mincomk/risuai
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Merge branch 'main' of https://github.com/kwaroran/RisuAI

Browse Source
This commit is contained in:
Kwaroran
2025-03-22 19:09:47 +09:00
parent 38472af4b8 c1aa28f669
commit e895900376
41 changed files with 4715 additions and 175 deletions
Download Patch File Download Diff File Expand all files Collapse all files

13
src/ts/process/index.svelte.ts
View File

@@ -1,5 +1,5 @@
import { get, writable } from "svelte/store";
import { type character, type MessageGenerationInfo, type Chat, changeToPreset } from "../storage/database.svelte";
import { type character, type MessageGenerationInfo, type Chat, changeToPreset, setCurrentChat } from "../storage/database.svelte";
import { DBState } from '../stores.svelte';
import { CharEmotion, selectedCharID } from "../stores.svelte";
import { ChatTokenizer, tokenize, tokenizeNum } from "../tokenizer";
@@ -63,6 +63,7 @@ export const doingChat = writable(false)
export const chatProcessStage = writable(0)
export const abortChat = writable(false)
export let previewFormated:OpenAIChat[] = []
export let previewBody:string = ''
export async function sendChat(chatProcessIndex = -1,arg:{
chatAdditonalTokens?:number,
@@ -70,6 +71,7 @@ export async function sendChat(chatProcessIndex = -1,arg:{
continue?:boolean,
usedContinueTokens?:number,
preview?:boolean
previewPrompt?:boolean
} = {}):Promise<boolean> {
chatProcessStage.set(0)
@@ -694,6 +696,7 @@ export async function sendChat(chatProcessIndex = -1,arg:{
const triggerResult = await runTrigger(currentChar, 'start', {chat: currentChat})
if(triggerResult){
currentChat = triggerResult.chat
setCurrentChat(currentChat)
ms = currentChat.message
currentTokens += triggerResult.tokens
if(triggerResult.stopSending){
@@ -1303,9 +1306,15 @@ export async function sendChat(chatProcessIndex = -1,arg:{
bias: {},
continue: arg.continue,
chatId: generationId,
imageResponse: DBState.db.outputImageModal
imageResponse: DBState.db.outputImageModal,
previewBody: arg.previewPrompt
}, 'model', abortSignal)
if(arg.previewPrompt && req.type === 'success'){
previewBody = req.result
return true
}
let result = ''
let emoChanged = false
let resendChat = false

21
src/ts/process/infunctions.ts
View File

@@ -17,6 +17,7 @@ function toRPN(expression:string) {
'≤': {precedence: 1, associativity: 'Left'},
'≥': {precedence: 1, associativity: 'Left'},
'=': {precedence: 1, associativity: 'Left'},
'≠': {precedence: 1, associativity: 'Left'},
'!': {precedence: 5, associativity: 'Right'},
};
const operatorsKeys = Object.keys(operators);
@@ -27,7 +28,11 @@ function toRPN(expression:string) {
let lastToken = ''
for(let i = 0; i < expression.length; i++) {
if(operatorsKeys.includes(expression[i])) {
const char = expression[i]
if (char === '-' && (i === 0 || operatorsKeys.includes(expression[i - 1]) || expression[i - 1] === '(')) {
lastToken += char
}
else if (operatorsKeys.includes(char)) {
if(lastToken !== '') {
expression2.push(lastToken)
}
@@ -35,10 +40,10 @@ function toRPN(expression:string) {
expression2.push('0')
}
lastToken = ''
expression2.push(expression[i])
expression2.push(char)
}
else{
lastToken += expression[i]
lastToken += char
}
}
@@ -94,6 +99,7 @@ function calculateRPN(expression:string) {
case '≤': stack.push(a <= b ? 1 : 0); break;
case '≥': stack.push(a >= b ? 1 : 0); break;
case '=': stack.push(a === b ? 1 : 0); break;
case '≠': stack.push(a !== b ? 1 : 0); break;
case '!': stack.push(b ? 0 : 1); break;
}
}
@@ -121,7 +127,14 @@ function executeRPNCalculation(text:string) {
return "0"
}
return parsed.toString()
}).replace(/&&/g, '&').replace(/\|\|/g, '|').replace(/<=/g, '≤').replace(/>=/g, '≥').replace(/==/g, '=').replace(/null/gi, '0')
})
.replace(/&&/g, '&')
.replace(/\|\|/g, '|')
.replace(/<=/g, '≤')
.replace(/>=/g, '≥')
.replace(/==/g, '=')
.replace(/!=/g, '≠')
.replace(/null/gi, '0')
const expression = toRPN(text);
const evaluated = calculateRPN(expression);
return evaluated

12
src/ts/process/lua.ts
View File

@@ -23,6 +23,8 @@ interface LuaEngineState {
engine: LuaEngine;
mutex: Mutex;
chat: Chat;
setVar: (key:string, value:string) => void,
getVar: (key:string) => string
}
let LuaEngines = new Map<string, LuaEngineState>()
@@ -55,12 +57,16 @@ export async function runLua(code:string, arg:{
code,
engine: await luaFactory.createEngine({injectObjects: true}),
mutex: new Mutex(),
chat
chat,
setVar,
getVar
}
LuaEngines.set(mode, luaEngineState)
wasEmpty = true
} else {
luaEngineState.chat = chat
luaEngineState.setVar = setVar
luaEngineState.getVar = getVar
}
return await luaEngineState.mutex.runExclusive(async () => {
if (wasEmpty || code !== luaEngineState.code) {
@@ -72,13 +78,13 @@ export async function runLua(code:string, arg:{
if(!LuaSafeIds.has(id) && !LuaEditDisplayIds.has(id)){
return
}
setVar(key, value)
luaEngineState.setVar(key, value)
})
luaEngine.global.set('getChatVar', (id:string,key:string) => {
if(!LuaSafeIds.has(id) && !LuaEditDisplayIds.has(id)){
return
}
return getVar(key)
return luaEngineState.getVar(key)
})
luaEngine.global.set('stopChat', (id:string) => {
if(!LuaSafeIds.has(id)){

6
src/ts/process/memory/hypamemory.ts
View File

@@ -133,9 +133,11 @@ export class HypaProcesser{
}
async addText(texts:string[]) {
const db = getDatabase()
const suffix = (this.model === 'custom' && db.hypaCustomSettings.model) ? `-${db.hypaCustomSettings.model}` : ""
for(let i=0;i<texts.length;i++){
const itm:memoryVector = await this.forage.getItem(texts[i] + '|' + this.model)
const itm:memoryVector = await this.forage.getItem(texts[i] + '|' + this.model + suffix)
if(itm){
itm.alreadySaved = true
this.vectors.push(itm)
@@ -164,7 +166,7 @@ export class HypaProcesser{
for(let i=0;i<memoryVectors.length;i++){
const vec = memoryVectors[i]
if(!vec.alreadySaved){
await this.forage.setItem(texts[i] + '|' + this.model, vec)
await this.forage.setItem(texts[i] + '|' + this.model + suffix, vec)
}
}

378
src/ts/process/request.ts
View File

@@ -22,6 +22,7 @@ import { extractJSON, getGeneralJSONSchema, getOpenAIJSONSchema } from "./templa
import { getModelInfo, LLMFlags, LLMFormat, type LLMModel } from "../model/modellist";
import { runTrigger } from "./triggers";
import { registerClaudeObserver } from "../observer.svelte";
import { v4 } from "uuid";
@@ -43,6 +44,7 @@ interface requestDataArgument{
schema?:string
extractJson?:string
imageResponse?:boolean
previewBody?:boolean
}
interface RequestDataArgumentExtended extends requestDataArgument{
@@ -485,6 +487,13 @@ export async function requestChatDataMain(arg:requestDataArgument, model:ModelMo
targ.customURL = db.forceReplaceUrl
}
if(db.seperateModelsForAxModels){
if(db.seperateModels[model]){
targ.aiModel = db.seperateModels[model]
targ.modelInfo = getModelInfo(targ.aiModel)
}
}
const format = targ.modelInfo.format
targ.formated = reformater(targ.formated, targ.modelInfo)
@@ -521,6 +530,8 @@ export async function requestChatDataMain(arg:requestDataArgument, model:ModelMo
return requestHorde(targ)
case LLMFormat.WebLLM:
return requestWebLLM(targ)
case LLMFormat.OpenAIResponseAPI:
return requestOpenAIResponseAPI(targ)
}
return {
@@ -726,8 +737,8 @@ async function requestOpenAI(arg:RequestDataArgumentExtended):Promise<requestDat
}
}
}
const res = await globalFetch(arg.customURL ?? "https://api.mistral.ai/v1/chat/completions", {
const targs = {
body: applyParameters({
model: requestModel,
messages: reformatedChat,
@@ -739,7 +750,20 @@ async function requestOpenAI(arg:RequestDataArgumentExtended):Promise<requestDat
},
abortSignal: arg.abortSignal,
chatId: arg.chatId
})
} as const
if(arg.previewBody){
return {
type: 'success',
result: JSON.stringify({
url: "https://api.mistral.ai/v1/chat/completions",
body: targs.body,
headers: targs.headers
})
}
}
const res = await globalFetch(arg.customURL ?? "https://api.mistral.ai/v1/chat/completions", targs)
const dat = res.data as any
if(res.ok){
@@ -959,6 +983,17 @@ async function requestOpenAI(arg:RequestDataArgumentExtended):Promise<requestDat
}
}
}
if(arg.previewBody){
return {
type: 'success',
result: JSON.stringify({
url: replacerURL,
body: body,
headers: headers
})
}
}
const da = await fetchNative(replacerURL, {
body: JSON.stringify(body),
method: "POST",
@@ -1140,6 +1175,17 @@ async function requestOpenAI(arg:RequestDataArgumentExtended):Promise<requestDat
}
}
if(arg.previewBody){
return {
type: 'success',
result: JSON.stringify({
url: replacerURL,
body: body,
headers: headers
})
}
}
const res = await globalFetch(replacerURL, {
body: body,
headers: headers,
@@ -1278,6 +1324,15 @@ async function requestOpenAILegacyInstruct(arg:RequestDataArgumentExtended):Prom
//return `\n\n${author}: ${m.content.trim()}`;
}).join("") + `\n## Response\n`;
if(arg.previewBody){
return {
type: 'success',
result: JSON.stringify({
error: "This model is not supported in preview mode"
})
}
}
const response = await globalFetch(arg.customURL ?? "https://api.openai.com/v1/completions", {
body: {
model: "gpt-3.5-turbo-instruct",
@@ -1310,6 +1365,165 @@ async function requestOpenAILegacyInstruct(arg:RequestDataArgumentExtended):Prom
}
interface OAIResponseInputItem {
content:({
type: 'input_text',
text: string
}|{
detail: 'high'|'low'|'auto'
type: 'input_image',
image_url: string
}|{
type: 'input_file',
file_data: string
filename?: string
})[]
role:'user'|'system'|'developer'
}
interface OAIResponseOutputItem {
content:({
type: 'output_text',
text: string,
annotations: []
})[]
type: 'message',
status: 'in_progress'|'complete'|'incomplete'
role:'assistant'
}
type OAIResponseItem = OAIResponseInputItem|OAIResponseOutputItem
async function requestOpenAIResponseAPI(arg:RequestDataArgumentExtended):Promise<requestDataResponse>{
const formated = arg.formated
const db = getDatabase()
const aiModel = arg.aiModel
const maxTokens = arg.maxTokens
const items:OAIResponseItem[] = []
for(let i=0;i<formated.length;i++){
const content = formated[i]
switch(content.role){
case 'function':
break
case 'assistant':{
const item:OAIResponseOutputItem = {
content: [],
role: content.role,
status: 'complete',
type: 'message',
}
item.content.push({
type: 'output_text',
text: content.content,
annotations: []
})
items.push(item)
break
}
case 'user':
case 'system':{
const item:OAIResponseInputItem = {
content: [],
role: content.role
}
item.content.push({
type: 'input_text',
text: content.content
})
content.multimodals ??= []
for(const multimodal of content.multimodals){
if(multimodal.type === 'image'){
item.content.push({
type: 'input_image',
detail: 'auto',
image_url: multimodal.base64
})
}
else{
item.content.push({
type: 'input_file',
file_data: multimodal.base64,
})
}
}
items.push(item)
break
}
}
}
if(items[items.length-1].role === 'assistant'){
(items[items.length-1] as OAIResponseOutputItem).status = 'incomplete'
}
const body = applyParameters({
model: arg.modelInfo.internalID ?? aiModel,
input: items,
max_output_tokens: maxTokens,
tools: [],
store: false
}, ['temperature', 'top_p'], {}, arg.mode)
if(arg.previewBody){
return {
type: 'success',
result: JSON.stringify({
url: "https://api.openai.com/v1/responses",
body: body,
headers: {
"Authorization": "Bearer " + db.openAIKey,
"Content-Type": "application/json"
}
})
}
}
if(db.modelTools.includes('search')){
body.tools.push('web_search_preview')
}
const response = await globalFetch("https://api.openai.com/v1/responses", {
body: body,
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.output?.find((m:OAIResponseOutputItem) => m.type === 'message') as OAIResponseOutputItem)?.content?.find(m => m.type === 'output_text')?.text
if(!text){
return {
type: 'fail',
result: JSON.stringify(response.data)
}
}
return {
type: 'success',
result: text
}
}
async function requestNovelAI(arg:RequestDataArgumentExtended):Promise<requestDataResponse>{
const formated = arg.formated
const db = getDatabase()
@@ -1324,6 +1538,15 @@ async function requestNovelAI(arg:RequestDataArgumentExtended):Promise<requestDa
sequence: number[], bias: number, ensure_sequence_finish: false, generate_once: true
}[] = []
if(arg.previewBody){
return {
type: 'success',
result: JSON.stringify({
error: "This model is not supported in preview mode"
})
}
}
for(let i=0;i<biasString.length;i++){
const bia = biasString[i]
const tokens = await tokenizeNum(bia[0])
@@ -1426,6 +1649,7 @@ async function requestOobaLegacy(arg:RequestDataArgumentExtended):Promise<reques
return risuChatParser(v.replace(/\\n/g, "\n"))
})
}
bodyTemplate = {
'max_new_tokens': db.maxResponse,
'do_sample': db.ooba.do_sample,
@@ -1454,6 +1678,17 @@ async function requestOobaLegacy(arg:RequestDataArgumentExtended):Promise<reques
'X-API-KEY': db.mancerHeader
}
if(arg.previewBody){
return {
type: 'success',
result: JSON.stringify({
url: blockingUrl,
body: bodyTemplate,
headers: headers
})
}
}
if(useStreaming){
const oobaboogaSocket = new WebSocket(streamUrl);
const statusCode = await new Promise((resolve) => {
@@ -1572,6 +1807,17 @@ async function requestOoba(arg:RequestDataArgumentExtended):Promise<requestDataR
}
}
if(arg.previewBody){
return {
type: 'success',
result: JSON.stringify({
url: urlStr,
body: bodyTemplate,
headers: {}
})
}
}
const response = await globalFetch(urlStr, {
body: bodyTemplate,
chatId: arg.chatId
@@ -1598,6 +1844,15 @@ async function requestPlugin(arg:RequestDataArgumentExtended):Promise<requestDat
const maxTokens = arg.maxTokens
const bias = arg.biasString
const v2Function = pluginV2.providers.get(db.currentPluginProvider)
if(arg.previewBody){
return {
type: 'success',
result: JSON.stringify({
error: "Plugin is not supported in preview mode"
})
}
}
const d = v2Function ? (await v2Function(applyParameters({
prompt_chat: formated,
@@ -1606,7 +1861,7 @@ async function requestPlugin(arg:RequestDataArgumentExtended):Promise<requestDat
max_tokens: maxTokens,
}, [
'frequency_penalty','min_p','presence_penalty','repetition_penalty','top_k','top_p','temperature'
], {}, arg.mode) as any)) : await pluginProcess({
], {}, arg.mode) as any, arg.abortSignal)) : await pluginProcess({
bias: bias,
prompt_chat: formated,
temperature: (db.temperature / 100),
@@ -2037,6 +2292,17 @@ async function requestGoogleCloudVertex(arg:RequestDataArgumentExtended):Promise
if(arg.modelInfo.format === LLMFormat.GoogleCloud && arg.useStreaming){
headers['Content-Type'] = 'application/json'
if(arg.previewBody){
return {
type: 'success',
result: JSON.stringify({
url: url,
body: body,
headers: headers
})
}
}
const f = await fetchNative(url, {
headers: headers,
body: JSON.stringify(body),
@@ -2127,6 +2393,17 @@ async function requestGoogleCloudVertex(arg:RequestDataArgumentExtended):Promise
}
}
if(arg.previewBody){
return {
type: 'success',
result: JSON.stringify({
url: url,
body: body,
headers: headers
})
}
}
const res = await globalFetch(url, {
headers: headers,
body: body,
@@ -2240,6 +2517,17 @@ async function requestKobold(arg:RequestDataArgumentExtended):Promise<requestDat
], {
'repetition_penalty': 'rep_pen'
}, arg.mode) as KoboldGenerationInputSchema
if(arg.previewBody){
return {
type: 'success',
result: JSON.stringify({
url: url.toString(),
body: body,
headers: {}
})
}
}
const da = await globalFetch(url.toString(), {
method: "POST",
@@ -2306,6 +2594,18 @@ async function requestNovelList(arg:RequestDataArgumentExtended):Promise<request
logit_bias: (logit_bias.length > 0) ? logit_bias.join("<<|>>") : undefined,
logit_bias_values: (logit_bias_values.length > 0) ? logit_bias_values.join("|") : undefined,
};
if(arg.previewBody){
return {
type: 'success',
result: JSON.stringify({
url: api_server_url + '/api',
body: send_body,
headers: headers
})
}
}
const response = await globalFetch(arg.customURL ?? api_server_url + '/api', {
method: 'POST',
headers: headers,
@@ -2339,6 +2639,15 @@ async function requestOllama(arg:RequestDataArgumentExtended):Promise<requestDat
const formated = arg.formated
const db = getDatabase()
if(arg.previewBody){
return {
type: 'success',
result: JSON.stringify({
error: "Preview body is not supported for Ollama"
})
}
}
const ollama = new Ollama({host: db.ollamaURL})
const response = await ollama.chat({
@@ -2453,6 +2762,20 @@ async function requestCohere(arg:RequestDataArgumentExtended):Promise<requestDat
console.log(body)
if(arg.previewBody){
return {
type: 'success',
result: JSON.stringify({
url: arg.customURL ?? 'https://api.cohere.com/v1/chat',
body: body,
headers: {
"Authorization": "Bearer " + db.cohereAPIKey,
"Content-Type": "application/json"
}
})
}
}
const res = await globalFetch(arg.customURL ?? 'https://api.cohere.com/v1/chat', {
method: "POST",
headers: {
@@ -2548,7 +2871,7 @@ async function requestClaude(arg:RequestDataArgumentExtended):Promise<requestDat
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 = [{
content = [{
type: 'text',
text: content
}]
@@ -2725,6 +3048,9 @@ async function requestClaude(arg:RequestDataArgumentExtended):Promise<requestDat
else if(body?.thinking?.budget_tokens && body?.thinking?.budget_tokens > 0){
body.thinking.type = 'enabled'
}
else if(body?.thinking?.budget_tokens === null){
delete body.thinking
}
if(systemPrompt === ''){
delete body.system
@@ -2783,6 +3109,18 @@ async function requestClaude(arg:RequestDataArgumentExtended):Promise<requestDat
const signed = await signer.sign(rq);
if(arg.previewBody){
return {
type: 'success',
result: JSON.stringify({
url: url,
body: params,
headers: signed.headers
})
}
}
const res = await globalFetch(url, {
method: "POST",
body: params,
@@ -2873,6 +3211,18 @@ async function requestClaude(arg:RequestDataArgumentExtended):Promise<requestDat
headers['anthropic-dangerous-direct-browser-access'] = 'true'
}
if(arg.previewBody){
return {
type: 'success',
result: JSON.stringify({
url: replacerURL,
body: body,
headers: headers
})
}
}
if(db.claudeRetrivalCaching){
registerClaudeObserver({
@@ -3100,6 +3450,15 @@ async function requestHorde(arg:RequestDataArgumentExtended):Promise<requestData
const currentChar = getCurrentCharacter()
const abortSignal = arg.abortSignal
if(arg.previewBody){
return {
type: 'success',
result: JSON.stringify({
error: "Preview body is not supported for Horde"
})
}
}
const prompt = applyChatTemplate(formated)
const realModel = aiModel.split(":::")[1]
@@ -3198,6 +3557,15 @@ async function requestWebLLM(arg:RequestDataArgumentExtended):Promise<requestDat
const temperature = arg.temperature
const realModel = aiModel.split(":::")[1]
const prompt = applyChatTemplate(formated)
if(arg.previewBody){
return {
type: 'success',
result: JSON.stringify({
error: "Preview body is not supported for WebLLM"
})
}
}
const v = await runTransformers(prompt, realModel, {
temperature: temperature,
max_new_tokens: maxTokens,