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/*
 * Copyright 2023 lzhpo
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package com.lzhpo.chatgpt.entity;

import com.fasterxml.jackson.annotation.JsonInclude;
import com.fasterxml.jackson.annotation.JsonProperty;
import javax.validation.constraints.Max;
import javax.validation.constraints.Min;
import lombok.AllArgsConstructor;
import lombok.Data;
import lombok.NoArgsConstructor;
import lombok.experimental.SuperBuilder;

/**
 * @author lzhpo
 */
@Data
@SuperBuilder
@NoArgsConstructor
@AllArgsConstructor
@JsonInclude(JsonInclude.Include.NON_NULL)
public class CommonConfig {

    /**
     * How many edits to generate for the input and instruction.
     */
    private Integer n;

    /**
     * What sampling temperature to use, between 0 and 2.
     *
     * Higher values like 0.8 will make the output more random,
     * while lower values like 0.2 will make it more focused and deterministic.
     *
     * 
We generally recommend altering this or top_p but not both.
     */
    @Min(0)
    @Max(2)
    private Number temperature;

    /**
     * An alternative to sampling with temperature, called nucleus sampling,
     * where the model considers the results of the tokens with top_p probability mass.
     * So 0.1 means only the tokens comprising the top 10% probability mass are considered.
     *
     * We generally recommend altering this or temperature but not both.
     */
    @JsonProperty("top_p")
    private Number topP;
}