class TextSimilarityGrader:`
+
+              A TextSimilarityGrader object which grades text based on similarity metrics.
+
+            - `class PythonGrader:`
+
+              A PythonGrader object that runs a python script on the input.
+
+            - `class ScoreModelGrader:`
+
+              A ScoreModelGrader object that uses a model to assign a score to the input.
+
+            - `class LabelModelGrader:`
+
+              A LabelModelGrader object which uses a model to assign labels to each item
+              in the evaluation.
+
+              - `List<Input> input`
+
+                - `Content content`
+
+                  Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items.
+
+                  - `String`
+
+                  - `class ResponseInputText:`
+
+                    A text input to the model.
+
+                  - `class OutputText:`
+
+                    A text output from the model.
+
+                    - `String text`
+
+                      The text output from the model.
+
+                    - `JsonValue; type "output_text"constant`
+
+                      The type of the output text. Always `output_text`.
+
+                      - `OUTPUT_TEXT("output_text")`
+
+                  - `class InputImage:`
+
+                    An image input block used within EvalItem content arrays.
+
+                    - `String imageUrl`
+
+                      The URL of the image input.
+
+                    - `JsonValue; type "input_image"constant`
+
+                      The type of the image input. Always `input_image`.
+
+                      - `INPUT_IMAGE("input_image")`
+
+                    - `Optional<String> detail`
+
+                      The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+                  - `class ResponseInputAudio:`
+
+                    An audio input to the model.
+
+                  - `List<EvalContentItem>`
+
+                    - `String`
+
+                    - `class ResponseInputText:`
+
+                      A text input to the model.
+
+                    - `OutputText`
+
+                    - `InputImage`
+
+                    - `class ResponseInputAudio:`
+
+                      An audio input to the model.
+
+                - `Role role`
+
+                  The role of the message input. One of `user`, `assistant`, `system`, or
+                  `developer`.
+
+                  - `USER("user")`
+
+                  - `ASSISTANT("assistant")`
+
+                  - `SYSTEM("system")`
+
+                  - `DEVELOPER("developer")`
+
+                - `Optional<Type> type`
+
+                  The type of the message input. Always `message`.
+
+                  - `MESSAGE("message")`
+
+              - `List<String> labels`
+
+                The labels to assign to each item in the evaluation.
+
+              - `String model`
+
+                The model to use for the evaluation. Must support structured outputs.
+
+              - `String name`
+
+                The name of the grader.
+
+              - `List<String> passingLabels`
+
+                The labels that indicate a passing result. Must be a subset of labels.
+
+              - `JsonValue; type "label_model"constant`
+
+                The object type, which is always `label_model`.
+
+                - `LABEL_MODEL("label_model")`
+
+          - `String name`
+
+            The name of the grader.
+
+          - `JsonValue; type "multi"constant`
+
+            The object type, which is always `multi`.
+
+            - `MULTI("multi")`
+
+      - `Optional<ReinforcementHyperparameters> hyperparameters`
+
+        The hyperparameters used for the reinforcement fine-tuning job.
+
+        - `Optional<BatchSize> batchSize`
+
+          Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+        - `Optional<ComputeMultiplier> computeMultiplier`
+
+          Multiplier on amount of compute used for exploring search space during training.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `double`
+
+        - `Optional<EvalInterval> evalInterval`
+
+          The number of training steps between evaluation runs.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+        - `Optional<EvalSamples> evalSamples`
+
+          Number of evaluation samples to generate per training step.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+        - `Optional<LearningRateMultiplier> learningRateMultiplier`
+
+          Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `double`
+
+        - `Optional<NEpochs> nEpochs`
+
+          The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+        - `Optional<ReasoningEffort> reasoningEffort`
+
+          Level of reasoning effort.
+
+          - `DEFAULT("default")`
+
+          - `LOW("low")`
+
+          - `MEDIUM("medium")`
+
+          - `HIGH("high")`
+
+    - `Optional<SupervisedMethod> supervised`
+
+      Configuration for the supervised fine-tuning method.
+
+      - `Optional<SupervisedHyperparameters> hyperparameters`
+
+        The hyperparameters used for the fine-tuning job.
+
+        - `Optional<BatchSize> batchSize`
+
+          Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+        - `Optional<LearningRateMultiplier> learningRateMultiplier`
+
+          Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `double`
+
+        - `Optional<NEpochs> nEpochs`
+
+          The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+  - `Optional<Long> seed`
+
+    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.
+
+  - `Optional<String> suffix`
+
+    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`.
+
+  - `Optional<String> validationFile`
+
+    The ID of an uploaded file that contains validation data.
+
+    If you provide this file, the data is used to generate validation
+    metrics periodically during fine-tuning. These metrics can be viewed in
+    the fine-tuning results file.
+    The same data should not be present in both train and validation files.
+
+    Your dataset must be formatted as a JSONL file. You must upload your file with the purpose `fine-tune`.
+
+    See the [fine-tuning guide](https://platform.openai.com/docs/guides/model-optimization) for more details.
+
+### Returns
+
+- `class FineTuningJob:`
+
+  The `fine_tuning.job` object represents a fine-tuning job that has been created through the API.
+
+  - `String id`
+
+    The object identifier, which can be referenced in the API endpoints.
+
+  - `long createdAt`
+
+    The Unix timestamp (in seconds) for when the fine-tuning job was created.
+
+  - `Optional<Error> error`
+
+    For fine-tuning jobs that have `failed`, this will contain more information on the cause of the failure.
+
+    - `String code`
+
+      A machine-readable error code.
+
+    - `String message`
+
+      A human-readable error message.
+
+    - `Optional<String> param`
+
+      The parameter that was invalid, usually `training_file` or `validation_file`. This field will be null if the failure was not parameter-specific.
+
+  - `Optional<String> fineTunedModel`
+
+    The name of the fine-tuned model that is being created. The value will be null if the fine-tuning job is still running.
+
+  - `Optional<Long> finishedAt`
+
+    The Unix timestamp (in seconds) for when the fine-tuning job was finished. The value will be null if the fine-tuning job is still running.
+
+  - `Hyperparameters hyperparameters`
+
+    The hyperparameters used for the fine-tuning job. This value will only be returned when running `supervised` jobs.
+
+    - `Optional<BatchSize> batchSize`
+
+      Number of examples in each batch. A larger batch size means that model parameters
+      are updated less frequently, but with lower variance.
+
+      - `JsonValue;`
+
+        - `AUTO("auto")`
+
+      - `long`
+
+    - `Optional<LearningRateMultiplier> learningRateMultiplier`
+
+      Scaling factor for the learning rate. A smaller learning rate may be useful to avoid
+      overfitting.
+
+      - `JsonValue;`
+
+        - `AUTO("auto")`
+
+      - `double`
+
+    - `Optional<NEpochs> nEpochs`
+
+      The number of epochs to train the model for. An epoch refers to one full cycle
+      through the training dataset.
+
+      - `JsonValue;`
+
+        - `AUTO("auto")`
+
+      - `long`
+
+  - `String model`
+
+    The base model that is being fine-tuned.
+
+  - `JsonValue; object_ "fine_tuning.job"constant`
+
+    The object type, which is always "fine_tuning.job".
+
+    - `FINE_TUNING_JOB("fine_tuning.job")`
+
+  - `String organizationId`
+
+    The organization that owns the fine-tuning job.
+
+  - `List<String> resultFiles`
+
+    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).
+
+  - `long seed`
+
+    The seed used for the fine-tuning job.
+
+  - `Status status`
+
+    The current status of the fine-tuning job, which can be either `validating_files`, `queued`, `running`, `succeeded`, `failed`, or `cancelled`.
+
+    - `VALIDATING_FILES("validating_files")`
+
+    - `QUEUED("queued")`
+
+    - `RUNNING("running")`
+
+    - `SUCCEEDED("succeeded")`
+
+    - `FAILED("failed")`
+
+    - `CANCELLED("cancelled")`
+
+  - `Optional<Long> trainedTokens`
+
+    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.
+
+  - `String trainingFile`
+
+    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).
+
+  - `Optional<String> validationFile`
+
+    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).
+
+  - `Optional<Long> estimatedFinish`
+
+    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.
+
+  - `Optional<List<FineTuningJobWandbIntegrationObject>> integrations`
+
+    A list of integrations to enable for this fine-tuning job.
+
+    - `JsonValue; type "wandb"constant`
+
+      The type of the integration being enabled for the fine-tuning job
+
+      - `WANDB("wandb")`
+
+    - `FineTuningJobWandbIntegration wandb`
+
+      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.
+
+      - `String project`
+
+        The name of the project that the new run will be created under.
+
+      - `Optional<String> entity`
+
+        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.
+
+      - `Optional<String> name`
+
+        A display name to set for the run. If not set, we will use the Job ID as the name.
+
+      - `Optional<List<String>> tags`
+
+        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}".
+
+  - `Optional<Metadata> metadata`
+
+    Set of 16 key-value pairs that can be attached to an object. This can be
+    useful for storing additional information about the object in a structured
+    format, and querying for objects via API or the dashboard.
+
+    Keys are strings with a maximum length of 64 characters. Values are strings
+    with a maximum length of 512 characters.
+
+  - `Optional<Method> method`
+
+    The method used for fine-tuning.
+
+    - `Type type`
+
+      The type of method. Is either `supervised`, `dpo`, or `reinforcement`.
+
+      - `SUPERVISED("supervised")`
+
+      - `DPO("dpo")`
+
+      - `REINFORCEMENT("reinforcement")`
+
+    - `Optional<DpoMethod> dpo`
+
+      Configuration for the DPO fine-tuning method.
+
+      - `Optional<DpoHyperparameters> hyperparameters`
+
+        The hyperparameters used for the DPO fine-tuning job.
+
+        - `Optional<BatchSize> batchSize`
+
+          Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+        - `Optional<Beta> beta`
+
+          The beta value for the DPO method. A higher beta value will increase the weight of the penalty between the policy and reference model.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `double`
+
+        - `Optional<LearningRateMultiplier> learningRateMultiplier`
+
+          Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `double`
+
+        - `Optional<NEpochs> nEpochs`
+
+          The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+    - `Optional<ReinforcementMethod> reinforcement`
+
+      Configuration for the reinforcement fine-tuning method.
+
+      - `Grader grader`
+
+        The grader used for the fine-tuning job.
+
+        - `class StringCheckGrader:`
+
+          A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+          - `String input`
+
+            The input text. This may include template strings.
+
+          - `String name`
+
+            The name of the grader.
+
+          - `Operation operation`
+
+            The string check operation to perform. One of `eq`, `ne`, `like`, or `ilike`.
+
+            - `EQ("eq")`
+
+            - `NE("ne")`
+
+            - `LIKE("like")`
+
+            - `ILIKE("ilike")`
+
+          - `String reference`
+
+            The reference text. This may include template strings.
+
+          - `JsonValue; type "string_check"constant`
+
+            The object type, which is always `string_check`.
+
+            - `STRING_CHECK("string_check")`
+
+        - `class TextSimilarityGrader:`
+
+          A TextSimilarityGrader object which grades text based on similarity metrics.
+
+          - `EvaluationMetric evaluationMetric`
+
+            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("cosine")`
+
+            - `FUZZY_MATCH("fuzzy_match")`
+
+            - `BLEU("bleu")`
+
+            - `GLEU("gleu")`
+
+            - `METEOR("meteor")`
+
+            - `ROUGE_1("rouge_1")`
+
+            - `ROUGE_2("rouge_2")`
+
+            - `ROUGE_3("rouge_3")`
+
+            - `ROUGE_4("rouge_4")`
+
+            - `ROUGE_5("rouge_5")`
+
+            - `ROUGE_L("rouge_l")`
+
+          - `String input`
+
+            The text being graded.
+
+          - `String name`
+
+            The name of the grader.
+
+          - `String reference`
+
+            The text being graded against.
+
+          - `JsonValue; type "text_similarity"constant`
+
+            The type of grader.
+
+            - `TEXT_SIMILARITY("text_similarity")`
+
+        - `class PythonGrader:`
+
+          A PythonGrader object that runs a python script on the input.
+
+          - `String name`
+
+            The name of the grader.
+
+          - `String source`
+
+            The source code of the python script.
+
+          - `JsonValue; type "python"constant`
+
+            The object type, which is always `python`.
+
+            - `PYTHON("python")`
+
+          - `Optional<String> imageTag`
+
+            The image tag to use for the python script.
+
+        - `class ScoreModelGrader:`
+
+          A ScoreModelGrader object that uses a model to assign a score to the input.
+
+          - `List<Input> input`
+
+            The input messages evaluated by the grader. Supports text, output text, input image, and input audio content blocks, and may include template strings.
+
+            - `Content content`
+
+              Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items.
+
+              - `String`
+
+              - `class ResponseInputText:`
+
+                A text input to the model.
+
+                - `String text`
+
+                  The text input to the model.
+
+                - `JsonValue; type "input_text"constant`
+
+                  The type of the input item. Always `input_text`.
+
+                  - `INPUT_TEXT("input_text")`
+
+                - `Optional<PromptCacheBreakpoint> promptCacheBreakpoint`
+
+                  Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's `prompt_cache_options.ttl`; the boundary is not rounded to a token block.
+
+                  - `JsonValue; mode "explicit"constant`
+
+                    The breakpoint mode. Always `explicit`.
+
+                    - `EXPLICIT("explicit")`
+
+              - `class OutputText:`
+
+                A text output from the model.
+
+                - `String text`
+
+                  The text output from the model.
+
+                - `JsonValue; type "output_text"constant`
+
+                  The type of the output text. Always `output_text`.
+
+                  - `OUTPUT_TEXT("output_text")`
+
+              - `class InputImage:`
+
+                An image input block used within EvalItem content arrays.
+
+                - `String imageUrl`
+
+                  The URL of the image input.
+
+                - `JsonValue; type "input_image"constant`
+
+                  The type of the image input. Always `input_image`.
+
+                  - `INPUT_IMAGE("input_image")`
+
+                - `Optional<String> detail`
+
+                  The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+              - `class ResponseInputAudio:`
+
+                An audio input to the model.
+
+                - `InputAudio inputAudio`
+
+                  - `String data`
+
+                    Base64-encoded audio data.
+
+                  - `Format format`
+
+                    The format of the audio data. Currently supported formats are `mp3` and
+                    `wav`.
+
+                    - `MP3("mp3")`
+
+                    - `WAV("wav")`
+
+                - `JsonValue; type "input_audio"constant`
+
+                  The type of the input item. Always `input_audio`.
+
+                  - `INPUT_AUDIO("input_audio")`
+
+              - `List<EvalContentItem>`
+
+                - `String`
+
+                - `class ResponseInputText:`
+
+                  A text input to the model.
+
+                - `OutputText`
+
+                  - `String text`
+
+                    The text output from the model.
+
+                  - `JsonValue; type "output_text"constant`
+
+                    The type of the output text. Always `output_text`.
+
+                    - `OUTPUT_TEXT("output_text")`
+
+                - `InputImage`
+
+                  - `String imageUrl`
+
+                    The URL of the image input.
+
+                  - `JsonValue; type "input_image"constant`
+
+                    The type of the image input. Always `input_image`.
+
+                    - `INPUT_IMAGE("input_image")`
+
+                  - `Optional<String> detail`
+
+                    The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+                - `class ResponseInputAudio:`
+
+                  An audio input to the model.
+
+            - `Role role`
+
+              The role of the message input. One of `user`, `assistant`, `system`, or
+              `developer`.
+
+              - `USER("user")`
+
+              - `ASSISTANT("assistant")`
+
+              - `SYSTEM("system")`
+
+              - `DEVELOPER("developer")`
+
+            - `Optional<Type> type`
+
+              The type of the message input. Always `message`.
+
+              - `MESSAGE("message")`
+
+          - `String model`
+
+            The model to use for the evaluation.
+
+          - `String name`
+
+            The name of the grader.
+
+          - `JsonValue; type "score_model"constant`
+
+            The object type, which is always `score_model`.
+
+            - `SCORE_MODEL("score_model")`
+
+          - `Optional<List<Double>> range`
+
+            The range of the score. Defaults to `[0, 1]`.
+
+          - `Optional<SamplingParams> samplingParams`
+
+            The sampling parameters for the model.
+
+            - `Optional<Long> maxCompletionsTokens`
+
+              The maximum number of tokens the grader model may generate in its response.
+
+            - `Optional<ReasoningEffort> reasoningEffort`
+
+              Constrains effort on reasoning for reasoning models. Currently supported
+              values are `none`, `minimal`, `low`, `medium`, `high`, `xhigh`, and `max`.
+              Reducing reasoning effort can result in faster responses and fewer tokens
+              used on reasoning in a response. Not all reasoning models support every
+              value. See the
+              [reasoning guide](https://platform.openai.com/docs/guides/reasoning)
+              for model-specific support.
+
+              - `NONE("none")`
+
+              - `MINIMAL("minimal")`
+
+              - `LOW("low")`
+
+              - `MEDIUM("medium")`
+
+              - `HIGH("high")`
+
+              - `XHIGH("xhigh")`
+
+              - `MAX("max")`
+
+            - `Optional<Long> seed`
+
+              A seed value to initialize the randomness, during sampling.
+
+            - `Optional<Double> temperature`
+
+              A higher temperature increases randomness in the outputs.
+
+            - `Optional<Double> topP`
+
+              An alternative to temperature for nucleus sampling; 1.0 includes all tokens.
+
+        - `class MultiGrader:`
+
+          A MultiGrader object combines the output of multiple graders to produce a single score.
+
+          - `String calculateOutput`
+
+            A formula to calculate the output based on grader results.
+
+          - `Graders graders`
+
+            A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+            - `class StringCheckGrader:`
+
+              A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+            - `class TextSimilarityGrader:`
+
+              A TextSimilarityGrader object which grades text based on similarity metrics.
+
+            - `class PythonGrader:`
+
+              A PythonGrader object that runs a python script on the input.
+
+            - `class ScoreModelGrader:`
+
+              A ScoreModelGrader object that uses a model to assign a score to the input.
+
+            - `class LabelModelGrader:`
+
+              A LabelModelGrader object which uses a model to assign labels to each item
+              in the evaluation.
+
+              - `List<Input> input`
+
+                - `Content content`
+
+                  Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items.
+
+                  - `String`
+
+                  - `class ResponseInputText:`
+
+                    A text input to the model.
+
+                  - `class OutputText:`
+
+                    A text output from the model.
+
+                    - `String text`
+
+                      The text output from the model.
+
+                    - `JsonValue; type "output_text"constant`
+
+                      The type of the output text. Always `output_text`.
+
+                      - `OUTPUT_TEXT("output_text")`
+
+                  - `class InputImage:`
+
+                    An image input block used within EvalItem content arrays.
+
+                    - `String imageUrl`
+
+                      The URL of the image input.
+
+                    - `JsonValue; type "input_image"constant`
+
+                      The type of the image input. Always `input_image`.
+
+                      - `INPUT_IMAGE("input_image")`
+
+                    - `Optional<String> detail`
+
+                      The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+                  - `class ResponseInputAudio:`
+
+                    An audio input to the model.
+
+                  - `List<EvalContentItem>`
+
+                    - `String`
+
+                    - `class ResponseInputText:`
+
+                      A text input to the model.
+
+                    - `OutputText`
+
+                    - `InputImage`
+
+                    - `class ResponseInputAudio:`
+
+                      An audio input to the model.
+
+                - `Role role`
+
+                  The role of the message input. One of `user`, `assistant`, `system`, or
+                  `developer`.
+
+                  - `USER("user")`
+
+                  - `ASSISTANT("assistant")`
+
+                  - `SYSTEM("system")`
+
+                  - `DEVELOPER("developer")`
+
+                - `Optional<Type> type`
+
+                  The type of the message input. Always `message`.
+
+                  - `MESSAGE("message")`
+
+              - `List<String> labels`
+
+                The labels to assign to each item in the evaluation.
+
+              - `String model`
+
+                The model to use for the evaluation. Must support structured outputs.
+
+              - `String name`
+
+                The name of the grader.
+
+              - `List<String> passingLabels`
+
+                The labels that indicate a passing result. Must be a subset of labels.
+
+              - `JsonValue; type "label_model"constant`
+
+                The object type, which is always `label_model`.
+
+                - `LABEL_MODEL("label_model")`
+
+          - `String name`
+
+            The name of the grader.
+
+          - `JsonValue; type "multi"constant`
+
+            The object type, which is always `multi`.
+
+            - `MULTI("multi")`
+
+      - `Optional<ReinforcementHyperparameters> hyperparameters`
+
+        The hyperparameters used for the reinforcement fine-tuning job.
+
+        - `Optional<BatchSize> batchSize`
+
+          Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+        - `Optional<ComputeMultiplier> computeMultiplier`
+
+          Multiplier on amount of compute used for exploring search space during training.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `double`
+
+        - `Optional<EvalInterval> evalInterval`
+
+          The number of training steps between evaluation runs.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+        - `Optional<EvalSamples> evalSamples`
+
+          Number of evaluation samples to generate per training step.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+        - `Optional<LearningRateMultiplier> learningRateMultiplier`
+
+          Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `double`
+
+        - `Optional<NEpochs> nEpochs`
+
+          The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+        - `Optional<ReasoningEffort> reasoningEffort`
+
+          Level of reasoning effort.
+
+          - `DEFAULT("default")`
+
+          - `LOW("low")`
+
+          - `MEDIUM("medium")`
+
+          - `HIGH("high")`
+
+    - `Optional<SupervisedMethod> supervised`
+
+      Configuration for the supervised fine-tuning method.
+
+      - `Optional<SupervisedHyperparameters> hyperparameters`
+
+        The hyperparameters used for the fine-tuning job.
+
+        - `Optional<BatchSize> batchSize`
+
+          Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+        - `Optional<LearningRateMultiplier> learningRateMultiplier`
+
+          Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `double`
+
+        - `Optional<NEpochs> nEpochs`
+
+          The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+### Example
+
+```java
+package com.openai.example;
+
+import com.openai.client.OpenAIClient;
+import com.openai.client.okhttp.OpenAIOkHttpClient;
+import com.openai.models.finetuning.jobs.FineTuningJob;
+import com.openai.models.finetuning.jobs.JobCreateParams;
+
+public final class Main {
+    private Main() {}
+
+    public static void main(String[] args) {
+        OpenAIClient client = OpenAIOkHttpClient.fromEnv();
+
+        JobCreateParams params = JobCreateParams.builder()
+            .model(JobCreateParams.Model.GPT_4O_MINI)
+            .trainingFile("file-abc123")
+            .build();
+        FineTuningJob fineTuningJob = client.fineTuning().jobs().create(params);
+    }
+}
+```
+
+#### 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
+
+`JobListPage fineTuning().jobs().list(JobListParamsparams = JobListParams.none(), RequestOptionsrequestOptions = RequestOptions.none())`
+
+**get** `/fine_tuning/jobs`
+
+List fine-tuning jobs
+
+### Parameters
+
+- `JobListParams params`
+
+  - `Optional<String> after`
+
+    Identifier for the last job from the previous pagination request.
+
+  - `Optional<Long> limit`
+
+    Number of fine-tuning jobs to retrieve.
+
+  - `Optional<Metadata> metadata`
+
+    Optional metadata filter. To filter, use the syntax `metadata[k]=v`. Alternatively, set `metadata=null` to indicate no metadata.
+
+### Returns
+
+- `class FineTuningJob:`
+
+  The `fine_tuning.job` object represents a fine-tuning job that has been created through the API.
+
+  - `String id`
+
+    The object identifier, which can be referenced in the API endpoints.
+
+  - `long createdAt`
+
+    The Unix timestamp (in seconds) for when the fine-tuning job was created.
+
+  - `Optional<Error> error`
+
+    For fine-tuning jobs that have `failed`, this will contain more information on the cause of the failure.
+
+    - `String code`
+
+      A machine-readable error code.
+
+    - `String message`
+
+      A human-readable error message.
+
+    - `Optional<String> param`
+
+      The parameter that was invalid, usually `training_file` or `validation_file`. This field will be null if the failure was not parameter-specific.
+
+  - `Optional<String> fineTunedModel`
+
+    The name of the fine-tuned model that is being created. The value will be null if the fine-tuning job is still running.
+
+  - `Optional<Long> finishedAt`
+
+    The Unix timestamp (in seconds) for when the fine-tuning job was finished. The value will be null if the fine-tuning job is still running.
+
+  - `Hyperparameters hyperparameters`
+
+    The hyperparameters used for the fine-tuning job. This value will only be returned when running `supervised` jobs.
+
+    - `Optional<BatchSize> batchSize`
+
+      Number of examples in each batch. A larger batch size means that model parameters
+      are updated less frequently, but with lower variance.
+
+      - `JsonValue;`
+
+        - `AUTO("auto")`
+
+      - `long`
+
+    - `Optional<LearningRateMultiplier> learningRateMultiplier`
+
+      Scaling factor for the learning rate. A smaller learning rate may be useful to avoid
+      overfitting.
+
+      - `JsonValue;`
+
+        - `AUTO("auto")`
+
+      - `double`
+
+    - `Optional<NEpochs> nEpochs`
+
+      The number of epochs to train the model for. An epoch refers to one full cycle
+      through the training dataset.
+
+      - `JsonValue;`
+
+        - `AUTO("auto")`
+
+      - `long`
+
+  - `String model`
+
+    The base model that is being fine-tuned.
+
+  - `JsonValue; object_ "fine_tuning.job"constant`
+
+    The object type, which is always "fine_tuning.job".
+
+    - `FINE_TUNING_JOB("fine_tuning.job")`
+
+  - `String organizationId`
+
+    The organization that owns the fine-tuning job.
+
+  - `List<String> resultFiles`
+
+    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).
+
+  - `long seed`
+
+    The seed used for the fine-tuning job.
+
+  - `Status status`
+
+    The current status of the fine-tuning job, which can be either `validating_files`, `queued`, `running`, `succeeded`, `failed`, or `cancelled`.
+
+    - `VALIDATING_FILES("validating_files")`
+
+    - `QUEUED("queued")`
+
+    - `RUNNING("running")`
+
+    - `SUCCEEDED("succeeded")`
+
+    - `FAILED("failed")`
+
+    - `CANCELLED("cancelled")`
+
+  - `Optional<Long> trainedTokens`
+
+    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.
+
+  - `String trainingFile`
+
+    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).
+
+  - `Optional<String> validationFile`
+
+    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).
+
+  - `Optional<Long> estimatedFinish`
+
+    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.
+
+  - `Optional<List<FineTuningJobWandbIntegrationObject>> integrations`
+
+    A list of integrations to enable for this fine-tuning job.
+
+    - `JsonValue; type "wandb"constant`
+
+      The type of the integration being enabled for the fine-tuning job
+
+      - `WANDB("wandb")`
+
+    - `FineTuningJobWandbIntegration wandb`
+
+      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.
+
+      - `String project`
+
+        The name of the project that the new run will be created under.
+
+      - `Optional<String> entity`
+
+        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.
+
+      - `Optional<String> name`
+
+        A display name to set for the run. If not set, we will use the Job ID as the name.
+
+      - `Optional<List<String>> tags`
+
+        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}".
+
+  - `Optional<Metadata> metadata`
+
+    Set of 16 key-value pairs that can be attached to an object. This can be
+    useful for storing additional information about the object in a structured
+    format, and querying for objects via API or the dashboard.
+
+    Keys are strings with a maximum length of 64 characters. Values are strings
+    with a maximum length of 512 characters.
+
+  - `Optional<Method> method`
+
+    The method used for fine-tuning.
+
+    - `Type type`
+
+      The type of method. Is either `supervised`, `dpo`, or `reinforcement`.
+
+      - `SUPERVISED("supervised")`
+
+      - `DPO("dpo")`
+
+      - `REINFORCEMENT("reinforcement")`
+
+    - `Optional<DpoMethod> dpo`
+
+      Configuration for the DPO fine-tuning method.
+
+      - `Optional<DpoHyperparameters> hyperparameters`
+
+        The hyperparameters used for the DPO fine-tuning job.
+
+        - `Optional<BatchSize> batchSize`
+
+          Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+        - `Optional<Beta> beta`
+
+          The beta value for the DPO method. A higher beta value will increase the weight of the penalty between the policy and reference model.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `double`
+
+        - `Optional<LearningRateMultiplier> learningRateMultiplier`
+
+          Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `double`
+
+        - `Optional<NEpochs> nEpochs`
+
+          The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+    - `Optional<ReinforcementMethod> reinforcement`
+
+      Configuration for the reinforcement fine-tuning method.
+
+      - `Grader grader`
+
+        The grader used for the fine-tuning job.
+
+        - `class StringCheckGrader:`
+
+          A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+          - `String input`
+
+            The input text. This may include template strings.
+
+          - `String name`
+
+            The name of the grader.
+
+          - `Operation operation`
+
+            The string check operation to perform. One of `eq`, `ne`, `like`, or `ilike`.
+
+            - `EQ("eq")`
+
+            - `NE("ne")`
+
+            - `LIKE("like")`
+
+            - `ILIKE("ilike")`
+
+          - `String reference`
+
+            The reference text. This may include template strings.
+
+          - `JsonValue; type "string_check"constant`
+
+            The object type, which is always `string_check`.
+
+            - `STRING_CHECK("string_check")`
+
+        - `class TextSimilarityGrader:`
+
+          A TextSimilarityGrader object which grades text based on similarity metrics.
+
+          - `EvaluationMetric evaluationMetric`
+
+            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("cosine")`
+
+            - `FUZZY_MATCH("fuzzy_match")`
+
+            - `BLEU("bleu")`
+
+            - `GLEU("gleu")`
+
+            - `METEOR("meteor")`
+
+            - `ROUGE_1("rouge_1")`
+
+            - `ROUGE_2("rouge_2")`
+
+            - `ROUGE_3("rouge_3")`
+
+            - `ROUGE_4("rouge_4")`
+
+            - `ROUGE_5("rouge_5")`
+
+            - `ROUGE_L("rouge_l")`
+
+          - `String input`
+
+            The text being graded.
+
+          - `String name`
+
+            The name of the grader.
+
+          - `String reference`
+
+            The text being graded against.
+
+          - `JsonValue; type "text_similarity"constant`
+
+            The type of grader.
+
+            - `TEXT_SIMILARITY("text_similarity")`
+
+        - `class PythonGrader:`
+
+          A PythonGrader object that runs a python script on the input.
+
+          - `String name`
+
+            The name of the grader.
+
+          - `String source`
+
+            The source code of the python script.
+
+          - `JsonValue; type "python"constant`
+
+            The object type, which is always `python`.
+
+            - `PYTHON("python")`
+
+          - `Optional<String> imageTag`
+
+            The image tag to use for the python script.
+
+        - `class ScoreModelGrader:`
+
+          A ScoreModelGrader object that uses a model to assign a score to the input.
+
+          - `List<Input> input`
+
+            The input messages evaluated by the grader. Supports text, output text, input image, and input audio content blocks, and may include template strings.
+
+            - `Content content`
+
+              Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items.
+
+              - `String`
+
+              - `class ResponseInputText:`
+
+                A text input to the model.
+
+                - `String text`
+
+                  The text input to the model.
+
+                - `JsonValue; type "input_text"constant`
+
+                  The type of the input item. Always `input_text`.
+
+                  - `INPUT_TEXT("input_text")`
+
+                - `Optional<PromptCacheBreakpoint> promptCacheBreakpoint`
+
+                  Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's `prompt_cache_options.ttl`; the boundary is not rounded to a token block.
+
+                  - `JsonValue; mode "explicit"constant`
+
+                    The breakpoint mode. Always `explicit`.
+
+                    - `EXPLICIT("explicit")`
+
+              - `class OutputText:`
+
+                A text output from the model.
+
+                - `String text`
+
+                  The text output from the model.
+
+                - `JsonValue; type "output_text"constant`
+
+                  The type of the output text. Always `output_text`.
+
+                  - `OUTPUT_TEXT("output_text")`
+
+              - `class InputImage:`
+
+                An image input block used within EvalItem content arrays.
+
+                - `String imageUrl`
+
+                  The URL of the image input.
+
+                - `JsonValue; type "input_image"constant`
+
+                  The type of the image input. Always `input_image`.
+
+                  - `INPUT_IMAGE("input_image")`
+
+                - `Optional<String> detail`
+
+                  The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+              - `class ResponseInputAudio:`
+
+                An audio input to the model.
+
+                - `InputAudio inputAudio`
+
+                  - `String data`
+
+                    Base64-encoded audio data.
+
+                  - `Format format`
+
+                    The format of the audio data. Currently supported formats are `mp3` and
+                    `wav`.
+
+                    - `MP3("mp3")`
+
+                    - `WAV("wav")`
+
+                - `JsonValue; type "input_audio"constant`
+
+                  The type of the input item. Always `input_audio`.
+
+                  - `INPUT_AUDIO("input_audio")`
+
+              - `List<EvalContentItem>`
+
+                - `String`
+
+                - `class ResponseInputText:`
+
+                  A text input to the model.
+
+                - `OutputText`
+
+                  - `String text`
+
+                    The text output from the model.
+
+                  - `JsonValue; type "output_text"constant`
+
+                    The type of the output text. Always `output_text`.
+
+                    - `OUTPUT_TEXT("output_text")`
+
+                - `InputImage`
+
+                  - `String imageUrl`
+
+                    The URL of the image input.
+
+                  - `JsonValue; type "input_image"constant`
+
+                    The type of the image input. Always `input_image`.
+
+                    - `INPUT_IMAGE("input_image")`
+
+                  - `Optional<String> detail`
+
+                    The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+                - `class ResponseInputAudio:`
+
+                  An audio input to the model.
+
+            - `Role role`
+
+              The role of the message input. One of `user`, `assistant`, `system`, or
+              `developer`.
+
+              - `USER("user")`
+
+              - `ASSISTANT("assistant")`
+
+              - `SYSTEM("system")`
+
+              - `DEVELOPER("developer")`
+
+            - `Optional<Type> type`
+
+              The type of the message input. Always `message`.
+
+              - `MESSAGE("message")`
+
+          - `String model`
+
+            The model to use for the evaluation.
+
+          - `String name`
+
+            The name of the grader.
+
+          - `JsonValue; type "score_model"constant`
+
+            The object type, which is always `score_model`.
+
+            - `SCORE_MODEL("score_model")`
+
+          - `Optional<List<Double>> range`
+
+            The range of the score. Defaults to `[0, 1]`.
+
+          - `Optional<SamplingParams> samplingParams`
+
+            The sampling parameters for the model.
+
+            - `Optional<Long> maxCompletionsTokens`
+
+              The maximum number of tokens the grader model may generate in its response.
+
+            - `Optional<ReasoningEffort> reasoningEffort`
+
+              Constrains effort on reasoning for reasoning models. Currently supported
+              values are `none`, `minimal`, `low`, `medium`, `high`, `xhigh`, and `max`.
+              Reducing reasoning effort can result in faster responses and fewer tokens
+              used on reasoning in a response. Not all reasoning models support every
+              value. See the
+              [reasoning guide](https://platform.openai.com/docs/guides/reasoning)
+              for model-specific support.
+
+              - `NONE("none")`
+
+              - `MINIMAL("minimal")`
+
+              - `LOW("low")`
+
+              - `MEDIUM("medium")`
+
+              - `HIGH("high")`
+
+              - `XHIGH("xhigh")`
+
+              - `MAX("max")`
+
+            - `Optional<Long> seed`
+
+              A seed value to initialize the randomness, during sampling.
+
+            - `Optional<Double> temperature`
+
+              A higher temperature increases randomness in the outputs.
+
+            - `Optional<Double> topP`
+
+              An alternative to temperature for nucleus sampling; 1.0 includes all tokens.
+
+        - `class MultiGrader:`
+
+          A MultiGrader object combines the output of multiple graders to produce a single score.
+
+          - `String calculateOutput`
+
+            A formula to calculate the output based on grader results.
+
+          - `Graders graders`
+
+            A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+            - `class StringCheckGrader:`
+
+              A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+            - `class TextSimilarityGrader:`
+
+              A TextSimilarityGrader object which grades text based on similarity metrics.
+
+            - `class PythonGrader:`
+
+              A PythonGrader object that runs a python script on the input.
+
+            - `class ScoreModelGrader:`
+
+              A ScoreModelGrader object that uses a model to assign a score to the input.
+
+            - `class LabelModelGrader:`
+
+              A LabelModelGrader object which uses a model to assign labels to each item
+              in the evaluation.
+
+              - `List<Input> input`
+
+                - `Content content`
+
+                  Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items.
+
+                  - `String`
+
+                  - `class ResponseInputText:`
+
+                    A text input to the model.
+
+                  - `class OutputText:`
+
+                    A text output from the model.
+
+                    - `String text`
+
+                      The text output from the model.
+
+                    - `JsonValue; type "output_text"constant`
+
+                      The type of the output text. Always `output_text`.
+
+                      - `OUTPUT_TEXT("output_text")`
+
+                  - `class InputImage:`
+
+                    An image input block used within EvalItem content arrays.
+
+                    - `String imageUrl`
+
+                      The URL of the image input.
+
+                    - `JsonValue; type "input_image"constant`
+
+                      The type of the image input. Always `input_image`.
+
+                      - `INPUT_IMAGE("input_image")`
+
+                    - `Optional<String> detail`
+
+                      The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+                  - `class ResponseInputAudio:`
+
+                    An audio input to the model.
+
+                  - `List<EvalContentItem>`
+
+                    - `String`
+
+                    - `class ResponseInputText:`
+
+                      A text input to the model.
+
+                    - `OutputText`
+
+                    - `InputImage`
+
+                    - `class ResponseInputAudio:`
+
+                      An audio input to the model.
+
+                - `Role role`
+
+                  The role of the message input. One of `user`, `assistant`, `system`, or
+                  `developer`.
+
+                  - `USER("user")`
+
+                  - `ASSISTANT("assistant")`
+
+                  - `SYSTEM("system")`
+
+                  - `DEVELOPER("developer")`
+
+                - `Optional<Type> type`
+
+                  The type of the message input. Always `message`.
+
+                  - `MESSAGE("message")`
+
+              - `List<String> labels`
+
+                The labels to assign to each item in the evaluation.
+
+              - `String model`
+
+                The model to use for the evaluation. Must support structured outputs.
+
+              - `String name`
+
+                The name of the grader.
+
+              - `List<String> passingLabels`
+
+                The labels that indicate a passing result. Must be a subset of labels.
+
+              - `JsonValue; type "label_model"constant`
+
+                The object type, which is always `label_model`.
+
+                - `LABEL_MODEL("label_model")`
+
+          - `String name`
+
+            The name of the grader.
+
+          - `JsonValue; type "multi"constant`
+
+            The object type, which is always `multi`.
+
+            - `MULTI("multi")`
+
+      - `Optional<ReinforcementHyperparameters> hyperparameters`
+
+        The hyperparameters used for the reinforcement fine-tuning job.
+
+        - `Optional<BatchSize> batchSize`
+
+          Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+        - `Optional<ComputeMultiplier> computeMultiplier`
+
+          Multiplier on amount of compute used for exploring search space during training.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `double`
+
+        - `Optional<EvalInterval> evalInterval`
+
+          The number of training steps between evaluation runs.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+        - `Optional<EvalSamples> evalSamples`
+
+          Number of evaluation samples to generate per training step.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+        - `Optional<LearningRateMultiplier> learningRateMultiplier`
+
+          Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `double`
+
+        - `Optional<NEpochs> nEpochs`
+
+          The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+        - `Optional<ReasoningEffort> reasoningEffort`
+
+          Level of reasoning effort.
+
+          - `DEFAULT("default")`
+
+          - `LOW("low")`
+
+          - `MEDIUM("medium")`
+
+          - `HIGH("high")`
+
+    - `Optional<SupervisedMethod> supervised`
+
+      Configuration for the supervised fine-tuning method.
+
+      - `Optional<SupervisedHyperparameters> hyperparameters`
+
+        The hyperparameters used for the fine-tuning job.
+
+        - `Optional<BatchSize> batchSize`
+
+          Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+        - `Optional<LearningRateMultiplier> learningRateMultiplier`
+
+          Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `double`
+
+        - `Optional<NEpochs> nEpochs`
+
+          The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+### Example
+
+```java
+package com.openai.example;
+
+import com.openai.client.OpenAIClient;
+import com.openai.client.okhttp.OpenAIOkHttpClient;
+import com.openai.models.finetuning.jobs.JobListPage;
+import com.openai.models.finetuning.jobs.JobListParams;
+
+public final class Main {
+    private Main() {}
+
+    public static void main(String[] args) {
+        OpenAIClient client = OpenAIOkHttpClient.fromEnv();
+
+        JobListPage page = client.fineTuning().jobs().list();
+    }
+}
+```
+
+#### 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
+
+`FineTuningJob fineTuning().jobs().retrieve(JobRetrieveParamsparams = JobRetrieveParams.none(), RequestOptionsrequestOptions = RequestOptions.none())`
+
+**get** `/fine_tuning/jobs/{fine_tuning_job_id}`
+
+Retrieve fine-tuning job
+
+### Parameters
+
+- `JobRetrieveParams params`
+
+  - `Optional<String> fineTuningJobId`
+
+### Returns
+
+- `class FineTuningJob:`
+
+  The `fine_tuning.job` object represents a fine-tuning job that has been created through the API.
+
+  - `String id`
+
+    The object identifier, which can be referenced in the API endpoints.
+
+  - `long createdAt`
+
+    The Unix timestamp (in seconds) for when the fine-tuning job was created.
+
+  - `Optional<Error> error`
+
+    For fine-tuning jobs that have `failed`, this will contain more information on the cause of the failure.
+
+    - `String code`
+
+      A machine-readable error code.
+
+    - `String message`
+
+      A human-readable error message.
+
+    - `Optional<String> param`
+
+      The parameter that was invalid, usually `training_file` or `validation_file`. This field will be null if the failure was not parameter-specific.
+
+  - `Optional<String> fineTunedModel`
+
+    The name of the fine-tuned model that is being created. The value will be null if the fine-tuning job is still running.
+
+  - `Optional<Long> finishedAt`
+
+    The Unix timestamp (in seconds) for when the fine-tuning job was finished. The value will be null if the fine-tuning job is still running.
+
+  - `Hyperparameters hyperparameters`
+
+    The hyperparameters used for the fine-tuning job. This value will only be returned when running `supervised` jobs.
+
+    - `Optional<BatchSize> batchSize`
+
+      Number of examples in each batch. A larger batch size means that model parameters
+      are updated less frequently, but with lower variance.
+
+      - `JsonValue;`
+
+        - `AUTO("auto")`
+
+      - `long`
+
+    - `Optional<LearningRateMultiplier> learningRateMultiplier`
+
+      Scaling factor for the learning rate. A smaller learning rate may be useful to avoid
+      overfitting.
+
+      - `JsonValue;`
+
+        - `AUTO("auto")`
+
+      - `double`
+
+    - `Optional<NEpochs> nEpochs`
+
+      The number of epochs to train the model for. An epoch refers to one full cycle
+      through the training dataset.
+
+      - `JsonValue;`
+
+        - `AUTO("auto")`
+
+      - `long`
+
+  - `String model`
+
+    The base model that is being fine-tuned.
+
+  - `JsonValue; object_ "fine_tuning.job"constant`
+
+    The object type, which is always "fine_tuning.job".
+
+    - `FINE_TUNING_JOB("fine_tuning.job")`
+
+  - `String organizationId`
+
+    The organization that owns the fine-tuning job.
+
+  - `List<String> resultFiles`
+
+    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).
+
+  - `long seed`
+
+    The seed used for the fine-tuning job.
+
+  - `Status status`
+
+    The current status of the fine-tuning job, which can be either `validating_files`, `queued`, `running`, `succeeded`, `failed`, or `cancelled`.
+
+    - `VALIDATING_FILES("validating_files")`
+
+    - `QUEUED("queued")`
+
+    - `RUNNING("running")`
+
+    - `SUCCEEDED("succeeded")`
+
+    - `FAILED("failed")`
+
+    - `CANCELLED("cancelled")`
+
+  - `Optional<Long> trainedTokens`
+
+    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.
+
+  - `String trainingFile`
+
+    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).
+
+  - `Optional<String> validationFile`
+
+    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).
+
+  - `Optional<Long> estimatedFinish`
+
+    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.
+
+  - `Optional<List<FineTuningJobWandbIntegrationObject>> integrations`
+
+    A list of integrations to enable for this fine-tuning job.
+
+    - `JsonValue; type "wandb"constant`
+
+      The type of the integration being enabled for the fine-tuning job
+
+      - `WANDB("wandb")`
+
+    - `FineTuningJobWandbIntegration wandb`
+
+      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.
+
+      - `String project`
+
+        The name of the project that the new run will be created under.
+
+      - `Optional<String> entity`
+
+        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.
+
+      - `Optional<String> name`
+
+        A display name to set for the run. If not set, we will use the Job ID as the name.
+
+      - `Optional<List<String>> tags`
+
+        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}".
+
+  - `Optional<Metadata> metadata`
+
+    Set of 16 key-value pairs that can be attached to an object. This can be
+    useful for storing additional information about the object in a structured
+    format, and querying for objects via API or the dashboard.
+
+    Keys are strings with a maximum length of 64 characters. Values are strings
+    with a maximum length of 512 characters.
+
+  - `Optional<Method> method`
+
+    The method used for fine-tuning.
+
+    - `Type type`
+
+      The type of method. Is either `supervised`, `dpo`, or `reinforcement`.
+
+      - `SUPERVISED("supervised")`
+
+      - `DPO("dpo")`
+
+      - `REINFORCEMENT("reinforcement")`
+
+    - `Optional<DpoMethod> dpo`
+
+      Configuration for the DPO fine-tuning method.
+
+      - `Optional<DpoHyperparameters> hyperparameters`
+
+        The hyperparameters used for the DPO fine-tuning job.
+
+        - `Optional<BatchSize> batchSize`
+
+          Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+        - `Optional<Beta> beta`
+
+          The beta value for the DPO method. A higher beta value will increase the weight of the penalty between the policy and reference model.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `double`
+
+        - `Optional<LearningRateMultiplier> learningRateMultiplier`
+
+          Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `double`
+
+        - `Optional<NEpochs> nEpochs`
+
+          The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+    - `Optional<ReinforcementMethod> reinforcement`
+
+      Configuration for the reinforcement fine-tuning method.
+
+      - `Grader grader`
+
+        The grader used for the fine-tuning job.
+
+        - `class StringCheckGrader:`
+
+          A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+          - `String input`
+
+            The input text. This may include template strings.
+
+          - `String name`
+
+            The name of the grader.
+
+          - `Operation operation`
+
+            The string check operation to perform. One of `eq`, `ne`, `like`, or `ilike`.
+
+            - `EQ("eq")`
+
+            - `NE("ne")`
+
+            - `LIKE("like")`
+
+            - `ILIKE("ilike")`
+
+          - `String reference`
+
+            The reference text. This may include template strings.
+
+          - `JsonValue; type "string_check"constant`
+
+            The object type, which is always `string_check`.
+
+            - `STRING_CHECK("string_check")`
+
+        - `class TextSimilarityGrader:`
+
+          A TextSimilarityGrader object which grades text based on similarity metrics.
+
+          - `EvaluationMetric evaluationMetric`
+
+            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("cosine")`
+
+            - `FUZZY_MATCH("fuzzy_match")`
+
+            - `BLEU("bleu")`
+
+            - `GLEU("gleu")`
+
+            - `METEOR("meteor")`
+
+            - `ROUGE_1("rouge_1")`
+
+            - `ROUGE_2("rouge_2")`
+
+            - `ROUGE_3("rouge_3")`
+
+            - `ROUGE_4("rouge_4")`
+
+            - `ROUGE_5("rouge_5")`
+
+            - `ROUGE_L("rouge_l")`
+
+          - `String input`
+
+            The text being graded.
+
+          - `String name`
+
+            The name of the grader.
+
+          - `String reference`
+
+            The text being graded against.
+
+          - `JsonValue; type "text_similarity"constant`
+
+            The type of grader.
+
+            - `TEXT_SIMILARITY("text_similarity")`
+
+        - `class PythonGrader:`
+
+          A PythonGrader object that runs a python script on the input.
+
+          - `String name`
+
+            The name of the grader.
+
+          - `String source`
+
+            The source code of the python script.
+
+          - `JsonValue; type "python"constant`
+
+            The object type, which is always `python`.
+
+            - `PYTHON("python")`
+
+          - `Optional<String> imageTag`
+
+            The image tag to use for the python script.
+
+        - `class ScoreModelGrader:`
+
+          A ScoreModelGrader object that uses a model to assign a score to the input.
+
+          - `List<Input> input`
+
+            The input messages evaluated by the grader. Supports text, output text, input image, and input audio content blocks, and may include template strings.
+
+            - `Content content`
+
+              Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items.
+
+              - `String`
+
+              - `class ResponseInputText:`
+
+                A text input to the model.
+
+                - `String text`
+
+                  The text input to the model.
+
+                - `JsonValue; type "input_text"constant`
+
+                  The type of the input item. Always `input_text`.
+
+                  - `INPUT_TEXT("input_text")`
+
+                - `Optional<PromptCacheBreakpoint> promptCacheBreakpoint`
+
+                  Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's `prompt_cache_options.ttl`; the boundary is not rounded to a token block.
+
+                  - `JsonValue; mode "explicit"constant`
+
+                    The breakpoint mode. Always `explicit`.
+
+                    - `EXPLICIT("explicit")`
+
+              - `class OutputText:`
+
+                A text output from the model.
+
+                - `String text`
+
+                  The text output from the model.
+
+                - `JsonValue; type "output_text"constant`
+
+                  The type of the output text. Always `output_text`.
+
+                  - `OUTPUT_TEXT("output_text")`
+
+              - `class InputImage:`
+
+                An image input block used within EvalItem content arrays.
+
+                - `String imageUrl`
+
+                  The URL of the image input.
+
+                - `JsonValue; type "input_image"constant`
+
+                  The type of the image input. Always `input_image`.
+
+                  - `INPUT_IMAGE("input_image")`
+
+                - `Optional<String> detail`
+
+                  The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+              - `class ResponseInputAudio:`
+
+                An audio input to the model.
+
+                - `InputAudio inputAudio`
+
+                  - `String data`
+
+                    Base64-encoded audio data.
+
+                  - `Format format`
+
+                    The format of the audio data. Currently supported formats are `mp3` and
+                    `wav`.
+
+                    - `MP3("mp3")`
+
+                    - `WAV("wav")`
+
+                - `JsonValue; type "input_audio"constant`
+
+                  The type of the input item. Always `input_audio`.
+
+                  - `INPUT_AUDIO("input_audio")`
+
+              - `List<EvalContentItem>`
+
+                - `String`
+
+                - `class ResponseInputText:`
+
+                  A text input to the model.
+
+                - `OutputText`
+
+                  - `String text`
+
+                    The text output from the model.
+
+                  - `JsonValue; type "output_text"constant`
+
+                    The type of the output text. Always `output_text`.
+
+                    - `OUTPUT_TEXT("output_text")`
+
+                - `InputImage`
+
+                  - `String imageUrl`
+
+                    The URL of the image input.
+
+                  - `JsonValue; type "input_image"constant`
+
+                    The type of the image input. Always `input_image`.
+
+                    - `INPUT_IMAGE("input_image")`
+
+                  - `Optional<String> detail`
+
+                    The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+                - `class ResponseInputAudio:`
+
+                  An audio input to the model.
+
+            - `Role role`
+
+              The role of the message input. One of `user`, `assistant`, `system`, or
+              `developer`.
+
+              - `USER("user")`
+
+              - `ASSISTANT("assistant")`
+
+              - `SYSTEM("system")`
+
+              - `DEVELOPER("developer")`
+
+            - `Optional<Type> type`
+
+              The type of the message input. Always `message`.
+
+              - `MESSAGE("message")`
+
+          - `String model`
+
+            The model to use for the evaluation.
+
+          - `String name`
+
+            The name of the grader.
+
+          - `JsonValue; type "score_model"constant`
+
+            The object type, which is always `score_model`.
+
+            - `SCORE_MODEL("score_model")`
+
+          - `Optional<List<Double>> range`
+
+            The range of the score. Defaults to `[0, 1]`.
+
+          - `Optional<SamplingParams> samplingParams`
+
+            The sampling parameters for the model.
+
+            - `Optional<Long> maxCompletionsTokens`
+
+              The maximum number of tokens the grader model may generate in its response.
+
+            - `Optional<ReasoningEffort> reasoningEffort`
+
+              Constrains effort on reasoning for reasoning models. Currently supported
+              values are `none`, `minimal`, `low`, `medium`, `high`, `xhigh`, and `max`.
+              Reducing reasoning effort can result in faster responses and fewer tokens
+              used on reasoning in a response. Not all reasoning models support every
+              value. See the
+              [reasoning guide](https://platform.openai.com/docs/guides/reasoning)
+              for model-specific support.
+
+              - `NONE("none")`
+
+              - `MINIMAL("minimal")`
+
+              - `LOW("low")`
+
+              - `MEDIUM("medium")`
+
+              - `HIGH("high")`
+
+              - `XHIGH("xhigh")`
+
+              - `MAX("max")`
+
+            - `Optional<Long> seed`
+
+              A seed value to initialize the randomness, during sampling.
+
+            - `Optional<Double> temperature`
+
+              A higher temperature increases randomness in the outputs.
+
+            - `Optional<Double> topP`
+
+              An alternative to temperature for nucleus sampling; 1.0 includes all tokens.
+
+        - `class MultiGrader:`
+
+          A MultiGrader object combines the output of multiple graders to produce a single score.
+
+          - `String calculateOutput`
+
+            A formula to calculate the output based on grader results.
+
+          - `Graders graders`
+
+            A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+            - `class StringCheckGrader:`
+
+              A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+            - `class TextSimilarityGrader:`
+
+              A TextSimilarityGrader object which grades text based on similarity metrics.
+
+            - `class PythonGrader:`
+
+              A PythonGrader object that runs a python script on the input.
+
+            - `class ScoreModelGrader:`
+
+              A ScoreModelGrader object that uses a model to assign a score to the input.
+
+            - `class LabelModelGrader:`
+
+              A LabelModelGrader object which uses a model to assign labels to each item
+              in the evaluation.
+
+              - `List<Input> input`
+
+                - `Content content`
+
+                  Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items.
+
+                  - `String`
+
+                  - `class ResponseInputText:`
+
+                    A text input to the model.
+
+                  - `class OutputText:`
+
+                    A text output from the model.
+
+                    - `String text`
+
+                      The text output from the model.
+
+                    - `JsonValue; type "output_text"constant`
+
+                      The type of the output text. Always `output_text`.
+
+                      - `OUTPUT_TEXT("output_text")`
+
+                  - `class InputImage:`
+
+                    An image input block used within EvalItem content arrays.
+
+                    - `String imageUrl`
+
+                      The URL of the image input.
+
+                    - `JsonValue; type "input_image"constant`
+
+                      The type of the image input. Always `input_image`.
+
+                      - `INPUT_IMAGE("input_image")`
+
+                    - `Optional<String> detail`
+
+                      The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+                  - `class ResponseInputAudio:`
+
+                    An audio input to the model.
+
+                  - `List<EvalContentItem>`
+
+                    - `String`
+
+                    - `class ResponseInputText:`
+
+                      A text input to the model.
+
+                    - `OutputText`
+
+                    - `InputImage`
+
+                    - `class ResponseInputAudio:`
+
+                      An audio input to the model.
+
+                - `Role role`
+
+                  The role of the message input. One of `user`, `assistant`, `system`, or
+                  `developer`.
+
+                  - `USER("user")`
+
+                  - `ASSISTANT("assistant")`
+
+                  - `SYSTEM("system")`
+
+                  - `DEVELOPER("developer")`
+
+                - `Optional<Type> type`
+
+                  The type of the message input. Always `message`.
+
+                  - `MESSAGE("message")`
+
+              - `List<String> labels`
+
+                The labels to assign to each item in the evaluation.
+
+              - `String model`
+
+                The model to use for the evaluation. Must support structured outputs.
+
+              - `String name`
+
+                The name of the grader.
+
+              - `List<String> passingLabels`
+
+                The labels that indicate a passing result. Must be a subset of labels.
+
+              - `JsonValue; type "label_model"constant`
+
+                The object type, which is always `label_model`.
+
+                - `LABEL_MODEL("label_model")`
+
+          - `String name`
+
+            The name of the grader.
+
+          - `JsonValue; type "multi"constant`
+
+            The object type, which is always `multi`.
+
+            - `MULTI("multi")`
+
+      - `Optional<ReinforcementHyperparameters> hyperparameters`
+
+        The hyperparameters used for the reinforcement fine-tuning job.
+
+        - `Optional<BatchSize> batchSize`
+
+          Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+        - `Optional<ComputeMultiplier> computeMultiplier`
+
+          Multiplier on amount of compute used for exploring search space during training.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `double`
+
+        - `Optional<EvalInterval> evalInterval`
+
+          The number of training steps between evaluation runs.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+        - `Optional<EvalSamples> evalSamples`
+
+          Number of evaluation samples to generate per training step.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+        - `Optional<LearningRateMultiplier> learningRateMultiplier`
+
+          Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `double`
+
+        - `Optional<NEpochs> nEpochs`
+
+          The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+        - `Optional<ReasoningEffort> reasoningEffort`
+
+          Level of reasoning effort.
+
+          - `DEFAULT("default")`
+
+          - `LOW("low")`
+
+          - `MEDIUM("medium")`
+
+          - `HIGH("high")`
+
+    - `Optional<SupervisedMethod> supervised`
+
+      Configuration for the supervised fine-tuning method.
+
+      - `Optional<SupervisedHyperparameters> hyperparameters`
+
+        The hyperparameters used for the fine-tuning job.
+
+        - `Optional<BatchSize> batchSize`
+
+          Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+        - `Optional<LearningRateMultiplier> learningRateMultiplier`
+
+          Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `double`
+
+        - `Optional<NEpochs> nEpochs`
+
+          The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+### Example
+
+```java
+package com.openai.example;
+
+import com.openai.client.OpenAIClient;
+import com.openai.client.okhttp.OpenAIOkHttpClient;
+import com.openai.models.finetuning.jobs.FineTuningJob;
+import com.openai.models.finetuning.jobs.JobRetrieveParams;
+
+public final class Main {
+    private Main() {}
+
+    public static void main(String[] args) {
+        OpenAIClient client = OpenAIOkHttpClient.fromEnv();
+
+        FineTuningJob fineTuningJob = client.fineTuning().jobs().retrieve("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
+
+`JobListEventsPage fineTuning().jobs().listEvents(JobListEventsParamsparams = JobListEventsParams.none(), RequestOptionsrequestOptions = RequestOptions.none())`
+
+**get** `/fine_tuning/jobs/{fine_tuning_job_id}/events`
+
+List fine-tuning events
+
+### Parameters
+
+- `JobListEventsParams params`
+
+  - `Optional<String> fineTuningJobId`
+
+  - `Optional<String> after`
+
+    Identifier for the last event from the previous pagination request.
+
+  - `Optional<Long> limit`
+
+    Number of events to retrieve.
+
+### Returns
+
+- `class FineTuningJobEvent:`
+
+  Fine-tuning job event object
+
+  - `String id`
+
+    The object identifier.
+
+  - `long createdAt`
+
+    The Unix timestamp (in seconds) for when the fine-tuning job was created.
+
+  - `Level level`
+
+    The log level of the event.
+
+    - `INFO("info")`
+
+    - `WARN("warn")`
+
+    - `ERROR("error")`
+
+  - `String message`
+
+    The message of the event.
+
+  - `JsonValue; object_ "fine_tuning.job.event"constant`
+
+    The object type, which is always "fine_tuning.job.event".
+
+    - `FINE_TUNING_JOB_EVENT("fine_tuning.job.event")`
+
+  - `Optional<JsonValue> data`
+
+    The data associated with the event.
+
+  - `Optional<Type> type`
+
+    The type of event.
+
+    - `MESSAGE("message")`
+
+    - `METRICS("metrics")`
+
+### Example
+
+```java
+package com.openai.example;
+
+import com.openai.client.OpenAIClient;
+import com.openai.client.okhttp.OpenAIOkHttpClient;
+import com.openai.models.finetuning.jobs.JobListEventsPage;
+import com.openai.models.finetuning.jobs.JobListEventsParams;
+
+public final class Main {
+    private Main() {}
+
+    public static void main(String[] args) {
+        OpenAIClient client = OpenAIOkHttpClient.fromEnv();
+
+        JobListEventsPage page = client.fineTuning().jobs().listEvents("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
+
+`FineTuningJob fineTuning().jobs().cancel(JobCancelParamsparams = JobCancelParams.none(), RequestOptionsrequestOptions = RequestOptions.none())`
+
+**post** `/fine_tuning/jobs/{fine_tuning_job_id}/cancel`
+
+Cancel fine-tuning
+
+### Parameters
+
+- `JobCancelParams params`
+
+  - `Optional<String> fineTuningJobId`
+
+### Returns
+
+- `class FineTuningJob:`
+
+  The `fine_tuning.job` object represents a fine-tuning job that has been created through the API.
+
+  - `String id`
+
+    The object identifier, which can be referenced in the API endpoints.
+
+  - `long createdAt`
+
+    The Unix timestamp (in seconds) for when the fine-tuning job was created.
+
+  - `Optional<Error> error`
+
+    For fine-tuning jobs that have `failed`, this will contain more information on the cause of the failure.
+
+    - `String code`
+
+      A machine-readable error code.
+
+    - `String message`
+
+      A human-readable error message.
+
+    - `Optional<String> param`
+
+      The parameter that was invalid, usually `training_file` or `validation_file`. This field will be null if the failure was not parameter-specific.
+
+  - `Optional<String> fineTunedModel`
+
+    The name of the fine-tuned model that is being created. The value will be null if the fine-tuning job is still running.
+
+  - `Optional<Long> finishedAt`
+
+    The Unix timestamp (in seconds) for when the fine-tuning job was finished. The value will be null if the fine-tuning job is still running.
+
+  - `Hyperparameters hyperparameters`
+
+    The hyperparameters used for the fine-tuning job. This value will only be returned when running `supervised` jobs.
+
+    - `Optional<BatchSize> batchSize`
+
+      Number of examples in each batch. A larger batch size means that model parameters
+      are updated less frequently, but with lower variance.
+
+      - `JsonValue;`
+
+        - `AUTO("auto")`
+
+      - `long`
+
+    - `Optional<LearningRateMultiplier> learningRateMultiplier`
+
+      Scaling factor for the learning rate. A smaller learning rate may be useful to avoid
+      overfitting.
+
+      - `JsonValue;`
+
+        - `AUTO("auto")`
+
+      - `double`
+
+    - `Optional<NEpochs> nEpochs`
+
+      The number of epochs to train the model for. An epoch refers to one full cycle
+      through the training dataset.
+
+      - `JsonValue;`
+
+        - `AUTO("auto")`
+
+      - `long`
+
+  - `String model`
+
+    The base model that is being fine-tuned.
+
+  - `JsonValue; object_ "fine_tuning.job"constant`
+
+    The object type, which is always "fine_tuning.job".
+
+    - `FINE_TUNING_JOB("fine_tuning.job")`
+
+  - `String organizationId`
+
+    The organization that owns the fine-tuning job.
+
+  - `List<String> resultFiles`
+
+    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).
+
+  - `long seed`
+
+    The seed used for the fine-tuning job.
+
+  - `Status status`
+
+    The current status of the fine-tuning job, which can be either `validating_files`, `queued`, `running`, `succeeded`, `failed`, or `cancelled`.
+
+    - `VALIDATING_FILES("validating_files")`
+
+    - `QUEUED("queued")`
+
+    - `RUNNING("running")`
+
+    - `SUCCEEDED("succeeded")`
+
+    - `FAILED("failed")`
+
+    - `CANCELLED("cancelled")`
+
+  - `Optional<Long> trainedTokens`
+
+    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.
+
+  - `String trainingFile`
+
+    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).
+
+  - `Optional<String> validationFile`
+
+    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).
+
+  - `Optional<Long> estimatedFinish`
+
+    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.
+
+  - `Optional<List<FineTuningJobWandbIntegrationObject>> integrations`
+
+    A list of integrations to enable for this fine-tuning job.
+
+    - `JsonValue; type "wandb"constant`
+
+      The type of the integration being enabled for the fine-tuning job
+
+      - `WANDB("wandb")`
+
+    - `FineTuningJobWandbIntegration wandb`
+
+      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.
+
+      - `String project`
+
+        The name of the project that the new run will be created under.
+
+      - `Optional<String> entity`
+
+        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.
+
+      - `Optional<String> name`
+
+        A display name to set for the run. If not set, we will use the Job ID as the name.
+
+      - `Optional<List<String>> tags`
+
+        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}".
+
+  - `Optional<Metadata> metadata`
+
+    Set of 16 key-value pairs that can be attached to an object. This can be
+    useful for storing additional information about the object in a structured
+    format, and querying for objects via API or the dashboard.
+
+    Keys are strings with a maximum length of 64 characters. Values are strings
+    with a maximum length of 512 characters.
+
+  - `Optional<Method> method`
+
+    The method used for fine-tuning.
+
+    - `Type type`
+
+      The type of method. Is either `supervised`, `dpo`, or `reinforcement`.
+
+      - `SUPERVISED("supervised")`
+
+      - `DPO("dpo")`
+
+      - `REINFORCEMENT("reinforcement")`
+
+    - `Optional<DpoMethod> dpo`
+
+      Configuration for the DPO fine-tuning method.
+
+      - `Optional<DpoHyperparameters> hyperparameters`
+
+        The hyperparameters used for the DPO fine-tuning job.
+
+        - `Optional<BatchSize> batchSize`
+
+          Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+        - `Optional<Beta> beta`
+
+          The beta value for the DPO method. A higher beta value will increase the weight of the penalty between the policy and reference model.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `double`
+
+        - `Optional<LearningRateMultiplier> learningRateMultiplier`
+
+          Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `double`
+
+        - `Optional<NEpochs> nEpochs`
+
+          The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+    - `Optional<ReinforcementMethod> reinforcement`
+
+      Configuration for the reinforcement fine-tuning method.
+
+      - `Grader grader`
+
+        The grader used for the fine-tuning job.
+
+        - `class StringCheckGrader:`
+
+          A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+          - `String input`
+
+            The input text. This may include template strings.
+
+          - `String name`
+
+            The name of the grader.
+
+          - `Operation operation`
+
+            The string check operation to perform. One of `eq`, `ne`, `like`, or `ilike`.
+
+            - `EQ("eq")`
+
+            - `NE("ne")`
+
+            - `LIKE("like")`
+
+            - `ILIKE("ilike")`
+
+          - `String reference`
+
+            The reference text. This may include template strings.
+
+          - `JsonValue; type "string_check"constant`
+
+            The object type, which is always `string_check`.
+
+            - `STRING_CHECK("string_check")`
+
+        - `class TextSimilarityGrader:`
+
+          A TextSimilarityGrader object which grades text based on similarity metrics.
+
+          - `EvaluationMetric evaluationMetric`
+
+            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("cosine")`
+
+            - `FUZZY_MATCH("fuzzy_match")`
+
+            - `BLEU("bleu")`
+
+            - `GLEU("gleu")`
+
+            - `METEOR("meteor")`
+
+            - `ROUGE_1("rouge_1")`
+
+            - `ROUGE_2("rouge_2")`
+
+            - `ROUGE_3("rouge_3")`
+
+            - `ROUGE_4("rouge_4")`
+
+            - `ROUGE_5("rouge_5")`
+
+            - `ROUGE_L("rouge_l")`
+
+          - `String input`
+
+            The text being graded.
+
+          - `String name`
+
+            The name of the grader.
+
+          - `String reference`
+
+            The text being graded against.
+
+          - `JsonValue; type "text_similarity"constant`
+
+            The type of grader.
+
+            - `TEXT_SIMILARITY("text_similarity")`
+
+        - `class PythonGrader:`
+
+          A PythonGrader object that runs a python script on the input.
+
+          - `String name`
+
+            The name of the grader.
+
+          - `String source`
+
+            The source code of the python script.
+
+          - `JsonValue; type "python"constant`
+
+            The object type, which is always `python`.
+
+            - `PYTHON("python")`
+
+          - `Optional<String> imageTag`
+
+            The image tag to use for the python script.
+
+        - `class ScoreModelGrader:`
+
+          A ScoreModelGrader object that uses a model to assign a score to the input.
+
+          - `List<Input> input`
+
+            The input messages evaluated by the grader. Supports text, output text, input image, and input audio content blocks, and may include template strings.
+
+            - `Content content`
+
+              Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items.
+
+              - `String`
+
+              - `class ResponseInputText:`
+
+                A text input to the model.
+
+                - `String text`
+
+                  The text input to the model.
+
+                - `JsonValue; type "input_text"constant`
+
+                  The type of the input item. Always `input_text`.
+
+                  - `INPUT_TEXT("input_text")`
+
+                - `Optional<PromptCacheBreakpoint> promptCacheBreakpoint`
+
+                  Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's `prompt_cache_options.ttl`; the boundary is not rounded to a token block.
+
+                  - `JsonValue; mode "explicit"constant`
+
+                    The breakpoint mode. Always `explicit`.
+
+                    - `EXPLICIT("explicit")`
+
+              - `class OutputText:`
+
+                A text output from the model.
+
+                - `String text`
+
+                  The text output from the model.
+
+                - `JsonValue; type "output_text"constant`
+
+                  The type of the output text. Always `output_text`.
+
+                  - `OUTPUT_TEXT("output_text")`
+
+              - `class InputImage:`
+
+                An image input block used within EvalItem content arrays.
+
+                - `String imageUrl`
+
+                  The URL of the image input.
+
+                - `JsonValue; type "input_image"constant`
+
+                  The type of the image input. Always `input_image`.
+
+                  - `INPUT_IMAGE("input_image")`
+
+                - `Optional<String> detail`
+
+                  The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+              - `class ResponseInputAudio:`
+
+                An audio input to the model.
+
+                - `InputAudio inputAudio`
+
+                  - `String data`
+
+                    Base64-encoded audio data.
+
+                  - `Format format`
+
+                    The format of the audio data. Currently supported formats are `mp3` and
+                    `wav`.
+
+                    - `MP3("mp3")`
+
+                    - `WAV("wav")`
+
+                - `JsonValue; type "input_audio"constant`
+
+                  The type of the input item. Always `input_audio`.
+
+                  - `INPUT_AUDIO("input_audio")`
+
+              - `List<EvalContentItem>`
+
+                - `String`
+
+                - `class ResponseInputText:`
+
+                  A text input to the model.
+
+                - `OutputText`
+
+                  - `String text`
+
+                    The text output from the model.
+
+                  - `JsonValue; type "output_text"constant`
+
+                    The type of the output text. Always `output_text`.
+
+                    - `OUTPUT_TEXT("output_text")`
+
+                - `InputImage`
+
+                  - `String imageUrl`
+
+                    The URL of the image input.
+
+                  - `JsonValue; type "input_image"constant`
+
+                    The type of the image input. Always `input_image`.
+
+                    - `INPUT_IMAGE("input_image")`
+
+                  - `Optional<String> detail`
+
+                    The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+                - `class ResponseInputAudio:`
+
+                  An audio input to the model.
+
+            - `Role role`
+
+              The role of the message input. One of `user`, `assistant`, `system`, or
+              `developer`.
+
+              - `USER("user")`
+
+              - `ASSISTANT("assistant")`
+
+              - `SYSTEM("system")`
+
+              - `DEVELOPER("developer")`
+
+            - `Optional<Type> type`
+
+              The type of the message input. Always `message`.
+
+              - `MESSAGE("message")`
+
+          - `String model`
+
+            The model to use for the evaluation.
+
+          - `String name`
+
+            The name of the grader.
+
+          - `JsonValue; type "score_model"constant`
+
+            The object type, which is always `score_model`.
+
+            - `SCORE_MODEL("score_model")`
+
+          - `Optional<List<Double>> range`
+
+            The range of the score. Defaults to `[0, 1]`.
+
+          - `Optional<SamplingParams> samplingParams`
+
+            The sampling parameters for the model.
+
+            - `Optional<Long> maxCompletionsTokens`
+
+              The maximum number of tokens the grader model may generate in its response.
+
+            - `Optional<ReasoningEffort> reasoningEffort`
+
+              Constrains effort on reasoning for reasoning models. Currently supported
+              values are `none`, `minimal`, `low`, `medium`, `high`, `xhigh`, and `max`.
+              Reducing reasoning effort can result in faster responses and fewer tokens
+              used on reasoning in a response. Not all reasoning models support every
+              value. See the
+              [reasoning guide](https://platform.openai.com/docs/guides/reasoning)
+              for model-specific support.
+
+              - `NONE("none")`
+
+              - `MINIMAL("minimal")`
+
+              - `LOW("low")`
+
+              - `MEDIUM("medium")`
+
+              - `HIGH("high")`
+
+              - `XHIGH("xhigh")`
+
+              - `MAX("max")`
+
+            - `Optional<Long> seed`
+
+              A seed value to initialize the randomness, during sampling.
+
+            - `Optional<Double> temperature`
+
+              A higher temperature increases randomness in the outputs.
+
+            - `Optional<Double> topP`
+
+              An alternative to temperature for nucleus sampling; 1.0 includes all tokens.
+
+        - `class MultiGrader:`
+
+          A MultiGrader object combines the output of multiple graders to produce a single score.
+
+          - `String calculateOutput`
+
+            A formula to calculate the output based on grader results.
+
+          - `Graders graders`
+
+            A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+            - `class StringCheckGrader:`
+
+              A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+            - `class TextSimilarityGrader:`
+
+              A TextSimilarityGrader object which grades text based on similarity metrics.
+
+            - `class PythonGrader:`
+
+              A PythonGrader object that runs a python script on the input.
+
+            - `class ScoreModelGrader:`
+
+              A ScoreModelGrader object that uses a model to assign a score to the input.
+
+            - `class LabelModelGrader:`
+
+              A LabelModelGrader object which uses a model to assign labels to each item
+              in the evaluation.
+
+              - `List<Input> input`
+
+                - `Content content`
+
+                  Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items.
+
+                  - `String`
+
+                  - `class ResponseInputText:`
+
+                    A text input to the model.
+
+                  - `class OutputText:`
+
+                    A text output from the model.
+
+                    - `String text`
+
+                      The text output from the model.
+
+                    - `JsonValue; type "output_text"constant`
+
+                      The type of the output text. Always `output_text`.
+
+                      - `OUTPUT_TEXT("output_text")`
+
+                  - `class InputImage:`
+
+                    An image input block used within EvalItem content arrays.
+
+                    - `String imageUrl`
+
+                      The URL of the image input.
+
+                    - `JsonValue; type "input_image"constant`
+
+                      The type of the image input. Always `input_image`.
+
+                      - `INPUT_IMAGE("input_image")`
+
+                    - `Optional<String> detail`
+
+                      The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+                  - `class ResponseInputAudio:`
+
+                    An audio input to the model.
+
+                  - `List<EvalContentItem>`
+
+                    - `String`
+
+                    - `class ResponseInputText:`
+
+                      A text input to the model.
+
+                    - `OutputText`
+
+                    - `InputImage`
+
+                    - `class ResponseInputAudio:`
+
+                      An audio input to the model.
+
+                - `Role role`
+
+                  The role of the message input. One of `user`, `assistant`, `system`, or
+                  `developer`.
+
+                  - `USER("user")`
+
+                  - `ASSISTANT("assistant")`
+
+                  - `SYSTEM("system")`
+
+                  - `DEVELOPER("developer")`
+
+                - `Optional<Type> type`
+
+                  The type of the message input. Always `message`.
+
+                  - `MESSAGE("message")`
+
+              - `List<String> labels`
+
+                The labels to assign to each item in the evaluation.
+
+              - `String model`
+
+                The model to use for the evaluation. Must support structured outputs.
+
+              - `String name`
+
+                The name of the grader.
+
+              - `List<String> passingLabels`
+
+                The labels that indicate a passing result. Must be a subset of labels.
+
+              - `JsonValue; type "label_model"constant`
+
+                The object type, which is always `label_model`.
+
+                - `LABEL_MODEL("label_model")`
+
+          - `String name`
+
+            The name of the grader.
+
+          - `JsonValue; type "multi"constant`
+
+            The object type, which is always `multi`.
+
+            - `MULTI("multi")`
+
+      - `Optional<ReinforcementHyperparameters> hyperparameters`
+
+        The hyperparameters used for the reinforcement fine-tuning job.
+
+        - `Optional<BatchSize> batchSize`
+
+          Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+        - `Optional<ComputeMultiplier> computeMultiplier`
+
+          Multiplier on amount of compute used for exploring search space during training.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `double`
+
+        - `Optional<EvalInterval> evalInterval`
+
+          The number of training steps between evaluation runs.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+        - `Optional<EvalSamples> evalSamples`
+
+          Number of evaluation samples to generate per training step.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+        - `Optional<LearningRateMultiplier> learningRateMultiplier`
+
+          Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `double`
+
+        - `Optional<NEpochs> nEpochs`
+
+          The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+        - `Optional<ReasoningEffort> reasoningEffort`
+
+          Level of reasoning effort.
+
+          - `DEFAULT("default")`
+
+          - `LOW("low")`
+
+          - `MEDIUM("medium")`
+
+          - `HIGH("high")`
+
+    - `Optional<SupervisedMethod> supervised`
+
+      Configuration for the supervised fine-tuning method.
+
+      - `Optional<SupervisedHyperparameters> hyperparameters`
+
+        The hyperparameters used for the fine-tuning job.
+
+        - `Optional<BatchSize> batchSize`
+
+          Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+        - `Optional<LearningRateMultiplier> learningRateMultiplier`
+
+          Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `double`
+
+        - `Optional<NEpochs> nEpochs`
+
+          The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+### Example
+
+```java
+package com.openai.example;
+
+import com.openai.client.OpenAIClient;
+import com.openai.client.okhttp.OpenAIOkHttpClient;
+import com.openai.models.finetuning.jobs.FineTuningJob;
+import com.openai.models.finetuning.jobs.JobCancelParams;
+
+public final class Main {
+    private Main() {}
+
+    public static void main(String[] args) {
+        OpenAIClient client = OpenAIOkHttpClient.fromEnv();
+
+        FineTuningJob fineTuningJob = client.fineTuning().jobs().cancel("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
+
+`FineTuningJob fineTuning().jobs().pause(JobPauseParamsparams = JobPauseParams.none(), RequestOptionsrequestOptions = RequestOptions.none())`
+
+**post** `/fine_tuning/jobs/{fine_tuning_job_id}/pause`
+
+Pause fine-tuning
+
+### Parameters
+
+- `JobPauseParams params`
+
+  - `Optional<String> fineTuningJobId`
+
+### Returns
+
+- `class FineTuningJob:`
+
+  The `fine_tuning.job` object represents a fine-tuning job that has been created through the API.
+
+  - `String id`
+
+    The object identifier, which can be referenced in the API endpoints.
+
+  - `long createdAt`
+
+    The Unix timestamp (in seconds) for when the fine-tuning job was created.
+
+  - `Optional<Error> error`
+
+    For fine-tuning jobs that have `failed`, this will contain more information on the cause of the failure.
+
+    - `String code`
+
+      A machine-readable error code.
+
+    - `String message`
+
+      A human-readable error message.
+
+    - `Optional<String> param`
+
+      The parameter that was invalid, usually `training_file` or `validation_file`. This field will be null if the failure was not parameter-specific.
+
+  - `Optional<String> fineTunedModel`
+
+    The name of the fine-tuned model that is being created. The value will be null if the fine-tuning job is still running.
+
+  - `Optional<Long> finishedAt`
+
+    The Unix timestamp (in seconds) for when the fine-tuning job was finished. The value will be null if the fine-tuning job is still running.
+
+  - `Hyperparameters hyperparameters`
+
+    The hyperparameters used for the fine-tuning job. This value will only be returned when running `supervised` jobs.
+
+    - `Optional<BatchSize> batchSize`
+
+      Number of examples in each batch. A larger batch size means that model parameters
+      are updated less frequently, but with lower variance.
+
+      - `JsonValue;`
+
+        - `AUTO("auto")`
+
+      - `long`
+
+    - `Optional<LearningRateMultiplier> learningRateMultiplier`
+
+      Scaling factor for the learning rate. A smaller learning rate may be useful to avoid
+      overfitting.
+
+      - `JsonValue;`
+
+        - `AUTO("auto")`
+
+      - `double`
+
+    - `Optional<NEpochs> nEpochs`
+
+      The number of epochs to train the model for. An epoch refers to one full cycle
+      through the training dataset.
+
+      - `JsonValue;`
+
+        - `AUTO("auto")`
+
+      - `long`
+
+  - `String model`
+
+    The base model that is being fine-tuned.
+
+  - `JsonValue; object_ "fine_tuning.job"constant`
+
+    The object type, which is always "fine_tuning.job".
+
+    - `FINE_TUNING_JOB("fine_tuning.job")`
+
+  - `String organizationId`
+
+    The organization that owns the fine-tuning job.
+
+  - `List<String> resultFiles`
+
+    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).
+
+  - `long seed`
+
+    The seed used for the fine-tuning job.
+
+  - `Status status`
+
+    The current status of the fine-tuning job, which can be either `validating_files`, `queued`, `running`, `succeeded`, `failed`, or `cancelled`.
+
+    - `VALIDATING_FILES("validating_files")`
+
+    - `QUEUED("queued")`
+
+    - `RUNNING("running")`
+
+    - `SUCCEEDED("succeeded")`
+
+    - `FAILED("failed")`
+
+    - `CANCELLED("cancelled")`
+
+  - `Optional<Long> trainedTokens`
+
+    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.
+
+  - `String trainingFile`
+
+    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).
+
+  - `Optional<String> validationFile`
+
+    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).
+
+  - `Optional<Long> estimatedFinish`
+
+    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.
+
+  - `Optional<List<FineTuningJobWandbIntegrationObject>> integrations`
+
+    A list of integrations to enable for this fine-tuning job.
+
+    - `JsonValue; type "wandb"constant`
+
+      The type of the integration being enabled for the fine-tuning job
+
+      - `WANDB("wandb")`
+
+    - `FineTuningJobWandbIntegration wandb`
+
+      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.
+
+      - `String project`
+
+        The name of the project that the new run will be created under.
+
+      - `Optional<String> entity`
+
+        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.
+
+      - `Optional<String> name`
+
+        A display name to set for the run. If not set, we will use the Job ID as the name.
+
+      - `Optional<List<String>> tags`
+
+        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}".
+
+  - `Optional<Metadata> metadata`
+
+    Set of 16 key-value pairs that can be attached to an object. This can be
+    useful for storing additional information about the object in a structured
+    format, and querying for objects via API or the dashboard.
+
+    Keys are strings with a maximum length of 64 characters. Values are strings
+    with a maximum length of 512 characters.
+
+  - `Optional<Method> method`
+
+    The method used for fine-tuning.
+
+    - `Type type`
+
+      The type of method. Is either `supervised`, `dpo`, or `reinforcement`.
+
+      - `SUPERVISED("supervised")`
+
+      - `DPO("dpo")`
+
+      - `REINFORCEMENT("reinforcement")`
+
+    - `Optional<DpoMethod> dpo`
+
+      Configuration for the DPO fine-tuning method.
+
+      - `Optional<DpoHyperparameters> hyperparameters`
+
+        The hyperparameters used for the DPO fine-tuning job.
+
+        - `Optional<BatchSize> batchSize`
+
+          Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+        - `Optional<Beta> beta`
+
+          The beta value for the DPO method. A higher beta value will increase the weight of the penalty between the policy and reference model.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `double`
+
+        - `Optional<LearningRateMultiplier> learningRateMultiplier`
+
+          Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `double`
+
+        - `Optional<NEpochs> nEpochs`
+
+          The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+    - `Optional<ReinforcementMethod> reinforcement`
+
+      Configuration for the reinforcement fine-tuning method.
+
+      - `Grader grader`
+
+        The grader used for the fine-tuning job.
+
+        - `class StringCheckGrader:`
+
+          A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+          - `String input`
+
+            The input text. This may include template strings.
+
+          - `String name`
+
+            The name of the grader.
+
+          - `Operation operation`
+
+            The string check operation to perform. One of `eq`, `ne`, `like`, or `ilike`.
+
+            - `EQ("eq")`
+
+            - `NE("ne")`
+
+            - `LIKE("like")`
+
+            - `ILIKE("ilike")`
+
+          - `String reference`
+
+            The reference text. This may include template strings.
+
+          - `JsonValue; type "string_check"constant`
+
+            The object type, which is always `string_check`.
+
+            - `STRING_CHECK("string_check")`
+
+        - `class TextSimilarityGrader:`
+
+          A TextSimilarityGrader object which grades text based on similarity metrics.
+
+          - `EvaluationMetric evaluationMetric`
+
+            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("cosine")`
+
+            - `FUZZY_MATCH("fuzzy_match")`
+
+            - `BLEU("bleu")`
+
+            - `GLEU("gleu")`
+
+            - `METEOR("meteor")`
+
+            - `ROUGE_1("rouge_1")`
+
+            - `ROUGE_2("rouge_2")`
+
+            - `ROUGE_3("rouge_3")`
+
+            - `ROUGE_4("rouge_4")`
+
+            - `ROUGE_5("rouge_5")`
+
+            - `ROUGE_L("rouge_l")`
+
+          - `String input`
+
+            The text being graded.
+
+          - `String name`
+
+            The name of the grader.
+
+          - `String reference`
+
+            The text being graded against.
+
+          - `JsonValue; type "text_similarity"constant`
+
+            The type of grader.
+
+            - `TEXT_SIMILARITY("text_similarity")`
+
+        - `class PythonGrader:`
+
+          A PythonGrader object that runs a python script on the input.
+
+          - `String name`
+
+            The name of the grader.
+
+          - `String source`
+
+            The source code of the python script.
+
+          - `JsonValue; type "python"constant`
+
+            The object type, which is always `python`.
+
+            - `PYTHON("python")`
+
+          - `Optional<String> imageTag`
+
+            The image tag to use for the python script.
+
+        - `class ScoreModelGrader:`
+
+          A ScoreModelGrader object that uses a model to assign a score to the input.
+
+          - `List<Input> input`
+
+            The input messages evaluated by the grader. Supports text, output text, input image, and input audio content blocks, and may include template strings.
+
+            - `Content content`
+
+              Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items.
+
+              - `String`
+
+              - `class ResponseInputText:`
+
+                A text input to the model.
+
+                - `String text`
+
+                  The text input to the model.
+
+                - `JsonValue; type "input_text"constant`
+
+                  The type of the input item. Always `input_text`.
+
+                  - `INPUT_TEXT("input_text")`
+
+                - `Optional<PromptCacheBreakpoint> promptCacheBreakpoint`
+
+                  Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's `prompt_cache_options.ttl`; the boundary is not rounded to a token block.
+
+                  - `JsonValue; mode "explicit"constant`
+
+                    The breakpoint mode. Always `explicit`.
+
+                    - `EXPLICIT("explicit")`
+
+              - `class OutputText:`
+
+                A text output from the model.
+
+                - `String text`
+
+                  The text output from the model.
+
+                - `JsonValue; type "output_text"constant`
+
+                  The type of the output text. Always `output_text`.
+
+                  - `OUTPUT_TEXT("output_text")`
+
+              - `class InputImage:`
+
+                An image input block used within EvalItem content arrays.
+
+                - `String imageUrl`
+
+                  The URL of the image input.
+
+                - `JsonValue; type "input_image"constant`
+
+                  The type of the image input. Always `input_image`.
+
+                  - `INPUT_IMAGE("input_image")`
+
+                - `Optional<String> detail`
+
+                  The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+              - `class ResponseInputAudio:`
+
+                An audio input to the model.
+
+                - `InputAudio inputAudio`
+
+                  - `String data`
+
+                    Base64-encoded audio data.
+
+                  - `Format format`
+
+                    The format of the audio data. Currently supported formats are `mp3` and
+                    `wav`.
+
+                    - `MP3("mp3")`
+
+                    - `WAV("wav")`
+
+                - `JsonValue; type "input_audio"constant`
+
+                  The type of the input item. Always `input_audio`.
+
+                  - `INPUT_AUDIO("input_audio")`
+
+              - `List<EvalContentItem>`
+
+                - `String`
+
+                - `class ResponseInputText:`
+
+                  A text input to the model.
+
+                - `OutputText`
+
+                  - `String text`
+
+                    The text output from the model.
+
+                  - `JsonValue; type "output_text"constant`
+
+                    The type of the output text. Always `output_text`.
+
+                    - `OUTPUT_TEXT("output_text")`
+
+                - `InputImage`
+
+                  - `String imageUrl`
+
+                    The URL of the image input.
+
+                  - `JsonValue; type "input_image"constant`
+
+                    The type of the image input. Always `input_image`.
+
+                    - `INPUT_IMAGE("input_image")`
+
+                  - `Optional<String> detail`
+
+                    The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+                - `class ResponseInputAudio:`
+
+                  An audio input to the model.
+
+            - `Role role`
+
+              The role of the message input. One of `user`, `assistant`, `system`, or
+              `developer`.
+
+              - `USER("user")`
+
+              - `ASSISTANT("assistant")`
+
+              - `SYSTEM("system")`
+
+              - `DEVELOPER("developer")`
+
+            - `Optional<Type> type`
+
+              The type of the message input. Always `message`.
+
+              - `MESSAGE("message")`
+
+          - `String model`
+
+            The model to use for the evaluation.
+
+          - `String name`
+
+            The name of the grader.
+
+          - `JsonValue; type "score_model"constant`
+
+            The object type, which is always `score_model`.
+
+            - `SCORE_MODEL("score_model")`
+
+          - `Optional<List<Double>> range`
+
+            The range of the score. Defaults to `[0, 1]`.
+
+          - `Optional<SamplingParams> samplingParams`
+
+            The sampling parameters for the model.
+
+            - `Optional<Long> maxCompletionsTokens`
+
+              The maximum number of tokens the grader model may generate in its response.
+
+            - `Optional<ReasoningEffort> reasoningEffort`
+
+              Constrains effort on reasoning for reasoning models. Currently supported
+              values are `none`, `minimal`, `low`, `medium`, `high`, `xhigh`, and `max`.
+              Reducing reasoning effort can result in faster responses and fewer tokens
+              used on reasoning in a response. Not all reasoning models support every
+              value. See the
+              [reasoning guide](https://platform.openai.com/docs/guides/reasoning)
+              for model-specific support.
+
+              - `NONE("none")`
+
+              - `MINIMAL("minimal")`
+
+              - `LOW("low")`
+
+              - `MEDIUM("medium")`
+
+              - `HIGH("high")`
+
+              - `XHIGH("xhigh")`
+
+              - `MAX("max")`
+
+            - `Optional<Long> seed`
+
+              A seed value to initialize the randomness, during sampling.
+
+            - `Optional<Double> temperature`
+
+              A higher temperature increases randomness in the outputs.
+
+            - `Optional<Double> topP`
+
+              An alternative to temperature for nucleus sampling; 1.0 includes all tokens.
+
+        - `class MultiGrader:`
+
+          A MultiGrader object combines the output of multiple graders to produce a single score.
+
+          - `String calculateOutput`
+
+            A formula to calculate the output based on grader results.
+
+          - `Graders graders`
+
+            A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+            - `class StringCheckGrader:`
+
+              A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+            - `class TextSimilarityGrader:`
+
+              A TextSimilarityGrader object which grades text based on similarity metrics.
+
+            - `class PythonGrader:`
+
+              A PythonGrader object that runs a python script on the input.
+
+            - `class ScoreModelGrader:`
+
+              A ScoreModelGrader object that uses a model to assign a score to the input.
+
+            - `class LabelModelGrader:`
+
+              A LabelModelGrader object which uses a model to assign labels to each item
+              in the evaluation.
+
+              - `List<Input> input`
+
+                - `Content content`
+
+                  Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items.
+
+                  - `String`
+
+                  - `class ResponseInputText:`
+
+                    A text input to the model.
+
+                  - `class OutputText:`
+
+                    A text output from the model.
+
+                    - `String text`
+
+                      The text output from the model.
+
+                    - `JsonValue; type "output_text"constant`
+
+                      The type of the output text. Always `output_text`.
+
+                      - `OUTPUT_TEXT("output_text")`
+
+                  - `class InputImage:`
+
+                    An image input block used within EvalItem content arrays.
+
+                    - `String imageUrl`
+
+                      The URL of the image input.
+
+                    - `JsonValue; type "input_image"constant`
+
+                      The type of the image input. Always `input_image`.
+
+                      - `INPUT_IMAGE("input_image")`
+
+                    - `Optional<String> detail`
+
+                      The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+                  - `class ResponseInputAudio:`
+
+                    An audio input to the model.
+
+                  - `List<EvalContentItem>`
+
+                    - `String`
+
+                    - `class ResponseInputText:`
+
+                      A text input to the model.
+
+                    - `OutputText`
+
+                    - `InputImage`
+
+                    - `class ResponseInputAudio:`
+
+                      An audio input to the model.
+
+                - `Role role`
+
+                  The role of the message input. One of `user`, `assistant`, `system`, or
+                  `developer`.
+
+                  - `USER("user")`
+
+                  - `ASSISTANT("assistant")`
+
+                  - `SYSTEM("system")`
+
+                  - `DEVELOPER("developer")`
+
+                - `Optional<Type> type`
+
+                  The type of the message input. Always `message`.
+
+                  - `MESSAGE("message")`
+
+              - `List<String> labels`
+
+                The labels to assign to each item in the evaluation.
+
+              - `String model`
+
+                The model to use for the evaluation. Must support structured outputs.
+
+              - `String name`
+
+                The name of the grader.
+
+              - `List<String> passingLabels`
+
+                The labels that indicate a passing result. Must be a subset of labels.
+
+              - `JsonValue; type "label_model"constant`
+
+                The object type, which is always `label_model`.
+
+                - `LABEL_MODEL("label_model")`
+
+          - `String name`
+
+            The name of the grader.
+
+          - `JsonValue; type "multi"constant`
+
+            The object type, which is always `multi`.
+
+            - `MULTI("multi")`
+
+      - `Optional<ReinforcementHyperparameters> hyperparameters`
+
+        The hyperparameters used for the reinforcement fine-tuning job.
+
+        - `Optional<BatchSize> batchSize`
+
+          Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+        - `Optional<ComputeMultiplier> computeMultiplier`
+
+          Multiplier on amount of compute used for exploring search space during training.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `double`
+
+        - `Optional<EvalInterval> evalInterval`
+
+          The number of training steps between evaluation runs.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+        - `Optional<EvalSamples> evalSamples`
+
+          Number of evaluation samples to generate per training step.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+        - `Optional<LearningRateMultiplier> learningRateMultiplier`
+
+          Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `double`
+
+        - `Optional<NEpochs> nEpochs`
+
+          The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+        - `Optional<ReasoningEffort> reasoningEffort`
+
+          Level of reasoning effort.
+
+          - `DEFAULT("default")`
+
+          - `LOW("low")`
+
+          - `MEDIUM("medium")`
+
+          - `HIGH("high")`
+
+    - `Optional<SupervisedMethod> supervised`
+
+      Configuration for the supervised fine-tuning method.
+
+      - `Optional<SupervisedHyperparameters> hyperparameters`
+
+        The hyperparameters used for the fine-tuning job.
+
+        - `Optional<BatchSize> batchSize`
+
+          Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+        - `Optional<LearningRateMultiplier> learningRateMultiplier`
+
+          Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `double`
+
+        - `Optional<NEpochs> nEpochs`
+
+          The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+### Example
+
+```java
+package com.openai.example;
+
+import com.openai.client.OpenAIClient;
+import com.openai.client.okhttp.OpenAIOkHttpClient;
+import com.openai.models.finetuning.jobs.FineTuningJob;
+import com.openai.models.finetuning.jobs.JobPauseParams;
+
+public final class Main {
+    private Main() {}
+
+    public static void main(String[] args) {
+        OpenAIClient client = OpenAIOkHttpClient.fromEnv();
+
+        FineTuningJob fineTuningJob = client.fineTuning().jobs().pause("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
+
+`FineTuningJob fineTuning().jobs().resume(JobResumeParamsparams = JobResumeParams.none(), RequestOptionsrequestOptions = RequestOptions.none())`
+
+**post** `/fine_tuning/jobs/{fine_tuning_job_id}/resume`
+
+Resume fine-tuning
+
+### Parameters
+
+- `JobResumeParams params`
+
+  - `Optional<String> fineTuningJobId`
+
+### Returns
+
+- `class FineTuningJob:`
+
+  The `fine_tuning.job` object represents a fine-tuning job that has been created through the API.
+
+  - `String id`
+
+    The object identifier, which can be referenced in the API endpoints.
+
+  - `long createdAt`
+
+    The Unix timestamp (in seconds) for when the fine-tuning job was created.
+
+  - `Optional<Error> error`
+
+    For fine-tuning jobs that have `failed`, this will contain more information on the cause of the failure.
+
+    - `String code`
+
+      A machine-readable error code.
+
+    - `String message`
+
+      A human-readable error message.
+
+    - `Optional<String> param`
+
+      The parameter that was invalid, usually `training_file` or `validation_file`. This field will be null if the failure was not parameter-specific.
+
+  - `Optional<String> fineTunedModel`
+
+    The name of the fine-tuned model that is being created. The value will be null if the fine-tuning job is still running.
+
+  - `Optional<Long> finishedAt`
+
+    The Unix timestamp (in seconds) for when the fine-tuning job was finished. The value will be null if the fine-tuning job is still running.
+
+  - `Hyperparameters hyperparameters`
+
+    The hyperparameters used for the fine-tuning job. This value will only be returned when running `supervised` jobs.
+
+    - `Optional<BatchSize> batchSize`
+
+      Number of examples in each batch. A larger batch size means that model parameters
+      are updated less frequently, but with lower variance.
+
+      - `JsonValue;`
+
+        - `AUTO("auto")`
+
+      - `long`
+
+    - `Optional<LearningRateMultiplier> learningRateMultiplier`
+
+      Scaling factor for the learning rate. A smaller learning rate may be useful to avoid
+      overfitting.
+
+      - `JsonValue;`
+
+        - `AUTO("auto")`
+
+      - `double`
+
+    - `Optional<NEpochs> nEpochs`
+
+      The number of epochs to train the model for. An epoch refers to one full cycle
+      through the training dataset.
+
+      - `JsonValue;`
+
+        - `AUTO("auto")`
+
+      - `long`
+
+  - `String model`
+
+    The base model that is being fine-tuned.
+
+  - `JsonValue; object_ "fine_tuning.job"constant`
+
+    The object type, which is always "fine_tuning.job".
+
+    - `FINE_TUNING_JOB("fine_tuning.job")`
+
+  - `String organizationId`
+
+    The organization that owns the fine-tuning job.
+
+  - `List<String> resultFiles`
+
+    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).
+
+  - `long seed`
+
+    The seed used for the fine-tuning job.
+
+  - `Status status`
+
+    The current status of the fine-tuning job, which can be either `validating_files`, `queued`, `running`, `succeeded`, `failed`, or `cancelled`.
+
+    - `VALIDATING_FILES("validating_files")`
+
+    - `QUEUED("queued")`
+
+    - `RUNNING("running")`
+
+    - `SUCCEEDED("succeeded")`
+
+    - `FAILED("failed")`
+
+    - `CANCELLED("cancelled")`
+
+  - `Optional<Long> trainedTokens`
+
+    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.
+
+  - `String trainingFile`
+
+    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).
+
+  - `Optional<String> validationFile`
+
+    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).
+
+  - `Optional<Long> estimatedFinish`
+
+    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.
+
+  - `Optional<List<FineTuningJobWandbIntegrationObject>> integrations`
+
+    A list of integrations to enable for this fine-tuning job.
+
+    - `JsonValue; type "wandb"constant`
+
+      The type of the integration being enabled for the fine-tuning job
+
+      - `WANDB("wandb")`
+
+    - `FineTuningJobWandbIntegration wandb`
+
+      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.
+
+      - `String project`
+
+        The name of the project that the new run will be created under.
+
+      - `Optional<String> entity`
+
+        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.
+
+      - `Optional<String> name`
+
+        A display name to set for the run. If not set, we will use the Job ID as the name.
+
+      - `Optional<List<String>> tags`
+
+        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}".
+
+  - `Optional<Metadata> metadata`
+
+    Set of 16 key-value pairs that can be attached to an object. This can be
+    useful for storing additional information about the object in a structured
+    format, and querying for objects via API or the dashboard.
+
+    Keys are strings with a maximum length of 64 characters. Values are strings
+    with a maximum length of 512 characters.
+
+  - `Optional<Method> method`
+
+    The method used for fine-tuning.
+
+    - `Type type`
+
+      The type of method. Is either `supervised`, `dpo`, or `reinforcement`.
+
+      - `SUPERVISED("supervised")`
+
+      - `DPO("dpo")`
+
+      - `REINFORCEMENT("reinforcement")`
+
+    - `Optional<DpoMethod> dpo`
+
+      Configuration for the DPO fine-tuning method.
+
+      - `Optional<DpoHyperparameters> hyperparameters`
+
+        The hyperparameters used for the DPO fine-tuning job.
+
+        - `Optional<BatchSize> batchSize`
+
+          Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+        - `Optional<Beta> beta`
+
+          The beta value for the DPO method. A higher beta value will increase the weight of the penalty between the policy and reference model.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `double`
+
+        - `Optional<LearningRateMultiplier> learningRateMultiplier`
+
+          Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `double`
+
+        - `Optional<NEpochs> nEpochs`
+
+          The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+    - `Optional<ReinforcementMethod> reinforcement`
+
+      Configuration for the reinforcement fine-tuning method.
+
+      - `Grader grader`
+
+        The grader used for the fine-tuning job.
+
+        - `class StringCheckGrader:`
+
+          A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+          - `String input`
+
+            The input text. This may include template strings.
+
+          - `String name`
+
+            The name of the grader.
+
+          - `Operation operation`
+
+            The string check operation to perform. One of `eq`, `ne`, `like`, or `ilike`.
+
+            - `EQ("eq")`
+
+            - `NE("ne")`
+
+            - `LIKE("like")`
+
+            - `ILIKE("ilike")`
+
+          - `String reference`
+
+            The reference text. This may include template strings.
+
+          - `JsonValue; type "string_check"constant`
+
+            The object type, which is always `string_check`.
+
+            - `STRING_CHECK("string_check")`
+
+        - `class TextSimilarityGrader:`
+
+          A TextSimilarityGrader object which grades text based on similarity metrics.
+
+          - `EvaluationMetric evaluationMetric`
+
+            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("cosine")`
+
+            - `FUZZY_MATCH("fuzzy_match")`
+
+            - `BLEU("bleu")`
+
+            - `GLEU("gleu")`
+
+            - `METEOR("meteor")`
+
+            - `ROUGE_1("rouge_1")`
+
+            - `ROUGE_2("rouge_2")`
+
+            - `ROUGE_3("rouge_3")`
+
+            - `ROUGE_4("rouge_4")`
+
+            - `ROUGE_5("rouge_5")`
+
+            - `ROUGE_L("rouge_l")`
+
+          - `String input`
+
+            The text being graded.
+
+          - `String name`
+
+            The name of the grader.
+
+          - `String reference`
+
+            The text being graded against.
+
+          - `JsonValue; type "text_similarity"constant`
+
+            The type of grader.
+
+            - `TEXT_SIMILARITY("text_similarity")`
+
+        - `class PythonGrader:`
+
+          A PythonGrader object that runs a python script on the input.
+
+          - `String name`
+
+            The name of the grader.
+
+          - `String source`
+
+            The source code of the python script.
+
+          - `JsonValue; type "python"constant`
+
+            The object type, which is always `python`.
+
+            - `PYTHON("python")`
+
+          - `Optional<String> imageTag`
+
+            The image tag to use for the python script.
+
+        - `class ScoreModelGrader:`
+
+          A ScoreModelGrader object that uses a model to assign a score to the input.
+
+          - `List<Input> input`
+
+            The input messages evaluated by the grader. Supports text, output text, input image, and input audio content blocks, and may include template strings.
+
+            - `Content content`
+
+              Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items.
+
+              - `String`
+
+              - `class ResponseInputText:`
+
+                A text input to the model.
+
+                - `String text`
+
+                  The text input to the model.
+
+                - `JsonValue; type "input_text"constant`
+
+                  The type of the input item. Always `input_text`.
+
+                  - `INPUT_TEXT("input_text")`
+
+                - `Optional<PromptCacheBreakpoint> promptCacheBreakpoint`
+
+                  Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's `prompt_cache_options.ttl`; the boundary is not rounded to a token block.
+
+                  - `JsonValue; mode "explicit"constant`
+
+                    The breakpoint mode. Always `explicit`.
+
+                    - `EXPLICIT("explicit")`
+
+              - `class OutputText:`
+
+                A text output from the model.
+
+                - `String text`
+
+                  The text output from the model.
+
+                - `JsonValue; type "output_text"constant`
+
+                  The type of the output text. Always `output_text`.
+
+                  - `OUTPUT_TEXT("output_text")`
+
+              - `class InputImage:`
+
+                An image input block used within EvalItem content arrays.
+
+                - `String imageUrl`
+
+                  The URL of the image input.
+
+                - `JsonValue; type "input_image"constant`
+
+                  The type of the image input. Always `input_image`.
+
+                  - `INPUT_IMAGE("input_image")`
+
+                - `Optional<String> detail`
+
+                  The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+              - `class ResponseInputAudio:`
+
+                An audio input to the model.
+
+                - `InputAudio inputAudio`
+
+                  - `String data`
+
+                    Base64-encoded audio data.
+
+                  - `Format format`
+
+                    The format of the audio data. Currently supported formats are `mp3` and
+                    `wav`.
+
+                    - `MP3("mp3")`
+
+                    - `WAV("wav")`
+
+                - `JsonValue; type "input_audio"constant`
+
+                  The type of the input item. Always `input_audio`.
+
+                  - `INPUT_AUDIO("input_audio")`
+
+              - `List<EvalContentItem>`
+
+                - `String`
+
+                - `class ResponseInputText:`
+
+                  A text input to the model.
+
+                - `OutputText`
+
+                  - `String text`
+
+                    The text output from the model.
+
+                  - `JsonValue; type "output_text"constant`
+
+                    The type of the output text. Always `output_text`.
+
+                    - `OUTPUT_TEXT("output_text")`
+
+                - `InputImage`
+
+                  - `String imageUrl`
+
+                    The URL of the image input.
+
+                  - `JsonValue; type "input_image"constant`
+
+                    The type of the image input. Always `input_image`.
+
+                    - `INPUT_IMAGE("input_image")`
+
+                  - `Optional<String> detail`
+
+                    The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+                - `class ResponseInputAudio:`
+
+                  An audio input to the model.
+
+            - `Role role`
+
+              The role of the message input. One of `user`, `assistant`, `system`, or
+              `developer`.
+
+              - `USER("user")`
+
+              - `ASSISTANT("assistant")`
+
+              - `SYSTEM("system")`
+
+              - `DEVELOPER("developer")`
+
+            - `Optional<Type> type`
+
+              The type of the message input. Always `message`.
+
+              - `MESSAGE("message")`
+
+          - `String model`
+
+            The model to use for the evaluation.
+
+          - `String name`
+
+            The name of the grader.
+
+          - `JsonValue; type "score_model"constant`
+
+            The object type, which is always `score_model`.
+
+            - `SCORE_MODEL("score_model")`
+
+          - `Optional<List<Double>> range`
+
+            The range of the score. Defaults to `[0, 1]`.
+
+          - `Optional<SamplingParams> samplingParams`
+
+            The sampling parameters for the model.
+
+            - `Optional<Long> maxCompletionsTokens`
+
+              The maximum number of tokens the grader model may generate in its response.
+
+            - `Optional<ReasoningEffort> reasoningEffort`
+
+              Constrains effort on reasoning for reasoning models. Currently supported
+              values are `none`, `minimal`, `low`, `medium`, `high`, `xhigh`, and `max`.
+              Reducing reasoning effort can result in faster responses and fewer tokens
+              used on reasoning in a response. Not all reasoning models support every
+              value. See the
+              [reasoning guide](https://platform.openai.com/docs/guides/reasoning)
+              for model-specific support.
+
+              - `NONE("none")`
+
+              - `MINIMAL("minimal")`
+
+              - `LOW("low")`
+
+              - `MEDIUM("medium")`
+
+              - `HIGH("high")`
+
+              - `XHIGH("xhigh")`
+
+              - `MAX("max")`
+
+            - `Optional<Long> seed`
+
+              A seed value to initialize the randomness, during sampling.
+
+            - `Optional<Double> temperature`
+
+              A higher temperature increases randomness in the outputs.
+
+            - `Optional<Double> topP`
+
+              An alternative to temperature for nucleus sampling; 1.0 includes all tokens.
+
+        - `class MultiGrader:`
+
+          A MultiGrader object combines the output of multiple graders to produce a single score.
+
+          - `String calculateOutput`
+
+            A formula to calculate the output based on grader results.
+
+          - `Graders graders`
+
+            A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+            - `class StringCheckGrader:`
+
+              A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+            - `class TextSimilarityGrader:`
+
+              A TextSimilarityGrader object which grades text based on similarity metrics.
+
+            - `class PythonGrader:`
+
+              A PythonGrader object that runs a python script on the input.
+
+            - `class ScoreModelGrader:`
+
+              A ScoreModelGrader object that uses a model to assign a score to the input.
+
+            - `class LabelModelGrader:`
+
+              A LabelModelGrader object which uses a model to assign labels to each item
+              in the evaluation.
+
+              - `List<Input> input`
+
+                - `Content content`
+
+                  Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items.
+
+                  - `String`
+
+                  - `class ResponseInputText:`
+
+                    A text input to the model.
+
+                  - `class OutputText:`
+
+                    A text output from the model.
+
+                    - `String text`
+
+                      The text output from the model.
+
+                    - `JsonValue; type "output_text"constant`
+
+                      The type of the output text. Always `output_text`.
+
+                      - `OUTPUT_TEXT("output_text")`
+
+                  - `class InputImage:`
+
+                    An image input block used within EvalItem content arrays.
+
+                    - `String imageUrl`
+
+                      The URL of the image input.
+
+                    - `JsonValue; type "input_image"constant`
+
+                      The type of the image input. Always `input_image`.
+
+                      - `INPUT_IMAGE("input_image")`
+
+                    - `Optional<String> detail`
+
+                      The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+                  - `class ResponseInputAudio:`
+
+                    An audio input to the model.
+
+                  - `List<EvalContentItem>`
+
+                    - `String`
+
+                    - `class ResponseInputText:`
+
+                      A text input to the model.
+
+                    - `OutputText`
+
+                    - `InputImage`
+
+                    - `class ResponseInputAudio:`
+
+                      An audio input to the model.
+
+                - `Role role`
+
+                  The role of the message input. One of `user`, `assistant`, `system`, or
+                  `developer`.
+
+                  - `USER("user")`
+
+                  - `ASSISTANT("assistant")`
+
+                  - `SYSTEM("system")`
+
+                  - `DEVELOPER("developer")`
+
+                - `Optional<Type> type`
+
+                  The type of the message input. Always `message`.
+
+                  - `MESSAGE("message")`
+
+              - `List<String> labels`
+
+                The labels to assign to each item in the evaluation.
+
+              - `String model`
+
+                The model to use for the evaluation. Must support structured outputs.
+
+              - `String name`
+
+                The name of the grader.
+
+              - `List<String> passingLabels`
+
+                The labels that indicate a passing result. Must be a subset of labels.
+
+              - `JsonValue; type "label_model"constant`
+
+                The object type, which is always `label_model`.
+
+                - `LABEL_MODEL("label_model")`
+
+          - `String name`
+
+            The name of the grader.
+
+          - `JsonValue; type "multi"constant`
+
+            The object type, which is always `multi`.
+
+            - `MULTI("multi")`
+
+      - `Optional<ReinforcementHyperparameters> hyperparameters`
+
+        The hyperparameters used for the reinforcement fine-tuning job.
+
+        - `Optional<BatchSize> batchSize`
+
+          Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+        - `Optional<ComputeMultiplier> computeMultiplier`
+
+          Multiplier on amount of compute used for exploring search space during training.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `double`
+
+        - `Optional<EvalInterval> evalInterval`
+
+          The number of training steps between evaluation runs.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+        - `Optional<EvalSamples> evalSamples`
+
+          Number of evaluation samples to generate per training step.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+        - `Optional<LearningRateMultiplier> learningRateMultiplier`
+
+          Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `double`
+
+        - `Optional<NEpochs> nEpochs`
+
+          The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+        - `Optional<ReasoningEffort> reasoningEffort`
+
+          Level of reasoning effort.
+
+          - `DEFAULT("default")`
+
+          - `LOW("low")`
+
+          - `MEDIUM("medium")`
+
+          - `HIGH("high")`
+
+    - `Optional<SupervisedMethod> supervised`
+
+      Configuration for the supervised fine-tuning method.
+
+      - `Optional<SupervisedHyperparameters> hyperparameters`
+
+        The hyperparameters used for the fine-tuning job.
+
+        - `Optional<BatchSize> batchSize`
+
+          Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+        - `Optional<LearningRateMultiplier> learningRateMultiplier`
+
+          Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `double`
+
+        - `Optional<NEpochs> nEpochs`
+
+          The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+### Example
+
+```java
+package com.openai.example;
+
+import com.openai.client.OpenAIClient;
+import com.openai.client.okhttp.OpenAIOkHttpClient;
+import com.openai.models.finetuning.jobs.FineTuningJob;
+import com.openai.models.finetuning.jobs.JobResumeParams;
+
+public final class Main {
+    private Main() {}
+
+    public static void main(String[] args) {
+        OpenAIClient client = OpenAIOkHttpClient.fromEnv();
+
+        FineTuningJob fineTuningJob = client.fineTuning().jobs().resume("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
+
+- `class FineTuningJob:`
+
+  The `fine_tuning.job` object represents a fine-tuning job that has been created through the API.
+
+  - `String id`
+
+    The object identifier, which can be referenced in the API endpoints.
+
+  - `long createdAt`
+
+    The Unix timestamp (in seconds) for when the fine-tuning job was created.
+
+  - `Optional<Error> error`
+
+    For fine-tuning jobs that have `failed`, this will contain more information on the cause of the failure.
+
+    - `String code`
+
+      A machine-readable error code.
+
+    - `String message`
+
+      A human-readable error message.
+
+    - `Optional<String> param`
+
+      The parameter that was invalid, usually `training_file` or `validation_file`. This field will be null if the failure was not parameter-specific.
+
+  - `Optional<String> fineTunedModel`
+
+    The name of the fine-tuned model that is being created. The value will be null if the fine-tuning job is still running.
+
+  - `Optional<Long> finishedAt`
+
+    The Unix timestamp (in seconds) for when the fine-tuning job was finished. The value will be null if the fine-tuning job is still running.
+
+  - `Hyperparameters hyperparameters`
+
+    The hyperparameters used for the fine-tuning job. This value will only be returned when running `supervised` jobs.
+
+    - `Optional<BatchSize> batchSize`
+
+      Number of examples in each batch. A larger batch size means that model parameters
+      are updated less frequently, but with lower variance.
+
+      - `JsonValue;`
+
+        - `AUTO("auto")`
+
+      - `long`
+
+    - `Optional<LearningRateMultiplier> learningRateMultiplier`
+
+      Scaling factor for the learning rate. A smaller learning rate may be useful to avoid
+      overfitting.
+
+      - `JsonValue;`
+
+        - `AUTO("auto")`
+
+      - `double`
+
+    - `Optional<NEpochs> nEpochs`
+
+      The number of epochs to train the model for. An epoch refers to one full cycle
+      through the training dataset.
+
+      - `JsonValue;`
+
+        - `AUTO("auto")`
+
+      - `long`
+
+  - `String model`
+
+    The base model that is being fine-tuned.
+
+  - `JsonValue; object_ "fine_tuning.job"constant`
+
+    The object type, which is always "fine_tuning.job".
+
+    - `FINE_TUNING_JOB("fine_tuning.job")`
+
+  - `String organizationId`
+
+    The organization that owns the fine-tuning job.
+
+  - `List<String> resultFiles`
+
+    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).
+
+  - `long seed`
+
+    The seed used for the fine-tuning job.
+
+  - `Status status`
+
+    The current status of the fine-tuning job, which can be either `validating_files`, `queued`, `running`, `succeeded`, `failed`, or `cancelled`.
+
+    - `VALIDATING_FILES("validating_files")`
+
+    - `QUEUED("queued")`
+
+    - `RUNNING("running")`
+
+    - `SUCCEEDED("succeeded")`
+
+    - `FAILED("failed")`
+
+    - `CANCELLED("cancelled")`
+
+  - `Optional<Long> trainedTokens`
+
+    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.
+
+  - `String trainingFile`
+
+    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).
+
+  - `Optional<String> validationFile`
+
+    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).
+
+  - `Optional<Long> estimatedFinish`
+
+    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.
+
+  - `Optional<List<FineTuningJobWandbIntegrationObject>> integrations`
+
+    A list of integrations to enable for this fine-tuning job.
+
+    - `JsonValue; type "wandb"constant`
+
+      The type of the integration being enabled for the fine-tuning job
+
+      - `WANDB("wandb")`
+
+    - `FineTuningJobWandbIntegration wandb`
+
+      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.
+
+      - `String project`
+
+        The name of the project that the new run will be created under.
+
+      - `Optional<String> entity`
+
+        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.
+
+      - `Optional<String> name`
+
+        A display name to set for the run. If not set, we will use the Job ID as the name.
+
+      - `Optional<List<String>> tags`
+
+        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}".
+
+  - `Optional<Metadata> metadata`
+
+    Set of 16 key-value pairs that can be attached to an object. This can be
+    useful for storing additional information about the object in a structured
+    format, and querying for objects via API or the dashboard.
+
+    Keys are strings with a maximum length of 64 characters. Values are strings
+    with a maximum length of 512 characters.
+
+  - `Optional<Method> method`
+
+    The method used for fine-tuning.
+
+    - `Type type`
+
+      The type of method. Is either `supervised`, `dpo`, or `reinforcement`.
+
+      - `SUPERVISED("supervised")`
+
+      - `DPO("dpo")`
+
+      - `REINFORCEMENT("reinforcement")`
+
+    - `Optional<DpoMethod> dpo`
+
+      Configuration for the DPO fine-tuning method.
+
+      - `Optional<DpoHyperparameters> hyperparameters`
+
+        The hyperparameters used for the DPO fine-tuning job.
+
+        - `Optional<BatchSize> batchSize`
+
+          Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+        - `Optional<Beta> beta`
+
+          The beta value for the DPO method. A higher beta value will increase the weight of the penalty between the policy and reference model.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `double`
+
+        - `Optional<LearningRateMultiplier> learningRateMultiplier`
+
+          Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `double`
+
+        - `Optional<NEpochs> nEpochs`
+
+          The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+    - `Optional<ReinforcementMethod> reinforcement`
+
+      Configuration for the reinforcement fine-tuning method.
+
+      - `Grader grader`
+
+        The grader used for the fine-tuning job.
+
+        - `class StringCheckGrader:`
+
+          A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+          - `String input`
+
+            The input text. This may include template strings.
+
+          - `String name`
+
+            The name of the grader.
+
+          - `Operation operation`
+
+            The string check operation to perform. One of `eq`, `ne`, `like`, or `ilike`.
+
+            - `EQ("eq")`
+
+            - `NE("ne")`
+
+            - `LIKE("like")`
+
+            - `ILIKE("ilike")`
+
+          - `String reference`
+
+            The reference text. This may include template strings.
+
+          - `JsonValue; type "string_check"constant`
+
+            The object type, which is always `string_check`.
+
+            - `STRING_CHECK("string_check")`
+
+        - `class TextSimilarityGrader:`
+
+          A TextSimilarityGrader object which grades text based on similarity metrics.
+
+          - `EvaluationMetric evaluationMetric`
+
+            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("cosine")`
+
+            - `FUZZY_MATCH("fuzzy_match")`
+
+            - `BLEU("bleu")`
+
+            - `GLEU("gleu")`
+
+            - `METEOR("meteor")`
+
+            - `ROUGE_1("rouge_1")`
+
+            - `ROUGE_2("rouge_2")`
+
+            - `ROUGE_3("rouge_3")`
+
+            - `ROUGE_4("rouge_4")`
+
+            - `ROUGE_5("rouge_5")`
+
+            - `ROUGE_L("rouge_l")`
+
+          - `String input`
+
+            The text being graded.
+
+          - `String name`
+
+            The name of the grader.
+
+          - `String reference`
+
+            The text being graded against.
+
+          - `JsonValue; type "text_similarity"constant`
+
+            The type of grader.
+
+            - `TEXT_SIMILARITY("text_similarity")`
+
+        - `class PythonGrader:`
+
+          A PythonGrader object that runs a python script on the input.
+
+          - `String name`
+
+            The name of the grader.
+
+          - `String source`
+
+            The source code of the python script.
+
+          - `JsonValue; type "python"constant`
+
+            The object type, which is always `python`.
+
+            - `PYTHON("python")`
+
+          - `Optional<String> imageTag`
+
+            The image tag to use for the python script.
+
+        - `class ScoreModelGrader:`
+
+          A ScoreModelGrader object that uses a model to assign a score to the input.
+
+          - `List<Input> input`
+
+            The input messages evaluated by the grader. Supports text, output text, input image, and input audio content blocks, and may include template strings.
+
+            - `Content content`
+
+              Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items.
+
+              - `String`
+
+              - `class ResponseInputText:`
+
+                A text input to the model.
+
+                - `String text`
+
+                  The text input to the model.
+
+                - `JsonValue; type "input_text"constant`
+
+                  The type of the input item. Always `input_text`.
+
+                  - `INPUT_TEXT("input_text")`
+
+                - `Optional<PromptCacheBreakpoint> promptCacheBreakpoint`
+
+                  Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's `prompt_cache_options.ttl`; the boundary is not rounded to a token block.
+
+                  - `JsonValue; mode "explicit"constant`
+
+                    The breakpoint mode. Always `explicit`.
+
+                    - `EXPLICIT("explicit")`
+
+              - `class OutputText:`
+
+                A text output from the model.
+
+                - `String text`
+
+                  The text output from the model.
+
+                - `JsonValue; type "output_text"constant`
+
+                  The type of the output text. Always `output_text`.
+
+                  - `OUTPUT_TEXT("output_text")`
+
+              - `class InputImage:`
+
+                An image input block used within EvalItem content arrays.
+
+                - `String imageUrl`
+
+                  The URL of the image input.
+
+                - `JsonValue; type "input_image"constant`
+
+                  The type of the image input. Always `input_image`.
+
+                  - `INPUT_IMAGE("input_image")`
+
+                - `Optional<String> detail`
+
+                  The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+              - `class ResponseInputAudio:`
+
+                An audio input to the model.
+
+                - `InputAudio inputAudio`
+
+                  - `String data`
+
+                    Base64-encoded audio data.
+
+                  - `Format format`
+
+                    The format of the audio data. Currently supported formats are `mp3` and
+                    `wav`.
+
+                    - `MP3("mp3")`
+
+                    - `WAV("wav")`
+
+                - `JsonValue; type "input_audio"constant`
+
+                  The type of the input item. Always `input_audio`.
+
+                  - `INPUT_AUDIO("input_audio")`
+
+              - `List<EvalContentItem>`
+
+                - `String`
+
+                - `class ResponseInputText:`
+
+                  A text input to the model.
+
+                - `OutputText`
+
+                  - `String text`
+
+                    The text output from the model.
+
+                  - `JsonValue; type "output_text"constant`
+
+                    The type of the output text. Always `output_text`.
+
+                    - `OUTPUT_TEXT("output_text")`
+
+                - `InputImage`
+
+                  - `String imageUrl`
+
+                    The URL of the image input.
+
+                  - `JsonValue; type "input_image"constant`
+
+                    The type of the image input. Always `input_image`.
+
+                    - `INPUT_IMAGE("input_image")`
+
+                  - `Optional<String> detail`
+
+                    The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+                - `class ResponseInputAudio:`
+
+                  An audio input to the model.
+
+            - `Role role`
+
+              The role of the message input. One of `user`, `assistant`, `system`, or
+              `developer`.
+
+              - `USER("user")`
+
+              - `ASSISTANT("assistant")`
+
+              - `SYSTEM("system")`
+
+              - `DEVELOPER("developer")`
+
+            - `Optional<Type> type`
+
+              The type of the message input. Always `message`.
+
+              - `MESSAGE("message")`
+
+          - `String model`
+
+            The model to use for the evaluation.
+
+          - `String name`
+
+            The name of the grader.
+
+          - `JsonValue; type "score_model"constant`
+
+            The object type, which is always `score_model`.
+
+            - `SCORE_MODEL("score_model")`
+
+          - `Optional<List<Double>> range`
+
+            The range of the score. Defaults to `[0, 1]`.
+
+          - `Optional<SamplingParams> samplingParams`
+
+            The sampling parameters for the model.
+
+            - `Optional<Long> maxCompletionsTokens`
+
+              The maximum number of tokens the grader model may generate in its response.
+
+            - `Optional<ReasoningEffort> reasoningEffort`
+
+              Constrains effort on reasoning for reasoning models. Currently supported
+              values are `none`, `minimal`, `low`, `medium`, `high`, `xhigh`, and `max`.
+              Reducing reasoning effort can result in faster responses and fewer tokens
+              used on reasoning in a response. Not all reasoning models support every
+              value. See the
+              [reasoning guide](https://platform.openai.com/docs/guides/reasoning)
+              for model-specific support.
+
+              - `NONE("none")`
+
+              - `MINIMAL("minimal")`
+
+              - `LOW("low")`
+
+              - `MEDIUM("medium")`
+
+              - `HIGH("high")`
+
+              - `XHIGH("xhigh")`
+
+              - `MAX("max")`
+
+            - `Optional<Long> seed`
+
+              A seed value to initialize the randomness, during sampling.
+
+            - `Optional<Double> temperature`
+
+              A higher temperature increases randomness in the outputs.
+
+            - `Optional<Double> topP`
+
+              An alternative to temperature for nucleus sampling; 1.0 includes all tokens.
+
+        - `class MultiGrader:`
+
+          A MultiGrader object combines the output of multiple graders to produce a single score.
+
+          - `String calculateOutput`
+
+            A formula to calculate the output based on grader results.
+
+          - `Graders graders`
+
+            A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+            - `class StringCheckGrader:`
+
+              A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+            - `class TextSimilarityGrader:`
+
+              A TextSimilarityGrader object which grades text based on similarity metrics.
+
+            - `class PythonGrader:`
+
+              A PythonGrader object that runs a python script on the input.
+
+            - `class ScoreModelGrader:`
+
+              A ScoreModelGrader object that uses a model to assign a score to the input.
+
+            - `class LabelModelGrader:`
+
+              A LabelModelGrader object which uses a model to assign labels to each item
+              in the evaluation.
+
+              - `List<Input> input`
+
+                - `Content content`
+
+                  Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items.
+
+                  - `String`
+
+                  - `class ResponseInputText:`
+
+                    A text input to the model.
+
+                  - `class OutputText:`
+
+                    A text output from the model.
+
+                    - `String text`
+
+                      The text output from the model.
+
+                    - `JsonValue; type "output_text"constant`
+
+                      The type of the output text. Always `output_text`.
+
+                      - `OUTPUT_TEXT("output_text")`
+
+                  - `class InputImage:`
+
+                    An image input block used within EvalItem content arrays.
+
+                    - `String imageUrl`
+
+                      The URL of the image input.
+
+                    - `JsonValue; type "input_image"constant`
+
+                      The type of the image input. Always `input_image`.
+
+                      - `INPUT_IMAGE("input_image")`
+
+                    - `Optional<String> detail`
+
+                      The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+                  - `class ResponseInputAudio:`
+
+                    An audio input to the model.
+
+                  - `List<EvalContentItem>`
+
+                    - `String`
+
+                    - `class ResponseInputText:`
+
+                      A text input to the model.
+
+                    - `OutputText`
+
+                    - `InputImage`
+
+                    - `class ResponseInputAudio:`
+
+                      An audio input to the model.
+
+                - `Role role`
+
+                  The role of the message input. One of `user`, `assistant`, `system`, or
+                  `developer`.
+
+                  - `USER("user")`
+
+                  - `ASSISTANT("assistant")`
+
+                  - `SYSTEM("system")`
+
+                  - `DEVELOPER("developer")`
+
+                - `Optional<Type> type`
+
+                  The type of the message input. Always `message`.
+
+                  - `MESSAGE("message")`
+
+              - `List<String> labels`
+
+                The labels to assign to each item in the evaluation.
+
+              - `String model`
+
+                The model to use for the evaluation. Must support structured outputs.
+
+              - `String name`
+
+                The name of the grader.
+
+              - `List<String> passingLabels`
+
+                The labels that indicate a passing result. Must be a subset of labels.
+
+              - `JsonValue; type "label_model"constant`
+
+                The object type, which is always `label_model`.
+
+                - `LABEL_MODEL("label_model")`
+
+          - `String name`
+
+            The name of the grader.
+
+          - `JsonValue; type "multi"constant`
+
+            The object type, which is always `multi`.
+
+            - `MULTI("multi")`
+
+      - `Optional<ReinforcementHyperparameters> hyperparameters`
+
+        The hyperparameters used for the reinforcement fine-tuning job.
+
+        - `Optional<BatchSize> batchSize`
+
+          Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+        - `Optional<ComputeMultiplier> computeMultiplier`
+
+          Multiplier on amount of compute used for exploring search space during training.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `double`
+
+        - `Optional<EvalInterval> evalInterval`
+
+          The number of training steps between evaluation runs.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+        - `Optional<EvalSamples> evalSamples`
+
+          Number of evaluation samples to generate per training step.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+        - `Optional<LearningRateMultiplier> learningRateMultiplier`
+
+          Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `double`
+
+        - `Optional<NEpochs> nEpochs`
+
+          The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+        - `Optional<ReasoningEffort> reasoningEffort`
+
+          Level of reasoning effort.
+
+          - `DEFAULT("default")`
+
+          - `LOW("low")`
+
+          - `MEDIUM("medium")`
+
+          - `HIGH("high")`
+
+    - `Optional<SupervisedMethod> supervised`
+
+      Configuration for the supervised fine-tuning method.
+
+      - `Optional<SupervisedHyperparameters> hyperparameters`
+
+        The hyperparameters used for the fine-tuning job.
+
+        - `Optional<BatchSize> batchSize`
+
+          Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+        - `Optional<LearningRateMultiplier> learningRateMultiplier`
+
+          Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `double`
+
+        - `Optional<NEpochs> nEpochs`
+
+          The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
+
+          - `JsonValue;`
+
+            - `AUTO("auto")`
+
+          - `long`
+
+### Fine Tuning Job Event
+
+- `class FineTuningJobEvent:`
+
+  Fine-tuning job event object
+
+  - `String id`
+
+    The object identifier.
+
+  - `long createdAt`
+
+    The Unix timestamp (in seconds) for when the fine-tuning job was created.
+
+  - `Level level`
+
+    The log level of the event.
+
+    - `INFO("info")`
+
+    - `WARN("warn")`
+
+    - `ERROR("error")`
+
+  - `String message`
+
+    The message of the event.
+
+  - `JsonValue; object_ "fine_tuning.job.event"constant`
+
+    The object type, which is always "fine_tuning.job.event".
+
+    - `FINE_TUNING_JOB_EVENT("fine_tuning.job.event")`
+
+  - `Optional<JsonValue> data`
+
+    The data associated with the event.
+
+  - `Optional<Type> type`
+
+    The type of event.
+
+    - `MESSAGE("message")`
+
+    - `METRICS("metrics")`
+
+### Fine Tuning Job Wandb Integration
+
+- `class FineTuningJobWandbIntegration:`
+
+  The settings for your integration with Weights and Biases. This payload specifies the project that
+  metrics will be sent to. Optionally, you can set an explicit display name for your run, add tags
+  to your run, and set a default entity (team, username, etc) to be associated with your run.
+
+  - `String project`
+
+    The name of the project that the new run will be created under.
+
+  - `Optional<String> entity`
+
+    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.
+
+  - `Optional<String> name`
+
+    A display name to set for the run. If not set, we will use the Job ID as the name.
+
+  - `Optional<List<String>> tags`
+
+    A list of tags to be attached to the newly created run. These tags are passed through directly to WandB. Some
+    default tags are generated by OpenAI: "openai/finetune", "openai/{base-model}", "openai/{ftjob-abcdef}".
+
+### Fine Tuning Job Wandb Integration Object
+
+- `class FineTuningJobWandbIntegrationObject:`
+
+  - `JsonValue; type "wandb"constant`
+
+    The type of the integration being enabled for the fine-tuning job
+
+    - `WANDB("wandb")`
+
+  - `FineTuningJobWandbIntegration wandb`
+
+    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.
+
+    - `String project`
+
+      The name of the project that the new run will be created under.
+
+    - `Optional<String> entity`
+
+      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.
+
+    - `Optional<String> name`
+
+      A display name to set for the run. If not set, we will use the Job ID as the name.
+
+    - `Optional<List<String>> tags`
+
+      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
+
+`CheckpointListPage fineTuning().jobs().checkpoints().list(CheckpointListParamsparams = CheckpointListParams.none(), RequestOptionsrequestOptions = RequestOptions.none())`
+
+**get** `/fine_tuning/jobs/{fine_tuning_job_id}/checkpoints`
+
+List fine-tuning checkpoints
+
+### Parameters
+
+- `CheckpointListParams params`
+
+  - `Optional<String> fineTuningJobId`
+
+  - `Optional<String> after`
+
+    Identifier for the last checkpoint ID from the previous pagination request.
+
+  - `Optional<Long> limit`
+
+    Number of checkpoints to retrieve.
+
+### Returns
+
+- `class FineTuningJobCheckpoint:`
+
+  The `fine_tuning.job.checkpoint` object represents a model checkpoint for a fine-tuning job that is ready to use.
+
+  - `String id`
+
+    The checkpoint identifier, which can be referenced in the API endpoints.
+
+  - `long createdAt`
+
+    The Unix timestamp (in seconds) for when the checkpoint was created.
+
+  - `String fineTunedModelCheckpoint`
+
+    The name of the fine-tuned checkpoint model that is created.
+
+  - `String fineTuningJobId`
+
+    The name of the fine-tuning job that this checkpoint was created from.
+
+  - `Metrics metrics`
+
+    Metrics at the step number during the fine-tuning job.
+
+    - `Optional<Double> fullValidLoss`
+
+    - `Optional<Double> fullValidMeanTokenAccuracy`
+
+    - `Optional<Double> step`
+
+    - `Optional<Double> trainLoss`
+
+    - `Optional<Double> trainMeanTokenAccuracy`
+
+    - `Optional<Double> validLoss`
+
+    - `Optional<Double> validMeanTokenAccuracy`
+
+  - `JsonValue; object_ "fine_tuning.job.checkpoint"constant`
+
+    The object type, which is always "fine_tuning.job.checkpoint".
+
+    - `FINE_TUNING_JOB_CHECKPOINT("fine_tuning.job.checkpoint")`
+
+  - `long stepNumber`
+
+    The step number that the checkpoint was created at.
+
+### Example
+
+```java
+package com.openai.example;
+
+import com.openai.client.OpenAIClient;
+import com.openai.client.okhttp.OpenAIOkHttpClient;
+import com.openai.models.finetuning.jobs.checkpoints.CheckpointListPage;
+import com.openai.models.finetuning.jobs.checkpoints.CheckpointListParams;
+
+public final class Main {
+    private Main() {}
+
+    public static void main(String[] args) {
+        OpenAIClient client = OpenAIOkHttpClient.fromEnv();
+
+        CheckpointListPage page = client.fineTuning().jobs().checkpoints().list("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
+
+- `class FineTuningJobCheckpoint:`
+
+  The `fine_tuning.job.checkpoint` object represents a model checkpoint for a fine-tuning job that is ready to use.
+
+  - `String id`
+
+    The checkpoint identifier, which can be referenced in the API endpoints.
+
+  - `long createdAt`
+
+    The Unix timestamp (in seconds) for when the checkpoint was created.
+
+  - `String fineTunedModelCheckpoint`
+
+    The name of the fine-tuned checkpoint model that is created.
+
+  - `String fineTuningJobId`
+
+    The name of the fine-tuning job that this checkpoint was created from.
+
+  - `Metrics metrics`
+
+    Metrics at the step number during the fine-tuning job.
+
+    - `Optional<Double> fullValidLoss`
+
+    - `Optional<Double> fullValidMeanTokenAccuracy`
+
+    - `Optional<Double> step`
+
+    - `Optional<Double> trainLoss`
+
+    - `Optional<Double> trainMeanTokenAccuracy`
+
+    - `Optional<Double> validLoss`
+
+    - `Optional<Double> validMeanTokenAccuracy`
+
+  - `JsonValue; object_ "fine_tuning.job.checkpoint"constant`
+
+    The object type, which is always "fine_tuning.job.checkpoint".
+
+    - `FINE_TUNING_JOB_CHECKPOINT("fine_tuning.job.checkpoint")`
+
+  - `long stepNumber`
+
+    The step number that the checkpoint was created at.
+
+# Checkpoints
+
+# Permissions
+
+## List checkpoint permissions
+
+`PermissionRetrieveResponse fineTuning().checkpoints().permissions().retrieve(PermissionRetrieveParamsparams = PermissionRetrieveParams.none(), RequestOptionsrequestOptions = RequestOptions.none())`
+
+**get** `/fine_tuning/checkpoints/{fine_tuned_model_checkpoint}/permissions`
+
+List checkpoint permissions
+
+### Parameters
+
+- `PermissionRetrieveParams params`
+
+  - `Optional<String> fineTunedModelCheckpoint`
+
+  - `Optional<String> after`
+
+    Identifier for the last permission ID from the previous pagination request.
+
+  - `Optional<Long> limit`
+
+    Number of permissions to retrieve.
+
+  - `Optional<Order> order`
+
+    The order in which to retrieve permissions.
+
+    - `ASCENDING("ascending")`
+
+    - `DESCENDING("descending")`
+
+  - `Optional<String> projectId`
+
+    The ID of the project to get permissions for.
+
+### Returns
+
+- `class PermissionRetrieveResponse:`
+
+  - `List<Data> data`
+
+    - `String id`
+
+      The permission identifier, which can be referenced in the API endpoints.
+
+    - `long createdAt`
+
+      The Unix timestamp (in seconds) for when the permission was created.
+
+    - `JsonValue; object_ "checkpoint.permission"constant`
+
+      The object type, which is always "checkpoint.permission".
+
+      - `CHECKPOINT_PERMISSION("checkpoint.permission")`
+
+    - `String projectId`
+
+      The project identifier that the permission is for.
+
+  - `boolean hasMore`
+
+  - `JsonValue; object_ "list"constant`
+
+    - `LIST("list")`
+
+  - `Optional<String> firstId`
+
+  - `Optional<String> lastId`
+
+### Example
+
+```java
+package com.openai.example;
+
+import com.openai.client.OpenAIClient;
+import com.openai.client.okhttp.OpenAIOkHttpClient;
+import com.openai.models.finetuning.checkpoints.permissions.PermissionRetrieveParams;
+import com.openai.models.finetuning.checkpoints.permissions.PermissionRetrieveResponse;
+
+public final class Main {
+    private Main() {}
+
+    public static void main(String[] args) {
+        OpenAIClient client = OpenAIOkHttpClient.fromEnv();
+
+        PermissionRetrieveResponse permission = client.fineTuning().checkpoints().permissions().retrieve("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
+
+`PermissionListPage fineTuning().checkpoints().permissions().list(PermissionListParamsparams = PermissionListParams.none(), RequestOptionsrequestOptions = RequestOptions.none())`
+
+**get** `/fine_tuning/checkpoints/{fine_tuned_model_checkpoint}/permissions`
+
+List checkpoint permissions
+
+### Parameters
+
+- `PermissionListParams params`
+
+  - `Optional<String> fineTunedModelCheckpoint`
+
+  - `Optional<String> after`
+
+    Identifier for the last permission ID from the previous pagination request.
+
+  - `Optional<Long> limit`
+
+    Number of permissions to retrieve.
+
+  - `Optional<Order> order`
+
+    The order in which to retrieve permissions.
+
+    - `ASCENDING("ascending")`
+
+    - `DESCENDING("descending")`
+
+  - `Optional<String> projectId`
+
+    The ID of the project to get permissions for.
+
+### Returns
+
+- `class PermissionListResponse:`
+
+  The `checkpoint.permission` object represents a permission for a fine-tuned model checkpoint.
+
+  - `String id`
+
+    The permission identifier, which can be referenced in the API endpoints.
+
+  - `long createdAt`
+
+    The Unix timestamp (in seconds) for when the permission was created.
+
+  - `JsonValue; object_ "checkpoint.permission"constant`
+
+    The object type, which is always "checkpoint.permission".
+
+    - `CHECKPOINT_PERMISSION("checkpoint.permission")`
+
+  - `String projectId`
+
+    The project identifier that the permission is for.
+
+### Example
+
+```java
+package com.openai.example;
+
+import com.openai.client.OpenAIClient;
+import com.openai.client.okhttp.OpenAIOkHttpClient;
+import com.openai.models.finetuning.checkpoints.permissions.PermissionListPage;
+import com.openai.models.finetuning.checkpoints.permissions.PermissionListParams;
+
+public final class Main {
+    private Main() {}
+
+    public static void main(String[] args) {
+        OpenAIClient client = OpenAIOkHttpClient.fromEnv();
+
+        PermissionListPage page = client.fineTuning().checkpoints().permissions().list("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
+
+`PermissionCreatePage fineTuning().checkpoints().permissions().create(PermissionCreateParamsparams, RequestOptionsrequestOptions = RequestOptions.none())`
+
+**post** `/fine_tuning/checkpoints/{fine_tuned_model_checkpoint}/permissions`
+
+Create checkpoint permissions
+
+### Parameters
+
+- `PermissionCreateParams params`
+
+  - `Optional<String> fineTunedModelCheckpoint`
+
+  - `List<String> projectIds`
+
+    The project identifiers to grant access to.
+
+### Returns
+
+- `class PermissionCreateResponse:`
+
+  The `checkpoint.permission` object represents a permission for a fine-tuned model checkpoint.
+
+  - `String id`
+
+    The permission identifier, which can be referenced in the API endpoints.
+
+  - `long createdAt`
+
+    The Unix timestamp (in seconds) for when the permission was created.
+
+  - `JsonValue; object_ "checkpoint.permission"constant`
+
+    The object type, which is always "checkpoint.permission".
+
+    - `CHECKPOINT_PERMISSION("checkpoint.permission")`
+
+  - `String projectId`
+
+    The project identifier that the permission is for.
+
+### Example
+
+```java
+package com.openai.example;
+
+import com.openai.client.OpenAIClient;
+import com.openai.client.okhttp.OpenAIOkHttpClient;
+import com.openai.models.finetuning.checkpoints.permissions.PermissionCreatePage;
+import com.openai.models.finetuning.checkpoints.permissions.PermissionCreateParams;
+
+public final class Main {
+    private Main() {}
+
+    public static void main(String[] args) {
+        OpenAIClient client = OpenAIOkHttpClient.fromEnv();
+
+        PermissionCreateParams params = PermissionCreateParams.builder()
+            .fineTunedModelCheckpoint("ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd")
+            .addProjectId("string")
+            .build();
+        PermissionCreatePage page = client.fineTuning().checkpoints().permissions().create(params);
+    }
+}
+```
+
+#### 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
+
+`PermissionDeleteResponse fineTuning().checkpoints().permissions().delete(PermissionDeleteParamsparams, RequestOptionsrequestOptions = RequestOptions.none())`
+
+**delete** `/fine_tuning/checkpoints/{fine_tuned_model_checkpoint}/permissions/{permission_id}`
+
+Delete checkpoint permission
+
+### Parameters
+
+- `PermissionDeleteParams params`
+
+  - `String fineTunedModelCheckpoint`
+
+  - `Optional<String> permissionId`
+
+### Returns
+
+- `class PermissionDeleteResponse:`
+
+  - `String id`
+
+    The ID of the fine-tuned model checkpoint permission that was deleted.
+
+  - `boolean deleted`
+
+    Whether the fine-tuned model checkpoint permission was successfully deleted.
+
+  - `JsonValue; object_ "checkpoint.permission"constant`
+
+    The object type, which is always "checkpoint.permission".
+
+    - `CHECKPOINT_PERMISSION("checkpoint.permission")`
+
+### Example
+
+```java
+package com.openai.example;
+
+import com.openai.client.OpenAIClient;
+import com.openai.client.okhttp.OpenAIOkHttpClient;
+import com.openai.models.finetuning.checkpoints.permissions.PermissionDeleteParams;
+import com.openai.models.finetuning.checkpoints.permissions.PermissionDeleteResponse;
+
+public final class Main {
+    private Main() {}
+
+    public static void main(String[] args) {
+        OpenAIClient client = OpenAIOkHttpClient.fromEnv();
+
+        PermissionDeleteParams params = PermissionDeleteParams.builder()
+            .fineTunedModelCheckpoint("ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd")
+            .permissionId("cp_zc4Q7MP6XxulcVzj4MZdwsAB")
+            .build();
+        PermissionDeleteResponse permission = client.fineTuning().checkpoints().permissions().delete(params);
+    }
+}
+```
+
+#### Response
+
+```json
+{
+  "id": "id",
+  "deleted": true,
+  "object": "checkpoint.permission"
+}
+```
+
+# Alpha
+
+# Graders
+
+## Run grader
+
+`GraderRunResponse fineTuning().alpha().graders().run(GraderRunParamsparams, RequestOptionsrequestOptions = RequestOptions.none())`
+
+**post** `/fine_tuning/alpha/graders/run`
+
+Run grader
+
+### Parameters
+
+- `GraderRunParams params`
+
+  - `Grader grader`
+
+    The grader used for the fine-tuning job.
+
+    - `class StringCheckGrader:`
+
+      A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+      - `String input`
+
+        The input text. This may include template strings.
+
+      - `String name`
+
+        The name of the grader.
+
+      - `Operation operation`
+
+        The string check operation to perform. One of `eq`, `ne`, `like`, or `ilike`.
+
+        - `EQ("eq")`
+
+        - `NE("ne")`
+
+        - `LIKE("like")`
+
+        - `ILIKE("ilike")`
+
+      - `String reference`
+
+        The reference text. This may include template strings.
+
+      - `JsonValue; type "string_check"constant`
+
+        The object type, which is always `string_check`.
+
+        - `STRING_CHECK("string_check")`
+
+    - `class TextSimilarityGrader:`
+
+      A TextSimilarityGrader object which grades text based on similarity metrics.
+
+      - `EvaluationMetric evaluationMetric`
+
+        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("cosine")`
+
+        - `FUZZY_MATCH("fuzzy_match")`
+
+        - `BLEU("bleu")`
+
+        - `GLEU("gleu")`
+
+        - `METEOR("meteor")`
+
+        - `ROUGE_1("rouge_1")`
+
+        - `ROUGE_2("rouge_2")`
+
+        - `ROUGE_3("rouge_3")`
+
+        - `ROUGE_4("rouge_4")`
+
+        - `ROUGE_5("rouge_5")`
+
+        - `ROUGE_L("rouge_l")`
+
+      - `String input`
+
+        The text being graded.
+
+      - `String name`
+
+        The name of the grader.
+
+      - `String reference`
+
+        The text being graded against.
+
+      - `JsonValue; type "text_similarity"constant`
+
+        The type of grader.
+
+        - `TEXT_SIMILARITY("text_similarity")`
+
+    - `class PythonGrader:`
+
+      A PythonGrader object that runs a python script on the input.
+
+      - `String name`
+
+        The name of the grader.
+
+      - `String source`
+
+        The source code of the python script.
+
+      - `JsonValue; type "python"constant`
+
+        The object type, which is always `python`.
+
+        - `PYTHON("python")`
+
+      - `Optional<String> imageTag`
+
+        The image tag to use for the python script.
+
+    - `class ScoreModelGrader:`
+
+      A ScoreModelGrader object that uses a model to assign a score to the input.
+
+      - `List<Input> input`
+
+        The input messages evaluated by the grader. Supports text, output text, input image, and input audio content blocks, and may include template strings.
+
+        - `Content content`
+
+          Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items.
+
+          - `String`
+
+          - `class ResponseInputText:`
+
+            A text input to the model.
+
+            - `String text`
+
+              The text input to the model.
+
+            - `JsonValue; type "input_text"constant`
+
+              The type of the input item. Always `input_text`.
+
+              - `INPUT_TEXT("input_text")`
+
+            - `Optional<PromptCacheBreakpoint> promptCacheBreakpoint`
+
+              Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's `prompt_cache_options.ttl`; the boundary is not rounded to a token block.
+
+              - `JsonValue; mode "explicit"constant`
+
+                The breakpoint mode. Always `explicit`.
+
+                - `EXPLICIT("explicit")`
+
+          - `class OutputText:`
+
+            A text output from the model.
+
+            - `String text`
+
+              The text output from the model.
+
+            - `JsonValue; type "output_text"constant`
+
+              The type of the output text. Always `output_text`.
+
+              - `OUTPUT_TEXT("output_text")`
+
+          - `class InputImage:`
+
+            An image input block used within EvalItem content arrays.
+
+            - `String imageUrl`
+
+              The URL of the image input.
+
+            - `JsonValue; type "input_image"constant`
+
+              The type of the image input. Always `input_image`.
+
+              - `INPUT_IMAGE("input_image")`
+
+            - `Optional<String> detail`
+
+              The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+          - `class ResponseInputAudio:`
+
+            An audio input to the model.
+
+            - `InputAudio inputAudio`
+
+              - `String data`
+
+                Base64-encoded audio data.
+
+              - `Format format`
+
+                The format of the audio data. Currently supported formats are `mp3` and
+                `wav`.
+
+                - `MP3("mp3")`
+
+                - `WAV("wav")`
+
+            - `JsonValue; type "input_audio"constant`
+
+              The type of the input item. Always `input_audio`.
+
+              - `INPUT_AUDIO("input_audio")`
+
+          - `List<EvalContentItem>`
+
+            - `String`
+
+            - `class ResponseInputText:`
+
+              A text input to the model.
+
+            - `OutputText`
+
+              - `String text`
+
+                The text output from the model.
+
+              - `JsonValue; type "output_text"constant`
+
+                The type of the output text. Always `output_text`.
+
+                - `OUTPUT_TEXT("output_text")`
+
+            - `InputImage`
+
+              - `String imageUrl`
+
+                The URL of the image input.
+
+              - `JsonValue; type "input_image"constant`
+
+                The type of the image input. Always `input_image`.
+
+                - `INPUT_IMAGE("input_image")`
+
+              - `Optional<String> detail`
+
+                The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+            - `class ResponseInputAudio:`
+
+              An audio input to the model.
+
+        - `Role role`
+
+          The role of the message input. One of `user`, `assistant`, `system`, or
+          `developer`.
+
+          - `USER("user")`
+
+          - `ASSISTANT("assistant")`
+
+          - `SYSTEM("system")`
+
+          - `DEVELOPER("developer")`
+
+        - `Optional<Type> type`
+
+          The type of the message input. Always `message`.
+
+          - `MESSAGE("message")`
+
+      - `String model`
+
+        The model to use for the evaluation.
+
+      - `String name`
+
+        The name of the grader.
+
+      - `JsonValue; type "score_model"constant`
+
+        The object type, which is always `score_model`.
+
+        - `SCORE_MODEL("score_model")`
+
+      - `Optional<List<Double>> range`
+
+        The range of the score. Defaults to `[0, 1]`.
+
+      - `Optional<SamplingParams> samplingParams`
+
+        The sampling parameters for the model.
+
+        - `Optional<Long> maxCompletionsTokens`
+
+          The maximum number of tokens the grader model may generate in its response.
+
+        - `Optional<ReasoningEffort> reasoningEffort`
+
+          Constrains effort on reasoning for reasoning models. Currently supported
+          values are `none`, `minimal`, `low`, `medium`, `high`, `xhigh`, and `max`.
+          Reducing reasoning effort can result in faster responses and fewer tokens
+          used on reasoning in a response. Not all reasoning models support every
+          value. See the
+          [reasoning guide](https://platform.openai.com/docs/guides/reasoning)
+          for model-specific support.
+
+          - `NONE("none")`
+
+          - `MINIMAL("minimal")`
+
+          - `LOW("low")`
+
+          - `MEDIUM("medium")`
+
+          - `HIGH("high")`
+
+          - `XHIGH("xhigh")`
+
+          - `MAX("max")`
+
+        - `Optional<Long> seed`
+
+          A seed value to initialize the randomness, during sampling.
+
+        - `Optional<Double> temperature`
+
+          A higher temperature increases randomness in the outputs.
+
+        - `Optional<Double> topP`
+
+          An alternative to temperature for nucleus sampling; 1.0 includes all tokens.
+
+    - `class MultiGrader:`
+
+      A MultiGrader object combines the output of multiple graders to produce a single score.
+
+      - `String calculateOutput`
+
+        A formula to calculate the output based on grader results.
+
+      - `Graders graders`
+
+        A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+        - `class StringCheckGrader:`
+
+          A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+        - `class TextSimilarityGrader:`
+
+          A TextSimilarityGrader object which grades text based on similarity metrics.
+
+        - `class PythonGrader:`
+
+          A PythonGrader object that runs a python script on the input.
+
+        - `class ScoreModelGrader:`
+
+          A ScoreModelGrader object that uses a model to assign a score to the input.
+
+        - `class LabelModelGrader:`
+
+          A LabelModelGrader object which uses a model to assign labels to each item
+          in the evaluation.
+
+          - `List<Input> input`
+
+            - `Content content`
+
+              Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items.
+
+              - `String`
+
+              - `class ResponseInputText:`
+
+                A text input to the model.
+
+              - `class OutputText:`
+
+                A text output from the model.
+
+                - `String text`
+
+                  The text output from the model.
+
+                - `JsonValue; type "output_text"constant`
+
+                  The type of the output text. Always `output_text`.
+
+                  - `OUTPUT_TEXT("output_text")`
+
+              - `class InputImage:`
+
+                An image input block used within EvalItem content arrays.
+
+                - `String imageUrl`
+
+                  The URL of the image input.
+
+                - `JsonValue; type "input_image"constant`
+
+                  The type of the image input. Always `input_image`.
+
+                  - `INPUT_IMAGE("input_image")`
+
+                - `Optional<String> detail`
+
+                  The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+              - `class ResponseInputAudio:`
+
+                An audio input to the model.
+
+              - `List<EvalContentItem>`
+
+                - `String`
+
+                - `class ResponseInputText:`
+
+                  A text input to the model.
+
+                - `OutputText`
+
+                - `InputImage`
+
+                - `class ResponseInputAudio:`
+
+                  An audio input to the model.
+
+            - `Role role`
+
+              The role of the message input. One of `user`, `assistant`, `system`, or
+              `developer`.
+
+              - `USER("user")`
+
+              - `ASSISTANT("assistant")`
+
+              - `SYSTEM("system")`
+
+              - `DEVELOPER("developer")`
+
+            - `Optional<Type> type`
+
+              The type of the message input. Always `message`.
+
+              - `MESSAGE("message")`
+
+          - `List<String> labels`
+
+            The labels to assign to each item in the evaluation.
+
+          - `String model`
+
+            The model to use for the evaluation. Must support structured outputs.
+
+          - `String name`
+
+            The name of the grader.
+
+          - `List<String> passingLabels`
+
+            The labels that indicate a passing result. Must be a subset of labels.
+
+          - `JsonValue; type "label_model"constant`
+
+            The object type, which is always `label_model`.
+
+            - `LABEL_MODEL("label_model")`
+
+      - `String name`
+
+        The name of the grader.
+
+      - `JsonValue; type "multi"constant`
+
+        The object type, which is always `multi`.
+
+        - `MULTI("multi")`
+
+  - `String modelSample`
+
+    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.
+
+  - `Optional<JsonValue> item`
+
+    The dataset item provided to the grader. This will be used to populate
+    the `item` namespace. See [the guide](https://platform.openai.com/docs/guides/graders) for more details.
+
+### Returns
+
+- `class GraderRunResponse:`
+
+  - `Metadata metadata`
+
+    - `Errors errors`
+
+      - `boolean formulaParseError`
+
+      - `boolean invalidVariableError`
+
+      - `boolean modelGraderParseError`
+
+      - `boolean modelGraderRefusalError`
+
+      - `boolean modelGraderServerError`
+
+      - `Optional<String> modelGraderServerErrorDetails`
+
+      - `boolean otherError`
+
+      - `boolean pythonGraderRuntimeError`
+
+      - `Optional<String> pythonGraderRuntimeErrorDetails`
+
+      - `boolean pythonGraderServerError`
+
+      - `Optional<String> pythonGraderServerErrorType`
+
+      - `boolean sampleParseError`
+
+      - `boolean truncatedObservationError`
+
+      - `boolean unresponsiveRewardError`
+
+    - `double executionTime`
+
+    - `String name`
+
+    - `Optional<String> sampledModelName`
+
+    - `Scores scores`
+
+    - `Optional<Long> tokenUsage`
+
+    - `String type`
+
+  - `ModelGraderTokenUsagePerModel modelGraderTokenUsagePerModel`
+
+  - `double reward`
+
+  - `SubRewards subRewards`
+
+### Example
+
+```java
+package com.openai.example;
+
+import com.openai.client.OpenAIClient;
+import com.openai.client.okhttp.OpenAIOkHttpClient;
+import com.openai.models.finetuning.alpha.graders.GraderRunParams;
+import com.openai.models.finetuning.alpha.graders.GraderRunResponse;
+import com.openai.models.graders.gradermodels.StringCheckGrader;
+
+public final class Main {
+    private Main() {}
+
+    public static void main(String[] args) {
+        OpenAIClient client = OpenAIOkHttpClient.fromEnv();
+
+        GraderRunParams params = GraderRunParams.builder()
+            .grader(StringCheckGrader.builder()
+                .input("input")
+                .name("name")
+                .operation(StringCheckGrader.Operation.EQ)
+                .reference("reference")
+                .build())
+            .modelSample("model_sample")
+            .build();
+        GraderRunResponse response = client.fineTuning().alpha().graders().run(params);
+    }
+}
+```
+
+#### 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
+
+`GraderValidateResponse fineTuning().alpha().graders().validate(GraderValidateParamsparams, RequestOptionsrequestOptions = RequestOptions.none())`
+
+**post** `/fine_tuning/alpha/graders/validate`
+
+Validate grader
+
+### Parameters
+
+- `GraderValidateParams params`
+
+  - `Grader grader`
+
+    The grader used for the fine-tuning job.
+
+    - `class StringCheckGrader:`
+
+      A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+      - `String input`
+
+        The input text. This may include template strings.
+
+      - `String name`
+
+        The name of the grader.
+
+      - `Operation operation`
+
+        The string check operation to perform. One of `eq`, `ne`, `like`, or `ilike`.
+
+        - `EQ("eq")`
+
+        - `NE("ne")`
+
+        - `LIKE("like")`
+
+        - `ILIKE("ilike")`
+
+      - `String reference`
+
+        The reference text. This may include template strings.
+
+      - `JsonValue; type "string_check"constant`
+
+        The object type, which is always `string_check`.
+
+        - `STRING_CHECK("string_check")`
+
+    - `class TextSimilarityGrader:`
+
+      A TextSimilarityGrader object which grades text based on similarity metrics.
+
+      - `EvaluationMetric evaluationMetric`
+
+        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("cosine")`
+
+        - `FUZZY_MATCH("fuzzy_match")`
+
+        - `BLEU("bleu")`
+
+        - `GLEU("gleu")`
+
+        - `METEOR("meteor")`
+
+        - `ROUGE_1("rouge_1")`
+
+        - `ROUGE_2("rouge_2")`
+
+        - `ROUGE_3("rouge_3")`
+
+        - `ROUGE_4("rouge_4")`
+
+        - `ROUGE_5("rouge_5")`
+
+        - `ROUGE_L("rouge_l")`
+
+      - `String input`
+
+        The text being graded.
+
+      - `String name`
+
+        The name of the grader.
+
+      - `String reference`
+
+        The text being graded against.
+
+      - `JsonValue; type "text_similarity"constant`
+
+        The type of grader.
+
+        - `TEXT_SIMILARITY("text_similarity")`
+
+    - `class PythonGrader:`
+
+      A PythonGrader object that runs a python script on the input.
+
+      - `String name`
+
+        The name of the grader.
+
+      - `String source`
+
+        The source code of the python script.
+
+      - `JsonValue; type "python"constant`
+
+        The object type, which is always `python`.
+
+        - `PYTHON("python")`
+
+      - `Optional<String> imageTag`
+
+        The image tag to use for the python script.
+
+    - `class ScoreModelGrader:`
+
+      A ScoreModelGrader object that uses a model to assign a score to the input.
+
+      - `List<Input> input`
+
+        The input messages evaluated by the grader. Supports text, output text, input image, and input audio content blocks, and may include template strings.
+
+        - `Content content`
+
+          Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items.
+
+          - `String`
+
+          - `class ResponseInputText:`
+
+            A text input to the model.
+
+            - `String text`
+
+              The text input to the model.
+
+            - `JsonValue; type "input_text"constant`
+
+              The type of the input item. Always `input_text`.
+
+              - `INPUT_TEXT("input_text")`
+
+            - `Optional<PromptCacheBreakpoint> promptCacheBreakpoint`
+
+              Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's `prompt_cache_options.ttl`; the boundary is not rounded to a token block.
+
+              - `JsonValue; mode "explicit"constant`
+
+                The breakpoint mode. Always `explicit`.
+
+                - `EXPLICIT("explicit")`
+
+          - `class OutputText:`
+
+            A text output from the model.
+
+            - `String text`
+
+              The text output from the model.
+
+            - `JsonValue; type "output_text"constant`
+
+              The type of the output text. Always `output_text`.
+
+              - `OUTPUT_TEXT("output_text")`
+
+          - `class InputImage:`
+
+            An image input block used within EvalItem content arrays.
+
+            - `String imageUrl`
+
+              The URL of the image input.
+
+            - `JsonValue; type "input_image"constant`
+
+              The type of the image input. Always `input_image`.
+
+              - `INPUT_IMAGE("input_image")`
+
+            - `Optional<String> detail`
+
+              The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+          - `class ResponseInputAudio:`
+
+            An audio input to the model.
+
+            - `InputAudio inputAudio`
+
+              - `String data`
+
+                Base64-encoded audio data.
+
+              - `Format format`
+
+                The format of the audio data. Currently supported formats are `mp3` and
+                `wav`.
+
+                - `MP3("mp3")`
+
+                - `WAV("wav")`
+
+            - `JsonValue; type "input_audio"constant`
+
+              The type of the input item. Always `input_audio`.
+
+              - `INPUT_AUDIO("input_audio")`
+
+          - `List<EvalContentItem>`
+
+            - `String`
+
+            - `class ResponseInputText:`
+
+              A text input to the model.
+
+            - `OutputText`
+
+              - `String text`
+
+                The text output from the model.
+
+              - `JsonValue; type "output_text"constant`
+
+                The type of the output text. Always `output_text`.
+
+                - `OUTPUT_TEXT("output_text")`
+
+            - `InputImage`
+
+              - `String imageUrl`
+
+                The URL of the image input.
+
+              - `JsonValue; type "input_image"constant`
+
+                The type of the image input. Always `input_image`.
+
+                - `INPUT_IMAGE("input_image")`
+
+              - `Optional<String> detail`
+
+                The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+            - `class ResponseInputAudio:`
+
+              An audio input to the model.
+
+        - `Role role`
+
+          The role of the message input. One of `user`, `assistant`, `system`, or
+          `developer`.
+
+          - `USER("user")`
+
+          - `ASSISTANT("assistant")`
+
+          - `SYSTEM("system")`
+
+          - `DEVELOPER("developer")`
+
+        - `Optional<Type> type`
+
+          The type of the message input. Always `message`.
+
+          - `MESSAGE("message")`
+
+      - `String model`
+
+        The model to use for the evaluation.
+
+      - `String name`
+
+        The name of the grader.
+
+      - `JsonValue; type "score_model"constant`
+
+        The object type, which is always `score_model`.
+
+        - `SCORE_MODEL("score_model")`
+
+      - `Optional<List<Double>> range`
+
+        The range of the score. Defaults to `[0, 1]`.
+
+      - `Optional<SamplingParams> samplingParams`
+
+        The sampling parameters for the model.
+
+        - `Optional<Long> maxCompletionsTokens`
+
+          The maximum number of tokens the grader model may generate in its response.
+
+        - `Optional<ReasoningEffort> reasoningEffort`
+
+          Constrains effort on reasoning for reasoning models. Currently supported
+          values are `none`, `minimal`, `low`, `medium`, `high`, `xhigh`, and `max`.
+          Reducing reasoning effort can result in faster responses and fewer tokens
+          used on reasoning in a response. Not all reasoning models support every
+          value. See the
+          [reasoning guide](https://platform.openai.com/docs/guides/reasoning)
+          for model-specific support.
+
+          - `NONE("none")`
+
+          - `MINIMAL("minimal")`
+
+          - `LOW("low")`
+
+          - `MEDIUM("medium")`
+
+          - `HIGH("high")`
+
+          - `XHIGH("xhigh")`
+
+          - `MAX("max")`
+
+        - `Optional<Long> seed`
+
+          A seed value to initialize the randomness, during sampling.
+
+        - `Optional<Double> temperature`
+
+          A higher temperature increases randomness in the outputs.
+
+        - `Optional<Double> topP`
+
+          An alternative to temperature for nucleus sampling; 1.0 includes all tokens.
+
+    - `class MultiGrader:`
+
+      A MultiGrader object combines the output of multiple graders to produce a single score.
+
+      - `String calculateOutput`
+
+        A formula to calculate the output based on grader results.
+
+      - `Graders graders`
+
+        A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+        - `class StringCheckGrader:`
+
+          A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+        - `class TextSimilarityGrader:`
+
+          A TextSimilarityGrader object which grades text based on similarity metrics.
+
+        - `class PythonGrader:`
+
+          A PythonGrader object that runs a python script on the input.
+
+        - `class ScoreModelGrader:`
+
+          A ScoreModelGrader object that uses a model to assign a score to the input.
+
+        - `class LabelModelGrader:`
+
+          A LabelModelGrader object which uses a model to assign labels to each item
+          in the evaluation.
+
+          - `List<Input> input`
+
+            - `Content content`
+
+              Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items.
+
+              - `String`
+
+              - `class ResponseInputText:`
+
+                A text input to the model.
+
+              - `class OutputText:`
+
+                A text output from the model.
+
+                - `String text`
+
+                  The text output from the model.
+
+                - `JsonValue; type "output_text"constant`
+
+                  The type of the output text. Always `output_text`.
+
+                  - `OUTPUT_TEXT("output_text")`
+
+              - `class InputImage:`
+
+                An image input block used within EvalItem content arrays.
+
+                - `String imageUrl`
+
+                  The URL of the image input.
+
+                - `JsonValue; type "input_image"constant`
+
+                  The type of the image input. Always `input_image`.
+
+                  - `INPUT_IMAGE("input_image")`
+
+                - `Optional<String> detail`
+
+                  The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+              - `class ResponseInputAudio:`
+
+                An audio input to the model.
+
+              - `List<EvalContentItem>`
+
+                - `String`
+
+                - `class ResponseInputText:`
+
+                  A text input to the model.
+
+                - `OutputText`
+
+                - `InputImage`
+
+                - `class ResponseInputAudio:`
+
+                  An audio input to the model.
+
+            - `Role role`
+
+              The role of the message input. One of `user`, `assistant`, `system`, or
+              `developer`.
+
+              - `USER("user")`
+
+              - `ASSISTANT("assistant")`
+
+              - `SYSTEM("system")`
+
+              - `DEVELOPER("developer")`
+
+            - `Optional<Type> type`
+
+              The type of the message input. Always `message`.
+
+              - `MESSAGE("message")`
+
+          - `List<String> labels`
+
+            The labels to assign to each item in the evaluation.
+
+          - `String model`
+
+            The model to use for the evaluation. Must support structured outputs.
+
+          - `String name`
+
+            The name of the grader.
+
+          - `List<String> passingLabels`
+
+            The labels that indicate a passing result. Must be a subset of labels.
+
+          - `JsonValue; type "label_model"constant`
+
+            The object type, which is always `label_model`.
+
+            - `LABEL_MODEL("label_model")`
+
+      - `String name`
+
+        The name of the grader.
+
+      - `JsonValue; type "multi"constant`
+
+        The object type, which is always `multi`.
+
+        - `MULTI("multi")`
+
+### Returns
+
+- `class GraderValidateResponse:`
+
+  - `Optional<Grader> grader`
+
+    The grader used for the fine-tuning job.
+
+    - `class StringCheckGrader:`
+
+      A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+      - `String input`
+
+        The input text. This may include template strings.
+
+      - `String name`
+
+        The name of the grader.
+
+      - `Operation operation`
+
+        The string check operation to perform. One of `eq`, `ne`, `like`, or `ilike`.
+
+        - `EQ("eq")`
+
+        - `NE("ne")`
+
+        - `LIKE("like")`
+
+        - `ILIKE("ilike")`
+
+      - `String reference`
+
+        The reference text. This may include template strings.
+
+      - `JsonValue; type "string_check"constant`
+
+        The object type, which is always `string_check`.
+
+        - `STRING_CHECK("string_check")`
+
+    - `class TextSimilarityGrader:`
+
+      A TextSimilarityGrader object which grades text based on similarity metrics.
+
+      - `EvaluationMetric evaluationMetric`
+
+        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("cosine")`
+
+        - `FUZZY_MATCH("fuzzy_match")`
+
+        - `BLEU("bleu")`
+
+        - `GLEU("gleu")`
+
+        - `METEOR("meteor")`
+
+        - `ROUGE_1("rouge_1")`
+
+        - `ROUGE_2("rouge_2")`
+
+        - `ROUGE_3("rouge_3")`
+
+        - `ROUGE_4("rouge_4")`
+
+        - `ROUGE_5("rouge_5")`
+
+        - `ROUGE_L("rouge_l")`
+
+      - `String input`
+
+        The text being graded.
+
+      - `String name`
+
+        The name of the grader.
+
+      - `String reference`
+
+        The text being graded against.
+
+      - `JsonValue; type "text_similarity"constant`
+
+        The type of grader.
+
+        - `TEXT_SIMILARITY("text_similarity")`
+
+    - `class PythonGrader:`
+
+      A PythonGrader object that runs a python script on the input.
+
+      - `String name`
+
+        The name of the grader.
+
+      - `String source`
+
+        The source code of the python script.
+
+      - `JsonValue; type "python"constant`
+
+        The object type, which is always `python`.
+
+        - `PYTHON("python")`
+
+      - `Optional<String> imageTag`
+
+        The image tag to use for the python script.
+
+    - `class ScoreModelGrader:`
+
+      A ScoreModelGrader object that uses a model to assign a score to the input.
+
+      - `List<Input> input`
+
+        The input messages evaluated by the grader. Supports text, output text, input image, and input audio content blocks, and may include template strings.
+
+        - `Content content`
+
+          Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items.
+
+          - `String`
+
+          - `class ResponseInputText:`
+
+            A text input to the model.
+
+            - `String text`
+
+              The text input to the model.
+
+            - `JsonValue; type "input_text"constant`
+
+              The type of the input item. Always `input_text`.
+
+              - `INPUT_TEXT("input_text")`
+
+            - `Optional<PromptCacheBreakpoint> promptCacheBreakpoint`
+
+              Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's `prompt_cache_options.ttl`; the boundary is not rounded to a token block.
+
+              - `JsonValue; mode "explicit"constant`
+
+                The breakpoint mode. Always `explicit`.
+
+                - `EXPLICIT("explicit")`
+
+          - `class OutputText:`
+
+            A text output from the model.
+
+            - `String text`
+
+              The text output from the model.
+
+            - `JsonValue; type "output_text"constant`
+
+              The type of the output text. Always `output_text`.
+
+              - `OUTPUT_TEXT("output_text")`
+
+          - `class InputImage:`
+
+            An image input block used within EvalItem content arrays.
+
+            - `String imageUrl`
+
+              The URL of the image input.
+
+            - `JsonValue; type "input_image"constant`
+
+              The type of the image input. Always `input_image`.
+
+              - `INPUT_IMAGE("input_image")`
+
+            - `Optional<String> detail`
+
+              The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+          - `class ResponseInputAudio:`
+
+            An audio input to the model.
+
+            - `InputAudio inputAudio`
+
+              - `String data`
+
+                Base64-encoded audio data.
+
+              - `Format format`
+
+                The format of the audio data. Currently supported formats are `mp3` and
+                `wav`.
+
+                - `MP3("mp3")`
+
+                - `WAV("wav")`
+
+            - `JsonValue; type "input_audio"constant`
+
+              The type of the input item. Always `input_audio`.
+
+              - `INPUT_AUDIO("input_audio")`
+
+          - `List<EvalContentItem>`
+
+            - `String`
+
+            - `class ResponseInputText:`
+
+              A text input to the model.
+
+            - `OutputText`
+
+              - `String text`
+
+                The text output from the model.
+
+              - `JsonValue; type "output_text"constant`
+
+                The type of the output text. Always `output_text`.
+
+                - `OUTPUT_TEXT("output_text")`
+
+            - `InputImage`
+
+              - `String imageUrl`
+
+                The URL of the image input.
+
+              - `JsonValue; type "input_image"constant`
+
+                The type of the image input. Always `input_image`.
+
+                - `INPUT_IMAGE("input_image")`
+
+              - `Optional<String> detail`
+
+                The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+            - `class ResponseInputAudio:`
+
+              An audio input to the model.
+
+        - `Role role`
+
+          The role of the message input. One of `user`, `assistant`, `system`, or
+          `developer`.
+
+          - `USER("user")`
+
+          - `ASSISTANT("assistant")`
+
+          - `SYSTEM("system")`
+
+          - `DEVELOPER("developer")`
+
+        - `Optional<Type> type`
+
+          The type of the message input. Always `message`.
+
+          - `MESSAGE("message")`
+
+      - `String model`
+
+        The model to use for the evaluation.
+
+      - `String name`
+
+        The name of the grader.
+
+      - `JsonValue; type "score_model"constant`
+
+        The object type, which is always `score_model`.
+
+        - `SCORE_MODEL("score_model")`
+
+      - `Optional<List<Double>> range`
+
+        The range of the score. Defaults to `[0, 1]`.
+
+      - `Optional<SamplingParams> samplingParams`
+
+        The sampling parameters for the model.
+
+        - `Optional<Long> maxCompletionsTokens`
+
+          The maximum number of tokens the grader model may generate in its response.
+
+        - `Optional<ReasoningEffort> reasoningEffort`
+
+          Constrains effort on reasoning for reasoning models. Currently supported
+          values are `none`, `minimal`, `low`, `medium`, `high`, `xhigh`, and `max`.
+          Reducing reasoning effort can result in faster responses and fewer tokens
+          used on reasoning in a response. Not all reasoning models support every
+          value. See the
+          [reasoning guide](https://platform.openai.com/docs/guides/reasoning)
+          for model-specific support.
+
+          - `NONE("none")`
+
+          - `MINIMAL("minimal")`
+
+          - `LOW("low")`
+
+          - `MEDIUM("medium")`
+
+          - `HIGH("high")`
+
+          - `XHIGH("xhigh")`
+
+          - `MAX("max")`
+
+        - `Optional<Long> seed`
+
+          A seed value to initialize the randomness, during sampling.
+
+        - `Optional<Double> temperature`
+
+          A higher temperature increases randomness in the outputs.
+
+        - `Optional<Double> topP`
+
+          An alternative to temperature for nucleus sampling; 1.0 includes all tokens.
+
+    - `class MultiGrader:`
+
+      A MultiGrader object combines the output of multiple graders to produce a single score.
+
+      - `String calculateOutput`
+
+        A formula to calculate the output based on grader results.
+
+      - `Graders graders`
+
+        A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+        - `class StringCheckGrader:`
+
+          A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
+
+        - `class TextSimilarityGrader:`
+
+          A TextSimilarityGrader object which grades text based on similarity metrics.
+
+        - `class PythonGrader:`
+
+          A PythonGrader object that runs a python script on the input.
+
+        - `class ScoreModelGrader:`
+
+          A ScoreModelGrader object that uses a model to assign a score to the input.
+
+        - `class LabelModelGrader:`
+
+          A LabelModelGrader object which uses a model to assign labels to each item
+          in the evaluation.
+
+          - `List<Input> input`
+
+            - `Content content`
+
+              Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items.
+
+              - `String`
+
+              - `class ResponseInputText:`
+
+                A text input to the model.
+
+              - `class OutputText:`
+
+                A text output from the model.
+
+                - `String text`
+
+                  The text output from the model.
+
+                - `JsonValue; type "output_text"constant`
+
+                  The type of the output text. Always `output_text`.
+
+                  - `OUTPUT_TEXT("output_text")`
+
+              - `class InputImage:`
+
+                An image input block used within EvalItem content arrays.
+
+                - `String imageUrl`
+
+                  The URL of the image input.
+
+                - `JsonValue; type "input_image"constant`
+
+                  The type of the image input. Always `input_image`.
+
+                  - `INPUT_IMAGE("input_image")`
+
+                - `Optional<String> detail`
+
+                  The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.
+
+              - `class ResponseInputAudio:`
+
+                An audio input to the model.
+
+              - `List<EvalContentItem>`
+
+                - `String`
+
+                - `class ResponseInputText:`
+
+                  A text input to the model.
+
+                - `OutputText`
+
+                - `InputImage`
+
+                - `class ResponseInputAudio:`
+
+                  An audio input to the model.
+
+            - `Role role`
+
+              The role of the message input. One of `user`, `assistant`, `system`, or
+              `developer`.
+
+              - `USER("user")`
+
+              - `ASSISTANT("assistant")`
+
+              - `SYSTEM("system")`
+
+              - `DEVELOPER("developer")`
+
+            - `Optional<Type> type`
+
+              The type of the message input. Always `message`.
+
+              - `MESSAGE("message")`
+
+          - `List<String> labels`
+
+            The labels to assign to each item in the evaluation.
+
+          - `String model`
+
+            The model to use for the evaluation. Must support structured outputs.
+
+          - `String name`
+
+            The name of the grader.
+
+          - `List<String> passingLabels`
+
+            The labels that indicate a passing result. Must be a subset of labels.
+
+          - `JsonValue; type "label_model"constant`
+
+            The object type, which is always `label_model`.
+
+            - `LABEL_MODEL("label_model")`
+
+      - `String name`
+
+        The name of the grader.
+
+      - `JsonValue; type "multi"constant`
+
+        The object type, which is always `multi`.
+
+        - `MULTI("multi")`
+
+### Example
+
+```java
+package com.openai.example;
+
+import com.openai.client.OpenAIClient;
+import com.openai.client.okhttp.OpenAIOkHttpClient;
+import com.openai.models.finetuning.alpha.graders.GraderValidateParams;
+import com.openai.models.finetuning.alpha.graders.GraderValidateResponse;
+import com.openai.models.graders.gradermodels.StringCheckGrader;
+
+public final class Main {
+    private Main() {}
+
+    public static void main(String[] args) {
+        OpenAIClient client = OpenAIOkHttpClient.fromEnv();
+
+        GraderValidateParams params = GraderValidateParams.builder()
+            .grader(StringCheckGrader.builder()
+                .input("input")
+                .name("name")
+                .operation(StringCheckGrader.Operation.EQ)
+                .reference("reference")
+                .build())
+            .build();
+        GraderValidateResponse response = client.fineTuning().alpha().graders().validate(params);
+    }
+}
+```
+
+#### Response
+
+```json
+{
+  "grader": {
+    "input": "input",
+    "name": "name",
+    "operation": "eq",
+    "reference": "reference",
+    "type": "string_check"
+  }
+}
+```