openai-client-base 0.12.0

Auto-generated Rust client for the OpenAI API
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/*
 * OpenAI API
 *
 * The OpenAI REST API. Please see https://platform.openai.com/docs/api-reference for more details.
 *
 * The version of the OpenAPI document: 2.3.0
 *
 * Generated by: https://openapi-generator.tech
 */

use crate::models;
use serde::{Deserialize, Serialize};

#[derive(Clone, Default, Debug, PartialEq, Serialize, Deserialize, bon::Builder)]
pub struct EvalGraderScoreModel {
    /// The object type, which is always `score_model`.
    #[serde(rename = "type")]
    pub r#type: Type,
    /// The name of the grader.
    #[serde(rename = "name")]
    pub name: String,
    /// ID of the model to use
    #[serde(rename = "model")]
    pub model: String,
    #[serde(rename = "sampling_params", skip_serializing_if = "Option::is_none")]
    pub sampling_params: Option<Box<models::GraderScoreModelSamplingParams>>,
    /// The input messages evaluated by the grader. Supports text, output text, input image, and input audio content blocks, and may include template strings.
    #[serde(rename = "input")]
    pub input: Vec<models::EvalItem>,
    /// The range of the score. Defaults to `[0, 1]`.
    #[serde(rename = "range", skip_serializing_if = "Option::is_none")]
    pub range: Option<Vec<f64>>,
    /// The threshold for the score.
    #[serde(rename = "pass_threshold", skip_serializing_if = "Option::is_none")]
    pub pass_threshold: Option<f64>,
}

impl EvalGraderScoreModel {
    pub fn new(
        r#type: Type,
        name: String,
        model: String,
        input: Vec<models::EvalItem>,
    ) -> EvalGraderScoreModel {
        EvalGraderScoreModel {
            r#type,
            name,
            model,
            sampling_params: None,
            input,
            range: None,
            pass_threshold: None,
        }
    }
}
/// The object type, which is always `score_model`.
#[derive(Clone, Copy, Debug, Eq, PartialEq, Ord, PartialOrd, Hash, Serialize, Deserialize)]
pub enum Type {
    #[serde(rename = "score_model")]
    ScoreModel,
}

impl Default for Type {
    fn default() -> Type {
        Self::ScoreModel
    }
}

impl std::fmt::Display for EvalGraderScoreModel {
    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
        match serde_json::to_string(self) {
            Ok(s) => write!(f, "{}", s),
            Err(_) => Err(std::fmt::Error),
        }
    }
}