305 lines
10 KiB
TypeScript
305 lines
10 KiB
TypeScript
import { OptionRealmService } from '@/define/db/service/optionService'
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import { OptionKeyName } from '@/define/enum/option'
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import { optionSerialization } from '../option/optionSerialization'
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import { SettingModal } from '@/define/model/setting'
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import { isEmpty } from 'lodash'
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import { GetOpenAISuccessResponse } from '@/define/response/openAIResponse'
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import { GetApiDefineDataById } from '@/define/data/apiData'
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import axios from 'axios'
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import { RetryWithBackoff } from '@/define/Tools/common'
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import { Book } from '@/define/model/book/book'
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import { AiInferenceModelModel, GetAIPromptOptionByValue } from '@/define/data/aiData/aiData'
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/**
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* AI推理通用工具类
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*
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* 该类提供了与AI推理相关的各种通用功能，包括:
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* - 初始化和获取推理设置
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* - 获取API提供商和模型信息
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* - 文本中占位符替换
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* - 获取上下文数据
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* - 构建请求消息
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* - 执行推理请求
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*
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* 主要用于处理小说分镜任务的AI推理流程，负责构建请求、发送请求
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* 和处理响应数据。
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*
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* @class AiReasonCommon
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* @example
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* const aiReason = new AiReasonCommon();
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* await aiReason.GetAISetting();
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* const result = await aiReason.OriginalInferencePrompt(taskDetail, allDetails, 2, characterData);
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*/
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export class AiReasonCommon {
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optionRealmService!: OptionRealmService
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aiReasonSetting!: SettingModal.InferenceAISettings
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/**
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* * 初始化 AiReasonCommon 类的实例
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* @returns {Promise<void>} - 返回一个 Promise 对象，表示初始化操作的完成状态
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*/
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async InitAiReasonCommon(): Promise<void> {
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if (!this.optionRealmService) {
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this.optionRealmService = await OptionRealmService.getInstance()
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}
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}
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/**
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* 获取推理设置
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* @returns {Promise<void>} - 返回一个 Promise 对象，表示获取操作的完成状态
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* @throws {Error} - 如果推理设置不完整，则抛出错误
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*/
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async GetAISetting(): Promise<void> {
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await this.InitAiReasonCommon()
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let res = this.optionRealmService.GetOptionByKey(OptionKeyName.InferenceAI.InferenceSetting)
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let aiReasonSetting = optionSerialization<SettingModal.InferenceAISettings>(
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res,
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'‘设置-> 推理设置’'
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)
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if (
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isEmpty(aiReasonSetting.apiProvider) ||
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isEmpty(aiReasonSetting.apiToken) ||
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isEmpty(aiReasonSetting.inferenceModel) ||
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isEmpty(aiReasonSetting.aiPromptValue)
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) {
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throw new Error(
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'请检查 ‘设置-> 推理设置’ 的API提供商、API令牌、推理模型、推理模式等是不是存在！'
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)
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}
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this.aiReasonSetting = aiReasonSetting
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}
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/**
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* 获取当前的API提供商信息
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* @returns
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*/
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GetAPIProviderMessage() {
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let apiProviders = GetApiDefineDataById(this.aiReasonSetting.apiProvider)
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return apiProviders
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}
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/**
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* 获取当前的推理模型信息
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* @returns {any} - 返回当前的推理模型信息
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* @throws {Error} - 如果推理模型不存在，则抛出错误
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*/
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GetInferenceModelMessage(): AiInferenceModelModel {
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let selectInferenceModel = GetAIPromptOptionByValue(this.aiReasonSetting.aiPromptValue)
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if (isEmpty(selectInferenceModel)) {
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throw new Error('请检查推理模型是否存在！')
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}
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return selectInferenceModel
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}
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/**
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* 替换字符串中的占位符为指定值
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*
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* 此方法查找字符串中所有格式为 {key} 的占位符，
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* 并用 replacements 对象中对应的值进行替换。
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*
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* @param {string} content - 包含占位符的原始字符串
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* @param {Record<string, string>} replacements - 键值对对象，键是要替换的占位符，值是替换内容
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* @returns {string} 完成所有占位符替换后的字符串
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*
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* @example
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* // 返回 "你好，张三，今天是星期一"
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* replaceObject("你好，{name}，今天是{day}", { name: "张三", day: "星期一" })
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*/
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replaceObject(content: string, replacements: Record<string, string>): string {
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let result = content
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for (let key in replacements) {
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result = result.replaceAll(`{${key}}`, replacements[key])
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}
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return result
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}
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/**
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* 替换消息对象数组中的占位符
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*
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* 此方法用于批量处理 OpenAI 请求消息数组，对每个消息对象的 content 字段
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* 进行占位符替换。常用于在发送 AI 推理请求前，将消息模板中的占位符
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* 替换为实际的动态内容。
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*
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* @param {OpenAIRequest.RequestMessage[]} message - OpenAI 请求消息数组
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* 每个消息对象包含 role (角色) 和 content (内容) 字段
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* @param {Record<string, string>} replacements - 键值对对象，键是要替换的占位符名，值是替换内容
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* @returns {OpenAIRequest.RequestMessage[]} 完成占位符替换后的新消息数组
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*
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* @example
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* const messages = [
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* { role: 'system', content: '你是一个{role}，擅长{skill}' },
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* { role: 'user', content: '请帮我{task}' }
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* ];
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* const replacements = {
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* role: '小说分析师',
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* skill: '情节分析',
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* task: '分析这段文字的情感色彩'
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* };
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* // 返回替换后的消息数组
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* const result = replaceMessageObject(messages, replacements);
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*
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* @see replaceObject - 单个字符串的占位符替换方法
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*/
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replaceMessageObject(
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messages: OpenAIRequest.RequestMessage[],
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replacements: Record<string, string>
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): OpenAIRequest.RequestMessage[] {
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// 使用 map 方法遍历消息数组，对每个消息对象进行处理
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return messages.map((item) => ({
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// 保持原有的所有属性（使用扩展运算符）
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...item,
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// 仅对 content 字段进行占位符替换处理
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content: this.replaceObject(item.content, replacements)
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}))
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}
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/**
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* 获取当前分镜的上下文数据
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* @param currentBookTaskDetail 当前分镜数据
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* @param bookTaskDetails 所有的小说分镜数据
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* @param contextCount 上下文行数
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*/
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GetBookTaskDetailContextData(
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currentBookTaskDetail: Book.SelectBookTaskDetail,
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bookTaskDetails: Book.SelectBookTaskDetail[],
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contextCount: number
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): string {
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let prefix = ''
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// 拼接一个word
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let i = (currentBookTaskDetail.no as number) - 1
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if (i <= contextCount) {
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prefix = bookTaskDetails
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.filter((_item, index) => index < i)
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.map((item) => item.afterGpt)
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.join('\r\n')
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} else if (i > contextCount) {
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prefix = bookTaskDetails
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.filter((_item, index) => i - index <= contextCount && i - index > 0)
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.map((item) => item.afterGpt)
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.join('\r\n')
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}
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let suffix = ''
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let o_i = bookTaskDetails.length - i
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if (o_i <= contextCount) {
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suffix = bookTaskDetails
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.filter((_item, index) => index > i)
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.map((item) => item.afterGpt)
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.join('\r\n')
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} else if (o_i > contextCount) {
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suffix = bookTaskDetails
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.filter((_item, index) => index - i <= contextCount && index - i > 0)
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.map((item) => item.afterGpt)
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.join('\r\n')
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}
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return `${prefix}\r\n${currentBookTaskDetail.afterGpt}\r\n${suffix}`
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}
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/**
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* 发起推理请求
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* @description 该方法用于发起推理请求，获取推理结果。包含重试机制和错误处理。
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*
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* @param {OpenAISuccessResponse} message - 要发送的消息对象
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* @returns {Promise<string>} - 返回一个 Promise 对象，表示获取操作的完成状态
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* @throws {Error} - 如果推理设置不完整，则抛出错误
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* @throws {Error} - 如果请求失败，则抛出错误
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* @throws {Error} - 如果响应数据格式不正确，则抛出错误
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*
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*/
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async FetchGpt(message: any, option: any = {}): Promise<string> {
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try {
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let data = {
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model: this.aiReasonSetting.inferenceModel,
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messages: message,
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...option
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}
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let apiProvider = this.GetAPIProviderMessage()
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let config = {
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method: 'post',
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maxBodyLength: Infinity,
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url: apiProvider.gpt_url,
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headers: {
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Authorization: `Bearer ${this.aiReasonSetting.apiToken}`,
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'Content-Type': 'application/json'
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},
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data: JSON.stringify(data)
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}
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let res = await RetryWithBackoff(
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async () => {
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return await axios.request(config)
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},
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5,
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2000
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)
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let content = GetOpenAISuccessResponse(res.data)
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// this.GetResponseContent(res, this.gptUrl)
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return content
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} catch (error) {
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throw error
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}
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}
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/**
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* 原创推理提示词数据
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* @param currentBookTaskDetail 要推理的小说分镜任务
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* @param bookTaskDetails 所有的小说分镜任务
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* @param contextCount 上下文的数量
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* @param autoAnalyzeCharacter 自动分析的角色数据字符串
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*/
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async OriginalInferencePrompt(
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currentBookTaskDetail: Book.SelectBookTaskDetail,
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bookTaskDetails: Book.SelectBookTaskDetail[],
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contextCount: number,
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characterString: string,
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sceneString: string
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) {
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await this.GetAISetting()
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// 获取当前的推理模式信息
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let selectInferenceModel = this.GetInferenceModelMessage()
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// 内置模式
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let context = this.GetBookTaskDetailContextData(
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currentBookTaskDetail,
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bookTaskDetails,
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contextCount
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)
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if (isEmpty(characterString) && selectInferenceModel.mustCharacter) {
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throw new Error('当前模式需要提前分析或者设置角色场景数据，请先分析角色/场景数据！')
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}
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let requestBody = selectInferenceModel.requestBody
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if (requestBody == null) {
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throw new Error('未找到对应的分镜预设的请求数据，请检查')
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}
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requestBody.messages = this.replaceMessageObject(requestBody.messages, {
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contextContent: context,
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textContent: currentBookTaskDetail.afterGpt ?? '',
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characterContent: characterString,
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sceneContent: sceneString,
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characterSceneContent: characterString + '\n' + sceneString,
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wordCount: '40'
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})
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delete requestBody.model
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// 开始请求
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let res = await this.FetchGpt(requestBody.messages, requestBody)
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if (res) {
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// 处理返回的数据，删除部分数据
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res = res
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.replace(/\)\s*\(/g, ', ')
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.replace(/^\(/, '')
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.replace(/\)$/, '')
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.replaceAll('*', '')
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.replaceAll('--', ' ')
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}
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return res
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}
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}
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