Add igp prompt
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@@ -241,6 +241,7 @@ export const languageEnglish = {
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finallyOption1Desc: "This will enable advanced tools, but it will make the UI more complex. Recommended for advanced users.",
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finallyOption1Desc: "This will enable advanced tools, but it will make the UI more complex. Recommended for advanced users.",
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finallyOption2: "No",
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finallyOption2: "No",
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finallyOption2Desc: "This will disable advanced tools, and make the UI more simple. Recommended for new users.",
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finallyOption2Desc: "This will disable advanced tools, and make the UI more simple. Recommended for new users.",
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igpPrompt: "if IGP Prompt is not a blank, it will be executed after the main model request, after main model execution, as a emotion model, adding the result after the main model response."
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},
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},
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triggerDesc: {
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triggerDesc: {
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v2Header: "Header",
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v2Header: "Header",
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@@ -1113,4 +1114,5 @@ export const languageEnglish = {
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fallbackWhenBlankResponse: "Fallback When Blank Response",
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fallbackWhenBlankResponse: "Fallback When Blank Response",
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doNotChangeFallbackModels: "Do Not Change Fallback Models on Preset Change",
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doNotChangeFallbackModels: "Do Not Change Fallback Models on Preset Change",
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customModels: "Custom Models",
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customModels: "Custom Models",
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igpPrompt: "IGP Prompt"
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}
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}
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@@ -988,7 +988,7 @@ export const LLMModels: LLMModel[] = [
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id: 'gemini-2.5-pro-exp-03-25',
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id: 'gemini-2.5-pro-exp-03-25',
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provider: LLMProvider.GoogleCloud,
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provider: LLMProvider.GoogleCloud,
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format: LLMFormat.GoogleCloud,
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format: LLMFormat.GoogleCloud,
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flags: [LLMFlags.geminiBlockOff,LLMFlags.hasImageInput, LLMFlags.hasImageOutput, LLMFlags.poolSupported, LLMFlags.hasAudioInput, LLMFlags.hasVideoInput, LLMFlags.hasStreaming, LLMFlags.requiresAlternateRole],
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flags: [LLMFlags.geminiBlockOff,LLMFlags.hasImageInput, LLMFlags.poolSupported, LLMFlags.hasAudioInput, LLMFlags.hasVideoInput, LLMFlags.hasStreaming, LLMFlags.requiresAlternateRole, LLMFlags.geminiThinking],
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parameters: ['temperature', 'top_k', 'top_p', 'presence_penalty', 'frequency_penalty'],
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parameters: ['temperature', 'top_k', 'top_p', 'presence_penalty', 'frequency_penalty'],
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tokenizer: LLMTokenizer.GoogleCloud,
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tokenizer: LLMTokenizer.GoogleCloud,
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recommended: true
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recommended: true
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@@ -27,7 +27,7 @@ import { runImageEmbedding } from "./transformers";
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import { hanuraiMemory } from "./memory/hanuraiMemory";
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import { hanuraiMemory } from "./memory/hanuraiMemory";
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import { hypaMemoryV2 } from "./memory/hypav2";
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import { hypaMemoryV2 } from "./memory/hypav2";
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import { runLuaEditTrigger } from "./lua";
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import { runLuaEditTrigger } from "./lua";
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import { parseChatML } from "../parser.svelte";
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import { getGlobalChatVar, parseChatML } from "../parser.svelte";
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import { getModelInfo, LLMFlags } from "../model/modellist";
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import { getModelInfo, LLMFlags } from "../model/modellist";
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import { hypaMemoryV3 } from "./memory/hypav3";
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import { hypaMemoryV3 } from "./memory/hypav3";
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import { getModuleAssets } from "./modules";
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import { getModuleAssets } from "./modules";
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@@ -1494,6 +1494,18 @@ export async function sendChat(chatProcessIndex = -1,arg:{
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})
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})
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}
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}
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const igp = risuChatParser(DBState.db.igpPrompt ?? "")
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if(igp){
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const igpFormated = parseChatML(igp)
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const rq = await requestChatData({
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formated: igpFormated,
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bias: {}
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},'emotion', abortSignal)
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DBState.db.characters[selectedChar].chats[selectedChat].message[DBState.db.characters[selectedChar].chats[selectedChat].message.length - 1].data += rq
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}
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if(resendChat){
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if(resendChat){
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doingChat.set(false)
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doingChat.set(false)
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return await sendChat(chatProcessIndex, {
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return await sendChat(chatProcessIndex, {
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@@ -980,6 +980,7 @@ export interface Database{
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params: string
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params: string
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flags: LLMFlags[]
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flags: LLMFlags[]
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}[]
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}[]
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igpPrompt:string
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}
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}
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interface SeparateParameters{
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interface SeparateParameters{
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