WIP: download and store web-based models instead of relying on kcpp

.gitignore

@@ -11,18 +11,3 @@ Thumbs.db
 # Yarn
 .yarn/
 .pnp.*
-
-t5xxl_fp8_e4m3fn.safetensors.aria2
-ae.safetensors
-clip_l.safetensors
-t5xxl_fp8_e4m3fn.safetensors
-flux1-kontext-dev-Q3_K_S.gguf
-gemma-3-4b-it.Q8_0.gguf
-.webui_secret_key
-chroma-unlocked-v29-Q3_K_L.gguf
-Qwen-Image-Edit-2509-Q4_K_S.gguf
-Qwen2.5-VL-7B-Instruct.mmproj-Q8_0.gguf
-Qwen2.5-VL-7B-Instruct.Q4_K_S.gguf
-qwen_image_vae.safetensors
-flux1-kontext-dev-Q4_K_S.gguf
-chroma-unlocked-v45-Q4_0.gguf

package.json

@@ -1,7 +1,7 @@
 {
   "name": "gerbil",
   "productName": "Gerbil",
-  "version": "1.9.0",
+  "version": "2.0.0",
   "description": "Run Large Language Models locally",
   "main": "out/main/index.js",
   "homepage": "./",
@@ -40,11 +40,11 @@
   "devDependencies": {
     "@eslint/js": "^9.39.1",
     "@types/node": "^24.10.1",
-    "@types/react": "^19.2.5",
+    "@types/react": "^19.2.6",
     "@types/react-dom": "^19.2.3",
     "@types/yauzl": "^2.10.3",
-    "@typescript-eslint/eslint-plugin": "^8.46.4",
+    "@typescript-eslint/eslint-plugin": "^8.47.0",
-    "@typescript-eslint/parser": "^8.46.4",
+    "@typescript-eslint/parser": "^8.47.0",
     "@vitejs/plugin-react": "^5.1.1",
     "cross-env": "^10.1.0",
     "electron": "^38.7.0",
@@ -67,7 +67,7 @@
   "dependencies": {
     "@codemirror/search": "^6.5.11",
     "@codemirror/theme-one-dark": "^6.1.3",
-    "@codemirror/view": "^6.38.7",
+    "@codemirror/view": "^6.38.8",
     "@fontsource/inter": "^5.2.8",
     "@huggingface/gguf": "^0.3.2",
     "@mantine/core": "^8.3.8",
@@ -75,7 +75,7 @@
     "@uiw/react-codemirror": "^4.25.3",
     "electron-updater": "^6.6.2",
     "execa": "^9.6.0",
-    "lucide-react": "^0.553.0",
+    "lucide-react": "^0.554.0",
     "react": "^19.2.0",
     "react-dom": "^19.2.0",
     "react-error-boundary": "^6.0.0",

src/components/screens/Launch/GeneralTab/index.tsx

@@ -44,6 +44,7 @@ export const GeneralTab = ({ configLoaded = true }: GeneralTabProps) => {
             onSelectFile={handleSelectModelFile}
             searchUrl="https://huggingface.co/models?pipeline_tag=text-generation&library=gguf&sort=trending"
             showAnalyze
+            paramType="model"
           />
 
           <div>

src/components/screens/Launch/ImageGenerationTab.tsx

@@ -77,15 +77,17 @@ export const ImageGenerationTab = () => {
         onSelectFile={handleSelectSdmodelFile}
         searchUrl="https://huggingface.co/models?pipeline_tag=text-to-image&library=gguf&sort=trending"
         showAnalyze
+        paramType="sdmodel"
       />
 
       <ModelFileField
-        label="T5-XXL File"
+        label="T5XXL File"
         value={sdt5xxl}
-        placeholder="Select a T5-XXL file or enter a direct URL"
+        placeholder="Select a T5-XXL encoder file or enter a direct URL"
-        tooltip="T5-XXL text encoder model for enhanced text understanding."
+        tooltip="T5-XXL text encoder model for advanced text understanding."
         onChange={handleSdt5xxlChange}
         onSelectFile={handleSelectSdt5xxlFile}
+        paramType="sdt5xxl"
       />
 
       <ModelFileField
@@ -95,6 +97,7 @@ export const ImageGenerationTab = () => {
         tooltip="CLIP-L text encoder model for text-image understanding."
         onChange={handleSdcliplChange}
         onSelectFile={handleSelectSdcliplFile}
+        paramType="sdclipl"
       />
 
       <ModelFileField
@@ -104,6 +107,7 @@ export const ImageGenerationTab = () => {
         tooltip="CLIP-G text encoder model for enhanced text-image understanding."
         onChange={handleSdclipgChange}
         onSelectFile={handleSelectSdclipgFile}
+        paramType="sdclipg"
       />
 
       <ModelFileField
@@ -113,6 +117,7 @@ export const ImageGenerationTab = () => {
         tooltip="PhotoMaker is a model that allows face cloning. Select a .safetensors PhotoMaker file to be loaded (SDXL only)."
         onChange={handleSdphotomakerChange}
         onSelectFile={handleSelectSdphotomakerFile}
+        paramType="sdphotomaker"
       />
 
       <ModelFileField
@@ -122,6 +127,7 @@ export const ImageGenerationTab = () => {
         tooltip="Variational Autoencoder model for improved image quality."
         onChange={handleSdvaeChange}
         onSelectFile={handleSelectSdvaeFile}
+        paramType="sdvae"
       />
 
       <ModelFileField
@@ -131,6 +137,7 @@ export const ImageGenerationTab = () => {
         tooltip="LoRa (Low-Rank Adaptation) file for customizing image generation. Select a .safetensors or .gguf LoRa file to be loaded. Should be unquantized."
         onChange={handleSdloraChange}
         onSelectFile={handleSelectSdloraFile}
+        paramType="sdlora"
       />
 
       <SelectWithTooltip

src/components/screens/Launch/ModelFileField.tsx

@@ -1,11 +1,19 @@
-import { Group, TextInput, ActionIcon, Tooltip, Button } from '@mantine/core';
+import { useEffect, useState } from 'react';
-import { useState } from 'react';
+import {
+  Group,
+  ActionIcon,
+  Tooltip,
+  Button,
+  Combobox,
+  useCombobox,
+  TextInput,
+} from '@mantine/core';
 import { File, Search, Info } from 'lucide-react';
 import { LabelWithTooltip } from '@/components/LabelWithTooltip';
 import { ModelAnalysisModal } from '@/components/screens/Launch/ModelAnalysisModal';
 import { getInputValidationState } from '@/utils/validation';
 import { logError } from '@/utils/logger';
-import type { ModelAnalysis } from '@/types';
+import type { ModelAnalysis, ModelParamType, CachedModel } from '@/types';
 
 interface ModelFileFieldProps {
   label: string;
@@ -16,6 +24,7 @@ interface ModelFileFieldProps {
   onSelectFile: () => void;
   searchUrl?: string;
   showAnalyze?: boolean;
+  paramType: ModelParamType;
 }
 
 export const ModelFileField = ({
@@ -27,6 +36,7 @@ export const ModelFileField = ({
   onSelectFile,
   searchUrl,
   showAnalyze = false,
+  paramType,
 }: ModelFileFieldProps) => {
   const validationState = getInputValidationState(value);
   const [analysisModalOpened, setAnalysisModalOpened] = useState(false);
@@ -35,6 +45,26 @@ export const ModelFileField = ({
   );
   const [analysisLoading, setAnalysisLoading] = useState(false);
   const [analysisError, setAnalysisError] = useState<string>();
+  const [cachedModels, setCachedModels] = useState<CachedModel[]>([]);
+  const combobox = useCombobox();
+
+  useEffect(() => {
+    (async () => {
+      try {
+        const models =
+          await window.electronAPI.kobold.getLocalModels(paramType);
+        setCachedModels(models);
+      } catch (error) {
+        logError('Failed to load cached models:', error as Error);
+      }
+    })();
+  }, [paramType]);
+
+  const options = cachedModels.map((model) => (
+    <Combobox.Option value={model.path} key={model.path}>
+      {model.author}/{model.model}
+    </Combobox.Option>
+  ));
 
   const getHelperText = () => {
     if (validationState === 'neutral') return undefined;
@@ -72,12 +102,37 @@ export const ModelFileField = ({
       <LabelWithTooltip label={label} tooltip={tooltip} />
       <Group gap="xs" align="flex-start">
         <div style={{ flex: 1 }}>
-          <TextInput
+          <Combobox
-            placeholder={placeholder}
+            store={combobox}
-            value={value}
+            onOptionSubmit={(val) => {
-            onChange={(event) => onChange(event.currentTarget.value)}
+              onChange(val);
-            error={validationState === 'invalid' ? getHelperText() : undefined}
+              combobox.closeDropdown();
-          />
+            }}
+          >
+            <Combobox.Target>
+              <TextInput
+                placeholder={placeholder}
+                value={value}
+                onChange={(event) => {
+                  onChange(event.currentTarget.value);
+                  combobox.openDropdown();
+                }}
+                onFocus={() => combobox.openDropdown()}
+                onBlur={() => combobox.closeDropdown()}
+                error={
+                  validationState === 'invalid' ? getHelperText() : undefined
+                }
+                rightSection={<Combobox.Chevron />}
+                rightSectionPointerEvents="none"
+              />
+            </Combobox.Target>
+
+            {options.length > 0 && (
+              <Combobox.Dropdown>
+                <Combobox.Options>{options}</Combobox.Options>
+              </Combobox.Dropdown>
+            )}
+          </Combobox>
         </div>
         <Button
           onClick={onSelectFile}

src/constants/index.ts

@@ -15,7 +15,7 @@ export const SERVER_READY_SIGNALS = {
 export const DEFAULT_CONTEXT_SIZE = 4096;
 
 export const DEFAULT_MODEL_URL =
-  'https://huggingface.co/MaziyarPanahi/gemma-3-4b-it-GGUF/resolve/main/gemma-3-4b-it.Q8_0.gguf?download=true';
+  'https://huggingface.co/MaziyarPanahi/gemma-3-4b-it-GGUF/resolve/main/gemma-3-4b-it.Q8_0.gguf';
 
 export const DEFAULT_AUTO_GPU_LAYERS = true;
 

src/main/ipc.ts

@@ -21,6 +21,7 @@ import {
   selectModelFile,
   selectInstallDirectory,
 } from '@/main/modules/koboldcpp/config';
+import { getLocalModelsForType } from '@/main/modules/koboldcpp/modelDownload';
 import { analyzeGGUFModel } from '@/main/modules/koboldcpp/analyze';
 import {
   get as getConfig,
@@ -156,6 +157,12 @@ export function setupIPCHandlers() {
     selectModelFile(title)
   );
 
+  ipcMain.handle('kobold:getLocalModels', (_, paramType: string) =>
+    getLocalModelsForType(
+      paramType as Parameters<typeof getLocalModelsForType>[0]
+    )
+  );
+
   ipcMain.handle('kobold:analyzeModel', async (_, filePath: string) =>
     analyzeGGUFModel(filePath)
   );

src/main/modules/koboldcpp/launcher/index.ts

@@ -15,13 +15,58 @@ import { startFrontend as startSillyTavernFrontend } from '@/main/modules/sillyt
 import { startFrontend as startOpenWebUIFrontend } from '@/main/modules/openwebui';
 import { patchKliteEmbd, patchKcppSduiEmbd, filterSpam } from './patches';
 import { startProxy, stopProxy } from '../proxy';
+import { resolveModelPath } from '../modelDownload';
 import type {
   FrontendPreference,
   ImageGenerationFrontendPreference,
+  ModelParamType,
 } from '@/types';
 
 let koboldProcess: ChildProcess | null = null;
 
+async function resolveModelPaths(args: string[]) {
+  const resolvedArgs: string[] = [];
+  const modelParams = [
+    '--model',
+    '--sdmodel',
+    '--sdt5xxl',
+    '--sdclipl',
+    '--sdclipg',
+    '--sdphotomaker',
+    '--sdvae',
+    '--sdlora',
+    '--mmproj',
+    '--whispermodel',
+    '--draftmodel',
+    '--ttsmodel',
+    '--ttswavtokenizer',
+    '--embeddingsmodel',
+  ];
+
+  for (let i = 0; i < args.length; i++) {
+    const arg = args[i];
+
+    if (modelParams.includes(arg) && i + 1 < args.length) {
+      resolvedArgs.push(arg);
+      const urlOrPath = args[i + 1];
+      try {
+        const paramType = arg.slice(2) as ModelParamType;
+        const resolvedPath = await resolveModelPath(urlOrPath, paramType);
+        resolvedArgs.push(resolvedPath);
+        i++;
+      } catch (error) {
+        logError(`Failed to resolve model path for ${arg}:`, error as Error);
+        resolvedArgs.push(urlOrPath);
+        i++;
+      }
+    } else {
+      resolvedArgs.push(arg);
+    }
+  }
+
+  return resolvedArgs;
+}
+
 export async function launchKoboldCpp(
   args: string[] = [],
   frontendPreference: FrontendPreference = 'koboldcpp',
@@ -64,7 +109,8 @@ export async function launchKoboldCpp(
       await patchKcppSduiEmbd(binaryDir);
     }
 
-    const finalArgs = [...args];
+    const resolvedArgs = await resolveModelPaths(args);
+    const finalArgs = [...resolvedArgs];
     const { host: koboldHost, port: koboldPort } = parseKoboldConfig(args);
 
     await startProxy(koboldHost, koboldPort);

src/main/modules/koboldcpp/modelDownload.ts

@@ -0,0 +1,291 @@
+import { join, basename, dirname } from 'path';
+import { mkdir, readdir, stat } from 'fs/promises';
+import { createWriteStream } from 'fs';
+import { get as httpGet } from 'http';
+import { get as httpsGet } from 'https';
+import { getInstallDir } from '@/main/modules/config';
+import { pathExists } from '@/utils/node/fs';
+import { logError } from '@/utils/node/logging';
+import { sendToRenderer } from '@/main/modules/window';
+import type { ModelParamType, CachedModel } from '@/types';
+
+interface DownloadProgress {
+  type: 'progress' | 'complete' | 'error';
+  percent?: number;
+  downloaded?: string;
+  total?: string;
+  speed?: string;
+  eta?: string;
+  error?: string;
+  localPath?: string;
+}
+
+function parseHuggingFaceUrl(url: string) {
+  const hfMatch = url.match(
+    /huggingface\.co\/([^/]+)\/([^/]+)\/(?:resolve|blob)\/[^/]+\/(.+)/
+  );
+
+  if (hfMatch) {
+    return {
+      author: hfMatch[1],
+      model: hfMatch[2],
+      filename: basename(hfMatch[3]),
+    };
+  }
+
+  return {
+    author: 'external',
+    model: 'models',
+    filename: basename(url.split('?')[0]),
+  };
+}
+
+export function getModelLocalPath(url: string, paramType: ModelParamType) {
+  const installDir = getInstallDir();
+  const { author, model, filename } = parseHuggingFaceUrl(url);
+
+  return join(installDir, 'models', paramType, author, model, filename);
+}
+
+function normalizeUrl(url: string) {
+  if (url.includes('huggingface.co') && url.includes('/blob/')) {
+    return url.replace('/blob/', '/resolve/');
+  }
+  return url;
+}
+
+async function downloadFile(
+  url: string,
+  outputPath: string,
+  onProgress: (progress: DownloadProgress) => void
+) {
+  const normalizedUrl = normalizeUrl(url);
+  const outputDir = dirname(outputPath);
+
+  await mkdir(outputDir, { recursive: true });
+
+  return new Promise<boolean>((resolve, reject) => {
+    const httpModule = normalizedUrl.startsWith('https') ? httpsGet : httpGet;
+
+    const handleRedirect = (requestUrl: string, redirectCount = 0): void => {
+      if (redirectCount > 10) {
+        reject(new Error('Too many redirects'));
+        return;
+      }
+
+      httpModule(requestUrl, (response) => {
+        if (
+          response.statusCode === 301 ||
+          response.statusCode === 302 ||
+          response.statusCode === 307 ||
+          response.statusCode === 308
+        ) {
+          const redirectUrl = response.headers.location;
+          if (redirectUrl) {
+            handleRedirect(redirectUrl, redirectCount + 1);
+          } else {
+            reject(new Error('Redirect without location header'));
+          }
+          return;
+        }
+
+        if (response.statusCode !== 200) {
+          reject(
+            new Error(`HTTP ${response.statusCode}: ${response.statusMessage}`)
+          );
+          return;
+        }
+
+        const totalBytes = parseInt(response.headers['content-length'] || '0');
+        let downloadedBytes = 0;
+        let lastReportTime = Date.now();
+        let lastReportedBytes = 0;
+
+        const fileStream = createWriteStream(outputPath);
+
+        response.on('data', (chunk: Buffer) => {
+          downloadedBytes += chunk.length;
+          fileStream.write(chunk);
+
+          const now = Date.now();
+          const timeDiff = (now - lastReportTime) / 1000;
+
+          if (timeDiff >= 0.5) {
+            const bytesDiff = downloadedBytes - lastReportedBytes;
+            const speedBytesPerSec = bytesDiff / timeDiff;
+            const percent = totalBytes
+              ? Math.round((downloadedBytes / totalBytes) * 100)
+              : 0;
+            const downloadedMB = (downloadedBytes / 1024 / 1024).toFixed(2);
+            const totalMB = (totalBytes / 1024 / 1024).toFixed(2);
+            const speedMBPerSec = (speedBytesPerSec / 1024 / 1024).toFixed(2);
+
+            const remainingBytes = totalBytes - downloadedBytes;
+            const etaSeconds = speedBytesPerSec
+              ? Math.round(remainingBytes / speedBytesPerSec)
+              : 0;
+            const etaMinutes = Math.floor(etaSeconds / 60);
+            const etaSecondsRemainder = etaSeconds % 60;
+            const etaStr =
+              etaMinutes > 0
+                ? `${etaMinutes}m${etaSecondsRemainder}s`
+                : `${etaSeconds}s`;
+
+            const progressMsg = totalBytes
+              ? `Downloaded ${downloadedMB}MB / ${totalMB}MB (${percent}%) - ${speedMBPerSec}MB/s - ETA: ${etaStr}`
+              : `Downloaded ${downloadedMB}MB - ${speedMBPerSec}MB/s`;
+
+            sendToRenderer('kobold-output', `\r${progressMsg}`);
+
+            onProgress({
+              type: 'progress',
+              percent,
+              downloaded: `${downloadedMB}MB`,
+              total: totalBytes ? `${totalMB}MB` : undefined,
+              speed: `${speedMBPerSec}MB/s`,
+              eta: totalBytes ? etaStr : undefined,
+            });
+
+            lastReportTime = now;
+            lastReportedBytes = downloadedBytes;
+          }
+        });
+
+        response.on('end', () => {
+          fileStream.end();
+          fileStream.on('finish', () => {
+            sendToRenderer('kobold-output', '\n');
+            resolve(true);
+          });
+        });
+
+        response.on('error', (err) => {
+          fileStream.close();
+          reject(err);
+        });
+
+        fileStream.on('error', (err) => {
+          reject(err);
+        });
+      }).on('error', (err) => {
+        reject(err);
+      });
+    };
+
+    handleRedirect(normalizedUrl);
+  });
+}
+
+function isValidModelUrl(url: string) {
+  if (!url || url.trim() === '') {
+    return false;
+  }
+
+  if (!url.startsWith('http://') && !url.startsWith('https://')) {
+    return false;
+  }
+
+  const validExtensions = ['.gguf', '.safetensors', '.bin', '.ggml'];
+  const urlPath = url.split('?')[0];
+  return validExtensions.some((ext) => urlPath.toLowerCase().endsWith(ext));
+}
+
+export async function resolveModelPath(
+  urlOrPath: string,
+  paramType: ModelParamType,
+  onProgress?: (progress: DownloadProgress) => void
+) {
+  if (!isValidModelUrl(urlOrPath)) {
+    return urlOrPath;
+  }
+
+  const localPath = getModelLocalPath(urlOrPath, paramType);
+
+  if (await pathExists(localPath)) {
+    sendToRenderer('kobold-output', `Using cached model at: ${localPath}\n`);
+    onProgress?.({
+      type: 'complete',
+      localPath,
+    });
+    return localPath;
+  }
+
+  sendToRenderer(
+    'kobold-output',
+    `Downloading model from ${urlOrPath} to ${localPath}...\n`
+  );
+
+  const progressCallback = onProgress || ((p: DownloadProgress) => p);
+
+  try {
+    await downloadFile(urlOrPath, localPath, progressCallback);
+
+    sendToRenderer(
+      'kobold-output',
+      `Model downloaded successfully to: ${localPath}\n\n`
+    );
+    progressCallback({
+      type: 'complete',
+      localPath,
+    });
+    return localPath;
+  } catch (error) {
+    progressCallback({
+      type: 'error',
+      error: `Download failed: ${error instanceof Error ? error.message : 'Unknown error'}`,
+    });
+    throw new Error(
+      `Failed to download model from ${urlOrPath}: ${error instanceof Error ? error.message : 'Unknown error'}`
+    );
+  }
+}
+
+export async function getLocalModelsForType(paramType: ModelParamType) {
+  const installDir = getInstallDir();
+  const modelsDir = join(installDir, 'models', paramType);
+
+  if (!(await pathExists(modelsDir))) {
+    return [];
+  }
+
+  const models: CachedModel[] = [];
+
+  try {
+    const authors = await readdir(modelsDir);
+
+    for (const author of authors) {
+      const authorPath = join(modelsDir, author);
+      const authorStat = await stat(authorPath);
+
+      if (authorStat.isDirectory()) {
+        const modelDirs = await readdir(authorPath);
+
+        for (const modelDir of modelDirs) {
+          const modelPath = join(authorPath, modelDir);
+          const modelStat = await stat(modelPath);
+
+          if (modelStat.isDirectory()) {
+            const files = await readdir(modelPath);
+
+            for (const file of files) {
+              const filePath = join(modelPath, file);
+              const fileStat = await stat(filePath);
+
+              if (fileStat.isFile()) {
+                models.push({
+                  path: filePath,
+                  author,
+                  model: modelDir,
+                });
+              }
+            }
+          }
+        }
+      }
+    }
+  } catch (error) {
+    logError('Error scanning local models:', error as Error);
+  }
+
+  return models;
+}

src/preload/index.ts

@@ -51,6 +51,8 @@ const koboldAPI: KoboldAPI = {
     ipcRenderer.invoke('kobold:parseConfigFile', filePath),
   selectModelFile: (title) =>
     ipcRenderer.invoke('kobold:selectModelFile', title),
+  getLocalModels: (paramType) =>
+    ipcRenderer.invoke('kobold:getLocalModels', paramType),
   analyzeModel: (filePath) =>
     ipcRenderer.invoke('kobold:analyzeModel', filePath),
   calculateOptimalLayers: (

src/types/electron.d.ts

@@ -10,6 +10,7 @@ import type {
   BackendSupport,
   Screen,
   ModelAnalysis,
+  CachedModel,
 } from '@/types';
 import type { MantineColorScheme } from '@mantine/core';
 import type {
@@ -156,6 +157,7 @@ export interface KoboldAPI {
   setSelectedConfig: (configName: string) => Promise<boolean>;
   parseConfigFile: (filePath: string) => Promise<KoboldConfig | null>;
   selectModelFile: (title?: string) => Promise<string | null>;
+  getLocalModels: (paramType: string) => Promise<CachedModel[]>;
   analyzeModel: (filePath: string) => Promise<ModelAnalysis>;
   calculateOptimalLayers: (
     modelPath: string,

src/types/index.d.ts

@@ -18,6 +18,28 @@ export type ImageGenerationFrontendPreference = 'match' | 'builtin';
 
 export type Screen = 'welcome' | 'download' | 'launch' | 'interface';
 
+export type ModelParamType =
+  | 'model'
+  | 'sdmodel'
+  | 'sdt5xxl'
+  | 'sdclipl'
+  | 'sdclipg'
+  | 'sdphotomaker'
+  | 'sdvae'
+  | 'sdlora'
+  | 'mmproj'
+  | 'whispermodel'
+  | 'draftmodel'
+  | 'ttsmodel'
+  | 'ttswavtokenizer'
+  | 'embeddingsmodel';
+
+export interface CachedModel {
+  path: string;
+  author: string;
+  model: string;
+}
+
 export interface GitHubAsset {
   name: string;
   browser_download_url: string;

src/utils/terminal.ts

@@ -1,27 +1,8 @@
 export const handleTerminalOutput = (prevContent: string, newData: string) => {
-  if (newData.includes('\r')) {
+  if (newData.startsWith('\r') && !newData.startsWith('\r\n')) {
-    const hasStandaloneCarriageReturns = /\r(?!\n)/g.test(newData);
+    const lines = prevContent.split('\n');
-
+    lines[lines.length - 1] = newData.slice(1);
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