diff --git a/package.json b/package.json
index 00723aa0..66885a23 100644
--- a/package.json
+++ b/package.json
@@ -26,6 +26,7 @@
     "@dqbd/tiktoken": "^1.0.7",
     "@huggingface/jinja": "^0.2.2",
     "@huggingface/transformers": "^3.1.1",
+    "@mlc-ai/web-llm": "^0.2.79",
     "@mlc-ai/web-tokenizers": "^0.1.2",
     "@risuai/ccardlib": "^0.4.1",
     "@rollup/rollup-win32-arm64-msvc": "^4.40.1",
diff --git a/pnpm-lock.yaml b/pnpm-lock.yaml
index 63e2c03e..d05f90f4 100644
--- a/pnpm-lock.yaml
+++ b/pnpm-lock.yaml
@@ -38,6 +38,9 @@ importers:
       '@huggingface/transformers':
         specifier: ^3.1.1
         version: 3.1.1
+      '@mlc-ai/web-llm':
+        specifier: ^0.2.79
+        version: 0.2.79
       '@mlc-ai/web-tokenizers':
         specifier: ^0.1.2
         version: 0.1.2
@@ -786,6 +789,9 @@ packages:
     resolution: {integrity: sha512-Yhlar6v9WQgUp/He7BdgzOz8lqMQ8sU+jkCq7Wx8Myc5YFJLbEe7lgui/V7G1qB1DJykHSGwreceSaD60Y0PUQ==}
     hasBin: true
 
+  '@mlc-ai/web-llm@0.2.79':
+    resolution: {integrity: sha512-Hy1ZHQ0o2bZGZoVnGK48+fts/ZSKwLe96xjvqL/6C59Mem9HoHTcFE07NC2E23mRmhd01tL655N6CPeYmwWgwQ==}
+
   '@mlc-ai/web-tokenizers@0.1.2':
     resolution: {integrity: sha512-zpeZjiw8vTuaSjIeoEDYJL1nOrhSL/7eAW7hhqd3CzIodLpuArfyiTZxKwIlew8kkqb0RIxooqeAqtlngh1p8g==}
 
@@ -2508,6 +2514,10 @@ packages:
   lodash@4.17.21:
     resolution: {integrity: sha512-v2kDEe57lecTulaDIuNTPy3Ry4gLGJ6Z1O3vE1krgXZNrsQ+LFTGHVxVjcXPs17LhbZVGedAJv8XZ1tvj5FvSg==}
 
+  loglevel@1.9.2:
+    resolution: {integrity: sha512-HgMmCqIJSAKqo68l0rS2AanEWfkxaZ5wNiEFb5ggm08lDs9Xl2KxBlX3PTcaD2chBM1gXAYf491/M2Rv8Jwayg==}
+    engines: {node: '>= 0.6.0'}
+
   long@5.2.3:
     resolution: {integrity: sha512-lcHwpNoggQTObv5apGNCTdJrO69eHOZMi4BNC+rTLER8iHAqGrUVeLh/irVIM7zTw2bOXA8T6uNPeujwOLg/2Q==}
 
@@ -4366,6 +4376,10 @@ snapshots:
       - supports-color
     optional: true
 
+  '@mlc-ai/web-llm@0.2.79':
+    dependencies:
+      loglevel: 1.9.2
+
   '@mlc-ai/web-tokenizers@0.1.2': {}
 
   '@msgpack/msgpack@2.8.0': {}
@@ -6084,6 +6098,8 @@ snapshots:
 
   lodash@4.17.21: {}
 
+  loglevel@1.9.2: {}
+
   long@5.2.3: {}
 
   lru-cache@10.1.0: {}
diff --git a/src/App.svelte b/src/App.svelte
index 7d21e2d8..be41032c 100644
--- a/src/App.svelte
+++ b/src/App.svelte
@@ -19,6 +19,9 @@
     import CustomGUISettingMenu from './lib/Setting/Pages/CustomGUISettingMenu.svelte';
     import { checkCharOrder } from './ts/globalApi.svelte';
     import { ArrowUpIcon, GlobeIcon, PlusIcon } from 'lucide-svelte';
+    import { hypaV3ModalOpen, hypaV3ProgressStore } from "./ts/stores.svelte";
+    import HypaV3Modal from './lib/Others/HypaV3Modal.svelte';
+    import HypaV3Progress from './lib/Others/HypaV3Progress.svelte';
 
   
     let didFirstSetup: boolean  = $derived(DBState.db?.didFirstSetup)
@@ -167,5 +170,11 @@
     {#if $openPersonaList}
         <ListedPersona close={() => {$openPersonaList = false}} />
     {/if}
+    {#if $hypaV3ModalOpen}
+        <HypaV3Modal />
+    {/if}
     <SavePopupIconComp />
+    {#if $hypaV3ProgressStore.open}
+        <HypaV3Progress />
+    {/if}
 </main>
\ No newline at end of file
diff --git a/src/lang/en.ts b/src/lang/en.ts
index ce9d06df..6de38200 100644
--- a/src/lang/en.ts
+++ b/src/lang/en.ts
@@ -176,6 +176,7 @@ export const languageEnglish = {
         comfyWorkflow: "Put the API workflow of comfy UI. you can get your API workflow in comfy UI by pressing the 'Workflow > Export (API)' button. you must also put {{risu_prompt}} in you workflow text. the {{risu_prompt}} will be replaced with the prompt provided by the Risu.",
         automaticCachePoint: "Automatically creates cache point after the chat ends, if the caching point doesn't exist.",
         experimentalChatCompressionDesc: "Compresses the unused chat data and saves in seperate file. this greatly reduces the size of the chat data, and greatly improves the performance, however its experimental and can be unstable, causing issues in backup feature and more.",
+        promptInfoInsideChatDesc: "When enabled, this stores prompt preset information in the chat metadata. The stored data includes the preset name, active toggles, and the prompt text. This may slightly increase processing time and storage usage.",
     },
     setup: {
         chooseProvider: "Choose AI Provider",
@@ -1122,4 +1123,9 @@ export const languageEnglish = {
     hypaMemoryV2Modal: "Hypa V2 Modal",
     hypaMemoryV3Modal: "Hypa V3 Modal",
     showMenuHypaMemoryModal: "Show Menu Hypa Modal",
+    promptInfoInsideChat: "Add Prompt Info to Chat",
+    promptTextInfoInsideChat: "Add Prompt Text to Chat",
+    promptInfoEmptyMessage: "No prompt information is available for this message.",
+    promptInfoEmptyToggle: "No custom toggles are currently active.",
+    promptInfoEmptyText: "No prompt text has been saved.",
 }
diff --git a/src/lang/ko.ts b/src/lang/ko.ts
index 7382e505..5702a696 100644
--- a/src/lang/ko.ts
+++ b/src/lang/ko.ts
@@ -125,6 +125,7 @@ export const languageKorean = {
         "groupOtherBotRole": "This defines a role that is used in group chat for characters that isn't speaker.",
         "chatHTML": "A HTML that would be inserted as each chat.\n\nYou can use CBS and special tags.\n- `<risutextbox>`: a textbox that would be used to render text\n- `<risuicon>`: an icon for user or assistant\n- `<risubuttons>`: icon buttons for chat edit, translations and etc.\n- `<risugeninfo>`: generation information button.",
         "autoTranslateCachedOnly": "자동 번역 옵션이 켜진 상태에서 활성화하면, 사용자가 이전에 번역한 메시지만 자동으로 번역됩니다.",
+        "promptInfoInsideChatDesc": "활성화되면 채팅 메타데이터에 프롬프트 프리셋 정보를 저장합니다. 저장되는 정보는 프롬프트 프리셋 이름과 활성화된 토글, 그리고 프롬프트 텍스트입니다. 약간의 처리 시간과 용량을 차지할 수 있습니다.",
     },
     "setup": {
         "chooseProvider": "AI 제공자를 선택해 주세요",
@@ -989,4 +990,9 @@ export const languageKorean = {
     "hypaMemoryV2Modal": "하이파 V2 모달",
     "hypaMemoryV3Modal": "하이파 V3 모달",
     "showMenuHypaMemoryModal": "메뉴에서 하이파 모달 보이기",
+    "promptInfoInsideChat": "채팅에 프롬프트 정보 추가하기",
+    "promptTextInfoInsideChat": "채팅에 프롬프트 텍스트 정보 추가하기",
+    "promptInfoEmptyMessage": "이 메시지에 대한 프롬프트 정보가 없습니다.",
+    "promptInfoEmptyToggle": "활성화된 커스텀 토글이 없습니다.",
+    "promptInfoEmptyText": "저장된 프롬프트 텍스트가 없습니다.",
 }
diff --git a/src/lib/ChatScreens/DefaultChatScreen.svelte b/src/lib/ChatScreens/DefaultChatScreen.svelte
index f4449e37..6fa1078e 100644
--- a/src/lib/ChatScreens/DefaultChatScreen.svelte
+++ b/src/lib/ChatScreens/DefaultChatScreen.svelte
@@ -3,7 +3,7 @@
     import Suggestion from './Suggestion.svelte';
     import AdvancedChatEditor from './AdvancedChatEditor.svelte';
     import { CameraIcon, DatabaseIcon, DicesIcon, GlobeIcon, ImagePlusIcon, LanguagesIcon, Laugh, MenuIcon, MicOffIcon, PackageIcon, Plus, RefreshCcwIcon, ReplyIcon, Send, StepForwardIcon, XIcon, BrainIcon } from "lucide-svelte";
-    import { selectedCharID, PlaygroundStore, createSimpleCharacter } from "../../ts/stores.svelte";
+    import { selectedCharID, PlaygroundStore, createSimpleCharacter, hypaV3ModalOpen } from "../../ts/stores.svelte";
     import Chat from "./Chat.svelte";
     import { type Message, type character, type groupChat } from "../../ts/storage/database.svelte";
     import { DBState } from 'src/ts/stores.svelte';
@@ -12,7 +12,7 @@
     import { findCharacterbyId, getUserIconProtrait, messageForm, sleep } from "../../ts/util";
     import { language } from "../../lang";
     import { isExpTranslator, translate } from "../../ts/translator/translator";
-    import { alertError, alertNormal, alertWait, showHypaV2Alert, showHypaV3Alert } from "../../ts/alert";
+    import { alertError, alertNormal, alertWait, showHypaV2Alert } from "../../ts/alert";
     import sendSound from '../../etc/send.mp3'
     import { processScript } from "src/ts/process/scripts";
     import CreatorQuote from "./CreatorQuote.svelte";
@@ -829,17 +829,17 @@
                     {/if}
 
                     {#if DBState.db.showMenuHypaMemoryModal}
-                        {#if DBState.db.supaModelType !== 'none' && (DBState.db.hypav2 || DBState.db.hypaV3)}
+                        {#if (DBState.db.supaModelType !== 'none' && DBState.db.hypav2) || DBState.db.hypaV3}
                             <div class="flex items-center cursor-pointer hover:text-green-500 transition-colors" onclick={() => {
                                 if (DBState.db.hypav2) {
                                     DBState.db.characters[$selectedCharID].chats[DBState.db.characters[$selectedCharID].chatPage].hypaV2Data ??= {
                                         lastMainChunkID: 0,
                                         mainChunks: [],
-                                        chunks: [],
+                                        chunks: []
                                     }
-                                    showHypaV2Alert();
+                                    showHypaV2Alert()
                                 } else if (DBState.db.hypaV3) {
-                                    showHypaV3Alert();
+                                    $hypaV3ModalOpen = true
                                 }
 
                                 openMenu = false
diff --git a/src/lib/Others/AlertComp.svelte b/src/lib/Others/AlertComp.svelte
index ed34cc3e..1dea03e1 100644
--- a/src/lib/Others/AlertComp.svelte
+++ b/src/lib/Others/AlertComp.svelte
@@ -25,6 +25,8 @@
     import { getCurrentCharacter } from "src/ts/storage/database.svelte";
     import { message } from "@tauri-apps/plugin-dialog";
     import HypaV3Modal from './HypaV3Modal.svelte';
+    import Googli from "../UI/Googli.svelte";
+
     let btn
     let input = $state('')
     let cardExportType = $state('realm')
@@ -221,6 +223,9 @@
                     <Button selected={generationInfoMenuIndex === 2} size="sm" onclick={() => {generationInfoMenuIndex = 2}}>
                         {language.log}
                     </Button>
+                    <Button selected={generationInfoMenuIndex === 3} size="sm" onclick={() => {generationInfoMenuIndex = 3}}>
+                        {language.prompt}
+                    </Button>
                     <button class="ml-auto" onclick={() => {
                         alertStore.set({
                             type: 'none',
@@ -291,6 +296,42 @@
                         {/if}
                     {/await}
                 {/if}
+                {#if generationInfoMenuIndex === 3}
+                    {#if Object.keys(DBState.db.characters[$selectedCharID].chats[DBState.db.characters[$selectedCharID].chatPage].message[$alertGenerationInfoStore.idx].promptInfo || {}).length === 0}
+                        <div class="text-gray-300 text-lg mt-2">{language.promptInfoEmptyMessage}</div>
+                    {:else}
+                        <div class="grid grid-cols-2 gap-y-2 gap-x-4 mt-4">
+                            <span class="text-blue-500">Preset Name</span>
+                            <span class="text-blue-500 justify-self-end">{DBState.db.characters[$selectedCharID].chats[DBState.db.characters[$selectedCharID].chatPage].message[$alertGenerationInfoStore.idx].promptInfo.promptName}</span>
+                            <span class="text-purple-500">Toggles</span>
+                            <div class="col-span-2 max-h-32 overflow-y-auto border border-stone-500 rounded p-2 bg-gray-900">
+                                {#if DBState.db.characters[$selectedCharID].chats[DBState.db.characters[$selectedCharID].chatPage].message[$alertGenerationInfoStore.idx].promptInfo.promptToggles.length === 0}
+                                    <div class="text-gray-500 italic text-center py-4">{language.promptInfoEmptyToggle}</div>
+                                {:else}
+                                    <div class="grid grid-cols-2 gap-y-2 gap-x-4">
+                                        {#each DBState.db.characters[$selectedCharID].chats[DBState.db.characters[$selectedCharID].chatPage].message[$alertGenerationInfoStore.idx].promptInfo.promptToggles as toggle}
+                                        <span class="text-gray-200 truncate">{toggle.key}</span>
+                                        <span class="text-gray-200 justify-self-end truncate">{toggle.value}</span>
+                                        {/each}
+                                    </div>
+                                {/if}
+                            </div>
+                            <span class="text-red-500">Prompt Text</span>
+                            <div class="col-span-2 max-h-80 overflow-y-auto border border-stone-500 rounded p-4 bg-gray-900">
+                                {#if !DBState.db.characters[$selectedCharID].chats[DBState.db.characters[$selectedCharID].chatPage].message[$alertGenerationInfoStore.idx].promptInfo.promptText}
+                                    <div class="text-gray-500 italic text-center py-4">{language.promptInfoEmptyText}</div>
+                                {:else}
+                                    {#each DBState.db.characters[$selectedCharID].chats[DBState.db.characters[$selectedCharID].chatPage].message[$alertGenerationInfoStore.idx].promptInfo.promptText as block}
+                                        <div class="mb-2">
+                                            <div class="font-bold text-gray-600">{block.role}</div>
+                                            <pre class="whitespace-pre-wrap text-sm bg-stone-900 p-2 rounded border border-stone-500">{block.content}</pre>
+                                        </div>
+                                    {/each}
+                                {/if}
+                            </div>
+                        </div>
+                    {/if}
+                {/if}
             {:else if $alertStore.type === 'hypaV2'}
                 <div class="flex flex-wrap gap-2 mb-4 max-w-full w-124">
                     <Button selected={generationInfoMenuIndex === 0} size="sm" onclick={() => {generationInfoMenuIndex = 0}}>
@@ -647,10 +688,6 @@
     </div>
 {/if}
 
-{#if $alertStore.type === "hypaV3"}
-    <HypaV3Modal />
-{/if}
-
 <style>
     .break-any{
         word-break: normal;
diff --git a/src/lib/Others/HypaV3Modal.svelte b/src/lib/Others/HypaV3Modal.svelte
index 14975b2a..63ee1be4 100644
--- a/src/lib/Others/HypaV3Modal.svelte
+++ b/src/lib/Others/HypaV3Modal.svelte
@@ -14,23 +14,22 @@
     CheckIcon,
   } from "lucide-svelte";
   import {
-    alertConfirm,
-    alertNormalWait,
-    showHypaV3Alert,
-  } from "../../ts/alert";
+    summarize,
+    getCurrentHypaV3Preset,
+  } from "src/ts/process/memory/hypav3";
+  import { type OpenAIChat } from "src/ts/process/index.svelte";
+  import { processScriptFull, risuChatParser } from "src/ts/process/scripts";
+  import { type Message } from "src/ts/storage/database.svelte";
+  import { translateHTML } from "src/ts/translator/translator";
+  import { alertConfirm, alertNormalWait } from "src/ts/alert";
   import {
     DBState,
-    alertStore,
     selectedCharID,
     settingsOpen,
     SettingsMenuIndex,
-  } from "../../ts/stores.svelte";
-  import { type OpenAIChat } from "../../ts/process/index.svelte";
-  import { processScriptFull, risuChatParser } from "../../ts/process/scripts";
-  import { summarize } from "../../ts/process/memory/hypav3";
-  import { type Message } from "../../ts/storage/database.svelte";
-  import { translateHTML } from "../../ts/translator/translator";
-  import { language } from "../../lang";
+    hypaV3ModalOpen,
+  } from "src/ts/stores.svelte";
+  import { language } from "src/lang";
 
   interface SummaryUI {
     originalRef: HTMLTextAreaElement;
@@ -452,9 +451,7 @@
 
       const summarizeResult = await summarize(toSummarize);
 
-      if (summarizeResult.success) {
-        summaryUIState.rerolledText = summarizeResult.data;
-      }
+      summaryUIState.rerolledText = summarizeResult;
     } catch (error) {
       summaryUIState.rerolledText = "Reroll failed";
     } finally {
@@ -507,7 +504,7 @@
       return null;
     }
 
-    return DBState.db.hypaV3Settings.processRegexScript
+    return getCurrentHypaV3Preset().settings.processRegexScript
       ? await processRegexScript(unprocessed)
       : unprocessed;
   }
@@ -642,7 +639,7 @@
       return null;
     }
 
-    return DBState.db.hypaV3Settings.processRegexScript
+    return getCurrentHypaV3Preset().settings.processRegexScript
       ? await processRegexScript(unprocessed)
       : unprocessed;
   }
@@ -826,7 +823,7 @@
 </script>
 
 <!-- Modal backdrop -->
-<div class="fixed inset-0 z-50 p-1 sm:p-2 bg-black/50">
+<div class="fixed inset-0 z-40 p-1 sm:p-2 bg-black/50">
   <!-- Modal wrapper -->
   <div class="flex justify-center w-full h-full">
     <!-- Modal window -->
@@ -877,13 +874,9 @@
             class="p-2 text-zinc-400 hover:text-zinc-200 transition-colors"
             tabindex="-1"
             onclick={() => {
-              alertStore.set({
-                type: "none",
-                msg: "",
-              });
-
-              settingsOpen.set(true);
-              SettingsMenuIndex.set(2); // Other bot settings
+              $hypaV3ModalOpen = false;
+              $settingsOpen = true;
+              $SettingsMenuIndex = 2; // Other bot settings
             }}
           >
             <SettingsIcon class="w-6 h-6" />
@@ -906,8 +899,6 @@
                   summaries: [],
                   lastSelectedSummaries: [],
                 };
-              } else {
-                showHypaV3Alert();
               }
             }}
           >
@@ -919,10 +910,7 @@
             class="p-2 text-zinc-400 hover:text-zinc-200 transition-colors"
             tabindex="-1"
             onclick={() => {
-              alertStore.set({
-                type: "none",
-                msg: "",
-              });
+              $hypaV3ModalOpen = false;
             }}
           >
             <XIcon class="w-6 h-6" />
@@ -960,8 +948,6 @@
                         )
                       );
                     }
-
-                    showHypaV3Alert();
                   }}
                 >
                   {language.hypaV3Modal.convertButton}
@@ -976,7 +962,7 @@
 
           <!-- Search Bar -->
         {:else if searchUIState}
-          <div class="sticky top-0 z-50 p-2 sm:p-3 bg-zinc-800">
+          <div class="sticky top-0 z-40 p-2 sm:p-3 bg-zinc-800">
             <div class="flex items-center gap-2">
               <div class="relative flex flex-1 items-center">
                 <form
@@ -1093,17 +1079,17 @@
                     <button
                       class="p-2 text-zinc-400 hover:text-rose-300 transition-colors"
                       tabindex="-1"
-                      disabled={!isOrphan(i)}
                       onclick={async () => {
                         if (
-                          await alertConfirm(language.hypaV3Modal.deleteThisConfirmMessage)
+                          await alertConfirm(
+                            language.hypaV3Modal.deleteThisConfirmMessage
+                          )
                         ) {
-                          hypaV3DataState.summaries = hypaV3DataState.summaries.filter(
-                            (_, index) => index !== i
-                          );
+                          hypaV3DataState.summaries =
+                            hypaV3DataState.summaries.filter(
+                              (_, index) => index !== i
+                            );
                         }
-
-                        showHypaV3Alert();
                       }}
                     >
                       <Trash2Icon class="w-4 h-4" />
@@ -1122,8 +1108,6 @@
                         ) {
                           hypaV3DataState.summaries.splice(i + 1);
                         }
-
-                        showHypaV3Alert();
                       }}
                     >
                       <ScissorsLineDashed class="w-4 h-4" />
diff --git a/src/lib/Others/HypaV3Progress.svelte b/src/lib/Others/HypaV3Progress.svelte
new file mode 100644
index 00000000..35d098ab
--- /dev/null
+++ b/src/lib/Others/HypaV3Progress.svelte
@@ -0,0 +1,55 @@
+<script lang="ts">
+  import { hypaV3ProgressStore } from "src/ts/stores.svelte";
+
+  let isExpanded = $state(false);
+
+  const toggleExpand = () => {
+    isExpanded = !isExpanded;
+  };
+</script>
+
+{#if isExpanded}
+  <div
+    class="absolute w-full h-full z-40 flex justify-center items-center pointer-events-none"
+  >
+    <button
+      class="bg-darkbg p-4 break-any rounded-md flex flex-col max-w-3xl max-h-full overflow-y-auto transition-opacity duration-300 pointer-events-auto"
+      type="button"
+      onclick={toggleExpand}
+    >
+      <span class="mb-6 text-left text-gray-500 text-sm"
+        >{$hypaV3ProgressStore.msg || ""}</span
+      >
+      <div
+        class="w-full min-w-64 md:min-w-138 h-2 bg-darkbg border border-darkborderc rounded-md"
+      >
+        <div
+          class="h-full bg-gradient-to-r from-blue-500 to-purple-800 saving-animation transition-[width]"
+        ></div>
+      </div>
+      <span class="w-full mt-6 text-center text-gray-500 text-sm"
+        >{$hypaV3ProgressStore.subMsg || ""}</span
+      >
+    </button>
+  </div>
+{:else}
+  <button
+    class="fixed top-4 right-4 z-40 bg-darkbg p-2 rounded-full shadow-lg transition-all duration-300 flex items-center justify-center"
+    type="button"
+    style="opacity: 0.8;"
+    onclick={toggleExpand}
+    onmouseenter={(e) => (e.currentTarget.style.opacity = "1")}
+    onmouseleave={(e) => (e.currentTarget.style.opacity = "0.8")}
+  >
+    <div class="w-8 h-8 relative">
+      <div
+        class="absolute inset-0 border-t-2 border-red-500 rounded-full animate-spin"
+      ></div>
+      <div
+        class="absolute inset-1 flex items-center justify-center text-xs text-gray-300"
+      >
+        {$hypaV3ProgressStore.miniMsg || ""}
+      </div>
+    </div>
+  </button>
+{/if}
diff --git a/src/lib/Setting/Pages/AdvancedSettings.svelte b/src/lib/Setting/Pages/AdvancedSettings.svelte
index 49a50881..d3a6c60c 100644
--- a/src/lib/Setting/Pages/AdvancedSettings.svelte
+++ b/src/lib/Setting/Pages/AdvancedSettings.svelte
@@ -190,6 +190,17 @@
     <Check bind:check={DBState.db.enableDevTools} name={language.enableDevTools}>
     </Check>
 </div>
+<div class="flex items-center mt-4">
+    <Check bind:check={DBState.db.promptInfoInsideChat} name={language.promptInfoInsideChat}>
+         <Help key="promptInfoInsideChatDesc"/>
+    </Check>
+</div>
+{#if DBState.db.promptInfoInsideChat}
+    <div class="flex items-center mt-4">
+        <Check bind:check={DBState.db.promptTextInfoInsideChat} name={language.promptTextInfoInsideChat}>
+        </Check>
+    </div>
+{/if}
 <div class="flex items-center mt-4">
     <Check bind:check={DBState.db.dynamicAssets} name={language.dynamicAssets}>
         <Help key="dynamicAssets"/>
diff --git a/src/lib/Setting/Pages/OtherBotSettings.svelte b/src/lib/Setting/Pages/OtherBotSettings.svelte
index 474eb59b..5d655eab 100644
--- a/src/lib/Setting/Pages/OtherBotSettings.svelte
+++ b/src/lib/Setting/Pages/OtherBotSettings.svelte
@@ -3,15 +3,14 @@
     import { language } from "src/lang";
     import Help from "src/lib/Others/Help.svelte";
     import { selectSingleFile } from "src/ts/util";
-    
-    import { DBState } from 'src/ts/stores.svelte';
-    import { isTauri, saveAsset } from "src/ts/globalApi.svelte";
+    import { alertError } from "src/ts/alert";
+    import { DBState, selectedCharID } from 'src/ts/stores.svelte';
+    import { isTauri, saveAsset, downloadFile } from "src/ts/globalApi.svelte";
     import NumberInput from "src/lib/UI/GUI/NumberInput.svelte";
     import TextInput from "src/lib/UI/GUI/TextInput.svelte";
     import SelectInput from "src/lib/UI/GUI/SelectInput.svelte";
     import OptionInput from "src/lib/UI/GUI/OptionInput.svelte";
     import SliderInput from "src/lib/UI/GUI/SliderInput.svelte";
-    import Button from "src/lib/UI/GUI/Button.svelte";
     import { getCharImage } from "src/ts/characters";
     import Arcodion from "src/lib/UI/Arcodion.svelte";
     import CheckInput from "src/lib/UI/GUI/CheckInput.svelte";
@@ -19,7 +18,9 @@
     import { untrack } from "svelte";
     import { tokenizePreset } from "src/ts/process/prompt";
     import { getCharToken } from "src/ts/tokenizer";
-    import { selectedCharID } from "src/ts/stores.svelte";
+    import { PlusIcon, PencilIcon, TrashIcon, DownloadIcon, FolderUpIcon } from "lucide-svelte";
+    import { alertError, alertInput, alertConfirm, alertNormal } from "src/ts/alert";
+    import { createHypaV3Preset } from "src/ts/process/memory/hypav3";
 
     $effect.pre(() => {
         DBState.db.NAIImgConfig ??= {
@@ -41,6 +42,7 @@
             autoSmea:false,
             legacy_uc:false,
             use_coords:false,
+            cfg_rescale:0,
             v4_prompt:{
                 caption:{
                     base_caption:'',
@@ -55,7 +57,12 @@
                     char_captions:[]
                 },
                 legacy_uc:false,
-            }
+            },
+            reference_image_multiple: [],
+            reference_strength_multiple: [0.7],
+            vibe_data: undefined,
+            vibe_model_selection: undefined,
+            noise_schedule: 'karras'
         }
         if (DBState.db.NAIImgConfig.sampler === 'ddim_v3'){
             DBState.db.NAIImgConfig.sm = false
@@ -67,25 +74,35 @@
 
     // HypaV3
     $effect(() => {
-        const newValue = Math.min(DBState.db.hypaV3Settings.recentMemoryRatio, 1);
+        const settings = DBState.db.hypaV3Presets?.[DBState.db.hypaV3PresetId]?.settings;
+        const currentValue = settings?.similarMemoryRatio;
+
+        if (!currentValue) return;
 
         untrack(() => {
-            DBState.db.hypaV3Settings.recentMemoryRatio = newValue;
-            
-            if (newValue + DBState.db.hypaV3Settings.similarMemoryRatio > 1) {
-                DBState.db.hypaV3Settings.similarMemoryRatio = 1 - newValue;
+            const newValue = Math.min(currentValue, 1);
+
+            settings.similarMemoryRatio = newValue;
+
+            if (newValue + settings.recentMemoryRatio > 1) {
+                settings.recentMemoryRatio = 1 - newValue;
             }
         })
     });
 
     $effect(() => {
-        const newValue = Math.min(DBState.db.hypaV3Settings.similarMemoryRatio, 1);
+        const settings = DBState.db.hypaV3Presets?.[DBState.db.hypaV3PresetId]?.settings;
+        const currentValue = settings?.recentMemoryRatio;
+
+        if (!currentValue) return;
 
         untrack(() => {
-            DBState.db.hypaV3Settings.similarMemoryRatio = newValue;
+            const newValue = Math.min(currentValue, 1);
 
-            if (newValue + DBState.db.hypaV3Settings.recentMemoryRatio > 1) {
-                DBState.db.hypaV3Settings.recentMemoryRatio = 1 - newValue;
+            settings.recentMemoryRatio = newValue;
+
+            if (newValue + settings.similarMemoryRatio > 1) {
+                settings.similarMemoryRatio = 1 - newValue;
             }
         })
     });
@@ -164,7 +181,7 @@
                 <OptionInput value="comfy" >ComfyUI (Legacy)</OptionInput>
             {/if}
         </SelectInput>
-        
+
         {#if DBState.db.sdProvider === 'webui'}
         <span class="text-draculared text-xs mb-2">You must use WebUI with --api flag</span>
             <span class="text-draculared text-xs mb-2">You must use WebUI without agpl license or use unmodified version with agpl license to observe the contents of the agpl license.</span>
@@ -175,17 +192,17 @@
             <TextInput size="sm" marginBottom placeholder="https://..." bind:value={DBState.db.webUiUrl}/>
             <span class="text-textcolor">Steps</span>
             <NumberInput size="sm" marginBottom min={0} max={100} bind:value={DBState.db.sdSteps}/>
-            
+
             <span class="text-textcolor">CFG Scale</span>
             <NumberInput size="sm" marginBottom min={0} max={20} bind:value={DBState.db.sdCFG}/>
-        
+
             <span class="text-textcolor">Width</span>
             <NumberInput size="sm" marginBottom min={0} max={2048} bind:value={DBState.db.sdConfig.width}/>
             <span class="text-textcolor">Height</span>
             <NumberInput size="sm" marginBottom min={0} max={2048} bind:value={DBState.db.sdConfig.height}/>
             <span class="text-textcolor">Sampler</span>
             <TextInput size="sm" marginBottom bind:value={DBState.db.sdConfig.sampler_name}/>
-            
+
             <div class="flex items-center mt-2">
                 <Check bind:check={DBState.db.sdConfig.enable_hr} name='Enable Hires'/>
             </div>
@@ -263,6 +280,13 @@
             <span class="text-textcolor">CFG rescale</span>
             <NumberInput size="sm" marginBottom min={0} max={1} bind:value={DBState.db.NAIImgConfig.cfg_rescale}/>
 
+            <span class="text-textcolor">Noise Schedule</span>
+            <SelectInput className="mt-2 mb-4" bind:value={DBState.db.NAIImgConfig.noise_schedule}>
+                <OptionInput value="karras">karras</OptionInput>
+                <OptionInput value="exponential">exponential</OptionInput>
+                <OptionInput value="polyexponential">polyexponential</OptionInput>
+            </SelectInput>
+
             {#if !DBState.db.NAII2I || DBState.db.NAIImgConfig.sampler !== 'ddim_v3'}
                 <Check bind:check={DBState.db.NAIImgConfig.sm} name="Use SMEA"/>
             {:else if DBState.db.NAIImgModel === 'nai-diffusion-4-full'
@@ -273,13 +297,17 @@
 
             {#if DBState.db.NAIImgModel === 'nai-diffusion-4-full'
             || DBState.db.NAIImgModel === 'nai-diffusion-4-curated-preview'}
+
+                <span class="text-textcolor">Prompt Guidance Rescale</span>
+                <SliderInput marginBottom min={0} max={1} step={0.02} fixed={2} bind:value={DBState.db.NAIImgConfig.cfg_rescale} />
+
+
                 <Check bind:check={DBState.db.NAIImgConfig.autoSmea} name='Auto Smea'/>
                 <Check bind:check={DBState.db.NAIImgConfig.use_coords} name='Use coords'/>
                 <Check bind:check={DBState.db.NAIImgConfig.legacy_uc} name='Use legacy uc'/>
 
                 <Check bind:check={DBState.db.NAIImgConfig.v4_prompt.use_coords} name='Use v4 prompt coords'/>
                 <Check bind:check={DBState.db.NAIImgConfig.v4_prompt.use_order} name='Use v4 prompt order'/>
-
                 <Check bind:check={DBState.db.NAIImgConfig.v4_negative_prompt.legacy_uc} name='Use v4 negative prompt legacy uc'/>
             {/if}
 
@@ -321,43 +349,138 @@
 
             <Check bind:check={DBState.db.NAIREF} name="Enable Reference" className="mt-4"/>
 
-            {#if DBState.db.NAIREF}
+            <!--{#if DBState.db.NAIREF}-->
+            <!--    <span class="text-textcolor mt-4">Information Extracted</span>-->
+            <!--    <SliderInput min={0} max={1} step={0.01} bind:value={DBState.db.NAIImgConfig.InfoExtracted}/>-->
+            <!--    <span class="text-textcolor2 mb-6 text-sm">{DBState.db.NAIImgConfig.InfoExtracted}</span>-->
+            <!--    <span class="text-textcolor">Reference Strength</span>-->
+            <!--    <SliderInput min={0} max={1} step={0.01} bind:value={DBState.db.NAIImgConfig.RefStrength}/>-->
+            <!--    <span class="text-textcolor2 mb-6 text-sm">{DBState.db.NAIImgConfig.RefStrength}</span>-->
 
+            <!--    <span class="text-textcolor">Reference image</span>-->
+            <!--    <button onclick={async () => {-->
+            <!--        const img = await selectSingleFile([-->
+            <!--            'jpg',-->
+            <!--            'jpeg',-->
+            <!--            'png',-->
+            <!--            'webp'-->
+            <!--        ])-->
+            <!--        if(!img){-->
+            <!--            return null-->
+            <!--        }-->
+            <!--        const saveId = await saveAsset(img.data)-->
+            <!--        DBState.db.NAIImgConfig.refimage = saveId-->
+            <!--    }}>-->
+            <!--        {#if DBState.db.NAIImgConfig.refimage === ''}-->
+            <!--            <div class="rounded-md h-20 w-20 shadow-lg bg-textcolor2 cursor-pointer hover:text-green-500"></div>-->
+            <!--        {:else}-->
+            <!--            {#await getCharImage(DBState.db.NAIImgConfig.refimage, 'css')}-->
+            <!--                <div class="rounded-md h-20 w-20 shadow-lg bg-textcolor2 cursor-pointer hover:text-green-500"></div>-->
+            <!--            {:then im}-->
+            <!--                <div class="rounded-md h-20 w-20 shadow-lg bg-textcolor2 cursor-pointer hover:text-green-500" style={im}></div>-->
+            <!--            {/await}-->
+            <!--        {/if}-->
+            <!--    </button>-->
+            <!--{/if}-->
+
+            <span class="text-textcolor mt-4">Vibe</span>
+            <button onclick={async () => {
+                const file = await selectSingleFile(['naiv4vibe'])
+                if(!file){
+                    return null
+                }
+                try {
+                    const vibeData = JSON.parse(new TextDecoder().decode(file.data))
+                    if (vibeData.version !== 1 || vibeData.identifier !== "novelai-vibe-transfer") {
+                        alertError("Invalid vibe file. Version must be 1.")
+                        return
+                    }
+
+                    // Store the vibe data
+                    DBState.db.NAIImgConfig.vibe_data = vibeData
+
+                    // Set the thumbnail as preview image for display
+                    if (vibeData.thumbnail) {
+                        // Clear the array and add the thumbnail
+                        DBState.db.NAIImgConfig.reference_image_multiple = [];
+
+                        // Set default model selection based on current model
+                        if (DBState.db.NAIImgModel.includes('nai-diffusion-4-full')) {
+                            DBState.db.NAIImgConfig.vibe_model_selection = 'v4full';
+                        } else if (DBState.db.NAIImgModel.includes('nai-diffusion-4-curated')) {
+                            DBState.db.NAIImgConfig.vibe_model_selection = 'v4curated';
+                        }
+
+                        // Set InfoExtracted to the first value for the selected model
+                        const selectedModel = DBState.db.NAIImgConfig.vibe_model_selection;
+                        if (selectedModel && vibeData.encodings[selectedModel]) {
+                            const encodings = vibeData.encodings[selectedModel];
+                            const firstKey = Object.keys(encodings)[0];
+                            if (firstKey) {
+                                DBState.db.NAIImgConfig.InfoExtracted = Number(encodings[firstKey].params.information_extracted);
+                            }
+                        }
+                    }
+
+                    // Initialize reference_strength_multiple if not set
+                    if (!DBState.db.NAIImgConfig.reference_strength_multiple || !Array.isArray(DBState.db.NAIImgConfig.reference_strength_multiple)) {
+                        DBState.db.NAIImgConfig.reference_strength_multiple = [0.7];
+                    }
+                } catch (error) {
+                    alertError("Error parsing vibe file: " + error)
+                }
+            }}>
+                <div class="rounded-md h-20 w-20 shadow-lg bg-textcolor2 cursor-pointer hover:text-green-500 flex items-center justify-center">
+                    <span class="text-sm">Upload Vibe</span>
+                </div>
+            </button>
+
+            {#if DBState.db.NAIImgConfig.vibe_data}
+                <div class="mt-2 relative">
+                    <img src={DBState.db.NAIImgConfig.vibe_data.thumbnail} alt="Vibe Preview" class="rounded-md h-60 shadow-lg" />
+                    <button 
+                        onclick={() => {
+                            DBState.db.NAIImgConfig.vibe_data = undefined;
+                            DBState.db.NAIImgConfig.vibe_model_selection = undefined;
+                        }}
+                        class="absolute top-2 right-2 bg-red-500 hover:bg-red-700 text-white font-bold py-1 px-2 rounded"
+                    >
+                        Delete
+                    </button>
+                </div>
+
+                <span class="text-textcolor mt-4">Vibe Model</span>
+                <SelectInput className="mt-2 mb-4" bind:value={DBState.db.NAIImgConfig.vibe_model_selection} onchange={(e) => {
+                    // When vibe model changes, set InfoExtracted to the first value
+                    if (DBState.db.NAIImgConfig.vibe_data?.encodings &&
+                        DBState.db.NAIImgConfig.vibe_model_selection &&
+                        DBState.db.NAIImgConfig.vibe_data.encodings[DBState.db.NAIImgConfig.vibe_model_selection]) {
+                        const encodings = DBState.db.NAIImgConfig.vibe_data.encodings[DBState.db.NAIImgConfig.vibe_model_selection];
+                        const firstKey = Object.keys(encodings)[0];
+                        if (firstKey) {
+                            DBState.db.NAIImgConfig.InfoExtracted = Number(encodings[firstKey].params.information_extracted);
+                        }
+                    }
+                }}>
+                    {#if DBState.db.NAIImgConfig.vibe_data.encodings?.v4full}
+                        <OptionInput value="v4full">nai-diffusion-4-full</OptionInput>
+                    {/if}
+                    {#if DBState.db.NAIImgConfig.vibe_data.encodings?.v4curated}
+                        <OptionInput value="v4curated">nai-diffusion-4-curated</OptionInput>
+                    {/if}
+                </SelectInput>
 
                 <span class="text-textcolor mt-4">Information Extracted</span>
-                <SliderInput min={0} max={1} step={0.01} bind:value={DBState.db.NAIImgConfig.InfoExtracted}/>
-                <span class="text-textcolor2 mb-6 text-sm">{DBState.db.NAIImgConfig.InfoExtracted}</span>
-                <span class="text-textcolor">Reference Strength</span>
-                <SliderInput min={0} max={1} step={0.01} bind:value={DBState.db.NAIImgConfig.RefStrength}/>
-                <span class="text-textcolor2 mb-6 text-sm">{DBState.db.NAIImgConfig.RefStrength}</span>
-
-
-
-
-                <span class="text-textcolor">Reference image</span>
-                <button onclick={async () => {
-                    const img = await selectSingleFile([
-                        'jpg',
-                        'jpeg',
-                        'png',
-                        'webp'
-                    ])
-                    if(!img){
-                        return null
-                    }
-                    const saveId = await saveAsset(img.data)
-                    DBState.db.NAIImgConfig.refimage = saveId
-                }}>
-                    {#if DBState.db.NAIImgConfig.refimage === ''}
-                        <div class="rounded-md h-20 w-20 shadow-lg bg-textcolor2 cursor-pointer hover:text-green-500"></div>
-                    {:else}
-                        {#await getCharImage(DBState.db.NAIImgConfig.refimage, 'css')}
-                            <div class="rounded-md h-20 w-20 shadow-lg bg-textcolor2 cursor-pointer hover:text-green-500"></div>
-                        {:then im}
-                            <div class="rounded-md h-20 w-20 shadow-lg bg-textcolor2 cursor-pointer hover:text-green-500" style={im}></div>
-                        {/await}
+                <SelectInput className="mt-2 mb-4" bind:value={DBState.db.NAIImgConfig.InfoExtracted}>
+                    {#if DBState.db.NAIImgConfig.vibe_model_selection && DBState.db.NAIImgConfig.vibe_data.encodings[DBState.db.NAIImgConfig.vibe_model_selection]}
+                        {#each Object.entries(DBState.db.NAIImgConfig.vibe_data.encodings[DBState.db.NAIImgConfig.vibe_model_selection]) as [key, value]}
+                            <OptionInput value={value.params.information_extracted}>{value.params.information_extracted}</OptionInput>
+                        {/each}
                     {/if}
-                </button>
+                </SelectInput>
+
+                <span class="text-textcolor mt-4">Reference Strength Multiple</span>
+                <SliderInput marginBottom min={0} max={1} step={0.1} fixed={2} bind:value={DBState.db.NAIImgConfig.reference_strength_multiple[0]} />
             {/if}
         {/if}
 
@@ -481,16 +604,16 @@
 
     <span class="text-textcolor mt-2">ElevenLabs API key</span>
     <TextInput size="sm" marginBottom bind:value={DBState.db.elevenLabKey}/>
-    
+
     <span class="text-textcolor mt-2">VOICEVOX URL</span>
     <TextInput size="sm" marginBottom bind:value={DBState.db.voicevoxUrl}/>
-    
+
     <span class="text-textcolor">OpenAI Key</span>
     <TextInput size="sm" marginBottom bind:value={DBState.db.openAIKey}/>
 
     <span class="text-textcolor mt-2">NovelAI API key</span>
     <TextInput size="sm" marginBottom placeholder="pst-..." bind:value={DBState.db.NAIApiKey}/>
-    
+
     <span class="text-textcolor">Huggingface Key</span>
     <TextInput size="sm" marginBottom bind:value={DBState.db.huggingfaceKey} placeholder="hf_..."/>
 
@@ -542,20 +665,11 @@
                 DBState.db.hanuraiEnable = false
                 DBState.db.hypaV3 = false
             } else if (value === 'hypaV3') {
-                DBState.db.supaModelType = 'subModel'
                 DBState.db.memoryAlgorithmType = 'hypaMemoryV3'
-                DBState.db.hypav2 = false
+                DBState.db.supaModelType = 'none'
                 DBState.db.hanuraiEnable = false
+                DBState.db.hypav2 = false
                 DBState.db.hypaV3 = true
-                DBState.db.hypaV3Settings.memoryTokensRatio = 0.2
-                DBState.db.hypaV3Settings.extraSummarizationRatio = 0
-                DBState.db.hypaV3Settings.maxChatsPerSummary = 4
-                DBState.db.hypaV3Settings.recentMemoryRatio = 0.4
-                DBState.db.hypaV3Settings.similarMemoryRatio = 0.4
-                DBState.db.hypaV3Settings.enableSimilarityCorrection = false
-                DBState.db.hypaV3Settings.preserveOrphanedMemory = false
-                DBState.db.hypaV3Settings.processRegexScript = false
-                DBState.db.hypaV3Settings.doNotSummarizeUserMessage = false
             } else {
                 DBState.db.supaModelType = 'none'
                 DBState.db.memoryAlgorithmType = 'none'
@@ -597,46 +711,191 @@
             <span class="text-textcolor">{language.hypaAllocatedTokens}</span>
             <NumberInput size="sm" marginBottom bind:value={DBState.db.hypaAllocatedTokens} min={100} />
         {:else if DBState.db.hypaV3}
-            <span class="mb-2 text-textcolor2 text-sm text-wrap break-words max-w-full">{language.hypaV3Settings.descriptionLabel}</span>
-            <span class="text-textcolor mt-4">{language.SuperMemory} {language.model}</span>
-            <SelectInput className="mt-2 mb-2" bind:value={DBState.db.supaModelType}>
-                <OptionInput value="distilbart">distilbart-cnn-6-6 (Free/Local)</OptionInput>
-                <OptionInput value="subModel">{language.submodel}</OptionInput>
-            </SelectInput>
-            <span class="text-textcolor">{language.summarizationPrompt} <Help key="summarizationPrompt"/></span>
-            <div class="mb-2">
-                <TextAreaInput size="sm" placeholder={language.hypaV3Settings.supaMemoryPromptPlaceHolder} bind:value={DBState.db.supaMemoryPrompt} />
-            </div>
-            {#await getMaxMemoryRatio() then maxMemoryRatio}
-            <span class="text-textcolor">{language.hypaV3Settings.maxMemoryTokensRatioLabel}</span>
-            <NumberInput marginBottom disabled size="sm" value={maxMemoryRatio} />
-            {:catch error}
-            <span class="text-red-400">{language.hypaV3Settings.maxMemoryTokensRatioError}</span>
-            {/await}
-            <span class="text-textcolor">{language.hypaV3Settings.memoryTokensRatioLabel}</span>
-            <SliderInput marginBottom min={0} max={1} step={0.01} fixed={2} bind:value={DBState.db.hypaV3Settings.memoryTokensRatio} />
-            <span class="text-textcolor">{language.hypaV3Settings.extraSummarizationRatioLabel}</span>
-            <SliderInput marginBottom min={0} max={1 - DBState.db.hypaV3Settings.memoryTokensRatio} step={0.01} fixed={2} bind:value={DBState.db.hypaV3Settings.extraSummarizationRatio} />
-            <span class="text-textcolor">{language.hypaV3Settings.maxChatsPerSummaryLabel}</span>
-            <NumberInput marginBottom size="sm" min={1} bind:value={DBState.db.hypaV3Settings.maxChatsPerSummary} />
-            <span class="text-textcolor">{language.hypaV3Settings.recentMemoryRatioLabel}</span>
-            <SliderInput marginBottom min={0} max={1} step={0.01} fixed={2} bind:value={DBState.db.hypaV3Settings.recentMemoryRatio} />
-            <span class="text-textcolor">{language.hypaV3Settings.similarMemoryRatioLabel}</span>
-            <SliderInput marginBottom min={0} max={1} step={0.01} fixed={2} bind:value={DBState.db.hypaV3Settings.similarMemoryRatio} />
-            <span class="text-textcolor">{language.hypaV3Settings.randomMemoryRatioLabel}</span>
-            <NumberInput marginBottom disabled size="sm" value={parseFloat((1 - DBState.db.hypaV3Settings.recentMemoryRatio - DBState.db.hypaV3Settings.similarMemoryRatio).toFixed(2))} />
-            <div class="flex mb-2">
-                <Check name={language.hypaV3Settings.enableSimilarityCorrectionLabel} bind:check={DBState.db.hypaV3Settings.enableSimilarityCorrection} />
-            </div>
-            <div class="flex mb-2">
-                <Check name={language.hypaV3Settings.preserveOrphanedMemoryLabel} bind:check={DBState.db.hypaV3Settings.preserveOrphanedMemory} />
-            </div>
-            <div class="flex mb-2">
-                <Check name={language.hypaV3Settings.applyRegexScriptWhenRerollingLabel} bind:check={DBState.db.hypaV3Settings.processRegexScript} />
-            </div>
-            <div class="flex mb-2">
-                <Check name={language.hypaV3Settings.doNotSummarizeUserMessageLabel} bind:check={DBState.db.hypaV3Settings.doNotSummarizeUserMessage} />
+            <span class="max-w-full mb-6 text-sm text-wrap break-words text-textcolor2">{language.hypaV3Settings.descriptionLabel}</span>
+            <span class="text-textcolor">Preset</span>
+            <select class={"border border-darkborderc focus:border-borderc rounded-md shadow-sm text-textcolor bg-transparent focus:ring-borderc focus:ring-2 focus:outline-none transition-colors duration-200 text-md px-4 py-2 mb-1"}
+                bind:value={DBState.db.hypaV3PresetId}
+            >
+                {#each DBState.db.hypaV3Presets as preset, i}
+                    <option class="bg-darkbg appearance-none" value={i}>{preset.name}</option>
+                {/each}
+            </select>
+
+            <div class="flex items-center mb-8">
+                <button class="mr-2 text-textcolor2 hover:text-green-500 cursor-pointer" onclick={() => {
+                    const newPreset = createHypaV3Preset()
+                    const presets = DBState.db.hypaV3Presets
+
+                    presets.push(newPreset)
+                    DBState.db.hypaV3Presets = presets
+                    DBState.db.hypaV3PresetId = DBState.db.hypaV3Presets.length - 1
+                }}>
+                    <PlusIcon size={24}/>
+                </button>
+
+                <button class="mr-2 text-textcolor2 hover:text-green-500 cursor-pointer" onclick={async () => {
+                    const presets = DBState.db.hypaV3Presets
+
+                    if(presets.length === 0){
+                        alertError("There must be least one preset.")
+                        return
+                    }
+
+                    const id = DBState.db.hypaV3PresetId
+                    const preset = presets[id]
+                    const newName = await alertInput(`Enter new name for ${preset.name}`)
+
+                    if (!newName || newName.trim().length === 0) return
+
+                    preset.name = newName
+                    DBState.db.hypaV3Presets = presets
+                }}>
+                    <PencilIcon size={24}/>
+                </button>
+
+                <button class="mr-2 text-textcolor2 hover:text-green-500 cursor-pointer" onclick={async (e) => {
+                    const presets = DBState.db.hypaV3Presets
+
+                    if(presets.length <= 1){
+                        alertError("There must be least one preset.")
+                        return
+                    }
+
+                    const id = DBState.db.hypaV3PresetId
+                    const preset = presets[id]
+                    const confirmed = await alertConfirm(`${language.removeConfirm}${preset.name}`)
+
+                    if (!confirmed) return
+
+                    DBState.db.hypaV3PresetId = 0
+                    presets.splice(id, 1)
+                    DBState.db.hypaV3Presets = presets
+                }}>
+                    <TrashIcon size={24}/>
+                </button>
+
+                <div class="ml-2 mr-4 w-px h-full bg-darkborderc"></div>
+
+                <button class="mr-2 text-textcolor2 hover:text-green-500 cursor-pointer" onclick={async() => {
+                    try {
+                        const presets = DBState.db.hypaV3Presets
+                        
+                        if(presets.length === 0){
+                            alertError("There must be least one preset.")
+                            return
+                        }
+
+                        const id = DBState.db.hypaV3PresetId
+                        const preset = presets[id]
+                        const bytesExport = Buffer.from(JSON.stringify({
+                            type: 'risu',
+                            ver: 1,
+                            data: preset
+                        }), 'utf-8')
+                        
+                        await downloadFile(`hypaV3_export_${preset.name}.json`, bytesExport)
+                        alertNormal(language.successExport)
+                    } catch (error) {
+                        alertError(`${error}`)
+                    }
+                }}>
+                    <DownloadIcon size={24}/>
+                </button>
+
+                <button class="mr-2 text-textcolor2 hover:text-green-500 cursor-pointer" onclick={async() => {
+                    try {
+                        const bytesImport = (await selectSingleFile(['json'])).data
+
+                        if(!bytesImport) return
+
+                        const objImport = JSON.parse(Buffer.from(bytesImport).toString('utf-8'))
+
+                        if(objImport.type !== 'risu' || !objImport.data) return
+
+                        const newPreset = createHypaV3Preset(
+                            objImport.data.name || "Imported Preset",
+                            objImport.data.settings || {}
+                        );
+                        const presets = DBState.db.hypaV3Presets
+                        
+                        presets.push(newPreset)
+                        DBState.db.hypaV3Presets = presets
+                        DBState.db.hypaV3PresetId = DBState.db.hypaV3Presets.length - 1
+
+                        alertNormal(language.successImport)
+                    } catch (error) {
+                        alertError(`${error}`)
+                    }
+                }}>
+                    <FolderUpIcon size={24}/>
+                </button>
             </div>
+
+            {#if DBState.db.hypaV3Presets?.[DBState.db.hypaV3PresetId]?.settings}
+                {@const settings = DBState.db.hypaV3Presets[DBState.db.hypaV3PresetId].settings}
+
+                <span class="text-textcolor">{language.SuperMemory} {language.model}</span>
+                <SelectInput className="mb-4" bind:value={settings.summarizationModel}>
+                    <OptionInput value="subModel">{language.submodel}</OptionInput>
+                    {#if "gpu" in navigator}
+                        <OptionInput value="Qwen3-1.7B-q4f32_1-MLC">Qwen3 1.7B (GPU)</OptionInput>
+                        <OptionInput value="Qwen3-4B-q4f32_1-MLC">Qwen3 4B (GPU)</OptionInput>
+                        <OptionInput value="Qwen3-8B-q4f32_1-MLC">Qwen3 8B (GPU)</OptionInput>
+                    {/if}
+                </SelectInput>
+                <span class="text-textcolor">{language.summarizationPrompt} <Help key="summarizationPrompt"/></span>
+                <div class="mb-4">
+                    <TextAreaInput size="sm" placeholder={language.hypaV3Settings.supaMemoryPromptPlaceHolder} bind:value={settings.summarizationPrompt} />
+                </div>
+                {#await getMaxMemoryRatio() then maxMemoryRatio}
+                <span class="text-textcolor">{language.hypaV3Settings.maxMemoryTokensRatioLabel}</span>
+                <NumberInput marginBottom disabled size="sm" value={maxMemoryRatio} />
+                {:catch error}
+                <span class="mb-4 text-red-400">{language.hypaV3Settings.maxMemoryTokensRatioError}</span>
+                {/await}
+                <span class="text-textcolor">{language.hypaV3Settings.memoryTokensRatioLabel}</span>
+                <SliderInput marginBottom min={0} max={1} step={0.01} fixed={2} bind:value={settings.memoryTokensRatio} />
+                <span class="text-textcolor">{language.hypaV3Settings.extraSummarizationRatioLabel}</span>
+                <SliderInput marginBottom min={0} max={1 - settings.memoryTokensRatio} step={0.01} fixed={2} bind:value={settings.extraSummarizationRatio} />
+                <span class="text-textcolor">{language.hypaV3Settings.maxChatsPerSummaryLabel}</span>
+                <NumberInput marginBottom size="sm" min={1} bind:value={settings.maxChatsPerSummary} />
+                <span class="text-textcolor">{language.hypaV3Settings.recentMemoryRatioLabel}</span>
+                <SliderInput marginBottom min={0} max={1} step={0.01} fixed={2} bind:value={settings.recentMemoryRatio} />
+                <span class="text-textcolor">{language.hypaV3Settings.similarMemoryRatioLabel}</span>
+                <SliderInput marginBottom min={0} max={1} step={0.01} fixed={2} bind:value={settings.similarMemoryRatio} />
+                <span class="text-textcolor">{language.hypaV3Settings.randomMemoryRatioLabel}</span>
+                <NumberInput marginBottom disabled size="sm" value={parseFloat((1 - settings.recentMemoryRatio - settings.similarMemoryRatio).toFixed(2))} />
+                <div class="mb-2">
+                    <Check name={language.hypaV3Settings.preserveOrphanedMemoryLabel} bind:check={settings.preserveOrphanedMemory} />
+                </div>
+                <div class="mb-2">
+                    <Check name={language.hypaV3Settings.applyRegexScriptWhenRerollingLabel} bind:check={settings.processRegexScript} />
+                </div>
+                <div class="mb-2">
+                    <Check name={language.hypaV3Settings.doNotSummarizeUserMessageLabel} bind:check={settings.doNotSummarizeUserMessage} />
+                </div>
+                <Arcodion name="Advanced Settings" styled>
+                    <div class="mb-2">
+                        <Check name="Use Experimental Implementation" bind:check={settings.useExperimentalImpl} />
+                    </div>
+                    {#if settings.useExperimentalImpl}
+                        <span class="text-textcolor">Summarization Requests Per Minute</span>
+                        <NumberInput marginBottom size="sm" min={1} bind:value={settings.summarizationRequestsPerMinute} />
+                        <span class="text-textcolor">Summarization Max Concurrent</span>
+                        <NumberInput marginBottom size="sm" min={1} max={10} bind:value={settings.summarizationMaxConcurrent} />
+                        <span class="text-textcolor">Embedding Requests Per Minute</span>
+                        <NumberInput marginBottom size="sm" min={1} bind:value={settings.embeddingRequestsPerMinute} />
+                        <span class="text-textcolor">Embedding Max Concurrent</span>
+                        <NumberInput marginBottom size="sm" min={1} max={10} bind:value={settings.embeddingMaxConcurrent} />
+                    {:else}
+                        <div class="mb-2">
+                            <Check name={language.hypaV3Settings.enableSimilarityCorrectionLabel} bind:check={settings.enableSimilarityCorrection} />
+                        </div>
+                    {/if}
+                </Arcodion>
+            {/if}
+
+            <div class="mb-8"></div>
         {:else if (DBState.db.supaModelType !== 'none' && DBState.db.hypav2 === false && DBState.db.hypaV3 === false)}
             <span class="mb-2 text-textcolor2 text-sm text-wrap break-words max-w-full">{language.supaDesc}</span>
             <span class="text-textcolor mt-4">{language.SuperMemory} {language.model}</span>
@@ -663,14 +922,17 @@
         <span class="text-textcolor">{language.embedding}</span>
         <SelectInput className="mt-2 mb-2" bind:value={DBState.db.hypaModel}>
             {#if 'gpu' in navigator}
+                <OptionInput value="MiniLMGPU">MiniLM L6 v2 (GPU)</OptionInput>
                 <OptionInput value="nomicGPU">Nomic Embed Text v1.5 (GPU)</OptionInput>
                 <OptionInput value="bgeSmallEnGPU">BGE Small English (GPU)</OptionInput>
                 <OptionInput value="bgem3GPU">BGE Medium 3 (GPU)</OptionInput>
+                <OptionInput value="multiMiniLMGPU">Multilingual MiniLM L12 v2 (GPU)</OptionInput>
             {/if}
             <OptionInput value="MiniLM">MiniLM L6 v2 (CPU)</OptionInput>
             <OptionInput value="nomic">Nomic Embed Text v1.5 (CPU)</OptionInput>
             <OptionInput value="bgeSmallEn">BGE Small English (CPU)</OptionInput>
             <OptionInput value="bgem3">BGE Medium 3 (CPU)</OptionInput>
+            <OptionInput value="multiMiniLM">Multilingual MiniLM L12 v2 (CPU)</OptionInput>
             <OptionInput value="openai3small">OpenAI text-embedding-3-small</OptionInput>
             <OptionInput value="openai3large">OpenAI text-embedding-3-large</OptionInput>
             <OptionInput value="ada">OpenAI Ada</OptionInput>
@@ -692,4 +954,4 @@
         {/if}
 
     </Arcodion>
-{/if}
\ No newline at end of file
+{/if}
diff --git a/src/lib/SideBars/CharConfig.svelte b/src/lib/SideBars/CharConfig.svelte
index c4c90a6e..3fa58c3f 100644
--- a/src/lib/SideBars/CharConfig.svelte
+++ b/src/lib/SideBars/CharConfig.svelte
@@ -3,12 +3,12 @@
     import { tokenizeAccurate } from "../../ts/tokenizer";
     import { saveImage as saveAsset, type Database, type character, type groupChat } from "../../ts/storage/database.svelte";
     import { DBState } from 'src/ts/stores.svelte';
-    import { CharConfigSubMenu, MobileGUI, ShowRealmFrameStore, selectedCharID } from "../../ts/stores.svelte";
+    import { CharConfigSubMenu, MobileGUI, ShowRealmFrameStore, selectedCharID, hypaV3ModalOpen } from "../../ts/stores.svelte";
     import { PlusIcon, SmileIcon, TrashIcon, UserIcon, ActivityIcon, BookIcon, User, CurlyBraces, Volume2Icon, DownloadIcon, FolderUpIcon, Share2Icon } from 'lucide-svelte'
     import Check from "../UI/GUI/CheckInput.svelte";
     import { addCharEmotion, addingEmotion, getCharImage, rmCharEmotion, selectCharImg, makeGroupImage, removeChar, changeCharImage } from "../../ts/characters";
     import LoreBook from "./LoreBook/LoreBookSetting.svelte";
-    import { alertConfirm, alertMd, alertNormal, alertSelectChar, alertTOS, showHypaV2Alert, showHypaV3Alert } from "../../ts/alert";
+    import { alertConfirm, alertMd, alertNormal, alertSelectChar, alertTOS, showHypaV2Alert } from "../../ts/alert";
     import BarIcon from "./BarIcon.svelte";
     import { findCharacterbyId, getAuthorNoteDefaultText, parseKeyValue, selectMultipleFile, selectSingleFile } from "../../ts/util";
     import { onDestroy } from "svelte";
@@ -1103,10 +1103,10 @@
             >
                 {language.hypaMemoryV2Modal}
             </Button>
-        {:else if DBState.db.supaModelType !== 'none' && DBState.db.hypaV3}
+        {:else if DBState.db.hypaV3}
             <Button
                 onclick={() => {
-                    showHypaV3Alert()
+                    $hypaV3ModalOpen = true
                 }}
                 className="mt-4"
             >
diff --git a/src/lib/SideBars/Toggles.svelte b/src/lib/SideBars/Toggles.svelte
index c980a6af..afefa2bd 100644
--- a/src/lib/SideBars/Toggles.svelte
+++ b/src/lib/SideBars/Toggles.svelte
@@ -53,9 +53,9 @@
             <CheckInput bind:check={DBState.db.jailbreakToggle} name={language.jailbreakToggle} reverse />
         </div>
         {@render toggles(true)}
-        {#if DBState.db.supaModelType !== 'none' || DBState.db.hanuraiEnable}
+        {#if DBState.db.supaModelType !== 'none' || DBState.db.hanuraiEnable || DBState.db.hypaV3}
             <div class="flex mt-2 items-center w-full" class:justify-end={$MobileGUI}>
-                <CheckInput bind:check={chara.supaMemory} reverse name={DBState.db.hanuraiEnable ? language.hanuraiMemory : DBState.db.hypaMemory ? language.ToggleHypaMemory : language.ToggleSuperMemory}/>
+                <CheckInput bind:check={chara.supaMemory} reverse name={DBState.db.hypaV3 ? language.ToggleHypaMemory : DBState.db.hanuraiEnable ? language.hanuraiMemory : DBState.db.hypaMemory ? language.ToggleHypaMemory : language.ToggleSuperMemory}/>
             </div>
         {/if}
     </div>
@@ -64,9 +64,9 @@
         <CheckInput bind:check={DBState.db.jailbreakToggle} name={language.jailbreakToggle}/>
     </div>
     {@render toggles()}
-    {#if DBState.db.supaModelType !== 'none' || DBState.db.hanuraiEnable}
+    {#if DBState.db.supaModelType !== 'none' || DBState.db.hanuraiEnable || DBState.db.hypaV3}
         <div class="flex mt-2 items-center">
-            <CheckInput bind:check={chara.supaMemory} name={DBState.db.hanuraiEnable ? language.hanuraiMemory : DBState.db.hypaMemory ? language.ToggleHypaMemory : language.ToggleSuperMemory}/>
+            <CheckInput bind:check={chara.supaMemory} name={DBState.db.hypaV3 ? language.ToggleHypaMemory : DBState.db.hanuraiEnable ? language.hanuraiMemory : DBState.db.hypaMemory ? language.ToggleHypaMemory : language.ToggleSuperMemory}/>
         </div>
     {/if}
 {/if}
\ No newline at end of file
diff --git a/src/lib/UI/GUI/OptionInput.svelte b/src/lib/UI/GUI/OptionInput.svelte
index 2112e776..4494e294 100644
--- a/src/lib/UI/GUI/OptionInput.svelte
+++ b/src/lib/UI/GUI/OptionInput.svelte
@@ -1,7 +1,7 @@
 <option value={value} selected={selected} class="bg-darkbg appearance-none">{@render children?.()}</option>
 <script lang="ts">
     interface Props {
-        value: string;
+        value: string | number;
         selected?: boolean;
         children?: import('svelte').Snippet;
     }
diff --git a/src/lib/UI/GUI/SelectInput.svelte b/src/lib/UI/GUI/SelectInput.svelte
index 5dd3f6ac..68d17b84 100644
--- a/src/lib/UI/GUI/SelectInput.svelte
+++ b/src/lib/UI/GUI/SelectInput.svelte
@@ -17,7 +17,7 @@
 </select>
 <script lang="ts">
     interface Props {
-        value: string;
+        value: string | number;
         className?: string;
         size?: 'sm'|'md'|'lg'|'xl';
         children?: import('svelte').Snippet;
diff --git a/src/ts/alert.ts b/src/ts/alert.ts
index c7c96a88..746f6797 100644
--- a/src/ts/alert.ts
+++ b/src/ts/alert.ts
@@ -10,7 +10,7 @@ export interface alertData{
     type: 'error'|'normal'|'none'|'ask'|'wait'|'selectChar'
             |'input'|'toast'|'wait2'|'markdown'|'select'|'login'
             |'tos'|'cardexport'|'requestdata'|'addchar'|'hypaV2'|'selectModule'
-            |'chatOptions'|'pukmakkurit'|'branches'|'hypaV3'|'progress',
+            |'chatOptions'|'pukmakkurit'|'branches'|'progress',
     msg: string,
     submsg?: string
 }
@@ -319,10 +319,3 @@ export function showHypaV2Alert(){
         'msg': ""
     })
 }
-
-export function showHypaV3Alert(){
-    alertStoreImported.set({
-        'type': 'hypaV3',
-        'msg': ""
-    })
-}
\ No newline at end of file
diff --git a/src/ts/process/index.svelte.ts b/src/ts/process/index.svelte.ts
index 65bb4157..5b10df9e 100644
--- a/src/ts/process/index.svelte.ts
+++ b/src/ts/process/index.svelte.ts
@@ -1,12 +1,12 @@
 import { get, writable } from "svelte/store";
-import { type character, type MessageGenerationInfo, type Chat, changeToPreset, setCurrentChat } from "../storage/database.svelte";
+import { type character, type MessageGenerationInfo, type Chat, type MessagePresetInfo, changeToPreset, setCurrentChat } from "../storage/database.svelte";
 import { DBState } from '../stores.svelte';
 import { CharEmotion, selectedCharID } from "../stores.svelte";
 import { ChatTokenizer, tokenize, tokenizeNum } from "../tokenizer";
 import { language } from "../../lang";
 import { alertError, alertToast } from "../alert";
 import { loadLoreBookV3Prompt } from "./lorebook.svelte";
-import { findCharacterbyId, getAuthorNoteDefaultText, getPersonaPrompt, getUserName, isLastCharPunctuation, trimUntilPunctuation } from "../util";
+import { findCharacterbyId, getAuthorNoteDefaultText, getPersonaPrompt, getUserName, isLastCharPunctuation, trimUntilPunctuation, parseToggleSyntax } from "../util";
 import { requestChatData } from "./request";
 import { stableDiff } from "./stableDiff";
 import { processScript, processScriptFull, risuChatParser } from "./scripts";
@@ -30,7 +30,7 @@ import { runLuaEditTrigger } from "./lua";
 import { getGlobalChatVar, parseChatML } from "../parser.svelte";
 import { getModelInfo, LLMFlags } from "../model/modellist";
 import { hypaMemoryV3 } from "./memory/hypav3";
-import { getModuleAssets } from "./modules";
+import { getModuleAssets, getModuleToggles } from "./modules";
 import { getFileSrc, readImage } from "../globalApi.svelte";
 
 export interface OpenAIChat{
@@ -186,6 +186,39 @@ export async function sendChat(chatProcessIndex = -1,arg:{
         return v
     })
     
+// ─────────────────────────────────────────────────────────
+// Snapshot preset name & toggles before sending a message.
+// Ensures correct metadata is recorded, even if presets
+// change immediately after clicking "send".
+//
+// Used later in promptInfo assembly (e.g. promptInfo.promptText)
+// ─────────────────────────────────────────────────────────
+    let promptInfo: MessagePresetInfo = {}
+    let initialPresetNameForPromptInfo = null
+    let initialPromptTogglesForPromptInfo: {
+        key: string,
+        value: string,
+    }[] = []
+    if(DBState.db.promptInfoInsideChat){
+        initialPresetNameForPromptInfo = DBState.db.botPresets[DBState.db.botPresetsId]?.name ?? ''
+        initialPromptTogglesForPromptInfo = parseToggleSyntax(DBState.db.customPromptTemplateToggle + getModuleToggles())
+            .flatMap(toggle => {
+                const raw = DBState.db.globalChatVariables[`toggle_${toggle.key}`]
+                if (toggle.type === 'select' || toggle.type === 'text') {
+                    return [{ key: toggle.value, value: toggle.options[raw] }];
+                }
+                if (raw === '1') {
+                    return [{ key: toggle.value, value: 'ON' }];
+                }
+                return [];
+            })
+
+        promptInfo = {
+            promptName: initialPresetNameForPromptInfo,
+            promptToggles: initialPromptTogglesForPromptInfo,
+        }
+    }
+// ─────────────────────────────────────────────────────────────
 
     let currentChar:character
     let caculatedChatTokens = 0
@@ -367,13 +400,15 @@ export async function sendChat(chatProcessIndex = -1,arg:{
     if(currentChat.note){
         unformated.authorNote.push({
             role: 'system',
-            content: risuChatParser(currentChat.note, {chara: currentChar})
+            content: risuChatParser(currentChat.note, {chara: currentChar}),
+            memo: 'authornote'
         })
     }
     else if(getAuthorNoteDefaultText() !== ''){
         unformated.authorNote.push({
             role: 'system',
-            content: risuChatParser(getAuthorNoteDefaultText(), {chara: currentChar})
+            content: risuChatParser(getAuthorNoteDefaultText(), {chara: currentChar}),
+            memo: 'authornote'
         })
     }
 
@@ -403,7 +438,8 @@ export async function sendChat(chatProcessIndex = -1,arg:{
 
         unformated.description.push({
             role: 'system',
-            content: description
+            content: description,
+            memo: 'description',
         })
 
         if(nowChatroom.type === 'group'){
@@ -424,7 +460,8 @@ export async function sendChat(chatProcessIndex = -1,arg:{
     for(const lorebook of normalActives){
         unformated.lorebook.push({
             role: lorebook.role,
-            content: risuChatParser(lorebook.prompt, {chara: currentChar})
+            content: risuChatParser(lorebook.prompt, {chara: currentChar}),
+            memo: 'lore',
         })
     }
 
@@ -448,7 +485,8 @@ export async function sendChat(chatProcessIndex = -1,arg:{
     if(DBState.db.personaPrompt){
         unformated.personaPrompt.push({
             role: 'system',
-            content: risuChatParser(getPersonaPrompt(), {chara: currentChar})
+            content: risuChatParser(getPersonaPrompt(), {chara: currentChar}),
+            memo: 'persona',
         })
     }
     
@@ -473,7 +511,8 @@ export async function sendChat(chatProcessIndex = -1,arg:{
     for(const lorebook of postEverythingLorebooks){
         unformated.postEverything.push({
             role: lorebook.role,
-            content: risuChatParser(lorebook.prompt, {chara: currentChar})
+            content: risuChatParser(lorebook.prompt, {chara: currentChar}),
+            memo: 'postEverything',
         })
     }
 
@@ -1061,6 +1100,12 @@ export async function sendChat(chatProcessIndex = -1,arg:{
         }
     }
 
+    type MemoType = 'persona' | 'description' | 'authornote' | 'supaMemory';
+    const promptBodyMap: Record<MemoType, string[]> = { persona: [], description: [], authornote: [], supaMemory: [] };
+    function pushPromptInfoBody(memo: MemoType, fmt: string) {
+        promptBodyMap[memo].push(risuChatParser(fmt));
+    }
+
     if(promptTemplate){
         const template = promptTemplate
 
@@ -1071,6 +1116,10 @@ export async function sendChat(chatProcessIndex = -1,arg:{
                     if(card.innerFormat && pmt.length > 0){
                         for(let i=0;i<pmt.length;i++){
                             pmt[i].content = risuChatParser(positionParser(card.innerFormat), {chara: currentChar}).replace('{{slot}}', pmt[i].content)
+
+                            if(DBState.db.promptInfoInsideChat && DBState.db.promptTextInfoInsideChat){
+                                pushPromptInfoBody(card.type, card.innerFormat)
+                            }
                         }
                     }
 
@@ -1082,6 +1131,10 @@ export async function sendChat(chatProcessIndex = -1,arg:{
                     if(card.innerFormat && pmt.length > 0){
                         for(let i=0;i<pmt.length;i++){
                             pmt[i].content = risuChatParser(positionParser(card.innerFormat), {chara: currentChar}).replace('{{slot}}', pmt[i].content)
+                            
+                            if(DBState.db.promptInfoInsideChat && DBState.db.promptTextInfoInsideChat){
+                                pushPromptInfoBody(card.type, card.innerFormat)
+                            }
                         }
                     }
 
@@ -1093,6 +1146,10 @@ export async function sendChat(chatProcessIndex = -1,arg:{
                     if(card.innerFormat && pmt.length > 0){
                         for(let i=0;i<pmt.length;i++){
                             pmt[i].content = risuChatParser(positionParser(card.innerFormat), {chara: currentChar}).replace('{{slot}}', pmt[i].content || card.defaultText || '')
+                            
+                            if(DBState.db.promptInfoInsideChat && DBState.db.promptTextInfoInsideChat){
+                                pushPromptInfoBody(card.type, card.innerFormat)
+                            }
                         }
                     }
 
@@ -1208,6 +1265,10 @@ export async function sendChat(chatProcessIndex = -1,arg:{
                     if(card.innerFormat && pmt.length > 0){
                         for(let i=0;i<pmt.length;i++){
                             pmt[i].content = risuChatParser(card.innerFormat, {chara: currentChar}).replace('{{slot}}', pmt[i].content)
+
+                            if(DBState.db.promptInfoInsideChat && DBState.db.promptTextInfoInsideChat){
+                                pushPromptInfoBody('supaMemory', card.innerFormat)
+                            }
                         }
                     }
 
@@ -1327,6 +1388,29 @@ export async function sendChat(chatProcessIndex = -1,arg:{
         return true
     }
 
+    
+    function isPromptMemo(m: string): m is MemoType {
+        return ['persona', 'description', 'authornote', 'supaMemory'].includes(m);
+    }
+    if(DBState.db.promptInfoInsideChat && DBState.db.promptTextInfoInsideChat){
+        const promptBodyInfo: OpenAIChat[] = formated.flatMap(format => {
+            if (isPromptMemo(format.memo)) {
+                return promptBodyMap[format.memo].map(content => ({
+                    role: format.role,
+                    content,
+                }))
+            }
+
+            if (format.memo == null) {
+                return [format]
+            }
+
+            return []
+        })
+        
+        promptInfo.promptText = promptBodyInfo
+    }
+
     let result = ''
     let emoChanged = false
     let resendChat = false
@@ -1353,6 +1437,7 @@ export async function sendChat(chatProcessIndex = -1,arg:{
                 saying: currentChar.chaId,
                 time: Date.now(),
                 generationInfo,
+                promptInfo,
             })
         }
         DBState.db.characters[selectedChar].chats[selectedChat].isStreaming = true
@@ -1432,7 +1517,8 @@ export async function sendChat(chatProcessIndex = -1,arg:{
                     data: result,
                     saying: currentChar.chaId,
                     time: Date.now(),
-                    generationInfo
+                    generationInfo,
+                    promptInfo,
                 }       
                 if(inlayResult.promise){
                     const p = await inlayResult.promise
@@ -1445,7 +1531,8 @@ export async function sendChat(chatProcessIndex = -1,arg:{
                     data: result,
                     saying: currentChar.chaId,
                     time: Date.now(),
-                    generationInfo
+                    generationInfo,
+                    promptInfo,
                 })
                 const ind = DBState.db.characters[selectedChar].chats[selectedChat].message.length - 1
                 if(inlayResult.promise){
diff --git a/src/ts/process/lua.ts b/src/ts/process/lua.ts
index f8f45283..074ba707 100644
--- a/src/ts/process/lua.ts
+++ b/src/ts/process/lua.ts
@@ -1,6 +1,6 @@
-import { getChatVar, hasher, setChatVar, getGlobalChatVar, type simpleCharacterArgument } from "../parser.svelte";
+import { getChatVar, hasher, setChatVar, getGlobalChatVar, type simpleCharacterArgument, risuChatParser } from "../parser.svelte";
 import { LuaEngine, LuaFactory } from "wasmoon";
-import { getCurrentCharacter, getCurrentChat, getDatabase, setCurrentChat, setDatabase, type Chat, type character, type groupChat } from "../storage/database.svelte";
+import { getCurrentCharacter, getCurrentChat, getDatabase, setDatabase, type Chat, type character, type groupChat, type loreBook } from "../storage/database.svelte";
 import { get } from "svelte/store";
 import { ReloadGUIPointer, selectedCharID } from "../stores.svelte";
 import { alertSelect, alertError, alertInput, alertNormal } from "../alert";
@@ -10,10 +10,12 @@ import { writeInlayImage } from "./files/inlays";
 import type { OpenAIChat } from "./index.svelte";
 import { requestChatData } from "./request";
 import { v4 } from "uuid";
-import { getModuleTriggers } from "./modules";
+import { getModuleLorebooks, getModuleTriggers } from "./modules";
 import { Mutex } from "../mutex";
 import { tokenize } from "../tokenizer";
 import { fetchNative } from "../globalApi.svelte";
+import { loadLoreBookV3Prompt } from './lorebook.svelte';
+import { getPersonaPrompt, getUserName } from '../util';
 
 let luaFactory:LuaFactory
 let LuaSafeIds = new Set<string>()
@@ -460,6 +462,26 @@ export async function runLua(code:string, arg:{
                 return char.firstMessage
             })
 
+            luaEngine.global.set('getPersonaName', (id:string) => {
+                if(!LuaSafeIds.has(id)){
+                    return
+                }
+
+                return getUserName()
+            })
+
+            luaEngine.global.set('getPersonaDescription', (id:string) => {
+                if(!LuaSafeIds.has(id)){
+                    return
+                }
+                
+                const db = getDatabase()
+                const selectedChar = get(selectedCharID)
+                const char = db.characters[selectedChar]
+
+                return risuChatParser(getPersonaPrompt(), { chara: char })
+            })
+
             luaEngine.global.set('getBackgroundEmbedding', async (id:string) => {
                 if(!LuaSafeIds.has(id)){
                     return
@@ -484,6 +506,67 @@ export async function runLua(code:string, arg:{
                 return true
             })
 
+            // Lore books
+            luaEngine.global.set('getLoreBooksMain', (id:string, search: string) => {
+                if(!LuaSafeIds.has(id)){
+                    return
+                }
+
+                const db = getDatabase()
+                const selectedChar = db.characters[get(selectedCharID)]
+                if (selectedChar.type !== 'character') {
+                    return
+                }
+
+                const loreBooks = [...selectedChar.chats[selectedChar.chatPage]?.localLore ?? [], ...selectedChar.globalLore, ...getModuleLorebooks()]
+                const found = loreBooks.filter((b) => b.comment === search)
+
+                return JSON.stringify(found.map((b) => ({ ...b, content: risuChatParser(b.content, { chara: selectedChar }) })))
+            })
+
+            luaEngine.global.set('loadLoreBooksMain', async (id:string, usedContext:number) => {
+                if(!LuaLowLevelIds.has(id)){
+                    return
+                }
+
+                const db = getDatabase()
+
+                const selectedChar = db.characters[get(selectedCharID)]
+
+                if (selectedChar.type !== 'character') {
+                    return
+                }
+
+                const fullLoreBooks = (await loadLoreBookV3Prompt()).actives
+                const maxContext = db.maxContext - usedContext
+                if (maxContext < 0) {
+                    return
+                }
+
+                let totalTokens = 0
+                const loreBooks = []
+
+                for (const book of fullLoreBooks) {
+                    const parsed = risuChatParser(book.prompt, { chara: selectedChar }).trim()
+                    if (parsed.length === 0) {
+                        continue
+                    }
+
+                    const tokens = await tokenize(parsed)
+
+                    if (totalTokens + tokens > maxContext) {
+                        break
+                    }
+                    totalTokens += tokens
+                    loreBooks.push({
+                        data: parsed,
+                        role: book.role === 'assistant' ? 'char' : book.role,
+                    })
+                }
+
+                return JSON.stringify(loreBooks)
+            })
+
             luaEngine.global.set('axLLMMain', async (id:string, promptStr:string) => {
                 let prompt:{
                     role: string,
@@ -708,6 +791,15 @@ function log(value)
     logMain(json.encode(value))
 end
 
+function getLoreBooks(id, search)
+    return json.decode(getLoreBooksMain(id, search))
+end
+
+
+function loadLoreBooks(id)
+    return json.decode(loadLoreBooksMain(id):await())
+end
+
 function LLM(id, prompt)
     return json.decode(LLMMain(id, json.encode(prompt)):await())
 end
diff --git a/src/ts/process/memory/hypamemory.ts b/src/ts/process/memory/hypamemory.ts
index 07b808fb..07af73d4 100644
--- a/src/ts/process/memory/hypamemory.ts
+++ b/src/ts/process/memory/hypamemory.ts
@@ -1,27 +1,33 @@
 import localforage from "localforage";
 import { globalFetch } from "src/ts/globalApi.svelte";
 import { runEmbedding } from "../transformers";
-import { alertError } from "src/ts/alert";
 import { appendLastPath } from "src/ts/util";
 import { getDatabase } from "src/ts/storage/database.svelte";
 
+export type HypaModel = 'custom'|'ada'|'openai3small'|'openai3large'|'MiniLM'|'MiniLMGPU'|'nomic'|'nomicGPU'|'bgeSmallEn'|'bgeSmallEnGPU'|'bgem3'|'bgem3GPU'|'multiMiniLM'|'multiMiniLMGPU'
 
-export type HypaModel = 'ada'|'MiniLM'|'nomic'|'custom'|'nomicGPU'|'bgeSmallEn'|'bgeSmallEnGPU'|'bgem3'|'bgem3GPU'|'openai3small'|'openai3large'
-
-const localModels = {
+// In a typical environment, bge-m3 is a heavy model.
+// If your GPU can't handle this model, you'll see errror below.
+// Failed to execute 'mapAsync' on 'GPUBuffer': [Device] is lost
+export const localModels = {
     models: {
         'MiniLM':'Xenova/all-MiniLM-L6-v2',
+        'MiniLMGPU': "Xenova/all-MiniLM-L6-v2",
         'nomic':'nomic-ai/nomic-embed-text-v1.5',
         'nomicGPU':'nomic-ai/nomic-embed-text-v1.5',
-        'bgeSmallEn': 'BAAI/bge-small-en-v1.5',
-        'bgeSmallEnGPU': 'BAAI/bge-small-en-v1.5',
-        'bgem3': 'BAAI/bge-m3',
-        'bgem3GPU': 'BAAI/bge-m3',
+        'bgeSmallEn': 'Xenova/bge-small-en-v1.5',
+        'bgeSmallEnGPU': 'Xenova/bge-small-en-v1.5',
+        'bgem3': 'Xenova/bge-m3',
+        'bgem3GPU': 'Xenova/bge-m3',
+        'multiMiniLM': 'Xenova/paraphrase-multilingual-MiniLM-L12-v2',
+        'multiMiniLMGPU': 'Xenova/paraphrase-multilingual-MiniLM-L12-v2',
     },
     gpuModels:[
+        'MiniLMGPU',
         'nomicGPU',
         'bgeSmallEnGPU',
-        'bgem3GPU'
+        'bgem3GPU',
+        'multiMiniLMGPU',
     ]
 }
 
@@ -44,7 +50,7 @@ export class HypaProcesser{
         else{
             this.model = model
         }
-        this.customEmbeddingUrl = customEmbeddingUrl || db.hypaCustomSettings.url
+        this.customEmbeddingUrl = customEmbeddingUrl?.trim() || db.hypaCustomSettings?.url?.trim() || ""
     }
 
     async embedDocuments(texts: string[]): Promise<VectorArray[]> {
@@ -80,10 +86,12 @@ export class HypaProcesser{
 
             const db = getDatabase()
             const fetchArgs = {
-                ...(db.hypaCustomSettings.key ? {headers: {"Authorization": "Bearer " + db.hypaCustomSettings.key}} : {}),
+                headers: {
+                    ...(db.hypaCustomSettings?.key?.trim() ? {"Authorization": "Bearer " + db.hypaCustomSettings.key.trim()} : {})
+                },
                 body: {
                     "input": input,
-                    ...(db.hypaCustomSettings.model ? {"model": db.hypaCustomSettings.model} : {})
+                    ...(db.hypaCustomSettings?.model?.trim() ? {"model": db.hypaCustomSettings.model.trim()} : {})
                 }
             };
  
@@ -99,7 +107,7 @@ export class HypaProcesser{
 
             gf = await globalFetch("https://api.openai.com/v1/embeddings", {
                 headers: {
-                    "Authorization": "Bearer " + db.supaMemoryKey || this.oaikey
+                    "Authorization": "Bearer " + (this.oaikey?.trim() || db.supaMemoryKey?.trim())
                 },
                 body: {
                     "input": input,
@@ -134,7 +142,7 @@ export class HypaProcesser{
     
     async addText(texts:string[]) {
         const db = getDatabase()
-        const suffix = (this.model === 'custom' && db.hypaCustomSettings.model) ? `-${db.hypaCustomSettings.model}` : ""
+        const suffix = (this.model === 'custom' && db.hypaCustomSettings?.model?.trim()) ? `-${db.hypaCustomSettings.model.trim()}` : ""
 
         for(let i=0;i<texts.length;i++){
             const itm:memoryVector = await this.forage.getItem(texts[i] + '|' + this.model + suffix)
@@ -205,7 +213,8 @@ export class HypaProcesser{
         return similarity(query1, query2)
     }
 }
-function similarity(a:VectorArray, b:VectorArray) {    
+
+export function similarity(a:VectorArray, b:VectorArray) {    
     let dot = 0;
     for(let i=0;i<a.length;i++){
         dot += a[i] * b[i]
@@ -227,4 +236,4 @@ const chunkArray = <T>(arr: T[], chunkSize: number) =>
         const chunk = chunks[chunkIndex] || [];
         chunks[chunkIndex] = chunk.concat([elem]);
         return chunks;
-}, [] as T[][]);
\ No newline at end of file
+}, [] as T[][]);
diff --git a/src/ts/process/memory/hypamemoryv2.ts b/src/ts/process/memory/hypamemoryv2.ts
new file mode 100644
index 00000000..14e1a08a
--- /dev/null
+++ b/src/ts/process/memory/hypamemoryv2.ts
@@ -0,0 +1,414 @@
+import localforage from "localforage";
+import { type HypaModel, localModels } from "./hypamemory";
+import { TaskRateLimiter, TaskCanceledError } from "./taskRateLimiter";
+import { runEmbedding } from "../transformers";
+import { globalFetch } from "src/ts/globalApi.svelte";
+import { getDatabase } from "src/ts/storage/database.svelte";
+import { appendLastPath } from "src/ts/util";
+
+export interface HypaProcessorV2Options {
+  model?: HypaModel;
+  customEmbeddingUrl?: string;
+  oaiKey?: string;
+  rateLimiter?: TaskRateLimiter;
+}
+
+export interface EmbeddingText<TMetadata> {
+  content: string;
+  metadata?: TMetadata;
+}
+
+export interface EmbeddingResult<TMetadata> extends EmbeddingText<TMetadata> {
+  embedding: EmbeddingVector;
+}
+
+export type EmbeddingVector = number[] | Float32Array;
+
+export class HypaProcessorV2<TMetadata> {
+  private static readonly LOG_PREFIX = "[HypaProcessorV2]";
+  public readonly options: HypaProcessorV2Options;
+  public progressCallback: (queuedCount: number) => void = null;
+  private vectors: Map<string, EmbeddingResult<TMetadata>> = new Map();
+  private forage: LocalForage = localforage.createInstance({
+    name: "hypaVector",
+  });
+
+  public constructor(options?: HypaProcessorV2Options) {
+    const db = getDatabase();
+
+    this.options = {
+      model: db.hypaModel || "MiniLM",
+      customEmbeddingUrl: db.hypaCustomSettings?.url?.trim() || "",
+      oaiKey: db.supaMemoryKey?.trim() || "",
+      rateLimiter: new TaskRateLimiter(),
+      ...options,
+    };
+  }
+
+  public async addTexts(ebdTexts: EmbeddingText<TMetadata>[]): Promise<void> {
+    await this.getEmbeds(ebdTexts, true);
+  }
+
+  public async similaritySearchScored(
+    query: string
+  ): Promise<[EmbeddingResult<TMetadata>, number][]> {
+    const results = await this.similaritySearchScoredBatch([query]);
+    return results[0];
+  }
+
+  public async similaritySearchScoredBatch(
+    queries: string[]
+  ): Promise<[EmbeddingResult<TMetadata>, number][][]> {
+    if (queries.length === 0) {
+      return [];
+    }
+
+    // Remove duplicate queries
+    const uniqueQueries = [...new Set(queries)];
+
+    // Convert queries to EmbeddingText array
+    const ebdTexts: EmbeddingText<TMetadata>[] = uniqueQueries.map((query) => ({
+      content: query,
+    }));
+
+    // Get query embeddings (don't save to memory)
+    const ebdResults = await this.getEmbeds(ebdTexts, false);
+
+    const scoredResultsMap = new Map<
+      string,
+      [EmbeddingResult<TMetadata>, number][]
+    >();
+
+    // Calculate similarity for each unique query
+    for (let i = 0; i < uniqueQueries.length; i++) {
+      const ebdResult = ebdResults[i];
+
+      const scoredVectors = Array.from(this.vectors.values())
+        .map((vector): [EmbeddingResult<TMetadata>, number] => [
+          vector,
+          this.similarity(ebdResult.embedding, vector.embedding),
+        ])
+        .sort((a, b) => b[1] - a[1]);
+
+      scoredResultsMap.set(uniqueQueries[i], scoredVectors);
+    }
+
+    return queries.map((query) => scoredResultsMap.get(query));
+  }
+
+  private async getEmbeds(
+    ebdTexts: EmbeddingText<TMetadata>[],
+    saveToMemory: boolean = true
+  ): Promise<EmbeddingResult<TMetadata>[]> {
+    if (ebdTexts.length === 0) {
+      return [];
+    }
+
+    const resultMap: Map<string, EmbeddingResult<TMetadata>> = new Map();
+    const toEmbed: EmbeddingText<TMetadata>[] = [];
+
+    // Load cache
+    const loadPromises = ebdTexts.map(async (item, index) => {
+      const { content, metadata } = item;
+
+      // Use if already in memory
+      if (this.vectors.has(content)) {
+        resultMap.set(content, this.vectors.get(content));
+        return;
+      }
+
+      try {
+        const cached = await this.forage.getItem<EmbeddingResult<TMetadata>>(
+          this.getCacheKey(content)
+        );
+
+        if (cached) {
+          // Debug log for cache hit
+          console.debug(
+            HypaProcessorV2.LOG_PREFIX,
+            `Cache hit for getting embedding ${index} with model ${this.options.model}`
+          );
+
+          // Add metadata
+          cached.metadata = metadata;
+
+          // Save to memory
+          if (saveToMemory) {
+            this.vectors.set(content, cached);
+          }
+
+          resultMap.set(content, cached);
+        } else {
+          toEmbed.push(item);
+        }
+      } catch (error) {
+        toEmbed.push(item);
+      }
+    });
+
+    await Promise.all(loadPromises);
+
+    if (toEmbed.length === 0) {
+      return ebdTexts.map((item) => resultMap.get(item.content));
+    }
+
+    // Chunking array
+    const chunkSize = await this.getOptimalChunkSize();
+
+    // Debug log for optimal chunk size
+    console.debug(
+      HypaProcessorV2.LOG_PREFIX,
+      `Optimal chunk size for ${this.options.model}: ${chunkSize}`
+    );
+
+    const chunks = this.chunkArray(toEmbed, chunkSize);
+
+    if (this.isLocalModel()) {
+      // Local model: Sequential processing
+      for (let i = 0; i < chunks.length; i++) {
+        // Progress callback
+        this.progressCallback?.(chunks.length - i - 1);
+
+        const chunk = chunks[i];
+        const embeddings = await this.getLocalEmbeds(
+          chunk.map((item) => item.content)
+        );
+
+        const savePromises = embeddings.map(async (embedding, j) => {
+          const { content, metadata } = chunk[j];
+
+          const ebdResult: EmbeddingResult<TMetadata> = {
+            content,
+            embedding,
+            metadata,
+          };
+
+          // Save to DB
+          await this.forage.setItem(this.getCacheKey(content), {
+            content,
+            embedding,
+          });
+
+          // Save to memory
+          if (saveToMemory) {
+            this.vectors.set(content, ebdResult);
+          }
+
+          resultMap.set(content, ebdResult);
+        });
+
+        await Promise.all(savePromises);
+      }
+    } else {
+      // API model: Parallel processing
+      const embeddingTasks = chunks.map((chunk) => {
+        const contents = chunk.map((item) => item.content);
+
+        return () => this.getAPIEmbeds(contents);
+      });
+
+      // Progress callback
+      this.options.rateLimiter.taskQueueChangeCallback = this.progressCallback;
+
+      const batchResult = await this.options.rateLimiter.executeBatch<
+        EmbeddingVector[]
+      >(embeddingTasks);
+      const errors: Error[] = [];
+
+      const chunksSavePromises = batchResult.results.map(async (result, i) => {
+        if (!result.success) {
+          errors.push(result.error);
+          return;
+        }
+
+        if (!result.data) {
+          errors.push(new Error("No embeddings found in the response."));
+          return;
+        }
+
+        const chunk = chunks[i];
+        const savePromises = result.data.map(async (embedding, j) => {
+          const { content, metadata } = chunk[j];
+
+          const ebdResult: EmbeddingResult<TMetadata> = {
+            content,
+            embedding,
+            metadata,
+          };
+
+          // Save to DB
+          await this.forage.setItem(this.getCacheKey(content), {
+            content,
+            embedding,
+          });
+
+          // Save to memory
+          if (saveToMemory) {
+            this.vectors.set(content, ebdResult);
+          }
+
+          resultMap.set(content, ebdResult);
+        });
+
+        await Promise.all(savePromises);
+      });
+
+      await Promise.all(chunksSavePromises);
+
+      // Throw major error if there are errors
+      if (errors.length > 0) {
+        const majorError =
+          errors.find((error) => !(error instanceof TaskCanceledError)) ||
+          errors[0];
+
+        throw majorError;
+      }
+    }
+
+    return ebdTexts.map((item) => resultMap.get(item.content));
+  }
+
+  private similarity(a: EmbeddingVector, b: EmbeddingVector): number {
+    let dot = 0;
+    let magA = 0;
+    let magB = 0;
+
+    for (let i = 0; i < a.length; i++) {
+      dot += a[i] * b[i];
+      magA += a[i] * a[i];
+      magB += b[i] * b[i];
+    }
+
+    return dot / (Math.sqrt(magA) * Math.sqrt(magB));
+  }
+
+  private getCacheKey(content: string): string {
+    const db = getDatabase();
+    const suffix =
+      this.options.model === "custom" && db.hypaCustomSettings?.model?.trim()
+        ? `-${db.hypaCustomSettings.model.trim()}`
+        : "";
+
+    return `${content}|${this.options.model}${suffix}`;
+  }
+
+  private async getOptimalChunkSize(): Promise<number> {
+    // API
+    if (!this.isLocalModel()) {
+      return 50;
+    }
+
+    const isMobile = /Android|iPhone|iPad|iPod|webOS/i.test(
+      navigator.userAgent
+    );
+
+    // WebGPU
+    if ("gpu" in navigator) {
+      return isMobile ? 5 : 10;
+    }
+
+    // WASM
+    const cpuCores = navigator.hardwareConcurrency || 4;
+    const baseChunkSize = isMobile ? Math.floor(cpuCores / 2) : cpuCores;
+
+    return Math.min(baseChunkSize, 10);
+  }
+
+  private isLocalModel(): boolean {
+    return Object.keys(localModels.models).includes(this.options.model);
+  }
+
+  private chunkArray<T>(array: T[], size: number): T[][] {
+    const chunks: T[][] = [];
+
+    for (let i = 0; i < array.length; i += size) {
+      chunks.push(array.slice(i, i + size));
+    }
+
+    return chunks;
+  }
+
+  private async getLocalEmbeds(contents: string[]): Promise<EmbeddingVector[]> {
+    const results: Float32Array[] = await runEmbedding(
+      contents,
+      localModels.models[this.options.model],
+      localModels.gpuModels.includes(this.options.model) ? "webgpu" : "wasm"
+    );
+
+    return results;
+  }
+
+  private async getAPIEmbeds(contents: string[]): Promise<EmbeddingVector[]> {
+    const db = getDatabase();
+    let response = null;
+
+    if (this.options.model === "custom") {
+      if (!this.options.customEmbeddingUrl) {
+        throw new Error("Custom model requires a Custom Server URL");
+      }
+
+      const replaceUrl = this.options.customEmbeddingUrl.endsWith("/embeddings")
+        ? this.options.customEmbeddingUrl
+        : appendLastPath(this.options.customEmbeddingUrl, "embeddings");
+
+      const fetchArgs = {
+        headers: {
+          ...(db.hypaCustomSettings?.key?.trim()
+            ? { Authorization: "Bearer " + db.hypaCustomSettings.key.trim() }
+            : {}),
+        },
+        body: {
+          input: contents,
+          ...(db.hypaCustomSettings?.model?.trim()
+            ? { model: db.hypaCustomSettings.model.trim() }
+            : {}),
+        },
+      };
+
+      response = await globalFetch(replaceUrl, fetchArgs);
+    } else if (
+      ["ada", "openai3small", "openai3large"].includes(this.options.model)
+    ) {
+      const models = {
+        ada: "text-embedding-ada-002",
+        openai3small: "text-embedding-3-small",
+        openai3large: "text-embedding-3-large",
+      };
+
+      const fetchArgs = {
+        headers: {
+          Authorization:
+            "Bearer " +
+            (this.options.oaiKey?.trim() || db.supaMemoryKey?.trim()),
+        },
+        body: {
+          input: contents,
+          model: models[this.options.model],
+        },
+      };
+
+      response = await globalFetch(
+        "https://api.openai.com/v1/embeddings",
+        fetchArgs
+      );
+    } else {
+      throw new Error(`Unsupported model: ${this.options.model}`);
+    }
+
+    if (!response.ok || !response.data.data) {
+      throw new Error(JSON.stringify(response.data));
+    }
+
+    const embeddings: EmbeddingVector[] = response.data.data.map(
+      (item: { embedding: EmbeddingVector }) => {
+        if (!item.embedding) {
+          throw new Error("No embeddings found in the response.");
+        }
+
+        return item.embedding;
+      }
+    );
+
+    return embeddings;
+  }
+}
diff --git a/src/ts/process/memory/hypav3.ts b/src/ts/process/memory/hypav3.ts
index f1e9f8a1..7985cf53 100644
--- a/src/ts/process/memory/hypav3.ts
+++ b/src/ts/process/memory/hypav3.ts
@@ -1,8 +1,6 @@
-import {
-  type VectorArray,
-  type memoryVector,
-  HypaProcesser,
-} from "./hypamemory";
+import { type memoryVector, HypaProcesser, similarity } from "./hypamemory";
+import { TaskRateLimiter } from "./taskRateLimiter";
+import { type EmbeddingText, HypaProcessorV2 } from "./hypamemoryv2";
 import {
   type Chat,
   type character,
@@ -11,15 +9,34 @@ import {
 } from "src/ts/storage/database.svelte";
 import { type OpenAIChat } from "../index.svelte";
 import { requestChatData } from "../request";
-import { runSummarizer } from "../transformers";
-import { globalFetch } from "src/ts/globalApi.svelte";
+import { chatCompletion, unloadEngine } from "../webllm";
 import { parseChatML } from "src/ts/parser.svelte";
+import { hypaV3ProgressStore } from "src/ts/stores.svelte";
 import { type ChatTokenizer } from "src/ts/tokenizer";
 
-interface Summary {
-  text: string;
-  chatMemos: Set<string>;
-  isImportant: boolean;
+export interface HypaV3Preset {
+  name: string;
+  settings: HypaV3Settings;
+}
+
+export interface HypaV3Settings {
+  summarizationModel: string;
+  summarizationPrompt: string;
+  memoryTokensRatio: number;
+  extraSummarizationRatio: number;
+  maxChatsPerSummary: number;
+  recentMemoryRatio: number;
+  similarMemoryRatio: number;
+  enableSimilarityCorrection: boolean;
+  preserveOrphanedMemory: boolean;
+  processRegexScript: boolean;
+  doNotSummarizeUserMessage: boolean;
+  // Experimental
+  useExperimentalImpl: boolean;
+  summarizationRequestsPerMinute: number;
+  summarizationMaxConcurrent: number;
+  embeddingRequestsPerMinute: number;
+  embeddingMaxConcurrent: number;
 }
 
 interface HypaV3Data {
@@ -36,228 +53,29 @@ export interface SerializableHypaV3Data {
   lastSelectedSummaries?: number[];
 }
 
+interface Summary {
+  text: string;
+  chatMemos: Set<string>;
+  isImportant: boolean;
+}
+
 interface SummaryChunk {
   text: string;
   summary: Summary;
 }
 
+export interface HypaV3Result {
+  currentTokens: number;
+  chats: OpenAIChat[];
+  error?: string;
+  memory?: SerializableHypaV3Data;
+}
+
+const logPrefix = "[HypaV3]";
+const memoryPromptTag = "Past Events Summary";
 const minChatsForSimilarity = 3;
-const maxSummarizationFailures = 3;
 const summarySeparator = "\n\n";
 
-// Helper function to check if one Set is a subset of another
-function isSubset(subset: Set<string>, superset: Set<string>): boolean {
-  for (const elem of subset) {
-    if (!superset.has(elem)) {
-      return false;
-    }
-  }
-  return true;
-}
-
-function toSerializableHypaV3Data(data: HypaV3Data): SerializableHypaV3Data {
-  return {
-    ...data,
-    summaries: data.summaries.map((summary) => ({
-      ...summary,
-      chatMemos: [...summary.chatMemos],
-    })),
-  };
-}
-
-function toHypaV3Data(serialData: SerializableHypaV3Data): HypaV3Data {
-  return {
-    ...serialData,
-    summaries: serialData.summaries.map((summary) => ({
-      ...summary,
-      // Convert null back to undefined (JSON serialization converts undefined to null)
-      chatMemos: new Set(
-        summary.chatMemos.map((memo) => (memo === null ? undefined : memo))
-      ),
-    })),
-  };
-}
-
-function encapsulateMemoryPrompt(memoryPrompt: string): string {
-  return `<Past Events Summary>${memoryPrompt}</Past Events Summary>`;
-}
-
-function cleanOrphanedSummary(chats: OpenAIChat[], data: HypaV3Data): void {
-  // Collect all memos from current chats
-  const currentChatMemos = new Set(chats.map((chat) => chat.memo));
-  const originalLength = data.summaries.length;
-
-  // Filter summaries - keep only those whose chatMemos are subset of current chat memos
-  data.summaries = data.summaries.filter((summary) => {
-    return isSubset(summary.chatMemos, currentChatMemos);
-  });
-
-  const removedCount = originalLength - data.summaries.length;
-
-  if (removedCount > 0) {
-    console.log(`[HypaV3] Cleaned ${removedCount} orphaned summaries.`);
-  }
-}
-
-export async function summarize(
-  oaiChats: OpenAIChat[]
-): Promise<{ success: boolean; data: string }> {
-  const db = getDatabase();
-  const stringifiedChats = oaiChats
-    .map((chat) => `${chat.role}: ${chat.content}`)
-    .join("\n");
-
-  if (db.supaModelType === "distilbart") {
-    try {
-      const summaryText = (await runSummarizer(stringifiedChats)).trim();
-      return { success: true, data: summaryText };
-    } catch (error) {
-      return {
-        success: false,
-        data: error,
-      };
-    }
-  }
-
-  const summarizePrompt =
-    db.supaMemoryPrompt === ""
-      ? "[Summarize the ongoing role story, It must also remove redundancy and unnecessary text and content from the output.]"
-      : db.supaMemoryPrompt;
-
-  switch (db.supaModelType) {
-    case "instruct35": {
-      console.log(
-        "[HypaV3] Using openAI gpt-3.5-turbo-instruct for summarization."
-      );
-
-      const requestPrompt = `${stringifiedChats}\n\n${summarizePrompt}\n\nOutput:`;
-      const response = await globalFetch(
-        "https://api.openai.com/v1/completions",
-        {
-          method: "POST",
-          headers: {
-            "Content-Type": "application/json",
-            Authorization: "Bearer " + db.supaMemoryKey,
-          },
-          body: {
-            model: "gpt-3.5-turbo-instruct",
-            prompt: requestPrompt,
-            max_tokens: db.maxResponse,
-            temperature: 0,
-          },
-        }
-      );
-
-      try {
-        if (!response.ok) {
-          return {
-            success: false,
-            data: JSON.stringify(response),
-          };
-        }
-
-        const summaryText =
-          response.data?.choices?.[0]?.message?.content?.trim();
-
-        if (!summaryText) {
-          return {
-            success: false,
-            data: JSON.stringify(response),
-          };
-        }
-
-        return { success: true, data: summaryText };
-      } catch (error) {
-        return {
-          success: false,
-          data: error,
-        };
-      }
-    }
-
-    case "subModel": {
-      console.log(`[HypaV3] Using ax model ${db.subModel} for summarization.`);
-
-      const requestMessages: OpenAIChat[] = parseChatML(
-        summarizePrompt.replaceAll("{{slot}}", stringifiedChats)
-      ) ?? [
-        {
-          role: "user",
-          content: stringifiedChats,
-        },
-        {
-          role: "system",
-          content: summarizePrompt,
-        },
-      ];
-
-      const response = await requestChatData(
-        {
-          formated: requestMessages,
-          bias: {},
-          useStreaming: false,
-          noMultiGen: true,
-        },
-        "memory"
-      );
-
-      if (response.type === "streaming" || response.type === "multiline") {
-        return {
-          success: false,
-          data: "unexpected response type",
-        };
-      }
-
-      if (response.type === "fail") {
-        return {
-          success: false,
-          data: response.result,
-        };
-      }
-
-      return { success: true, data: response.result.trim() };
-    }
-
-    default: {
-      return {
-        success: false,
-        data: `unsupported model ${db.supaModelType} for summarization`,
-      };
-    }
-  }
-}
-
-async function retryableSummarize(
-  oaiChats: OpenAIChat[]
-): Promise<{ success: boolean; data: string }> {
-  let summarizationFailures = 0;
-
-  while (summarizationFailures < maxSummarizationFailures) {
-    console.log(
-      "[HypaV3] Attempting summarization:",
-      "\nAttempt:",
-      summarizationFailures + 1,
-      "\nTarget:",
-      oaiChats
-    );
-
-    const summarizeResult = await summarize(oaiChats);
-
-    if (!summarizeResult.success) {
-      console.log("[HypaV3] Summarization failed:", summarizeResult.data);
-      summarizationFailures++;
-
-      if (summarizationFailures >= maxSummarizationFailures) {
-        return summarizeResult;
-      }
-
-      continue;
-    }
-
-    return summarizeResult;
-  }
-}
-
 export async function hypaMemoryV3(
   chats: OpenAIChat[],
   currentTokens: number,
@@ -265,24 +83,74 @@ export async function hypaMemoryV3(
   room: Chat,
   char: character | groupChat,
   tokenizer: ChatTokenizer
-): Promise<{
-  currentTokens: number;
-  chats: OpenAIChat[];
-  error?: string;
-  memory?: SerializableHypaV3Data;
-}> {
+): Promise<HypaV3Result> {
+  const settings = getCurrentHypaV3Preset().settings;
+
+  try {
+    if (settings.useExperimentalImpl) {
+      console.log(logPrefix, "Using experimental implementation.");
+
+      return await hypaMemoryV3MainExp(
+        chats,
+        currentTokens,
+        maxContextTokens,
+        room,
+        char,
+        tokenizer
+      );
+    }
+
+    return await hypaMemoryV3Main(
+      chats,
+      currentTokens,
+      maxContextTokens,
+      room,
+      char,
+      tokenizer
+    );
+  } catch (error) {
+    if (error instanceof Error) {
+      // Standard Error instance
+      error.message = `${logPrefix} ${error.message}`;
+      throw error;
+    }
+
+    // Fallback for non-Error object
+    let errorMessage: string;
+
+    try {
+      errorMessage = JSON.stringify(error);
+    } catch {
+      errorMessage = String(error);
+    }
+
+    throw new Error(`${logPrefix} ${errorMessage}`);
+  } finally {
+    if (settings.summarizationModel !== "subModel") {
+      try {
+        unloadEngine();
+      } catch {}
+    }
+  }
+}
+
+async function hypaMemoryV3MainExp(
+  chats: OpenAIChat[],
+  currentTokens: number,
+  maxContextTokens: number,
+  room: Chat,
+  char: character | groupChat,
+  tokenizer: ChatTokenizer
+): Promise<HypaV3Result> {
   const db = getDatabase();
+  const settings = getCurrentHypaV3Preset().settings;
 
   // Validate settings
-  if (
-    db.hypaV3Settings.recentMemoryRatio + db.hypaV3Settings.similarMemoryRatio >
-    1
-  ) {
+  if (settings.recentMemoryRatio + settings.similarMemoryRatio > 1) {
     return {
       currentTokens,
       chats,
-      error:
-        "[HypaV3] The sum of Recent Memory Ratio and Similar Memory Ratio is greater than 1.",
+      error: `${logPrefix} The sum of Recent Memory Ratio and Similar Memory Ratio is greater than 1.`,
     };
   }
 
@@ -300,7 +168,7 @@ export async function hypaMemoryV3(
   }
 
   // Clean orphaned summaries
-  if (!db.hypaV3Settings.preserveOrphanedMemory) {
+  if (!settings.preserveOrphanedMemory) {
     cleanOrphanedSummary(chats, data);
   }
 
@@ -324,33 +192,32 @@ export async function hypaMemoryV3(
     }
   }
 
+  console.log(logPrefix, "Starting index:", startIdx);
+
   // Reserve memory tokens
   const emptyMemoryTokens = await tokenizer.tokenizeChat({
     role: "system",
-    content: encapsulateMemoryPrompt(""),
+    content: wrapWithXml(memoryPromptTag, ""),
   });
   const memoryTokens = Math.floor(
-    maxContextTokens * db.hypaV3Settings.memoryTokensRatio
+    maxContextTokens * settings.memoryTokensRatio
   );
-  const shouldReserveEmptyMemoryTokens =
-    data.summaries.length === 0 &&
-    currentTokens + emptyMemoryTokens <= maxContextTokens;
-  let availableMemoryTokens = shouldReserveEmptyMemoryTokens
-    ? 0
-    : memoryTokens - emptyMemoryTokens;
+  const shouldReserveMemoryTokens =
+    data.summaries.length > 0 || currentTokens > maxContextTokens;
+  let availableMemoryTokens = shouldReserveMemoryTokens
+    ? memoryTokens - emptyMemoryTokens
+    : 0;
 
-  if (shouldReserveEmptyMemoryTokens) {
-    currentTokens += emptyMemoryTokens;
-    console.log("[HypaV3] Reserved empty memory tokens:", emptyMemoryTokens);
-  } else {
+  if (shouldReserveMemoryTokens) {
     currentTokens += memoryTokens;
-    console.log("[HypaV3] Reserved max memory tokens:", memoryTokens);
+    console.log(logPrefix, "Reserved memory tokens:", memoryTokens);
   }
 
   // If summarization is needed
-  let summarizationMode = currentTokens > maxContextTokens;
+  const summarizationMode = currentTokens > maxContextTokens;
   const targetTokens =
-    maxContextTokens * (1 - db.hypaV3Settings.extraSummarizationRatio);
+    maxContextTokens * (1 - settings.extraSummarizationRatio);
+  const toSummarizeArray: OpenAIChat[][] = [];
 
   while (summarizationMode) {
     if (currentTokens <= targetTokens) {
@@ -364,43 +231,41 @@ export async function hypaMemoryV3(
         return {
           currentTokens,
           chats,
-          error: `[HypaV3] Cannot summarize further: input token count (${currentTokens}) exceeds max context size (${maxContextTokens}), but minimum ${minChatsForSimilarity} messages required.`,
+          error: `${logPrefix} Cannot summarize further: input token count (${currentTokens}) exceeds max context size (${maxContextTokens}), but minimum ${minChatsForSimilarity} messages required.`,
           memory: toSerializableHypaV3Data(data),
         };
       }
     }
 
     const toSummarize: OpenAIChat[] = [];
-    const endIdx = Math.min(
-      startIdx + db.hypaV3Settings.maxChatsPerSummary,
-      chats.length - minChatsForSimilarity
-    );
     let toSummarizeTokens = 0;
+    let currentIndex = startIdx;
 
     console.log(
-      "[HypaV3] Evaluating summarization batch:",
+      logPrefix,
+      "Evaluating summarization batch:",
       "\nCurrent Tokens:",
       currentTokens,
       "\nMax Context Tokens:",
       maxContextTokens,
       "\nStart Index:",
       startIdx,
-      "\nEnd Index:",
-      endIdx,
-      "\nChat Count:",
-      endIdx - startIdx,
       "\nMax Chats Per Summary:",
-      db.hypaV3Settings.maxChatsPerSummary
+      settings.maxChatsPerSummary
     );
 
-    for (let i = startIdx; i < endIdx; i++) {
-      const chat = chats[i];
+    while (
+      toSummarize.length < settings.maxChatsPerSummary &&
+      currentIndex < chats.length - minChatsForSimilarity
+    ) {
+      const chat = chats[currentIndex];
       const chatTokens = await tokenizer.tokenizeChat(chat);
 
       console.log(
-        "[HypaV3] Evaluating chat:",
+        logPrefix,
+        "Evaluating chat:",
         "\nIndex:",
-        i,
+        currentIndex,
         "\nRole:",
         chat.role,
         "\nContent:",
@@ -411,23 +276,40 @@ export async function hypaMemoryV3(
 
       toSummarizeTokens += chatTokens;
 
-      if (i === 0 || !chat.content.trim()) {
+      let shouldSummarize = true;
+
+      if (
+        chat.name === "example_user" ||
+        chat.name === "example_assistant" ||
+        chat.memo === "NewChatExample"
+      ) {
         console.log(
-          `[HypaV3] Skipping ${
-            i === 0 ? "[Start a new chat]" : "empty content"
-          } at index ${i}`
+          logPrefix,
+          `Skipping example chat at index ${currentIndex}`
         );
-
-        continue;
+        shouldSummarize = false;
       }
 
-      if (db.hypaV3Settings.doNotSummarizeUserMessage && chat.role === "user") {
-        console.log(`[HypaV3] Skipping user role at index ${i}`);
-
-        continue;
+      if (chat.memo === "NewChat") {
+        console.log(logPrefix, `Skipping new chat at index ${currentIndex}`);
+        shouldSummarize = false;
       }
 
-      toSummarize.push(chat);
+      if (chat.content.trim().length === 0) {
+        console.log(logPrefix, `Skipping empty chat at index ${currentIndex}`);
+        shouldSummarize = false;
+      }
+
+      if (settings.doNotSummarizeUserMessage && chat.role === "user") {
+        console.log(logPrefix, `Skipping user role at index ${currentIndex}`);
+        shouldSummarize = false;
+      }
+
+      if (shouldSummarize) {
+        toSummarize.push(chat);
+      }
+
+      currentIndex++;
     }
 
     // Stop summarization if further reduction would go below target tokens (unless we're over max tokens)
@@ -436,43 +318,119 @@ export async function hypaMemoryV3(
       currentTokens - toSummarizeTokens < targetTokens
     ) {
       console.log(
-        `[HypaV3] Stopping summarization: currentTokens(${currentTokens}) - toSummarizeTokens(${toSummarizeTokens}) < targetTokens(${targetTokens})`
+        logPrefix,
+        "Stopping summarization:",
+        `\ncurrentTokens(${currentTokens}) - toSummarizeTokens(${toSummarizeTokens}) < targetTokens(${targetTokens})`
       );
       break;
     }
 
-    // Attempt summarization
+    // Collect summarization batch
     if (toSummarize.length > 0) {
-      const summarizeResult = await retryableSummarize(toSummarize);
+      console.log(
+        logPrefix,
+        "Collecting summarization batch:",
+        "\nTarget:",
+        toSummarize
+      );
+
+      toSummarizeArray.push([...toSummarize]);
+    }
+
+    currentTokens -= toSummarizeTokens;
+    startIdx = currentIndex;
+  }
+
+  // Process all collected summarization tasks
+  if (toSummarizeArray.length > 0) {
+    // Initialize rate limiter
+    // Local model must be processed sequentially
+    const rateLimiter = new TaskRateLimiter({
+      tasksPerMinute:
+        settings.summarizationModel === "subModel"
+          ? settings.summarizationRequestsPerMinute
+          : 1000,
+      maxConcurrentTasks:
+        settings.summarizationModel === "subModel"
+          ? settings.summarizationMaxConcurrent
+          : 1,
+    });
+
+    rateLimiter.taskQueueChangeCallback = (queuedCount) => {
+      hypaV3ProgressStore.set({
+        open: true,
+        miniMsg: `${rateLimiter.queuedTaskCount}`,
+        msg: `${logPrefix} Summarizing...`,
+        subMsg: `${rateLimiter.queuedTaskCount} queued`,
+      });
+    };
+
+    const summarizationTasks = toSummarizeArray.map(
+      (item) => () => summarize(item)
+    );
+
+    // Start of performance measurement: summarize
+    console.log(
+      logPrefix,
+      `Starting ${toSummarizeArray.length} summarization.`
+    );
+    const summarizeStartTime = performance.now();
+
+    const batchResult = await rateLimiter.executeBatch<string>(
+      summarizationTasks
+    );
+
+    const summarizeEndTime = performance.now();
+    console.debug(
+      `${logPrefix} summarization completed in ${
+        summarizeEndTime - summarizeStartTime
+      }ms`
+    );
+    // End of performance measurement: summarize
+
+    hypaV3ProgressStore.set({
+      open: false,
+      miniMsg: "",
+      msg: "",
+      subMsg: "",
+    });
+
+    // Note:
+    // We can't save some successful summaries to the DB temporarily
+    // because don't know the actual summarization model name.
+    // It is possible that the user can change the summarization model.
+    for (let i = 0; i < batchResult.results.length; i++) {
+      const result = batchResult.results[i];
+
+      // Push consecutive successes
+      if (!result.success || !result.data) {
+        const errorMessage = !result.success
+          ? result.error
+          : "Empty summary returned";
+
+        console.log(logPrefix, "Summarization failed:", `\n${errorMessage}`);
 
-      if (
-        !summarizeResult.success ||
-        !summarizeResult.data ||
-        summarizeResult.data.trim().length === 0
-      ) {
         return {
           currentTokens,
           chats,
-          error: `[HypaV3] Summarization failed after maximum retries: ${summarizeResult.data}`,
+          error: `${logPrefix} Summarization failed: ${errorMessage}`,
           memory: toSerializableHypaV3Data(data),
         };
       }
 
+      const summaryText = result.data;
+
       data.summaries.push({
-        text: summarizeResult.data,
-        chatMemos: new Set(toSummarize.map((chat) => chat.memo)),
+        text: summaryText,
+        chatMemos: new Set(toSummarizeArray[i].map((chat) => chat.memo)),
         isImportant: false,
       });
     }
-
-    currentTokens -= toSummarizeTokens;
-    startIdx = endIdx;
   }
 
   console.log(
-    `[HypaV3] ${
-      summarizationMode ? "Completed" : "Skipped"
-    } summarization phase:`,
+    logPrefix,
+    `${summarizationMode ? "Completed" : "Skipped"} summarization phase:`,
     "\nCurrent Tokens:",
     currentTokens,
     "\nMax Context Tokens:",
@@ -483,20 +441,11 @@ export async function hypaMemoryV3(
 
   // Early return if no summaries
   if (data.summaries.length === 0) {
-    // Generate final memory prompt
-    const memory = encapsulateMemoryPrompt("");
-
-    const newChats: OpenAIChat[] = [
-      {
-        role: "system",
-        content: memory,
-        memo: "supaMemory",
-      },
-      ...chats.slice(startIdx),
-    ];
+    const newChats: OpenAIChat[] = chats.slice(startIdx);
 
     console.log(
-      "[HypaV3] Exiting function:",
+      logPrefix,
+      "Exiting function:",
       "\nCurrent Tokens:",
       currentTokens,
       "\nAll chats, including memory prompt:",
@@ -514,49 +463,50 @@ export async function hypaMemoryV3(
 
   const selectedSummaries: Summary[] = [];
   const randomMemoryRatio =
-    1 -
-    db.hypaV3Settings.recentMemoryRatio -
-    db.hypaV3Settings.similarMemoryRatio;
+    1 - settings.recentMemoryRatio - settings.similarMemoryRatio;
 
   // Select important summaries
-  const selectedImportantSummaries: Summary[] = [];
+  {
+    const selectedImportantSummaries: Summary[] = [];
 
-  for (const summary of data.summaries) {
-    if (summary.isImportant) {
-      const summaryTokens = await tokenizer.tokenizeChat({
-        role: "system",
-        content: summary.text + summarySeparator,
-      });
+    for (const summary of data.summaries) {
+      if (summary.isImportant) {
+        const summaryTokens = await tokenizer.tokenizeChat({
+          role: "system",
+          content: summary.text + summarySeparator,
+        });
 
-      if (summaryTokens > availableMemoryTokens) {
-        break;
+        if (summaryTokens > availableMemoryTokens) {
+          break;
+        }
+
+        selectedImportantSummaries.push(summary);
+
+        availableMemoryTokens -= summaryTokens;
       }
-
-      selectedImportantSummaries.push(summary);
-
-      availableMemoryTokens -= summaryTokens;
     }
+
+    selectedSummaries.push(...selectedImportantSummaries);
+
+    console.log(
+      logPrefix,
+      "After important memory selection:",
+      "\nSummary Count:",
+      selectedImportantSummaries.length,
+      "\nSummaries:",
+      selectedImportantSummaries,
+      "\nAvailable Memory Tokens:",
+      availableMemoryTokens
+    );
   }
 
-  selectedSummaries.push(...selectedImportantSummaries);
-
-  console.log(
-    "[HypaV3] After important memory selection:",
-    "\nSummary Count:",
-    selectedImportantSummaries.length,
-    "\nSummaries:",
-    selectedImportantSummaries,
-    "\nAvailable Memory Tokens:",
-    availableMemoryTokens
-  );
-
   // Select recent summaries
   const reservedRecentMemoryTokens = Math.floor(
-    availableMemoryTokens * db.hypaV3Settings.recentMemoryRatio
+    availableMemoryTokens * settings.recentMemoryRatio
   );
   let consumedRecentMemoryTokens = 0;
 
-  if (db.hypaV3Settings.recentMemoryRatio > 0) {
+  if (settings.recentMemoryRatio > 0) {
     const selectedRecentSummaries: Summary[] = [];
 
     // Target only summaries that haven't been selected yet
@@ -586,7 +536,8 @@ export async function hypaMemoryV3(
     selectedSummaries.push(...selectedRecentSummaries);
 
     console.log(
-      "[HypaV3] After recent memory selection:",
+      logPrefix,
+      "After recent memory selection:",
       "\nSummary Count:",
       selectedRecentSummaries.length,
       "\nSummaries:",
@@ -600,11 +551,11 @@ export async function hypaMemoryV3(
 
   // Select similar summaries
   let reservedSimilarMemoryTokens = Math.floor(
-    availableMemoryTokens * db.hypaV3Settings.similarMemoryRatio
+    availableMemoryTokens * settings.similarMemoryRatio
   );
   let consumedSimilarMemoryTokens = 0;
 
-  if (db.hypaV3Settings.similarMemoryRatio > 0) {
+  if (settings.similarMemoryRatio > 0) {
     const selectedSimilarSummaries: Summary[] = [];
 
     // Utilize unused token space from recent selection
@@ -614,7 +565,8 @@ export async function hypaMemoryV3(
 
       reservedSimilarMemoryTokens += unusedRecentTokens;
       console.log(
-        "[HypaV3] Additional available token space for similar memory:",
+        logPrefix,
+        "Additional available token space for similar memory:",
         "\nFrom recent:",
         unusedRecentTokens
       );
@@ -625,155 +577,182 @@ export async function hypaMemoryV3(
       (e) => !selectedSummaries.includes(e)
     );
 
-    // Dynamically generate summary chunks
-    const summaryChunks: SummaryChunk[] = [];
+    // Dynamically generate embedding texts
+    const ebdTexts: EmbeddingText<Summary>[] = unusedSummaries.flatMap(
+      (summary) => {
+        const splitted = summary.text
+          .split("\n\n")
+          .filter((e) => e.trim().length > 0);
 
-    unusedSummaries.forEach((summary) => {
-      const splitted = summary.text
-        .split("\n\n")
-        .filter((e) => e.trim().length > 0);
+        return splitted.map((e) => ({
+          content: e.trim(),
+          metadata: summary,
+        }));
+      }
+    );
 
-      summaryChunks.push(
-        ...splitted.map((e) => ({
-          text: e.trim(),
-          summary,
-        }))
-      );
+    // Initialize embedding processor
+    const processor = new HypaProcessorV2<Summary>({
+      rateLimiter: new TaskRateLimiter({
+        tasksPerMinute: settings.embeddingRequestsPerMinute,
+        maxConcurrentTasks: settings.embeddingMaxConcurrent,
+      }),
     });
 
-    // Fetch memory from summaryChunks
-    const processor = new HypaProcesserEx(db.hypaModel);
-    processor.oaikey = db.supaMemoryKey;
+    processor.progressCallback = (queuedCount) => {
+      hypaV3ProgressStore.set({
+        open: true,
+        miniMsg: `${queuedCount}`,
+        msg: `${logPrefix} Similarity searching...`,
+        subMsg: `${queuedCount} queued`,
+      });
+    };
 
-    // Add summaryChunks to processor for similarity search
     try {
-      await processor.addSummaryChunks(summaryChunks);
+      // Start of performance measurement: addTexts
+      console.log(
+        `${logPrefix} Starting addTexts with ${ebdTexts.length} chunks`
+      );
+      const addStartTime = performance.now();
+
+      // Add EmbeddingTexts to processor for similarity search
+      await processor.addTexts(ebdTexts);
+
+      const addEndTime = performance.now();
+      console.debug(
+        `${logPrefix} addTexts completed in ${addEndTime - addStartTime}ms`
+      );
+      // End of performance measurement: addTexts
     } catch (error) {
       return {
         currentTokens,
         chats,
-        error: `[HypaV3] Similarity search failed: ${error}`,
+        error: `${logPrefix} Similarity search failed: ${error}`,
         memory: toSerializableHypaV3Data(data),
       };
-    }
-
-    const scoredSummaries = new Map<Summary, number>();
-
-    // (1) Raw recent chat search
-    for (let i = 0; i < minChatsForSimilarity; i++) {
-      const pop = chats[chats.length - i - 1];
-
-      if (!pop) break;
-
-      try {
-        const searched = await processor.similaritySearchScoredEx(pop.content);
-
-        for (const [chunk, similarity] of searched) {
-          const summary = chunk.summary;
-
-          scoredSummaries.set(
-            summary,
-            (scoredSummaries.get(summary) || 0) + similarity
-          );
-        }
-      } catch (error) {
-        return {
-          currentTokens,
-          chats,
-          error: `[HypaV3] Similarity search failed: ${error}`,
-          memory: toSerializableHypaV3Data(data),
-        };
-      }
-    }
-
-    // (2) Summarized recent chat search
-    if (db.hypaV3Settings.enableSimilarityCorrection) {
-      // Attempt summarization
-      const recentChats = chats.slice(-minChatsForSimilarity);
-      const summarizeResult = await retryableSummarize(recentChats);
-
-      if (
-        !summarizeResult.success ||
-        !summarizeResult.data ||
-        summarizeResult.data.trim().length === 0
-      ) {
-        return {
-          currentTokens,
-          chats,
-          error: `[HypaV3] Summarization failed after maximum retries: ${summarizeResult.data}`,
-          memory: toSerializableHypaV3Data(data),
-        };
-      }
-
-      try {
-        const searched = await processor.similaritySearchScoredEx(
-          summarizeResult.data
-        );
-
-        for (const [chunk, similarity] of searched) {
-          const summary = chunk.summary;
-
-          scoredSummaries.set(
-            summary,
-            (scoredSummaries.get(summary) || 0) + similarity
-          );
-        }
-      } catch (error) {
-        return {
-          currentTokens,
-          chats,
-          error: `[HypaV3] Similarity search failed: ${error}`,
-          memory: toSerializableHypaV3Data(data),
-        };
-      }
-
-      console.log("[HypaV3] Similarity corrected.");
-    }
-
-    // Sort in descending order
-    const scoredArray = [...scoredSummaries.entries()].sort(
-      ([, scoreA], [, scoreB]) => scoreB - scoreA
-    );
-
-    while (scoredArray.length > 0) {
-      const [summary] = scoredArray.shift();
-      const summaryTokens = await tokenizer.tokenizeChat({
-        role: "system",
-        content: summary.text + summarySeparator,
+    } finally {
+      hypaV3ProgressStore.set({
+        open: false,
+        miniMsg: "",
+        msg: "",
+        subMsg: "",
       });
-
-      /*
-      console.log(
-        "[HypaV3] Trying to add similar summary:",
-        "\nSummary Tokens:",
-        summaryTokens,
-        "\nConsumed Similar Memory Tokens:",
-        consumedSimilarMemoryTokens,
-        "\nReserved Tokens:",
-        reservedSimilarMemoryTokens,
-        "\nWould exceed:",
-        summaryTokens + consumedSimilarMemoryTokens > reservedSimilarMemoryTokens
-      );
-      */
-
-      if (
-        summaryTokens + consumedSimilarMemoryTokens >
-        reservedSimilarMemoryTokens
-      ) {
-        console.log(
-          `[HypaV3] Stopping similar memory selection: consumedSimilarMemoryTokens(${consumedSimilarMemoryTokens}) + summaryTokens(${summaryTokens}) > reservedSimilarMemoryTokens(${reservedSimilarMemoryTokens})`
-        );
-        break;
-      }
-
-      selectedSimilarSummaries.push(summary);
-      consumedSimilarMemoryTokens += summaryTokens;
     }
 
-    selectedSummaries.push(...selectedSimilarSummaries);
+    const recentChats = chats
+      .slice(-minChatsForSimilarity)
+      .filter((chat) => chat.content.trim().length > 0);
+    const queries: string[] = recentChats.flatMap((chat) => {
+      return chat.content.split("\n\n").filter((e) => e.trim().length > 0);
+    });
+
+    if (queries.length > 0) {
+      const scoredSummaries = new Map<Summary, number>();
+
+      try {
+        // Start of performance measurement: similarity search
+        console.log(
+          `${logPrefix} Starting similarity search with ${recentChats.length} queries`
+        );
+        const searchStartTime = performance.now();
+
+        const batchScoredResults = await processor.similaritySearchScoredBatch(
+          queries
+        );
+
+        const searchEndTime = performance.now();
+        console.debug(
+          `${logPrefix} Similarity search completed in ${
+            searchEndTime - searchStartTime
+          }ms`
+        );
+        // End of performance measurement: similarity search
+
+        for (const scoredResults of batchScoredResults) {
+          for (const [ebdResult, similarity] of scoredResults) {
+            const summary = ebdResult.metadata;
+
+            scoredSummaries.set(
+              summary,
+              (scoredSummaries.get(summary) || 0) + similarity
+            );
+          }
+        }
+      } catch (error) {
+        return {
+          currentTokens,
+          chats,
+          error: `${logPrefix} Similarity search failed: ${error}`,
+          memory: toSerializableHypaV3Data(data),
+        };
+      } finally {
+        hypaV3ProgressStore.set({
+          open: false,
+          miniMsg: "",
+          msg: "",
+          subMsg: "",
+        });
+      }
+
+      // Normalize scores
+      if (scoredSummaries.size > 0) {
+        const maxScore = Math.max(...scoredSummaries.values());
+
+        for (const [summary, score] of scoredSummaries.entries()) {
+          scoredSummaries.set(summary, score / maxScore);
+        }
+      }
+
+      // Sort in descending order
+      const scoredArray = [...scoredSummaries.entries()].sort(
+        ([, scoreA], [, scoreB]) => scoreB - scoreA
+      );
+
+      while (scoredArray.length > 0) {
+        const [summary] = scoredArray.shift();
+        const summaryTokens = await tokenizer.tokenizeChat({
+          role: "system",
+          content: summary.text + summarySeparator,
+        });
+
+        /*
+        console.log(
+          logPrefix,
+          "Trying to add similar summary:",
+          "\nSummary Tokens:",
+          summaryTokens,
+          "\nConsumed Similar Memory Tokens:",
+          consumedSimilarMemoryTokens,
+          "\nReserved Tokens:",
+          reservedSimilarMemoryTokens,
+          "\nWould exceed:",
+          summaryTokens + consumedSimilarMemoryTokens >
+            reservedSimilarMemoryTokens
+        );
+        */
+
+        if (
+          summaryTokens + consumedSimilarMemoryTokens >
+          reservedSimilarMemoryTokens
+        ) {
+          console.log(
+            logPrefix,
+            "Stopping similar memory selection:",
+            `\nconsumedSimilarMemoryTokens(${consumedSimilarMemoryTokens}) + summaryTokens(${summaryTokens}) > reservedSimilarMemoryTokens(${reservedSimilarMemoryTokens})`
+          );
+          break;
+        }
+
+        selectedSimilarSummaries.push(summary);
+        consumedSimilarMemoryTokens += summaryTokens;
+      }
+
+      selectedSummaries.push(...selectedSimilarSummaries);
+    }
 
     console.log(
-      "[HypaV3] After similar memory selection:",
+      logPrefix,
+      "After similar memory selection:",
       "\nSummary Count:",
       selectedSimilarSummaries.length,
       "\nSummaries:",
@@ -802,7 +781,8 @@ export async function hypaMemoryV3(
 
     reservedRandomMemoryTokens += unusedRecentTokens + unusedSimilarTokens;
     console.log(
-      "[HypaV3] Additional available token space for random memory:",
+      logPrefix,
+      "Additional available token space for random memory:",
       "\nFrom recent:",
       unusedRecentTokens,
       "\nFrom similar:",
@@ -837,7 +817,8 @@ export async function hypaMemoryV3(
     selectedSummaries.push(...selectedRandomSummaries);
 
     console.log(
-      "[HypaV3] After random memory selection:",
+      logPrefix,
+      "After random memory selection:",
       "\nSummary Count:",
       selectedRandomSummaries.length,
       "\nSummaries:",
@@ -855,7 +836,8 @@ export async function hypaMemoryV3(
   );
 
   // Generate final memory prompt
-  const memory = encapsulateMemoryPrompt(
+  const memory = wrapWithXml(
+    memoryPromptTag,
     selectedSummaries.map((e) => e.text).join(summarySeparator)
   );
   const realMemoryTokens = await tokenizer.tokenizeChat({
@@ -864,16 +846,15 @@ export async function hypaMemoryV3(
   });
 
   // Release reserved memory tokens
-  if (shouldReserveEmptyMemoryTokens) {
-    currentTokens -= emptyMemoryTokens;
-  } else {
+  if (shouldReserveMemoryTokens) {
     currentTokens -= memoryTokens;
   }
 
   currentTokens += realMemoryTokens;
 
   console.log(
-    "[HypaV3] Final memory selection:",
+    logPrefix,
+    "Final memory selection:",
     "\nSummary Count:",
     selectedSummaries.length,
     "\nSummaries:",
@@ -886,7 +867,7 @@ export async function hypaMemoryV3(
 
   if (currentTokens > maxContextTokens) {
     throw new Error(
-      `[HypaV3] Unexpected error: input token count (${currentTokens}) exceeds max context size (${maxContextTokens})`
+      `Unexpected error: input token count (${currentTokens}) exceeds max context size (${maxContextTokens})`
     );
   }
 
@@ -905,7 +886,8 @@ export async function hypaMemoryV3(
   ];
 
   console.log(
-    "[HypaV3] Exiting function:",
+    logPrefix,
+    "Exiting function:",
     "\nCurrent Tokens:",
     currentTokens,
     "\nAll chats, including memory prompt:",
@@ -921,26 +903,870 @@ export async function hypaMemoryV3(
   };
 }
 
-type SummaryChunkVector = {
+async function hypaMemoryV3Main(
+  chats: OpenAIChat[],
+  currentTokens: number,
+  maxContextTokens: number,
+  room: Chat,
+  char: character | groupChat,
+  tokenizer: ChatTokenizer
+): Promise<HypaV3Result> {
+  const db = getDatabase();
+  const settings = getCurrentHypaV3Preset().settings;
+
+  // Validate settings
+  if (settings.recentMemoryRatio + settings.similarMemoryRatio > 1) {
+    return {
+      currentTokens,
+      chats,
+      error: `${logPrefix} The sum of Recent Memory Ratio and Similar Memory Ratio is greater than 1.`,
+    };
+  }
+
+  // Initial token correction
+  currentTokens -= db.maxResponse;
+
+  // Load existing hypa data if available
+  let data: HypaV3Data = {
+    summaries: [],
+    lastSelectedSummaries: [],
+  };
+
+  if (room.hypaV3Data) {
+    data = toHypaV3Data(room.hypaV3Data);
+  }
+
+  // Clean orphaned summaries
+  if (!settings.preserveOrphanedMemory) {
+    cleanOrphanedSummary(chats, data);
+  }
+
+  // Determine starting index
+  let startIdx = 0;
+
+  if (data.summaries.length > 0) {
+    const lastSummary = data.summaries.at(-1);
+    const lastChatIndex = chats.findIndex(
+      (chat) => chat.memo === [...lastSummary.chatMemos].at(-1)
+    );
+
+    if (lastChatIndex !== -1) {
+      startIdx = lastChatIndex + 1;
+
+      // Exclude tokens from summarized chats
+      const summarizedChats = chats.slice(0, lastChatIndex + 1);
+      for (const chat of summarizedChats) {
+        currentTokens -= await tokenizer.tokenizeChat(chat);
+      }
+    }
+  }
+
+  console.log(logPrefix, "Starting index:", startIdx);
+
+  // Reserve memory tokens
+  const emptyMemoryTokens = await tokenizer.tokenizeChat({
+    role: "system",
+    content: wrapWithXml(memoryPromptTag, ""),
+  });
+  const memoryTokens = Math.floor(
+    maxContextTokens * settings.memoryTokensRatio
+  );
+  const shouldReserveEmptyMemoryTokens =
+    data.summaries.length === 0 &&
+    currentTokens + emptyMemoryTokens <= maxContextTokens;
+  let availableMemoryTokens = shouldReserveEmptyMemoryTokens
+    ? 0
+    : memoryTokens - emptyMemoryTokens;
+
+  if (shouldReserveEmptyMemoryTokens) {
+    currentTokens += emptyMemoryTokens;
+    console.log(logPrefix, "Reserved empty memory tokens:", emptyMemoryTokens);
+  } else {
+    currentTokens += memoryTokens;
+    console.log(logPrefix, "Reserved max memory tokens:", memoryTokens);
+  }
+
+  // If summarization is needed
+  const summarizationMode = currentTokens > maxContextTokens;
+  const targetTokens =
+    maxContextTokens * (1 - settings.extraSummarizationRatio);
+
+  while (summarizationMode) {
+    if (currentTokens <= targetTokens) {
+      break;
+    }
+
+    if (chats.length - startIdx <= minChatsForSimilarity) {
+      if (currentTokens <= maxContextTokens) {
+        break;
+      } else {
+        return {
+          currentTokens,
+          chats,
+          error: `${logPrefix} Cannot summarize further: input token count (${currentTokens}) exceeds max context size (${maxContextTokens}), but minimum ${minChatsForSimilarity} messages required.`,
+          memory: toSerializableHypaV3Data(data),
+        };
+      }
+    }
+
+    const toSummarize: OpenAIChat[] = [];
+    const endIdx = Math.min(
+      startIdx + settings.maxChatsPerSummary,
+      chats.length - minChatsForSimilarity
+    );
+    let toSummarizeTokens = 0;
+
+    console.log(
+      logPrefix,
+      "Evaluating summarization batch:",
+      "\nCurrent Tokens:",
+      currentTokens,
+      "\nMax Context Tokens:",
+      maxContextTokens,
+      "\nStart Index:",
+      startIdx,
+      "\nEnd Index:",
+      endIdx,
+      "\nChat Count:",
+      endIdx - startIdx,
+      "\nMax Chats Per Summary:",
+      settings.maxChatsPerSummary
+    );
+
+    for (let i = startIdx; i < endIdx; i++) {
+      const chat = chats[i];
+      const chatTokens = await tokenizer.tokenizeChat(chat);
+
+      console.log(
+        logPrefix,
+        "Evaluating chat:",
+        "\nIndex:",
+        i,
+        "\nRole:",
+        chat.role,
+        "\nContent:",
+        "\n" + chat.content,
+        "\nTokens:",
+        chatTokens
+      );
+
+      toSummarizeTokens += chatTokens;
+
+      if (
+        chat.name === "example_user" ||
+        chat.name === "example_assistant" ||
+        chat.memo === "NewChatExample"
+      ) {
+        console.log(logPrefix, `Skipping example chat at index ${i}`);
+        continue;
+      }
+
+      if (chat.memo === "NewChat") {
+        console.log(logPrefix, `Skipping new chat at index ${i}`);
+        continue;
+      }
+
+      if (chat.content.trim().length === 0) {
+        console.log(logPrefix, `Skipping empty chat at index ${i}`);
+        continue;
+      }
+
+      if (settings.doNotSummarizeUserMessage && chat.role === "user") {
+        console.log(logPrefix, `Skipping user role at index ${i}`);
+        continue;
+      }
+
+      toSummarize.push(chat);
+    }
+
+    // Stop summarization if further reduction would go below target tokens (unless we're over max tokens)
+    if (
+      currentTokens <= maxContextTokens &&
+      currentTokens - toSummarizeTokens < targetTokens
+    ) {
+      console.log(
+        logPrefix,
+        "Stopping summarization:",
+        `\ncurrentTokens(${currentTokens}) - toSummarizeTokens(${toSummarizeTokens}) < targetTokens(${targetTokens})`
+      );
+      break;
+    }
+
+    // Attempt summarization
+    if (toSummarize.length > 0) {
+      console.log(
+        logPrefix,
+        "Attempting summarization:",
+        "\nTarget:",
+        toSummarize
+      );
+
+      try {
+        const summarizeResult = await summarize(toSummarize);
+
+        data.summaries.push({
+          text: summarizeResult,
+          chatMemos: new Set(toSummarize.map((chat) => chat.memo)),
+          isImportant: false,
+        });
+      } catch (error) {
+        console.log(logPrefix, "Summarization failed:", `\n${error}`);
+
+        return {
+          currentTokens,
+          chats,
+          error: `${logPrefix} Summarization failed: ${error}`,
+          memory: toSerializableHypaV3Data(data),
+        };
+      }
+    }
+
+    currentTokens -= toSummarizeTokens;
+    startIdx = endIdx;
+  }
+
+  console.log(
+    logPrefix,
+    `${summarizationMode ? "Completed" : "Skipped"} summarization phase:`,
+    "\nCurrent Tokens:",
+    currentTokens,
+    "\nMax Context Tokens:",
+    maxContextTokens,
+    "\nAvailable Memory Tokens:",
+    availableMemoryTokens
+  );
+
+  // Early return if no summaries
+  if (data.summaries.length === 0) {
+    // Generate final memory prompt
+    const memory = wrapWithXml(memoryPromptTag, "");
+
+    const newChats: OpenAIChat[] = [
+      {
+        role: "system",
+        content: memory,
+        memo: "supaMemory",
+      },
+      ...chats.slice(startIdx),
+    ];
+
+    console.log(
+      logPrefix,
+      "Exiting function:",
+      "\nCurrent Tokens:",
+      currentTokens,
+      "\nAll chats, including memory prompt:",
+      newChats,
+      "\nMemory Data:",
+      data
+    );
+
+    return {
+      currentTokens,
+      chats: newChats,
+      memory: toSerializableHypaV3Data(data),
+    };
+  }
+
+  const selectedSummaries: Summary[] = [];
+  const randomMemoryRatio =
+    1 - settings.recentMemoryRatio - settings.similarMemoryRatio;
+
+  // Select important summaries
+  {
+    const selectedImportantSummaries: Summary[] = [];
+
+    for (const summary of data.summaries) {
+      if (summary.isImportant) {
+        const summaryTokens = await tokenizer.tokenizeChat({
+          role: "system",
+          content: summary.text + summarySeparator,
+        });
+
+        if (summaryTokens > availableMemoryTokens) {
+          break;
+        }
+
+        selectedImportantSummaries.push(summary);
+
+        availableMemoryTokens -= summaryTokens;
+      }
+    }
+
+    selectedSummaries.push(...selectedImportantSummaries);
+
+    console.log(
+      logPrefix,
+      "After important memory selection:",
+      "\nSummary Count:",
+      selectedImportantSummaries.length,
+      "\nSummaries:",
+      selectedImportantSummaries,
+      "\nAvailable Memory Tokens:",
+      availableMemoryTokens
+    );
+  }
+
+  // Select recent summaries
+  const reservedRecentMemoryTokens = Math.floor(
+    availableMemoryTokens * settings.recentMemoryRatio
+  );
+  let consumedRecentMemoryTokens = 0;
+
+  if (settings.recentMemoryRatio > 0) {
+    const selectedRecentSummaries: Summary[] = [];
+
+    // Target only summaries that haven't been selected yet
+    const unusedSummaries = data.summaries.filter(
+      (e) => !selectedSummaries.includes(e)
+    );
+
+    // Add one by one from the end
+    for (let i = unusedSummaries.length - 1; i >= 0; i--) {
+      const summary = unusedSummaries[i];
+      const summaryTokens = await tokenizer.tokenizeChat({
+        role: "system",
+        content: summary.text + summarySeparator,
+      });
+
+      if (
+        summaryTokens + consumedRecentMemoryTokens >
+        reservedRecentMemoryTokens
+      ) {
+        break;
+      }
+
+      selectedRecentSummaries.push(summary);
+      consumedRecentMemoryTokens += summaryTokens;
+    }
+
+    selectedSummaries.push(...selectedRecentSummaries);
+
+    console.log(
+      logPrefix,
+      "After recent memory selection:",
+      "\nSummary Count:",
+      selectedRecentSummaries.length,
+      "\nSummaries:",
+      selectedRecentSummaries,
+      "\nReserved Tokens:",
+      reservedRecentMemoryTokens,
+      "\nConsumed Tokens:",
+      consumedRecentMemoryTokens
+    );
+  }
+
+  // Select similar summaries
+  let reservedSimilarMemoryTokens = Math.floor(
+    availableMemoryTokens * settings.similarMemoryRatio
+  );
+  let consumedSimilarMemoryTokens = 0;
+
+  if (settings.similarMemoryRatio > 0) {
+    const selectedSimilarSummaries: Summary[] = [];
+
+    // Utilize unused token space from recent selection
+    if (randomMemoryRatio <= 0) {
+      const unusedRecentTokens =
+        reservedRecentMemoryTokens - consumedRecentMemoryTokens;
+
+      reservedSimilarMemoryTokens += unusedRecentTokens;
+      console.log(
+        logPrefix,
+        "Additional available token space for similar memory:",
+        "\nFrom recent:",
+        unusedRecentTokens
+      );
+    }
+
+    // Target only summaries that haven't been selected yet
+    const unusedSummaries = data.summaries.filter(
+      (e) => !selectedSummaries.includes(e)
+    );
+
+    // Dynamically generate summary chunks
+    const summaryChunks: SummaryChunk[] = [];
+
+    unusedSummaries.forEach((summary) => {
+      const splitted = summary.text
+        .split("\n\n")
+        .filter((e) => e.trim().length > 0);
+
+      summaryChunks.push(
+        ...splitted.map((e) => ({
+          text: e.trim(),
+          summary,
+        }))
+      );
+    });
+
+    // Initialize embedding processor
+    const processor = new HypaProcesserEx(db.hypaModel);
+    processor.oaikey = db.supaMemoryKey;
+
+    // Add summaryChunks to processor for similarity search
+    try {
+      await processor.addSummaryChunks(summaryChunks);
+    } catch (error) {
+      return {
+        currentTokens,
+        chats,
+        error: `${logPrefix} Similarity search failed: ${error}`,
+        memory: toSerializableHypaV3Data(data),
+      };
+    }
+
+    const scoredSummaries = new Map<Summary, number>();
+    const recentChats = chats
+      .slice(-minChatsForSimilarity)
+      .filter((chat) => chat.content.trim().length > 0);
+
+    if (recentChats.length > 0) {
+      // Raw recent chat search
+      const queries = recentChats.map((chat) => chat.content);
+
+      if (settings.enableSimilarityCorrection && recentChats.length > 1) {
+        // Raw + Summarized recent chat search
+        // Summarizing is meaningful when there are more than 2 recent chats
+
+        // Attempt summarization
+        console.log(
+          logPrefix,
+          "Attempting summarization for similarity search:",
+          "\nTarget:",
+          recentChats
+        );
+
+        try {
+          const summarizeResult = await summarize(recentChats);
+
+          queries.push(summarizeResult);
+        } catch (error) {
+          console.log(logPrefix, "Summarization failed:", `\n${error}`);
+
+          return {
+            currentTokens,
+            chats,
+            error: `${logPrefix} Summarization failed: ${error}`,
+            memory: toSerializableHypaV3Data(data),
+          };
+        }
+      }
+
+      try {
+        for (const query of queries) {
+          const scoredChunks = await processor.similaritySearchScoredEx(query);
+
+          for (const [chunk, similarity] of scoredChunks) {
+            const summary = chunk.summary;
+
+            scoredSummaries.set(
+              summary,
+              (scoredSummaries.get(summary) || 0) + similarity
+            );
+          }
+        }
+      } catch (error) {
+        return {
+          currentTokens,
+          chats,
+          error: `${logPrefix} Similarity search failed: ${error}`,
+          memory: toSerializableHypaV3Data(data),
+        };
+      }
+    }
+
+    // Sort in descending order
+    const scoredArray = [...scoredSummaries.entries()].sort(
+      ([, scoreA], [, scoreB]) => scoreB - scoreA
+    );
+
+    while (scoredArray.length > 0) {
+      const [summary] = scoredArray.shift();
+      const summaryTokens = await tokenizer.tokenizeChat({
+        role: "system",
+        content: summary.text + summarySeparator,
+      });
+
+      /*
+      console.log(
+        logPrefix,
+        "Trying to add similar summary:",
+        "\nSummary Tokens:",
+        summaryTokens,
+        "\nConsumed Similar Memory Tokens:",
+        consumedSimilarMemoryTokens,
+        "\nReserved Tokens:",
+        reservedSimilarMemoryTokens,
+        "\nWould exceed:",
+        summaryTokens + consumedSimilarMemoryTokens >
+          reservedSimilarMemoryTokens
+      );
+      */
+
+      if (
+        summaryTokens + consumedSimilarMemoryTokens >
+        reservedSimilarMemoryTokens
+      ) {
+        console.log(
+          logPrefix,
+          "Stopping similar memory selection:",
+          `\nconsumedSimilarMemoryTokens(${consumedSimilarMemoryTokens}) + summaryTokens(${summaryTokens}) > reservedSimilarMemoryTokens(${reservedSimilarMemoryTokens})`
+        );
+        break;
+      }
+
+      selectedSimilarSummaries.push(summary);
+      consumedSimilarMemoryTokens += summaryTokens;
+    }
+
+    selectedSummaries.push(...selectedSimilarSummaries);
+
+    console.log(
+      logPrefix,
+      "After similar memory selection:",
+      "\nSummary Count:",
+      selectedSimilarSummaries.length,
+      "\nSummaries:",
+      selectedSimilarSummaries,
+      "\nReserved Tokens:",
+      reservedSimilarMemoryTokens,
+      "\nConsumed Tokens:",
+      consumedSimilarMemoryTokens
+    );
+  }
+
+  // Select random summaries
+  let reservedRandomMemoryTokens = Math.floor(
+    availableMemoryTokens * randomMemoryRatio
+  );
+  let consumedRandomMemoryTokens = 0;
+
+  if (randomMemoryRatio > 0) {
+    const selectedRandomSummaries: Summary[] = [];
+
+    // Utilize unused token space from recent and similar selection
+    const unusedRecentTokens =
+      reservedRecentMemoryTokens - consumedRecentMemoryTokens;
+    const unusedSimilarTokens =
+      reservedSimilarMemoryTokens - consumedSimilarMemoryTokens;
+
+    reservedRandomMemoryTokens += unusedRecentTokens + unusedSimilarTokens;
+    console.log(
+      logPrefix,
+      "Additional available token space for random memory:",
+      "\nFrom recent:",
+      unusedRecentTokens,
+      "\nFrom similar:",
+      unusedSimilarTokens,
+      "\nTotal added:",
+      unusedRecentTokens + unusedSimilarTokens
+    );
+
+    // Target only summaries that haven't been selected yet
+    const unusedSummaries = data.summaries
+      .filter((e) => !selectedSummaries.includes(e))
+      .sort(() => Math.random() - 0.5); // Random shuffle
+
+    for (const summary of unusedSummaries) {
+      const summaryTokens = await tokenizer.tokenizeChat({
+        role: "system",
+        content: summary.text + summarySeparator,
+      });
+
+      if (
+        summaryTokens + consumedRandomMemoryTokens >
+        reservedRandomMemoryTokens
+      ) {
+        // Trying to select more random memory
+        continue;
+      }
+
+      selectedRandomSummaries.push(summary);
+      consumedRandomMemoryTokens += summaryTokens;
+    }
+
+    selectedSummaries.push(...selectedRandomSummaries);
+
+    console.log(
+      logPrefix,
+      "After random memory selection:",
+      "\nSummary Count:",
+      selectedRandomSummaries.length,
+      "\nSummaries:",
+      selectedRandomSummaries,
+      "\nReserved Tokens:",
+      reservedRandomMemoryTokens,
+      "\nConsumed Tokens:",
+      consumedRandomMemoryTokens
+    );
+  }
+
+  // Sort selected summaries chronologically (by index)
+  selectedSummaries.sort(
+    (a, b) => data.summaries.indexOf(a) - data.summaries.indexOf(b)
+  );
+
+  // Generate final memory prompt
+  const memory = wrapWithXml(
+    memoryPromptTag,
+    selectedSummaries.map((e) => e.text).join(summarySeparator)
+  );
+  const realMemoryTokens = await tokenizer.tokenizeChat({
+    role: "system",
+    content: memory,
+  });
+
+  // Release reserved memory tokens
+  if (shouldReserveEmptyMemoryTokens) {
+    currentTokens -= emptyMemoryTokens;
+  } else {
+    currentTokens -= memoryTokens;
+  }
+
+  currentTokens += realMemoryTokens;
+
+  console.log(
+    logPrefix,
+    "Final memory selection:",
+    "\nSummary Count:",
+    selectedSummaries.length,
+    "\nSummaries:",
+    selectedSummaries,
+    "\nReal Memory Tokens:",
+    realMemoryTokens,
+    "\nAvailable Memory Tokens:",
+    availableMemoryTokens
+  );
+
+  if (currentTokens > maxContextTokens) {
+    throw new Error(
+      `Unexpected error: input token count (${currentTokens}) exceeds max context size (${maxContextTokens})`
+    );
+  }
+
+  // Save last selected summaries
+  data.lastSelectedSummaries = selectedSummaries.map((selectedSummary) =>
+    data.summaries.findIndex((summary) => summary === selectedSummary)
+  );
+
+  const newChats: OpenAIChat[] = [
+    {
+      role: "system",
+      content: memory,
+      memo: "supaMemory",
+    },
+    ...chats.slice(startIdx),
+  ];
+
+  console.log(
+    logPrefix,
+    "Exiting function:",
+    "\nCurrent Tokens:",
+    currentTokens,
+    "\nAll chats, including memory prompt:",
+    newChats,
+    "\nMemory Data:",
+    data
+  );
+
+  return {
+    currentTokens,
+    chats: newChats,
+    memory: toSerializableHypaV3Data(data),
+  };
+}
+
+function toHypaV3Data(serialData: SerializableHypaV3Data): HypaV3Data {
+  return {
+    ...serialData,
+    summaries: serialData.summaries.map((summary) => ({
+      ...summary,
+      // Convert null back to undefined (JSON serialization converts undefined to null)
+      chatMemos: new Set(
+        summary.chatMemos.map((memo) => (memo === null ? undefined : memo))
+      ),
+    })),
+  };
+}
+
+function toSerializableHypaV3Data(data: HypaV3Data): SerializableHypaV3Data {
+  return {
+    ...data,
+    summaries: data.summaries.map((summary) => ({
+      ...summary,
+      chatMemos: [...summary.chatMemos],
+    })),
+  };
+}
+
+function cleanOrphanedSummary(chats: OpenAIChat[], data: HypaV3Data): void {
+  // Collect all memos from current chats
+  const currentChatMemos = new Set(chats.map((chat) => chat.memo));
+  const originalLength = data.summaries.length;
+
+  // Filter summaries - keep only those whose chatMemos are subset of current chat memos
+  data.summaries = data.summaries.filter((summary) => {
+    return isSubset(summary.chatMemos, currentChatMemos);
+  });
+
+  const removedCount = originalLength - data.summaries.length;
+
+  if (removedCount > 0) {
+    console.log(logPrefix, `Cleaned ${removedCount} orphaned summaries.`);
+  }
+}
+
+function isSubset(subset: Set<string>, superset: Set<string>): boolean {
+  for (const elem of subset) {
+    if (!superset.has(elem)) {
+      return false;
+    }
+  }
+
+  return true;
+}
+
+function wrapWithXml(tag: string, content: string): string {
+  return `<${tag}>\n${content}\n</${tag}>`;
+}
+
+export async function summarize(oaiMessages: OpenAIChat[]): Promise<string> {
+  const db = getDatabase();
+  const settings = getCurrentHypaV3Preset().settings;
+
+  const strMessages = oaiMessages
+    .map((chat) => `${chat.role}: ${chat.content}`)
+    .join("\n");
+
+  const summarizationPrompt =
+    settings.summarizationPrompt.trim() === ""
+      ? "[Summarize the ongoing role story, It must also remove redundancy and unnecessary text and content from the output.]"
+      : settings.summarizationPrompt;
+
+  const formated: OpenAIChat[] = parseChatML(
+    summarizationPrompt.replaceAll("{{slot}}", strMessages)
+  ) ?? [
+    {
+      role: "user",
+      content: strMessages,
+    },
+    {
+      role: "system",
+      content: summarizationPrompt,
+    },
+  ];
+
+  // API
+  if (settings.summarizationModel === "subModel") {
+    console.log(logPrefix, `Using ax model ${db.subModel} for summarization.`);
+
+    const response = await requestChatData(
+      {
+        formated,
+        bias: {},
+        useStreaming: false,
+        noMultiGen: true,
+      },
+      "memory"
+    );
+
+    if (response.type === "streaming" || response.type === "multiline") {
+      throw new Error("Unexpected response type");
+    }
+
+    if (response.type === "fail") {
+      throw new Error(response.result);
+    }
+
+    if (!response.result || response.result.trim().length === 0) {
+      throw new Error("Empty summary returned");
+    }
+
+    return response.result.trim();
+  }
+
+  // Local
+  const content = await chatCompletion(formated, settings.summarizationModel, {
+    max_tokens: 8192,
+    temperature: 0,
+    extra_body: {
+      enable_thinking: false,
+    },
+  });
+
+  if (!content || content.trim().length === 0) {
+    throw new Error("Empty summary returned");
+  }
+
+  // Remove think content
+  const thinkRegex = /<think>[\s\S]*?<\/think>/g;
+
+  return content.replace(thinkRegex, "").trim();
+}
+
+export function getCurrentHypaV3Preset(): HypaV3Preset {
+  const db = getDatabase();
+  const preset = db.hypaV3Presets?.[db.hypaV3PresetId];
+
+  if (!preset) {
+    throw new Error("Preset not found. Please select a valid preset.");
+  }
+
+  return preset;
+}
+
+export function createHypaV3Preset(
+  name = "New Preset",
+  existingSettings = {}
+): HypaV3Preset {
+  const settings: HypaV3Settings = {
+    summarizationModel: "subModel",
+    summarizationPrompt: "",
+    memoryTokensRatio: 0.2,
+    extraSummarizationRatio: 0,
+    maxChatsPerSummary: 6,
+    recentMemoryRatio: 0.4,
+    similarMemoryRatio: 0.4,
+    enableSimilarityCorrection: false,
+    preserveOrphanedMemory: false,
+    processRegexScript: false,
+    doNotSummarizeUserMessage: false,
+    // Experimental
+    useExperimentalImpl: false,
+    summarizationRequestsPerMinute: 20,
+    summarizationMaxConcurrent: 1,
+    embeddingRequestsPerMinute: 100,
+    embeddingMaxConcurrent: 1,
+  };
+
+  if (
+    existingSettings &&
+    typeof existingSettings === "object" &&
+    !Array.isArray(existingSettings)
+  ) {
+    for (const [key, value] of Object.entries(existingSettings)) {
+      if (key in settings && typeof value === typeof settings[key]) {
+        settings[key] = value;
+      }
+    }
+  }
+
+  return {
+    name,
+    settings,
+  };
+}
+
+interface SummaryChunkVector {
   chunk: SummaryChunk;
   vector: memoryVector;
-};
+}
 
 class HypaProcesserEx extends HypaProcesser {
   // Maintain references to SummaryChunks and their associated memoryVectors
   summaryChunkVectors: SummaryChunkVector[] = [];
 
-  // Calculate dot product similarity between two vectors
-  similarity(a: VectorArray, b: VectorArray): number {
-    let dot = 0;
-
-    for (let i = 0; i < a.length; i++) {
-      dot += a[i] * b[i];
-    }
-
-    return dot;
-  }
-
   async addSummaryChunks(chunks: SummaryChunk[]): Promise<void> {
     // Maintain the superclass's caching structure by adding texts
     const texts = chunks.map((chunk) => chunk.text);
@@ -977,7 +1803,7 @@ class HypaProcesserEx extends HypaProcesser {
     return this.summaryChunkVectors
       .map((scv) => ({
         chunk: scv.chunk,
-        similarity: this.similarity(queryVector, scv.vector.embedding),
+        similarity: similarity(queryVector, scv.vector.embedding),
       }))
       .sort((a, b) => (a.similarity > b.similarity ? -1 : 0))
       .map((result) => [result.chunk, result.similarity]);
diff --git a/src/ts/process/memory/taskRateLimiter.ts b/src/ts/process/memory/taskRateLimiter.ts
new file mode 100644
index 00000000..0d6cfae3
--- /dev/null
+++ b/src/ts/process/memory/taskRateLimiter.ts
@@ -0,0 +1,188 @@
+export interface TaskRateLimiterOptions {
+  tasksPerMinute?: number;
+  maxConcurrentTasks?: number;
+  failFast?: boolean;
+}
+
+export interface BatchResult<TData> {
+  results: TaskResult<TData>[];
+  successCount: number;
+  failureCount: number;
+  allSucceeded: boolean;
+}
+
+export interface TaskResult<TData> {
+  success: boolean;
+  data?: TData;
+  error?: Error;
+}
+
+export class TaskRateLimiter {
+  private static readonly LOG_PREFIX = "[TaskRateLimiter]";
+  public readonly options: TaskRateLimiterOptions;
+  public taskQueueChangeCallback: (queuedCount: number) => void = null;
+  private timestamps: number[] = [];
+  private active: number = 0;
+  private queue: Array<{
+    task: () => Promise<TaskResult<any>>;
+    resolve: (result: TaskResult<any>) => void;
+  }> = [];
+
+  public constructor(options?: TaskRateLimiterOptions) {
+    this.options = {
+      tasksPerMinute: 20,
+      maxConcurrentTasks: 5,
+      failFast: true,
+      ...options,
+    };
+
+    if (this.options.maxConcurrentTasks > this.options.tasksPerMinute) {
+      throw new Error("maxConcurrentTasks must be less than tasksPerMinute");
+    }
+  }
+
+  public async executeTask<TData>(
+    task: () => Promise<TData>
+  ): Promise<TaskResult<TData>> {
+    return new Promise<TaskResult<TData>>((resolve) => {
+      this.queue.push({
+        task: async () => {
+          try {
+            const data = await task();
+            return { success: true, data };
+          } catch (error) {
+            return { success: false, error };
+          }
+        },
+        resolve,
+      });
+
+      this.taskQueueChangeCallback?.(this.queue.length);
+      this.processNextFromQueue();
+    });
+  }
+
+  public async executeBatch<TData>(
+    tasks: Array<() => Promise<TData>>
+  ): Promise<BatchResult<TData>> {
+    const taskResults = await Promise.all(
+      tasks.map((task) => this.executeTask(task))
+    );
+    const successCount = taskResults.filter((r) => r.success).length;
+    const failureCount = taskResults.length - successCount;
+
+    return {
+      results: taskResults,
+      successCount,
+      failureCount,
+      allSucceeded: failureCount === 0,
+    };
+  }
+
+  public cancelPendingTasks(reason: string): void {
+    const error = new TaskCanceledError(reason);
+
+    while (this.queue.length > 0) {
+      const { resolve } = this.queue.shift();
+      resolve({ success: false, error });
+    }
+
+    this.taskQueueChangeCallback?.(this.queue.length);
+  }
+
+  public get queuedTaskCount(): number {
+    return this.queue.length;
+  }
+
+  private processNextFromQueue(): void {
+    if (this.queue.length === 0) return;
+
+    if (this.active >= this.options.maxConcurrentTasks) {
+      // Debug log for concurrency limit hit
+      console.debug(
+        TaskRateLimiter.LOG_PREFIX,
+        "Concurrency limit hit:",
+        "\nTasks in last minute:",
+        this.timestamps.length + "/" + this.options.tasksPerMinute,
+        "\nActive tasks:",
+        this.active + "/" + this.options.maxConcurrentTasks,
+        "\nWaiting tasks in queue:",
+        this.queue.length
+      );
+
+      return;
+    }
+
+    this.timestamps = this.timestamps.filter(
+      (ts) => Date.now() - ts <= 60 * 1000
+    );
+
+    if (this.timestamps.length >= this.options.tasksPerMinute) {
+      const oldestTimestamp = Math.min(...this.timestamps);
+      const timeUntilExpiry = Math.max(
+        100,
+        60 * 1000 - (Date.now() - oldestTimestamp)
+      );
+
+      // Debug log for rate limit hit
+      console.debug(
+        TaskRateLimiter.LOG_PREFIX,
+        "Rate limit hit:",
+        "\nTasks in last minute:",
+        this.timestamps.length + "/" + this.options.tasksPerMinute,
+        "\nActive tasks:",
+        this.active + "/" + this.options.maxConcurrentTasks,
+        "\nWaiting tasks in queue:",
+        this.queue.length,
+        "\nWill retry in:",
+        timeUntilExpiry + "ms"
+      );
+
+      // Wait until rate limit window advances before retrying
+      setTimeout(() => this.processNextFromQueue(), timeUntilExpiry);
+      return;
+    }
+
+    const { task, resolve } = this.queue.shift();
+
+    this.active++;
+    this.taskQueueChangeCallback?.(this.queue.length);
+    this.timestamps.push(Date.now());
+
+    // Debug log for task start
+    console.debug(
+      TaskRateLimiter.LOG_PREFIX,
+      "Task started:",
+      "\nTasks in last minute:",
+      this.timestamps.length + "/" + this.options.tasksPerMinute,
+      "\nActive tasks:",
+      this.active + "/" + this.options.maxConcurrentTasks,
+      "\nWaiting tasks in queue:",
+      this.queue.length
+    );
+
+    task()
+      .then((result) => {
+        resolve(result);
+
+        if (!result.success && this.options.failFast) {
+          this.cancelPendingTasks("Task canceled due to previous failure");
+        }
+      })
+      .finally(() => {
+        this.active--;
+
+        // Prevents call stack overflow while maintaining concurrency limits
+        queueMicrotask(() => this.processNextFromQueue());
+      });
+  }
+}
+
+export class TaskCanceledError extends Error {
+  public readonly name: string;
+
+  public constructor(message: string) {
+    super(message);
+    this.name = "TaskCanceledError";
+  }
+}
diff --git a/src/ts/process/stableDiff.ts b/src/ts/process/stableDiff.ts
index 74e56dd2..ab26263f 100644
--- a/src/ts/process/stableDiff.ts
+++ b/src/ts/process/stableDiff.ts
@@ -145,20 +145,22 @@ export async function generateAIImage(genPrompt:string, currentChar:character, n
                     "sm": false,
                     "sm_dyn": false,
                     "noise": db.NAIImgConfig.noise,
-                    "noise_schedule": db.NAIImgConfig.noise_schedule,
+                    "noise_schedule": "karras",
+                    "normalize_reference_strength_multiple":false,
                     "strength": db.NAIImgConfig.strength,
                     "ucPreset": 3,
                     "uncond_scale": 1,
                     "qualityToggle": false,
-                    "lagacy_v3_extend": false,
-                    "lagacy": false,
-                    "reference_information_extracted": db.NAIImgConfig.InfoExtracted,
-                    "reference_strength": db.NAIImgConfig.RefStrength,
+                    "legacy_v3_extend": false,
+                    "legacy": false,
+                    // "reference_information_extracted": db.NAIImgConfig.InfoExtracted,
+                    // Only set reference_strength if we're not using reference_strength_multiple
+                    "reference_strength": db.NAIImgConfig.reference_strength_multiple !== undefined ? undefined : db.NAIImgConfig.RefStrength,
                     //add v4
                     "autoSmea": db.NAIImgConfig.autoSmea,
-                    use_coords: db.NAIImgConfig.use_coords,
-                    legacy_uc: db.NAIImgConfig.legacy_uc,
-                    v4_prompt:{
+                    "use_coords": db.NAIImgConfig.use_coords,
+                    "legacy_uc": db.NAIImgConfig.legacy_uc,
+                    "v4_prompt":{
                         caption:{
                             base_caption:genPrompt,
                             char_captions: []
@@ -172,7 +174,9 @@ export async function generateAIImage(genPrompt:string, currentChar:character, n
                             char_captions: []
                         },
                         legacy_uc: db.NAIImgConfig.v4_negative_prompt.legacy_uc,
-                    }
+                    },
+                    "reference_image_multiple" : [],
+                    "reference_strength_multiple" : [],
                 }
             },
             headers:{
@@ -181,13 +185,51 @@ export async function generateAIImage(genPrompt:string, currentChar:character, n
             rawResponse: true
         }
 
+        // Add vibe reference_image_multiple if exists
+        if(db.NAIImgConfig.vibe_data) {
+            const vibeData = db.NAIImgConfig.vibe_data;
+            // Determine which model to use based on vibe_model_selection or fallback to current model
+            const modelKey = db.NAIImgConfig.vibe_model_selection || 
+                            (db.NAIImgModel.includes('nai-diffusion-4-full') ? 'v4full' : 
+                             db.NAIImgModel.includes('nai-diffusion-4-curated') ? 'v4curated' : null);
+
+            if(modelKey && vibeData.encodings && vibeData.encodings[modelKey]) {
+                // Initialize arrays if they don't exist
+                if(!commonReq.body.parameters.reference_image_multiple) {
+                    commonReq.body.parameters.reference_image_multiple = [];
+                }
+                if(!commonReq.body.parameters.reference_strength_multiple) {
+                    commonReq.body.parameters.reference_strength_multiple = [];
+                }
+
+                // Use selected encoding or first available
+                let encodingKey = db.NAIImgConfig.vibe_model_selection ? 
+                                 Object.keys(vibeData.encodings[modelKey]).find(key => 
+                                    vibeData.encodings[modelKey][key].params.information_extracted === 
+                                    (db.NAIImgConfig.InfoExtracted || 1)) : 
+                                 Object.keys(vibeData.encodings[modelKey])[0];
+
+                if(encodingKey) {
+                    const encoding = vibeData.encodings[modelKey][encodingKey].encoding;
+                    // Add encoding to the array
+                    commonReq.body.parameters.reference_image_multiple.push(encoding);
+
+                    // Add reference_strength_multiple if it exists
+                    const strength = db.NAIImgConfig.reference_strength_multiple && 
+                                    db.NAIImgConfig.reference_strength_multiple.length > 0 ? 
+                                    db.NAIImgConfig.reference_strength_multiple[0] : 0.5;
+                    commonReq.body.parameters.reference_strength_multiple.push(strength);
+                }
+            }
+        }
+
         if(db.NAII2I){
             let seed = Math.floor(Math.random() * 10000000000)
-         
+
             let base64img = ''
             if(db.NAIImgConfig.image === ''){
                 const charimg = currentChar.image;
-                
+
                 const img = await readImage(charimg)
                 base64img = Buffer.from(img).toString('base64');
             }   else{
@@ -201,7 +243,7 @@ export async function generateAIImage(genPrompt:string, currentChar:character, n
                     refimgbase64 = Buffer.from(await readImage(db.NAIImgConfig.refimage)).toString('base64');
                 }
             }
-            
+
             reqlist = commonReq;
             reqlist.body.action = "img2img";
             reqlist.body.parameters.image = base64img;
@@ -211,6 +253,8 @@ export async function generateAIImage(genPrompt:string, currentChar:character, n
             if(refimgbase64 !== undefined){
                 reqlist.body.parameters.reference_image = refimgbase64
             }
+
+
             console.log({img2img:reqlist});
         }else{
 
@@ -219,7 +263,7 @@ export async function generateAIImage(genPrompt:string, currentChar:character, n
                 let base64img = ''
                 if(db.NAIImgConfig.image === ''){
                     const charimg = currentChar.image;
-                    
+
                     const img = await readImage(charimg)
                     base64img = Buffer.from(img).toString('base64');
                 }   else{
@@ -228,10 +272,12 @@ export async function generateAIImage(genPrompt:string, currentChar:character, n
                 reqlist = commonReq;
                 reqlist.body.action = 'generate';
                 reqlist.body.parameters.reference_image = base64img;
+
                 console.log({generate:reqlist});
             } else {
                 reqlist = commonReq;
                 reqlist.body.action = 'generate';
+
                 console.log({nothing:reqlist});
             }
         }
@@ -407,7 +453,7 @@ export async function generateAIImage(genPrompt:string, currentChar:character, n
                         if(inputKeys[j] === 'seed' && typeof input === 'number'){
                             input = Math.floor(Math.random() * 1000000000)
                         }
-                        
+
                         node.inputs[inputKeys[j]] = input
                     }
                 }
@@ -435,7 +481,7 @@ export async function generateAIImage(genPrompt:string, currentChar:character, n
                 }
                 await new Promise(r => setTimeout(r, 1000))
             } // Check history until the generation is complete.
-            const genImgInfo = Object.values(item.outputs).flatMap((output: any) => output.images || [])[0];
+            const genImgInfo = Object.values(item.outputs).flatMap((output: any) => output.images)[0];
 
             const imgResponse = await fetchNative(createUrl('/view', {
                 filename: genImgInfo.filename,
@@ -495,7 +541,7 @@ export async function generateAIImage(genPrompt:string, currentChar:character, n
             CharEmotion.set(charemotions)
         }
         return returnSdData
-        
+
     }
     if(db.sdProvider === 'fal'){
         const model = db.falModel
diff --git a/src/ts/process/transformers.ts b/src/ts/process/transformers.ts
index 4e238fa2..ea3a32d6 100644
--- a/src/ts/process/transformers.ts
+++ b/src/ts/process/transformers.ts
@@ -60,12 +60,19 @@ export const runEmbedding = async (texts: string[], model:EmbeddingModel = 'Xeno
     console.log('running embedding')
     let embeddingModelQuery = model + device
     if(!extractor || embeddingModelQuery !== lastEmbeddingModelQuery){
+        // Dispose old extractor
+        if(extractor) {
+            await extractor.dispose()
+        }
         extractor = await pipeline('feature-extraction', model, {
+            // Default dtype for webgpu is fp32, so we can use q8, which is the default dtype in wasm.
+            ...(device === 'webgpu' ? { dtype: "q8" } : {}),
             device: device,
             progress_callback: (progress) => {
                 console.log(progress)
             }
         });
+        lastEmbeddingModelQuery = embeddingModelQuery
         console.log('extractor loaded')
     }
     let result = await extractor(texts, { pooling: 'mean', normalize: true });
diff --git a/src/ts/process/webllm.ts b/src/ts/process/webllm.ts
new file mode 100644
index 00000000..cb1c1485
--- /dev/null
+++ b/src/ts/process/webllm.ts
@@ -0,0 +1,60 @@
+import {
+  type ChatCompletionMessageParam,
+  type ChatCompletionRequestNonStreaming,
+  MLCEngine,
+  CreateMLCEngine,
+} from "@mlc-ai/web-llm";
+
+let engine: MLCEngine = null;
+let lastModel: string = null;
+
+export async function chatCompletion(
+  messages: { role: string; content: string }[],
+  model: string,
+  config: Record<string, any>
+): Promise<string> {
+  try {
+    if (!engine || lastModel !== model) {
+      if (engine) engine.unload();
+
+      const initProgressCallback = (progress) => {
+        console.log("[WebLLM]", progress);
+      };
+
+      engine = await CreateMLCEngine(
+        model,
+        {
+          initProgressCallback,
+        },
+        { context_window_size: 16384 }
+      );
+
+      lastModel = model;
+    }
+
+    const request: ChatCompletionRequestNonStreaming = {
+      messages: messages as ChatCompletionMessageParam[],
+      temperature: 0,
+      max_tokens: 4096,
+      ...config,
+    };
+    const completion = await engine.chat.completions.create(request);
+    const content = completion.choices[0].message.content;
+
+    return content;
+  } catch (error) {
+    if (error instanceof Error) {
+      throw error;
+    }
+
+    throw new Error(JSON.stringify(error));
+  }
+}
+
+export async function unloadEngine(): Promise<void> {
+  if (!engine) return;
+
+  await engine.unload();
+  engine = null;
+  lastModel = null;
+}
diff --git a/src/ts/storage/database.svelte.ts b/src/ts/storage/database.svelte.ts
index 7a5fb478..07cd9173 100644
--- a/src/ts/storage/database.svelte.ts
+++ b/src/ts/storage/database.svelte.ts
@@ -11,6 +11,7 @@ import { prebuiltNAIpresets, prebuiltPresets } from '../process/templates/templa
 import { defaultColorScheme, type ColorScheme } from '../gui/colorscheme';
 import type { PromptItem, PromptSettings } from '../process/prompt';
 import type { OobaChatCompletionRequestParams } from '../model/ooba';
+import { type HypaV3Settings, type HypaV3Preset, createHypaV3Preset } from '../process/memory/hypav3'
 
 export let appVer = "159.0.0"
 export let webAppSubVer = ''
@@ -271,6 +272,7 @@ export function setDatabase(data:Database){
             autoSmea:false,
             legacy_uc:false,
             use_coords:false,
+            cfg_rescale:0,
             v4_prompt:{
                 caption:{
                     base_caption:'',
@@ -309,6 +311,9 @@ export function setDatabase(data:Database){
             legacy_uc:false,
         };
     }
+    if(checkNullish(data.NAIImgConfig.cfg_rescale)){
+        data.NAIImgConfig.cfg_rescale = 0;
+    }
     if(checkNullish(data.customTextTheme)){
         data.customTextTheme = {
             FontColorStandard: "#f8f8f2",
@@ -515,17 +520,21 @@ export function setDatabase(data:Database){
     data.checkCorruption ??= true
     data.OaiCompAPIKeys ??= {}
     data.reasoningEffort ??= 0
-    data.hypaV3Settings = {
-        memoryTokensRatio: data.hypaV3Settings?.memoryTokensRatio ?? 0.2,
-        extraSummarizationRatio: data.hypaV3Settings?.extraSummarizationRatio ?? 0,
-        maxChatsPerSummary: data.hypaV3Settings?.maxChatsPerSummary ?? 4,
-        recentMemoryRatio: data.hypaV3Settings?.recentMemoryRatio ?? 0.4,
-        similarMemoryRatio: data.hypaV3Settings?.similarMemoryRatio ?? 0.4,
-        enableSimilarityCorrection: data.hypaV3Settings?.enableSimilarityCorrection ?? false,
-        preserveOrphanedMemory: data.hypaV3Settings?.preserveOrphanedMemory ?? false,
-        processRegexScript: data.hypaV3Settings?.processRegexScript ?? false,
-        doNotSummarizeUserMessage: data.hypaV3Settings?.doNotSummarizeUserMessage ?? false
+    data.hypaV3Presets ??= [
+        createHypaV3Preset("Default", {
+            summarizationPrompt: data.supaMemoryPrompt ? data.supaMemoryPrompt : "",
+            ...data.hypaV3Settings
+        })
+    ]
+    if (data.hypaV3Presets.length > 0) {
+        data.hypaV3Presets = data.hypaV3Presets.map((preset, i) =>
+            createHypaV3Preset(
+                preset.name || `Preset ${i + 1}`,
+                preset.settings || {}
+            )
+        )
     }
+    data.hypaV3PresetId ??= 0
     data.returnCSSError ??= true
     data.useExperimentalGoogleTranslator ??= false
     if(data.antiClaudeOverload){ //migration
@@ -535,7 +544,7 @@ export function setDatabase(data:Database){
     data.hypaCustomSettings = {
         url: data.hypaCustomSettings?.url ?? "",
         key: data.hypaCustomSettings?.key ?? "",
-        model: data.hypaCustomSettings?.model ?? "",       
+        model: data.hypaCustomSettings?.model ?? ""     
     }
     data.doNotChangeSeperateModels ??= false
     data.modelTools ??= []
@@ -960,17 +969,10 @@ export interface Database{
     showPromptComparison:boolean
     checkCorruption:boolean
     hypaV3:boolean
-    hypaV3Settings: {
-        memoryTokensRatio: number
-        extraSummarizationRatio: number
-        maxChatsPerSummary: number
-        recentMemoryRatio: number
-        similarMemoryRatio: number
-        enableSimilarityCorrection: boolean
-        preserveOrphanedMemory: boolean
-        processRegexScript: boolean
-        doNotSummarizeUserMessage: boolean
-    }
+    hypaV3Settings: HypaV3Settings // legacy
+    hypaV3Presets: HypaV3Preset[]
+    hypaV3PresetId: number
+    showMenuHypaMemoryModal:boolean
     OaiCompAPIKeys: {[key:string]:string}
     inlayErrorResponse:boolean
     reasoningEffort:number
@@ -1026,6 +1028,8 @@ export interface Database{
     igpPrompt:string
     useTokenizerCaching:boolean
     showMenuHypaMemoryModal:boolean
+    promptInfoInsideChat:boolean
+    promptTextInfoInsideChat:boolean
 }
 
 interface SeparateParameters{
@@ -1165,7 +1169,7 @@ export interface character{
         },
         chunk_length:number,
         normalize:boolean,
-        
+
     }
     supaMemory?:boolean
     additionalAssets?:[string, string, string][]
@@ -1424,12 +1428,17 @@ export interface NAIImgConfig{
     InfoExtracted:number,
     RefStrength:number
     //add 4
+    cfg_rescale:number,
     autoSmea:boolean,
     use_coords:boolean,
     legacy_uc: boolean,
     v4_prompt:NAIImgConfigV4Prompt,
     v4_negative_prompt:NAIImgConfigV4NegativePrompt,
-
+    //add vibe
+    reference_image_multiple?:string[],
+    reference_strength_multiple?:number[],
+    vibe_data?:NAIVibeData,
+    vibe_model_selection?:string
 }
 
 //add 4
@@ -1458,6 +1467,35 @@ interface NAIImgConfigV4CharCaption{
         }[]
 }
 
+// NAI Vibe Data interfaces
+interface NAIVibeData {
+    identifier: string;
+    version: number;
+    type: string;
+    image: string;
+    id: string;
+    encodings: {
+        [key: string]: {
+            [key: string]: NAIVibeEncoding;
+        }
+    };
+    name: string;
+    thumbnail: string;
+    createdAt: number;
+    importInfo: {
+        model: string;
+        information_extracted: number;
+        strength: number;
+    };
+}
+
+interface NAIVibeEncoding {
+    encoding: string;
+    params: {
+        information_extracted: number;
+    };
+}
+
 interface ComfyConfig{
     workflow:string,
     posNodeID: string,
@@ -1504,6 +1542,7 @@ export interface Message{
     chatId?:string
     time?: number
     generationInfo?: MessageGenerationInfo
+    promptInfo?: MessagePresetInfo
     name?:string
     otherUser?:boolean
 }
@@ -1516,6 +1555,12 @@ export interface MessageGenerationInfo{
     maxContext?: number
 }
 
+export interface MessagePresetInfo{
+    promptName?: string,
+    promptToggles?: {key: string, value: string}[],
+    promptText?: OpenAIChat[],
+}
+
 interface AINsettings{
     top_p: number,
     rep_pen: number,
@@ -1882,6 +1927,7 @@ import type { Parameter } from '../process/request';
 import type { HypaModel } from '../process/memory/hypamemory';
 import type { SerializableHypaV3Data } from '../process/memory/hypav3';
 import { defaultHotkeys, type Hotkey } from '../defaulthotkeys';
+import type { OpenAIChat } from '../process/index.svelte';
 
 export async function downloadPreset(id:number, type:'json'|'risupreset'|'return' = 'json'){
     saveCurrentPreset()
@@ -2070,7 +2116,7 @@ export async function importPreset(f:{
             }
             else{
                 console.log("Prompt not found", prompt)
-            
+
             }
         }
         if(pre?.assistant_prefill){
diff --git a/src/ts/stores.svelte.ts b/src/ts/stores.svelte.ts
index ba714e6c..316ca189 100644
--- a/src/ts/stores.svelte.ts
+++ b/src/ts/stores.svelte.ts
@@ -50,6 +50,13 @@ export const alertStore = writable({
     type: 'none',
     msg: 'n',
 } as alertData)
+export const hypaV3ModalOpen = writable(false)
+export const hypaV3ProgressStore = writable({
+    open: false,
+    miniMsg: '',
+    msg: '',
+    subMsg: '',
+})
 export const selIdState = $state({
     selId: -1
 })