# Alpha # Graders ## Run grader `client.FineTuning.Alpha.Graders.Run(ctx, body) (*FineTuningAlphaGraderRunResponse, error)` **post** `/fine_tuning/alpha/graders/run` Run a grader. ### Parameters - `body FineTuningAlphaGraderRunParams` - `Grader param.Field[FineTuningAlphaGraderRunParamsGraderUnion]` 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. - `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. - `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. - `type TextSimilarityGrader struct{…}` A TextSimilarityGrader object which grades text based on similarity metrics. - `type PythonGrader struct{…}` A PythonGrader object that runs a python script on the input. - `type ScoreModelGrader struct{…}` A ScoreModelGrader object that uses a model to assign a score to the input. - `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. - `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. - `type GraderInputs []GraderInputUnion` A list of inputs, each of which may be either an input text, output text, input image, or input audio object. - `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"` - `ModelSample param.Field[string]` The model sample to be evaluated. This value will be used to populate the `sample` namespace. See [the guide](https://platform.openai.com/docs/guides/graders) for more details. The `output_json` variable will be populated if the model sample is a valid JSON string. - `Item param.Field[any]` 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 - `type FineTuningAlphaGraderRunResponse struct{…}` - `Metadata FineTuningAlphaGraderRunResponseMetadata` - `Errors FineTuningAlphaGraderRunResponseMetadataErrors` - `FormulaParseError bool` - `InvalidVariableError bool` - `ModelGraderParseError bool` - `ModelGraderRefusalError bool` - `ModelGraderServerError bool` - `ModelGraderServerErrorDetails string` - `OtherError bool` - `PythonGraderRuntimeError bool` - `PythonGraderRuntimeErrorDetails string` - `PythonGraderServerError bool` - `PythonGraderServerErrorType string` - `SampleParseError bool` - `TruncatedObservationError bool` - `UnresponsiveRewardError bool` - `ExecutionTime float64` - `Name string` - `SampledModelName string` - `Scores map[string, any]` - `TokenUsage int64` - `Type string` - `ModelGraderTokenUsagePerModel map[string, any]` - `Reward float64` - `SubRewards map[string, any]` ### Example ```go package main import ( "context" "fmt" "github.com/openai/openai-go" "github.com/openai/openai-go/option" ) func main() { client := openai.NewClient( option.WithAPIKey("My API Key"), ) response, err := client.FineTuning.Alpha.Graders.Run(context.TODO(), openai.FineTuningAlphaGraderRunParams{ Grader: openai.FineTuningAlphaGraderRunParamsGraderUnion{ OfStringCheck: &openai.StringCheckGraderParam{ Input: "input", Name: "name", Operation: openai.StringCheckGraderOperationEq, Reference: "reference", }, }, ModelSample: "model_sample", }) if err != nil { panic(err.Error()) } fmt.Printf("%+v\n", response.Metadata) } ``` #### 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 `client.FineTuning.Alpha.Graders.Validate(ctx, body) (*FineTuningAlphaGraderValidateResponse, error)` **post** `/fine_tuning/alpha/graders/validate` Validate a grader. ### Parameters - `body FineTuningAlphaGraderValidateParams` - `Grader param.Field[FineTuningAlphaGraderValidateParamsGraderUnion]` 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. - `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. - `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. - `type TextSimilarityGrader struct{…}` A TextSimilarityGrader object which grades text based on similarity metrics. - `type PythonGrader struct{…}` A PythonGrader object that runs a python script on the input. - `type ScoreModelGrader struct{…}` A ScoreModelGrader object that uses a model to assign a score to the input. - `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. - `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. - `type GraderInputs []GraderInputUnion` A list of inputs, each of which may be either an input text, output text, input image, or input audio object. - `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"` ### Returns - `type FineTuningAlphaGraderValidateResponse struct{…}` - `Grader FineTuningAlphaGraderValidateResponseGraderUnion` 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. - `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. - `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. - `type TextSimilarityGrader struct{…}` A TextSimilarityGrader object which grades text based on similarity metrics. - `type PythonGrader struct{…}` A PythonGrader object that runs a python script on the input. - `type ScoreModelGrader struct{…}` A ScoreModelGrader object that uses a model to assign a score to the input. - `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. - `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. - `type GraderInputs []GraderInputUnion` A list of inputs, each of which may be either an input text, output text, input image, or input audio object. - `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"` ### Example ```go package main import ( "context" "fmt" "github.com/openai/openai-go" "github.com/openai/openai-go/option" ) func main() { client := openai.NewClient( option.WithAPIKey("My API Key"), ) response, err := client.FineTuning.Alpha.Graders.Validate(context.TODO(), openai.FineTuningAlphaGraderValidateParams{ Grader: openai.FineTuningAlphaGraderValidateParamsGraderUnion{ OfStringCheckGrader: &openai.StringCheckGraderParam{ Input: "input", Name: "name", Operation: openai.StringCheckGraderOperationEq, Reference: "reference", }, }, }) if err != nil { panic(err.Error()) } fmt.Printf("%+v\n", response.Grader) } ``` #### Response ```json { "grader": { "input": "input", "name": "name", "operation": "eq", "reference": "reference", "type": "string_check" } } ```