# Methods ## Domain Types ### Dpo Hyperparameters - `type DpoHyperparametersResp struct{…}` The hyperparameters used for the DPO fine-tuning job. - `BatchSize DpoHyperparametersBatchSizeUnionResp` Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. - `type Auto string` - `const AutoAuto Auto = "auto"` - `int64` - `Beta DpoHyperparametersBetaUnionResp` The beta value for the DPO method. A higher beta value will increase the weight of the penalty between the policy and reference model. - `type Auto string` - `const AutoAuto Auto = "auto"` - `float64` - `LearningRateMultiplier DpoHyperparametersLearningRateMultiplierUnionResp` Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. - `type Auto string` - `const AutoAuto Auto = "auto"` - `float64` - `NEpochs DpoHyperparametersNEpochsUnionResp` The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. - `type Auto string` - `const AutoAuto Auto = "auto"` - `int64` ### Dpo Method - `type DpoMethod struct{…}` Configuration for the DPO fine-tuning method. - `Hyperparameters DpoHyperparametersResp` The hyperparameters used for the DPO fine-tuning job. - `BatchSize DpoHyperparametersBatchSizeUnionResp` Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. - `type Auto string` - `const AutoAuto Auto = "auto"` - `int64` - `Beta DpoHyperparametersBetaUnionResp` The beta value for the DPO method. A higher beta value will increase the weight of the penalty between the policy and reference model. - `type Auto string` - `const AutoAuto Auto = "auto"` - `float64` - `LearningRateMultiplier DpoHyperparametersLearningRateMultiplierUnionResp` Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. - `type Auto string` - `const AutoAuto Auto = "auto"` - `float64` - `NEpochs DpoHyperparametersNEpochsUnionResp` The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. - `type Auto string` - `const AutoAuto Auto = "auto"` - `int64` ### Reinforcement Hyperparameters - `type ReinforcementHyperparametersResp struct{…}` The hyperparameters used for the reinforcement fine-tuning job. - `BatchSize ReinforcementHyperparametersBatchSizeUnionResp` Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. - `type Auto string` - `const AutoAuto Auto = "auto"` - `int64` - `ComputeMultiplier ReinforcementHyperparametersComputeMultiplierUnionResp` Multiplier on amount of compute used for exploring search space during training. - `type Auto string` - `const AutoAuto Auto = "auto"` - `float64` - `EvalInterval ReinforcementHyperparametersEvalIntervalUnionResp` The number of training steps between evaluation runs. - `type Auto string` - `const AutoAuto Auto = "auto"` - `int64` - `EvalSamples ReinforcementHyperparametersEvalSamplesUnionResp` Number of evaluation samples to generate per training step. - `type Auto string` - `const AutoAuto Auto = "auto"` - `int64` - `LearningRateMultiplier ReinforcementHyperparametersLearningRateMultiplierUnionResp` Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. - `type Auto string` - `const AutoAuto Auto = "auto"` - `float64` - `NEpochs ReinforcementHyperparametersNEpochsUnionResp` The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. - `type Auto string` - `const AutoAuto Auto = "auto"` - `int64` - `ReasoningEffort ReinforcementHyperparametersReasoningEffort` Level of reasoning effort. - `const ReinforcementHyperparametersReasoningEffortDefault ReinforcementHyperparametersReasoningEffort = "default"` - `const ReinforcementHyperparametersReasoningEffortLow ReinforcementHyperparametersReasoningEffort = "low"` - `const ReinforcementHyperparametersReasoningEffortMedium ReinforcementHyperparametersReasoningEffort = "medium"` - `const ReinforcementHyperparametersReasoningEffortHigh ReinforcementHyperparametersReasoningEffort = "high"` ### Reinforcement Method - `type ReinforcementMethod struct{…}` Configuration for the reinforcement fine-tuning method. - `Grader ReinforcementMethodGraderUnion` The grader used for the fine-tuning job. - `type StringCheckGrader struct{…}` A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. - `Input string` The input text. This may include template strings. - `Name string` The name of the grader. - `Operation StringCheckGraderOperation` The string check operation to perform. One of `eq`, `ne`, `like`, or `ilike`. - `const StringCheckGraderOperationEq StringCheckGraderOperation = "eq"` - `const StringCheckGraderOperationNe StringCheckGraderOperation = "ne"` - `const StringCheckGraderOperationLike StringCheckGraderOperation = "like"` - `const StringCheckGraderOperationIlike StringCheckGraderOperation = "ilike"` - `Reference string` The reference text. This may include template strings. - `Type StringCheck` The object type, which is always `string_check`. - `const StringCheckStringCheck StringCheck = "string_check"` - `type TextSimilarityGrader struct{…}` A TextSimilarityGrader object which grades text based on similarity metrics. - `EvaluationMetric TextSimilarityGraderEvaluationMetric` 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`. - `const TextSimilarityGraderEvaluationMetricCosine TextSimilarityGraderEvaluationMetric = "cosine"` - `const TextSimilarityGraderEvaluationMetricFuzzyMatch TextSimilarityGraderEvaluationMetric = "fuzzy_match"` - `const TextSimilarityGraderEvaluationMetricBleu TextSimilarityGraderEvaluationMetric = "bleu"` - `const TextSimilarityGraderEvaluationMetricGleu TextSimilarityGraderEvaluationMetric = "gleu"` - `const TextSimilarityGraderEvaluationMetricMeteor TextSimilarityGraderEvaluationMetric = "meteor"` - `const TextSimilarityGraderEvaluationMetricRouge1 TextSimilarityGraderEvaluationMetric = "rouge_1"` - `const TextSimilarityGraderEvaluationMetricRouge2 TextSimilarityGraderEvaluationMetric = "rouge_2"` - `const TextSimilarityGraderEvaluationMetricRouge3 TextSimilarityGraderEvaluationMetric = "rouge_3"` - `const TextSimilarityGraderEvaluationMetricRouge4 TextSimilarityGraderEvaluationMetric = "rouge_4"` - `const TextSimilarityGraderEvaluationMetricRouge5 TextSimilarityGraderEvaluationMetric = "rouge_5"` - `const TextSimilarityGraderEvaluationMetricRougeL TextSimilarityGraderEvaluationMetric = "rouge_l"` - `Input string` The text being graded. - `Name string` The name of the grader. - `Reference string` The text being graded against. - `Type TextSimilarity` The type of grader. - `const TextSimilarityTextSimilarity TextSimilarity = "text_similarity"` - `type PythonGrader struct{…}` A PythonGrader object that runs a python script on the input. - `Name string` The name of the grader. - `Source string` The source code of the python script. - `Type Python` The object type, which is always `python`. - `const PythonPython Python = "python"` - `ImageTag string` The image tag to use for the python script. - `type ScoreModelGrader struct{…}` A ScoreModelGrader object that uses a model to assign a score to the input. - `Input []ScoreModelGraderInput` The input messages evaluated by the grader. Supports text, output text, input image, and input audio content blocks, and may include template strings. - `Content ScoreModelGraderInputContentUnion` 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` - `type ResponseInputText struct{…}` A text input to the model. - `Text string` The text input to the model. - `Type InputText` The type of the input item. Always `input_text`. - `const InputTextInputText InputText = "input_text"` - `type ScoreModelGraderInputContentOutputText struct{…}` A text output from the model. - `Text string` The text output from the model. - `Type OutputText` The type of the output text. Always `output_text`. - `const OutputTextOutputText OutputText = "output_text"` - `type ScoreModelGraderInputContentInputImage struct{…}` An image input block used within EvalItem content arrays. - `ImageURL string` The URL of the image input. - `Type InputImage` The type of the image input. Always `input_image`. - `const InputImageInputImage InputImage = "input_image"` - `Detail string` The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. - `type ResponseInputAudio struct{…}` An audio input to the model. - `InputAudio ResponseInputAudioInputAudio` - `Data string` Base64-encoded audio data. - `Format string` The format of the audio data. Currently supported formats are `mp3` and `wav`. - `const ResponseInputAudioInputAudioFormatMP3 ResponseInputAudioInputAudioFormat = "mp3"` - `const ResponseInputAudioInputAudioFormatWAV ResponseInputAudioInputAudioFormat = "wav"` - `Type InputAudio` The type of the input item. Always `input_audio`. - `const InputAudioInputAudio InputAudio = "input_audio"` - `type GraderInputs []GraderInputUnion` A list of inputs, each of which may be either an input text, output text, input image, or input audio object. - `string` - `type ResponseInputText struct{…}` A text input to the model. - `Text string` The text input to the model. - `Type InputText` The type of the input item. Always `input_text`. - `const InputTextInputText InputText = "input_text"` - `type GraderInputOutputText struct{…}` A text output from the model. - `Text string` The text output from the model. - `Type OutputText` The type of the output text. Always `output_text`. - `const OutputTextOutputText OutputText = "output_text"` - `type GraderInputInputImage struct{…}` An image input block used within EvalItem content arrays. - `ImageURL string` The URL of the image input. - `Type InputImage` The type of the image input. Always `input_image`. - `const InputImageInputImage InputImage = "input_image"` - `Detail string` The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. - `type ResponseInputAudio struct{…}` An audio input to the model. - `InputAudio ResponseInputAudioInputAudio` - `Data string` Base64-encoded audio data. - `Format string` The format of the audio data. Currently supported formats are `mp3` and `wav`. - `const ResponseInputAudioInputAudioFormatMP3 ResponseInputAudioInputAudioFormat = "mp3"` - `const ResponseInputAudioInputAudioFormatWAV ResponseInputAudioInputAudioFormat = "wav"` - `Type InputAudio` The type of the input item. Always `input_audio`. - `const InputAudioInputAudio InputAudio = "input_audio"` - `Role string` The role of the message input. One of `user`, `assistant`, `system`, or `developer`. - `const ScoreModelGraderInputRoleUser ScoreModelGraderInputRole = "user"` - `const ScoreModelGraderInputRoleAssistant ScoreModelGraderInputRole = "assistant"` - `const ScoreModelGraderInputRoleSystem ScoreModelGraderInputRole = "system"` - `const ScoreModelGraderInputRoleDeveloper ScoreModelGraderInputRole = "developer"` - `Type string` The type of the message input. Always `message`. - `const ScoreModelGraderInputTypeMessage ScoreModelGraderInputType = "message"` - `Model string` The model to use for the evaluation. - `Name string` The name of the grader. - `Type ScoreModel` The object type, which is always `score_model`. - `const ScoreModelScoreModel ScoreModel = "score_model"` - `Range []float64` The range of the score. Defaults to `[0, 1]`. - `SamplingParams ScoreModelGraderSamplingParams` The sampling parameters for the model. - `MaxCompletionsTokens int64` The maximum number of tokens the grader model may generate in its response. - `ReasoningEffort ReasoningEffort` Constrains effort on reasoning for [reasoning models](https://platform.openai.com/docs/guides/reasoning). Currently supported values are `none`, `minimal`, `low`, `medium`, `high`, and `xhigh`. Reducing reasoning effort can result in faster responses and fewer tokens used on reasoning in a response. - `gpt-5.1` defaults to `none`, which does not perform reasoning. The supported reasoning values for `gpt-5.1` are `none`, `low`, `medium`, and `high`. Tool calls are supported for all reasoning values in gpt-5.1. - All models before `gpt-5.1` default to `medium` reasoning effort, and do not support `none`. - The `gpt-5-pro` model defaults to (and only supports) `high` reasoning effort. - `xhigh` is supported for all models after `gpt-5.1-codex-max`. - `const ReasoningEffortNone ReasoningEffort = "none"` - `const ReasoningEffortMinimal ReasoningEffort = "minimal"` - `const ReasoningEffortLow ReasoningEffort = "low"` - `const ReasoningEffortMedium ReasoningEffort = "medium"` - `const ReasoningEffortHigh ReasoningEffort = "high"` - `const ReasoningEffortXhigh ReasoningEffort = "xhigh"` - `Seed int64` A seed value to initialize the randomness, during sampling. - `Temperature float64` A higher temperature increases randomness in the outputs. - `TopP float64` An alternative to temperature for nucleus sampling; 1.0 includes all tokens. - `type MultiGrader struct{…}` A MultiGrader object combines the output of multiple graders to produce a single score. - `CalculateOutput string` A formula to calculate the output based on grader results. - `Graders MultiGraderGradersUnion` A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. - `type StringCheckGrader struct{…}` A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. - `Input string` The input text. This may include template strings. - `Name string` The name of the grader. - `Operation StringCheckGraderOperation` The string check operation to perform. One of `eq`, `ne`, `like`, or `ilike`. - `const StringCheckGraderOperationEq StringCheckGraderOperation = "eq"` - `const StringCheckGraderOperationNe StringCheckGraderOperation = "ne"` - `const StringCheckGraderOperationLike StringCheckGraderOperation = "like"` - `const StringCheckGraderOperationIlike StringCheckGraderOperation = "ilike"` - `Reference string` The reference text. This may include template strings. - `Type StringCheck` The object type, which is always `string_check`. - `const StringCheckStringCheck StringCheck = "string_check"` - `type TextSimilarityGrader struct{…}` A TextSimilarityGrader object which grades text based on similarity metrics. - `EvaluationMetric TextSimilarityGraderEvaluationMetric` 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`. - `const TextSimilarityGraderEvaluationMetricCosine TextSimilarityGraderEvaluationMetric = "cosine"` - `const TextSimilarityGraderEvaluationMetricFuzzyMatch TextSimilarityGraderEvaluationMetric = "fuzzy_match"` - `const TextSimilarityGraderEvaluationMetricBleu TextSimilarityGraderEvaluationMetric = "bleu"` - `const TextSimilarityGraderEvaluationMetricGleu TextSimilarityGraderEvaluationMetric = "gleu"` - `const TextSimilarityGraderEvaluationMetricMeteor TextSimilarityGraderEvaluationMetric = "meteor"` - `const TextSimilarityGraderEvaluationMetricRouge1 TextSimilarityGraderEvaluationMetric = "rouge_1"` - `const TextSimilarityGraderEvaluationMetricRouge2 TextSimilarityGraderEvaluationMetric = "rouge_2"` - `const TextSimilarityGraderEvaluationMetricRouge3 TextSimilarityGraderEvaluationMetric = "rouge_3"` - `const TextSimilarityGraderEvaluationMetricRouge4 TextSimilarityGraderEvaluationMetric = "rouge_4"` - `const TextSimilarityGraderEvaluationMetricRouge5 TextSimilarityGraderEvaluationMetric = "rouge_5"` - `const TextSimilarityGraderEvaluationMetricRougeL TextSimilarityGraderEvaluationMetric = "rouge_l"` - `Input string` The text being graded. - `Name string` The name of the grader. - `Reference string` The text being graded against. - `Type TextSimilarity` The type of grader. - `const TextSimilarityTextSimilarity TextSimilarity = "text_similarity"` - `type PythonGrader struct{…}` A PythonGrader object that runs a python script on the input. - `Name string` The name of the grader. - `Source string` The source code of the python script. - `Type Python` The object type, which is always `python`. - `const PythonPython Python = "python"` - `ImageTag string` The image tag to use for the python script. - `type ScoreModelGrader struct{…}` A ScoreModelGrader object that uses a model to assign a score to the input. - `Input []ScoreModelGraderInput` The input messages evaluated by the grader. Supports text, output text, input image, and input audio content blocks, and may include template strings. - `Content ScoreModelGraderInputContentUnion` 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` - `type ResponseInputText struct{…}` A text input to the model. - `Text string` The text input to the model. - `Type InputText` The type of the input item. Always `input_text`. - `const InputTextInputText InputText = "input_text"` - `type ScoreModelGraderInputContentOutputText struct{…}` A text output from the model. - `Text string` The text output from the model. - `Type OutputText` The type of the output text. Always `output_text`. - `const OutputTextOutputText OutputText = "output_text"` - `type ScoreModelGraderInputContentInputImage struct{…}` An image input block used within EvalItem content arrays. - `ImageURL string` The URL of the image input. - `Type InputImage` The type of the image input. Always `input_image`. - `const InputImageInputImage InputImage = "input_image"` - `Detail string` The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. - `type ResponseInputAudio struct{…}` An audio input to the model. - `InputAudio ResponseInputAudioInputAudio` - `Data string` Base64-encoded audio data. - `Format string` The format of the audio data. Currently supported formats are `mp3` and `wav`. - `const ResponseInputAudioInputAudioFormatMP3 ResponseInputAudioInputAudioFormat = "mp3"` - `const ResponseInputAudioInputAudioFormatWAV ResponseInputAudioInputAudioFormat = "wav"` - `Type InputAudio` The type of the input item. Always `input_audio`. - `const InputAudioInputAudio InputAudio = "input_audio"` - `type GraderInputs []GraderInputUnion` A list of inputs, each of which may be either an input text, output text, input image, or input audio object. - `string` - `type ResponseInputText struct{…}` A text input to the model. - `Text string` The text input to the model. - `Type InputText` The type of the input item. Always `input_text`. - `const InputTextInputText InputText = "input_text"` - `type GraderInputOutputText struct{…}` A text output from the model. - `Text string` The text output from the model. - `Type OutputText` The type of the output text. Always `output_text`. - `const OutputTextOutputText OutputText = "output_text"` - `type GraderInputInputImage struct{…}` An image input block used within EvalItem content arrays. - `ImageURL string` The URL of the image input. - `Type InputImage` The type of the image input. Always `input_image`. - `const InputImageInputImage InputImage = "input_image"` - `Detail string` The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. - `type ResponseInputAudio struct{…}` An audio input to the model. - `InputAudio ResponseInputAudioInputAudio` - `Data string` Base64-encoded audio data. - `Format string` The format of the audio data. Currently supported formats are `mp3` and `wav`. - `const ResponseInputAudioInputAudioFormatMP3 ResponseInputAudioInputAudioFormat = "mp3"` - `const ResponseInputAudioInputAudioFormatWAV ResponseInputAudioInputAudioFormat = "wav"` - `Type InputAudio` The type of the input item. Always `input_audio`. - `const InputAudioInputAudio InputAudio = "input_audio"` - `Role string` The role of the message input. One of `user`, `assistant`, `system`, or `developer`. - `const ScoreModelGraderInputRoleUser ScoreModelGraderInputRole = "user"` - `const ScoreModelGraderInputRoleAssistant ScoreModelGraderInputRole = "assistant"` - `const ScoreModelGraderInputRoleSystem ScoreModelGraderInputRole = "system"` - `const ScoreModelGraderInputRoleDeveloper ScoreModelGraderInputRole = "developer"` - `Type string` The type of the message input. Always `message`. - `const ScoreModelGraderInputTypeMessage ScoreModelGraderInputType = "message"` - `Model string` The model to use for the evaluation. - `Name string` The name of the grader. - `Type ScoreModel` The object type, which is always `score_model`. - `const ScoreModelScoreModel ScoreModel = "score_model"` - `Range []float64` The range of the score. Defaults to `[0, 1]`. - `SamplingParams ScoreModelGraderSamplingParams` The sampling parameters for the model. - `MaxCompletionsTokens int64` The maximum number of tokens the grader model may generate in its response. - `ReasoningEffort ReasoningEffort` Constrains effort on reasoning for [reasoning models](https://platform.openai.com/docs/guides/reasoning). Currently supported values are `none`, `minimal`, `low`, `medium`, `high`, and `xhigh`. Reducing reasoning effort can result in faster responses and fewer tokens used on reasoning in a response. - `gpt-5.1` defaults to `none`, which does not perform reasoning. The supported reasoning values for `gpt-5.1` are `none`, `low`, `medium`, and `high`. Tool calls are supported for all reasoning values in gpt-5.1. - All models before `gpt-5.1` default to `medium` reasoning effort, and do not support `none`. - The `gpt-5-pro` model defaults to (and only supports) `high` reasoning effort. - `xhigh` is supported for all models after `gpt-5.1-codex-max`. - `const ReasoningEffortNone ReasoningEffort = "none"` - `const ReasoningEffortMinimal ReasoningEffort = "minimal"` - `const ReasoningEffortLow ReasoningEffort = "low"` - `const ReasoningEffortMedium ReasoningEffort = "medium"` - `const ReasoningEffortHigh ReasoningEffort = "high"` - `const ReasoningEffortXhigh ReasoningEffort = "xhigh"` - `Seed int64` A seed value to initialize the randomness, during sampling. - `Temperature float64` A higher temperature increases randomness in the outputs. - `TopP float64` An alternative to temperature for nucleus sampling; 1.0 includes all tokens. - `type LabelModelGrader struct{…}` A LabelModelGrader object which uses a model to assign labels to each item in the evaluation. - `Input []LabelModelGraderInput` - `Content LabelModelGraderInputContentUnion` 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` - `type ResponseInputText struct{…}` A text input to the model. - `Text string` The text input to the model. - `Type InputText` The type of the input item. Always `input_text`. - `const InputTextInputText InputText = "input_text"` - `type LabelModelGraderInputContentOutputText struct{…}` A text output from the model. - `Text string` The text output from the model. - `Type OutputText` The type of the output text. Always `output_text`. - `const OutputTextOutputText OutputText = "output_text"` - `type LabelModelGraderInputContentInputImage struct{…}` An image input block used within EvalItem content arrays. - `ImageURL string` The URL of the image input. - `Type InputImage` The type of the image input. Always `input_image`. - `const InputImageInputImage InputImage = "input_image"` - `Detail string` The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. - `type ResponseInputAudio struct{…}` An audio input to the model. - `InputAudio ResponseInputAudioInputAudio` - `Data string` Base64-encoded audio data. - `Format string` The format of the audio data. Currently supported formats are `mp3` and `wav`. - `const ResponseInputAudioInputAudioFormatMP3 ResponseInputAudioInputAudioFormat = "mp3"` - `const ResponseInputAudioInputAudioFormatWAV ResponseInputAudioInputAudioFormat = "wav"` - `Type InputAudio` The type of the input item. Always `input_audio`. - `const InputAudioInputAudio InputAudio = "input_audio"` - `type GraderInputs []GraderInputUnion` A list of inputs, each of which may be either an input text, output text, input image, or input audio object. - `string` - `type ResponseInputText struct{…}` A text input to the model. - `Text string` The text input to the model. - `Type InputText` The type of the input item. Always `input_text`. - `const InputTextInputText InputText = "input_text"` - `type GraderInputOutputText struct{…}` A text output from the model. - `Text string` The text output from the model. - `Type OutputText` The type of the output text. Always `output_text`. - `const OutputTextOutputText OutputText = "output_text"` - `type GraderInputInputImage struct{…}` An image input block used within EvalItem content arrays. - `ImageURL string` The URL of the image input. - `Type InputImage` The type of the image input. Always `input_image`. - `const InputImageInputImage InputImage = "input_image"` - `Detail string` The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. - `type ResponseInputAudio struct{…}` An audio input to the model. - `InputAudio ResponseInputAudioInputAudio` - `Data string` Base64-encoded audio data. - `Format string` The format of the audio data. Currently supported formats are `mp3` and `wav`. - `const ResponseInputAudioInputAudioFormatMP3 ResponseInputAudioInputAudioFormat = "mp3"` - `const ResponseInputAudioInputAudioFormatWAV ResponseInputAudioInputAudioFormat = "wav"` - `Type InputAudio` The type of the input item. Always `input_audio`. - `const InputAudioInputAudio InputAudio = "input_audio"` - `Role string` The role of the message input. One of `user`, `assistant`, `system`, or `developer`. - `const LabelModelGraderInputRoleUser LabelModelGraderInputRole = "user"` - `const LabelModelGraderInputRoleAssistant LabelModelGraderInputRole = "assistant"` - `const LabelModelGraderInputRoleSystem LabelModelGraderInputRole = "system"` - `const LabelModelGraderInputRoleDeveloper LabelModelGraderInputRole = "developer"` - `Type string` The type of the message input. Always `message`. - `const LabelModelGraderInputTypeMessage LabelModelGraderInputType = "message"` - `Labels []string` The labels to assign to each item in the evaluation. - `Model string` The model to use for the evaluation. Must support structured outputs. - `Name string` The name of the grader. - `PassingLabels []string` The labels that indicate a passing result. Must be a subset of labels. - `Type LabelModel` The object type, which is always `label_model`. - `const LabelModelLabelModel LabelModel = "label_model"` - `Name string` The name of the grader. - `Type Multi` The object type, which is always `multi`. - `const MultiMulti Multi = "multi"` - `Hyperparameters ReinforcementHyperparametersResp` The hyperparameters used for the reinforcement fine-tuning job. - `BatchSize ReinforcementHyperparametersBatchSizeUnionResp` Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. - `type Auto string` - `const AutoAuto Auto = "auto"` - `int64` - `ComputeMultiplier ReinforcementHyperparametersComputeMultiplierUnionResp` Multiplier on amount of compute used for exploring search space during training. - `type Auto string` - `const AutoAuto Auto = "auto"` - `float64` - `EvalInterval ReinforcementHyperparametersEvalIntervalUnionResp` The number of training steps between evaluation runs. - `type Auto string` - `const AutoAuto Auto = "auto"` - `int64` - `EvalSamples ReinforcementHyperparametersEvalSamplesUnionResp` Number of evaluation samples to generate per training step. - `type Auto string` - `const AutoAuto Auto = "auto"` - `int64` - `LearningRateMultiplier ReinforcementHyperparametersLearningRateMultiplierUnionResp` Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. - `type Auto string` - `const AutoAuto Auto = "auto"` - `float64` - `NEpochs ReinforcementHyperparametersNEpochsUnionResp` The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. - `type Auto string` - `const AutoAuto Auto = "auto"` - `int64` - `ReasoningEffort ReinforcementHyperparametersReasoningEffort` Level of reasoning effort. - `const ReinforcementHyperparametersReasoningEffortDefault ReinforcementHyperparametersReasoningEffort = "default"` - `const ReinforcementHyperparametersReasoningEffortLow ReinforcementHyperparametersReasoningEffort = "low"` - `const ReinforcementHyperparametersReasoningEffortMedium ReinforcementHyperparametersReasoningEffort = "medium"` - `const ReinforcementHyperparametersReasoningEffortHigh ReinforcementHyperparametersReasoningEffort = "high"` ### Supervised Hyperparameters - `type SupervisedHyperparametersResp struct{…}` The hyperparameters used for the fine-tuning job. - `BatchSize SupervisedHyperparametersBatchSizeUnionResp` Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. - `type Auto string` - `const AutoAuto Auto = "auto"` - `int64` - `LearningRateMultiplier SupervisedHyperparametersLearningRateMultiplierUnionResp` Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. - `type Auto string` - `const AutoAuto Auto = "auto"` - `float64` - `NEpochs SupervisedHyperparametersNEpochsUnionResp` The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. - `type Auto string` - `const AutoAuto Auto = "auto"` - `int64` ### Supervised Method - `type SupervisedMethod struct{…}` Configuration for the supervised fine-tuning method. - `Hyperparameters SupervisedHyperparametersResp` The hyperparameters used for the fine-tuning job. - `BatchSize SupervisedHyperparametersBatchSizeUnionResp` Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. - `type Auto string` - `const AutoAuto Auto = "auto"` - `int64` - `LearningRateMultiplier SupervisedHyperparametersLearningRateMultiplierUnionResp` Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. - `type Auto string` - `const AutoAuto Auto = "auto"` - `float64` - `NEpochs SupervisedHyperparametersNEpochsUnionResp` The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. - `type Auto string` - `const AutoAuto Auto = "auto"` - `int64`