import { APIResource } from "../../core/resource.js";
import * as Shared from "../shared.js";
import * as ResponsesAPI from "../responses/responses.js";
export declare class GraderModels extends APIResource {
}
/**
 * A LabelModelGrader object which uses a model to assign labels to each item in
 * the evaluation.
 */
export interface LabelModelGrader {
    input: Array<LabelModelGrader.Input>;
    /**
     * The labels to assign to each item in the evaluation.
     */
    labels: Array<string>;
    /**
     * The model to use for the evaluation. Must support structured outputs.
     */
    model: string;
    /**
     * The name of the grader.
     */
    name: string;
    /**
     * The labels that indicate a passing result. Must be a subset of labels.
     */
    passing_labels: Array<string>;
    /**
     * The object type, which is always `label_model`.
     */
    type: 'label_model';
}
export declare namespace LabelModelGrader {
    /**
     * A message input to the model with a role indicating instruction following
     * hierarchy. Instructions given with the `developer` or `system` role take
     * precedence over instructions given with the `user` role. Messages with the
     * `assistant` role are presumed to have been generated by the model in previous
     * interactions.
     */
    interface Input {
        /**
         * Inputs to the model - can contain template strings.
         */
        content: string | ResponsesAPI.ResponseInputText | Input.OutputText | Input.InputImage | ResponsesAPI.ResponseInputAudio | Array<unknown>;
        /**
         * The role of the message input. One of `user`, `assistant`, `system`, or
         * `developer`.
         */
        role: 'user' | 'assistant' | 'system' | 'developer';
        /**
         * The type of the message input. Always `message`.
         */
        type?: 'message';
    }
    namespace Input {
        /**
         * A text output from the model.
         */
        interface OutputText {
            /**
             * The text output from the model.
             */
            text: string;
            /**
             * The type of the output text. Always `output_text`.
             */
            type: 'output_text';
        }
        /**
         * An image input to the model.
         */
        interface InputImage {
            /**
             * The URL of the image input.
             */
            image_url: string;
            /**
             * The type of the image input. Always `input_image`.
             */
            type: 'input_image';
            /**
             * The detail level of the image to be sent to the model. One of `high`, `low`, or
             * `auto`. Defaults to `auto`.
             */
            detail?: string;
        }
    }
}
/**
 * A MultiGrader object combines the output of multiple graders to produce a single
 * score.
 */
export interface MultiGrader {
    /**
     * A formula to calculate the output based on grader results.
     */
    calculate_output: string;
    /**
     * A StringCheckGrader object that performs a string comparison between input and
     * reference using a specified operation.
     */
    graders: StringCheckGrader | TextSimilarityGrader | PythonGrader | ScoreModelGrader | LabelModelGrader;
    /**
     * The name of the grader.
     */
    name: string;
    /**
     * The object type, which is always `multi`.
     */
    type: 'multi';
}
/**
 * A PythonGrader object that runs a python script on the input.
 */
export interface PythonGrader {
    /**
     * The name of the grader.
     */
    name: string;
    /**
     * The source code of the python script.
     */
    source: string;
    /**
     * The object type, which is always `python`.
     */
    type: 'python';
    /**
     * The image tag to use for the python script.
     */
    image_tag?: string;
}
/**
 * A ScoreModelGrader object that uses a model to assign a score to the input.
 */
export interface ScoreModelGrader {
    /**
     * The input text. This may include template strings.
     */
    input: Array<ScoreModelGrader.Input>;
    /**
     * The model to use for the evaluation.
     */
    model: string;
    /**
     * The name of the grader.
     */
    name: string;
    /**
     * The object type, which is always `score_model`.
     */
    type: 'score_model';
    /**
     * The range of the score. Defaults to `[0, 1]`.
     */
    range?: Array<number>;
    /**
     * The sampling parameters for the model.
     */
    sampling_params?: ScoreModelGrader.SamplingParams;
}
export declare namespace ScoreModelGrader {
    /**
     * A message input to the model with a role indicating instruction following
     * hierarchy. Instructions given with the `developer` or `system` role take
     * precedence over instructions given with the `user` role. Messages with the
     * `assistant` role are presumed to have been generated by the model in previous
     * interactions.
     */
    interface Input {
        /**
         * Inputs to the model - can contain template strings.
         */
        content: string | ResponsesAPI.ResponseInputText | Input.OutputText | Input.InputImage | ResponsesAPI.ResponseInputAudio | Array<unknown>;
        /**
         * The role of the message input. One of `user`, `assistant`, `system`, or
         * `developer`.
         */
        role: 'user' | 'assistant' | 'system' | 'developer';
        /**
         * The type of the message input. Always `message`.
         */
        type?: 'message';
    }
    namespace Input {
        /**
         * A text output from the model.
         */
        interface OutputText {
            /**
             * The text output from the model.
             */
            text: string;
            /**
             * The type of the output text. Always `output_text`.
             */
            type: 'output_text';
        }
        /**
         * An image input to the model.
         */
        interface InputImage {
            /**
             * The URL of the image input.
             */
            image_url: string;
            /**
             * The type of the image input. Always `input_image`.
             */
            type: 'input_image';
            /**
             * The detail level of the image to be sent to the model. One of `high`, `low`, or
             * `auto`. Defaults to `auto`.
             */
            detail?: string;
        }
    }
    /**
     * The sampling parameters for the model.
     */
    interface SamplingParams {
        /**
         * The maximum number of tokens the grader model may generate in its response.
         */
        max_completions_tokens?: number | null;
        /**
         * Constrains effort on reasoning for
         * [reasoning models](https://platform.openai.com/docs/guides/reasoning). Currently
         * supported values are `minimal`, `low`, `medium`, and `high`. Reducing reasoning
         * effort can result in faster responses and fewer tokens used on reasoning in a
         * response.
         *
         * Note: The `gpt-5-pro` model defaults to (and only supports) `high` reasoning
         * effort.
         */
        reasoning_effort?: Shared.ReasoningEffort | null;
        /**
         * A seed value to initialize the randomness, during sampling.
         */
        seed?: number | null;
        /**
         * A higher temperature increases randomness in the outputs.
         */
        temperature?: number | null;
        /**
         * An alternative to temperature for nucleus sampling; 1.0 includes all tokens.
         */
        top_p?: number | null;
    }
}
/**
 * A StringCheckGrader object that performs a string comparison between input and
 * reference using a specified operation.
 */
export interface StringCheckGrader {
    /**
     * The input text. This may include template strings.
     */
    input: string;
    /**
     * The name of the grader.
     */
    name: string;
    /**
     * The string check operation to perform. One of `eq`, `ne`, `like`, or `ilike`.
     */
    operation: 'eq' | 'ne' | 'like' | 'ilike';
    /**
     * The reference text. This may include template strings.
     */
    reference: string;
    /**
     * The object type, which is always `string_check`.
     */
    type: 'string_check';
}
/**
 * A TextSimilarityGrader object which grades text based on similarity metrics.
 */
export interface TextSimilarityGrader {
    /**
     * 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`.
     */
    evaluation_metric: 'cosine' | 'fuzzy_match' | 'bleu' | 'gleu' | 'meteor' | 'rouge_1' | 'rouge_2' | 'rouge_3' | 'rouge_4' | 'rouge_5' | 'rouge_l';
    /**
     * The text being graded.
     */
    input: string;
    /**
     * The name of the grader.
     */
    name: string;
    /**
     * The text being graded against.
     */
    reference: string;
    /**
     * The type of grader.
     */
    type: 'text_similarity';
}
export declare namespace GraderModels {
    export { type LabelModelGrader as LabelModelGrader, type MultiGrader as MultiGrader, type PythonGrader as PythonGrader, type ScoreModelGrader as ScoreModelGrader, type StringCheckGrader as StringCheckGrader, type TextSimilarityGrader as TextSimilarityGrader, };
}
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