1389 lines
48 KiB
TypeScript
1389 lines
48 KiB
TypeScript
import { get, writable } from "svelte/store";
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import { DataBase, setDatabase, type character, type MessageGenerationInfo, type Chat } from "../storage/database";
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import { CharEmotion, selectedCharID } from "../stores";
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import { ChatTokenizer, tokenize, tokenizeNum } from "../tokenizer";
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import { language } from "../../lang";
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import { alertError } from "../alert";
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import { loadLoreBookPrompt } from "./lorebook";
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import { findCharacterbyId, getAuthorNoteDefaultText } from "../util";
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import { requestChatData } from "./request";
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import { stableDiff } from "./stableDiff";
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import { processScript, processScriptFull, risuChatParser } from "./scripts";
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import { exampleMessage } from "./exampleMessages";
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import { sayTTS } from "./tts";
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import { supaMemory } from "./memory/supaMemory";
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import { v4 } from "uuid";
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import { cloneDeep } from "lodash";
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import { groupOrder } from "./group";
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import { runTrigger } from "./triggers";
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import { HypaProcesser } from "./memory/hypamemory";
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import { additionalInformations } from "./embedding/addinfo";
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import { cipherChat, decipherChat } from "./cipherChat";
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import { getInlayImage, supportsInlayImage } from "./files/image";
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import { getGenerationModelString } from "./models/modelString";
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import { sendPeerChar } from "../sync/multiuser";
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import { runInlayScreen } from "./inlayScreen";
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import { runCharacterJS } from "../plugins/embedscript";
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import { addRerolls } from "./prereroll";
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import { runImageEmbedding } from "./transformers";
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export interface OpenAIChat{
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role: 'system'|'user'|'assistant'|'function'
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content: string
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memo?:string
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name?:string
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removable?:boolean
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attr?:string[]
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multimodals?: MultiModal[]
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}
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export interface MultiModal{
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type:'image'|'video'
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base64:string,
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height?:number,
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width?:number
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}
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export interface OpenAIChatFull extends OpenAIChat{
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function_call?: {
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name: string
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arguments:string
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}
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}
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export const doingChat = writable(false)
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export const chatProcessStage = writable(0)
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export const abortChat = writable(false)
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export async function sendChat(chatProcessIndex = -1,arg:{chatAdditonalTokens?:number,signal?:AbortSignal,continue?:boolean} = {}):Promise<boolean> {
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chatProcessStage.set(0)
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const abortSignal = arg.signal ?? (new AbortController()).signal
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let isAborted = false
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let findCharCache:{[key:string]:character} = {}
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function findCharacterbyIdwithCache(id:string){
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const d = findCharCache[id]
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if(!!d){
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return d
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}
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else{
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const r = findCharacterbyId(id)
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findCharCache[id] = r
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return r
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}
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}
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function runCurrentChatFunction(chat:Chat){
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chat.message = chat.message.map((v) => {
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v.data = risuChatParser(v.data, {chara: currentChar, runVar: true})
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return v
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})
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return chat
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}
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function reformatContent(data:string){
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if(chatProcessIndex === -1){
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return data.trim()
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}
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return data.trim()
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}
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let isDoing = get(doingChat)
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if(isDoing){
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if(chatProcessIndex === -1){
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return false
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}
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}
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doingChat.set(true)
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let db = get(DataBase)
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let selectedChar = get(selectedCharID)
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const nowChatroom = db.characters[selectedChar]
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let selectedChat = nowChatroom.chatPage
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nowChatroom.chats[nowChatroom.chatPage].message = nowChatroom.chats[nowChatroom.chatPage].message.map((v) => {
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v.chatId = v.chatId ?? v4()
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return v
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})
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let currentChar:character
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let caculatedChatTokens = 0
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if(db.aiModel.startsWith('gpt')){
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caculatedChatTokens += 5
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}
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else{
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caculatedChatTokens += 3
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}
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if(nowChatroom.type === 'group'){
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if(chatProcessIndex === -1){
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const charNames =nowChatroom.characters.map((v) => findCharacterbyIdwithCache(v).name)
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const messages = nowChatroom.chats[nowChatroom.chatPage].message
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const lastMessage = messages[messages.length-1]
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let order = nowChatroom.characters.map((v,i) => {
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return {
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id: v,
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talkness: nowChatroom.characterActive[i] ? nowChatroom.characterTalks[i] : -1,
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index: i
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}
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}).filter((v) => {
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return v.talkness > 0
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})
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if(!nowChatroom.orderByOrder){
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order = groupOrder(order, lastMessage?.data).filter((v) => {
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if(v.id === lastMessage?.saying){
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return false
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}
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return true
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})
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}
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for(let i=0;i<order.length;i++){
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const r = await sendChat(order[i].index, {
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chatAdditonalTokens: caculatedChatTokens,
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signal: abortSignal
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})
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if(!r){
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return false
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}
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}
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return true
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}
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else{
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currentChar = findCharacterbyIdwithCache(nowChatroom.characters[chatProcessIndex])
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if(!currentChar){
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alertError(`cannot find character: ${nowChatroom.characters[chatProcessIndex]}`)
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return false
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}
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}
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}
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else{
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currentChar = nowChatroom
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}
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let chatAdditonalTokens = arg.chatAdditonalTokens ?? caculatedChatTokens
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const tokenizer = new ChatTokenizer(chatAdditonalTokens, db.aiModel.startsWith('gpt') ? 'noName' : 'name')
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let currentChat = runCurrentChatFunction(nowChatroom.chats[selectedChat])
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nowChatroom.chats[selectedChat] = currentChat
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let maxContextTokens = db.maxContext
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if(db.aiModel === 'gpt35'){
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if(maxContextTokens > 4000){
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maxContextTokens = 4000
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}
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}
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if(db.aiModel === 'gpt35_16k' || db.aiModel === 'gpt35_16k_0613'){
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if(maxContextTokens > 16000){
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maxContextTokens = 16000
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}
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}
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if(db.aiModel === 'gpt4'){
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if(maxContextTokens > 8000){
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maxContextTokens = 8000
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}
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}
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if(db.aiModel === 'deepai'){
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if(maxContextTokens > 3000){
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maxContextTokens = 3000
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}
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}
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chatProcessStage.set(1)
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let unformated = {
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'main':([] as OpenAIChat[]),
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'jailbreak':([] as OpenAIChat[]),
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'chats':([] as OpenAIChat[]),
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'lorebook':([] as OpenAIChat[]),
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'globalNote':([] as OpenAIChat[]),
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'authorNote':([] as OpenAIChat[]),
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'lastChat':([] as OpenAIChat[]),
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'description':([] as OpenAIChat[]),
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'postEverything':([] as OpenAIChat[]),
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'personaPrompt':([] as OpenAIChat[])
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}
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let promptTemplate = cloneDeep(db.promptTemplate)
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const usingPromptTemplate = !!promptTemplate
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if(promptTemplate){
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let hasPostEverything = false
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for(const card of promptTemplate){
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if(card.type === 'postEverything'){
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hasPostEverything = true
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break
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}
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}
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if(!hasPostEverything){
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promptTemplate.push({
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type: 'postEverything'
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})
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}
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}
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if(currentChar.utilityBot && (!(usingPromptTemplate && db.proomptSettings.utilOverride))){
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promptTemplate = [
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{
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"type": "plain",
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"text": "",
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"role": "system",
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"type2": "main"
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},
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{
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"type": "description",
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},
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{
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"type": "lorebook",
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},
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{
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"type": "chat",
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"rangeStart": 0,
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"rangeEnd": "end"
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},
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{
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"type": "plain",
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"text": "",
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"role": "system",
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"type2": "globalNote"
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},
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{
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'type': "postEverything"
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}
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]
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}
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if((!currentChar.utilityBot) && (!promptTemplate)){
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const mainp = currentChar.systemPrompt?.replaceAll('{{original}}', db.mainPrompt) || db.mainPrompt
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function formatPrompt(data:string){
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if(!data.startsWith('@@')){
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data = "@@system\n" + data
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}
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const parts = data.split(/@@@?(user|assistant|system)\n/);
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// Initialize empty array for the chat objects
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const chatObjects: OpenAIChat[] = [];
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// Loop through the parts array two elements at a time
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for (let i = 1; i < parts.length; i += 2) {
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const role = parts[i] as 'user' | 'assistant' | 'system';
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const content = parts[i + 1]?.trim() || '';
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chatObjects.push({ role, content });
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}
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return chatObjects;
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}
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unformated.main.push(...formatPrompt(risuChatParser(mainp + ((db.additionalPrompt === '' || (!db.promptPreprocess)) ? '' : `\n${db.additionalPrompt}`), {chara: currentChar})))
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if(db.jailbreakToggle){
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unformated.jailbreak.push(...formatPrompt(risuChatParser(db.jailbreak, {chara: currentChar})))
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}
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unformated.globalNote.push(...formatPrompt(risuChatParser(currentChar.replaceGlobalNote?.replaceAll('{{original}}', db.globalNote) || db.globalNote, {chara:currentChar})))
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}
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if(currentChat.note){
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unformated.authorNote.push({
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role: 'system',
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content: risuChatParser(currentChat.note, {chara: currentChar})
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})
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}
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else if(getAuthorNoteDefaultText() !== ''){
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unformated.authorNote.push({
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role: 'system',
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content: risuChatParser(getAuthorNoteDefaultText(), {chara: currentChar})
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})
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}
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if(db.chainOfThought && (!(usingPromptTemplate && db.proomptSettings.customChainOfThought))){
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unformated.postEverything.push({
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role: 'system',
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content: `<instruction> - before respond everything, Think step by step as a ai assistant how would you respond inside <Thoughts> xml tag. this must be less than 5 paragraphs.</instruction>`
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})
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}
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{
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let description = risuChatParser((db.promptPreprocess ? db.descriptionPrefix: '') + currentChar.desc, {chara: currentChar})
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const additionalInfo = await additionalInformations(currentChar, currentChat)
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if(additionalInfo){
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description += '\n\n' + risuChatParser(additionalInfo, {chara:currentChar})
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}
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if(currentChar.personality){
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description += risuChatParser("\n\nDescription of {{char}}: " + currentChar.personality, {chara: currentChar})
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}
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if(currentChar.scenario){
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description += risuChatParser("\n\nCircumstances and context of the dialogue: " + currentChar.scenario, {chara: currentChar})
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}
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unformated.description.push({
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role: 'system',
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content: description
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})
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if(nowChatroom.type === 'group'){
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const systemMsg = `[Write the next reply only as ${currentChar.name}]`
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unformated.postEverything.push({
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role: 'system',
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content: systemMsg
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})
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}
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}
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const lorepmt = await loadLoreBookPrompt()
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unformated.lorebook.push({
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role: 'system',
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content: risuChatParser(lorepmt.act, {chara: currentChar})
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})
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if(db.personaPrompt){
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unformated.personaPrompt.push({
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role: 'system',
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content: risuChatParser(db.personaPrompt, {chara: currentChar})
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})
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}
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if(currentChar.inlayViewScreen){
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if(currentChar.viewScreen === 'emotion'){
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unformated.postEverything.push({
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role: 'system',
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content: currentChar.newGenData.emotionInstructions.replaceAll('{{slot}}', currentChar.emotionImages.map((v) => v[0]).join(', '))
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})
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}
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if(currentChar.viewScreen === 'imggen'){
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unformated.postEverything.push({
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role: 'system',
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content: currentChar.newGenData.instructions
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})
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}
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}
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if(lorepmt.special_act){
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unformated.postEverything.push({
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role: 'system',
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content: risuChatParser(lorepmt.special_act, {chara: currentChar})
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})
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}
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//await tokenize currernt
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let currentTokens = db.maxResponse
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let supaMemoryCardUsed = false
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//for unexpected error
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currentTokens += 50
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if(promptTemplate){
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const template = promptTemplate
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async function tokenizeChatArray(chats:OpenAIChat[]){
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for(const chat of chats){
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const tokens = await tokenizer.tokenizeChat(chat)
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currentTokens += tokens
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}
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}
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for(const card of template){
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switch(card.type){
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case 'persona':{
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let pmt = cloneDeep(unformated.personaPrompt)
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if(card.innerFormat && pmt.length > 0){
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for(let i=0;i<pmt.length;i++){
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pmt[i].content = risuChatParser(card.innerFormat, {chara: currentChar}).replace('{{slot}}', pmt[i].content)
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}
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}
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await tokenizeChatArray(pmt)
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break
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}
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case 'description':{
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let pmt = cloneDeep(unformated.description)
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if(card.innerFormat && pmt.length > 0){
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for(let i=0;i<pmt.length;i++){
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pmt[i].content = risuChatParser(card.innerFormat, {chara: currentChar}).replace('{{slot}}', pmt[i].content)
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}
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}
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await tokenizeChatArray(pmt)
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break
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}
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case 'authornote':{
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let pmt = cloneDeep(unformated.authorNote)
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if(card.innerFormat && pmt.length > 0){
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for(let i=0;i<pmt.length;i++){
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pmt[i].content = risuChatParser(card.innerFormat, {chara: currentChar}).replace('{{slot}}', pmt[i].content || card.defaultText || '')
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}
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}
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await tokenizeChatArray(pmt)
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break
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}
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case 'lorebook':{
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await tokenizeChatArray(unformated.lorebook)
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break
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}
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case 'postEverything':{
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await tokenizeChatArray(unformated.postEverything)
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if(usingPromptTemplate && db.proomptSettings.postEndInnerFormat){
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await tokenizeChatArray([{
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role: 'system',
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content: db.proomptSettings.postEndInnerFormat
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}])
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}
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break
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}
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case 'plain':
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case 'jailbreak':
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case 'cot':{
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if((!db.jailbreakToggle) && (card.type === 'jailbreak')){
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continue
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}
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if((!db.chainOfThought) && (card.type === 'cot')){
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continue
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}
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const convertRole = {
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"system": "system",
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"user": "user",
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"bot": "assistant"
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} as const
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let content = card.text
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if(card.type2 === 'globalNote'){
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content = (risuChatParser(currentChar.replaceGlobalNote?.replaceAll('{{original}}', content) || content, {chara: currentChar, role: card.role}))
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}
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else if(card.type2 === 'main'){
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content = (risuChatParser(content, {chara: currentChar, role: card.role}))
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}
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else{
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content = risuChatParser(content, {chara: currentChar, role: card.role})
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}
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const prompt:OpenAIChat ={
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role: convertRole[card.role],
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content: content
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}
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await tokenizeChatArray([prompt])
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break
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}
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case 'chat':{
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let start = card.rangeStart
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let end = (card.rangeEnd === 'end') ? unformated.chats.length : card.rangeEnd
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if(start < 0){
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start = unformated.chats.length + start
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if(start < 0){
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start = 0
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}
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}
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if(end < 0){
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end = unformated.chats.length + end
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if(end < 0){
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end = 0
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}
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}
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if(start >= end){
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break
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}
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let chats = unformated.chats.slice(start, end)
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if(usingPromptTemplate && db.proomptSettings.sendChatAsSystem && (!card.chatAsOriginalOnSystem)){
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chats = systemizeChat(chats)
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}
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await tokenizeChatArray(chats)
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break
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}
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case 'memory':{
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supaMemoryCardUsed = true
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break
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}
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}
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}
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}
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else{
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for(const key in unformated){
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const chats = unformated[key] as OpenAIChat[]
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for(const chat of chats){
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currentTokens += await tokenizer.tokenizeChat(chat)
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}
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}
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}
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const examples = exampleMessage(currentChar, db.username)
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for(const example of examples){
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currentTokens += await tokenizer.tokenizeChat(example)
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}
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let chats:OpenAIChat[] = examples
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if(!db.aiModel.startsWith('novelai')){
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chats.push({
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role: 'system',
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content: '[Start a new chat]',
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memo: "NewChat"
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})
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}
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if(nowChatroom.type !== 'group'){
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const firstMsg = nowChatroom.firstMsgIndex === -1 ? nowChatroom.firstMessage : nowChatroom.alternateGreetings[nowChatroom.firstMsgIndex]
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|
|
const chat:OpenAIChat = {
|
|
role: 'assistant',
|
|
content: await (processScript(nowChatroom,
|
|
risuChatParser(firstMsg, {chara: currentChar}),
|
|
'editprocess'))
|
|
}
|
|
|
|
if(usingPromptTemplate && db.proomptSettings.sendName){
|
|
chat.content = `${currentChar.name}: ${chat.content}`
|
|
chat.attr = ['nameAdded']
|
|
}
|
|
chats.push(chat)
|
|
currentTokens += await tokenizer.tokenizeChat(chat)
|
|
}
|
|
|
|
let ms = currentChat.message
|
|
|
|
const triggerResult = await runTrigger(currentChar, 'start', {chat: currentChat})
|
|
if(triggerResult){
|
|
currentChat = triggerResult.chat
|
|
ms = currentChat.message
|
|
currentTokens += triggerResult.tokens
|
|
if(triggerResult.stopSending){
|
|
doingChat.set(false)
|
|
return false
|
|
}
|
|
}
|
|
|
|
let index = 0
|
|
for(const msg of ms){
|
|
let formatedChat = await processScript(nowChatroom,risuChatParser(msg.data, {chara: currentChar, role: msg.role}), 'editprocess')
|
|
let name = ''
|
|
if(msg.role === 'char'){
|
|
if(msg.saying){
|
|
name = `${findCharacterbyIdwithCache(msg.saying).name}`
|
|
}
|
|
else{
|
|
name = `${currentChar.name}`
|
|
}
|
|
}
|
|
else if(msg.role === 'user'){
|
|
name = `${db.username}`
|
|
}
|
|
if(!msg.chatId){
|
|
msg.chatId = v4()
|
|
}
|
|
let inlays:string[] = []
|
|
if(msg.role === 'char'){
|
|
formatedChat = formatedChat.replace(/{{inlay::(.+?)}}/g, '')
|
|
}
|
|
else{
|
|
const inlayMatch = formatedChat.match(/{{inlay::(.+?)}}/g)
|
|
if(inlayMatch){
|
|
for(const inlay of inlayMatch){
|
|
inlays.push(inlay)
|
|
}
|
|
}
|
|
}
|
|
|
|
let multimodal:MultiModal[] = []
|
|
if(inlays.length > 0){
|
|
for(const inlay of inlays){
|
|
const inlayName = inlay.replace('{{inlay::', '').replace('}}', '')
|
|
const inlayData = await getInlayImage(inlayName)
|
|
if(inlayData){
|
|
if(supportsInlayImage()){
|
|
multimodal.push({
|
|
type: 'image',
|
|
base64: inlayData.data,
|
|
width: inlayData.width,
|
|
height: inlayData.height
|
|
})
|
|
}
|
|
else{
|
|
const captionResult = await runImageEmbedding(inlayData.data)
|
|
formatedChat += `[${captionResult[0].generated_text}]`
|
|
}
|
|
}
|
|
formatedChat = formatedChat.replace(inlay, '')
|
|
}
|
|
}
|
|
|
|
let attr:string[] = []
|
|
|
|
if(nowChatroom.type === 'group' || (usingPromptTemplate && db.proomptSettings.sendName)){
|
|
formatedChat = name + ': ' + formatedChat
|
|
attr.push('nameAdded')
|
|
}
|
|
if(usingPromptTemplate && db.proomptSettings.customChainOfThought && db.proomptSettings.maxThoughtTagDepth !== -1){
|
|
const depth = ms.length - index
|
|
if(depth >= db.proomptSettings.maxThoughtTagDepth){
|
|
formatedChat = formatedChat.replace(/<Thoughts>(.+?)<\/Thoughts>/gm, '')
|
|
}
|
|
}
|
|
|
|
const chat:OpenAIChat = {
|
|
role: msg.role === 'user' ? 'user' : 'assistant',
|
|
content: formatedChat,
|
|
memo: msg.chatId,
|
|
attr: attr,
|
|
multimodals: multimodal
|
|
}
|
|
if(chat.multimodals.length === 0){
|
|
delete chat.multimodals
|
|
}
|
|
chats.push(chat)
|
|
currentTokens += await tokenizer.tokenizeChat(chat)
|
|
index++
|
|
}
|
|
|
|
if(nowChatroom.supaMemory && db.supaMemoryType !== 'none'){
|
|
chatProcessStage.set(2)
|
|
const sp = await supaMemory(chats, currentTokens, maxContextTokens, currentChat, nowChatroom, tokenizer, {
|
|
asHyper: db.hypaMemory
|
|
})
|
|
if(sp.error){
|
|
alertError(sp.error)
|
|
return false
|
|
}
|
|
chats = sp.chats
|
|
currentTokens = sp.currentTokens
|
|
currentChat.supaMemoryData = sp.memory ?? currentChat.supaMemoryData
|
|
db.characters[selectedChar].chats[selectedChat].supaMemoryData = currentChat.supaMemoryData
|
|
console.log(currentChat.supaMemoryData)
|
|
DataBase.set(db)
|
|
currentChat.lastMemory = sp.lastId ?? currentChat.lastMemory
|
|
chatProcessStage.set(1)
|
|
}
|
|
else{
|
|
while(currentTokens > maxContextTokens){
|
|
if(chats.length <= 1){
|
|
alertError(language.errors.toomuchtoken + "\n\nRequired Tokens: " + currentTokens)
|
|
|
|
return false
|
|
}
|
|
|
|
currentTokens -= await tokenizer.tokenizeChat(chats[0])
|
|
chats.splice(0, 1)
|
|
}
|
|
currentChat.lastMemory = chats[0].memo
|
|
}
|
|
|
|
let biases:[string,number][] = db.bias.concat(currentChar.bias).map((v) => {
|
|
return [risuChatParser(v[0].replaceAll("\\n","\n"), {chara: currentChar}),v[1]]
|
|
})
|
|
|
|
let memories:OpenAIChat[] = []
|
|
|
|
|
|
|
|
if(!promptTemplate){
|
|
unformated.lastChat.push(chats[chats.length - 1])
|
|
chats.splice(chats.length - 1, 1)
|
|
}
|
|
|
|
unformated.chats = chats.map((v) => {
|
|
if(v.memo !== 'supaMemory' && v.memo !== 'hypaMemory'){
|
|
v.removable = true
|
|
}
|
|
else if(supaMemoryCardUsed){
|
|
memories.push(v)
|
|
return {
|
|
role: 'system',
|
|
content: '',
|
|
} as const
|
|
}
|
|
return v
|
|
}).filter((v) => {
|
|
return v.content !== ''
|
|
})
|
|
|
|
|
|
if(triggerResult){
|
|
if(triggerResult.additonalSysPrompt.promptend){
|
|
unformated.postEverything.push({
|
|
role: 'system',
|
|
content: triggerResult.additonalSysPrompt.promptend
|
|
})
|
|
}
|
|
if(triggerResult.additonalSysPrompt.historyend){
|
|
unformated.lastChat.push({
|
|
role: 'system',
|
|
content: triggerResult.additonalSysPrompt.historyend
|
|
})
|
|
}
|
|
if(triggerResult.additonalSysPrompt.start){
|
|
unformated.lastChat.unshift({
|
|
role: 'system',
|
|
content: triggerResult.additonalSysPrompt.start
|
|
})
|
|
}
|
|
}
|
|
|
|
|
|
//make into one
|
|
|
|
let formated:OpenAIChat[] = []
|
|
const formatOrder = cloneDeep(db.formatingOrder)
|
|
if(formatOrder){
|
|
formatOrder.push('postEverything')
|
|
}
|
|
|
|
//continue chat model
|
|
if(arg.continue && (db.aiModel.startsWith('claude') || db.aiModel.startsWith('gpt') || db.aiModel.startsWith('openrouter') || db.aiModel.startsWith('reverse_proxy'))){
|
|
unformated.postEverything.push({
|
|
role: 'system',
|
|
content: '[Continue the last response]'
|
|
})
|
|
}
|
|
|
|
function pushPrompts(cha:OpenAIChat[]){
|
|
for(const chat of cha){
|
|
if(!chat.content.trim()){
|
|
continue
|
|
}
|
|
if(!(db.aiModel.startsWith('gpt') || db.aiModel.startsWith('claude') || db.aiModel === 'openrouter' || db.aiModel === 'reverse_proxy')){
|
|
formated.push(chat)
|
|
continue
|
|
}
|
|
if(chat.role === 'system'){
|
|
const endf = formated.at(-1)
|
|
if(endf && endf.role === 'system' && endf.memo === chat.memo && endf.name === chat.name){
|
|
formated[formated.length - 1].content += '\n\n' + chat.content
|
|
}
|
|
else{
|
|
formated.push(chat)
|
|
}
|
|
formated.at(-1).content += ''
|
|
}
|
|
else{
|
|
formated.push(chat)
|
|
}
|
|
}
|
|
}
|
|
|
|
if(promptTemplate){
|
|
const template = promptTemplate
|
|
|
|
for(const card of template){
|
|
switch(card.type){
|
|
case 'persona':{
|
|
let pmt = cloneDeep(unformated.personaPrompt)
|
|
if(card.innerFormat && pmt.length > 0){
|
|
for(let i=0;i<pmt.length;i++){
|
|
pmt[i].content = risuChatParser(card.innerFormat, {chara: currentChar}).replace('{{slot}}', pmt[i].content)
|
|
}
|
|
}
|
|
|
|
pushPrompts(pmt)
|
|
break
|
|
}
|
|
case 'description':{
|
|
let pmt = cloneDeep(unformated.description)
|
|
if(card.innerFormat && pmt.length > 0){
|
|
for(let i=0;i<pmt.length;i++){
|
|
pmt[i].content = risuChatParser(card.innerFormat, {chara: currentChar}).replace('{{slot}}', pmt[i].content)
|
|
}
|
|
}
|
|
|
|
pushPrompts(pmt)
|
|
break
|
|
}
|
|
case 'authornote':{
|
|
let pmt = cloneDeep(unformated.authorNote)
|
|
if(card.innerFormat && pmt.length > 0){
|
|
for(let i=0;i<pmt.length;i++){
|
|
pmt[i].content = risuChatParser(card.innerFormat, {chara: currentChar}).replace('{{slot}}', pmt[i].content || card.defaultText || '')
|
|
}
|
|
}
|
|
|
|
pushPrompts(pmt)
|
|
break
|
|
}
|
|
case 'lorebook':{
|
|
pushPrompts(unformated.lorebook)
|
|
break
|
|
}
|
|
case 'postEverything':{
|
|
pushPrompts(unformated.postEverything)
|
|
if(usingPromptTemplate && db.proomptSettings.postEndInnerFormat){
|
|
pushPrompts([{
|
|
role: 'system',
|
|
content: db.proomptSettings.postEndInnerFormat
|
|
}])
|
|
}
|
|
break
|
|
}
|
|
case 'plain':
|
|
case 'jailbreak':
|
|
case 'cot':{
|
|
if((!db.jailbreakToggle) && (card.type === 'jailbreak')){
|
|
continue
|
|
}
|
|
if((!db.chainOfThought) && (card.type === 'cot')){
|
|
continue
|
|
}
|
|
|
|
const convertRole = {
|
|
"system": "system",
|
|
"user": "user",
|
|
"bot": "assistant"
|
|
} as const
|
|
|
|
let content = card.text
|
|
|
|
if(card.type2 === 'globalNote'){
|
|
content = (risuChatParser(currentChar.replaceGlobalNote?.replaceAll('{{original}}', content) || content, {chara:currentChar, role: card.role}))
|
|
}
|
|
else if(card.type2 === 'main'){
|
|
content = (risuChatParser(content, {chara: currentChar, role: card.role}))
|
|
}
|
|
else{
|
|
content = risuChatParser(content, {chara: currentChar, role: card.role})
|
|
}
|
|
|
|
const prompt:OpenAIChat ={
|
|
role: convertRole[card.role],
|
|
content: content
|
|
}
|
|
|
|
pushPrompts([prompt])
|
|
break
|
|
}
|
|
case 'chat':{
|
|
let start = card.rangeStart
|
|
let end = (card.rangeEnd === 'end') ? unformated.chats.length : card.rangeEnd
|
|
if(start < 0){
|
|
start = unformated.chats.length + start
|
|
if(start < 0){
|
|
start = 0
|
|
}
|
|
}
|
|
if(end < 0){
|
|
end = unformated.chats.length + end
|
|
if(end < 0){
|
|
end = 0
|
|
}
|
|
}
|
|
|
|
if(start >= end){
|
|
break
|
|
}
|
|
|
|
let chats = unformated.chats.slice(start, end)
|
|
if(usingPromptTemplate && db.proomptSettings.sendChatAsSystem && (!card.chatAsOriginalOnSystem)){
|
|
chats = systemizeChat(chats)
|
|
}
|
|
pushPrompts(chats)
|
|
break
|
|
}
|
|
case 'memory':{
|
|
let pmt = cloneDeep(memories)
|
|
if(card.innerFormat && pmt.length > 0){
|
|
for(let i=0;i<pmt.length;i++){
|
|
pmt[i].content = risuChatParser(card.innerFormat, {chara: currentChar}).replace('{{slot}}', pmt[i].content)
|
|
}
|
|
}
|
|
|
|
pushPrompts(pmt)
|
|
}
|
|
}
|
|
}
|
|
}
|
|
else{
|
|
for(let i=0;i<formatOrder.length;i++){
|
|
const cha = unformated[formatOrder[i]]
|
|
pushPrompts(cha)
|
|
}
|
|
}
|
|
|
|
|
|
formated = formated.map((v) => {
|
|
v.content = v.content.trim()
|
|
return v
|
|
})
|
|
|
|
if(db.cipherChat){
|
|
formated = cipherChat(formated)
|
|
}
|
|
|
|
|
|
if(currentChar.depth_prompt && currentChar.depth_prompt.prompt && currentChar.depth_prompt.prompt.length > 0){
|
|
//depth_prompt
|
|
const depthPrompt = currentChar.depth_prompt
|
|
formated.splice(formated.length - depthPrompt.depth, 0, {
|
|
role: 'system',
|
|
content: risuChatParser(depthPrompt.prompt, {chara: currentChar})
|
|
})
|
|
}
|
|
|
|
formated = await runCharacterJS({
|
|
code: null,
|
|
mode: 'modifyRequestChat',
|
|
data: formated
|
|
})
|
|
|
|
//token rechecking
|
|
let inputTokens = 0
|
|
|
|
for(const chat of formated){
|
|
inputTokens += await tokenizer.tokenizeChat(chat)
|
|
}
|
|
|
|
if(inputTokens > maxContextTokens){
|
|
let pointer = 0
|
|
while(inputTokens > maxContextTokens){
|
|
if(pointer >= formated.length){
|
|
alertError(language.errors.toomuchtoken + "\n\nAt token rechecking. Required Tokens: " + inputTokens)
|
|
return false
|
|
}
|
|
if(formated[pointer].removable){
|
|
inputTokens -= await tokenizer.tokenizeChat(formated[pointer])
|
|
formated[pointer].content = ''
|
|
}
|
|
pointer++
|
|
}
|
|
formated = formated.filter((v) => {
|
|
return v.content !== ''
|
|
})
|
|
}
|
|
|
|
//estimate tokens
|
|
let outputTokens = db.maxResponse
|
|
if(inputTokens + outputTokens > maxContextTokens){
|
|
outputTokens = maxContextTokens - inputTokens
|
|
}
|
|
const generationId = v4()
|
|
const generationModel = getGenerationModelString()
|
|
|
|
const generationInfo:MessageGenerationInfo = {
|
|
model: generationModel,
|
|
generationId: generationId,
|
|
inputTokens: inputTokens,
|
|
outputTokens: outputTokens,
|
|
maxContext: maxContextTokens,
|
|
}
|
|
chatProcessStage.set(3)
|
|
const req = await requestChatData({
|
|
formated: formated,
|
|
biasString: biases,
|
|
currentChar: currentChar,
|
|
useStreaming: true,
|
|
isGroupChat: nowChatroom.type === 'group',
|
|
bias: {},
|
|
continue: arg.continue,
|
|
chatId: generationId
|
|
}, 'model', abortSignal)
|
|
|
|
let result = ''
|
|
let emoChanged = false
|
|
|
|
if(abortSignal.aborted === true){
|
|
return false
|
|
}
|
|
if(req.type === 'fail'){
|
|
alertError(req.result)
|
|
return false
|
|
}
|
|
else if(req.type === 'streaming'){
|
|
const reader = req.result.getReader()
|
|
let msgIndex = db.characters[selectedChar].chats[selectedChat].message.length
|
|
let prefix = ''
|
|
if(arg.continue){
|
|
msgIndex -= 1
|
|
prefix = db.characters[selectedChar].chats[selectedChat].message[msgIndex].data
|
|
}
|
|
else{
|
|
db.characters[selectedChar].chats[selectedChat].message.push({
|
|
role: 'char',
|
|
data: "",
|
|
saying: currentChar.chaId,
|
|
time: Date.now(),
|
|
generationInfo,
|
|
})
|
|
}
|
|
db.characters[selectedChar].chats[selectedChat].isStreaming = true
|
|
let lastResponseChunk:{[key:string]:string} = {}
|
|
while(abortSignal.aborted === false){
|
|
const readed = (await reader.read())
|
|
if(readed.value){
|
|
lastResponseChunk = readed.value
|
|
const firstChunkKey = Object.keys(lastResponseChunk)[0]
|
|
result = lastResponseChunk[firstChunkKey]
|
|
if(!result){
|
|
result = ''
|
|
}
|
|
if(db.cipherChat){
|
|
result = decipherChat(result)
|
|
}
|
|
const result2 = await processScriptFull(nowChatroom, reformatContent(prefix + result), 'editoutput', msgIndex)
|
|
db.characters[selectedChar].chats[selectedChat].message[msgIndex].data = result2.data
|
|
emoChanged = result2.emoChanged
|
|
db.characters[selectedChar].reloadKeys += 1
|
|
setDatabase(db)
|
|
}
|
|
if(readed.done){
|
|
db.characters[selectedChar].chats[selectedChat].isStreaming = false
|
|
db.characters[selectedChar].reloadKeys += 1
|
|
setDatabase(db)
|
|
break
|
|
}
|
|
}
|
|
|
|
addRerolls(generationId, Object.values(lastResponseChunk))
|
|
|
|
db.characters[selectedChar].chats[selectedChat] = runCurrentChatFunction(db.characters[selectedChar].chats[selectedChat])
|
|
currentChat = db.characters[selectedChar].chats[selectedChat]
|
|
const triggerResult = await runTrigger(currentChar, 'output', {chat:currentChat})
|
|
if(triggerResult && triggerResult.chat){
|
|
currentChat = triggerResult.chat
|
|
}
|
|
const inlayr = runInlayScreen(currentChar, currentChat.message[msgIndex].data)
|
|
currentChat.message[msgIndex].data = inlayr.text
|
|
db.characters[selectedChar].chats[selectedChat] = currentChat
|
|
setDatabase(db)
|
|
if(inlayr.promise){
|
|
const t = await inlayr.promise
|
|
currentChat.message[msgIndex].data = t
|
|
db.characters[selectedChar].chats[selectedChat] = currentChat
|
|
setDatabase(db)
|
|
}
|
|
await sayTTS(currentChar, result)
|
|
}
|
|
else{
|
|
const msgs = (req.type === 'success') ? [['char',req.result]] as const
|
|
: (req.type === 'multiline') ? req.result
|
|
: []
|
|
let mrerolls:string[] = []
|
|
for(let i=0;i<msgs.length;i++){
|
|
let msg = msgs[i]
|
|
let mess = msg[1]
|
|
if(db.cipherChat){
|
|
mess = decipherChat(result)
|
|
}
|
|
let msgIndex = db.characters[selectedChar].chats[selectedChat].message.length
|
|
let result2 = await processScriptFull(nowChatroom, reformatContent(mess), 'editoutput', msgIndex)
|
|
if(i === 0 && arg.continue){
|
|
msgIndex -= 1
|
|
let beforeChat = db.characters[selectedChar].chats[selectedChat].message[msgIndex]
|
|
result2 = await processScriptFull(nowChatroom, reformatContent(beforeChat.data + mess), 'editoutput', msgIndex)
|
|
}
|
|
result = result2.data
|
|
const inlayResult = runInlayScreen(currentChar, result)
|
|
result = inlayResult.text
|
|
emoChanged = result2.emoChanged
|
|
if(i === 0 && arg.continue){
|
|
db.characters[selectedChar].chats[selectedChat].message[msgIndex] = {
|
|
role: 'char',
|
|
data: result,
|
|
saying: currentChar.chaId,
|
|
time: Date.now(),
|
|
generationInfo
|
|
}
|
|
if(inlayResult.promise){
|
|
const p = await inlayResult.promise
|
|
db.characters[selectedChar].chats[selectedChat].message[msgIndex].data = p
|
|
}
|
|
}
|
|
else if(i===0){
|
|
db.characters[selectedChar].chats[selectedChat].message.push({
|
|
role: msg[0],
|
|
data: result,
|
|
saying: currentChar.chaId,
|
|
time: Date.now(),
|
|
generationInfo
|
|
})
|
|
const ind = db.characters[selectedChar].chats[selectedChat].message.length - 1
|
|
if(inlayResult.promise){
|
|
const p = await inlayResult.promise
|
|
db.characters[selectedChar].chats[selectedChat].message[ind].data = p
|
|
}
|
|
mrerolls.push(result)
|
|
}
|
|
else{
|
|
mrerolls.push(result)
|
|
}
|
|
db.characters[selectedChar].reloadKeys += 1
|
|
await sayTTS(currentChar, result)
|
|
setDatabase(db)
|
|
}
|
|
|
|
if(mrerolls.length >1){
|
|
addRerolls(generationId, mrerolls)
|
|
}
|
|
|
|
db.characters[selectedChar].chats[selectedChat] = runCurrentChatFunction(db.characters[selectedChar].chats[selectedChat])
|
|
currentChat = db.characters[selectedChar].chats[selectedChat]
|
|
|
|
const triggerResult = await runTrigger(currentChar, 'output', {chat:currentChat})
|
|
if(triggerResult && triggerResult.chat){
|
|
db.characters[selectedChar].chats[selectedChat] = triggerResult.chat
|
|
setDatabase(db)
|
|
}
|
|
}
|
|
|
|
if(db.autoContinueMinTokens > 0 && (await tokenize(result)) < db.autoContinueMinTokens){
|
|
doingChat.set(false)
|
|
return await sendChat(chatProcessIndex, {
|
|
chatAdditonalTokens: arg.chatAdditonalTokens,
|
|
continue: true,
|
|
signal: abortSignal
|
|
})
|
|
}
|
|
|
|
chatProcessStage.set(4)
|
|
|
|
sendPeerChar()
|
|
|
|
if(req.special){
|
|
if(req.special.emotion){
|
|
let charemotions = get(CharEmotion)
|
|
let currentEmotion = currentChar.emotionImages
|
|
|
|
let tempEmotion = charemotions[currentChar.chaId]
|
|
if(!tempEmotion){
|
|
tempEmotion = []
|
|
}
|
|
if(tempEmotion.length > 4){
|
|
tempEmotion.splice(0, 1)
|
|
}
|
|
|
|
for(const emo of currentEmotion){
|
|
if(emo[0] === req.special.emotion){
|
|
const emos:[string, string,number] = [emo[0], emo[1], Date.now()]
|
|
tempEmotion.push(emos)
|
|
charemotions[currentChar.chaId] = tempEmotion
|
|
CharEmotion.set(charemotions)
|
|
emoChanged = true
|
|
break
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
if(!currentChar.inlayViewScreen){
|
|
if(currentChar.viewScreen === 'emotion' && (!emoChanged) && (abortSignal.aborted === false)){
|
|
|
|
let currentEmotion = currentChar.emotionImages
|
|
let emotionList = currentEmotion.map((a) => {
|
|
return a[0]
|
|
})
|
|
let charemotions = get(CharEmotion)
|
|
|
|
let tempEmotion = charemotions[currentChar.chaId]
|
|
if(!tempEmotion){
|
|
tempEmotion = []
|
|
}
|
|
if(tempEmotion.length > 4){
|
|
tempEmotion.splice(0, 1)
|
|
}
|
|
|
|
if(db.emotionProcesser === 'embedding'){
|
|
const hypaProcesser = new HypaProcesser('MiniLM')
|
|
await hypaProcesser.addText(emotionList.map((v) => 'emotion:' + v))
|
|
let searched = (await hypaProcesser.similaritySearchScored(result)).map((v) => {
|
|
v[0] = v[0].replace("emotion:",'')
|
|
return v
|
|
})
|
|
|
|
//give panaltys
|
|
for(let i =0;i<tempEmotion.length;i++){
|
|
const emo = tempEmotion[i]
|
|
//give panalty index
|
|
const index = searched.findIndex((v) => {
|
|
return v[0] === emo[0]
|
|
})
|
|
|
|
const modifier = ((5 - ((tempEmotion.length - (i + 1))))) / 200
|
|
|
|
if(index !== -1){
|
|
searched[index][1] -= modifier
|
|
}
|
|
}
|
|
|
|
//make a sorted array by score
|
|
const emoresult = searched.sort((a,b) => {
|
|
return b[1] - a[1]
|
|
}).map((v) => {
|
|
return v[0]
|
|
})
|
|
|
|
for(const emo of currentEmotion){
|
|
if(emo[0] === emoresult[0]){
|
|
const emos:[string, string,number] = [emo[0], emo[1], Date.now()]
|
|
tempEmotion.push(emos)
|
|
charemotions[currentChar.chaId] = tempEmotion
|
|
CharEmotion.set(charemotions)
|
|
break
|
|
}
|
|
}
|
|
|
|
|
|
|
|
return true
|
|
}
|
|
|
|
function shuffleArray(array:string[]) {
|
|
for (let i = array.length - 1; i > 0; i--) {
|
|
const j = Math.floor(Math.random() * (i + 1));
|
|
[array[i], array[j]] = [array[j], array[i]];
|
|
}
|
|
return array
|
|
}
|
|
|
|
let emobias:{[key:number]:number} = {}
|
|
|
|
for(const emo of emotionList){
|
|
const tokens = await tokenizeNum(emo)
|
|
for(const token of tokens){
|
|
emobias[token] = 10
|
|
}
|
|
}
|
|
|
|
for(let i =0;i<tempEmotion.length;i++){
|
|
const emo = tempEmotion[i]
|
|
|
|
const tokens = await tokenizeNum(emo[0])
|
|
const modifier = 20 - ((tempEmotion.length - (i + 1)) * (20/4))
|
|
|
|
for(const token of tokens){
|
|
emobias[token] -= modifier
|
|
if(emobias[token] < -100){
|
|
emobias[token] = -100
|
|
}
|
|
}
|
|
}
|
|
|
|
const promptbody:OpenAIChat[] = [
|
|
{
|
|
role:'system',
|
|
content: `${db.emotionPrompt2 || "From the list below, choose a word that best represents a character's outfit description, action, or emotion in their dialogue. Prioritize selecting words related to outfit first, then action, and lastly emotion. Print out the chosen word."}\n\n list: ${shuffleArray(emotionList).join(', ')} \noutput only one word.`
|
|
},
|
|
{
|
|
role: 'user',
|
|
content: `"Good morning, Master! Is there anything I can do for you today?"`
|
|
},
|
|
{
|
|
role: 'assistant',
|
|
content: 'happy'
|
|
},
|
|
{
|
|
role: 'user',
|
|
content: result
|
|
},
|
|
]
|
|
|
|
const rq = await requestChatData({
|
|
formated: promptbody,
|
|
bias: emobias,
|
|
currentChar: currentChar,
|
|
temperature: 0.4,
|
|
maxTokens: 30,
|
|
}, 'submodel', abortSignal)
|
|
|
|
if(rq.type === 'fail' || rq.type === 'streaming' || rq.type === 'multiline'){
|
|
if(abortSignal.aborted){
|
|
return true
|
|
}
|
|
alertError(`${rq.result}`)
|
|
return true
|
|
}
|
|
else{
|
|
emotionList = currentEmotion.map((a) => {
|
|
return a[0]
|
|
})
|
|
try {
|
|
const emotion:string = rq.result.replace(/ |\n/g,'').trim().toLocaleLowerCase()
|
|
let emotionSelected = false
|
|
for(const emo of currentEmotion){
|
|
if(emo[0] === emotion){
|
|
const emos:[string, string,number] = [emo[0], emo[1], Date.now()]
|
|
tempEmotion.push(emos)
|
|
charemotions[currentChar.chaId] = tempEmotion
|
|
CharEmotion.set(charemotions)
|
|
emotionSelected = true
|
|
break
|
|
}
|
|
}
|
|
if(!emotionSelected){
|
|
for(const emo of currentEmotion){
|
|
if(emotion.includes(emo[0])){
|
|
const emos:[string, string,number] = [emo[0], emo[1], Date.now()]
|
|
tempEmotion.push(emos)
|
|
charemotions[currentChar.chaId] = tempEmotion
|
|
CharEmotion.set(charemotions)
|
|
emotionSelected = true
|
|
break
|
|
}
|
|
}
|
|
}
|
|
if(!emotionSelected && emotionList.includes('neutral')){
|
|
const emo = currentEmotion[emotionList.indexOf('neutral')]
|
|
const emos:[string, string,number] = [emo[0], emo[1], Date.now()]
|
|
tempEmotion.push(emos)
|
|
charemotions[currentChar.chaId] = tempEmotion
|
|
CharEmotion.set(charemotions)
|
|
emotionSelected = true
|
|
}
|
|
} catch (error) {
|
|
alertError(language.errors.httpError + `${error}`)
|
|
return true
|
|
}
|
|
}
|
|
|
|
return true
|
|
|
|
|
|
}
|
|
else if(currentChar.viewScreen === 'imggen'){
|
|
if(chatProcessIndex !== -1){
|
|
alertError("Stable diffusion in group chat is not supported")
|
|
}
|
|
|
|
const msgs = db.characters[selectedChar].chats[selectedChat].message
|
|
let msgStr = ''
|
|
for(let i = (msgs.length - 1);i>=0;i--){
|
|
if(msgs[i].role === 'char'){
|
|
msgStr = `character: ${msgs[i].data.replace(/\n/, ' ')} \n` + msgStr
|
|
}
|
|
else{
|
|
msgStr = `user: ${msgs[i].data.replace(/\n/, ' ')} \n` + msgStr
|
|
break
|
|
}
|
|
}
|
|
|
|
|
|
await stableDiff(currentChar, msgStr)
|
|
}
|
|
}
|
|
|
|
return true
|
|
}
|
|
|
|
function systemizeChat(chat:OpenAIChat[]){
|
|
for(let i=0;i<chat.length;i++){
|
|
if(chat[i].role === 'user' || chat[i].role === 'assistant'){
|
|
const attr = chat[i].attr ?? []
|
|
if(chat[i].name?.startsWith('example_')){
|
|
chat[i].content = chat[i].name + ': ' + chat[i].content
|
|
}
|
|
else if(!attr.includes('nameAdded')){
|
|
chat[i].content = chat[i].role + ': ' + chat[i].content
|
|
}
|
|
chat[i].role = 'system'
|
|
delete chat[i].memo
|
|
delete chat[i].name
|
|
}
|
|
}
|
|
return chat
|
|
} |