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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};
/// FineTuneReinforcementRequestInput : Per-line training example for reinforcement fine-tuning. Note that `messages` and `tools` are the only reserved keywords. Any other arbitrary key-value data can be included on training datapoints and will be available to reference during grading under the `{{ item.XXX }}` template variable. Input messages may contain text or image content only. Audio and file input messages are not currently supported for fine-tuning.
#[derive(Clone, Default, Debug, PartialEq, Serialize, Deserialize, bon::Builder)]
pub struct FineTuneReinforcementRequestInput {
#[serde(rename = "messages")]
pub messages: Vec<models::FineTuneReinforcementRequestInputMessagesInner>,
/// A list of tools the model may generate JSON inputs for.
#[serde(rename = "tools", skip_serializing_if = "Option::is_none")]
pub tools: Option<Vec<models::ChatCompletionTool>>,
}
impl FineTuneReinforcementRequestInput {
/// Per-line training example for reinforcement fine-tuning. Note that `messages` and `tools` are the only reserved keywords. Any other arbitrary key-value data can be included on training datapoints and will be available to reference during grading under the `{{ item.XXX }}` template variable. Input messages may contain text or image content only. Audio and file input messages are not currently supported for fine-tuning.
pub fn new(
messages: Vec<models::FineTuneReinforcementRequestInputMessagesInner>,
) -> FineTuneReinforcementRequestInput {
FineTuneReinforcementRequestInput {
messages,
tools: None,
}
}
}
impl std::fmt::Display for FineTuneReinforcementRequestInput {
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),
}
}
}