# Alpha # Graders ## Run grader `GraderRunResponse fineTuning().alpha().graders().run(GraderRunParamsparams, RequestOptionsrequestOptions = RequestOptions.none())` **post** `/fine_tuning/alpha/graders/run` Run a 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 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` 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")` - `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 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` - `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 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` 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> range` The range of the score. Defaults to `[0, 1]`. - `Optional samplingParams` The sampling parameters for the model. - `Optional maxCompletionsTokens` The maximum number of tokens the grader model may generate in its response. - `Optional reasoningEffort` Constrains effort on reasoning for [reasoning models](https://platform.openai.com/docs/guides/reasoning). Currently supported values are `none`, `minimal`, `low`, `medium`, `high`, and `xhigh`. Reducing reasoning effort can result in faster responses and fewer tokens used on reasoning in a response. - `gpt-5.1` defaults to `none`, which does not perform reasoning. The supported reasoning values for `gpt-5.1` are `none`, `low`, `medium`, and `high`. Tool calls are supported for all reasoning values in gpt-5.1. - All models before `gpt-5.1` default to `medium` reasoning effort, and do not support `none`. - The `gpt-5-pro` model defaults to (and only supports) `high` reasoning effort. - `xhigh` is supported for all models after `gpt-5.1-codex-max`. - `NONE("none")` - `MINIMAL("minimal")` - `LOW("low")` - `MEDIUM("medium")` - `HIGH("high")` - `XHIGH("xhigh")` - `Optional seed` A seed value to initialize the randomness, during sampling. - `Optional temperature` A higher temperature increases randomness in the outputs. - `Optional 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` - `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 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` - `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` The type of the message input. Always `message`. - `MESSAGE("message")` - `List 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 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 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 modelGraderServerErrorDetails` - `boolean otherError` - `boolean pythonGraderRuntimeError` - `Optional pythonGraderRuntimeErrorDetails` - `boolean pythonGraderServerError` - `Optional pythonGraderServerErrorType` - `boolean sampleParseError` - `boolean truncatedObservationError` - `boolean unresponsiveRewardError` - `double executionTime` - `String name` - `Optional sampledModelName` - `Scores scores` - `Optional 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 a 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 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` 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")` - `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 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` - `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 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` 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> range` The range of the score. Defaults to `[0, 1]`. - `Optional samplingParams` The sampling parameters for the model. - `Optional maxCompletionsTokens` The maximum number of tokens the grader model may generate in its response. - `Optional reasoningEffort` Constrains effort on reasoning for [reasoning models](https://platform.openai.com/docs/guides/reasoning). Currently supported values are `none`, `minimal`, `low`, `medium`, `high`, and `xhigh`. Reducing reasoning effort can result in faster responses and fewer tokens used on reasoning in a response. - `gpt-5.1` defaults to `none`, which does not perform reasoning. The supported reasoning values for `gpt-5.1` are `none`, `low`, `medium`, and `high`. Tool calls are supported for all reasoning values in gpt-5.1. - All models before `gpt-5.1` default to `medium` reasoning effort, and do not support `none`. - The `gpt-5-pro` model defaults to (and only supports) `high` reasoning effort. - `xhigh` is supported for all models after `gpt-5.1-codex-max`. - `NONE("none")` - `MINIMAL("minimal")` - `LOW("low")` - `MEDIUM("medium")` - `HIGH("high")` - `XHIGH("xhigh")` - `Optional seed` A seed value to initialize the randomness, during sampling. - `Optional temperature` A higher temperature increases randomness in the outputs. - `Optional 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` - `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 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` - `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` The type of the message input. Always `message`. - `MESSAGE("message")` - `List 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 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` 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 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` 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")` - `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 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` - `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 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` 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> range` The range of the score. Defaults to `[0, 1]`. - `Optional samplingParams` The sampling parameters for the model. - `Optional maxCompletionsTokens` The maximum number of tokens the grader model may generate in its response. - `Optional reasoningEffort` Constrains effort on reasoning for [reasoning models](https://platform.openai.com/docs/guides/reasoning). Currently supported values are `none`, `minimal`, `low`, `medium`, `high`, and `xhigh`. Reducing reasoning effort can result in faster responses and fewer tokens used on reasoning in a response. - `gpt-5.1` defaults to `none`, which does not perform reasoning. The supported reasoning values for `gpt-5.1` are `none`, `low`, `medium`, and `high`. Tool calls are supported for all reasoning values in gpt-5.1. - All models before `gpt-5.1` default to `medium` reasoning effort, and do not support `none`. - The `gpt-5-pro` model defaults to (and only supports) `high` reasoning effort. - `xhigh` is supported for all models after `gpt-5.1-codex-max`. - `NONE("none")` - `MINIMAL("minimal")` - `LOW("low")` - `MEDIUM("medium")` - `HIGH("high")` - `XHIGH("xhigh")` - `Optional seed` A seed value to initialize the randomness, during sampling. - `Optional temperature` A higher temperature increases randomness in the outputs. - `Optional 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` - `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 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` - `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` The type of the message input. Always `message`. - `MESSAGE("message")` - `List 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 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" } } ```