feat: add trigger effect RunAxLLM (#752)

# PR Checklist
- [ ] Have you checked if it works normally in all models? *Ignore this
if it doesn't use models.*
- [ ] Have you checked if it works normally in all web, local, and node
hosted versions? If it doesn't, have you blocked it in those versions?
- [ ] Have you added type definitions?

# Description
This PR introduces new trigger effect 'RunAxLLM' which allows running
auxiliary model separately from the main model.
Basically, the logic is the same except that a request of type 'otherAx'
is made instead of 'model'.

src/lang/en.ts

@@ -842,6 +842,7 @@ export const languageEnglish = {
     checkCorruption: "Check Corruption",
     showPromptComparison: "Show Prompt Comparison",
     inlayErrorResponse: "Inlay Error Response",
+    triggerEffRunAxLLM: "Run Auxiliary Model",
     hypaV3Settings: {
         descriptionLabel: "HypaMemory V3 is a long-term memory system that uses both summarization and vector search.",
         supaMemoryPromptPlaceHolder: "Leave it blank to use default",

src/lang/ko.ts

@@ -768,6 +768,7 @@ export const languageKorean = {
     "translateBeforeHTMLFormatting": "HTML 포맷 전 번역",
     "retranslate": "다시 번역",
     "loading": "로딩중",
+    "triggerEffRunAxLLM": "보조 모델 실행",
     "autoTranslateCachedOnly": "캐시된 메시지만 자동 번역",
     "hypaV3Settings": {
         "descriptionLabel": "HypaMemory V3는 요약과 벡터 검색을 모두 사용하는 장기 기억 시스템입니다.",

src/lib/SideBars/Scripts/TriggerData.svelte

@@ -304,6 +304,13 @@
                                 index: ''
                             }
                         }
+                        else if(effect.type === 'runAxLLM'){
+                            value.effect[i] = {
+                                type: 'runAxLLM',
+                                value: '',
+                                inputVar: ''
+                            }
+                        }
                     }}>
                         <OptionInput value="setvar">{language.triggerEffSetVar}</OptionInput>
                         <OptionInput value="impersonate">{language.triggerEffImperson}</OptionInput>
@@ -319,6 +326,7 @@
                         <OptionInput value="runImgGen">{language.runImgGen}</OptionInput>
                         <OptionInput value="cutchat">{language.cutChat}</OptionInput>
                         <OptionInput value="modifychat">{language.modifyChat}</OptionInput>
+                        <OptionInput value="runAxLLM">{language.triggerEffRunAxLLM}</OptionInput>
                     </SelectInput>
                     {#if
                         (value.type !== 'start' && (effect.type === 'systemprompt' || effect.type === 'stop')) ||
@@ -333,7 +341,8 @@
                             effect.type === 'showAlert' ||
                             effect.type === 'sendAIprompt' ||
                             effect.type === 'extractRegex' ||
-                            effect.type === 'runImgGen'
+                            effect.type === 'runImgGen' ||
+                            effect.type === 'runAxLLM'
                         )
                     }
                         <span class="text-red-400 text-sm">{language.triggerLowLevelOnly}</span>
@@ -459,6 +468,14 @@
                         <TextAreaInput highlight bind:value={effect.value} />
                     
                     {/if}
+
+                    {#if effect.type === 'runAxLLM'}
+                    <span class="text-textcolor2 text-sm">{language.prompt} <Help key="triggerLLMPrompt" /></span>
+                    <TextAreaInput highlight bind:value={effect.value} />
+
+                    <span class="text-textcolor2 text-sm">{language.resultStoredVar}</span>
+                    <TextInput bind:value={effect.inputVar} />
+                    {/if}
                 {/each}
             </div>
        </div>

src/ts/process/lua.ts

@@ -419,6 +419,64 @@ export async function runLua(code:string, arg:{
                 return true
             })
 
+            luaEngine.global.set('axLLMMain', async (id:string, promptStr:string) => {
+                let prompt:{
+                    role: string,
+                    content: string
+                }[] = JSON.parse(promptStr)
+                if(!LuaLowLevelIds.has(id)){
+                    return
+                }
+                let promptbody:OpenAIChat[] = prompt.map((dict) => {
+                    let role:'system'|'user'|'assistant' = 'assistant'
+                    switch(dict['role']){
+                        case 'system':
+                        case 'sys':
+                            role = 'system'
+                            break
+                        case 'user':
+                            role = 'user'
+                            break
+                        case 'assistant':
+                        case 'bot':
+                        case 'char':{
+                            role = 'assistant'
+                            break
+                        }
+                    }
+
+                    return {
+                        content: dict['content'] ?? '',
+                        role: role,
+                    }
+                })
+                const result = await requestChatData({
+                    formated: promptbody,
+                    bias: {},
+                    useStreaming: false,
+                    noMultiGen: true,
+                }, 'otherAx')
+
+                if(result.type === 'fail'){
+                    return JSON.stringify({
+                        success: false,
+                        result: 'Error: ' + result.result
+                    })
+                }
+
+                if(result.type === 'streaming' || result.type === 'multiline'){
+                    return JSON.stringify({
+                        success: false,
+                        result: result.result
+                    })
+                }
+
+                return JSON.stringify({
+                    success: true,
+                    result: result.result
+                })
+            })
+
             await luaEngine.doString(luaCodeWarper(code))
             luaEngineState.code = code
         }
@@ -538,6 +596,10 @@ function LLM(id, prompt)
     return json.decode(LLMMain(id, json.encode(prompt)):await())
 end
 
+function axLLM(id, prompt)
+    return json.decode(axLLMMain(id, json.encode(prompt)):await())
+end
+
 local editRequestFuncs = {}
 local editDisplayFuncs = {}
 local editInputFuncs = {}

src/ts/process/triggers.ts

@@ -25,7 +25,7 @@ export interface triggerscript{
 
 export type triggerCondition = triggerConditionsVar|triggerConditionsExists|triggerConditionsChatIndex
 
-export type triggerEffect = triggerCode|triggerEffectCutChat|triggerEffectModifyChat|triggerEffectImgGen|triggerEffectRegex|triggerEffectRunLLM|triggerEffectCheckSimilarity|triggerEffectSendAIprompt|triggerEffectShowAlert|triggerEffectSetvar|triggerEffectSystemPrompt|triggerEffectImpersonate|triggerEffectCommand|triggerEffectStop|triggerEffectRunTrigger
+export type triggerEffect = triggerCode|triggerEffectCutChat|triggerEffectModifyChat|triggerEffectImgGen|triggerEffectRegex|triggerEffectRunLLM|triggerEffectCheckSimilarity|triggerEffectSendAIprompt|triggerEffectShowAlert|triggerEffectSetvar|triggerEffectSystemPrompt|triggerEffectImpersonate|triggerEffectCommand|triggerEffectStop|triggerEffectRunTrigger|triggerEffectRunAxLLM
 
 export type triggerConditionsVar = {
     type:'var'|'value'
@@ -138,6 +138,12 @@ export interface triggerEffectRunLLM{
     inputVar: string
 }
 
+export interface triggerEffectRunAxLLM{
+    type: 'runAxLLM',
+    value: string,
+    inputVar: string
+}
+
 export type additonalSysPrompt = {
     start:string,
     historyend: string,
@@ -504,6 +510,7 @@ export async function runTrigger(char:character,mode:triggerMode, arg:{
                     setVar(effect.inputVar, res)
                     break
                 }
+
                 case 'triggerlua':{
                     const triggerCodeResult = await runLua(effect.code,{
                         lowLevelAccess: trigger.lowLevelAccess,
@@ -520,6 +527,33 @@ export async function runTrigger(char:character,mode:triggerMode, arg:{
                     chat = getCurrentChat()
                     break
                 }
+
+                case 'runAxLLM':{
+                    if(!trigger.lowLevelAccess){
+                        break
+                    }
+                    const effectValue = risuChatParser(effect.value,{chara:char})
+                    const varName = effect.inputVar
+                    let promptbody:OpenAIChat[] = parseChatML(effectValue)
+                    if(!promptbody){
+                        promptbody = [{role:'user', content:effectValue}]
+                    }
+                    const result = await requestChatData({
+                        formated: promptbody,
+                        bias: {},
+                        useStreaming: false,
+                        noMultiGen: true,
+                    }, 'otherAx')
+
+                    if(result.type === 'fail' || result.type === 'streaming' || result.type === 'multiline'){
+                        setVar(varName, 'Error: ' + result.result)
+                    }
+                    else{
+                        setVar(varName, result.result)
+                    }
+
+                    break
+                }
             }
         }
     }