2561 lines
98 KiB
TypeScript
2561 lines
98 KiB
TypeScript
import { get } from "svelte/store";
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import type { MultiModal, OpenAIChat, OpenAIChatFull } from ".";
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import { DataBase, type character } from "../storage/database";
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import { pluginProcess } from "../plugins/plugins";
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import { language } from "../../lang";
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import { stringlizeAINChat, stringlizeChat, getStopStrings, unstringlizeAIN, unstringlizeChat } from "./stringlize";
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import { addFetchLog, fetchNative, globalFetch, isNodeServer, isTauri, textifyReadableStream } from "../storage/globalApi";
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import { sleep } from "../util";
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import { NovelAIBadWordIds, stringlizeNAIChat } from "./models/nai";
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import { strongBan, tokenize, tokenizeNum } from "../tokenizer";
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import { runGGUFModel } from "./models/local";
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import { risuChatParser } from "../parser";
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import { SignatureV4 } from "@smithy/signature-v4";
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import { HttpRequest } from "@smithy/protocol-http";
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import { Sha256 } from "@aws-crypto/sha256-js";
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import { v4 } from "uuid";
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import { supportsInlayImage } from "./files/image";
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import { Capacitor } from "@capacitor/core";
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import { getFreeOpenRouterModel } from "../model/openrouter";
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import { runTransformers } from "./transformers";
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import {createParser} from 'eventsource-parser'
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import {Ollama} from 'ollama/dist/browser.mjs'
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import { applyChatTemplate } from "./templates/chatTemplate";
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interface requestDataArgument{
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formated: OpenAIChat[]
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bias: {[key:number]:number}
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biasString?: [string,number][]
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currentChar?: character
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temperature?: number
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maxTokens?:number
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PresensePenalty?: number
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frequencyPenalty?: number,
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useStreaming?:boolean
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isGroupChat?:boolean
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useEmotion?:boolean
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continue?:boolean
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chatId?:string
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noMultiGen?:boolean
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}
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type requestDataResponse = {
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type: 'success'|'fail'
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result: string
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noRetry?: boolean,
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special?: {
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emotion?: string
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}
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}|{
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type: "streaming",
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result: ReadableStream<StreamResponseChunk>,
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special?: {
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emotion?: string
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}
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}|{
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type: "multiline",
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result: ['user'|'char',string][],
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special?: {
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emotion?: string
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}
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}
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interface StreamResponseChunk{[key:string]:string}
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interface OaiFunctions {
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name: string;
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description: string;
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parameters: {
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type: string;
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properties: {
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[key:string]: {
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type: string;
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enum: string[]
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};
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};
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required: string[];
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};
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}
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export async function requestChatData(arg:requestDataArgument, model:'model'|'submodel', abortSignal:AbortSignal=null):Promise<requestDataResponse> {
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const db = get(DataBase)
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let trys = 0
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while(true){
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const da = await requestChatDataMain(arg, model, abortSignal)
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if(da.type !== 'fail' || da.noRetry){
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return da
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}
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trys += 1
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if(trys > db.requestRetrys){
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return da
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}
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}
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}
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interface OpenAITextContents {
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type: 'text'
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text: string
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}
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interface OpenAIImageContents {
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type: 'image'|'image_url'
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image_url: {
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url: string
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detail: string
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}
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}
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type OpenAIContents = OpenAITextContents|OpenAIImageContents
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export interface OpenAIChatExtra {
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role: 'system'|'user'|'assistant'|'function'
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content: string|OpenAIContents[]
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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 async function requestChatDataMain(arg:requestDataArgument, model:'model'|'submodel', abortSignal:AbortSignal=null):Promise<requestDataResponse> {
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const db = get(DataBase)
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let formated = structuredClone(arg.formated)
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let maxTokens = arg.maxTokens ??db.maxResponse
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let temperature = arg.temperature ?? (db.temperature / 100)
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let bias = arg.bias
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let currentChar = arg.currentChar
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let useStreaming = db.useStreaming && arg.useStreaming
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arg.continue = arg.continue ?? false
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let biasString = arg.biasString ?? []
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const aiModel = (model === 'model' || (!db.advancedBotSettings)) ? db.aiModel : db.subModel
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const multiGen = (db.genTime > 1 && aiModel.startsWith('gpt') && (!arg.continue)) && (!arg.noMultiGen)
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let raiModel = aiModel
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if(aiModel === 'reverse_proxy'){
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if(db.proxyRequestModel === 'custom' && db.customProxyRequestModel.startsWith('claude')){
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raiModel = db.customProxyRequestModel
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}
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if(db.proxyRequestModel.startsWith('claude')){
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raiModel = db.proxyRequestModel
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}
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if(db.forceProxyAsOpenAI){
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raiModel = 'reverse_proxy'
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}
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}
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console.log(formated)
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switch(raiModel){
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case 'gpt35':
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case 'gpt35_0613':
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case 'gpt35_16k':
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case 'gpt35_16k_0613':
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case 'gpt4':
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case 'gpt45':
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case 'gpt4_32k':
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case 'gpt4_0613':
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case 'gpt4_32k_0613':
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case 'gpt4_1106':
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case 'gpt4_0125':
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case 'gpt35_0125':
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case 'gpt35_1106':
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case 'gpt35_0301':
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case 'gpt4_0314':
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case 'gptvi4_1106':
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case 'openrouter':
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case 'mistral-tiny':
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case 'mistral-small':
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case 'mistral-medium':
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case 'mistral-small-latest':
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case 'mistral-medium-latest':
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case 'mistral-large-latest':
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case 'open-mistral-nemo':
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case 'gpt4_turbo_20240409':
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case 'gpt4_turbo':
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case 'gpt4o':
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case 'gpt4o-2024-05-13':
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case 'gpt4om':
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case 'gpt4om-2024-07-18':
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case 'gpt4o-2024-08-06':
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case 'gpt4o-chatgpt':
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case 'reverse_proxy':{
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let formatedChat:OpenAIChatExtra[] = []
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for(let i=0;i<formated.length;i++){
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const m = formated[i]
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if(m.multimodals && m.multimodals.length > 0 && m.role === 'user'){
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let v:OpenAIChatExtra = structuredClone(m)
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let contents:OpenAIContents[] = []
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for(let j=0;j<m.multimodals.length;j++){
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contents.push({
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"type": "image_url",
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"image_url": {
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"url": m.multimodals[j].base64,
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"detail": db.gptVisionQuality
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}
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})
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}
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contents.push({
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"type": "text",
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"text": m.content
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})
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v.content = contents
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formatedChat.push(v)
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}
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else{
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formatedChat.push(m)
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}
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}
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let oobaSystemPrompts:string[] = []
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for(let i=0;i<formatedChat.length;i++){
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if(formatedChat[i].role !== 'function'){
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if(!(formatedChat[i].name && formatedChat[i].name.startsWith('example_') && db.newOAIHandle)){
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formatedChat[i].name = undefined
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}
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if(db.newOAIHandle && formatedChat[i].memo && formatedChat[i].memo.startsWith('NewChat')){
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formatedChat[i].content = ''
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}
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delete formatedChat[i].memo
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delete formatedChat[i].removable
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delete formatedChat[i].attr
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delete formatedChat[i].multimodals
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}
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if(aiModel === 'reverse_proxy' && db.reverseProxyOobaMode && formatedChat[i].role === 'system'){
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const cont = formatedChat[i].content
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if(typeof(cont) === 'string'){
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oobaSystemPrompts.push(cont)
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formatedChat[i].content = ''
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}
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}
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}
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if(oobaSystemPrompts.length > 0){
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formatedChat.push({
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role: 'system',
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content: oobaSystemPrompts.join('\n')
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})
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}
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if(db.newOAIHandle){
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formatedChat = formatedChat.filter(m => {
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return m.content !== ''
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})
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}
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for(let i=0;i<biasString.length;i++){
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const bia = biasString[i]
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if(bia[1] === -101){
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bias = await strongBan(bia[0], bias)
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continue
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}
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const tokens = await tokenizeNum(bia[0])
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for(const token of tokens){
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bias[token] = bia[1]
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}
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}
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let oaiFunctions:OaiFunctions[] = []
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if(arg.useEmotion){
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oaiFunctions.push(
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{
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"name": "set_emotion",
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"description": "sets a role playing character's emotion display. must be called one time at the end of response.",
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"parameters": {
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"type": "object",
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"properties": {
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"emotion": {
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"type": "string", "enum": []
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},
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},
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"required": ["emotion"],
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},
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}
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)
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}
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if(oaiFunctions.length === 0){
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oaiFunctions = undefined
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}
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const oaiFunctionCall = oaiFunctions ? (arg.useEmotion ? {"name": "set_emotion"} : "auto") : undefined
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let requestModel = (aiModel === 'reverse_proxy' || aiModel === 'openrouter') ? db.proxyRequestModel : aiModel
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let openrouterRequestModel = db.openrouterRequestModel
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if(aiModel === 'reverse_proxy' && db.proxyRequestModel === 'custom'){
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requestModel = db.customProxyRequestModel
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}
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if(aiModel === 'openrouter' && db.openrouterRequestModel === 'risu/free'){
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openrouterRequestModel = await getFreeOpenRouterModel()
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}
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console.log(formatedChat)
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if(aiModel.startsWith('mistral') || aiModel === 'open-mistral-nemo'){
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requestModel = aiModel
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let reformatedChat:OpenAIChatExtra[] = []
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for(let i=0;i<formatedChat.length;i++){
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const chat = formatedChat[i]
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if(i === 0){
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if(chat.role === 'user' || chat.role === 'system'){
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reformatedChat.push({
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role: chat.role,
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content: chat.content
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})
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}
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else{
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reformatedChat.push({
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role: 'system',
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content: chat.role + ':' + chat.content
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})
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}
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}
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else{
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const prevChat = reformatedChat[reformatedChat.length-1]
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if(prevChat.role === chat.role){
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reformatedChat[reformatedChat.length-1].content += '\n' + chat.content
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continue
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}
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else if(chat.role === 'system'){
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if(prevChat.role === 'user'){
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reformatedChat[reformatedChat.length-1].content += '\nSystem:' + chat.content
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}
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else{
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reformatedChat.push({
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role: 'user',
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content: 'System:' + chat.content
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})
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}
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}
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else if(chat.role === 'function'){
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reformatedChat.push({
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role: 'user',
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content: chat.content
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})
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}
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else{
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reformatedChat.push({
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role: chat.role,
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content: chat.content
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})
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}
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}
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}
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const res = await globalFetch("https://api.mistral.ai/v1/chat/completions", {
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body: {
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model: requestModel,
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messages: reformatedChat,
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temperature: temperature,
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max_tokens: maxTokens,
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top_p: db.top_p,
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safe_prompt: false
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},
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headers: {
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"Authorization": "Bearer " + db.mistralKey,
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},
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abortSignal,
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chatId: arg.chatId
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})
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const dat = res.data as any
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if(res.ok){
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try {
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const msg:OpenAIChatFull = (dat.choices[0].message)
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return {
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type: 'success',
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result: msg.content
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}
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} catch (error) {
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return {
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type: 'fail',
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result: (language.errors.httpError + `${JSON.stringify(dat)}`)
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}
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}
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}
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else{
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if(dat.error && dat.error.message){
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return {
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type: 'fail',
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result: (language.errors.httpError + `${dat.error.message}`)
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}
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}
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else{
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return {
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type: 'fail',
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result: (language.errors.httpError + `${JSON.stringify(res.data)}`)
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}
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}
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}
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}
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db.cipherChat = false
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let body = ({
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model: aiModel === 'openrouter' ? openrouterRequestModel :
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requestModel === 'gpt35' ? 'gpt-3.5-turbo'
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: requestModel === 'gpt35_0613' ? 'gpt-3.5-turbo-0613'
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: requestModel === 'gpt35_16k' ? 'gpt-3.5-turbo-16k'
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: requestModel === 'gpt35_16k_0613' ? 'gpt-3.5-turbo-16k-0613'
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: requestModel === 'gpt4' ? 'gpt-4'
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: requestModel === 'gpt45' ? 'gpt-4.5-preview'
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: requestModel === 'gpt4_32k' ? 'gpt-4-32k'
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: requestModel === "gpt4_0613" ? 'gpt-4-0613'
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: requestModel === "gpt4_32k_0613" ? 'gpt-4-32k-0613'
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: requestModel === "gpt4_1106" ? 'gpt-4-1106-preview'
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: requestModel === 'gpt4_0125' ? 'gpt-4-0125-preview'
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: requestModel === "gptvi4_1106" ? 'gpt-4-vision-preview'
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: requestModel === "gpt35_0125" ? 'gpt-3.5-turbo-0125'
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: requestModel === "gpt35_1106" ? 'gpt-3.5-turbo-1106'
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: requestModel === 'gpt35_0301' ? 'gpt-3.5-turbo-0301'
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: requestModel === 'gpt4_0314' ? 'gpt-4-0314'
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: requestModel === 'gpt4_turbo_20240409' ? 'gpt-4-turbo-2024-04-09'
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: requestModel === 'gpt4_turbo' ? 'gpt-4-turbo'
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: requestModel === 'gpt4o' ? 'gpt-4o'
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: requestModel === 'gpt4o-2024-05-13' ? 'gpt-4o-2024-05-13'
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: requestModel === 'gpt4om' ? 'gpt-4o-mini'
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: requestModel === 'gpt4om-2024-07-18' ? 'gpt-4o-mini-2024-07-18'
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: requestModel === 'gpt4o-2024-08-06' ? 'gpt-4o-2024-08-06'
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: requestModel === 'gpt4o-chatgpt' ? 'chatgpt-4o-latest'
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: (!requestModel) ? 'gpt-3.5-turbo'
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: requestModel,
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messages: formatedChat,
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temperature: temperature,
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max_tokens: maxTokens,
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presence_penalty: arg.PresensePenalty || (db.PresensePenalty / 100),
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frequency_penalty: arg.frequencyPenalty || (db.frequencyPenalty / 100),
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logit_bias: bias,
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stream: false,
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top_p: db.top_p,
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})
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if(db.generationSeed > 0){
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// @ts-ignore
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body.seed = db.generationSeed
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}
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if(db.putUserOpen){
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// @ts-ignore
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body.user = getOpenUserString()
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}
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if(aiModel === 'openrouter'){
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if(db.top_k !== 0){
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//@ts-ignore
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body.top_k = db.top_k
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}
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if(db.openrouterFallback){
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//@ts-ignore
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body.route = "fallback"
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}
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//@ts-ignore
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body.repetition_penalty = db.repetition_penalty
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//@ts-ignore
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body.min_p = db.min_p
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//@ts-ignore
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body.top_a = db.top_a
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//@ts-ignore
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body.transforms = db.openrouterMiddleOut ? ['middle-out'] : []
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if(db.openrouterProvider){
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//@ts-ignore
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body.provider = {
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order: [db.openrouterProvider]
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}
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}
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if(db.useInstructPrompt){
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//@ts-ignore
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delete body.messages
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const prompt = applyChatTemplate(formated)
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//@ts-ignore
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body.prompt = prompt
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}
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}
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if(aiModel === 'reverse_proxy' && db.reverseProxyOobaMode){
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const OobaBodyTemplate = db.reverseProxyOobaArgs
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const keys = Object.keys(OobaBodyTemplate)
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for(const key of keys){
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if(OobaBodyTemplate[key] !== undefined && OobaBodyTemplate[key] !== null){
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// @ts-ignore
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body[key] = OobaBodyTemplate[key]
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}
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}
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}
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|
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if(supportsInlayImage()){
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// inlay models doesn't support logit_bias
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// OpenAI's gpt based llm model supports both logit_bias and inlay image
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if(!(
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aiModel.startsWith('gpt') ||
|
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(aiModel == 'reverse_proxy' && (
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db.proxyRequestModel?.startsWith('gpt') ||
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(db.proxyRequestModel === 'custom' && db.customProxyRequestModel.startsWith('gpt'))
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)))){
|
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// @ts-ignore
|
|
delete body.logit_bias
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}
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}
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|
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let replacerURL = aiModel === 'openrouter' ? "https://openrouter.ai/api/v1/chat/completions" :
|
|
(aiModel === 'reverse_proxy') ? (db.forceReplaceUrl) : ('https://api.openai.com/v1/chat/completions')
|
|
|
|
let risuIdentify = false
|
|
if(replacerURL.startsWith("risu::")){
|
|
risuIdentify = true
|
|
replacerURL = replacerURL.replace("risu::", '')
|
|
}
|
|
|
|
if(aiModel === 'reverse_proxy' && db.autofillRequestUrl){
|
|
if(replacerURL.endsWith('v1')){
|
|
replacerURL += '/chat/completions'
|
|
}
|
|
else if(replacerURL.endsWith('v1/')){
|
|
replacerURL += 'chat/completions'
|
|
}
|
|
else if(!(replacerURL.endsWith('completions') || replacerURL.endsWith('completions/'))){
|
|
if(replacerURL.endsWith('/')){
|
|
replacerURL += 'v1/chat/completions'
|
|
}
|
|
else{
|
|
replacerURL += '/v1/chat/completions'
|
|
}
|
|
}
|
|
}
|
|
|
|
let headers = {
|
|
"Authorization": "Bearer " + (aiModel === 'reverse_proxy' ? db.proxyKey : (aiModel === 'openrouter' ? db.openrouterKey : db.openAIKey)),
|
|
"Content-Type": "application/json"
|
|
}
|
|
|
|
if(aiModel === 'openrouter'){
|
|
headers["X-Title"] = 'RisuAI'
|
|
headers["HTTP-Referer"] = 'https://risuai.xyz'
|
|
}
|
|
if(risuIdentify){
|
|
headers["X-Proxy-Risu"] = 'RisuAI'
|
|
}
|
|
if(multiGen){
|
|
// @ts-ignore
|
|
body.n = db.genTime
|
|
}
|
|
let throughProxi = (!isTauri) && (!isNodeServer) && (!db.usePlainFetch) && (!Capacitor.isNativePlatform())
|
|
if(useStreaming){
|
|
body.stream = true
|
|
let urlHost = new URL(replacerURL).host
|
|
if(urlHost.includes("localhost") || urlHost.includes("172.0.0.1") || urlHost.includes("0.0.0.0")){
|
|
if(!isTauri){
|
|
return {
|
|
type: 'fail',
|
|
result: 'You are trying local request on streaming. this is not allowed dude to browser/os security policy. turn off streaming.',
|
|
}
|
|
}
|
|
}
|
|
const da = await fetchNative(replacerURL, {
|
|
body: JSON.stringify(body),
|
|
method: "POST",
|
|
headers: headers,
|
|
signal: abortSignal,
|
|
chatId: arg.chatId
|
|
})
|
|
|
|
if(da.status !== 200){
|
|
return {
|
|
type: "fail",
|
|
result: await textifyReadableStream(da.body)
|
|
}
|
|
}
|
|
|
|
if (!da.headers.get('Content-Type').includes('text/event-stream')){
|
|
return {
|
|
type: "fail",
|
|
result: await textifyReadableStream(da.body)
|
|
}
|
|
}
|
|
|
|
addFetchLog({
|
|
body: body,
|
|
response: "Streaming",
|
|
success: true,
|
|
url: replacerURL,
|
|
})
|
|
|
|
let dataUint = new Uint8Array([])
|
|
|
|
const transtream = new TransformStream<Uint8Array, StreamResponseChunk>( {
|
|
async transform(chunk, control) {
|
|
dataUint = Buffer.from(new Uint8Array([...dataUint, ...chunk]))
|
|
try {
|
|
const datas = dataUint.toString().split('\n')
|
|
let readed:{[key:string]:string} = {}
|
|
for(const data of datas){
|
|
if(data.startsWith("data: ")){
|
|
try {
|
|
const rawChunk = data.replace("data: ", "")
|
|
if(rawChunk === "[DONE]"){
|
|
control.enqueue(readed)
|
|
return
|
|
}
|
|
const choices = JSON.parse(rawChunk).choices
|
|
for(const choice of choices){
|
|
const chunk = choice.delta.content ?? choices.text
|
|
if(chunk){
|
|
if(multiGen){
|
|
const ind = choice.index.toString()
|
|
if(!readed[ind]){
|
|
readed[ind] = ""
|
|
}
|
|
readed[ind] += chunk
|
|
}
|
|
else{
|
|
if(!readed["0"]){
|
|
readed["0"] = ""
|
|
}
|
|
readed["0"] += chunk
|
|
}
|
|
}
|
|
}
|
|
} catch (error) {}
|
|
}
|
|
}
|
|
control.enqueue(readed)
|
|
} catch (error) {
|
|
|
|
}
|
|
}
|
|
},)
|
|
|
|
da.body.pipeTo(transtream.writable)
|
|
|
|
return {
|
|
type: 'streaming',
|
|
result: transtream.readable
|
|
}
|
|
}
|
|
|
|
if(raiModel === 'reverse_proxy'){
|
|
const additionalParams = db.additionalParams
|
|
for(let i=0;i<additionalParams.length;i++){
|
|
let key = additionalParams[i][0]
|
|
let value = additionalParams[i][1]
|
|
|
|
if(!key || !value){
|
|
continue
|
|
}
|
|
|
|
if(value === '{{none}}'){
|
|
if(key.startsWith('header::')){
|
|
key = key.replace('header::', '')
|
|
delete headers[key]
|
|
}
|
|
else{
|
|
delete body[key]
|
|
}
|
|
continue
|
|
}
|
|
|
|
if(key.startsWith('header::')){
|
|
key = key.replace('header::', '')
|
|
headers[key] = value
|
|
}
|
|
else if(value.startsWith('json::')){
|
|
value = value.replace('json::', '')
|
|
try {
|
|
body[key] = JSON.parse(value)
|
|
} catch (error) {}
|
|
}
|
|
else if(isNaN(parseFloat(value))){
|
|
body[key] = value
|
|
}
|
|
else{
|
|
body[key] = parseFloat(value)
|
|
}
|
|
}
|
|
}
|
|
|
|
const res = await globalFetch(replacerURL, {
|
|
body: body,
|
|
headers: headers,
|
|
abortSignal,
|
|
useRisuToken:throughProxi,
|
|
chatId: arg.chatId
|
|
})
|
|
|
|
const dat = res.data as any
|
|
if(res.ok){
|
|
try {
|
|
if(multiGen && dat.choices){
|
|
return {
|
|
type: 'multiline',
|
|
result: dat.choices.map((v) => {
|
|
return ["char",v.message.content]
|
|
})
|
|
}
|
|
|
|
}
|
|
|
|
if(dat?.choices[0]?.text){
|
|
return {
|
|
type: 'success',
|
|
result: dat.choices[0].text
|
|
}
|
|
}
|
|
const msg:OpenAIChatFull = (dat.choices[0].message)
|
|
return {
|
|
type: 'success',
|
|
result: msg.content
|
|
}
|
|
} catch (error) {
|
|
return {
|
|
type: 'fail',
|
|
result: (language.errors.httpError + `${JSON.stringify(dat)}`)
|
|
}
|
|
}
|
|
}
|
|
else{
|
|
if(dat.error && dat.error.message){
|
|
return {
|
|
type: 'fail',
|
|
result: (language.errors.httpError + `${dat.error.message}`)
|
|
}
|
|
}
|
|
else{
|
|
return {
|
|
type: 'fail',
|
|
result: (language.errors.httpError + `${JSON.stringify(res.data)}`)
|
|
}
|
|
}
|
|
}
|
|
|
|
break
|
|
}
|
|
case 'novelai':
|
|
case 'novelai_kayra':{
|
|
console.log(arg.continue)
|
|
const prompt = stringlizeNAIChat(formated, currentChar?.name ?? '', arg.continue)
|
|
let logit_bias_exp:{
|
|
sequence: number[], bias: number, ensure_sequence_finish: false, generate_once: true
|
|
}[] = []
|
|
|
|
for(let i=0;i<biasString.length;i++){
|
|
const bia = biasString[i]
|
|
const tokens = await tokenizeNum(bia[0])
|
|
|
|
const tokensInNumberArray:number[] = []
|
|
|
|
for(const token of tokens){
|
|
tokensInNumberArray.push(token)
|
|
}
|
|
logit_bias_exp.push({
|
|
sequence: tokensInNumberArray,
|
|
bias: bia[1],
|
|
ensure_sequence_finish: false,
|
|
generate_once: true
|
|
})
|
|
}
|
|
|
|
let prefix = 'vanilla'
|
|
|
|
if(db.NAIadventure){
|
|
prefix = 'theme_textadventure'
|
|
}
|
|
|
|
const gen = db.NAIsettings
|
|
const payload = {
|
|
temperature:temperature,
|
|
max_length: maxTokens,
|
|
min_length: 1,
|
|
top_k: gen.topK,
|
|
top_p: gen.topP,
|
|
top_a: gen.topA,
|
|
tail_free_sampling: gen.tailFreeSampling,
|
|
repetition_penalty: gen.repetitionPenalty,
|
|
repetition_penalty_range: gen.repetitionPenaltyRange,
|
|
repetition_penalty_slope: gen.repetitionPenaltySlope,
|
|
repetition_penalty_frequency: gen.frequencyPenalty,
|
|
repetition_penalty_presence: gen.presencePenalty,
|
|
generate_until_sentence: true,
|
|
use_cache: false,
|
|
use_string: true,
|
|
return_full_text: false,
|
|
prefix: prefix,
|
|
order: [6, 2, 3, 0, 4, 1, 5, 8],
|
|
typical_p: gen.typicalp,
|
|
repetition_penalty_whitelist:[49256,49264,49231,49230,49287,85,49255,49399,49262,336,333,432,363,468,492,745,401,426,623,794,1096,2919,2072,7379,1259,2110,620,526,487,16562,603,805,761,2681,942,8917,653,3513,506,5301,562,5010,614,10942,539,2976,462,5189,567,2032,123,124,125,126,127,128,129,130,131,132,588,803,1040,49209,4,5,6,7,8,9,10,11,12],
|
|
stop_sequences: [[49287], [49405]],
|
|
bad_words_ids: NovelAIBadWordIds,
|
|
logit_bias_exp: logit_bias_exp,
|
|
mirostat_lr: gen.mirostat_lr ?? 1,
|
|
mirostat_tau: gen.mirostat_tau ?? 0,
|
|
cfg_scale: gen.cfg_scale ?? 1,
|
|
cfg_uc: ""
|
|
}
|
|
|
|
|
|
|
|
|
|
const body = {
|
|
"input": prompt,
|
|
"model": aiModel === 'novelai_kayra' ? 'kayra-v1' : 'clio-v1',
|
|
"parameters":payload
|
|
}
|
|
|
|
const da = await globalFetch("https://api.novelai.net/ai/generate", {
|
|
body: body,
|
|
headers: {
|
|
"Authorization": "Bearer " + db.novelai.token
|
|
},
|
|
abortSignal,
|
|
chatId: arg.chatId
|
|
})
|
|
|
|
if((!da.ok )|| (!da.data.output)){
|
|
return {
|
|
type: 'fail',
|
|
result: (language.errors.httpError + `${JSON.stringify(da.data)}`)
|
|
}
|
|
}
|
|
return {
|
|
type: "success",
|
|
result: unstringlizeChat(da.data.output, formated, currentChar?.name ?? '')
|
|
}
|
|
}
|
|
|
|
case 'instructgpt35':{
|
|
const prompt = formated.filter(m => m.content?.trim()).map(m => {
|
|
let author = '';
|
|
|
|
if(m.role == 'system'){
|
|
m.content = m.content.trim();
|
|
}
|
|
|
|
console.log(m.role +":"+m.content);
|
|
switch (m.role) {
|
|
case 'user': author = 'User'; break;
|
|
case 'assistant': author = 'Assistant'; break;
|
|
case 'system': author = 'Instruction'; break;
|
|
default: author = m.role; break;
|
|
}
|
|
|
|
return `\n## ${author}\n${m.content.trim()}`;
|
|
//return `\n\n${author}: ${m.content.trim()}`;
|
|
}).join("") + `\n## Response\n`;
|
|
|
|
const response = await globalFetch( "https://api.openai.com/v1/completions", {
|
|
body: {
|
|
model: "gpt-3.5-turbo-instruct",
|
|
prompt: prompt,
|
|
max_tokens: maxTokens,
|
|
temperature: temperature,
|
|
top_p: 1,
|
|
stop:["User:"," User:", "user:", " user:"],
|
|
presence_penalty: arg.PresensePenalty || (db.PresensePenalty / 100),
|
|
frequency_penalty: arg.frequencyPenalty || (db.frequencyPenalty / 100),
|
|
},
|
|
headers: {
|
|
"Content-Type": "application/json",
|
|
"Authorization": "Bearer " + db.openAIKey,
|
|
},
|
|
chatId: arg.chatId
|
|
});
|
|
|
|
if(!response.ok){
|
|
return {
|
|
type: 'fail',
|
|
result: (language.errors.httpError + `${JSON.stringify(response.data)}`)
|
|
}
|
|
}
|
|
const text:string = response.data.choices[0].text
|
|
return {
|
|
type: 'success',
|
|
result: text.replace(/##\n/g, '')
|
|
}
|
|
}
|
|
case "textgen_webui":
|
|
case 'mancer':{
|
|
let streamUrl = db.textgenWebUIStreamURL.replace(/\/api.*/, "/api/v1/stream")
|
|
let blockingUrl = db.textgenWebUIBlockingURL.replace(/\/api.*/, "/api/v1/generate")
|
|
let bodyTemplate:any
|
|
const suggesting = model === "submodel"
|
|
const prompt = applyChatTemplate(formated)
|
|
let stopStrings = getStopStrings(suggesting)
|
|
if(db.localStopStrings){
|
|
stopStrings = db.localStopStrings.map((v) => {
|
|
return risuChatParser(v.replace(/\\n/g, "\n"))
|
|
})
|
|
}
|
|
bodyTemplate = {
|
|
'max_new_tokens': db.maxResponse,
|
|
'do_sample': db.ooba.do_sample,
|
|
'temperature': (db.temperature / 100),
|
|
'top_p': db.ooba.top_p,
|
|
'typical_p': db.ooba.typical_p,
|
|
'repetition_penalty': db.ooba.repetition_penalty,
|
|
'encoder_repetition_penalty': db.ooba.encoder_repetition_penalty,
|
|
'top_k': db.ooba.top_k,
|
|
'min_length': db.ooba.min_length,
|
|
'no_repeat_ngram_size': db.ooba.no_repeat_ngram_size,
|
|
'num_beams': db.ooba.num_beams,
|
|
'penalty_alpha': db.ooba.penalty_alpha,
|
|
'length_penalty': db.ooba.length_penalty,
|
|
'early_stopping': false,
|
|
'truncation_length': maxTokens,
|
|
'ban_eos_token': db.ooba.ban_eos_token,
|
|
'stopping_strings': stopStrings,
|
|
'seed': -1,
|
|
add_bos_token: db.ooba.add_bos_token,
|
|
topP: db.top_p,
|
|
prompt: prompt
|
|
}
|
|
|
|
const headers = (aiModel === 'textgen_webui') ? {} : {
|
|
'X-API-KEY': db.mancerHeader
|
|
}
|
|
|
|
if(useStreaming){
|
|
const oobaboogaSocket = new WebSocket(streamUrl);
|
|
const statusCode = await new Promise((resolve) => {
|
|
oobaboogaSocket.onopen = () => resolve(0)
|
|
oobaboogaSocket.onerror = () => resolve(1001)
|
|
oobaboogaSocket.onclose = ({ code }) => resolve(code)
|
|
})
|
|
if(abortSignal.aborted || statusCode !== 0) {
|
|
oobaboogaSocket.close()
|
|
return ({
|
|
type: "fail",
|
|
result: abortSignal.reason || `WebSocket connection failed to '${streamUrl}' failed!`,
|
|
})
|
|
}
|
|
|
|
const close = () => {
|
|
oobaboogaSocket.close()
|
|
}
|
|
const stream = new ReadableStream({
|
|
start(controller){
|
|
let readed = "";
|
|
oobaboogaSocket.onmessage = async (event) => {
|
|
const json = JSON.parse(event.data);
|
|
if (json.event === "stream_end") {
|
|
close()
|
|
controller.close()
|
|
return
|
|
}
|
|
if (json.event !== "text_stream") return
|
|
readed += json.text
|
|
controller.enqueue(readed)
|
|
};
|
|
oobaboogaSocket.send(JSON.stringify(bodyTemplate));
|
|
},
|
|
cancel(){
|
|
close()
|
|
}
|
|
})
|
|
oobaboogaSocket.onerror = close
|
|
oobaboogaSocket.onclose = close
|
|
abortSignal.addEventListener("abort", close)
|
|
|
|
return {
|
|
type: 'streaming',
|
|
result: stream
|
|
}
|
|
}
|
|
|
|
const res = await globalFetch(blockingUrl, {
|
|
body: bodyTemplate,
|
|
headers: headers,
|
|
abortSignal,
|
|
chatId: arg.chatId
|
|
})
|
|
|
|
const dat = res.data as any
|
|
if(res.ok){
|
|
try {
|
|
let result:string = dat.results[0].text
|
|
if(suggesting){
|
|
result = "\n" + db.autoSuggestPrefix + result
|
|
}
|
|
|
|
return {
|
|
type: 'success',
|
|
result: unstringlizeChat(result, formated, currentChar?.name ?? '')
|
|
}
|
|
} catch (error) {
|
|
return {
|
|
type: 'fail',
|
|
result: (language.errors.httpError + `${error}`)
|
|
}
|
|
}
|
|
}
|
|
else{
|
|
return {
|
|
type: 'fail',
|
|
result: (language.errors.httpError + `${JSON.stringify(res.data)}`)
|
|
}
|
|
}
|
|
}
|
|
|
|
case 'ooba': {
|
|
const suggesting = model === "submodel"
|
|
const prompt = applyChatTemplate(formated)
|
|
let stopStrings = getStopStrings(suggesting)
|
|
if(db.localStopStrings){
|
|
stopStrings = db.localStopStrings.map((v) => {
|
|
return risuChatParser(v.replace(/\\n/g, "\n"))
|
|
})
|
|
}
|
|
let bodyTemplate:Record<string, any> = {
|
|
'prompt': prompt,
|
|
presence_penalty: arg.PresensePenalty || (db.PresensePenalty / 100),
|
|
frequency_penalty: arg.frequencyPenalty || (db.frequencyPenalty / 100),
|
|
logit_bias: {},
|
|
max_tokens: maxTokens,
|
|
stop: stopStrings,
|
|
temperature: temperature,
|
|
top_p: db.top_p,
|
|
}
|
|
|
|
const url = new URL(db.textgenWebUIBlockingURL)
|
|
url.pathname = "/v1/completions"
|
|
const urlStr = url.toString()
|
|
|
|
const OobaBodyTemplate = db.reverseProxyOobaArgs
|
|
const keys = Object.keys(OobaBodyTemplate)
|
|
for(const key of keys){
|
|
if(OobaBodyTemplate[key] !== undefined && OobaBodyTemplate[key] !== null){
|
|
bodyTemplate[key] = OobaBodyTemplate[key]
|
|
}
|
|
}
|
|
|
|
const response = await globalFetch(urlStr, {
|
|
body: bodyTemplate,
|
|
chatId: arg.chatId
|
|
})
|
|
|
|
if(!response.ok){
|
|
return {
|
|
type: 'fail',
|
|
result: (language.errors.httpError + `${JSON.stringify(response.data)}`)
|
|
}
|
|
}
|
|
const text:string = response.data.choices[0].text
|
|
return {
|
|
type: 'success',
|
|
result: text.replace(/##\n/g, '')
|
|
}
|
|
|
|
}
|
|
|
|
case 'custom':{
|
|
const d = await pluginProcess({
|
|
bias: bias,
|
|
prompt_chat: formated,
|
|
temperature: (db.temperature / 100),
|
|
max_tokens: maxTokens,
|
|
presence_penalty: (db.PresensePenalty / 100),
|
|
frequency_penalty: (db.frequencyPenalty / 100)
|
|
})
|
|
if(!d){
|
|
return {
|
|
type: 'fail',
|
|
result: (language.errors.unknownModel)
|
|
}
|
|
}
|
|
else if(!d.success){
|
|
return {
|
|
type: 'fail',
|
|
result: d.content
|
|
}
|
|
}
|
|
else{
|
|
return {
|
|
type: 'success',
|
|
result: d.content
|
|
}
|
|
}
|
|
break
|
|
}
|
|
case 'palm2':
|
|
case 'palm2_unicorn':{
|
|
const bodyData = {
|
|
"instances": [
|
|
{
|
|
"content": stringlizeChat(formated, currentChar?.name ?? '', arg.continue)
|
|
}
|
|
],
|
|
"parameters": {
|
|
"candidateCount": 1,
|
|
"maxOutputTokens": maxTokens,
|
|
"stopSequences": [
|
|
"system:", "user:", "assistant:"
|
|
],
|
|
"temperature": temperature,
|
|
}
|
|
};
|
|
|
|
const API_ENDPOINT="us-central1-aiplatform.googleapis.com"
|
|
const PROJECT_ID=db.google.projectId
|
|
const MODEL_ID= aiModel === 'palm2' ? 'text-bison' :
|
|
'palm2_unicorn' ? 'text-unicorn' :
|
|
''
|
|
const LOCATION_ID="us-central1"
|
|
|
|
const url = `https://${API_ENDPOINT}/v1/projects/${PROJECT_ID}/locations/${LOCATION_ID}/publishers/google/models/${MODEL_ID}:predict`;
|
|
const res = await globalFetch(url, {
|
|
body: bodyData,
|
|
headers: {
|
|
"Content-Type": "application/json",
|
|
"Authorization": "Bearer " + db.google.accessToken
|
|
},
|
|
abortSignal,
|
|
chatId: arg.chatId
|
|
})
|
|
if(res.ok){
|
|
console.log(res.data)
|
|
if(res.data.predictions){
|
|
let output:string = res.data.predictions[0].content
|
|
const ind = output.search(/(system note)|(user)|(assistant):/gi)
|
|
if(ind >= 0){
|
|
output = output.substring(0, ind)
|
|
}
|
|
return {
|
|
type: 'success',
|
|
result: output
|
|
}
|
|
}
|
|
else{
|
|
return {
|
|
type: 'fail',
|
|
result: `${JSON.stringify(res.data)}`
|
|
}
|
|
}
|
|
}
|
|
else{
|
|
return {
|
|
type: 'fail',
|
|
result: `${JSON.stringify(res.data)}`
|
|
}
|
|
}
|
|
}
|
|
case 'gemini-pro':
|
|
case 'gemini-pro-vision':
|
|
case 'gemini-1.5-pro-latest':
|
|
case 'gemini-1.5-flash':
|
|
case 'gemini-ultra':
|
|
case 'gemini-ultra-vision':{
|
|
interface GeminiPart{
|
|
text?:string
|
|
"inlineData"?: {
|
|
"mimeType": string,
|
|
"data": string
|
|
},
|
|
}
|
|
|
|
interface GeminiChat {
|
|
role: "USER"|"MODEL"
|
|
parts:|GeminiPart[]
|
|
}
|
|
|
|
|
|
let reformatedChat:GeminiChat[] = []
|
|
let pendingImage = ''
|
|
|
|
for(let i=0;i<formated.length;i++){
|
|
const chat = formated[i]
|
|
if(chat.memo && chat.memo.startsWith('inlayImage')){
|
|
pendingImage = chat.content
|
|
continue
|
|
}
|
|
if(i === 0){
|
|
if(chat.role === 'user' || chat.role === 'assistant'){
|
|
reformatedChat.push({
|
|
role: chat.role === 'user' ? 'USER' : 'MODEL',
|
|
parts: [{
|
|
text: chat.content
|
|
}]
|
|
})
|
|
}
|
|
else{
|
|
reformatedChat.push({
|
|
role: "USER",
|
|
parts: [{
|
|
text: chat.role + ':' + chat.content
|
|
}]
|
|
})
|
|
}
|
|
}
|
|
else{
|
|
const prevChat = reformatedChat[reformatedChat.length-1]
|
|
const qRole =
|
|
chat.role === 'user' ? 'USER' :
|
|
chat.role === 'assistant' ? 'MODEL' :
|
|
chat.role
|
|
|
|
if(prevChat.role === qRole){
|
|
reformatedChat[reformatedChat.length-1].parts[0].text += '\n' + chat.content
|
|
continue
|
|
}
|
|
else if(chat.role === 'system'){
|
|
if(prevChat.role === 'USER'){
|
|
reformatedChat[reformatedChat.length-1].parts[0].text += '\nsystem:' + chat.content
|
|
}
|
|
else{
|
|
reformatedChat.push({
|
|
role: "USER",
|
|
parts: [{
|
|
text: chat.role + ':' + chat.content
|
|
}]
|
|
})
|
|
}
|
|
}
|
|
else if(chat.role === 'user' && pendingImage !== ''){
|
|
//conver image to jpeg so it can be inlined
|
|
const canv = document.createElement('canvas')
|
|
const img = new Image()
|
|
img.src = pendingImage
|
|
await img.decode()
|
|
canv.width = img.width
|
|
canv.height = img.height
|
|
const ctx = canv.getContext('2d')
|
|
ctx.drawImage(img, 0, 0)
|
|
const base64 = canv.toDataURL('image/jpeg').replace(/^data:image\/jpeg;base64,/, "")
|
|
const mimeType = 'image/jpeg'
|
|
pendingImage = ''
|
|
canv.remove()
|
|
img.remove()
|
|
|
|
reformatedChat.push({
|
|
role: "USER",
|
|
parts: [
|
|
{
|
|
text: chat.content,
|
|
},
|
|
{
|
|
inlineData: {
|
|
mimeType: mimeType,
|
|
data: base64
|
|
}
|
|
}]
|
|
})
|
|
}
|
|
else if(chat.role === 'assistant' || chat.role === 'user'){
|
|
reformatedChat.push({
|
|
role: chat.role === 'user' ? 'USER' : 'MODEL',
|
|
parts: [{
|
|
text: chat.content
|
|
}]
|
|
})
|
|
}
|
|
else{
|
|
reformatedChat.push({
|
|
role: "USER",
|
|
parts: [{
|
|
text: chat.role + ':' + chat.content
|
|
}]
|
|
})
|
|
}
|
|
}
|
|
}
|
|
|
|
const uncensoredCatagory = [
|
|
{
|
|
"category": "HARM_CATEGORY_SEXUALLY_EXPLICIT",
|
|
"threshold": "BLOCK_NONE"
|
|
},
|
|
{
|
|
"category": "HARM_CATEGORY_HATE_SPEECH",
|
|
"threshold": "BLOCK_NONE"
|
|
},
|
|
{
|
|
"category": "HARM_CATEGORY_HARASSMENT",
|
|
"threshold": "BLOCK_NONE"
|
|
},
|
|
{
|
|
"category": "HARM_CATEGORY_DANGEROUS_CONTENT",
|
|
"threshold": "BLOCK_NONE"
|
|
},
|
|
]
|
|
|
|
|
|
const body = {
|
|
contents: reformatedChat,
|
|
generation_config: {
|
|
"maxOutputTokens": maxTokens,
|
|
"temperature": temperature,
|
|
"topP": db.top_p,
|
|
},
|
|
safetySettings: uncensoredCatagory
|
|
}
|
|
|
|
let headers:{[key:string]:string} = {}
|
|
|
|
const PROJECT_ID=db.google.projectId
|
|
const REGION="us-central1"
|
|
if(PROJECT_ID !== 'aigoogle'){
|
|
headers['Authorization'] = "Bearer " + db.google.accessToken
|
|
}
|
|
|
|
const url = PROJECT_ID !== 'aigoogle' ?
|
|
`https://${REGION}-aiplatform.googleapis.com/v1/projects/${PROJECT_ID}/locations/us-central1/publishers/google/models/${aiModel}:streamGenerateContent`
|
|
: `https://generativelanguage.googleapis.com/v1beta/models/${aiModel}:generateContent?key=${db.google.accessToken}`
|
|
const res = await globalFetch(url, {
|
|
headers: headers,
|
|
body: body,
|
|
chatId: arg.chatId
|
|
})
|
|
|
|
if(!res.ok){
|
|
return {
|
|
type: 'fail',
|
|
result: `${JSON.stringify(res.data)}`
|
|
}
|
|
}
|
|
|
|
let fullRes = ''
|
|
|
|
const processDataItem = (data:any) => {
|
|
if(data?.candidates?.[0]?.content?.parts?.[0]?.text){
|
|
fullRes += data.candidates[0].content.parts[0].text
|
|
}
|
|
else if(data?.errors){
|
|
return {
|
|
type: 'fail',
|
|
result: `${JSON.stringify(data.errors)}`
|
|
}
|
|
}
|
|
else{
|
|
return {
|
|
type: 'fail',
|
|
result: `${JSON.stringify(data)}`
|
|
}
|
|
}
|
|
}
|
|
|
|
// traverse responded data if it contains multipart contents
|
|
if (typeof (res.data)[Symbol.iterator] === 'function') {
|
|
for(const data of res.data){
|
|
processDataItem(data)
|
|
}
|
|
} else {
|
|
processDataItem(res.data)
|
|
}
|
|
|
|
return {
|
|
type: 'success',
|
|
result: fullRes
|
|
}
|
|
|
|
}
|
|
case "kobold":{
|
|
const prompt = applyChatTemplate(formated)
|
|
const url = new URL(db.koboldURL)
|
|
if(url.pathname.length < 3){
|
|
url.pathname = 'api/v1/generate'
|
|
}
|
|
|
|
const body:KoboldGenerationInputSchema = {
|
|
"prompt": prompt,
|
|
"temperature": (db.temperature / 100),
|
|
"top_p": db.top_p,
|
|
max_length: maxTokens,
|
|
max_context_length: db.maxContext,
|
|
n: 1
|
|
}
|
|
|
|
const da = await globalFetch(url.toString(), {
|
|
method: "POST",
|
|
body: body,
|
|
headers: {
|
|
"content-type": "application/json",
|
|
},
|
|
abortSignal,
|
|
chatId: arg.chatId
|
|
})
|
|
|
|
if(!da.ok){
|
|
return {
|
|
type: "fail",
|
|
result: da.data,
|
|
noRetry: true
|
|
}
|
|
}
|
|
|
|
const data = da.data
|
|
return {
|
|
type: 'success',
|
|
result: data.results[0].text
|
|
}
|
|
}
|
|
case "novellist":
|
|
case "novellist_damsel":{
|
|
const auth_key = db.novellistAPI;
|
|
const api_server_url = 'https://api.tringpt.com/';
|
|
const logit_bias:string[] = []
|
|
const logit_bias_values:string[] = []
|
|
for(let i=0;i<biasString.length;i++){
|
|
const bia = biasString[i]
|
|
logit_bias.push(bia[0])
|
|
logit_bias_values.push(bia[1].toString())
|
|
}
|
|
const headers = {
|
|
'Authorization': `Bearer ${auth_key}`,
|
|
'Content-Type': 'application/json'
|
|
};
|
|
|
|
const send_body = {
|
|
text: stringlizeAINChat(formated, currentChar?.name ?? '', arg.continue),
|
|
length: maxTokens,
|
|
temperature: temperature,
|
|
top_p: db.ainconfig.top_p,
|
|
top_k: db.ainconfig.top_k,
|
|
rep_pen: db.ainconfig.rep_pen,
|
|
top_a: db.ainconfig.top_a,
|
|
rep_pen_slope: db.ainconfig.rep_pen_slope,
|
|
rep_pen_range: db.ainconfig.rep_pen_range,
|
|
typical_p: db.ainconfig.typical_p,
|
|
badwords: db.ainconfig.badwords,
|
|
model: aiModel === 'novellist_damsel' ? 'damsel' : 'supertrin',
|
|
stoptokens: ["「"].join("<<|>>") + db.ainconfig.stoptokens,
|
|
logit_bias: (logit_bias.length > 0) ? logit_bias.join("<<|>>") : undefined,
|
|
logit_bias_values: (logit_bias_values.length > 0) ? logit_bias_values.join("|") : undefined,
|
|
};
|
|
const response = await globalFetch(api_server_url + '/api', {
|
|
method: 'POST',
|
|
headers: headers,
|
|
body: send_body,
|
|
chatId: arg.chatId
|
|
});
|
|
|
|
if(!response.ok){
|
|
return {
|
|
type: 'fail',
|
|
result: response.data
|
|
}
|
|
}
|
|
|
|
if(response.data.error){
|
|
return {
|
|
'type': 'fail',
|
|
'result': `${response.data.error.replace("token", "api key")}`
|
|
}
|
|
}
|
|
|
|
const result = response.data.data[0];
|
|
const unstr = unstringlizeAIN(result, formated, currentChar?.name ?? '')
|
|
return {
|
|
'type': 'multiline',
|
|
'result': unstr
|
|
}
|
|
}
|
|
case 'risullm-proto':{
|
|
const res = await globalFetch('https://sv.risuai.xyz/risullm', {
|
|
body: {
|
|
messages: formated.map((v) => {
|
|
if(v.role === 'system'){
|
|
return {
|
|
role: "user",
|
|
content: "System: " + v.content
|
|
}
|
|
}
|
|
if(v.role === 'function'){
|
|
return {
|
|
role: "user",
|
|
content: "Function: " + v.content
|
|
|
|
}
|
|
}
|
|
return {
|
|
role: v.role,
|
|
content: v.content
|
|
}
|
|
})
|
|
},
|
|
headers: {
|
|
"X-Api-Key": db.proxyKey
|
|
}
|
|
})
|
|
|
|
const resp:string = res?.data?.response
|
|
|
|
if(!resp){
|
|
return {
|
|
type: 'fail',
|
|
result: JSON.stringify(res.data)
|
|
}
|
|
}
|
|
|
|
return {
|
|
type: 'success',
|
|
result: resp.replace(/\\n/g, '\n')
|
|
}
|
|
}
|
|
case 'ollama-hosted':{
|
|
const ollama = new Ollama({host: db.ollamaURL})
|
|
|
|
const response = await ollama.chat({
|
|
model: db.ollamaModel,
|
|
messages: formated.map((v) => {
|
|
return {
|
|
role: v.role,
|
|
content: v.content
|
|
}
|
|
}).filter((v) => {
|
|
return v.role === 'assistant' || v.role === 'user' || v.role === 'system'
|
|
}),
|
|
stream: true
|
|
})
|
|
|
|
const readableStream = new ReadableStream<StreamResponseChunk>({
|
|
async start(controller){
|
|
for await(const chunk of response){
|
|
controller.enqueue({
|
|
"0": chunk.message.content
|
|
})
|
|
}
|
|
controller.close()
|
|
}
|
|
})
|
|
|
|
return {
|
|
type: 'streaming',
|
|
result: readableStream
|
|
}
|
|
}
|
|
case 'cohere-command-r':
|
|
case 'cohere-command-r-plus':{
|
|
const modelName = aiModel.replace('cohere-', '')
|
|
let lastChatPrompt = ''
|
|
let preamble = ''
|
|
|
|
let lastChat = formated[formated.length-1]
|
|
if(lastChat.role === 'user'){
|
|
lastChatPrompt = lastChat.content
|
|
formated.pop()
|
|
}
|
|
else{
|
|
while(lastChat.role !== 'user'){
|
|
lastChat = formated.pop()
|
|
if(!lastChat){
|
|
return {
|
|
type: 'fail',
|
|
result: 'Cohere requires a user message to generate a response'
|
|
}
|
|
}
|
|
lastChatPrompt = (lastChat.role === 'user' ? '' : `${lastChat.role}: `) + '\n' + lastChat.content + lastChatPrompt
|
|
}
|
|
}
|
|
|
|
const firstChat = formated[0]
|
|
if(firstChat.role === 'system'){
|
|
preamble = firstChat.content
|
|
formated.shift()
|
|
}
|
|
|
|
//reformat chat
|
|
|
|
|
|
|
|
|
|
let body = {
|
|
message: lastChatPrompt,
|
|
chat_history: formated.map((v) => {
|
|
if(v.role === 'assistant'){
|
|
return {
|
|
role: 'CHATBOT',
|
|
message: v.content
|
|
}
|
|
}
|
|
if(v.role === 'system'){
|
|
return {
|
|
role: 'SYSTEM',
|
|
message: v.content
|
|
}
|
|
}
|
|
if(v.role === 'user'){
|
|
return {
|
|
role: 'USER',
|
|
message: v.content
|
|
}
|
|
}
|
|
return null
|
|
}).filter((v) => v !== null).filter((v) => {
|
|
return v.message
|
|
}),
|
|
temperature: temperature,
|
|
k: db.top_k,
|
|
p: (db.top_p > 0.99) ? 0.99 : (db.top_p < 0.01) ? 0.01 : db.top_p,
|
|
presence_penalty: arg.PresensePenalty || (db.PresensePenalty / 100),
|
|
frequency_penalty: arg.frequencyPenalty || (db.frequencyPenalty / 100),
|
|
}
|
|
|
|
if(preamble){
|
|
if(body.chat_history.length > 0){
|
|
// @ts-ignore
|
|
body.preamble = preamble
|
|
}
|
|
else{
|
|
body.message = `system: ${preamble}`
|
|
}
|
|
}
|
|
|
|
console.log(body)
|
|
|
|
const res = await globalFetch('https://api.cohere.com/v1/chat', {
|
|
method: "POST",
|
|
headers: {
|
|
"Authorization": "Bearer " + db.cohereAPIKey,
|
|
"Content-Type": "application/json"
|
|
},
|
|
body: body
|
|
})
|
|
|
|
if(!res.ok){
|
|
return {
|
|
type: 'fail',
|
|
result: JSON.stringify(res.data)
|
|
}
|
|
}
|
|
|
|
const result = res.data.text
|
|
if(!result){
|
|
return {
|
|
type: 'fail',
|
|
result: JSON.stringify(res.data)
|
|
}
|
|
}
|
|
|
|
return {
|
|
type: 'success',
|
|
result: result
|
|
}
|
|
}
|
|
|
|
default:{
|
|
if(raiModel.startsWith('claude-3')){
|
|
let replacerURL = (aiModel === 'reverse_proxy') ? (db.forceReplaceUrl) : ('https://api.anthropic.com/v1/messages')
|
|
let apiKey = (aiModel === 'reverse_proxy') ? db.proxyKey : db.claudeAPIKey
|
|
if(aiModel === 'reverse_proxy' && db.autofillRequestUrl){
|
|
if(replacerURL.endsWith('v1')){
|
|
replacerURL += '/messages'
|
|
}
|
|
else if(replacerURL.endsWith('v1/')){
|
|
replacerURL += 'messages'
|
|
}
|
|
else if(!(replacerURL.endsWith('messages') || replacerURL.endsWith('messages/'))){
|
|
if(replacerURL.endsWith('/')){
|
|
replacerURL += 'v1/messages'
|
|
}
|
|
else{
|
|
replacerURL += '/v1/messages'
|
|
}
|
|
}
|
|
}
|
|
|
|
interface Claude3TextBlock {
|
|
type: 'text',
|
|
text: string,
|
|
cache_control?: {"type": "ephemeral"}
|
|
}
|
|
|
|
interface Claude3ImageBlock {
|
|
type: 'image',
|
|
source: {
|
|
type: 'base64'
|
|
media_type: string,
|
|
data: string
|
|
}
|
|
cache_control?: {"type": "ephemeral"}
|
|
}
|
|
|
|
type Claude3ContentBlock = Claude3TextBlock|Claude3ImageBlock
|
|
|
|
interface Claude3Chat {
|
|
role: 'user'|'assistant'
|
|
content: Claude3ContentBlock[]
|
|
}
|
|
|
|
interface Claude3ExtendedChat {
|
|
role: 'user'|'assistant'
|
|
content: Claude3ContentBlock[]|string
|
|
}
|
|
|
|
let claudeChat: Claude3Chat[] = []
|
|
let systemPrompt:string = ''
|
|
|
|
const addClaudeChat = (chat:{
|
|
role: 'user'|'assistant'
|
|
content: string
|
|
}, multimodals?:MultiModal[]) => {
|
|
if(claudeChat.length > 0 && claudeChat[claudeChat.length-1].role === chat.role){
|
|
let content = claudeChat[claudeChat.length-1].content
|
|
if(multimodals && multimodals.length > 0 && !Array.isArray(content)){
|
|
content = [{
|
|
type: 'text',
|
|
text: content
|
|
}]
|
|
}
|
|
|
|
if(Array.isArray(content)){
|
|
let lastContent = content[content.length-1]
|
|
if( lastContent?.type === 'text'){
|
|
lastContent.text += "\n\n" + chat.content
|
|
content[content.length-1] = lastContent
|
|
}
|
|
else{
|
|
content.push({
|
|
type: 'text',
|
|
text: chat.content
|
|
})
|
|
}
|
|
|
|
if(multimodals && multimodals.length > 0){
|
|
for(const modal of multimodals){
|
|
if(modal.type === 'image'){
|
|
const dataurl = modal.base64
|
|
const base64 = dataurl.split(',')[1]
|
|
const mediaType = dataurl.split(';')[0].split(':')[1]
|
|
|
|
content.unshift({
|
|
type: 'image',
|
|
source: {
|
|
type: 'base64',
|
|
media_type: mediaType,
|
|
data: base64
|
|
}
|
|
})
|
|
}
|
|
}
|
|
}
|
|
}
|
|
claudeChat[claudeChat.length-1].content = content
|
|
}
|
|
else{
|
|
let formatedChat:Claude3Chat = {
|
|
role: chat.role,
|
|
content: [{
|
|
type: 'text',
|
|
text: chat.content
|
|
}]
|
|
}
|
|
if(multimodals && multimodals.length > 0){
|
|
formatedChat.content = [{
|
|
type: 'text',
|
|
text: chat.content
|
|
}]
|
|
for(const modal of multimodals){
|
|
if(modal.type === 'image'){
|
|
const dataurl = modal.base64
|
|
const base64 = dataurl.split(',')[1]
|
|
const mediaType = dataurl.split(';')[0].split(':')[1]
|
|
|
|
formatedChat.content.unshift({
|
|
type: 'image',
|
|
source: {
|
|
type: 'base64',
|
|
media_type: mediaType,
|
|
data: base64
|
|
}
|
|
})
|
|
}
|
|
}
|
|
|
|
}
|
|
claudeChat.push(formatedChat)
|
|
}
|
|
}
|
|
for(const chat of formated){
|
|
switch(chat.role){
|
|
case 'user':{
|
|
addClaudeChat({
|
|
role: 'user',
|
|
content: chat.content
|
|
}, chat.multimodals)
|
|
break
|
|
}
|
|
case 'assistant':{
|
|
addClaudeChat({
|
|
role: 'assistant',
|
|
content: chat.content
|
|
}, chat.multimodals)
|
|
break
|
|
}
|
|
case 'system':{
|
|
if(claudeChat.length === 0){
|
|
systemPrompt += '\n\n' + chat.content
|
|
}
|
|
else{
|
|
addClaudeChat({
|
|
role: 'user',
|
|
content: "System: " + chat.content
|
|
})
|
|
}
|
|
break
|
|
}
|
|
case 'function':{
|
|
//ignore function for now
|
|
break
|
|
}
|
|
}
|
|
}
|
|
if(claudeChat.length === 0 && systemPrompt === ''){
|
|
return {
|
|
type: 'fail',
|
|
result: 'No input'
|
|
}
|
|
}
|
|
if(claudeChat.length === 0 && systemPrompt !== ''){
|
|
claudeChat.push({
|
|
role: 'user',
|
|
content: [{
|
|
type: 'text',
|
|
text: 'Start'
|
|
}]
|
|
})
|
|
systemPrompt = ''
|
|
}
|
|
if(claudeChat[0].role !== 'user'){
|
|
claudeChat.unshift({
|
|
role: 'user',
|
|
content: [{
|
|
type: 'text',
|
|
text: 'Start'
|
|
}]
|
|
})
|
|
}
|
|
if(db.claudeCachingExperimental){
|
|
for(let i = 0;i<4;i++){
|
|
const ind = claudeChat.findLastIndex((v) => {
|
|
if(v.role !== 'user'){
|
|
return false
|
|
}
|
|
if(v.content.length === 0){
|
|
return false
|
|
}
|
|
if(v.content[0].cache_control){ // if it already has cache control, skip
|
|
return false
|
|
}
|
|
return true
|
|
})
|
|
console.log(ind)
|
|
if(ind === -1){
|
|
break
|
|
}
|
|
claudeChat[ind].content[0].cache_control = {
|
|
type: 'ephemeral'
|
|
}
|
|
}
|
|
}
|
|
|
|
let finalChat:Claude3ExtendedChat[] = claudeChat
|
|
|
|
if(aiModel === 'reverse_proxy'){
|
|
finalChat = claudeChat.map((v) => {
|
|
if(v.content.length > 0 && v.content[0].type === 'text'){
|
|
return {
|
|
role: v.role,
|
|
content: v.content[0].text
|
|
}
|
|
}
|
|
})
|
|
}
|
|
|
|
|
|
let body = {
|
|
model: raiModel,
|
|
messages: finalChat,
|
|
system: systemPrompt.trim(),
|
|
max_tokens: maxTokens,
|
|
temperature: temperature,
|
|
top_p: db.top_p,
|
|
top_k: db.top_k,
|
|
stream: useStreaming ?? false
|
|
}
|
|
|
|
if(systemPrompt === ''){
|
|
delete body.system
|
|
}
|
|
|
|
const bedrock = db.claudeAws
|
|
|
|
if(bedrock && aiModel !== 'reverse_proxy'){
|
|
function getCredentialParts(key:string) {
|
|
const [accessKeyId, secretAccessKey, region] = key.split(":");
|
|
|
|
if (!accessKeyId || !secretAccessKey || !region) {
|
|
throw new Error("The key assigned to this request is invalid.");
|
|
}
|
|
|
|
return { accessKeyId, secretAccessKey, region };
|
|
}
|
|
const { accessKeyId, secretAccessKey, region } = getCredentialParts(apiKey);
|
|
|
|
const AMZ_HOST = "bedrock-runtime.%REGION%.amazonaws.com";
|
|
const host = AMZ_HOST.replace("%REGION%", region);
|
|
const stream = false; // todo?
|
|
|
|
// https://docs.aws.amazon.com/bedrock/latest/userguide/model-ids.html
|
|
const modelIDs = [
|
|
"anthropic.claude-v2",
|
|
"anthropic.claude-v2:1",
|
|
"anthropic.claude-3-haiku-20240307-v1:0",
|
|
"anthropic.claude-3-sonnet-20240229-v1:0",
|
|
"anthropic.claude-3-5-sonnet-20240620-v1:0",
|
|
"anthropic.claude-3-opus-20240229-v1:0"
|
|
];
|
|
|
|
const awsModel =
|
|
raiModel.includes("3-opus") ? modelIDs[5] :
|
|
raiModel.includes("3-5-sonnet") ? modelIDs[4] :
|
|
raiModel.includes("3-sonnet") ? modelIDs[3] :
|
|
modelIDs[2];
|
|
const url = `https://${host}/model/${awsModel}/invoke${stream ? "-with-response-stream" : ""}`
|
|
|
|
const params = {
|
|
messages : claudeChat,
|
|
system: systemPrompt.trim(),
|
|
max_tokens: maxTokens,
|
|
// stop_sequences: null,
|
|
temperature: temperature,
|
|
top_p: db.top_p,
|
|
top_k: db.top_k,
|
|
anthropic_version: "bedrock-2023-05-31",
|
|
}
|
|
|
|
const rq = new HttpRequest({
|
|
method: "POST",
|
|
protocol: "https:",
|
|
hostname: host,
|
|
path: `/model/${awsModel}/invoke${stream ? "-with-response-stream" : ""}`,
|
|
headers: {
|
|
["Host"]: host,
|
|
["Content-Type"]: "application/json",
|
|
["accept"]: "application/json",
|
|
},
|
|
body: JSON.stringify(params),
|
|
});
|
|
|
|
const signer = new SignatureV4({
|
|
sha256: Sha256,
|
|
credentials: { accessKeyId, secretAccessKey },
|
|
region,
|
|
service: "bedrock",
|
|
});
|
|
|
|
const signed = await signer.sign(rq);
|
|
|
|
const res = await globalFetch(url, {
|
|
method: "POST",
|
|
body: params,
|
|
headers: signed.headers,
|
|
plainFetchForce: true,
|
|
chatId: arg.chatId
|
|
})
|
|
|
|
if(!res.ok){
|
|
return {
|
|
type: 'fail',
|
|
result: JSON.stringify(res.data)
|
|
}
|
|
}
|
|
if(res.data.error){
|
|
return {
|
|
type: 'fail',
|
|
result: JSON.stringify(res.data.error)
|
|
}
|
|
}
|
|
return {
|
|
type: 'success',
|
|
result: res.data.content[0].text
|
|
|
|
}
|
|
}
|
|
|
|
|
|
let headers:{
|
|
[key:string]:string
|
|
} = {
|
|
"Content-Type": "application/json",
|
|
"x-api-key": apiKey,
|
|
"anthropic-version": "2023-06-01",
|
|
"accept": "application/json",
|
|
}
|
|
|
|
if(db.claudeCachingExperimental){
|
|
headers['anthropic-beta'] = 'prompt-caching-2024-07-31'
|
|
}
|
|
|
|
if(useStreaming){
|
|
|
|
const res = await fetchNative(replacerURL, {
|
|
body: JSON.stringify(body),
|
|
headers: headers,
|
|
method: "POST",
|
|
chatId: arg.chatId
|
|
})
|
|
|
|
if(res.status !== 200){
|
|
return {
|
|
type: 'fail',
|
|
result: await textifyReadableStream(res.body)
|
|
}
|
|
}
|
|
let rerequesting = false
|
|
let breakError = ''
|
|
|
|
|
|
const stream = new ReadableStream<StreamResponseChunk>({
|
|
async start(controller){
|
|
let text = ''
|
|
let reader = res.body.getReader()
|
|
const decoder = new TextDecoder()
|
|
const parser = createParser(async (e) => {
|
|
try {
|
|
if(e.type === 'event'){
|
|
switch(e.event){
|
|
case 'content_block_delta': {
|
|
if(e.data){
|
|
text += JSON.parse(e.data).delta?.text
|
|
controller.enqueue({
|
|
"0": text
|
|
})
|
|
}
|
|
break
|
|
}
|
|
case 'error': {
|
|
if(e.data){
|
|
const errormsg:string = JSON.parse(e.data).error?.message
|
|
if(errormsg && errormsg.toLocaleLowerCase().includes('overload') && db.antiClaudeOverload){
|
|
console.log('Overload detected, retrying...')
|
|
reader.cancel()
|
|
rerequesting = true
|
|
await sleep(2000)
|
|
body.max_tokens -= await tokenize(text)
|
|
if(body.max_tokens < 0){
|
|
body.max_tokens = 0
|
|
}
|
|
if(body.messages.at(-1)?.role !== 'assistant'){
|
|
body.messages.push({
|
|
role: 'assistant',
|
|
content: [{
|
|
type: 'text',
|
|
text: ''
|
|
}]
|
|
})
|
|
}
|
|
let block = body.messages[body.messages.length-1].content
|
|
if(typeof block === 'string'){
|
|
body.messages[body.messages.length-1].content += text
|
|
}
|
|
else if(block[0].type === 'text'){
|
|
block[0].text += text
|
|
}
|
|
const res = await fetchNative(replacerURL, {
|
|
body: JSON.stringify(body),
|
|
headers: {
|
|
"Content-Type": "application/json",
|
|
"x-api-key": apiKey,
|
|
"anthropic-version": "2023-06-01",
|
|
"accept": "application/json",
|
|
},
|
|
method: "POST",
|
|
chatId: arg.chatId
|
|
})
|
|
if(res.status !== 200){
|
|
breakError = 'Error: ' + await textifyReadableStream(res.body)
|
|
break
|
|
}
|
|
reader = res.body.getReader()
|
|
rerequesting = false
|
|
break
|
|
}
|
|
text += "Error:" + JSON.parse(e.data).error?.message
|
|
controller.enqueue({
|
|
"0": text
|
|
})
|
|
}
|
|
break
|
|
}
|
|
}
|
|
}
|
|
} catch (error) {}
|
|
})
|
|
while(true){
|
|
if(rerequesting){
|
|
if(breakError){
|
|
controller.enqueue({
|
|
"0": breakError
|
|
})
|
|
break
|
|
}
|
|
await sleep(1000)
|
|
continue
|
|
}
|
|
try {
|
|
const {done, value} = await reader.read()
|
|
if(done){
|
|
if(rerequesting){
|
|
continue
|
|
}
|
|
break
|
|
}
|
|
parser.feed(decoder.decode(value))
|
|
} catch (error) {
|
|
await sleep(1)
|
|
}
|
|
}
|
|
controller.close()
|
|
},
|
|
cancel(){
|
|
}
|
|
})
|
|
|
|
return {
|
|
type: 'streaming',
|
|
result: stream
|
|
}
|
|
|
|
}
|
|
const res = await globalFetch(replacerURL, {
|
|
body: body,
|
|
headers: headers,
|
|
method: "POST",
|
|
chatId: arg.chatId
|
|
})
|
|
|
|
if(!res.ok){
|
|
return {
|
|
type: 'fail',
|
|
result: JSON.stringify(res.data)
|
|
}
|
|
}
|
|
if(res.data.error){
|
|
return {
|
|
type: 'fail',
|
|
result: JSON.stringify(res.data.error)
|
|
}
|
|
}
|
|
const resText = res?.data?.content?.[0]?.text
|
|
if(!resText){
|
|
return {
|
|
type: 'fail',
|
|
result: JSON.stringify(res.data)
|
|
}
|
|
}
|
|
return {
|
|
type: 'success',
|
|
result: resText
|
|
}
|
|
}
|
|
else if(raiModel.startsWith('claude')){
|
|
|
|
let replacerURL = (aiModel === 'reverse_proxy') ? (db.forceReplaceUrl) : ('https://api.anthropic.com/v1/complete')
|
|
let apiKey = (aiModel === 'reverse_proxy') ? db.proxyKey : db.claudeAPIKey
|
|
if(aiModel === 'reverse_proxy'){
|
|
if(replacerURL.endsWith('v1')){
|
|
replacerURL += '/complete'
|
|
}
|
|
else if(replacerURL.endsWith('v1/')){
|
|
replacerURL += 'complete'
|
|
}
|
|
else if(!(replacerURL.endsWith('complete') || replacerURL.endsWith('complete/'))){
|
|
if(replacerURL.endsWith('/')){
|
|
replacerURL += 'v1/complete'
|
|
}
|
|
else{
|
|
replacerURL += '/v1/complete'
|
|
}
|
|
}
|
|
}
|
|
|
|
for(let i=0;i<formated.length;i++){
|
|
if(arg.isGroupChat && formated[i].name){
|
|
formated[i].content = formated[i].name + ": " + formated[i].content
|
|
}
|
|
formated[i].name = undefined
|
|
}
|
|
|
|
|
|
let latestRole = 'user'
|
|
let requestPrompt = formated.map((v, i) => {
|
|
let prefix = ''
|
|
switch (v.role){
|
|
case "assistant":
|
|
prefix = "\n\nAssistant: "
|
|
break
|
|
case "user":
|
|
prefix = "\n\nHuman: "
|
|
break
|
|
case "system":
|
|
prefix = "\n\nSystem: "
|
|
break
|
|
}
|
|
latestRole = v.role
|
|
if(raiModel.startsWith('claude-2') && (!raiModel.startsWith('claude-2.0'))){
|
|
if(v.role === 'system' && i === 0){
|
|
prefix = ''
|
|
}
|
|
}
|
|
return prefix + v.content
|
|
}).join('')
|
|
|
|
if(latestRole !== 'assistant'){
|
|
requestPrompt += '\n\nAssistant: '
|
|
}
|
|
|
|
|
|
const bedrock = db.claudeAws
|
|
|
|
if(bedrock && aiModel !== 'reverse_proxy'){
|
|
function getCredentialParts(key:string) {
|
|
const [accessKeyId, secretAccessKey, region] = key.split(":");
|
|
|
|
if (!accessKeyId || !secretAccessKey || !region) {
|
|
throw new Error("The key assigned to this request is invalid.");
|
|
}
|
|
|
|
return { accessKeyId, secretAccessKey, region };
|
|
}
|
|
const { accessKeyId, secretAccessKey, region } = getCredentialParts(apiKey);
|
|
|
|
const AMZ_HOST = "bedrock-runtime.%REGION%.amazonaws.com";
|
|
const host = AMZ_HOST.replace("%REGION%", region);
|
|
|
|
const stream = false
|
|
|
|
const LATEST_AWS_V2_MINOR_VERSION = 1;
|
|
let awsModel = `anthropic.claude-v2:${LATEST_AWS_V2_MINOR_VERSION}`;
|
|
|
|
const pattern = /^(claude-)?(instant-)?(v)?(\d+)(\.(\d+))?(-\d+k)?$/i;
|
|
const match = raiModel.match(pattern);
|
|
|
|
if (match) {
|
|
const [, , instant, v, major, dot, minor] = match;
|
|
|
|
if (instant) {
|
|
awsModel = "anthropic.claude-instant-v1";
|
|
}
|
|
|
|
// There's only one v1 model
|
|
else if (major === "1") {
|
|
awsModel = "anthropic.claude-v1";
|
|
}
|
|
|
|
// Try to map Anthropic API v2 models to AWS v2 models
|
|
else if (major === "2") {
|
|
if (minor === "0") {
|
|
awsModel = "anthropic.claude-v2";
|
|
} else if (!v && !dot && !minor) {
|
|
awsModel = "anthropic.claude-v2";
|
|
}
|
|
}
|
|
}
|
|
|
|
const url = `https://${host}/model/${awsModel}/invoke${stream ? "-with-response-stream" : ""}`
|
|
const params = {
|
|
prompt : requestPrompt.startsWith("\n\nHuman: ") ? requestPrompt : "\n\nHuman: " + requestPrompt,
|
|
max_tokens_to_sample: maxTokens,
|
|
stop_sequences: ["\n\nHuman:", "\n\nSystem:", "\n\nAssistant:"],
|
|
temperature: temperature,
|
|
top_p: db.top_p,
|
|
//top_k: db.top_k,
|
|
}
|
|
const rq = new HttpRequest({
|
|
method: "POST",
|
|
protocol: "https:",
|
|
hostname: host,
|
|
path: `/model/${awsModel}/invoke${stream ? "-with-response-stream" : ""}`,
|
|
headers: {
|
|
["Host"]: host,
|
|
["Content-Type"]: "application/json",
|
|
["accept"]: "application/json",
|
|
//"anthropic-version": "2023-06-01",
|
|
},
|
|
body: JSON.stringify(params),
|
|
});
|
|
|
|
|
|
const signer = new SignatureV4({
|
|
sha256: Sha256,
|
|
credentials: { accessKeyId, secretAccessKey },
|
|
region,
|
|
service: "bedrock",
|
|
});
|
|
|
|
const signed = await signer.sign(rq);
|
|
|
|
const da = await globalFetch(url, {
|
|
method: "POST",
|
|
body: params,
|
|
headers: signed.headers,
|
|
plainFetchForce: true,
|
|
chatId: arg.chatId
|
|
})
|
|
|
|
|
|
if((!da.ok) || (da.data.error)){
|
|
return {
|
|
type: 'fail',
|
|
result: `${JSON.stringify(da.data)}`
|
|
}
|
|
}
|
|
|
|
const res = da.data
|
|
|
|
return {
|
|
type: "success",
|
|
result: res.completion,
|
|
}
|
|
}
|
|
|
|
const da = await globalFetch(replacerURL, {
|
|
method: "POST",
|
|
body: {
|
|
prompt : "\n\nHuman: " + requestPrompt,
|
|
model: raiModel,
|
|
max_tokens_to_sample: maxTokens,
|
|
stop_sequences: ["\n\nHuman:", "\n\nSystem:", "\n\nAssistant:"],
|
|
temperature: temperature,
|
|
},
|
|
headers: {
|
|
"Content-Type": "application/json",
|
|
"x-api-key": apiKey,
|
|
"anthropic-version": "2023-06-01",
|
|
"accept": "application/json"
|
|
},
|
|
useRisuToken: aiModel === 'reverse_proxy',
|
|
chatId: arg.chatId
|
|
})
|
|
|
|
if((!da.ok) || (da.data.error)){
|
|
return {
|
|
type: 'fail',
|
|
result: `${JSON.stringify(da.data)}`
|
|
}
|
|
}
|
|
|
|
const res = da.data
|
|
|
|
return {
|
|
type: "success",
|
|
result: res.completion,
|
|
}
|
|
|
|
}
|
|
if(aiModel.startsWith("horde:::")){
|
|
const prompt = applyChatTemplate(formated)
|
|
|
|
const realModel = aiModel.split(":::")[1]
|
|
|
|
const argument = {
|
|
"prompt": prompt,
|
|
"params": {
|
|
"n": 1,
|
|
"max_context_length": db.maxContext + 100,
|
|
"max_length": db.maxResponse,
|
|
"singleline": false,
|
|
"temperature": db.temperature / 100,
|
|
"top_k": db.top_k,
|
|
"top_p": db.top_p,
|
|
},
|
|
"trusted_workers": false,
|
|
"workerslow_workers": true,
|
|
"_blacklist": false,
|
|
"dry_run": false,
|
|
"models": [realModel, realModel.trim(), ' ' + realModel, realModel + ' ']
|
|
}
|
|
|
|
if(realModel === 'auto'){
|
|
delete argument.models
|
|
}
|
|
|
|
let apiKey = '0000000000'
|
|
if(db.hordeConfig.apiKey.length > 2){
|
|
apiKey = db.hordeConfig.apiKey
|
|
}
|
|
|
|
const da = await fetch("https://stablehorde.net/api/v2/generate/text/async", {
|
|
body: JSON.stringify(argument),
|
|
method: "POST",
|
|
headers: {
|
|
"content-type": "application/json",
|
|
"apikey": apiKey
|
|
},
|
|
signal: abortSignal
|
|
})
|
|
|
|
if(da.status !== 202){
|
|
return {
|
|
type: "fail",
|
|
result: await da.text()
|
|
}
|
|
}
|
|
|
|
const json:{
|
|
id:string,
|
|
kudos:number,
|
|
message:string
|
|
} = await da.json()
|
|
|
|
let warnMessage = ""
|
|
if(json.message){
|
|
warnMessage = "with " + json.message
|
|
}
|
|
|
|
while(true){
|
|
await sleep(2000)
|
|
const data = await (await fetch("https://stablehorde.net/api/v2/generate/text/status/" + json.id)).json()
|
|
if(!data.is_possible){
|
|
fetch("https://stablehorde.net/api/v2/generate/text/status/" + json.id, {
|
|
method: "DELETE"
|
|
})
|
|
return {
|
|
type: 'fail',
|
|
result: "Response not possible" + warnMessage,
|
|
noRetry: true
|
|
}
|
|
}
|
|
if(data.done && Array.isArray(data.generations) && data.generations.length > 0){
|
|
const generations:{text:string}[] = data.generations
|
|
if(generations && generations.length > 0){
|
|
return {
|
|
type: "success",
|
|
result: unstringlizeChat(generations[0].text, formated, currentChar?.name ?? '')
|
|
}
|
|
}
|
|
return {
|
|
type: 'fail',
|
|
result: "No Generations when done",
|
|
noRetry: true
|
|
}
|
|
}
|
|
}
|
|
|
|
|
|
}
|
|
if(aiModel.startsWith('hf:::')){
|
|
const realModel = aiModel.split(":::")[1]
|
|
const suggesting = model === "submodel"
|
|
const prompt = applyChatTemplate(formated)
|
|
const v = await runTransformers(prompt, realModel, {
|
|
temperature: temperature,
|
|
max_new_tokens: maxTokens,
|
|
top_k: db.ooba.top_k,
|
|
top_p: db.ooba.top_p,
|
|
repetition_penalty: db.ooba.repetition_penalty,
|
|
typical_p: db.ooba.typical_p,
|
|
})
|
|
return {
|
|
type: 'success',
|
|
result: unstringlizeChat(v.generated_text as string, formated, currentChar?.name ?? '')
|
|
}
|
|
}
|
|
if(aiModel.startsWith('local_')){
|
|
console.log('running local model')
|
|
const suggesting = model === "submodel"
|
|
const prompt = applyChatTemplate(formated)
|
|
const stopStrings = getStopStrings(suggesting)
|
|
console.log(stopStrings)
|
|
const modelPath = aiModel.replace('local_', '')
|
|
const res = await runGGUFModel({
|
|
prompt: prompt,
|
|
modelPath: modelPath,
|
|
temperature: temperature,
|
|
top_p: db.top_p,
|
|
top_k: db.top_k,
|
|
maxTokens: maxTokens,
|
|
presencePenalty: arg.PresensePenalty || (db.PresensePenalty / 100),
|
|
frequencyPenalty: arg.frequencyPenalty || (db.frequencyPenalty / 100),
|
|
repeatPenalty: 0,
|
|
maxContext: db.maxContext,
|
|
stop: stopStrings,
|
|
})
|
|
let decoded = ''
|
|
const transtream = new TransformStream<Uint8Array, StreamResponseChunk>({
|
|
async transform(chunk, control) {
|
|
const decodedChunk = new TextDecoder().decode(chunk)
|
|
decoded += decodedChunk
|
|
control.enqueue({
|
|
"0": decoded
|
|
})
|
|
}
|
|
})
|
|
res.pipeTo(transtream.writable)
|
|
|
|
return {
|
|
type: 'streaming',
|
|
result: transtream.readable
|
|
}
|
|
}
|
|
return {
|
|
type: 'fail',
|
|
result: (language.errors.unknownModel)
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
|
|
let userString = ''
|
|
let requestedTimes = 999
|
|
let refreshTime = 0
|
|
function getOpenUserString(){
|
|
if(refreshTime < Date.now() && requestedTimes > 2 ){
|
|
refreshTime = Date.now() + (300000 * Math.random()) + 60000
|
|
userString = v4()
|
|
requestedTimes = 0
|
|
}
|
|
requestedTimes += 1
|
|
console.log(userString)
|
|
return userString
|
|
}
|
|
|
|
|
|
|
|
export interface KoboldSamplerSettingsSchema {
|
|
rep_pen?: number;
|
|
rep_pen_range?: number;
|
|
rep_pen_slope?: number;
|
|
top_k?: number;
|
|
top_a?: number;
|
|
top_p?: number;
|
|
tfs?: number;
|
|
typical?: number;
|
|
temperature?: number;
|
|
}
|
|
|
|
export interface KoboldGenerationInputSchema extends KoboldSamplerSettingsSchema {
|
|
prompt: string;
|
|
use_memory?: boolean;
|
|
use_story?: boolean;
|
|
use_authors_note?: boolean;
|
|
use_world_info?: boolean;
|
|
use_userscripts?: boolean;
|
|
soft_prompt?: string;
|
|
max_length?: number;
|
|
max_context_length?: number;
|
|
n: number;
|
|
disable_output_formatting?: boolean;
|
|
frmttriminc?: boolean;
|
|
frmtrmblln?: boolean;
|
|
frmtrmspch?: boolean;
|
|
singleline?: boolean;
|
|
disable_input_formatting?: boolean;
|
|
frmtadsnsp?: boolean;
|
|
quiet?: boolean;
|
|
sampler_order?: number[];
|
|
sampler_seed?: number;
|
|
sampler_full_determinism?: boolean;
|
|
} |