Spaces:

multimodalart
/

ai-toolkit

Running on CPU Upgrade

App Files Files Community

multimodalart HF Staff commited on Sep 17

Commit

a52d5db

verified ·

1 Parent(s): 1125d73

Delete src

Browse files

This view is limited to 50 files because it contains too many changes. See raw diff

Files changed (50) hide show

src/app/api/auth/hf/callback/route.ts +0 -112
src/app/api/auth/hf/login/route.ts +0 -36
src/app/api/auth/hf/validate/route.ts +0 -22
src/app/api/auth/route.ts +0 -6
src/app/api/caption/get/route.ts +0 -46
src/app/api/datasets/create/route.tsx +0 -25
src/app/api/datasets/delete/route.tsx +0 -24
src/app/api/datasets/list/route.ts +0 -25
src/app/api/datasets/listImages/route.ts +0 -61
src/app/api/datasets/upload/route.ts +0 -57
src/app/api/files/[...filePath]/route.ts +0 -116
src/app/api/gpu/route.ts +0 -121
src/app/api/hf-hub/route.ts +0 -165
src/app/api/hf-jobs/route.ts +0 -761
src/app/api/img/[...imagePath]/route.ts +0 -78
src/app/api/img/caption/route.ts +0 -29
src/app/api/img/delete/route.ts +0 -34
src/app/api/img/upload/route.ts +0 -58
src/app/api/jobs/[jobID]/delete/route.ts +0 -32
src/app/api/jobs/[jobID]/files/route.ts +0 -48
src/app/api/jobs/[jobID]/log/route.ts +0 -35
src/app/api/jobs/[jobID]/samples/route.ts +0 -40
src/app/api/jobs/[jobID]/start/route.ts +0 -215
src/app/api/jobs/[jobID]/stop/route.ts +0 -23
src/app/api/jobs/route.ts +0 -67
src/app/api/settings/route.ts +0 -59
src/app/api/zip/route.ts +0 -78
src/app/apple-icon.png +0 -0
src/app/dashboard/page.tsx +0 -85
src/app/datasets/[datasetName]/page.tsx +0 -190
src/app/datasets/page.tsx +0 -217
src/app/favicon.ico +0 -0
src/app/globals.css +0 -72
src/app/icon.png +0 -0
src/app/icon.svg +0 -0
src/app/jobs/[jobID]/page.tsx +0 -147
src/app/jobs/new/AdvancedJob.tsx +0 -146
src/app/jobs/new/SimpleJob.tsx +0 -973
src/app/jobs/new/jobConfig.ts +0 -167
src/app/jobs/new/options.ts +0 -441
src/app/jobs/new/page.tsx +0 -306
src/app/jobs/page.tsx +0 -49
src/app/layout.tsx +0 -50
src/app/manifest.json +0 -21
src/app/page.tsx +0 -5
src/app/settings/page.tsx +0 -264
src/components/AddImagesModal.tsx +0 -152
src/components/AddSingleImageModal.tsx +0 -141
src/components/AuthWrapper.tsx +0 -166
src/components/Card.tsx +0 -15

src/app/api/auth/hf/callback/route.ts DELETED Viewed

@@ -1,112 +0,0 @@
-import { NextRequest, NextResponse } from 'next/server';
-import { cookies } from 'next/headers';
-const TOKEN_ENDPOINT = 'https://huggingface.co/oauth/token';
-const USERINFO_ENDPOINT = 'https://huggingface.co/oauth/userinfo';
-const STATE_COOKIE = 'hf_oauth_state';
-function htmlResponse(script: string) {
-  return new NextResponse(
-    `<!DOCTYPE html><html><body><script>${script}</script></body></html>`,
-    {
-      headers: { 'Content-Type': 'text/html; charset=utf-8' },
-    },
-  );
-}
-export async function GET(request: NextRequest) {
-  const clientId = process.env.HF_OAUTH_CLIENT_ID || process.env.NEXT_PUBLIC_HF_OAUTH_CLIENT_ID;
-  const clientSecret = process.env.HF_OAUTH_CLIENT_SECRET;
-  if (!clientId || !clientSecret) {
-    return NextResponse.json({ error: 'OAuth application is not configured' }, { status: 500 });
-  }
-  const { searchParams } = new URL(request.url);
-  const code = searchParams.get('code');
-  const incomingState = searchParams.get('state');
-  const cookieStore = cookies();
-  const storedState = cookieStore.get(STATE_COOKIE)?.value;
-  cookieStore.delete(STATE_COOKIE);
-  const origin = request.nextUrl.origin;
-  if (!code || !incomingState || !storedState || incomingState !== storedState) {
-    const script = `
-      window.opener && window.opener.postMessage({
-        type: 'HF_OAUTH_ERROR',
-        payload: { message: 'Invalid or expired OAuth state.' }
-      }, '${origin}');
-      window.close();
-    `;
-    return htmlResponse(script.trim());
-  }
-  const redirectUri = process.env.HF_OAUTH_REDIRECT_URI || process.env.NEXT_PUBLIC_HF_OAUTH_REDIRECT_URI || `${origin}/api/auth/hf/callback`;
-  try {
-    const tokenResponse = await fetch(TOKEN_ENDPOINT, {
-      method: 'POST',
-      headers: {
-        'Content-Type': 'application/x-www-form-urlencoded',
-      },
-      body: new URLSearchParams({
-        grant_type: 'authorization_code',
-        code,
-        redirect_uri: redirectUri,
-        client_id: clientId,
-        client_secret: clientSecret,
-      }),
-    });
-    if (!tokenResponse.ok) {
-      const errorPayload = await tokenResponse.json().catch(() => ({}));
-      throw new Error(errorPayload?.error_description || 'Failed to exchange code for token');
-    }
-    const tokenData = await tokenResponse.json();
-    const accessToken = tokenData?.access_token;
-    if (!accessToken) {
-      throw new Error('Access token missing in response');
-    }
-    const userResponse = await fetch(USERINFO_ENDPOINT, {
-      headers: {
-        Authorization: `Bearer ${accessToken}`,
-      },
-    });
-    if (!userResponse.ok) {
-      throw new Error('Failed to fetch user info');
-    }
-    const profile = await userResponse.json();
-    const namespace = profile?.preferred_username || profile?.name || 'user';
-    const script = `
-      window.opener && window.opener.postMessage({
-        type: 'HF_OAUTH_SUCCESS',
-        payload: {
-          token: ${JSON.stringify(accessToken)},
-          namespace: ${JSON.stringify(namespace)},
-        }
-      }, '${origin}');
-      window.close();
-    `;
-    return htmlResponse(script.trim());
-  } catch (error: any) {
-    const message = error?.message || 'OAuth flow failed';
-    const script = `
-      window.opener && window.opener.postMessage({
-        type: 'HF_OAUTH_ERROR',
-        payload: { message: ${JSON.stringify(message)} }
-      }, '${origin}');
-      window.close();
-    `;
-    return htmlResponse(script.trim());
-  }
-}

src/app/api/auth/hf/login/route.ts DELETED Viewed

@@ -1,36 +0,0 @@
-import { randomUUID } from 'crypto';
-import { NextRequest, NextResponse } from 'next/server';
-const HF_AUTHORIZE_URL = 'https://huggingface.co/oauth/authorize';
-const STATE_COOKIE = 'hf_oauth_state';
-export async function GET(request: NextRequest) {
-  const clientId = process.env.HF_OAUTH_CLIENT_ID || process.env.NEXT_PUBLIC_HF_OAUTH_CLIENT_ID;
-  if (!clientId) {
-    return NextResponse.json({ error: 'OAuth client ID not configured' }, { status: 500 });
-  }
-  const state = randomUUID();
-  const origin = request.nextUrl.origin;
-  const redirectUri = process.env.HF_OAUTH_REDIRECT_URI || process.env.NEXT_PUBLIC_HF_OAUTH_REDIRECT_URI || `${origin}/api/auth/hf/callback`;
-  const authorizeUrl = new URL(HF_AUTHORIZE_URL);
-  authorizeUrl.searchParams.set('response_type', 'code');
-  authorizeUrl.searchParams.set('client_id', clientId);
-  authorizeUrl.searchParams.set('redirect_uri', redirectUri);
-  authorizeUrl.searchParams.set('scope', 'openid profile read-repos');
-  authorizeUrl.searchParams.set('state', state);
-  const response = NextResponse.redirect(authorizeUrl.toString(), { status: 302 });
-  response.cookies.set({
-    name: STATE_COOKIE,
-    value: state,
-    httpOnly: true,
-    sameSite: 'lax',
-    secure: process.env.NODE_ENV === 'production',
-    maxAge: 60 * 5,
-    path: '/',
-  });
-  return response;
-}

src/app/api/auth/hf/validate/route.ts DELETED Viewed

@@ -1,22 +0,0 @@
-import { NextRequest, NextResponse } from 'next/server';
-import { whoAmI } from '@huggingface/hub';
-export async function POST(request: NextRequest) {
-  try {
-    const body = await request.json().catch(() => ({}));
-    const token = (body?.token || '').trim();
-    if (!token) {
-      return NextResponse.json({ error: 'Token is required' }, { status: 400 });
-    }
-    const info = await whoAmI({ accessToken: token });
-    return NextResponse.json({
-      name: info?.name || info?.username || 'user',
-      email: info?.email || null,
-      orgs: info?.orgs || [],
-    });
-  } catch (error: any) {
-    return NextResponse.json({ error: error?.message || 'Invalid token' }, { status: 401 });
-  }
-}

src/app/api/auth/route.ts DELETED Viewed

@@ -1,6 +0,0 @@
-import { NextResponse } from 'next/server';
-export async function GET() {
-  // if this gets hit, auth has already been verified
-  return NextResponse.json({ isAuthenticated: true });
-}

src/app/api/caption/get/route.ts DELETED Viewed

@@ -1,46 +0,0 @@
-/* eslint-disable */
-import { NextRequest, NextResponse } from 'next/server';
-import fs from 'fs';
-import path from 'path';
-import { getDatasetsRoot } from '@/server/settings';
-export async function POST(request: NextRequest) {
-  const body = await request.json();
-  const { imgPath } = body;
-  console.log('Received POST request for caption:', imgPath);
-  try {
-    // Decode the path
-    const filepath = imgPath;
-    console.log('Decoded image path:', filepath);
-    // caption name is the filepath without extension but with .txt
-    const captionPath = filepath.replace(/\.[^/.]+$/, '') + '.txt';
-    // Get allowed directories
-    const allowedDir = await getDatasetsRoot();
-    // Security check: Ensure path is in allowed directory
-    const isAllowed = filepath.startsWith(allowedDir) && !filepath.includes('..');
-    if (!isAllowed) {
-      console.warn(`Access denied: ${filepath} not in ${allowedDir}`);
-      return new NextResponse('Access denied', { status: 403 });
-    }
-    // Check if file exists
-    if (!fs.existsSync(captionPath)) {
-      // send back blank string if caption file does not exist
-      return new NextResponse('');
-    }
-    // Read caption file
-    const caption = fs.readFileSync(captionPath, 'utf-8');
-    // Return caption
-    return new NextResponse(caption);
-  } catch (error) {
-    console.error('Error getting caption:', error);
-    return new NextResponse('Error getting caption', { status: 500 });
-  }
-}

src/app/api/datasets/create/route.tsx DELETED Viewed

@@ -1,25 +0,0 @@
-import { NextResponse } from 'next/server';
-import fs from 'fs';
-import path from 'path';
-import { getDatasetsRoot } from '@/server/settings';
-export async function POST(request: Request) {
-  try {
-    const body = await request.json();
-    let { name } = body;
-    // clean name by making lower case,  removing special characters, and replacing spaces with underscores
-    name = name.toLowerCase().replace(/[^a-z0-9]+/g, '_');
-    let datasetsPath = await getDatasetsRoot();
-    let datasetPath = path.join(datasetsPath, name);
-    // if folder doesnt exist, create it
-    if (!fs.existsSync(datasetPath)) {
-      fs.mkdirSync(datasetPath);
-    }
-    return NextResponse.json({ success: true, name: name, path: datasetPath });
-  } catch (error) {
-    return NextResponse.json({ error: 'Failed to create dataset' }, { status: 500 });
-  }
-}

src/app/api/datasets/delete/route.tsx DELETED Viewed

@@ -1,24 +0,0 @@
-import { NextResponse } from 'next/server';
-import fs from 'fs';
-import path from 'path';
-import { getDatasetsRoot } from '@/server/settings';
-export async function POST(request: Request) {
-  try {
-    const body = await request.json();
-    const { name } = body;
-    let datasetsPath = await getDatasetsRoot();
-    let datasetPath = path.join(datasetsPath, name);
-    // if folder doesnt exist, ignore
-    if (!fs.existsSync(datasetPath)) {
-      return NextResponse.json({ success: true });
-    }
-    // delete it and return success
-    fs.rmdirSync(datasetPath, { recursive: true });
-    return NextResponse.json({ success: true });
-  } catch (error) {
-    return NextResponse.json({ error: 'Failed to create dataset' }, { status: 500 });
-  }
-}

src/app/api/datasets/list/route.ts DELETED Viewed

@@ -1,25 +0,0 @@
-import { NextResponse } from 'next/server';
-import fs from 'fs';
-import { getDatasetsRoot } from '@/server/settings';
-export async function GET() {
-  try {
-    let datasetsPath = await getDatasetsRoot();
-    // if folder doesnt exist, create it
-    if (!fs.existsSync(datasetsPath)) {
-      fs.mkdirSync(datasetsPath);
-    }
-    // find all the folders in the datasets folder
-    let folders = fs
-      .readdirSync(datasetsPath, { withFileTypes: true })
-      .filter(dirent => dirent.isDirectory())
-      .filter(dirent => !dirent.name.startsWith('.'))
-      .map(dirent => dirent.name);
-    return NextResponse.json(folders);
-  } catch (error) {
-    return NextResponse.json({ error: 'Failed to fetch datasets' }, { status: 500 });
-  }
-}

src/app/api/datasets/listImages/route.ts DELETED Viewed

@@ -1,61 +0,0 @@
-import { NextResponse } from 'next/server';
-import fs from 'fs';
-import path from 'path';
-import { getDatasetsRoot } from '@/server/settings';
-export async function POST(request: Request) {
-  const datasetsPath = await getDatasetsRoot();
-  const body = await request.json();
-  const { datasetName } = body;
-  const datasetFolder = path.join(datasetsPath, datasetName);
-  try {
-    // Check if folder exists
-    if (!fs.existsSync(datasetFolder)) {
-      return NextResponse.json({ error: `Folder '${datasetName}' not found` }, { status: 404 });
-    }
-    // Find all images recursively
-    const imageFiles = findImagesRecursively(datasetFolder);
-    // Format response
-    const result = imageFiles.map(imgPath => ({
-      img_path: imgPath,
-    }));
-    return NextResponse.json({ images: result });
-  } catch (error) {
-    console.error('Error finding images:', error);
-    return NextResponse.json({ error: 'Failed to process request' }, { status: 500 });
-  }
-}
-/**
- * Recursively finds all image files in a directory and its subdirectories
- * @param dir Directory to search
- * @returns Array of absolute paths to image files
- */
-function findImagesRecursively(dir: string): string[] {
-  const imageExtensions = ['.png', '.jpg', '.jpeg', '.webp', '.mp4', '.avi', '.mov', '.mkv', '.wmv', '.m4v', '.flv'];
-  let results: string[] = [];
-  const items = fs.readdirSync(dir);
-  for (const item of items) {
-    const itemPath = path.join(dir, item);
-    const stat = fs.statSync(itemPath);
-    if (stat.isDirectory() && item !== '_controls' && !item.startsWith('.')) {
-      // If it's a directory, recursively search it
-      results = results.concat(findImagesRecursively(itemPath));
-    } else {
-      // If it's a file, check if it's an image
-      const ext = path.extname(itemPath).toLowerCase();
-      if (imageExtensions.includes(ext)) {
-        results.push(itemPath);
-      }
-    }
-  }
-  return results;
-}

src/app/api/datasets/upload/route.ts DELETED Viewed

@@ -1,57 +0,0 @@
-// src/app/api/datasets/upload/route.ts
-import { NextRequest, NextResponse } from 'next/server';
-import { writeFile, mkdir } from 'fs/promises';
-import { join } from 'path';
-import { getDatasetsRoot } from '@/server/settings';
-export async function POST(request: NextRequest) {
-  try {
-    const datasetsPath = await getDatasetsRoot();
-    if (!datasetsPath) {
-      return NextResponse.json({ error: 'Datasets path not found' }, { status: 500 });
-    }
-    const formData = await request.formData();
-    const files = formData.getAll('files');
-    const datasetName = formData.get('datasetName') as string;
-    if (!files || files.length === 0) {
-      return NextResponse.json({ error: 'No files provided' }, { status: 400 });
-    }
-    // Create upload directory if it doesn't exist
-    const uploadDir = join(datasetsPath, datasetName);
-    await mkdir(uploadDir, { recursive: true });
-    const savedFiles: string[] = [];
-    // Process files sequentially to avoid overwhelming the system
-    for (let i = 0; i < files.length; i++) {
-      const file = files[i] as any;
-      const bytes = await file.arrayBuffer();
-      const buffer = Buffer.from(bytes);
-      // Clean filename and ensure it's unique
-      const fileName = file.name.replace(/[^a-zA-Z0-9.-]/g, '_');
-      const filePath = join(uploadDir, fileName);
-      await writeFile(filePath, buffer);
-      savedFiles.push(fileName);
-    }
-    return NextResponse.json({
-      message: 'Files uploaded successfully',
-      files: savedFiles,
-    });
-  } catch (error) {
-    console.error('Upload error:', error);
-    return NextResponse.json({ error: 'Error uploading files' }, { status: 500 });
-  }
-}
-// Increase payload size limit (default is 4mb)
-export const config = {
-  api: {
-    bodyParser: false,
-    responseLimit: '50mb',
-  },
-};

src/app/api/files/[...filePath]/route.ts DELETED Viewed

@@ -1,116 +0,0 @@
-/* eslint-disable */
-import { NextRequest, NextResponse } from 'next/server';
-import fs from 'fs';
-import path from 'path';
-import { getDatasetsRoot, getTrainingFolder } from '@/server/settings';
-export async function GET(request: NextRequest, { params }: { params: { filePath: string } }) {
-  const { filePath } = await params;
-  try {
-    // Decode the path
-    const decodedFilePath = decodeURIComponent(filePath);
-    // Get allowed directories
-    const datasetRoot = await getDatasetsRoot();
-    const trainingRoot = await getTrainingFolder();
-    const allowedDirs = [datasetRoot, trainingRoot];
-    // Security check: Ensure path is in allowed directory
-    const isAllowed =
-      allowedDirs.some(allowedDir => decodedFilePath.startsWith(allowedDir)) && !decodedFilePath.includes('..');
-    if (!isAllowed) {
-      console.warn(`Access denied: ${decodedFilePath} not in ${allowedDirs.join(', ')}`);
-      return new NextResponse('Access denied', { status: 403 });
-    }
-    // Check if file exists
-    if (!fs.existsSync(decodedFilePath)) {
-      console.warn(`File not found: ${decodedFilePath}`);
-      return new NextResponse('File not found', { status: 404 });
-    }
-    // Get file info
-    const stat = fs.statSync(decodedFilePath);
-    if (!stat.isFile()) {
-      return new NextResponse('Not a file', { status: 400 });
-    }
-    // Get filename for Content-Disposition
-    const filename = path.basename(decodedFilePath);
-    // Determine content type
-    const ext = path.extname(decodedFilePath).toLowerCase();
-    const contentTypeMap: { [key: string]: string } = {
-      '.jpg': 'image/jpeg',
-      '.jpeg': 'image/jpeg',
-      '.png': 'image/png',
-      '.gif': 'image/gif',
-      '.webp': 'image/webp',
-      '.svg': 'image/svg+xml',
-      '.bmp': 'image/bmp',
-      '.safetensors': 'application/octet-stream',
-      '.zip': 'application/zip',
-      // Videos
-      '.mp4': 'video/mp4',
-      '.avi': 'video/x-msvideo',
-      '.mov': 'video/quicktime',
-      '.mkv': 'video/x-matroska',
-      '.wmv': 'video/x-ms-wmv',
-      '.m4v': 'video/x-m4v',
-      '.flv': 'video/x-flv'
-    };
-    const contentType = contentTypeMap[ext] || 'application/octet-stream';
-    // Get range header for partial content support
-    const range = request.headers.get('range');
-    // Common headers for better download handling
-    const commonHeaders = {
-      'Content-Type': contentType,
-      'Accept-Ranges': 'bytes',
-      'Cache-Control': 'public, max-age=86400',
-      'Content-Disposition': `attachment; filename="${encodeURIComponent(filename)}"`,
-      'X-Content-Type-Options': 'nosniff',
-    };
-    if (range) {
-      // Parse range header
-      const parts = range.replace(/bytes=/, '').split('-');
-      const start = parseInt(parts[0], 10);
-      const end = parts[1] ? parseInt(parts[1], 10) : Math.min(start + 10 * 1024 * 1024, stat.size - 1); // 10MB chunks
-      const chunkSize = end - start + 1;
-      const fileStream = fs.createReadStream(decodedFilePath, {
-        start,
-        end,
-        highWaterMark: 64 * 1024, // 64KB buffer
-      });
-      return new NextResponse(fileStream as any, {
-        status: 206,
-        headers: {
-          ...commonHeaders,
-          'Content-Range': `bytes ${start}-${end}/${stat.size}`,
-          'Content-Length': String(chunkSize),
-        },
-      });
-    } else {
-      // For full file download, read directly without streaming wrapper
-      const fileStream = fs.createReadStream(decodedFilePath, {
-        highWaterMark: 64 * 1024, // 64KB buffer
-      });
-      return new NextResponse(fileStream as any, {
-        headers: {
-          ...commonHeaders,
-          'Content-Length': String(stat.size),
-        },
-      });
-    }
-  } catch (error) {
-    console.error('Error serving file:', error);
-    return new NextResponse('Internal Server Error', { status: 500 });
-  }
-}

src/app/api/gpu/route.ts DELETED Viewed

@@ -1,121 +0,0 @@
-import { NextResponse } from 'next/server';
-import { exec } from 'child_process';
-import { promisify } from 'util';
-import os from 'os';
-const execAsync = promisify(exec);
-export async function GET() {
-  try {
-    // Get platform
-    const platform = os.platform();
-    const isWindows = platform === 'win32';
-    // Check if nvidia-smi is available
-    const hasNvidiaSmi = await checkNvidiaSmi(isWindows);
-    if (!hasNvidiaSmi) {
-      return NextResponse.json({
-        hasNvidiaSmi: false,
-        gpus: [],
-        error: 'nvidia-smi not found or not accessible',
-      });
-    }
-    // Get GPU stats
-    const gpuStats = await getGpuStats(isWindows);
-    return NextResponse.json({
-      hasNvidiaSmi: true,
-      gpus: gpuStats,
-    });
-  } catch (error) {
-    console.error('Error fetching NVIDIA GPU stats:', error);
-    return NextResponse.json(
-      {
-        hasNvidiaSmi: false,
-        gpus: [],
-        error: `Failed to fetch GPU stats: ${error instanceof Error ? error.message : String(error)}`,
-      },
-      { status: 500 },
-    );
-  }
-}
-async function checkNvidiaSmi(isWindows: boolean): Promise<boolean> {
-  try {
-    if (isWindows) {
-      // Check if nvidia-smi is available on Windows
-      // It's typically located in C:\Program Files\NVIDIA Corporation\NVSMI\nvidia-smi.exe
-      // but we'll just try to run it directly as it may be in PATH
-      await execAsync('nvidia-smi -L');
-    } else {
-      // Linux/macOS check
-      await execAsync('which nvidia-smi');
-    }
-    return true;
-  } catch (error) {
-    return false;
-  }
-}
-async function getGpuStats(isWindows: boolean) {
-  // Command is the same for both platforms, but the path might be different
-  const command =
-    'nvidia-smi --query-gpu=index,name,driver_version,temperature.gpu,utilization.gpu,utilization.memory,memory.total,memory.free,memory.used,power.draw,power.limit,clocks.current.graphics,clocks.current.memory,fan.speed --format=csv,noheader,nounits';
-  // Execute command
-  const { stdout } = await execAsync(command);
-  // Parse CSV output
-  const gpus = stdout
-    .trim()
-    .split('\n')
-    .map(line => {
-      const [
-        index,
-        name,
-        driverVersion,
-        temperature,
-        gpuUtil,
-        memoryUtil,
-        memoryTotal,
-        memoryFree,
-        memoryUsed,
-        powerDraw,
-        powerLimit,
-        clockGraphics,
-        clockMemory,
-        fanSpeed,
-      ] = line.split(', ').map(item => item.trim());
-      return {
-        index: parseInt(index),
-        name,
-        driverVersion,
-        temperature: parseInt(temperature),
-        utilization: {
-          gpu: parseInt(gpuUtil),
-          memory: parseInt(memoryUtil),
-        },
-        memory: {
-          total: parseInt(memoryTotal),
-          free: parseInt(memoryFree),
-          used: parseInt(memoryUsed),
-        },
-        power: {
-          draw: parseFloat(powerDraw),
-          limit: parseFloat(powerLimit),
-        },
-        clocks: {
-          graphics: parseInt(clockGraphics),
-          memory: parseInt(clockMemory),
-        },
-        fan: {
-          speed: parseInt(fanSpeed) || 0, // Some GPUs might not report fan speed, default to 0
-        },
-      };
-    });
-  return gpus;
-}

src/app/api/hf-hub/route.ts DELETED Viewed

@@ -1,165 +0,0 @@
-import { NextRequest, NextResponse } from 'next/server';
-import { whoAmI, createRepo, uploadFiles, datasetInfo } from '@huggingface/hub';
-import { readdir, stat } from 'fs/promises';
-import path from 'path';
-export async function POST(request: NextRequest) {
-  try {
-    const body = await request.json();
-    const { action, token, namespace, datasetName, datasetPath, datasetId } = body;
-    if (!token) {
-      return NextResponse.json({ error: 'HF token is required' }, { status: 400 });
-    }
-    switch (action) {
-      case 'whoami':
-        try {
-          const user = await whoAmI({ accessToken: token });
-          return NextResponse.json({ user });
-        } catch (error) {
-          return NextResponse.json({ error: 'Invalid token or network error' }, { status: 401 });
-        }
-      case 'createDataset':
-        try {
-          if (!namespace || !datasetName) {
-            return NextResponse.json({ error: 'Namespace and dataset name required' }, { status: 400 });
-          }
-          const repoId = `datasets/${namespace}/${datasetName}`;
-          // Create repository
-          await createRepo({
-            repo: repoId,
-            accessToken: token,
-            private: false,
-          });
-          return NextResponse.json({ success: true, repoId });
-        } catch (error: any) {
-          if (error.message?.includes('already exists')) {
-            return NextResponse.json({ success: true, repoId: `${namespace}/${datasetName}`, exists: true });
-          }
-          return NextResponse.json({ error: error.message || 'Failed to create dataset' }, { status: 500 });
-        }
-      case 'uploadDataset':
-        try {
-          if (!namespace || !datasetName || !datasetPath) {
-            return NextResponse.json({ error: 'Missing required parameters' }, { status: 400 });
-          }
-          const repoId = `datasets/${namespace}/${datasetName}`;
-          // Check if directory exists
-          try {
-            await stat(datasetPath);
-          } catch {
-            return NextResponse.json({ error: 'Dataset path does not exist' }, { status: 400 });
-          }
-          // Read files from directory and upload them
-          const files = await readdir(datasetPath);
-          const filesToUpload = [];
-          for (const fileName of files) {
-            const filePath = path.join(datasetPath, fileName);
-            const fileStats = await stat(filePath);
-            if (fileStats.isFile()) {
-              filesToUpload.push({
-                path: fileName,
-                content: new URL(`file://${filePath}`)
-              });
-            }
-          }
-          if (filesToUpload.length > 0) {
-            await uploadFiles({
-              repo: repoId,
-              accessToken: token,
-              files: filesToUpload,
-            });
-          }
-          return NextResponse.json({ success: true, repoId });
-        } catch (error: any) {
-          console.error('Upload error:', error);
-          return NextResponse.json({ error: error.message || 'Failed to upload dataset' }, { status: 500 });
-        }
-      case 'listFiles':
-        try {
-          if (!datasetPath) {
-            return NextResponse.json({ error: 'Dataset path required' }, { status: 400 });
-          }
-          const files = await readdir(datasetPath, { withFileTypes: true });
-          const imageExtensions = ['.jpg', '.jpeg', '.png', '.webp', '.bmp'];
-          const imageFiles = files
-            .filter(file => file.isFile())
-            .filter(file => imageExtensions.some(ext => file.name.toLowerCase().endsWith(ext)))
-            .map(file => ({
-              name: file.name,
-              path: path.join(datasetPath, file.name),
-            }));
-          const captionFiles = files
-            .filter(file => file.isFile())
-            .filter(file => file.name.endsWith('.txt'))
-            .map(file => ({
-              name: file.name,
-              path: path.join(datasetPath, file.name),
-            }));
-          return NextResponse.json({
-            images: imageFiles,
-            captions: captionFiles,
-            total: imageFiles.length
-          });
-        } catch (error: any) {
-          return NextResponse.json({ error: error.message || 'Failed to list files' }, { status: 500 });
-        }
-      case 'validateDataset':
-        try {
-          if (!datasetId) {
-            return NextResponse.json({ error: 'Dataset ID required' }, { status: 400 });
-          }
-          // Try to get dataset info to validate it exists and is accessible
-          const dataset = await datasetInfo({
-            name: datasetId,
-            accessToken: token,
-          });
-          return NextResponse.json({
-            exists: true,
-            dataset: {
-              id: dataset.id,
-              author: dataset.author,
-              downloads: dataset.downloads,
-              likes: dataset.likes,
-              private: dataset.private,
-            }
-          });
-        } catch (error: any) {
-          if (error.message?.includes('404') || error.message?.includes('not found')) {
-            return NextResponse.json({ exists: false }, { status: 200 });
-          }
-          if (error.message?.includes('401') || error.message?.includes('403')) {
-            return NextResponse.json({ error: 'Dataset not accessible with current token' }, { status: 403 });
-          }
-          return NextResponse.json({ error: error.message || 'Failed to validate dataset' }, { status: 500 });
-        }
-      default:
-        return NextResponse.json({ error: 'Invalid action' }, { status: 400 });
-    }
-  } catch (error: any) {
-    console.error('HF Hub API error:', error);
-    return NextResponse.json({ error: error.message || 'Internal server error' }, { status: 500 });
-  }
-}

src/app/api/hf-jobs/route.ts DELETED Viewed

@@ -1,761 +0,0 @@
-import { NextRequest, NextResponse } from 'next/server';
-import { spawn } from 'child_process';
-import { writeFile } from 'fs/promises';
-import path from 'path';
-import { tmpdir } from 'os';
-export async function POST(request: NextRequest) {
-  try {
-    const body = await request.json();
-    const { action, token, hardware, namespace, jobConfig, datasetRepo } = body;
-    switch (action) {
-      case 'checkStatus':
-        try {
-          if (!token || !jobConfig?.hf_job_id) {
-            return NextResponse.json({ error: 'Token and job ID required' }, { status: 400 });
-          }
-          const jobStatus = await checkHFJobStatus(token, jobConfig.hf_job_id);
-          return NextResponse.json({ status: jobStatus });
-        } catch (error: any) {
-          console.error('Job status check error:', error);
-          return NextResponse.json({ error: error.message }, { status: 500 });
-        }
-      case 'generateScript':
-        try {
-          const uvScript = generateUVScript({
-            jobConfig,
-            datasetRepo,
-            namespace,
-            token: token || 'YOUR_HF_TOKEN',
-          });
-          return NextResponse.json({
-            script: uvScript,
-            filename: `train_${jobConfig.config.name.replace(/[^a-zA-Z0-9]/g, '_')}.py`
-          });
-        } catch (error: any) {
-          return NextResponse.json({ error: error.message }, { status: 500 });
-        }
-      case 'submitJob':
-        try {
-          if (!token || !hardware) {
-            return NextResponse.json({ error: 'Token and hardware required' }, { status: 400 });
-          }
-          // Generate UV script
-          const uvScript = generateUVScript({
-            jobConfig,
-            datasetRepo,
-            namespace,
-            token,
-          });
-          // Write script to temporary file
-          const scriptPath = path.join(tmpdir(), `train_${Date.now()}.py`);
-          await writeFile(scriptPath, uvScript);
-          // Submit HF job using uv run
-          const jobId = await submitHFJobUV(token, hardware, scriptPath);
-          return NextResponse.json({
-            success: true,
-            jobId,
-            message: `Job submitted successfully with ID: ${jobId}`
-          });
-        } catch (error: any) {
-          console.error('Job submission error:', error);
-          return NextResponse.json({ error: error.message }, { status: 500 });
-        }
-      default:
-        return NextResponse.json({ error: 'Invalid action' }, { status: 400 });
-    }
-  } catch (error: any) {
-    console.error('HF Jobs API error:', error);
-    return NextResponse.json({ error: error.message }, { status: 500 });
-  }
-}
-function generateUVScript({ jobConfig, datasetRepo, namespace, token }: {
-  jobConfig: any;
-  datasetRepo: string;
-  namespace: string;
-  token: string;
-}) {
-  const config = jobConfig.config;
-  const process = config.process[0];
-  return `# /// script
-# dependencies = [
-#     "torch>=2.0.0",
-#     "torchvision",
-#     "torchao==0.10.0",
-#     "safetensors",
-#     "diffusers @ git+https://github.com/huggingface/diffusers@7a2b78bf0f788d311cc96b61e660a8e13e3b1e63",
-#     "transformers==4.52.4",
-#     "lycoris-lora==1.8.3",
-#     "flatten_json",
-#     "pyyaml",
-#     "oyaml",
-#     "tensorboard",
-#     "kornia",
-#     "invisible-watermark",
-#     "einops",
-#     "accelerate",
-#     "toml",
-#     "albumentations==1.4.15",
-#     "albucore==0.0.16",
-#     "pydantic",
-#     "omegaconf",
-#     "k-diffusion",
-#     "open_clip_torch",
-#     "timm",
-#     "prodigyopt",
-#     "controlnet_aux==0.0.10",
-#     "python-dotenv",
-#     "bitsandbytes",
-#     "hf_transfer",
-#     "lpips",
-#     "pytorch_fid",
-#     "optimum-quanto==0.2.4",
-#     "sentencepiece",
-#     "huggingface_hub",
-#     "peft",
-#     "python-slugify",
-#     "opencv-python-headless",
-#     "pytorch-wavelets==1.3.0",
-#     "matplotlib==3.10.1",
-#     "setuptools==69.5.1",
-#     "datasets==4.0.0",
-#     "pyarrow==20.0.0",
-#     "pillow",
-#     "ftfy",
-# ]
-# ///
-import os
-import sys
-import subprocess
-import argparse
-import oyaml as yaml
-from datasets import load_dataset
-from huggingface_hub import HfApi, create_repo, upload_folder, snapshot_download
-import tempfile
-import shutil
-import glob
-from PIL import Image
-def setup_ai_toolkit():
-    """Clone and setup ai-toolkit repository"""
-    repo_dir = "ai-toolkit"
-    if not os.path.exists(repo_dir):
-        print("Cloning ai-toolkit repository...")
-        subprocess.run(
-            ["git", "clone", "https://github.com/ostris/ai-toolkit.git", repo_dir],
-            check=True
-        )
-    sys.path.insert(0, os.path.abspath(repo_dir))
-    return repo_dir
-def download_dataset(dataset_repo: str, local_path: str):
-    """Download dataset from HF Hub as files"""
-    print(f"Downloading dataset from {dataset_repo}...")
-    # Create local dataset directory
-    os.makedirs(local_path, exist_ok=True)
-    # Use snapshot_download to get the dataset files directly
-    from huggingface_hub import snapshot_download
-    try:
-        # First try to download as a structured dataset
-        dataset = load_dataset(dataset_repo, split="train")
-        # Download images and captions from structured dataset
-        for i, item in enumerate(dataset):
-            # Save image
-            if "image" in item:
-                image_path = os.path.join(local_path, f"image_{i:06d}.jpg")
-                image = item["image"]
-                # Convert RGBA to RGB if necessary (for JPEG compatibility)
-                if image.mode == 'RGBA':
-                    # Create a white background and paste the RGBA image on it
-                    background = Image.new('RGB', image.size, (255, 255, 255))
-                    background.paste(image, mask=image.split()[-1])  # Use alpha channel as mask
-                    image = background
-                elif image.mode not in ['RGB', 'L']:
-                    # Convert any other mode to RGB
-                    image = image.convert('RGB')
-                image.save(image_path, 'JPEG')
-            # Save caption
-            if "text" in item:
-                caption_path = os.path.join(local_path, f"image_{i:06d}.txt")
-                with open(caption_path, "w", encoding="utf-8") as f:
-                    f.write(item["text"])
-        print(f"Downloaded {len(dataset)} items to {local_path}")
-    except Exception as e:
-        print(f"Failed to load as structured dataset: {e}")
-        print("Attempting to download raw files...")
-        # Download the dataset repository as files
-        temp_repo_path = snapshot_download(repo_id=dataset_repo, repo_type="dataset")
-        # Copy all image and text files to the local path
-        import glob
-        import shutil
-        print(f"Downloaded repo to: {temp_repo_path}")
-        print(f"Contents: {os.listdir(temp_repo_path)}")
-        # Find all image files
-        image_extensions = ['*.jpg', '*.jpeg', '*.png', '*.webp', '*.bmp', '*.JPG', '*.JPEG', '*.PNG']
-        image_files = []
-        for ext in image_extensions:
-            pattern = os.path.join(temp_repo_path, "**", ext)
-            found_files = glob.glob(pattern, recursive=True)
-            image_files.extend(found_files)
-            print(f"Pattern {pattern} found {len(found_files)} files")
-        # Find all text files
-        text_files = glob.glob(os.path.join(temp_repo_path, "**", "*.txt"), recursive=True)
-        print(f"Found {len(image_files)} image files and {len(text_files)} text files")
-        # Copy image files
-        for i, img_file in enumerate(image_files):
-            dest_path = os.path.join(local_path, f"image_{i:06d}.jpg")
-            # Load and convert image if needed
-            try:
-                with Image.open(img_file) as image:
-                    if image.mode == 'RGBA':
-                        background = Image.new('RGB', image.size, (255, 255, 255))
-                        background.paste(image, mask=image.split()[-1])
-                        image = background
-                    elif image.mode not in ['RGB', 'L']:
-                        image = image.convert('RGB')
-                    image.save(dest_path, 'JPEG')
-            except Exception as img_error:
-                print(f"Error processing image {img_file}: {img_error}")
-                continue
-        # Copy text files (captions)
-        for i, txt_file in enumerate(text_files[:len(image_files)]):  # Match number of images
-            dest_path = os.path.join(local_path, f"image_{i:06d}.txt")
-            try:
-                shutil.copy2(txt_file, dest_path)
-            except Exception as txt_error:
-                print(f"Error copying text file {txt_file}: {txt_error}")
-                continue
-        print(f"Downloaded {len(image_files)} images and {len(text_files)} captions to {local_path}")
-def create_config(dataset_path: str, output_path: str):
-    """Create training configuration"""
-    import json
-    # Load config from JSON string and fix boolean/null values for Python
-    config_str = """${JSON.stringify(jobConfig, null, 2)}"""
-    config_str = config_str.replace('true', 'True').replace('false', 'False').replace('null', 'None')
-    config = eval(config_str)
-    # Update paths for cloud environment
-    config["config"]["process"][0]["datasets"][0]["folder_path"] = dataset_path
-    config["config"]["process"][0]["training_folder"] = output_path
-    # Remove sqlite_db_path as it's not needed for cloud training
-    if "sqlite_db_path" in config["config"]["process"][0]:
-        del config["config"]["process"][0]["sqlite_db_path"]
-    # Also change trainer type from ui_trainer to standard trainer to avoid UI dependencies
-    if config["config"]["process"][0]["type"] == "ui_trainer":
-        config["config"]["process"][0]["type"] = "sd_trainer"
-    return config
-def upload_results(output_path: str, model_name: str, namespace: str, token: str, config: dict):
-    """Upload trained model to HF Hub with README generation and proper file organization"""
-    import tempfile
-    import shutil
-    import glob
-    import re
-    import yaml
-    from datetime import datetime
-    from huggingface_hub import create_repo, upload_file, HfApi
-    try:
-        repo_id = f"{namespace}/{model_name}"
-        # Create repository
-        create_repo(repo_id=repo_id, token=token, exist_ok=True)
-        print(f"Uploading model to {repo_id}...")
-        # Create temporary directory for organized upload
-        with tempfile.TemporaryDirectory() as temp_upload_dir:
-            api = HfApi()
-            # 1. Find and upload model files to root directory
-            safetensors_files = glob.glob(os.path.join(output_path, "**", "*.safetensors"), recursive=True)
-            json_files = glob.glob(os.path.join(output_path, "**", "*.json"), recursive=True)
-            txt_files = glob.glob(os.path.join(output_path, "**", "*.txt"), recursive=True)
-            uploaded_files = []
-            # Upload .safetensors files to root
-            for file_path in safetensors_files:
-                filename = os.path.basename(file_path)
-                print(f"Uploading {filename} to repository root...")
-                api.upload_file(
-                    path_or_fileobj=file_path,
-                    path_in_repo=filename,
-                    repo_id=repo_id,
-                    token=token
-                )
-                uploaded_files.append(filename)
-            # Upload relevant JSON config files to root (skip metadata.json and other internal files)
-            config_files_uploaded = []
-            for file_path in json_files:
-                filename = os.path.basename(file_path)
-                # Only upload important config files, skip internal metadata
-                if any(keyword in filename.lower() for keyword in ['config', 'adapter', 'lora', 'model']):
-                    print(f"Uploading {filename} to repository root...")
-                    api.upload_file(
-                        path_or_fileobj=file_path,
-                        path_in_repo=filename,
-                        repo_id=repo_id,
-                        token=token
-                    )
-                    uploaded_files.append(filename)
-                    config_files_uploaded.append(filename)
-            # 2. Handle sample images
-            samples_uploaded = []
-            samples_dir = os.path.join(output_path, "samples")
-            if os.path.isdir(samples_dir):
-                print("Uploading sample images...")
-                # Create samples directory in repo
-                for filename in os.listdir(samples_dir):
-                    if filename.lower().endswith(('.jpg', '.jpeg', '.png', '.webp')):
-                        file_path = os.path.join(samples_dir, filename)
-                        repo_path = f"samples/{filename}"
-                        api.upload_file(
-                            path_or_fileobj=file_path,
-                            path_in_repo=repo_path,
-                            repo_id=repo_id,
-                            token=token
-                        )
-                        samples_uploaded.append(repo_path)
-            # 3. Generate and upload README.md
-            readme_content = generate_model_card_readme(
-                repo_id=repo_id,
-                config=config,
-                model_name=model_name,
-                samples_dir=samples_dir if os.path.isdir(samples_dir) else None,
-                uploaded_files=uploaded_files
-            )
-            # Create README.md file and upload to root
-            readme_path = os.path.join(temp_upload_dir, "README.md")
-            with open(readme_path, "w", encoding="utf-8") as f:
-                f.write(readme_content)
-            print("Uploading README.md to repository root...")
-            api.upload_file(
-                path_or_fileobj=readme_path,
-                path_in_repo="README.md",
-                repo_id=repo_id,
-                token=token
-            )
-            print(f"Model uploaded successfully to https://huggingface.co/{repo_id}")
-            print(f"Files uploaded: {len(uploaded_files)} model files, {len(samples_uploaded)} samples, README.md")
-    except Exception as e:
-        print(f"Failed to upload model: {e}")
-        raise e
-def generate_model_card_readme(repo_id: str, config: dict, model_name: str, samples_dir: str = None, uploaded_files: list = None) -> str:
-    """Generate README.md content for the model card based on AI Toolkit's implementation"""
-    import re
-    import yaml
-    import os
-    try:
-        # Extract configuration details
-        process_config = config.get("config", {}).get("process", [{}])[0]
-        model_config = process_config.get("model", {})
-        train_config = process_config.get("train", {})
-        sample_config = process_config.get("sample", {})
-        # Gather model info
-        base_model = model_config.get("name_or_path", "unknown")
-        trigger_word = process_config.get("trigger_word")
-        arch = model_config.get("arch", "")
-        # Determine license based on base model
-        if "FLUX.1-schnell" in base_model:
-            license_info = {"license": "apache-2.0"}
-        elif "FLUX.1-dev" in base_model:
-            license_info = {
-                "license": "other",
-                "license_name": "flux-1-dev-non-commercial-license",
-                "license_link": "https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md"
-            }
-        else:
-            license_info = {"license": "creativeml-openrail-m"}
-        # Generate tags based on model architecture
-        tags = ["text-to-image"]
-        if "xl" in arch.lower():
-            tags.append("stable-diffusion-xl")
-        if "flux" in arch.lower():
-            tags.append("flux")
-        if "lumina" in arch.lower():
-            tags.append("lumina2")
-        if "sd3" in arch.lower() or "v3" in arch.lower():
-            tags.append("sd3")
-        # Add LoRA-specific tags
-        tags.extend(["lora", "diffusers", "template:sd-lora", "ai-toolkit"])
-        # Generate widgets from sample images and prompts
-        widgets = []
-        if samples_dir and os.path.isdir(samples_dir):
-            sample_prompts = sample_config.get("samples", [])
-            if not sample_prompts:
-                # Fallback to old format
-                sample_prompts = [{"prompt": p} for p in sample_config.get("prompts", [])]
-            # Get sample image files
-            sample_files = []
-            if os.path.isdir(samples_dir):
-                for filename in os.listdir(samples_dir):
-                    if filename.lower().endswith(('.jpg', '.jpeg', '.png', '.webp')):
-                        # Parse filename pattern: timestamp__steps_index.jpg
-                        match = re.search(r"__(\d+)_(\d+)\.jpg$", filename)
-                        if match:
-                            steps, index = int(match.group(1)), int(match.group(2))
-                            # Only use samples from final training step
-                            final_steps = train_config.get("steps", 1000)
-                            if steps == final_steps:
-                                sample_files.append((index, f"samples/{filename}"))
-            # Sort by index and create widgets
-            sample_files.sort(key=lambda x: x[0])
-            for i, prompt_obj in enumerate(sample_prompts):
-                prompt = prompt_obj.get("prompt", "") if isinstance(prompt_obj, dict) else str(prompt_obj)
-                if i < len(sample_files):
-                    _, image_path = sample_files[i]
-                    widgets.append({
-                        "text": prompt,
-                        "output": {"url": image_path}
-                    })
-        # Determine torch dtype based on model
-        dtype = "torch.bfloat16" if "flux" in arch.lower() else "torch.float16"
-        # Find the main safetensors file for usage example
-        main_safetensors = f"{model_name}.safetensors"
-        if uploaded_files:
-            safetensors_files = [f for f in uploaded_files if f.endswith('.safetensors')]
-            if safetensors_files:
-                main_safetensors = safetensors_files[0]
-        # Construct YAML frontmatter
-        frontmatter = {
-            "tags": tags,
-            "base_model": base_model,
-            **license_info
-        }
-        if widgets:
-            frontmatter["widget"] = widgets
-        if trigger_word:
-            frontmatter["instance_prompt"] = trigger_word
-        # Get first prompt for usage example
-        usage_prompt = trigger_word or "a beautiful landscape"
-        if widgets:
-            usage_prompt = widgets[0]["text"]
-        elif trigger_word:
-            usage_prompt = trigger_word
-        # Construct README content
-        trigger_section = f"You should use \`{trigger_word}\` to trigger the image generation." if trigger_word else "No trigger words defined."
-        # Build YAML frontmatter string
-        frontmatter_yaml = yaml.dump(frontmatter, default_flow_style=False, allow_unicode=True, sort_keys=False).strip()
-        readme_content = f"""---
-{frontmatter_yaml}
----
-# {model_name}
-Model trained with [AI Toolkit by Ostris](https://github.com/ostris/ai-toolkit)
-<Gallery />
-## Trigger words
-{trigger_section}
-## Download model and use it with ComfyUI, AUTOMATIC1111, SD.Next, Invoke AI, etc.
-Weights for this model are available in Safetensors format.
-[Download]({repo_id}/tree/main) them in the Files & versions tab.
-## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)
-\`\`\`py
-from diffusers import AutoPipelineForText2Image
-import torch
-pipeline = AutoPipelineForText2Image.from_pretrained('{base_model}', torch_dtype={dtype}).to('cuda')
-pipeline.load_lora_weights('{repo_id}', weight_name='{main_safetensors}')
-image = pipeline('{usage_prompt}').images[0]
-image.save("my_image.png")
-\`\`\`
-For more details, including weighting, merging and fusing LoRAs, check the [documentation on loading LoRAs in diffusers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters)
-"""
-        return readme_content
-    except Exception as e:
-        print(f"Error generating README: {e}")
-        # Fallback simple README
-        return f"""# {model_name}
-Model trained with [AI Toolkit by Ostris](https://github.com/ostris/ai-toolkit)
-## Download model
-Weights for this model are available in Safetensors format.
-[Download]({repo_id}/tree/main) them in the Files & versions tab.
-"""
-def main():
-    # Setup environment - token comes from HF Jobs secrets
-    if "HF_TOKEN" not in os.environ:
-        raise ValueError("HF_TOKEN environment variable not set")
-    # Install system dependencies for headless operation
-    print("Installing system dependencies...")
-    try:
-        subprocess.run(["apt-get", "update"], check=True, capture_output=True)
-        subprocess.run([
-            "apt-get", "install", "-y",
-            "libgl1-mesa-glx",
-            "libglib2.0-0",
-            "libsm6",
-            "libxext6",
-            "libxrender-dev",
-            "libgomp1",
-            "ffmpeg"
-        ], check=True, capture_output=True)
-        print("System dependencies installed successfully")
-    except subprocess.CalledProcessError as e:
-        print(f"Failed to install system dependencies: {e}")
-        print("Continuing without system dependencies...")
-    # Setup ai-toolkit
-    toolkit_dir = setup_ai_toolkit()
-    # Create temporary directories
-    with tempfile.TemporaryDirectory() as temp_dir:
-        dataset_path = os.path.join(temp_dir, "dataset")
-        output_path = os.path.join(temp_dir, "output")
-        # Download dataset
-        download_dataset("${datasetRepo}", dataset_path)
-        # Create config
-        config = create_config(dataset_path, output_path)
-        config_path = os.path.join(temp_dir, "config.yaml")
-        with open(config_path, "w") as f:
-            yaml.dump(config, f, default_flow_style=False)
-        # Run training
-        print("Starting training...")
-        os.chdir(toolkit_dir)
-        subprocess.run([
-            sys.executable, "run.py",
-            config_path
-        ], check=True)
-        print("Training completed!")
-        # Upload results
-        model_name = f"${jobConfig.config.name}-lora"
-        upload_results(output_path, model_name, "${namespace}", os.environ["HF_TOKEN"], config)
-if __name__ == "__main__":
-    main()
-`;
-}
-async function submitHFJobUV(token: string, hardware: string, scriptPath: string): Promise<string> {
-  return new Promise((resolve, reject) => {
-    // Ensure token is available
-    if (!token) {
-      reject(new Error('HF_TOKEN is required'));
-      return;
-    }
-    console.log('Setting up environment with HF_TOKEN for job submission');
-    console.log(`Command: hf jobs uv run --flavor ${hardware} --timeout 5h --secrets HF_TOKEN --detach ${scriptPath}`);
-    // Use hf jobs uv run command with timeout and detach to get job ID
-    const childProcess = spawn('hf', [
-      'jobs', 'uv', 'run',
-      '--flavor', hardware,
-      '--timeout', '5h',
-      '--secrets', 'HF_TOKEN',
-      '--detach',
-      scriptPath
-    ], {
-      env: {
-        ...process.env,
-        HF_TOKEN: token
-      }
-    });
-    let output = '';
-    let error = '';
-    childProcess.stdout.on('data', (data) => {
-      const text = data.toString();
-      output += text;
-      console.log('HF Jobs stdout:', text);
-    });
-    childProcess.stderr.on('data', (data) => {
-      const text = data.toString();
-      error += text;
-      console.log('HF Jobs stderr:', text);
-    });
-    childProcess.on('close', (code) => {
-      console.log('HF Jobs process closed with code:', code);
-      console.log('Full output:', output);
-      console.log('Full error:', error);
-      if (code === 0) {
-        // With --detach flag, the output should be just the job ID
-        const fullText = (output + ' ' + error).trim();
-        // Updated patterns to handle variable-length hex job IDs (16-24+ characters)
-        const jobIdPatterns = [
-          /Job started with ID:\s*([a-f0-9]{16,})/i,                    // "Job started with ID: 68b26b73767540db9fc726ac"
-          /job\s+([a-f0-9]{16,})/i,                                     // "job 68b26b73767540db9fc726ac"
-          /Job ID:\s*([a-f0-9]{16,})/i,                                 // "Job ID: 68b26b73767540db9fc726ac"
-          /created\s+job\s+([a-f0-9]{16,})/i,                          // "created job 68b26b73767540db9fc726ac"
-          /submitted.*?job\s+([a-f0-9]{16,})/i,                        // "submitted ... job 68b26b73767540db9fc726ac"
-          /https:\/\/huggingface\.co\/jobs\/[^\/]+\/([a-f0-9]{16,})/i,  // URL pattern
-          /([a-f0-9]{20,})/i,                                          // Fallback: any 20+ char hex string
-        ];
-        let jobId = 'unknown';
-        for (const pattern of jobIdPatterns) {
-          const match = fullText.match(pattern);
-          if (match && match[1] && match[1] !== 'started') {
-            jobId = match[1];
-            console.log(`Extracted job ID using pattern: ${pattern.toString()} -> ${jobId}`);
-            break;
-          }
-        }
-        resolve(jobId);
-      } else {
-        reject(new Error(error || output || 'Failed to submit job'));
-      }
-    });
-    childProcess.on('error', (err) => {
-      console.error('HF Jobs process error:', err);
-      reject(new Error(`Process error: ${err.message}`));
-    });
-  });
-}
-async function checkHFJobStatus(token: string, jobId: string): Promise<any> {
-  return new Promise((resolve, reject) => {
-    console.log(`Checking HF Job status for: ${jobId}`);
-    const childProcess = spawn('hf', [
-      'jobs', 'inspect', jobId
-    ], {
-      env: {
-        ...process.env,
-        HF_TOKEN: token
-      }
-    });
-    let output = '';
-    let error = '';
-    childProcess.stdout.on('data', (data) => {
-      const text = data.toString();
-      output += text;
-    });
-    childProcess.stderr.on('data', (data) => {
-      const text = data.toString();
-      error += text;
-    });
-    childProcess.on('close', (code) => {
-      if (code === 0) {
-        try {
-          // Parse the JSON output from hf jobs inspect
-          const jobInfo = JSON.parse(output);
-          if (Array.isArray(jobInfo) && jobInfo.length > 0) {
-            const job = jobInfo[0];
-            resolve({
-              id: job.id,
-              status: job.status?.stage || 'UNKNOWN',
-              message: job.status?.message,
-              created_at: job.created_at,
-              flavor: job.flavor,
-              url: job.url,
-            });
-          } else {
-            reject(new Error('Invalid job info response'));
-          }
-        } catch (parseError: any) {
-          console.error('Failed to parse job status:', parseError, output);
-          reject(new Error('Failed to parse job status'));
-        }
-      } else {
-        reject(new Error(error || output || 'Failed to check job status'));
-      }
-    });
-    childProcess.on('error', (err) => {
-      console.error('HF Jobs inspect process error:', err);
-      reject(new Error(`Process error: ${err.message}`));
-    });
-  });
-}

src/app/api/img/[...imagePath]/route.ts DELETED Viewed

@@ -1,78 +0,0 @@
-/* eslint-disable */
-import { NextRequest, NextResponse } from 'next/server';
-import fs from 'fs';
-import path from 'path';
-import { getDatasetsRoot, getTrainingFolder, getDataRoot } from '@/server/settings';
-export async function GET(request: NextRequest, { params }: { params: { imagePath: string } }) {
-  const { imagePath } = await params;
-  try {
-    // Decode the path
-    const filepath = decodeURIComponent(imagePath);
-    // Get allowed directories
-    const datasetRoot = await getDatasetsRoot();
-    const trainingRoot = await getTrainingFolder();
-    const dataRoot = await getDataRoot();
-    const allowedDirs = [datasetRoot, trainingRoot, dataRoot];
-    // Security check: Ensure path is in allowed directory
-    const isAllowed = allowedDirs.some(allowedDir => filepath.startsWith(allowedDir)) && !filepath.includes('..');
-    if (!isAllowed) {
-      console.warn(`Access denied: ${filepath} not in ${allowedDirs.join(', ')}`);
-      return new NextResponse('Access denied', { status: 403 });
-    }
-    // Check if file exists
-    if (!fs.existsSync(filepath)) {
-      console.warn(`File not found: ${filepath}`);
-      return new NextResponse('File not found', { status: 404 });
-    }
-    // Get file info
-    const stat = fs.statSync(filepath);
-    if (!stat.isFile()) {
-      return new NextResponse('Not a file', { status: 400 });
-    }
-    // Determine content type
-    const ext = path.extname(filepath).toLowerCase();
-    const contentTypeMap: { [key: string]: string } = {
-      // Images
-      '.jpg': 'image/jpeg',
-      '.jpeg': 'image/jpeg',
-      '.png': 'image/png',
-      '.gif': 'image/gif',
-      '.webp': 'image/webp',
-      '.svg': 'image/svg+xml',
-      '.bmp': 'image/bmp',
-      // Videos
-      '.mp4': 'video/mp4',
-      '.avi': 'video/x-msvideo',
-      '.mov': 'video/quicktime',
-      '.mkv': 'video/x-matroska',
-      '.wmv': 'video/x-ms-wmv',
-      '.m4v': 'video/x-m4v',
-      '.flv': 'video/x-flv'
-    };
-    const contentType = contentTypeMap[ext] || 'application/octet-stream';
-    // Read file as buffer
-    const fileBuffer = fs.readFileSync(filepath);
-    // Return file with appropriate headers
-    return new NextResponse(fileBuffer, {
-      headers: {
-        'Content-Type': contentType,
-        'Content-Length': String(stat.size),
-        'Cache-Control': 'public, max-age=86400',
-      },
-    });
-  } catch (error) {
-    console.error('Error serving image:', error);
-    return new NextResponse('Internal Server Error', { status: 500 });
-  }
-}

src/app/api/img/caption/route.ts DELETED Viewed

@@ -1,29 +0,0 @@
-import { NextResponse } from 'next/server';
-import fs from 'fs';
-import { getDatasetsRoot } from '@/server/settings';
-export async function POST(request: Request) {
-  try {
-    const body = await request.json();
-    const { imgPath, caption } = body;
-    let datasetsPath = await getDatasetsRoot();
-    // make sure the dataset path is in the image path
-    if (!imgPath.startsWith(datasetsPath)) {
-      return NextResponse.json({ error: 'Invalid image path' }, { status: 400 });
-    }
-    // if img doesnt exist, ignore
-    if (!fs.existsSync(imgPath)) {
-      return NextResponse.json({ error: 'Image does not exist' }, { status: 404 });
-    }
-    // check for caption
-    const captionPath = imgPath.replace(/\.[^/.]+$/, '') + '.txt';
-    // save caption to file
-    fs.writeFileSync(captionPath, caption);
-    return NextResponse.json({ success: true });
-  } catch (error) {
-    return NextResponse.json({ error: 'Failed to create dataset' }, { status: 500 });
-  }
-}

src/app/api/img/delete/route.ts DELETED Viewed

@@ -1,34 +0,0 @@
-import { NextResponse } from 'next/server';
-import fs from 'fs';
-import { getDatasetsRoot } from '@/server/settings';
-export async function POST(request: Request) {
-  try {
-    const body = await request.json();
-    const { imgPath } = body;
-    let datasetsPath = await getDatasetsRoot();
-    // make sure the dataset path is in the image path
-    if (!imgPath.startsWith(datasetsPath)) {
-      return NextResponse.json({ error: 'Invalid image path' }, { status: 400 });
-    }
-    // if img doesnt exist, ignore
-    if (!fs.existsSync(imgPath)) {
-      return NextResponse.json({ success: true });
-    }
-    // delete it and return success
-    fs.unlinkSync(imgPath);
-    // check for caption
-    const captionPath = imgPath.replace(/\.[^/.]+$/, '') + '.txt';
-    if (fs.existsSync(captionPath)) {
-      // delete caption file
-      fs.unlinkSync(captionPath);
-    }
-    return NextResponse.json({ success: true });
-  } catch (error) {
-    return NextResponse.json({ error: 'Failed to create dataset' }, { status: 500 });
-  }
-}

src/app/api/img/upload/route.ts DELETED Viewed

@@ -1,58 +0,0 @@
-// src/app/api/datasets/upload/route.ts
-import { NextRequest, NextResponse } from 'next/server';
-import { writeFile, mkdir } from 'fs/promises';
-import { join } from 'path';
-import { getDataRoot } from '@/server/settings';
-import {v4 as uuidv4} from 'uuid';
-export async function POST(request: NextRequest) {
-  try {
-    const dataRoot = await getDataRoot();
-    if (!dataRoot) {
-      return NextResponse.json({ error: 'Data root path not found' }, { status: 500 });
-    }
-    const imgRoot = join(dataRoot, 'images');
-    const formData = await request.formData();
-    const files = formData.getAll('files');
-    if (!files || files.length === 0) {
-      return NextResponse.json({ error: 'No files provided' }, { status: 400 });
-    }
-    // make it recursive if it doesn't exist
-    await mkdir(imgRoot, { recursive: true });
-    const savedFiles = await Promise.all(
-      files.map(async (file: any) => {
-        const bytes = await file.arrayBuffer();
-        const buffer = Buffer.from(bytes);
-        const extension = file.name.split('.').pop() || 'jpg';
-        // Clean filename and ensure it's unique
-        const fileName = `${uuidv4()}`; // Use UUID for unique file names
-        const filePath = join(imgRoot, `${fileName}.${extension}`);
-        await writeFile(filePath, buffer);
-        return filePath;
-      }),
-    );
-    return NextResponse.json({
-      message: 'Files uploaded successfully',
-      files: savedFiles,
-    });
-  } catch (error) {
-    console.error('Upload error:', error);
-    return NextResponse.json({ error: 'Error uploading files' }, { status: 500 });
-  }
-}
-// Increase payload size limit (default is 4mb)
-export const config = {
-  api: {
-    bodyParser: false,
-    responseLimit: '50mb',
-  },
-};

src/app/api/jobs/[jobID]/delete/route.ts DELETED Viewed

@@ -1,32 +0,0 @@
-import { NextRequest, NextResponse } from 'next/server';
-import { PrismaClient } from '@prisma/client';
-import { getTrainingFolder } from '@/server/settings';
-import path from 'path';
-import fs from 'fs';
-const prisma = new PrismaClient();
-export async function GET(request: NextRequest, { params }: { params: { jobID: string } }) {
-  const { jobID } = await params;
-  const job = await prisma.job.findUnique({
-    where: { id: jobID },
-  });
-  if (!job) {
-    return NextResponse.json({ error: 'Job not found' }, { status: 404 });
-  }
-  const trainingRoot = await getTrainingFolder();
-  const trainingFolder = path.join(trainingRoot, job.name);
-  if (fs.existsSync(trainingFolder)) {
-    fs.rmdirSync(trainingFolder, { recursive: true });
-  }
-  await prisma.job.delete({
-    where: { id: jobID },
-  });
-  return NextResponse.json(job);
-}

src/app/api/jobs/[jobID]/files/route.ts DELETED Viewed

@@ -1,48 +0,0 @@
-import { NextRequest, NextResponse } from 'next/server';
-import { PrismaClient } from '@prisma/client';
-import path from 'path';
-import fs from 'fs';
-import { getTrainingFolder } from '@/server/settings';
-const prisma = new PrismaClient();
-export async function GET(request: NextRequest, { params }: { params: { jobID: string } }) {
-  const { jobID } = await params;
-  const job = await prisma.job.findUnique({
-    where: { id: jobID },
-  });
-  if (!job) {
-    return NextResponse.json({ error: 'Job not found' }, { status: 404 });
-  }
-  const trainingFolder = await getTrainingFolder();
-  const jobFolder = path.join(trainingFolder, job.name);
-  if (!fs.existsSync(jobFolder)) {
-    return NextResponse.json({ files: [] });
-  }
-  // find all safetensors files in the job folder
-  let files = fs
-    .readdirSync(jobFolder)
-    .filter(file => {
-      return file.endsWith('.safetensors');
-    })
-    .map(file => {
-      return path.join(jobFolder, file);
-    })
-    .sort();
-  // get the file size for each file
-  const fileObjects = files.map(file => {
-    const stats = fs.statSync(file);
-    return {
-      path: file,
-      size: stats.size,
-    };
-  });
-  return NextResponse.json({ files: fileObjects });
-}

src/app/api/jobs/[jobID]/log/route.ts DELETED Viewed

@@ -1,35 +0,0 @@
-import { NextRequest, NextResponse } from 'next/server';
-import { PrismaClient } from '@prisma/client';
-import path from 'path';
-import fs from 'fs';
-import { getTrainingFolder } from '@/server/settings';
-const prisma = new PrismaClient();
-export async function GET(request: NextRequest, { params }: { params: { jobID: string } }) {
-  const { jobID } = await params;
-  const job = await prisma.job.findUnique({
-    where: { id: jobID },
-  });
-  if (!job) {
-    return NextResponse.json({ error: 'Job not found' }, { status: 404 });
-  }
-  const trainingFolder = await getTrainingFolder();
-  const jobFolder = path.join(trainingFolder, job.name);
-  const logPath = path.join(jobFolder, 'log.txt');
-  if (!fs.existsSync(logPath)) {
-    return NextResponse.json({ log: '' });
-  }
-  let log = '';
-  try {
-    log = fs.readFileSync(logPath, 'utf-8');
-  } catch (error) {
-    console.error('Error reading log file:', error);
-    log = 'Error reading log file';
-  }
-  return NextResponse.json({ log: log });
-}

src/app/api/jobs/[jobID]/samples/route.ts DELETED Viewed

@@ -1,40 +0,0 @@
-import { NextRequest, NextResponse } from 'next/server';
-import { PrismaClient } from '@prisma/client';
-import path from 'path';
-import fs from 'fs';
-import { getTrainingFolder } from '@/server/settings';
-const prisma = new PrismaClient();
-export async function GET(request: NextRequest, { params }: { params: { jobID: string } }) {
-  const { jobID } = await params;
-  const job = await prisma.job.findUnique({
-    where: { id: jobID },
-  });
-  if (!job) {
-    return NextResponse.json({ error: 'Job not found' }, { status: 404 });
-  }
-  // setup the training
-  const trainingFolder = await getTrainingFolder();
-  const samplesFolder = path.join(trainingFolder, job.name, 'samples');
-  if (!fs.existsSync(samplesFolder)) {
-    return NextResponse.json({ samples: [] });
-  }
-  // find all img (png, jpg, jpeg) files in the samples folder
-  const samples = fs
-    .readdirSync(samplesFolder)
-    .filter(file => {
-      return file.endsWith('.png') || file.endsWith('.jpg') || file.endsWith('.jpeg') || file.endsWith('.webp');
-    })
-    .map(file => {
-      return path.join(samplesFolder, file);
-    })
-    .sort();
-  return NextResponse.json({ samples });
-}

src/app/api/jobs/[jobID]/start/route.ts DELETED Viewed

@@ -1,215 +0,0 @@
-import { NextRequest, NextResponse } from 'next/server';
-import { PrismaClient } from '@prisma/client';
-import { TOOLKIT_ROOT } from '@/paths';
-import { spawn } from 'child_process';
-import path from 'path';
-import fs from 'fs';
-import os from 'os';
-import { getTrainingFolder, getHFToken } from '@/server/settings';
-const isWindows = process.platform === 'win32';
-const prisma = new PrismaClient();
-export async function GET(request: NextRequest, { params }: { params: { jobID: string } }) {
-  const { jobID } = await params;
-  const job = await prisma.job.findUnique({
-    where: { id: jobID },
-  });
-  if (!job) {
-    return NextResponse.json({ error: 'Job not found' }, { status: 404 });
-  }
-  // update job status to 'running'
-  await prisma.job.update({
-    where: { id: jobID },
-    data: {
-      status: 'running',
-      stop: false,
-      info: 'Starting job...',
-    },
-  });
-  // setup the training
-  const trainingRoot = await getTrainingFolder();
-  const trainingFolder = path.join(trainingRoot, job.name);
-  if (!fs.existsSync(trainingFolder)) {
-    fs.mkdirSync(trainingFolder, { recursive: true });
-  }
-  // make the config file
-  const configPath = path.join(trainingFolder, '.job_config.json');
-  //log to path
-  const logPath = path.join(trainingFolder, 'log.txt');
-  try {
-    // if the log path exists, move it to a folder called logs and rename it {num}_log.txt, looking for the highest num
-    // if the log path does not exist, create it
-    if (fs.existsSync(logPath)) {
-      const logsFolder = path.join(trainingFolder, 'logs');
-      if (!fs.existsSync(logsFolder)) {
-        fs.mkdirSync(logsFolder, { recursive: true });
-      }
-      let num = 0;
-      while (fs.existsSync(path.join(logsFolder, `${num}_log.txt`))) {
-        num++;
-      }
-      fs.renameSync(logPath, path.join(logsFolder, `${num}_log.txt`));
-    }
-  } catch (e) {
-    console.error('Error moving log file:', e);
-  }
-  // update the config dataset path
-  const jobConfig = JSON.parse(job.job_config);
-  jobConfig.config.process[0].sqlite_db_path = path.join(TOOLKIT_ROOT, 'aitk_db.db');
-  // write the config file
-  fs.writeFileSync(configPath, JSON.stringify(jobConfig, null, 2));
-  let pythonPath = 'python';
-  // use .venv or venv if it exists
-  if (fs.existsSync(path.join(TOOLKIT_ROOT, '.venv'))) {
-    if (isWindows) {
-      pythonPath = path.join(TOOLKIT_ROOT, '.venv', 'Scripts', 'python.exe');
-    } else {
-      pythonPath = path.join(TOOLKIT_ROOT, '.venv', 'bin', 'python');
-    }
-  } else if (fs.existsSync(path.join(TOOLKIT_ROOT, 'venv'))) {
-    if (isWindows) {
-      pythonPath = path.join(TOOLKIT_ROOT, 'venv', 'Scripts', 'python.exe');
-    } else {
-      pythonPath = path.join(TOOLKIT_ROOT, 'venv', 'bin', 'python');
-    }
-  }
-  const runFilePath = path.join(TOOLKIT_ROOT, 'run.py');
-  if (!fs.existsSync(runFilePath)) {
-    return NextResponse.json({ error: 'run.py not found' }, { status: 500 });
-  }
-  const additionalEnv: any = {
-    AITK_JOB_ID: jobID,
-    CUDA_VISIBLE_DEVICES: `${job.gpu_ids}`,
-    IS_AI_TOOLKIT_UI: '1'
-  };
-  // HF_TOKEN
-  const hfToken = await getHFToken();
-  if (hfToken && hfToken.trim() !== '') {
-    additionalEnv.HF_TOKEN = hfToken;
-  }
-  // Add the --log argument to the command
-  const args = [runFilePath, configPath, '--log', logPath];
-  try {
-    let subprocess;
-    if (isWindows) {
-      // For Windows, use 'cmd.exe' to open a new command window
-      subprocess = spawn('cmd.exe', ['/c', 'start', 'cmd.exe', '/k', pythonPath, ...args], {
-        env: {
-          ...process.env,
-          ...additionalEnv,
-        },
-        cwd: TOOLKIT_ROOT,
-        windowsHide: false,
-      });
-    } else {
-      // For non-Windows platforms
-      subprocess = spawn(pythonPath, args, {
-        detached: true,
-        stdio: ['ignore', 'pipe', 'pipe'], // Changed from 'ignore' to capture output
-        env: {
-          ...process.env,
-          ...additionalEnv,
-        },
-        cwd: TOOLKIT_ROOT,
-      });
-    }
-    // Start monitoring in the background without blocking the response
-    const monitorProcess = async () => {
-      const startTime = Date.now();
-      let errorOutput = '';
-      let stdoutput = '';
-      if (subprocess.stderr) {
-        subprocess.stderr.on('data', data => {
-          errorOutput += data.toString();
-        });
-        subprocess.stdout.on('data', data => {
-          stdoutput += data.toString();
-          // truncate to only get the last 500 characters
-          if (stdoutput.length > 500) {
-            stdoutput = stdoutput.substring(stdoutput.length - 500);
-          }
-        });
-      }
-      subprocess.on('exit', async code => {
-        const currentTime = Date.now();
-        const duration = (currentTime - startTime) / 1000;
-        console.log(`Job ${jobID} exited with code ${code} after ${duration} seconds.`);
-        // wait for 5 seconds to give it time to stop itself. It id still has a status of running in the db, update it to stopped
-        await new Promise(resolve => setTimeout(resolve, 5000));
-        const updatedJob = await prisma.job.findUnique({
-          where: { id: jobID },
-        });
-        if (updatedJob?.status === 'running') {
-          let errorString = errorOutput;
-          if (errorString.trim() === '') {
-            errorString = stdoutput;
-          }
-          await prisma.job.update({
-            where: { id: jobID },
-            data: {
-              status: 'error',
-              info: `Error launching job: ${errorString.substring(0, 500)}`,
-            },
-          });
-        }
-      });
-      // Wait 30 seconds before releasing the process
-      await new Promise(resolve => setTimeout(resolve, 30000));
-      // Detach the process for non-Windows systems
-      if (!isWindows && subprocess.unref) {
-        subprocess.unref();
-      }
-    };
-    // Start the monitoring without awaiting it
-    monitorProcess().catch(err => {
-      console.error(`Error in process monitoring for job ${jobID}:`, err);
-    });
-    // Return the response immediately
-    return NextResponse.json(job);
-  } catch (error: any) {
-    // Handle any exceptions during process launch
-    console.error('Error launching process:', error);
-    await prisma.job.update({
-      where: { id: jobID },
-      data: {
-        status: 'error',
-        info: `Error launching job: ${error?.message || 'Unknown error'}`,
-      },
-    });
-    return NextResponse.json(
-      {
-        error: 'Failed to launch job process',
-        details: error?.message || 'Unknown error',
-      },
-      { status: 500 },
-    );
-  }
-}

src/app/api/jobs/[jobID]/stop/route.ts DELETED Viewed

@@ -1,23 +0,0 @@
-import { NextRequest, NextResponse } from 'next/server';
-import { PrismaClient } from '@prisma/client';
-const prisma = new PrismaClient();
-export async function GET(request: NextRequest, { params }: { params: { jobID: string } }) {
-  const { jobID } = await params;
-  const job = await prisma.job.findUnique({
-    where: { id: jobID },
-  });
-  // update job status to 'running'
-  await prisma.job.update({
-    where: { id: jobID },
-    data: {
-      stop: true,
-      info: 'Stopping job...',
-    },
-  });
-  return NextResponse.json(job);
-}

src/app/api/jobs/route.ts DELETED Viewed

@@ -1,67 +0,0 @@
-import { NextResponse } from 'next/server';
-import { PrismaClient } from '@prisma/client';
-const prisma = new PrismaClient();
-export async function GET(request: Request) {
-  const { searchParams } = new URL(request.url);
-  const id = searchParams.get('id');
-  try {
-    if (id) {
-      const job = await prisma.job.findUnique({
-        where: { id },
-      });
-      return NextResponse.json(job);
-    }
-    const jobs = await prisma.job.findMany({
-      orderBy: { created_at: 'desc' },
-    });
-    return NextResponse.json({ jobs: jobs });
-  } catch (error) {
-    console.error(error);
-    return NextResponse.json({ error: 'Failed to fetch training data' }, { status: 500 });
-  }
-}
-export async function POST(request: Request) {
-  try {
-    const body = await request.json();
-    const { id, name, job_config, gpu_ids } = body;
-    // Ensure gpu_ids is never null/undefined - provide default value
-    const safeGpuIds = gpu_ids || '0';
-    if (id) {
-      // Update existing training
-      const training = await prisma.job.update({
-        where: { id },
-        data: {
-          name,
-          gpu_ids: safeGpuIds,
-          job_config: JSON.stringify(job_config),
-        },
-      });
-      return NextResponse.json(training);
-    } else {
-      // Create new training
-      const training = await prisma.job.create({
-        data: {
-          name,
-          gpu_ids: safeGpuIds,
-          job_config: JSON.stringify(job_config),
-        },
-      });
-      return NextResponse.json(training);
-    }
-  } catch (error: any) {
-    if (error.code === 'P2002') {
-      // Handle unique constraint violation, 409=Conflict
-      return NextResponse.json({ error: 'Job name already exists' }, { status: 409 });
-    }
-    console.error(error);
-    // Handle other errors
-    return NextResponse.json({ error: 'Failed to save training data' }, { status: 500 });
-  }
-}

src/app/api/settings/route.ts DELETED Viewed

@@ -1,59 +0,0 @@
-import { NextResponse } from 'next/server';
-import { PrismaClient } from '@prisma/client';
-import { defaultTrainFolder, defaultDatasetsFolder } from '@/paths';
-import { flushCache } from '@/server/settings';
-const prisma = new PrismaClient();
-export async function GET() {
-  try {
-    const settings = await prisma.settings.findMany();
-    const settingsObject = settings.reduce((acc: any, setting) => {
-      acc[setting.key] = setting.value;
-      return acc;
-    }, {});
-    // if TRAINING_FOLDER is not set, use default
-    if (!settingsObject.TRAINING_FOLDER || settingsObject.TRAINING_FOLDER === '') {
-      settingsObject.TRAINING_FOLDER = defaultTrainFolder;
-    }
-    // if DATASETS_FOLDER is not set, use default
-    if (!settingsObject.DATASETS_FOLDER || settingsObject.DATASETS_FOLDER === '') {
-      settingsObject.DATASETS_FOLDER = defaultDatasetsFolder;
-    }
-    return NextResponse.json(settingsObject);
-  } catch (error) {
-    return NextResponse.json({ error: 'Failed to fetch settings' }, { status: 500 });
-  }
-}
-export async function POST(request: Request) {
-  try {
-    const body = await request.json();
-    const { HF_TOKEN, TRAINING_FOLDER, DATASETS_FOLDER } = body;
-    // Upsert both settings
-    await Promise.all([
-      prisma.settings.upsert({
-        where: { key: 'HF_TOKEN' },
-        update: { value: HF_TOKEN },
-        create: { key: 'HF_TOKEN', value: HF_TOKEN },
-      }),
-      prisma.settings.upsert({
-        where: { key: 'TRAINING_FOLDER' },
-        update: { value: TRAINING_FOLDER },
-        create: { key: 'TRAINING_FOLDER', value: TRAINING_FOLDER },
-      }),
-      prisma.settings.upsert({
-        where: { key: 'DATASETS_FOLDER' },
-        update: { value: DATASETS_FOLDER },
-        create: { key: 'DATASETS_FOLDER', value: DATASETS_FOLDER },
-      }),
-    ]);
-    flushCache();
-    return NextResponse.json({ success: true });
-  } catch (error) {
-    return NextResponse.json({ error: 'Failed to update settings' }, { status: 500 });
-  }
-}

src/app/api/zip/route.ts DELETED Viewed

@@ -1,78 +0,0 @@
-/* eslint-disable */
-import { NextRequest, NextResponse } from 'next/server';
-import fs from 'fs';
-import fsp from 'fs/promises';
-import path from 'path';
-import archiver from 'archiver';
-import { getTrainingFolder } from '@/server/settings';
-export const runtime = 'nodejs'; // ensure Node APIs are available
-export const dynamic = 'force-dynamic'; // long-running, non-cached
-type PostBody = {
-  zipTarget: 'samples'; //only samples for now
-  jobName: string;
-};
-async function resolveSafe(p: string) {
-  // resolve symlinks + normalize
-  return await fsp.realpath(p);
-}
-export async function POST(request: NextRequest) {
-  try {
-    const body = (await request.json()) as PostBody;
-    if (!body || !body.jobName) {
-      return NextResponse.json({ error: 'jobName is required' }, { status: 400 });
-    }
-    const trainingRoot = await resolveSafe(await getTrainingFolder());
-    const folderPath = await resolveSafe(path.join(trainingRoot, body.jobName, 'samples'));
-    const outputPath = path.resolve(trainingRoot, body.jobName, 'samples.zip');
-    // Must be a directory
-    let stat: fs.Stats;
-    try {
-      stat = await fsp.stat(folderPath);
-    } catch {
-      return new NextResponse('Folder not found', { status: 404 });
-    }
-    if (!stat.isDirectory()) {
-      return new NextResponse('Not a directory', { status: 400 });
-    }
-    // delete current one if it exists
-    if (fs.existsSync(outputPath)) {
-      await fsp.unlink(outputPath);
-    }
-    // Create write stream & archive
-    await new Promise<void>((resolve, reject) => {
-      const output = fs.createWriteStream(outputPath);
-      const archive = archiver('zip', { zlib: { level: 9 } });
-      output.on('close', () => resolve());
-      output.on('error', reject);
-      archive.on('error', reject);
-      archive.pipe(output);
-      // Add the directory contents (place them under the folder's base name in the zip)
-      const rootName = path.basename(folderPath);
-      archive.directory(folderPath, rootName);
-      archive.finalize().catch(reject);
-    });
-    // Return the absolute path so your existing /api/files/[...filePath] can serve it
-    // Example download URL (client-side): `/api/files/${encodeURIComponent(resolvedOutPath)}`
-    return NextResponse.json({
-      ok: true,
-      zipPath: outputPath,
-      fileName: path.basename(outputPath),
-    });
-  } catch (err) {
-    console.error('Zip error:', err);
-    return new NextResponse('Internal Server Error', { status: 500 });
-  }
-}

src/app/apple-icon.png DELETED Viewed

Binary file (8.87 kB)

src/app/dashboard/page.tsx DELETED Viewed

@@ -1,85 +0,0 @@
-'use client';
-import JobsTable from '@/components/JobsTable';
-import { TopBar, MainContent } from '@/components/layout';
-import Link from 'next/link';
-import { useAuth } from '@/contexts/AuthContext';
-import HFLoginButton from '@/components/HFLoginButton';
-export default function Dashboard() {
-  const { status: authStatus, namespace } = useAuth();
-  const isAuthenticated = authStatus === 'authenticated';
-  return (
-    <>
-      <TopBar>
-        <div>
-          <h1 className="text-lg">Dashboard</h1>
-        </div>
-        <div className="flex-1" />
-      </TopBar>
-      <MainContent>
-        <div className="border border-gray-800 rounded-xl bg-gray-900 p-6 flex flex-col gap-4">
-          <div>
-            <h2 className="text-xl font-semibold text-gray-100">
-              {isAuthenticated ? `Welcome back, ${namespace || 'creator'}!` : 'Welcome to Ostris AI Toolkit'}
-            </h2>
-            <p className="text-sm text-gray-400 mt-2">
-              {isAuthenticated
-                ? 'You are signed in with Hugging Face and can manage jobs, datasets, and submissions.'
-                : 'Authenticate with Hugging Face or add a personal access token to create jobs, upload datasets, and launch training.'}
-            </p>
-          </div>
-          {isAuthenticated ? (
-            <div className="flex flex-wrap items-center gap-3 text-sm">
-              <Link
-                href="/jobs/new"
-                className="px-4 py-2 rounded-md bg-blue-600 hover:bg-blue-500 text-white transition-colors"
-              >
-                Create a Training Job
-              </Link>
-              <Link
-                href="/datasets"
-                className="px-4 py-2 rounded-md bg-gray-800 hover:bg-gray-700 text-gray-200 transition-colors"
-              >
-                Manage Datasets
-              </Link>
-              <Link
-                href="/settings"
-                className="px-4 py-2 rounded-md border border-gray-700 text-gray-300 hover:border-gray-600 transition-colors"
-              >
-                Settings
-              </Link>
-            </div>
-          ) : (
-            <div className="flex flex-wrap items-center gap-3 text-sm">
-              <HFLoginButton size="md" />
-              <Link
-                href="/settings"
-                className="text-xs text-blue-400 hover:text-blue-300"
-              >
-                Or manage tokens in Settings
-              </Link>
-            </div>
-          )}
-        </div>
-        <div className="w-full mt-6">
-          <div className="flex justify-between items-center mb-2">
-            <h1 className="text-md">Active Jobs</h1>
-            <div className="text-xs text-gray-500">
-              <Link href="/jobs">View All</Link>
-            </div>
-          </div>
-          {isAuthenticated ? (
-            <JobsTable onlyActive />
-          ) : (
-            <div className="border border-gray-800 rounded-lg p-6 bg-gray-900 text-gray-400 text-sm">
-              Sign in with Hugging Face or add an access token in Settings to view and manage jobs.
-            </div>
-          )}
-        </div>
-      </MainContent>
-    </>
-  );
-}

src/app/datasets/[datasetName]/page.tsx DELETED Viewed

@@ -1,190 +0,0 @@
-'use client';
-import { useEffect, useState, use, useMemo } from 'react';
-import { LuImageOff, LuLoader, LuBan } from 'react-icons/lu';
-import { FaChevronLeft } from 'react-icons/fa';
-import DatasetImageCard from '@/components/DatasetImageCard';
-import { Button } from '@headlessui/react';
-import AddImagesModal, { openImagesModal } from '@/components/AddImagesModal';
-import { TopBar, MainContent } from '@/components/layout';
-import { apiClient } from '@/utils/api';
-import FullscreenDropOverlay from '@/components/FullscreenDropOverlay';
-import { useRouter } from 'next/navigation';
-import { usingBrowserDb } from '@/utils/env';
-import { hasUserDataset } from '@/utils/storage/datasetStorage';
-import { useAuth } from '@/contexts/AuthContext';
-import HFLoginButton from '@/components/HFLoginButton';
-import Link from 'next/link';
-export default function DatasetPage({ params }: { params: { datasetName: string } }) {
-  const [imgList, setImgList] = useState<{ img_path: string }[]>([]);
-  const usableParams = use(params as any) as { datasetName: string };
-  const datasetName = usableParams.datasetName;
-  const [status, setStatus] = useState<'idle' | 'loading' | 'success' | 'error'>('idle');
-  const router = useRouter();
-  const { status: authStatus } = useAuth();
-  const isAuthenticated = authStatus === 'authenticated';
-  const hasDatasetEntry = !usingBrowserDb || hasUserDataset(datasetName);
-  const allowAccess = hasDatasetEntry && isAuthenticated;
-  const refreshImageList = (dbName: string) => {
-    setStatus('loading');
-    console.log('Fetching images for dataset:', dbName);
-    apiClient
-      .post('/api/datasets/listImages', { datasetName: dbName })
-      .then((res: any) => {
-        const data = res.data;
-        console.log('Images:', data.images);
-        // sort
-        data.images.sort((a: { img_path: string }, b: { img_path: string }) => a.img_path.localeCompare(b.img_path));
-        setImgList(data.images);
-        setStatus('success');
-      })
-      .catch(error => {
-        console.error('Error fetching images:', error);
-        setStatus('error');
-      });
-  };
-  useEffect(() => {
-    if (!datasetName) {
-      return;
-    }
-    if (!isAuthenticated) {
-      return;
-    }
-    if (!hasDatasetEntry) {
-      setImgList([]);
-      setStatus('error');
-      router.replace('/datasets');
-      return;
-    }
-    refreshImageList(datasetName);
-  }, [datasetName, hasDatasetEntry, isAuthenticated, router]);
-  if (!allowAccess) {
-    return (
-      <>
-        <TopBar>
-          <div>
-            <Button className="text-gray-500 dark:text-gray-300 px-3 mt-1" onClick={() => history.back()}>
-              <FaChevronLeft />
-            </Button>
-          </div>
-          <div>
-            <h1 className="text-lg">Dataset: {datasetName}</h1>
-          </div>
-          <div className="flex-1"></div>
-        </TopBar>
-        <MainContent>
-          <div className="border border-gray-800 rounded-lg p-6 bg-gray-900 text-gray-400 text-sm flex flex-col gap-4">
-            <p>You need to sign in with Hugging Face or provide a valid token to view this dataset.</p>
-            <div className="flex items-center gap-3">
-              <HFLoginButton size="sm" />
-              <Link href="/settings" className="text-xs text-blue-400 hover:text-blue-300">
-                Manage authentication in Settings
-              </Link>
-            </div>
-          </div>
-        </MainContent>
-      </>
-    );
-  }
-  const PageInfoContent = useMemo(() => {
-    let icon = null;
-    let text = '';
-    let subtitle = '';
-    let showIt = false;
-    let bgColor = '';
-    let textColor = '';
-    let iconColor = '';
-    if (status == 'loading') {
-      icon = <LuLoader className="animate-spin w-8 h-8" />;
-      text = 'Loading Images';
-      subtitle = 'Please wait while we fetch your dataset images...';
-      showIt = true;
-      bgColor = 'bg-gray-50 dark:bg-gray-800/50';
-      textColor = 'text-gray-900 dark:text-gray-100';
-      iconColor = 'text-gray-500 dark:text-gray-400';
-    }
-    if (status == 'error') {
-      icon = <LuBan className="w-8 h-8" />;
-      text = 'Error Loading Images';
-      subtitle = 'There was a problem fetching the images. Please try refreshing the page.';
-      showIt = true;
-      bgColor = 'bg-red-50 dark:bg-red-950/20';
-      textColor = 'text-red-900 dark:text-red-100';
-      iconColor = 'text-red-600 dark:text-red-400';
-    }
-    if (status == 'success' && imgList.length === 0) {
-      icon = <LuImageOff className="w-8 h-8" />;
-      text = 'No Images Found';
-      subtitle = 'This dataset is empty. Click "Add Images" to get started.';
-      showIt = true;
-      bgColor = 'bg-gray-50 dark:bg-gray-800/50';
-      textColor = 'text-gray-900 dark:text-gray-100';
-      iconColor = 'text-gray-500 dark:text-gray-400';
-    }
-    if (!showIt) return null;
-    return (
-      <div
-        className={`mt-10 flex flex-col items-center justify-center py-16 px-8 rounded-xl border-2 border-gray-700 border-dashed ${bgColor} ${textColor} mx-auto max-w-md text-center`}
-      >
-        <div className={`${iconColor} mb-4`}>{icon}</div>
-        <h3 className="text-lg font-semibold mb-2">{text}</h3>
-        <p className="text-sm opacity-75 leading-relaxed">{subtitle}</p>
-      </div>
-    );
-  }, [status, imgList.length]);
-  return (
-    <>
-      {/* Fixed top bar */}
-      <TopBar>
-        <div>
-          <Button className="text-gray-500 dark:text-gray-300 px-3 mt-1" onClick={() => history.back()}>
-            <FaChevronLeft />
-          </Button>
-        </div>
-        <div>
-          <h1 className="text-lg">Dataset: {datasetName}</h1>
-        </div>
-        <div className="flex-1"></div>
-        <div>
-          <Button
-            className="text-gray-200 bg-slate-600 px-3 py-1 rounded-md"
-            onClick={() => openImagesModal(datasetName, () => refreshImageList(datasetName))}
-          >
-            Add Images
-          </Button>
-        </div>
-      </TopBar>
-      <MainContent>
-        {PageInfoContent}
-        {status === 'success' && imgList.length > 0 && (
-          <div className="grid grid-cols-1 sm:grid-cols-2 md:grid-cols-3 lg:grid-cols-4 gap-4">
-            {imgList.map(img => (
-              <DatasetImageCard
-                key={img.img_path}
-                alt="image"
-                imageUrl={img.img_path}
-                onDelete={() => refreshImageList(datasetName)}
-              />
-            ))}
-          </div>
-        )}
-      </MainContent>
-      <AddImagesModal />
-      <FullscreenDropOverlay
-        datasetName={datasetName}
-        onComplete={() => refreshImageList(datasetName)}
-      />
-    </>
-  );
-}

src/app/datasets/page.tsx DELETED Viewed

@@ -1,217 +0,0 @@
-'use client';
-import { useState } from 'react';
-import { Modal } from '@/components/Modal';
-import Link from 'next/link';
-import { TextInput } from '@/components/formInputs';
-import useDatasetList from '@/hooks/useDatasetList';
-import { Button } from '@headlessui/react';
-import { FaRegTrashAlt } from 'react-icons/fa';
-import { openConfirm } from '@/components/ConfirmModal';
-import { TopBar, MainContent } from '@/components/layout';
-import UniversalTable, { TableColumn } from '@/components/UniversalTable';
-import { apiClient } from '@/utils/api';
-import { useRouter } from 'next/navigation';
-import { usingBrowserDb } from '@/utils/env';
-import { addUserDataset, removeUserDataset } from '@/utils/storage/datasetStorage';
-import { useAuth } from '@/contexts/AuthContext';
-import HFLoginButton from '@/components/HFLoginButton';
-export default function Datasets() {
-  const router = useRouter();
-  const { datasets, status, refreshDatasets } = useDatasetList();
-  const [newDatasetName, setNewDatasetName] = useState('');
-  const [isNewDatasetModalOpen, setIsNewDatasetModalOpen] = useState(false);
-  const { status: authStatus } = useAuth();
-  const isAuthenticated = authStatus === 'authenticated';
-  // Transform datasets array into rows with objects
-  const tableRows = datasets.map(dataset => ({
-    name: dataset,
-    actions: dataset, // Pass full dataset name for actions
-  }));
-  const columns: TableColumn[] = [
-    {
-      title: 'Dataset Name',
-      key: 'name',
-      render: row => (
-        <Link href={`/datasets/${row.name}`} className="text-gray-200 hover:text-gray-100">
-          {row.name}
-        </Link>
-      ),
-    },
-    {
-      title: 'Actions',
-      key: 'actions',
-      className: 'w-20 text-right',
-      render: row => (
-        <button
-          className="text-gray-200 hover:bg-red-600 p-2 rounded-full transition-colors"
-          onClick={() => handleDeleteDataset(row.name)}
-        >
-          <FaRegTrashAlt />
-        </button>
-      ),
-    },
-  ];
-  const handleDeleteDataset = (datasetName: string) => {
-    openConfirm({
-      title: 'Delete Dataset',
-      message: `Are you sure you want to delete the dataset "${datasetName}"? This action cannot be undone.`,
-      type: 'warning',
-      confirmText: 'Delete',
-      onConfirm: () => {
-        apiClient
-          .post('/api/datasets/delete', { name: datasetName })
-          .then(() => {
-            console.log('Dataset deleted:', datasetName);
-            if (usingBrowserDb) {
-              removeUserDataset(datasetName);
-            }
-            refreshDatasets();
-          })
-          .catch(error => {
-            console.error('Error deleting dataset:', error);
-          });
-      },
-    });
-  };
-  const handleCreateDataset = async (e: React.FormEvent) => {
-    e.preventDefault();
-    if (!isAuthenticated) {
-      return;
-    }
-    try {
-      const data = await apiClient.post('/api/datasets/create', { name: newDatasetName }).then(res => res.data);
-      console.log('New dataset created:', data);
-      if (usingBrowserDb && data?.name) {
-        addUserDataset(data.name, data?.path || '');
-      }
-      refreshDatasets();
-      setNewDatasetName('');
-      setIsNewDatasetModalOpen(false);
-    } catch (error) {
-      console.error('Error creating new dataset:', error);
-    }
-  };
-  const openNewDatasetModal = () => {
-    if (!isAuthenticated) {
-      return;
-    }
-    openConfirm({
-      title: 'New Dataset',
-      message: 'Enter the name of the new dataset:',
-      type: 'info',
-      confirmText: 'Create',
-      inputTitle: 'Dataset Name',
-      onConfirm: async (name?: string) => {
-        if (!name) {
-          console.error('Dataset name is required.');
-          return;
-        }
-        if (!isAuthenticated) {
-          return;
-        }
-        try {
-          const data = await apiClient.post('/api/datasets/create', { name }).then(res => res.data);
-          console.log('New dataset created:', data);
-          if (usingBrowserDb && data?.name) {
-            addUserDataset(data.name, data?.path || '');
-          }
-          if (data.name) {
-            router.push(`/datasets/${data.name}`);
-          } else {
-            refreshDatasets();
-          }
-        } catch (error) {
-          console.error('Error creating new dataset:', error);
-        }
-      },
-    });
-  };
-  return (
-    <>
-      <TopBar>
-        <div>
-          <h1 className="text-2xl font-semibold text-gray-100">Datasets</h1>
-        </div>
-        <div className="flex-1"></div>
-        <div>
-          {isAuthenticated ? (
-            <Button
-              className="text-gray-200 bg-slate-600 px-4 py-2 rounded-md hover:bg-slate-500 transition-colors"
-              onClick={() => openNewDatasetModal()}
-            >
-              New Dataset
-            </Button>
-          ) : (
-            <span className="text-gray-600 bg-gray-900 px-3 py-1 rounded-md border border-gray-800">
-              Sign in to add datasets
-            </span>
-          )}
-        </div>
-      </TopBar>
-      <MainContent>
-        {isAuthenticated ? (
-          <UniversalTable
-            columns={columns}
-            rows={tableRows}
-            isLoading={status === 'loading'}
-            onRefresh={refreshDatasets}
-          />
-        ) : (
-          <div className="border border-gray-800 rounded-lg p-6 bg-gray-900 text-gray-400 text-sm flex flex-col gap-4">
-            <p>Sign in with Hugging Face or add an access token to manage datasets.</p>
-            <div className="flex items-center gap-3">
-              <HFLoginButton size="sm" />
-              <Link href="/settings" className="text-xs text-blue-400 hover:text-blue-300">
-                Manage authentication in Settings
-              </Link>
-            </div>
-          </div>
-        )}
-      </MainContent>
-      <Modal
-        isOpen={isNewDatasetModalOpen}
-        onClose={() => setIsNewDatasetModalOpen(false)}
-        title="New Dataset"
-        size="md"
-      >
-        <div className="space-y-4 text-gray-200">
-          <form onSubmit={handleCreateDataset}>
-            <div className="text-sm text-gray-400">
-              This will create a new folder with the name below in your dataset folder.
-            </div>
-            <div className="mt-4">
-              <TextInput label="Dataset Name" value={newDatasetName} onChange={value => setNewDatasetName(value)} />
-            </div>
-            <div className="mt-6 flex justify-end space-x-3">
-              <button
-                type="button"
-                className="rounded-md bg-gray-700 px-4 py-2 text-gray-200 hover:bg-gray-600 focus:outline-none focus:ring-2 focus:ring-gray-500"
-                onClick={() => setIsNewDatasetModalOpen(false)}
-              >
-                Cancel
-              </button>
-              <button
-                type="submit"
-                className="rounded-md bg-blue-600 px-4 py-2 text-white hover:bg-blue-700 focus:outline-none focus:ring-2 focus:ring-blue-500 disabled:opacity-50 disabled:cursor-not-allowed"
-                disabled={!isAuthenticated}
-              >
-                Confirm
-              </button>
-            </div>
-          </form>
-        </div>
-      </Modal>
-    </>
-  );
-}

src/app/favicon.ico DELETED Viewed

Binary file (15.1 kB)

src/app/globals.css DELETED Viewed

@@ -1,72 +0,0 @@
-@tailwind base;
-@tailwind components;
-@tailwind utilities;
-:root {
-  --background: #ffffff;
-  --foreground: #171717;
-}
-@media (prefers-color-scheme: dark) {
-  :root {
-    --background: #0a0a0a;
-    --foreground: #ededed;
-  }
-}
-body {
-  color: var(--foreground);
-  background: var(--background);
-  font-family: Arial, Helvetica, sans-serif;
-}
-@layer components {
-  /* control */
-  .aitk-react-select-container .aitk-react-select__control {
-    @apply flex w-full h-8 min-h-0 px-0 text-sm bg-gray-800 border border-gray-700 rounded-sm hover:border-gray-600 items-center;
-  }
-  /* selected label */
-  .aitk-react-select-container .aitk-react-select__single-value {
-    @apply flex-1 min-w-0 truncate text-sm text-neutral-200;
-  }
-  /* invisible input (keeps focus & typing, never wraps) */
-  .aitk-react-select-container .aitk-react-select__input-container {
-    @apply text-neutral-200;
-  }
-  /* focus */
-  .aitk-react-select-container .aitk-react-select__control--is-focused {
-    @apply ring-2 ring-gray-600 border-transparent hover:border-transparent shadow-none;
-  }
-  /* menu */
-  .aitk-react-select-container .aitk-react-select__menu {
-    @apply bg-gray-800 border border-gray-700;
-  }
-  /* options */
-  .aitk-react-select-container .aitk-react-select__option {
-    @apply text-sm text-neutral-200 bg-gray-800 hover:bg-gray-700;
-  }
-  /* indicator separator */
-  .aitk-react-select-container .aitk-react-select__indicator-separator {
-    @apply bg-gray-600;
-  }
-  /* indicators */
-  .aitk-react-select-container .aitk-react-select__indicators,
-  .aitk-react-select-container .aitk-react-select__indicator {
-    @apply py-0 flex items-center;
-  }
-  /* placeholder */
-  .aitk-react-select-container .aitk-react-select__placeholder {
-    @apply text-sm text-neutral-200;
-  }
-}

src/app/icon.png DELETED Viewed

Binary file (4.42 kB)

src/app/icon.svg DELETED Viewed

src/app/jobs/[jobID]/page.tsx DELETED Viewed

@@ -1,147 +0,0 @@
-'use client';
-import { useState, use } from 'react';
-import { FaChevronLeft } from 'react-icons/fa';
-import { Button } from '@headlessui/react';
-import { TopBar, MainContent } from '@/components/layout';
-import useJob from '@/hooks/useJob';
-import SampleImages, {SampleImagesMenu} from '@/components/SampleImages';
-import JobOverview from '@/components/JobOverview';
-import { redirect } from 'next/navigation';
-import { useAuth } from '@/contexts/AuthContext';
-import HFLoginButton from '@/components/HFLoginButton';
-import Link from 'next/link';
-import JobActionBar from '@/components/JobActionBar';
-import JobConfigViewer from '@/components/JobConfigViewer';
-import { JobRecord } from '@/types';
-type PageKey = 'overview' | 'samples' | 'config';
-interface Page {
-  name: string;
-  value: PageKey;
-  component: React.ComponentType<{ job: JobRecord }>;
-  menuItem?: React.ComponentType<{ job?: JobRecord | null }> | null;
-  mainCss?: string;
-}
-const pages: Page[] = [
-  {
-    name: 'Overview',
-    value: 'overview',
-    component: JobOverview,
-    mainCss: 'pt-24',
-  },
-  {
-    name: 'Samples',
-    value: 'samples',
-    component: SampleImages,
-    menuItem: SampleImagesMenu,
-    mainCss: 'pt-24',
-  },
-  {
-    name: 'Config File',
-    value: 'config',
-    component: JobConfigViewer,
-    mainCss: 'pt-[80px] px-0 pb-0',
-  },
-];
-export default function JobPage({ params }: { params: { jobID: string } }) {
-  const usableParams = use(params as any) as { jobID: string };
-  const jobID = usableParams.jobID;
-  const { job, status, refreshJob } = useJob(jobID, 5000);
-  const [pageKey, setPageKey] = useState<PageKey>('overview');
-  const { status: authStatus } = useAuth();
-  const isAuthenticated = authStatus === 'authenticated';
-  const page = pages.find(p => p.value === pageKey);
-  if (!isAuthenticated) {
-    return (
-      <>
-        <TopBar>
-          <div>
-            <Button className="text-gray-500 dark:text-gray-300 px-3 mt-1" onClick={() => redirect('/jobs')}>
-              <FaChevronLeft />
-            </Button>
-          </div>
-          <div>
-            <h1 className="text-lg">Job Details</h1>
-          </div>
-          <div className="flex-1"></div>
-        </TopBar>
-        <MainContent>
-          <div className="border border-gray-800 rounded-lg p-6 bg-gray-900 text-gray-400 text-sm flex flex-col gap-4">
-            <p>Sign in with Hugging Face or add an access token to view job details.</p>
-            <div className="flex items-center gap-3">
-              <HFLoginButton size="sm" />
-              <Link href="/settings" className="text-xs text-blue-400 hover:text-blue-300">
-                Manage authentication in Settings
-              </Link>
-            </div>
-          </div>
-        </MainContent>
-      </>
-    );
-  }
-  return (
-    <>
-      {/* Fixed top bar */}
-      <TopBar>
-        <div>
-          <Button className="text-gray-500 dark:text-gray-300 px-3 mt-1" onClick={() => redirect('/jobs')}>
-            <FaChevronLeft />
-          </Button>
-        </div>
-        <div>
-          <h1 className="text-lg">Job: {job?.name}</h1>
-        </div>
-        <div className="flex-1"></div>
-        {job && (
-          <JobActionBar
-            job={job}
-            onRefresh={refreshJob}
-            hideView
-            afterDelete={() => {
-              redirect('/jobs');
-            }}
-          />
-        )}
-      </TopBar>
-      <MainContent className={pages.find(page => page.value === pageKey)?.mainCss}>
-        {status === 'loading' && job == null && <p>Loading...</p>}
-        {status === 'error' && job == null && <p>Error fetching job</p>}
-        {job && (
-          <>
-            {pages.map(page => {
-              const Component = page.component;
-              return page.value === pageKey ? <Component key={page.value} job={job} /> : null;
-            })}
-          </>
-        )}
-      </MainContent>
-      <div className="bg-gray-800 absolute top-12 left-0 w-full h-8 flex items-center px-2 text-sm">
-        {pages.map(page => (
-          <Button
-            key={page.value}
-            onClick={() => setPageKey(page.value)}
-            className={`px-4 py-1 h-8  ${page.value === pageKey ? 'bg-gray-300 dark:bg-gray-700' : ''}`}
-          >
-            {page.name}
-          </Button>
-        ))}
-        {
-          page?.menuItem && (
-            <>
-            <div className='flex-grow'>
-            </div>
-              <page.menuItem job={job} />
-            </>
-          )
-        }
-      </div>
-    </>
-  );
-}

src/app/jobs/new/AdvancedJob.tsx DELETED Viewed

@@ -1,146 +0,0 @@
-'use client';
-import { useEffect, useState, useRef } from 'react';
-import { JobConfig } from '@/types';
-import YAML from 'yaml';
-import Editor, { OnMount } from '@monaco-editor/react';
-import type { editor } from 'monaco-editor';
-import { SettingsData } from '@/types';
-import { migrateJobConfig } from './jobConfig';
-type Props = {
-  jobConfig: JobConfig;
-  setJobConfig: (value: any, key?: string) => void;
-  status: 'idle' | 'saving' | 'success' | 'error';
-  handleSubmit: (event: React.FormEvent<HTMLFormElement>) => void;
-  runId: string | null;
-  gpuIDs: string | null;
-  setGpuIDs: (value: string | null) => void;
-  gpuList: any;
-  datasetOptions: any;
-  settings: SettingsData;
-};
-const isDev = process.env.NODE_ENV === 'development';
-const yamlConfig: YAML.DocumentOptions &
-  YAML.SchemaOptions &
-  YAML.ParseOptions &
-  YAML.CreateNodeOptions &
-  YAML.ToStringOptions = {
-  indent: 2,
-  lineWidth: 999999999999,
-  defaultStringType: 'QUOTE_DOUBLE',
-  defaultKeyType: 'PLAIN',
-  directives: true,
-};
-export default function AdvancedJob({ jobConfig, setJobConfig, settings }: Props) {
-  const [editorValue, setEditorValue] = useState<string>('');
-  const lastJobConfigUpdateStringRef = useRef('');
-  const editorRef = useRef<editor.IStandaloneCodeEditor | null>(null);
-  // Track if the editor has been mounted
-  const isEditorMounted = useRef(false);
-  // Handler for editor mounting
-  const handleEditorDidMount: OnMount = editor => {
-    editorRef.current = editor;
-    isEditorMounted.current = true;
-    // Initial content setup
-    try {
-      const yamlContent = YAML.stringify(jobConfig, yamlConfig);
-      setEditorValue(yamlContent);
-      lastJobConfigUpdateStringRef.current = JSON.stringify(jobConfig);
-    } catch (e) {
-      console.warn(e);
-    }
-  };
-  useEffect(() => {
-    const lastUpdate = lastJobConfigUpdateStringRef.current;
-    const currentUpdate = JSON.stringify(jobConfig);
-    // Skip if no changes or editor not yet mounted
-    if (lastUpdate === currentUpdate || !isEditorMounted.current) {
-      return;
-    }
-    try {
-      // Preserve cursor position and selection
-      const editor = editorRef.current;
-      if (editor) {
-        // Save current editor state
-        const position = editor.getPosition();
-        const selection = editor.getSelection();
-        const scrollTop = editor.getScrollTop();
-        // Update content
-        const yamlContent = YAML.stringify(jobConfig, yamlConfig);
-        // Only update if the content is actually different
-        if (yamlContent !== editor.getValue()) {
-          // Set value directly on the editor model instead of using React state
-          editor.getModel()?.setValue(yamlContent);
-          // Restore cursor position and selection
-          if (position) editor.setPosition(position);
-          if (selection) editor.setSelection(selection);
-          editor.setScrollTop(scrollTop);
-        }
-        lastJobConfigUpdateStringRef.current = currentUpdate;
-      }
-    } catch (e) {
-      console.warn(e);
-    }
-  }, [jobConfig]);
-  const handleChange = (value: string | undefined) => {
-    if (value === undefined) return;
-    try {
-      const parsed = YAML.parse(value);
-      // Don't update jobConfig if the change came from the editor itself
-      // to avoid a circular update loop
-      if (JSON.stringify(parsed) !== lastJobConfigUpdateStringRef.current) {
-        lastJobConfigUpdateStringRef.current = JSON.stringify(parsed);
-        // We have to ensure certain things are always set
-        try {
-          parsed.config.process[0].type = 'ui_trainer';
-          parsed.config.process[0].sqlite_db_path = './aitk_db.db';
-          parsed.config.process[0].training_folder = settings.TRAINING_FOLDER;
-          parsed.config.process[0].device = 'cuda';
-          parsed.config.process[0].performance_log_every = 10;
-        } catch (e) {
-          console.warn(e);
-        }
-        migrateJobConfig(parsed);
-        setJobConfig(parsed);
-      }
-    } catch (e) {
-      // Don't update on parsing errors
-      console.warn(e);
-    }
-  };
-  return (
-    <>
-      <Editor
-        height="100%"
-        width="100%"
-        defaultLanguage="yaml"
-        value={editorValue}
-        theme="vs-dark"
-        onChange={handleChange}
-        onMount={handleEditorDidMount}
-        options={{
-          minimap: { enabled: true },
-          scrollBeyondLastLine: false,
-          automaticLayout: true,
-        }}
-      />
-    </>
-  );
-}

src/app/jobs/new/SimpleJob.tsx DELETED Viewed

@@ -1,973 +0,0 @@
-'use client';
-import { useMemo, useState } from 'react';
-import { modelArchs, ModelArch, groupedModelOptions, quantizationOptions, defaultQtype } from './options';
-import { defaultDatasetConfig } from './jobConfig';
-import { GroupedSelectOption, JobConfig, SelectOption } from '@/types';
-import { objectCopy } from '@/utils/basic';
-import { TextInput, SelectInput, Checkbox, FormGroup, NumberInput } from '@/components/formInputs';
-import Card from '@/components/Card';
-import { X } from 'lucide-react';
-import AddSingleImageModal, { openAddImageModal } from '@/components/AddSingleImageModal';
-import {FlipHorizontal2, FlipVertical2} from "lucide-react";
-import HFJobsWorkflow from '@/components/HFJobsWorkflow';
-type Props = {
-  jobConfig: JobConfig;
-  setJobConfig: (value: any, key: string) => void;
-  status: 'idle' | 'saving' | 'success' | 'error';
-  handleSubmit: (event: React.FormEvent<HTMLFormElement>) => void;
-  runId: string | null;
-  gpuIDs: string | null;
-  setGpuIDs: (value: string | null) => void;
-  gpuList: any;
-  datasetOptions: any;
-  trainingBackend?: 'local' | 'hf-jobs';
-  setTrainingBackend?: (backend: 'local' | 'hf-jobs') => void;
-  hfJobSubmitted?: boolean;
-  onHFJobComplete?: (jobId: string, localJobId?: string) => void;
-  forceHFBackend?: boolean;
-};
-const isDev = process.env.NODE_ENV === 'development';
-export default function SimpleJob({
-  jobConfig,
-  setJobConfig,
-  handleSubmit,
-  status,
-  runId,
-  gpuIDs,
-  setGpuIDs,
-  gpuList,
-  datasetOptions,
-  trainingBackend: parentTrainingBackend,
-  setTrainingBackend: parentSetTrainingBackend,
-  hfJobSubmitted,
-  onHFJobComplete,
-  forceHFBackend = false,
-}: Props) {
-  const [localTrainingBackend, setLocalTrainingBackend] = useState(forceHFBackend ? 'hf-jobs' : 'local');
-  const trainingBackend = parentTrainingBackend || localTrainingBackend;
-  const setTrainingBackend = forceHFBackend
-    ? (_: 'local' | 'hf-jobs') => undefined
-    : parentSetTrainingBackend || setLocalTrainingBackend;
-  const backendOptions = forceHFBackend
-    ? [{ value: 'hf-jobs', label: 'HF Jobs (Cloud)' }]
-    : [
-        { value: 'local', label: 'Local GPU' },
-        { value: 'hf-jobs', label: 'HF Jobs (Cloud)' },
-      ];
-  const modelArch = useMemo(() => {
-    return modelArchs.find(a => a.name === jobConfig.config.process[0].model.arch) as ModelArch;
-  }, [jobConfig.config.process[0].model.arch]);
-  const isVideoModel = !!(modelArch?.group === 'video');
-  const numTopCards = useMemo(() => {
-    let count = 4; // job settings, model config, target config, save config
-    if (modelArch?.additionalSections?.includes('model.multistage')) {
-      count += 1; // add multistage card
-    }
-    if (!modelArch?.disableSections?.includes('model.quantize')) {
-      count += 1; // add quantization card
-    }
-    return count;
-  }, [modelArch]);
-  let topBarClass = 'grid grid-cols-1 md:grid-cols-2 lg:grid-cols-4 xl:grid-cols-4 gap-6';
-  if (numTopCards == 5) {
-    topBarClass = 'grid grid-cols-1 md:grid-cols-2 lg:grid-cols-3 xl:grid-cols-5 gap-6';
-  }
-  if (numTopCards == 6) {
-    topBarClass = 'grid grid-cols-1 md:grid-cols-2 lg:grid-cols-3 xl:grid-cols-3 2xl:grid-cols-6 gap-6';
-  }
-  const transformerQuantizationOptions: GroupedSelectOption[] | SelectOption[] = useMemo(() => {
-    const hasARA = modelArch?.accuracyRecoveryAdapters && Object.keys(modelArch.accuracyRecoveryAdapters).length > 0;
-    if (!hasARA) {
-      return quantizationOptions;
-    }
-    let newQuantizationOptions = [
-      {
-        label: 'Standard',
-        options: [quantizationOptions[0], quantizationOptions[1]],
-      },
-    ];
-    // add ARAs if they exist for the model
-    let ARAs: SelectOption[] = [];
-    if (modelArch.accuracyRecoveryAdapters) {
-      for (const [label, value] of Object.entries(modelArch.accuracyRecoveryAdapters)) {
-         ARAs.push({ value, label });
-      }
-    }
-    if (ARAs.length > 0) {
-      newQuantizationOptions.push({
-        label: 'Accuracy Recovery Adapters',
-        options: ARAs,
-      });
-    }
-    let additionalQuantizationOptions: SelectOption[] = [];
-    // add the quantization options if they are not already included
-    for (let i = 2; i < quantizationOptions.length; i++) {
-      const option = quantizationOptions[i];
-      additionalQuantizationOptions.push(option);
-    }
-    if (additionalQuantizationOptions.length > 0) {
-      newQuantizationOptions.push({
-        label: 'Additional Quantization Options',
-        options: additionalQuantizationOptions,
-      });
-    }
-    return newQuantizationOptions;
-  }, [modelArch]);
-  return (
-    <>
-      <form onSubmit={handleSubmit} className="space-y-8">
-        <div className={topBarClass}>
-          <Card title="Job">
-            <TextInput
-              label="Training Name"
-              value={jobConfig.config.name}
-              docKey="config.name"
-              onChange={value => setJobConfig(value, 'config.name')}
-              placeholder="Enter training name"
-              disabled={runId !== null}
-              required
-            />
-            <SelectInput
-              label="Training Backend"
-              value={trainingBackend}
-              onChange={(value) => {
-                setTrainingBackend(value);
-              }}
-              options={backendOptions}
-              disabled={forceHFBackend}
-            />
-            {trainingBackend === 'local' && (
-              <SelectInput
-                label="GPU ID"
-                value={`${gpuIDs}`}
-                docKey="gpuids"
-                onChange={value => setGpuIDs(value)}
-                options={gpuList.map((gpu: any) => ({ value: `${gpu.index}`, label: `GPU #${gpu.index}` }))}
-              />
-            )}
-            <TextInput
-              label="Trigger Word"
-              value={jobConfig.config.process[0].trigger_word || ''}
-              docKey="config.process[0].trigger_word"
-              onChange={(value: string | null) => {
-                if (value?.trim() === '') {
-                  value = null;
-                }
-                setJobConfig(value, 'config.process[0].trigger_word');
-              }}
-              placeholder=""
-              required
-            />
-            {trainingBackend === 'hf-jobs' && (
-              <div className={`mt-4 p-3 rounded ${
-                hfJobSubmitted
-                  ? 'bg-green-900/20 border border-green-700'
-                  : 'bg-yellow-900/20 border border-yellow-700'
-              }`}>
-                <p className={`text-sm ${
-                  hfJobSubmitted ? 'text-green-400' : 'text-yellow-400'
-                }`}>
-                  {hfJobSubmitted
-                    ? '✓ HF Job already submitted! You can modify settings and resubmit if needed.'
-                    : '⏳ HF Job ready for submission. Submit to the cloud below.'
-                  }
-                </p>
-              </div>
-            )}
-          </Card>
-          {/* Model Configuration Section */}
-          <Card title="Model">
-            <SelectInput
-              label="Model Architecture"
-              value={jobConfig.config.process[0].model.arch}
-              onChange={value => {
-                const currentArch = modelArchs.find(a => a.name === jobConfig.config.process[0].model.arch);
-                if (!currentArch || currentArch.name === value) {
-                  return;
-                }
-                // update the defaults when a model is selected
-                const newArch = modelArchs.find(model => model.name === value);
-                // update vram setting
-                if (!newArch?.additionalSections?.includes('model.low_vram')) {
-                  setJobConfig(false, 'config.process[0].model.low_vram');
-                }
-                // revert defaults from previous model
-                for (const key in currentArch.defaults) {
-                  setJobConfig(currentArch.defaults[key][1], key);
-                }
-                if (newArch?.defaults) {
-                  for (const key in newArch.defaults) {
-                    setJobConfig(newArch.defaults[key][0], key);
-                  }
-                }
-                // set new model
-                setJobConfig(value, 'config.process[0].model.arch');
-                // update datasets
-                const hasControlPath = newArch?.additionalSections?.includes('datasets.control_path') || false;
-                const hasNumFrames = newArch?.additionalSections?.includes('datasets.num_frames') || false;
-                const controls = newArch?.controls ?? [];
-                const datasets = jobConfig.config.process[0].datasets.map(dataset => {
-                  const newDataset = objectCopy(dataset);
-                  newDataset.controls = controls;
-                  if (!hasControlPath) {
-                    newDataset.control_path = null; // reset control path if not applicable
-                  }
-                  if (!hasNumFrames) {
-                    newDataset.num_frames = 1; // reset num_frames if not applicable
-                  }
-                  return newDataset;
-                });
-                setJobConfig(datasets, 'config.process[0].datasets');
-                // update samples
-                const hasSampleCtrlImg = newArch?.additionalSections?.includes('sample.ctrl_img') || false;
-                const samples = jobConfig.config.process[0].sample.samples.map(sample => {
-                  const newSample = objectCopy(sample);
-                  if (!hasSampleCtrlImg) {
-                    delete newSample.ctrl_img; // remove ctrl_img if not applicable
-                  }
-                  return newSample;
-                });
-                setJobConfig(samples, 'config.process[0].sample.samples');
-              }}
-              options={groupedModelOptions}
-            />
-            <TextInput
-              label="Name or Path"
-              value={jobConfig.config.process[0].model.name_or_path}
-              docKey="config.process[0].model.name_or_path"
-              onChange={(value: string | null) => {
-                if (value?.trim() === '') {
-                  value = null;
-                }
-                setJobConfig(value, 'config.process[0].model.name_or_path');
-              }}
-              placeholder=""
-              required
-            />
-            {modelArch?.additionalSections?.includes('model.low_vram') && (
-              <FormGroup label="Options">
-                <Checkbox
-                  label="Low VRAM"
-                  checked={jobConfig.config.process[0].model.low_vram}
-                  onChange={value => setJobConfig(value, 'config.process[0].model.low_vram')}
-                />
-              </FormGroup>
-            )}
-          </Card>
-          {modelArch?.disableSections?.includes('model.quantize') ? null : (
-            <Card title="Quantization">
-              <SelectInput
-                label="Transformer"
-                value={jobConfig.config.process[0].model.quantize ? jobConfig.config.process[0].model.qtype : ''}
-                onChange={value => {
-                  if (value === '') {
-                    setJobConfig(false, 'config.process[0].model.quantize');
-                    value = defaultQtype;
-                  } else {
-                    setJobConfig(true, 'config.process[0].model.quantize');
-                  }
-                  setJobConfig(value, 'config.process[0].model.qtype');
-                }}
-                options={transformerQuantizationOptions}
-              />
-              <SelectInput
-                label="Text Encoder"
-                value={jobConfig.config.process[0].model.quantize_te ? jobConfig.config.process[0].model.qtype_te : ''}
-                onChange={value => {
-                  if (value === '') {
-                    setJobConfig(false, 'config.process[0].model.quantize_te');
-                    value = defaultQtype;
-                  } else {
-                    setJobConfig(true, 'config.process[0].model.quantize_te');
-                  }
-                  setJobConfig(value, 'config.process[0].model.qtype_te');
-                }}
-                options={quantizationOptions}
-              />
-            </Card>
-          )}
-          {modelArch?.additionalSections?.includes('model.multistage') && (
-            <Card title="Multistage">
-              <FormGroup label="Stages to Train" docKey={'model.multistage'}>
-                <Checkbox
-                  label="High Noise"
-                  checked={jobConfig.config.process[0].model.model_kwargs?.train_high_noise || false}
-                  onChange={value => setJobConfig(value, 'config.process[0].model.model_kwargs.train_high_noise')}
-                />
-                <Checkbox
-                  label="Low Noise"
-                  checked={jobConfig.config.process[0].model.model_kwargs?.train_low_noise || false}
-                  onChange={value => setJobConfig(value, 'config.process[0].model.model_kwargs.train_low_noise')}
-                />
-              </FormGroup>
-              <NumberInput
-                  label="Switch Every"
-                  value={jobConfig.config.process[0].train.switch_boundary_every}
-                  onChange={value => setJobConfig(value, 'config.process[0].train.switch_boundary_every')}
-                  placeholder="eg. 1"
-                  docKey={'train.switch_boundary_every'}
-                  min={1}
-                  required
-                />
-            </Card>
-          )}
-          <Card title="Target">
-            <SelectInput
-              label="Target Type"
-              value={jobConfig.config.process[0].network?.type ?? 'lora'}
-              onChange={value => setJobConfig(value, 'config.process[0].network.type')}
-              options={[
-                { value: 'lora', label: 'LoRA' },
-                { value: 'lokr', label: 'LoKr' },
-              ]}
-            />
-            {jobConfig.config.process[0].network?.type == 'lokr' && (
-              <SelectInput
-                label="LoKr Factor"
-                value={`${jobConfig.config.process[0].network?.lokr_factor ?? -1}`}
-                onChange={value => setJobConfig(parseInt(value), 'config.process[0].network.lokr_factor')}
-                options={[
-                  { value: '-1', label: 'Auto' },
-                  { value: '4', label: '4' },
-                  { value: '8', label: '8' },
-                  { value: '16', label: '16' },
-                  { value: '32', label: '32' },
-                ]}
-              />
-            )}
-            {jobConfig.config.process[0].network?.type == 'lora' && (
-              <>
-                <NumberInput
-                  label="Linear Rank"
-                  value={jobConfig.config.process[0].network.linear}
-                  onChange={value => {
-                    console.log('onChange', value);
-                    setJobConfig(value, 'config.process[0].network.linear');
-                    setJobConfig(value, 'config.process[0].network.linear_alpha');
-                  }}
-                  placeholder="eg. 16"
-                  min={0}
-                  max={1024}
-                  required
-                />
-                {modelArch?.disableSections?.includes('network.conv') ? null : (
-                  <NumberInput
-                    label="Conv Rank"
-                    value={jobConfig.config.process[0].network.conv}
-                    onChange={value => {
-                      console.log('onChange', value);
-                      setJobConfig(value, 'config.process[0].network.conv');
-                      setJobConfig(value, 'config.process[0].network.conv_alpha');
-                    }}
-                    placeholder="eg. 16"
-                    min={0}
-                    max={1024}
-                  />
-                )}
-              </>
-            )}
-          </Card>
-          <Card title="Save">
-            <SelectInput
-              label="Data Type"
-              value={jobConfig.config.process[0].save.dtype}
-              onChange={value => setJobConfig(value, 'config.process[0].save.dtype')}
-              options={[
-                { value: 'bf16', label: 'BF16' },
-                { value: 'fp16', label: 'FP16' },
-                { value: 'fp32', label: 'FP32' },
-              ]}
-            />
-            <NumberInput
-              label="Save Every"
-              value={jobConfig.config.process[0].save.save_every}
-              onChange={value => setJobConfig(value, 'config.process[0].save.save_every')}
-              placeholder="eg. 250"
-              min={1}
-              required
-            />
-            <NumberInput
-              label="Max Step Saves to Keep"
-              value={jobConfig.config.process[0].save.max_step_saves_to_keep}
-              onChange={value => setJobConfig(value, 'config.process[0].save.max_step_saves_to_keep')}
-              placeholder="eg. 4"
-              min={1}
-              required
-            />
-          </Card>
-        </div>
-        <div>
-          <Card title="Training">
-            <div className="grid grid-cols-1 md:grid-cols-3 lg:grid-cols-5 gap-6">
-              <div>
-                <NumberInput
-                  label="Batch Size"
-                  value={jobConfig.config.process[0].train.batch_size}
-                  onChange={value => setJobConfig(value, 'config.process[0].train.batch_size')}
-                  placeholder="eg. 4"
-                  min={1}
-                  required
-                />
-                <NumberInput
-                  label="Gradient Accumulation"
-                  className="pt-2"
-                  value={jobConfig.config.process[0].train.gradient_accumulation}
-                  onChange={value => setJobConfig(value, 'config.process[0].train.gradient_accumulation')}
-                  placeholder="eg. 1"
-                  min={1}
-                  required
-                />
-                <NumberInput
-                  label="Steps"
-                  className="pt-2"
-                  value={jobConfig.config.process[0].train.steps}
-                  onChange={value => setJobConfig(value, 'config.process[0].train.steps')}
-                  placeholder="eg. 2000"
-                  min={1}
-                  required
-                />
-              </div>
-              <div>
-                <SelectInput
-                  label="Optimizer"
-                  value={jobConfig.config.process[0].train.optimizer}
-                  onChange={value => setJobConfig(value, 'config.process[0].train.optimizer')}
-                  options={[
-                    { value: 'adamw8bit', label: 'AdamW8Bit' },
-                    { value: 'adafactor', label: 'Adafactor' },
-                  ]}
-                />
-                <NumberInput
-                  label="Learning Rate"
-                  className="pt-2"
-                  value={jobConfig.config.process[0].train.lr}
-                  onChange={value => setJobConfig(value, 'config.process[0].train.lr')}
-                  placeholder="eg. 0.0001"
-                  min={0}
-                  required
-                />
-                <NumberInput
-                  label="Weight Decay"
-                  className="pt-2"
-                  value={jobConfig.config.process[0].train.optimizer_params.weight_decay}
-                  onChange={value => setJobConfig(value, 'config.process[0].train.optimizer_params.weight_decay')}
-                  placeholder="eg. 0.0001"
-                  min={0}
-                  required
-                />
-              </div>
-              <div>
-                {modelArch?.disableSections?.includes('train.timestep_type') ? null : (
-                  <SelectInput
-                    label="Timestep Type"
-                    value={jobConfig.config.process[0].train.timestep_type}
-                    disabled={modelArch?.disableSections?.includes('train.timestep_type') || false}
-                    onChange={value => setJobConfig(value, 'config.process[0].train.timestep_type')}
-                    options={[
-                      { value: 'sigmoid', label: 'Sigmoid' },
-                      { value: 'linear', label: 'Linear' },
-                      { value: 'shift', label: 'Shift' },
-                      { value: 'weighted', label: 'Weighted' },
-                    ]}
-                  />
-                )}
-                <SelectInput
-                  label="Timestep Bias"
-                  className="pt-2"
-                  value={jobConfig.config.process[0].train.content_or_style}
-                  onChange={value => setJobConfig(value, 'config.process[0].train.content_or_style')}
-                  options={[
-                    { value: 'balanced', label: 'Balanced' },
-                    { value: 'content', label: 'High Noise' },
-                    { value: 'style', label: 'Low Noise' },
-                  ]}
-                />
-                <SelectInput
-                  label="Noise Scheduler"
-                  className="pt-2"
-                  value={jobConfig.config.process[0].train.noise_scheduler}
-                  onChange={value => setJobConfig(value, 'config.process[0].train.noise_scheduler')}
-                  options={[
-                    { value: 'flowmatch', label: 'FlowMatch' },
-                    { value: 'ddpm', label: 'DDPM' },
-                  ]}
-                />
-              </div>
-              <div>
-                <FormGroup label="EMA (Exponential Moving Average)">
-                  <Checkbox
-                    label="Use EMA"
-                    className="pt-1"
-                    checked={jobConfig.config.process[0].train.ema_config?.use_ema || false}
-                    onChange={value => setJobConfig(value, 'config.process[0].train.ema_config.use_ema')}
-                  />
-                </FormGroup>
-                {jobConfig.config.process[0].train.ema_config?.use_ema && (
-                  <NumberInput
-                    label="EMA Decay"
-                    className="pt-2"
-                    value={jobConfig.config.process[0].train.ema_config?.ema_decay as number}
-                    onChange={value => setJobConfig(value, 'config.process[0].train.ema_config?.ema_decay')}
-                    placeholder="eg. 0.99"
-                    min={0}
-                  />
-                )}
-                <FormGroup label="Text Encoder Optimizations" className="pt-2">
-                  <Checkbox
-                    label="Unload TE"
-                    checked={jobConfig.config.process[0].train.unload_text_encoder || false}
-                    docKey={'train.unload_text_encoder'}
-                    onChange={value => {
-                      setJobConfig(value, 'config.process[0].train.unload_text_encoder');
-                      if (value) {
-                        setJobConfig(false, 'config.process[0].train.cache_text_embeddings');
-                      }
-                    }}
-                  />
-                  <Checkbox
-                    label="Cache Text Embeddings"
-                    checked={jobConfig.config.process[0].train.cache_text_embeddings || false}
-                    docKey={'train.cache_text_embeddings'}
-                    onChange={value => {
-                      setJobConfig(value, 'config.process[0].train.cache_text_embeddings');
-                      if (value) {
-                        setJobConfig(false, 'config.process[0].train.unload_text_encoder');
-                      }
-                    }}
-                  />
-                </FormGroup>
-              </div>
-              <div>
-                <FormGroup label="Regularization">
-                  <Checkbox
-                    label="Differtial Output Preservation"
-                    className="pt-1"
-                    checked={jobConfig.config.process[0].train.diff_output_preservation || false}
-                    onChange={value => setJobConfig(value, 'config.process[0].train.diff_output_preservation')}
-                  />
-                </FormGroup>
-                {jobConfig.config.process[0].train.diff_output_preservation && (
-                  <>
-                    <NumberInput
-                      label="DOP Loss Multiplier"
-                      className="pt-2"
-                      value={jobConfig.config.process[0].train.diff_output_preservation_multiplier as number}
-                      onChange={value =>
-                        setJobConfig(value, 'config.process[0].train.diff_output_preservation_multiplier')
-                      }
-                      placeholder="eg. 1.0"
-                      min={0}
-                    />
-                    <TextInput
-                      label="DOP Preservation Class"
-                      className="pt-2"
-                      value={jobConfig.config.process[0].train.diff_output_preservation_class as string}
-                      onChange={value => setJobConfig(value, 'config.process[0].train.diff_output_preservation_class')}
-                      placeholder="eg. woman"
-                    />
-                  </>
-                )}
-              </div>
-            </div>
-          </Card>
-        </div>
-        <div>
-          <Card title="Datasets">
-            <>
-              {jobConfig.config.process[0].datasets.map((dataset, i) => (
-                <div key={i} className="p-4 rounded-lg bg-gray-800 relative">
-                  <button
-                    type="button"
-                    onClick={() =>
-                      setJobConfig(
-                        jobConfig.config.process[0].datasets.filter((_, index) => index !== i),
-                        'config.process[0].datasets',
-                      )
-                    }
-                    className="absolute top-2 right-2 bg-red-800 hover:bg-red-700 rounded-full p-1 text-sm transition-colors"
-                  >
-                    <X />
-                  </button>
-                  <h2 className="text-lg font-bold mb-4">Dataset {i + 1}</h2>
-                  <div className="grid grid-cols-1 md:grid-cols-2 lg:grid-cols-4 gap-6">
-                    <div>
-                      <SelectInput
-                        label="Dataset"
-                        value={dataset.folder_path}
-                        onChange={value => setJobConfig(value, `config.process[0].datasets[${i}].folder_path`)}
-                        options={datasetOptions}
-                      />
-                      {modelArch?.additionalSections?.includes('datasets.control_path') && (
-                        <SelectInput
-                          label="Control Dataset"
-                          docKey="datasets.control_path"
-                          value={dataset.control_path ?? ''}
-                          className="pt-2"
-                          onChange={value =>
-                            setJobConfig(value == '' ? null : value, `config.process[0].datasets[${i}].control_path`)
-                          }
-                          options={[{ value: '', label: <>&nbsp;</> }, ...datasetOptions]}
-                        />
-                      )}
-                      <NumberInput
-                        label="LoRA Weight"
-                        value={dataset.network_weight}
-                        className="pt-2"
-                        onChange={value => setJobConfig(value, `config.process[0].datasets[${i}].network_weight`)}
-                        placeholder="eg. 1.0"
-                      />
-                    </div>
-                    <div>
-                      <TextInput
-                        label="Default Caption"
-                        value={dataset.default_caption}
-                        onChange={value => setJobConfig(value, `config.process[0].datasets[${i}].default_caption`)}
-                        placeholder="eg. A photo of a cat"
-                      />
-                      <NumberInput
-                        label="Caption Dropout Rate"
-                        className="pt-2"
-                        value={dataset.caption_dropout_rate}
-                        onChange={value => setJobConfig(value, `config.process[0].datasets[${i}].caption_dropout_rate`)}
-                        placeholder="eg. 0.05"
-                        min={0}
-                        required
-                      />
-                      {modelArch?.additionalSections?.includes('datasets.num_frames') && (
-                        <NumberInput
-                          label="Num Frames"
-                          className="pt-2"
-                          docKey="datasets.num_frames"
-                          value={dataset.num_frames}
-                          onChange={value => setJobConfig(value, `config.process[0].datasets[${i}].num_frames`)}
-                          placeholder="eg. 41"
-                          min={1}
-                          required
-                        />
-                      )}
-                    </div>
-                    <div>
-                      <FormGroup label="Settings" className="">
-                        <Checkbox
-                          label="Cache Latents"
-                          checked={dataset.cache_latents_to_disk || false}
-                          onChange={value =>
-                            setJobConfig(value, `config.process[0].datasets[${i}].cache_latents_to_disk`)
-                          }
-                        />
-                        <Checkbox
-                          label="Is Regularization"
-                          checked={dataset.is_reg || false}
-                          onChange={value => setJobConfig(value, `config.process[0].datasets[${i}].is_reg`)}
-                        />
-                        {modelArch?.additionalSections?.includes('datasets.do_i2v') && (
-                          <Checkbox
-                            label="Do I2V"
-                            checked={dataset.do_i2v || false}
-                            onChange={value => setJobConfig(value, `config.process[0].datasets[${i}].do_i2v`)}
-                            docKey="datasets.do_i2v"
-                          />
-                        )}
-                      </FormGroup>
-                      <FormGroup label="Flipping" docKey={'datasets.flip'} className="mt-2">
-                        <Checkbox
-                          label={<>Flip X <FlipHorizontal2 className="inline-block w-4 h-4 ml-1" /></>}
-                          checked={dataset.flip_x || false}
-                          onChange={value => setJobConfig(value, `config.process[0].datasets[${i}].flip_x`)}
-                        />
-                        <Checkbox
-                          label={<>Flip Y <FlipVertical2 className="inline-block w-4 h-4 ml-1" /></>}
-                          checked={dataset.flip_y || false}
-                          onChange={value => setJobConfig(value, `config.process[0].datasets[${i}].flip_y`)}
-                        />
-                      </FormGroup>
-                    </div>
-                    <div>
-                      <FormGroup label="Resolutions" className="pt-2">
-                        <div className="grid grid-cols-2 gap-2">
-                          {[
-                            [256, 512, 768],
-                            [1024, 1280, 1536],
-                          ].map(resGroup => (
-                            <div key={resGroup[0]} className="space-y-2">
-                              {resGroup.map(res => (
-                                <Checkbox
-                                  key={res}
-                                  label={res.toString()}
-                                  checked={dataset.resolution.includes(res)}
-                                  onChange={value => {
-                                    const resolutions = dataset.resolution.includes(res)
-                                      ? dataset.resolution.filter(r => r !== res)
-                                      : [...dataset.resolution, res];
-                                    setJobConfig(resolutions, `config.process[0].datasets[${i}].resolution`);
-                                  }}
-                                />
-                              ))}
-                            </div>
-                          ))}
-                        </div>
-                      </FormGroup>
-                    </div>
-                  </div>
-                </div>
-              ))}
-              <button
-                type="button"
-                onClick={() => {
-                  const newDataset = objectCopy(defaultDatasetConfig);
-                  // automaticallt add the controls for a new dataset
-                  const controls = modelArch?.controls ?? [];
-                  newDataset.controls = controls;
-                  setJobConfig([...jobConfig.config.process[0].datasets, newDataset], 'config.process[0].datasets');
-                }}
-                className="w-full px-4 py-2 bg-gray-700 hover:bg-gray-600 rounded-lg transition-colors"
-              >
-                Add Dataset
-              </button>
-            </>
-          </Card>
-        </div>
-        <div>
-          <Card title="Sample">
-            <div
-              className={
-                isVideoModel
-                  ? 'grid grid-cols-1 md:grid-cols-3 lg:grid-cols-5 gap-6'
-                  : 'grid grid-cols-1 md:grid-cols-2 lg:grid-cols-4 gap-6'
-              }
-            >
-              <div>
-                <NumberInput
-                  label="Sample Every"
-                  value={jobConfig.config.process[0].sample.sample_every}
-                  onChange={value => setJobConfig(value, 'config.process[0].sample.sample_every')}
-                  placeholder="eg. 250"
-                  min={1}
-                  required
-                />
-                <SelectInput
-                  label="Sampler"
-                  className="pt-2"
-                  value={jobConfig.config.process[0].sample.sampler}
-                  onChange={value => setJobConfig(value, 'config.process[0].sample.sampler')}
-                  options={[
-                    { value: 'flowmatch', label: 'FlowMatch' },
-                    { value: 'ddpm', label: 'DDPM' },
-                  ]}
-                />
-                <NumberInput
-                  label="Guidance Scale"
-                  value={jobConfig.config.process[0].sample.guidance_scale}
-                  onChange={value => setJobConfig(value, 'config.process[0].sample.guidance_scale')}
-                  placeholder="eg. 1.0"
-                  className="pt-2"
-                  min={0}
-                  required
-                />
-                <NumberInput
-                  label="Sample Steps"
-                  value={jobConfig.config.process[0].sample.sample_steps}
-                  onChange={value => setJobConfig(value, 'config.process[0].sample.sample_steps')}
-                  placeholder="eg. 1"
-                  className="pt-2"
-                  min={1}
-                  required
-                />
-              </div>
-              <div>
-                <NumberInput
-                  label="Width"
-                  value={jobConfig.config.process[0].sample.width}
-                  onChange={value => setJobConfig(value, 'config.process[0].sample.width')}
-                  placeholder="eg. 1024"
-                  min={0}
-                  required
-                />
-                <NumberInput
-                  label="Height"
-                  value={jobConfig.config.process[0].sample.height}
-                  onChange={value => setJobConfig(value, 'config.process[0].sample.height')}
-                  placeholder="eg. 1024"
-                  className="pt-2"
-                  min={0}
-                  required
-                />
-                {isVideoModel && (
-                  <div>
-                    <NumberInput
-                      label="Num Frames"
-                      value={jobConfig.config.process[0].sample.num_frames}
-                      onChange={value => setJobConfig(value, 'config.process[0].sample.num_frames')}
-                      placeholder="eg. 0"
-                      className="pt-2"
-                      min={0}
-                      required
-                    />
-                    <NumberInput
-                      label="FPS"
-                      value={jobConfig.config.process[0].sample.fps}
-                      onChange={value => setJobConfig(value, 'config.process[0].sample.fps')}
-                      placeholder="eg. 0"
-                      className="pt-2"
-                      min={0}
-                      required
-                    />
-                  </div>
-                )}
-              </div>
-              <div>
-                <NumberInput
-                  label="Seed"
-                  value={jobConfig.config.process[0].sample.seed}
-                  onChange={value => setJobConfig(value, 'config.process[0].sample.seed')}
-                  placeholder="eg. 0"
-                  min={0}
-                  required
-                />
-                <Checkbox
-                  label="Walk Seed"
-                  className="pt-4 pl-2"
-                  checked={jobConfig.config.process[0].sample.walk_seed}
-                  onChange={value => setJobConfig(value, 'config.process[0].sample.walk_seed')}
-                />
-              </div>
-              <div>
-                <FormGroup label="Advanced Sampling" className="pt-2">
-                  <div>
-                    <Checkbox
-                      label="Skip First Sample"
-                      className="pt-4"
-                      checked={jobConfig.config.process[0].train.skip_first_sample || false}
-                      onChange={value => setJobConfig(value, 'config.process[0].train.skip_first_sample')}
-                    />
-                  </div>
-                  <div>
-                    <Checkbox
-                      label="Disable Sampling"
-                      className="pt-1"
-                      checked={jobConfig.config.process[0].train.disable_sampling || false}
-                      onChange={value => setJobConfig(value, 'config.process[0].train.disable_sampling')}
-                    />
-                  </div>
-                </FormGroup>
-              </div>
-            </div>
-            <FormGroup label={`Sample Prompts (${jobConfig.config.process[0].sample.samples.length})`} className="pt-2">
-              <div></div>
-            </FormGroup>
-            {jobConfig.config.process[0].sample.samples.map((sample, i) => (
-              <div key={i} className="rounded-lg pl-4 pr-1 mb-4 bg-gray-950">
-                <div className="flex items-center space-x-2">
-                  <div className="flex-1">
-                    <div className="flex">
-                      <div className="flex-1">
-                        <TextInput
-                          label={`Prompt`}
-                          value={sample.prompt}
-                          onChange={value => setJobConfig(value, `config.process[0].sample.samples[${i}].prompt`)}
-                          placeholder="Enter prompt"
-                          required
-                        />
-                      </div>
-                      {modelArch?.additionalSections?.includes('sample.ctrl_img') && (
-                        <div
-                          className="h-14 w-14 mt-2 ml-4 border border-gray-500 flex items-center justify-center rounded cursor-pointer hover:bg-gray-700 transition-colors"
-                          style={{
-                            backgroundImage: sample.ctrl_img
-                              ? `url(${`/api/img/${encodeURIComponent(sample.ctrl_img)}`})`
-                              : 'none',
-                            backgroundSize: 'cover',
-                            backgroundPosition: 'center',
-                            marginBottom: '-1rem',
-                          }}
-                          onClick={() => {
-                            openAddImageModal(imagePath => {
-                              console.log('Selected image path:', imagePath);
-                              if (!imagePath) return;
-                              setJobConfig(imagePath, `config.process[0].sample.samples[${i}].ctrl_img`);
-                            });
-                          }}
-                        >
-                          {!sample.ctrl_img && (
-                            <div className="text-gray-400 text-xs text-center font-bold">Add Control Image</div>
-                          )}
-                        </div>
-                      )}
-                    </div>
-                    <div className="pb-4"></div>
-                  </div>
-                  <div>
-                    <button
-                      type="button"
-                      onClick={() =>
-                        setJobConfig(
-                          jobConfig.config.process[0].sample.samples.filter((_, index) => index !== i),
-                          'config.process[0].sample.samples',
-                        )
-                      }
-                      className="rounded-full p-1 text-sm"
-                    >
-                      <X />
-                    </button>
-                  </div>
-                </div>
-              </div>
-            ))}
-            <button
-              type="button"
-              onClick={() =>
-                setJobConfig(
-                  [...jobConfig.config.process[0].sample.samples, { prompt: '' }],
-                  'config.process[0].sample.samples',
-                )
-              }
-              className="w-full px-4 py-2 bg-gray-700 hover:bg-gray-600 rounded-lg transition-colors"
-            >
-              Add Prompt
-            </button>
-          </Card>
-        </div>
-        {status === 'success' && <p className="text-green-500 text-center">Training saved successfully!</p>}
-        {status === 'error' && <p className="text-red-500 text-center">Error saving training. Please try again.</p>}
-      </form>
-      {trainingBackend === 'hf-jobs' && (
-        <div className="mt-8">
-          <HFJobsWorkflow
-            jobConfig={jobConfig}
-            onComplete={(jobId, localJobId) => {
-              console.log('HF Job submitted:', jobId, 'Local job ID:', localJobId);
-              if (onHFJobComplete) {
-                onHFJobComplete(jobId, localJobId);
-              }
-            }}
-          />
-        </div>
-      )}
-      <AddSingleImageModal />
-    </>
-  );
-}

src/app/jobs/new/jobConfig.ts DELETED Viewed

@@ -1,167 +0,0 @@
-import { JobConfig, DatasetConfig } from '@/types';
-export const defaultDatasetConfig: DatasetConfig = {
-  folder_path: '/path/to/images/folder',
-  control_path: null,
-  mask_path: null,
-  mask_min_value: 0.1,
-  default_caption: '',
-  caption_ext: 'txt',
-  caption_dropout_rate: 0.05,
-  cache_latents_to_disk: false,
-  is_reg: false,
-  network_weight: 1,
-  resolution: [512, 768, 1024],
-  controls: [],
-  shrink_video_to_frames: true,
-  num_frames: 1,
-  do_i2v: true,
-  flip_x: false,
-  flip_y: false,
-};
-export const defaultJobConfig: JobConfig = {
-  job: 'extension',
-  config: {
-    name: 'my_first_lora_v1',
-    process: [
-      {
-        type: 'ui_trainer',
-        training_folder: 'output',
-        sqlite_db_path: './aitk_db.db',
-        device: 'cuda',
-        trigger_word: null,
-        performance_log_every: 10,
-        network: {
-          type: 'lora',
-          linear: 32,
-          linear_alpha: 32,
-          conv: 16,
-          conv_alpha: 16,
-          lokr_full_rank: true,
-          lokr_factor: -1,
-          network_kwargs: {
-            ignore_if_contains: [],
-          },
-        },
-        save: {
-          dtype: 'bf16',
-          save_every: 250,
-          max_step_saves_to_keep: 4,
-          save_format: 'diffusers',
-          push_to_hub: false,
-        },
-        datasets: [defaultDatasetConfig],
-        train: {
-          batch_size: 1,
-          bypass_guidance_embedding: true,
-          steps: 3000,
-          gradient_accumulation: 1,
-          train_unet: true,
-          train_text_encoder: false,
-          gradient_checkpointing: true,
-          noise_scheduler: 'flowmatch',
-          optimizer: 'adamw8bit',
-          timestep_type: 'sigmoid',
-          content_or_style: 'balanced',
-          optimizer_params: {
-            weight_decay: 1e-4,
-          },
-          unload_text_encoder: false,
-          cache_text_embeddings: false,
-          lr: 0.0001,
-          ema_config: {
-            use_ema: false,
-            ema_decay: 0.99,
-          },
-          skip_first_sample: false,
-          disable_sampling: false,
-          dtype: 'bf16',
-          diff_output_preservation: false,
-          diff_output_preservation_multiplier: 1.0,
-          diff_output_preservation_class: 'person',
-          switch_boundary_every: 1,
-        },
-        model: {
-          name_or_path: 'ostris/Flex.1-alpha',
-          quantize: true,
-          qtype: 'qfloat8',
-          quantize_te: true,
-          qtype_te: 'qfloat8',
-          arch: 'flex1',
-          low_vram: false,
-          model_kwargs: {},
-        },
-        sample: {
-          sampler: 'flowmatch',
-          sample_every: 250,
-          width: 1024,
-          height: 1024,
-          samples: [
-            {
-              prompt: 'woman with red hair, playing chess at the park, bomb going off in the background'
-            },
-            {
-              prompt: 'a woman holding a coffee cup, in a beanie, sitting at a cafe',
-            },
-            {
-              prompt: 'a horse is a DJ at a night club, fish eye lens, smoke machine, lazer lights, holding a martini',
-            },
-            {
-              prompt: 'a man showing off his cool new t shirt at the beach, a shark is jumping out of the water in the background',
-            },
-            {
-              prompt: 'a bear building a log cabin in the snow covered mountains',
-            },
-            {
-              prompt: 'woman playing the guitar, on stage, singing a song, laser lights, punk rocker',
-            },
-            {
-              prompt: 'hipster man with a beard, building a chair, in a wood shop',
-            },
-            {
-              prompt: 'photo of a man, white background, medium shot, modeling clothing, studio lighting, white backdrop',
-            },
-            {
-              prompt: "a man holding a sign that says, 'this is a sign'",
-            },
-            {
-              prompt: 'a bulldog, in a post apocalyptic world, with a shotgun, in a leather jacket, in a desert, with a motorcycle',
-            },
-          ],
-          neg: '',
-          seed: 42,
-          walk_seed: true,
-          guidance_scale: 4,
-          sample_steps: 25,
-          num_frames: 1,
-          fps: 1,
-        },
-      },
-    ],
-  },
-  meta: {
-    name: '[name]',
-    version: '1.0',
-  },
-};
-export const migrateJobConfig = (jobConfig: JobConfig): JobConfig => {
-  // upgrade prompt strings to samples
-  if (
-    jobConfig?.config?.process &&
-    jobConfig.config.process[0]?.sample &&
-    Array.isArray(jobConfig.config.process[0].sample.prompts) &&
-    jobConfig.config.process[0].sample.prompts.length > 0
-  ) {
-    let newSamples = [];
-    for (const prompt of jobConfig.config.process[0].sample.prompts) {
-      newSamples.push({
-        prompt: prompt,
-      });
-    }
-    jobConfig.config.process[0].sample.samples = newSamples;
-    delete jobConfig.config.process[0].sample.prompts;
-  }
-  return jobConfig;
-};

src/app/jobs/new/options.ts DELETED Viewed

@@ -1,441 +0,0 @@
-import { GroupedSelectOption, SelectOption } from '@/types';
-type Control = 'depth' | 'line' | 'pose' | 'inpaint';
-type DisableableSections = 'model.quantize' | 'train.timestep_type' | 'network.conv';
-type AdditionalSections =
-  | 'datasets.control_path'
-  | 'datasets.do_i2v'
-  | 'sample.ctrl_img'
-  | 'datasets.num_frames'
-  | 'model.multistage'
-  | 'model.low_vram';
-type ModelGroup = 'image' | 'instruction' | 'video';
-export interface ModelArch {
-  name: string;
-  label: string;
-  group: ModelGroup;
-  controls?: Control[];
-  isVideoModel?: boolean;
-  defaults?: { [key: string]: any };
-  disableSections?: DisableableSections[];
-  additionalSections?: AdditionalSections[];
-  accuracyRecoveryAdapters?: { [key: string]: string };
-}
-const defaultNameOrPath = '';
-export const modelArchs: ModelArch[] = [
-  {
-    name: 'flux',
-    label: 'FLUX.1',
-    group: 'image',
-    defaults: {
-      // default updates when [selected, unselected] in the UI
-      'config.process[0].model.name_or_path': ['black-forest-labs/FLUX.1-dev', defaultNameOrPath],
-      'config.process[0].model.quantize': [true, false],
-      'config.process[0].model.quantize_te': [true, false],
-      'config.process[0].sample.sampler': ['flowmatch', 'flowmatch'],
-      'config.process[0].train.noise_scheduler': ['flowmatch', 'flowmatch'],
-    },
-    disableSections: ['network.conv'],
-  },
-  {
-    name: 'flux_kontext',
-    label: 'FLUX.1-Kontext-dev',
-    group: 'instruction',
-    defaults: {
-      // default updates when [selected, unselected] in the UI
-      'config.process[0].model.name_or_path': ['black-forest-labs/FLUX.1-Kontext-dev', defaultNameOrPath],
-      'config.process[0].model.quantize': [true, false],
-      'config.process[0].model.quantize_te': [true, false],
-      'config.process[0].sample.sampler': ['flowmatch', 'flowmatch'],
-      'config.process[0].train.noise_scheduler': ['flowmatch', 'flowmatch'],
-      'config.process[0].train.timestep_type': ['weighted', 'sigmoid'],
-    },
-    disableSections: ['network.conv'],
-    additionalSections: ['datasets.control_path', 'sample.ctrl_img'],
-  },
-  {
-    name: 'flex1',
-    label: 'Flex.1',
-    group: 'image',
-    defaults: {
-      // default updates when [selected, unselected] in the UI
-      'config.process[0].model.name_or_path': ['ostris/Flex.1-alpha', defaultNameOrPath],
-      'config.process[0].model.quantize': [true, false],
-      'config.process[0].model.quantize_te': [true, false],
-      'config.process[0].train.bypass_guidance_embedding': [true, false],
-      'config.process[0].sample.sampler': ['flowmatch', 'flowmatch'],
-      'config.process[0].train.noise_scheduler': ['flowmatch', 'flowmatch'],
-    },
-    disableSections: ['network.conv'],
-  },
-  {
-    name: 'flex2',
-    label: 'Flex.2',
-    group: 'image',
-    controls: ['depth', 'line', 'pose', 'inpaint'],
-    defaults: {
-      // default updates when [selected, unselected] in the UI
-      'config.process[0].model.name_or_path': ['ostris/Flex.2-preview', defaultNameOrPath],
-      'config.process[0].model.quantize': [true, false],
-      'config.process[0].model.quantize_te': [true, false],
-      'config.process[0].model.model_kwargs': [
-        {
-          invert_inpaint_mask_chance: 0.2,
-          inpaint_dropout: 0.5,
-          control_dropout: 0.5,
-          inpaint_random_chance: 0.2,
-          do_random_inpainting: true,
-          random_blur_mask: true,
-          random_dialate_mask: true,
-        },
-        {},
-      ],
-      'config.process[0].train.bypass_guidance_embedding': [true, false],
-      'config.process[0].sample.sampler': ['flowmatch', 'flowmatch'],
-      'config.process[0].train.noise_scheduler': ['flowmatch', 'flowmatch'],
-    },
-    disableSections: ['network.conv'],
-  },
-  {
-    name: 'chroma',
-    label: 'Chroma',
-    group: 'image',
-    defaults: {
-      // default updates when [selected, unselected] in the UI
-      'config.process[0].model.name_or_path': ['lodestones/Chroma1-Base', defaultNameOrPath],
-      'config.process[0].model.quantize': [true, false],
-      'config.process[0].model.quantize_te': [true, false],
-      'config.process[0].sample.sampler': ['flowmatch', 'flowmatch'],
-      'config.process[0].train.noise_scheduler': ['flowmatch', 'flowmatch'],
-    },
-    disableSections: ['network.conv'],
-  },
-  {
-    name: 'wan21:1b',
-    label: 'Wan 2.1 (1.3B)',
-    group: 'video',
-    isVideoModel: true,
-    defaults: {
-      // default updates when [selected, unselected] in the UI
-      'config.process[0].model.name_or_path': ['Wan-AI/Wan2.1-T2V-1.3B-Diffusers', defaultNameOrPath],
-      'config.process[0].model.quantize': [false, false],
-      'config.process[0].model.quantize_te': [true, false],
-      'config.process[0].sample.sampler': ['flowmatch', 'flowmatch'],
-      'config.process[0].train.noise_scheduler': ['flowmatch', 'flowmatch'],
-      'config.process[0].sample.num_frames': [41, 1],
-      'config.process[0].sample.fps': [16, 1],
-    },
-    disableSections: ['network.conv'],
-    additionalSections: ['datasets.num_frames', 'model.low_vram'],
-  },
-  {
-    name: 'wan21_i2v:14b480p',
-    label: 'Wan 2.1 I2V (14B-480P)',
-    group: 'video',
-    isVideoModel: true,
-    defaults: {
-      // default updates when [selected, unselected] in the UI
-      'config.process[0].model.name_or_path': ['Wan-AI/Wan2.1-I2V-14B-480P-Diffusers', defaultNameOrPath],
-      'config.process[0].model.quantize': [true, false],
-      'config.process[0].model.quantize_te': [true, false],
-      'config.process[0].sample.sampler': ['flowmatch', 'flowmatch'],
-      'config.process[0].train.noise_scheduler': ['flowmatch', 'flowmatch'],
-      'config.process[0].sample.num_frames': [41, 1],
-      'config.process[0].sample.fps': [16, 1],
-      'config.process[0].train.timestep_type': ['weighted', 'sigmoid'],
-    },
-    disableSections: ['network.conv'],
-    additionalSections: ['sample.ctrl_img', 'datasets.num_frames', 'model.low_vram'],
-  },
-  {
-    name: 'wan21_i2v:14b',
-    label: 'Wan 2.1 I2V (14B-720P)',
-    group: 'video',
-    isVideoModel: true,
-    defaults: {
-      // default updates when [selected, unselected] in the UI
-      'config.process[0].model.name_or_path': ['Wan-AI/Wan2.1-I2V-14B-720P-Diffusers', defaultNameOrPath],
-      'config.process[0].model.quantize': [true, false],
-      'config.process[0].model.quantize_te': [true, false],
-      'config.process[0].sample.sampler': ['flowmatch', 'flowmatch'],
-      'config.process[0].train.noise_scheduler': ['flowmatch', 'flowmatch'],
-      'config.process[0].sample.num_frames': [41, 1],
-      'config.process[0].sample.fps': [16, 1],
-      'config.process[0].train.timestep_type': ['weighted', 'sigmoid'],
-    },
-    disableSections: ['network.conv'],
-    additionalSections: ['sample.ctrl_img', 'datasets.num_frames', 'model.low_vram'],
-  },
-  {
-    name: 'wan21:14b',
-    label: 'Wan 2.1 (14B)',
-    group: 'video',
-    isVideoModel: true,
-    defaults: {
-      // default updates when [selected, unselected] in the UI
-      'config.process[0].model.name_or_path': ['Wan-AI/Wan2.1-T2V-14B-Diffusers', defaultNameOrPath],
-      'config.process[0].model.quantize': [true, false],
-      'config.process[0].model.quantize_te': [true, false],
-      'config.process[0].sample.sampler': ['flowmatch', 'flowmatch'],
-      'config.process[0].train.noise_scheduler': ['flowmatch', 'flowmatch'],
-      'config.process[0].sample.num_frames': [41, 1],
-      'config.process[0].sample.fps': [16, 1],
-    },
-    disableSections: ['network.conv'],
-    additionalSections: ['datasets.num_frames', 'model.low_vram'],
-  },
-  {
-    name: 'wan22_14b:t2v',
-    label: 'Wan 2.2 (14B)',
-    group: 'video',
-    isVideoModel: true,
-    defaults: {
-      // default updates when [selected, unselected] in the UI
-      'config.process[0].model.name_or_path': ['ai-toolkit/Wan2.2-T2V-A14B-Diffusers-bf16', defaultNameOrPath],
-      'config.process[0].model.quantize': [true, false],
-      'config.process[0].model.quantize_te': [true, false],
-      'config.process[0].sample.sampler': ['flowmatch', 'flowmatch'],
-      'config.process[0].train.noise_scheduler': ['flowmatch', 'flowmatch'],
-      'config.process[0].sample.num_frames': [41, 1],
-      'config.process[0].sample.fps': [16, 1],
-      'config.process[0].model.low_vram': [true, false],
-      'config.process[0].train.timestep_type': ['linear', 'sigmoid'],
-      'config.process[0].model.model_kwargs': [
-        {
-          train_high_noise: true,
-          train_low_noise: true,
-        },
-        {},
-      ],
-    },
-    disableSections: ['network.conv'],
-    additionalSections: ['datasets.num_frames', 'model.low_vram', 'model.multistage'],
-    accuracyRecoveryAdapters: {
-      // '3 bit with ARA': 'uint3|ostris/accuracy_recovery_adapters/wan22_14b_t2i_torchao_uint3.safetensors',
-      '4 bit with ARA': 'uint4|ostris/accuracy_recovery_adapters/wan22_14b_t2i_torchao_uint4.safetensors',
-    },
-  },
-  {
-    name: 'wan22_14b_i2v',
-    label: 'Wan 2.2 I2V (14B)',
-    group: 'video',
-    isVideoModel: true,
-    defaults: {
-      // default updates when [selected, unselected] in the UI
-      'config.process[0].model.name_or_path': ['ai-toolkit/Wan2.2-I2V-A14B-Diffusers-bf16', defaultNameOrPath],
-      'config.process[0].model.quantize': [true, false],
-      'config.process[0].model.quantize_te': [true, false],
-      'config.process[0].sample.sampler': ['flowmatch', 'flowmatch'],
-      'config.process[0].train.noise_scheduler': ['flowmatch', 'flowmatch'],
-      'config.process[0].sample.num_frames': [41, 1],
-      'config.process[0].sample.fps': [16, 1],
-      'config.process[0].model.low_vram': [true, false],
-      'config.process[0].train.timestep_type': ['linear', 'sigmoid'],
-      'config.process[0].model.model_kwargs': [
-        {
-          train_high_noise: true,
-          train_low_noise: true,
-        },
-        {},
-      ],
-    },
-    disableSections: ['network.conv'],
-    additionalSections: ['sample.ctrl_img', 'datasets.num_frames', 'model.low_vram', 'model.multistage'],
-    accuracyRecoveryAdapters: {
-      '4 bit with ARA': 'uint4|ostris/accuracy_recovery_adapters/wan22_14b_i2v_torchao_uint4.safetensors',
-    },
-  },
-  {
-    name: 'wan22_5b',
-    label: 'Wan 2.2 TI2V (5B)',
-    group: 'video',
-    isVideoModel: true,
-    defaults: {
-      // default updates when [selected, unselected] in the UI
-      'config.process[0].model.name_or_path': ['Wan-AI/Wan2.2-TI2V-5B-Diffusers', defaultNameOrPath],
-      'config.process[0].model.quantize': [true, false],
-      'config.process[0].model.quantize_te': [true, false],
-      'config.process[0].model.low_vram': [true, false],
-      'config.process[0].sample.sampler': ['flowmatch', 'flowmatch'],
-      'config.process[0].train.noise_scheduler': ['flowmatch', 'flowmatch'],
-      'config.process[0].sample.num_frames': [121, 1],
-      'config.process[0].sample.fps': [24, 1],
-      'config.process[0].sample.width': [768, 1024],
-      'config.process[0].sample.height': [768, 1024],
-      'config.process[0].train.timestep_type': ['weighted', 'sigmoid'],
-    },
-    disableSections: ['network.conv'],
-    additionalSections: ['sample.ctrl_img', 'datasets.num_frames', 'model.low_vram', 'datasets.do_i2v'],
-  },
-  {
-    name: 'lumina2',
-    label: 'Lumina2',
-    group: 'image',
-    defaults: {
-      // default updates when [selected, unselected] in the UI
-      'config.process[0].model.name_or_path': ['Alpha-VLLM/Lumina-Image-2.0', defaultNameOrPath],
-      'config.process[0].model.quantize': [false, false],
-      'config.process[0].model.quantize_te': [true, false],
-      'config.process[0].sample.sampler': ['flowmatch', 'flowmatch'],
-      'config.process[0].train.noise_scheduler': ['flowmatch', 'flowmatch'],
-    },
-    disableSections: ['network.conv'],
-  },
-  {
-    name: 'qwen_image',
-    label: 'Qwen-Image',
-    group: 'image',
-    defaults: {
-      // default updates when [selected, unselected] in the UI
-      'config.process[0].model.name_or_path': ['Qwen/Qwen-Image', defaultNameOrPath],
-      'config.process[0].model.quantize': [true, false],
-      'config.process[0].model.quantize_te': [true, false],
-      'config.process[0].model.low_vram': [true, false],
-      'config.process[0].sample.sampler': ['flowmatch', 'flowmatch'],
-      'config.process[0].train.noise_scheduler': ['flowmatch', 'flowmatch'],
-      'config.process[0].train.timestep_type': ['weighted', 'sigmoid'],
-      'config.process[0].model.qtype': ['qfloat8', 'qfloat8'],
-    },
-    disableSections: ['network.conv'],
-    additionalSections: ['model.low_vram'],
-    accuracyRecoveryAdapters: {
-      '3 bit with ARA': 'uint3|ostris/accuracy_recovery_adapters/qwen_image_torchao_uint3.safetensors',
-    },
-  },
-  {
-    name: 'qwen_image_edit',
-    label: 'Qwen-Image-Edit',
-    group: 'instruction',
-    defaults: {
-      // default updates when [selected, unselected] in the UI
-      'config.process[0].model.name_or_path': ['Qwen/Qwen-Image-Edit', defaultNameOrPath],
-      'config.process[0].model.quantize': [true, false],
-      'config.process[0].model.quantize_te': [true, false],
-      'config.process[0].model.low_vram': [true, false],
-      'config.process[0].sample.sampler': ['flowmatch', 'flowmatch'],
-      'config.process[0].train.noise_scheduler': ['flowmatch', 'flowmatch'],
-      'config.process[0].train.timestep_type': ['weighted', 'sigmoid'],
-      'config.process[0].model.qtype': ['qfloat8', 'qfloat8'],
-    },
-    disableSections: ['network.conv'],
-    additionalSections: ['datasets.control_path', 'sample.ctrl_img', 'model.low_vram'],
-    accuracyRecoveryAdapters: {
-      '3 bit with ARA': 'uint3|ostris/accuracy_recovery_adapters/qwen_image_edit_torchao_uint3.safetensors',
-    },
-  },
-  {
-    name: 'hidream',
-    label: 'HiDream',
-    group: 'image',
-    defaults: {
-      // default updates when [selected, unselected] in the UI
-      'config.process[0].model.name_or_path': ['HiDream-ai/HiDream-I1-Full', defaultNameOrPath],
-      'config.process[0].model.quantize': [true, false],
-      'config.process[0].model.quantize_te': [true, false],
-      'config.process[0].sample.sampler': ['flowmatch', 'flowmatch'],
-      'config.process[0].train.noise_scheduler': ['flowmatch', 'flowmatch'],
-      'config.process[0].train.lr': [0.0002, 0.0001],
-      'config.process[0].train.timestep_type': ['shift', 'sigmoid'],
-      'config.process[0].network.network_kwargs.ignore_if_contains': [['ff_i.experts', 'ff_i.gate'], []],
-    },
-    disableSections: ['network.conv'],
-    additionalSections: ['model.low_vram'],
-  },
-  {
-    name: 'hidream_e1',
-    label: 'HiDream E1',
-    group: 'instruction',
-    defaults: {
-      // default updates when [selected, unselected] in the UI
-      'config.process[0].model.name_or_path': ['HiDream-ai/HiDream-E1-1', defaultNameOrPath],
-      'config.process[0].model.quantize': [true, false],
-      'config.process[0].model.quantize_te': [true, false],
-      'config.process[0].sample.sampler': ['flowmatch', 'flowmatch'],
-      'config.process[0].train.noise_scheduler': ['flowmatch', 'flowmatch'],
-      'config.process[0].train.lr': [0.0001, 0.0001],
-      'config.process[0].train.timestep_type': ['weighted', 'sigmoid'],
-      'config.process[0].network.network_kwargs.ignore_if_contains': [['ff_i.experts', 'ff_i.gate'], []],
-    },
-    disableSections: ['network.conv'],
-    additionalSections: ['datasets.control_path', 'sample.ctrl_img', 'model.low_vram'],
-  },
-  {
-    name: 'sdxl',
-    label: 'SDXL',
-    group: 'image',
-    defaults: {
-      // default updates when [selected, unselected] in the UI
-      'config.process[0].model.name_or_path': ['stabilityai/stable-diffusion-xl-base-1.0', defaultNameOrPath],
-      'config.process[0].model.quantize': [false, false],
-      'config.process[0].model.quantize_te': [false, false],
-      'config.process[0].sample.sampler': ['ddpm', 'flowmatch'],
-      'config.process[0].train.noise_scheduler': ['ddpm', 'flowmatch'],
-      'config.process[0].sample.guidance_scale': [6, 4],
-    },
-    disableSections: ['model.quantize', 'train.timestep_type'],
-  },
-  {
-    name: 'sd15',
-    label: 'SD 1.5',
-    group: 'image',
-    defaults: {
-      // default updates when [selected, unselected] in the UI
-      'config.process[0].model.name_or_path': ['stable-diffusion-v1-5/stable-diffusion-v1-5', defaultNameOrPath],
-      'config.process[0].sample.sampler': ['ddpm', 'flowmatch'],
-      'config.process[0].train.noise_scheduler': ['ddpm', 'flowmatch'],
-      'config.process[0].sample.width': [512, 1024],
-      'config.process[0].sample.height': [512, 1024],
-      'config.process[0].sample.guidance_scale': [6, 4],
-    },
-    disableSections: ['model.quantize', 'train.timestep_type'],
-  },
-  {
-    name: 'omnigen2',
-    label: 'OmniGen2',
-    group: 'image',
-    defaults: {
-      // default updates when [selected, unselected] in the UI
-      'config.process[0].model.name_or_path': ['OmniGen2/OmniGen2', defaultNameOrPath],
-      'config.process[0].sample.sampler': ['flowmatch', 'flowmatch'],
-      'config.process[0].train.noise_scheduler': ['flowmatch', 'flowmatch'],
-      'config.process[0].model.quantize': [false, false],
-      'config.process[0].model.quantize_te': [true, false],
-    },
-    disableSections: ['network.conv'],
-    additionalSections: ['datasets.control_path', 'sample.ctrl_img'],
-  },
-].sort((a, b) => {
-  // Sort by label, case-insensitive
-  return a.label.localeCompare(b.label, undefined, { sensitivity: 'base' });
-}) as any;
-export const groupedModelOptions: GroupedSelectOption[] = modelArchs.reduce((acc, arch) => {
-  const group = acc.find(g => g.label === arch.group);
-  if (group) {
-    group.options.push({ value: arch.name, label: arch.label });
-  } else {
-    acc.push({
-      label: arch.group,
-      options: [{ value: arch.name, label: arch.label }],
-    });
-  }
-  return acc;
-}, [] as GroupedSelectOption[]);
-export const quantizationOptions: SelectOption[] = [
-  { value: '', label: '- NONE -' },
-  { value: 'qfloat8', label: 'float8 (default)' },
-  { value: 'uint8', label: '8 bit' },
-  { value: 'uint7', label: '7 bit' },
-  { value: 'uint6', label: '6 bit' },
-  { value: 'uint5', label: '5 bit' },
-  { value: 'uint4', label: '4 bit' },
-  { value: 'uint3', label: '3 bit' },
-  { value: 'uint2', label: '2 bit' },
-];
-export const defaultQtype = 'qfloat8';

src/app/jobs/new/page.tsx DELETED Viewed

@@ -1,306 +0,0 @@
-'use client';
-import { useEffect, useState } from 'react';
-import { useSearchParams, useRouter } from 'next/navigation';
-import Link from 'next/link';
-import { defaultJobConfig, defaultDatasetConfig, migrateJobConfig } from './jobConfig';
-import { JobConfig } from '@/types';
-import { objectCopy } from '@/utils/basic';
-import { useNestedState } from '@/utils/hooks';
-import { SelectInput } from '@/components/formInputs';
-import useSettings from '@/hooks/useSettings';
-import useGPUInfo from '@/hooks/useGPUInfo';
-import useDatasetList from '@/hooks/useDatasetList';
-import path from 'path';
-import { TopBar, MainContent } from '@/components/layout';
-import { Button } from '@headlessui/react';
-import { FaChevronLeft } from 'react-icons/fa';
-import SimpleJob from './SimpleJob';
-import AdvancedJob from './AdvancedJob';
-import ErrorBoundary from '@/components/ErrorBoundary';
-import { getJob, upsertJob } from '@/utils/storage/jobStorage';
-import { usingBrowserDb } from '@/utils/env';
-import { getUserDatasetPath, updateUserDatasetPath } from '@/utils/storage/datasetStorage';
-import { apiClient } from '@/utils/api';
-import { useAuth } from '@/contexts/AuthContext';
-import HFLoginButton from '@/components/HFLoginButton';
-const isDev = process.env.NODE_ENV === 'development';
-export default function TrainingForm() {
-  const router = useRouter();
-  const searchParams = useSearchParams();
-  const runId = searchParams.get('id');
-  const { status: authStatus } = useAuth();
-  const isAuthenticated = authStatus === 'authenticated';
-  const [gpuIDs, setGpuIDs] = useState<string | null>(null);
-  const { settings, isSettingsLoaded } = useSettings();
-  const { gpuList, isGPUInfoLoaded } = useGPUInfo();
-  const { datasets, status: datasetFetchStatus } = useDatasetList();
-  const [datasetOptions, setDatasetOptions] = useState<{ value: string; label: string }[]>([]);
-  const [showAdvancedView, setShowAdvancedView] = useState(false);
-  const [jobConfig, setJobConfig] = useNestedState<JobConfig>(objectCopy(defaultJobConfig));
-  const [status, setStatus] = useState<'idle' | 'saving' | 'success' | 'error'>('idle');
-  // Track HF Jobs backend state
-  const [trainingBackend, setTrainingBackend] = useState<'local' | 'hf-jobs'>(
-    usingBrowserDb ? 'hf-jobs' : 'local',
-  );
-  const [hfJobSubmitted, setHfJobSubmitted] = useState(false);
-  useEffect(() => {
-    if (!isSettingsLoaded || !isAuthenticated) return;
-    if (datasetFetchStatus !== 'success') return;
-    let isMounted = true;
-    const buildDatasetOptions = async () => {
-      const options = await Promise.all(
-        datasets.map(async name => {
-          let datasetPath = settings.DATASETS_FOLDER ? path.join(settings.DATASETS_FOLDER, name) : '';
-          if (usingBrowserDb) {
-            const storedPath = getUserDatasetPath(name);
-            if (storedPath) {
-              datasetPath = storedPath;
-            } else {
-              try {
-                const response = await apiClient
-                  .post('/api/datasets/create', { name })
-                  .then(res => res.data);
-                if (response?.path) {
-                  datasetPath = response.path;
-                  updateUserDatasetPath(name, datasetPath);
-                }
-              } catch (err) {
-                console.error('Error resolving dataset path:', err);
-              }
-            }
-          }
-          if (!datasetPath) {
-            datasetPath = name;
-          }
-          return { value: datasetPath, label: name };
-        }),
-      );
-      if (!isMounted) {
-        return;
-      }
-      setDatasetOptions(options);
-      const defaultDatasetPath = defaultDatasetConfig.folder_path;
-      for (let i = 0; i < jobConfig.config.process[0].datasets.length; i++) {
-        const dataset = jobConfig.config.process[0].datasets[i];
-        if (dataset.folder_path === defaultDatasetPath) {
-          if (options.length > 0) {
-            setJobConfig(options[0].value, `config.process[0].datasets[${i}].folder_path`);
-          }
-        }
-      }
-    };
-    buildDatasetOptions();
-    return () => {
-      isMounted = false;
-    };
-  }, [datasets, settings, isSettingsLoaded, datasetFetchStatus]);
-  useEffect(() => {
-    if (runId) {
-      getJob(runId)
-        .then(data => {
-          if (!data) {
-            throw new Error('Job not found');
-          }
-          setGpuIDs(data.gpu_ids);
-          const parsedJobConfig = migrateJobConfig(JSON.parse(data.job_config));
-          setJobConfig(parsedJobConfig);
-          if (parsedJobConfig.is_hf_job) {
-            setTrainingBackend('hf-jobs');
-            setHfJobSubmitted(true);
-          }
-        })
-        .catch(error => console.error('Error fetching training:', error));
-    }
-  }, [runId]);
-  useEffect(() => {
-    if (isGPUInfoLoaded) {
-      if (gpuIDs === null && gpuList.length > 0) {
-        setGpuIDs(`${gpuList[0].index}`);
-      }
-    }
-  }, [gpuList, isGPUInfoLoaded]);
-  useEffect(() => {
-    if (isSettingsLoaded) {
-      setJobConfig(settings.TRAINING_FOLDER, 'config.process[0].training_folder');
-    }
-  }, [settings, isSettingsLoaded]);
-  const saveJob = async () => {
-    if (!isAuthenticated) return;
-    if (status === 'saving') return;
-    setStatus('saving');
-    try {
-      const savedJob = await upsertJob({
-        id: runId || undefined,
-        name: jobConfig.config.name,
-        gpu_ids: gpuIDs,
-        job_config: {
-          ...jobConfig,
-          is_hf_job: trainingBackend === 'hf-jobs',
-          hf_job_submitted: hfJobSubmitted,
-          training_backend: trainingBackend,
-        },
-        status: trainingBackend === 'hf-jobs' ? (hfJobSubmitted ? 'submitted' : 'stopped') : undefined,
-      });
-      setStatus('success');
-      router.push(`/jobs/${savedJob.id}`);
-    } catch (error: any) {
-      console.log('Error saving training:', error);
-      if (error?.code === 'P2002') {
-        alert('Training name already exists. Please choose a different name.');
-      } else {
-        alert('Failed to save job. Please try again.');
-      }
-    } finally {
-      setTimeout(() => {
-        setStatus('idle');
-      }, 2000);
-    }
-  };
-  const handleSubmit = async (e: React.FormEvent) => {
-    e.preventDefault();
-    saveJob();
-  };
-  return (
-    <>
-      <TopBar>
-        <div>
-          <Button className="text-gray-500 dark:text-gray-300 px-3 mt-1" onClick={() => history.back()}>
-            <FaChevronLeft />
-          </Button>
-        </div>
-        <div>
-          <h1 className="text-lg">{runId ? 'Edit Training Job' : 'New Training Job'}</h1>
-        </div>
-        <div className="flex-1"></div>
-        {showAdvancedView && isAuthenticated && (
-          <>
-            <div>
-              <SelectInput
-                value={`${gpuIDs}`}
-                onChange={value => setGpuIDs(value)}
-                options={gpuList.map((gpu: any) => ({ value: `${gpu.index}`, label: `GPU #${gpu.index}` }))}
-              />
-            </div>
-            <div className="mx-4 bg-gray-200 dark:bg-gray-800 w-1 h-6"></div>
-          </>
-        )}
-        <div className="pr-2">
-          <Button
-            className="text-gray-200 bg-gray-800 px-3 py-1 rounded-md"
-            onClick={() => setShowAdvancedView(!showAdvancedView)}
-          >
-            {showAdvancedView ? 'Show Simple' : 'Show Advanced'}
-          </Button>
-        </div>
-        <div>
-          <Button
-            className="text-gray-200 bg-green-800 hover:bg-green-700 px-3 py-1 rounded-md"
-            onClick={() => saveJob()}
-            disabled={!isAuthenticated || status === 'saving'}
-          >
-            {status === 'saving'
-              ? 'Saving...'
-              : runId
-              ? 'Update Job'
-              : 'Create Job'}
-          </Button>
-        </div>
-      </TopBar>
-      {!isAuthenticated ? (
-        <MainContent>
-          <div className="border border-gray-800 rounded-lg p-6 bg-gray-900 text-gray-400 text-sm flex flex-col gap-4">
-            <p>You need to sign in with Hugging Face or provide a valid access token before creating or editing jobs.</p>
-            <div className="flex items-center gap-3">
-              <HFLoginButton size="sm" />
-              <Link href="/settings" className="text-xs text-blue-400 hover:text-blue-300">
-                Manage authentication in Settings
-              </Link>
-            </div>
-          </div>
-        </MainContent>
-      ) : showAdvancedView ? (
-        <div className="pt-[48px] absolute top-0 left-0 w-full h-full overflow-auto">
-          <AdvancedJob
-            jobConfig={jobConfig}
-            setJobConfig={setJobConfig}
-            status={status}
-            handleSubmit={handleSubmit}
-            runId={runId}
-            gpuIDs={gpuIDs}
-            setGpuIDs={setGpuIDs}
-            gpuList={gpuList}
-            datasetOptions={datasetOptions}
-            settings={settings}
-          />
-        </div>
-      ) : (
-        <MainContent>
-          <ErrorBoundary
-            fallback={
-              <div className="flex items-center justify-center h-64 text-lg text-red-600 font-medium bg-red-100 dark:bg-red-900/20 dark:text-red-400 border border-red-300 dark:border-red-700 rounded-lg">
-                Advanced job detected. Please switch to advanced view to continue.
-              </div>
-            }
-          >
-            <SimpleJob
-              jobConfig={jobConfig}
-              setJobConfig={setJobConfig}
-              status={status}
-              handleSubmit={handleSubmit}
-              runId={runId}
-              gpuIDs={gpuIDs}
-              setGpuIDs={setGpuIDs}
-              gpuList={gpuList}
-              datasetOptions={datasetOptions}
-              trainingBackend={trainingBackend}
-              setTrainingBackend={usingBrowserDb ? undefined : setTrainingBackend}
-              hfJobSubmitted={hfJobSubmitted}
-              onHFJobComplete={(jobId: string, localJobId?: string) => {
-                setHfJobSubmitted(true);
-                // Redirect to the job detail page
-                if (localJobId) {
-                  router.push(`/jobs/${localJobId}`);
-                }
-              }}
-              forceHFBackend={usingBrowserDb}
-            />
-          </ErrorBoundary>
-          <div className="pt-20"></div>
-        </MainContent>
-      )}
-    </>
-  );
-}
-  useEffect(() => {
-    if (!isAuthenticated) {
-      setDatasetOptions([]);
-    }
-  }, [isAuthenticated]);

src/app/jobs/page.tsx DELETED Viewed

@@ -1,49 +0,0 @@
-'use client';
-import JobsTable from '@/components/JobsTable';
-import { TopBar, MainContent } from '@/components/layout';
-import Link from 'next/link';
-import { useAuth } from '@/contexts/AuthContext';
-import HFLoginButton from '@/components/HFLoginButton';
-export default function Dashboard() {
-  const { status: authStatus } = useAuth();
-  const isAuthenticated = authStatus === 'authenticated';
-  return (
-    <>
-      <TopBar>
-        <div>
-          <h1 className="text-lg">Training Jobs</h1>
-        </div>
-        <div className="flex-1"></div>
-        <div>
-          {isAuthenticated ? (
-            <Link href="/jobs/new" className="text-gray-200 bg-slate-600 px-3 py-1 rounded-md">
-              New Training Job
-            </Link>
-          ) : (
-            <span className="text-gray-600 bg-gray-900 px-3 py-1 rounded-md border border-gray-800">
-              Sign in to create jobs
-            </span>
-          )}
-        </div>
-      </TopBar>
-      <MainContent>
-        {isAuthenticated ? (
-          <JobsTable />
-        ) : (
-          <div className="border border-gray-800 rounded-lg p-6 bg-gray-900 text-gray-400 text-sm flex flex-col gap-4">
-            <p>Sign in with Hugging Face or add a personal access token to view and manage training jobs.</p>
-            <div className="flex items-center gap-3">
-              <HFLoginButton size="sm" />
-              <Link href="/settings" className="text-xs text-blue-400 hover:text-blue-300">
-                Manage tokens in Settings
-              </Link>
-            </div>
-          </div>
-        )}
-      </MainContent>
-    </>
-  );
-}

src/app/layout.tsx DELETED Viewed

@@ -1,50 +0,0 @@
-import type { Metadata } from 'next';
-import { Inter } from 'next/font/google';
-import './globals.css';
-import Sidebar from '@/components/Sidebar';
-import { ThemeProvider } from '@/components/ThemeProvider';
-import ConfirmModal from '@/components/ConfirmModal';
-import SampleImageModal from '@/components/SampleImageModal';
-import { Suspense } from 'react';
-import AuthWrapper from '@/components/AuthWrapper';
-import DocModal from '@/components/DocModal';
-import { AuthProvider } from '@/contexts/AuthContext';
-export const dynamic = 'force-dynamic';
-const inter = Inter({ subsets: ['latin'] });
-export const metadata: Metadata = {
-  title: 'Ostris - AI Toolkit',
-  description: 'A toolkit for building AI things.',
-};
-export default function RootLayout({ children }: { children: React.ReactNode }) {
-  // Check if the AI_TOOLKIT_AUTH environment variable is set
-  const authRequired = process.env.AI_TOOLKIT_AUTH ? true : false;
-  return (
-    <html lang="en" className="dark">
-      <head>
-        <meta name="apple-mobile-web-app-title" content="AI-Toolkit" />
-      </head>
-      <body className={inter.className} suppressHydrationWarning={true}>
-        <ThemeProvider>
-          <AuthProvider>
-            <AuthWrapper authRequired={authRequired}>
-              <div className="flex h-screen bg-gray-950">
-                <Sidebar />
-                <main className="flex-1 overflow-auto bg-gray-950 text-gray-100 relative">
-                  <Suspense>{children}</Suspense>
-                </main>
-              </div>
-            </AuthWrapper>
-          </AuthProvider>
-        </ThemeProvider>
-        <ConfirmModal />
-        <DocModal />
-        <SampleImageModal />
-      </body>
-    </html>
-  );
-}

src/app/manifest.json DELETED Viewed

@@ -1,21 +0,0 @@
-{
-  "name": "AI Toolkit",
-  "short_name": "AIToolkit",
-  "icons": [
-    {
-      "src": "/web-app-manifest-192x192.png",
-      "sizes": "192x192",
-      "type": "image/png",
-      "purpose": "maskable"
-    },
-    {
-      "src": "/web-app-manifest-512x512.png",
-      "sizes": "512x512",
-      "type": "image/png",
-      "purpose": "maskable"
-    }
-  ],
-  "theme_color": "#000000",
-  "background_color": "#000000",
-  "display": "standalone"
-}

src/app/page.tsx DELETED Viewed

@@ -1,5 +0,0 @@
-import { redirect } from 'next/navigation';
-export default function Home() {
-  redirect('/dashboard');
-}

src/app/settings/page.tsx DELETED Viewed

@@ -1,264 +0,0 @@
-'use client';
-import { useEffect, useState } from 'react';
-import useSettings from '@/hooks/useSettings';
-import { TopBar, MainContent } from '@/components/layout';
-import { persistSettings } from '@/utils/storage/settingsStorage';
-import { useAuth } from '@/contexts/AuthContext';
-import HFLoginButton from '@/components/HFLoginButton';
-import { useMemo } from 'react';
-import Link from 'next/link';
-export default function Settings() {
-  const { settings, setSettings } = useSettings();
-  const { status: authStatus, namespace, oauthAvailable, loginWithOAuth, logout, setManualToken, error: authError, token: authToken } = useAuth();
-  const [status, setStatus] = useState<'idle' | 'saving' | 'success' | 'error'>('idle');
-  const [manualToken, setManualTokenInput] = useState(settings.HF_TOKEN || '');
-  const isAuthenticated = authStatus === 'authenticated';
-  useEffect(() => {
-    setManualTokenInput(settings.HF_TOKEN || '');
-  }, [settings.HF_TOKEN]);
-  const handleSubmit = async (e: React.FormEvent) => {
-    e.preventDefault();
-    setStatus('saving');
-    persistSettings(settings)
-      .then(() => {
-        setStatus('success');
-      })
-      .catch(error => {
-        console.error('Error saving settings:', error);
-        setStatus('error');
-      })
-      .finally(() => {
-        setTimeout(() => setStatus('idle'), 2000);
-      });
-  };
-  const handleChange = (e: React.ChangeEvent<HTMLInputElement>) => {
-    const { name, value } = e.target;
-    setSettings(prev => ({ ...prev, [name]: value }));
-  };
-  const handleManualSubmit = async (e: React.FormEvent) => {
-    e.preventDefault();
-    await setManualToken(manualToken);
-  };
-  const authDescription = useMemo(() => {
-    if (authStatus === 'checking') {
-      return 'Checking your Hugging Face session…';
-    }
-    if (isAuthenticated) {
-      return `Connected as ${namespace}`;
-    }
-    return 'Sign in to use Hugging Face Jobs or submit your own access token.';
-  }, [authStatus, isAuthenticated, namespace]);
-  return (
-    <>
-      <TopBar>
-        <div>
-          <h1 className="text-lg">Settings</h1>
-        </div>
-        <div className="flex-1"></div>
-        <div className="flex items-center gap-3 pr-2 text-sm text-gray-400">
-          {isAuthenticated ? (
-            <span>Welcome, {namespace || 'user'}</span>
-          ) : (
-            <span>Authenticate to unlock training features</span>
-          )}
-        </div>
-      </TopBar>
-      <MainContent>
-        <div className="grid gap-4 md:grid-cols-2 mb-6">
-          <div className="border border-gray-800 rounded-xl p-5 bg-gray-900">
-            <div className="flex items-center justify-between mb-4">
-              <div>
-                <h2 className="text-md font-semibold text-gray-100">Sign in with Hugging Face</h2>
-                <p className="text-sm text-gray-400 mt-1">{authDescription}</p>
-              </div>
-              {isAuthenticated && (
-                <span className="text-xs px-2 py-1 rounded-full bg-emerald-900 text-emerald-300">Authenticated</span>
-              )}
-            </div>
-            <div className="flex items-center gap-3">
-              {isAuthenticated ? (
-                <button
-                  type="button"
-                  onClick={logout}
-                  className="px-4 py-2 rounded-md border border-gray-700 text-sm bg-gray-800 hover:bg-gray-700 transition-colors"
-                >
-                  Sign out
-                </button>
-              ) : (
-                <>
-                  <HFLoginButton size="md" className="bg-transparent border-none p-0" />
-                  {!oauthAvailable && (
-                    <span className="text-xs text-yellow-500">
-                      OAuth is unavailable. Set HF_OAUTH_CLIENT_ID/SECRET on the server.
-                    </span>
-                  )}
-                </>
-              )}
-            </div>
-            {!isAuthenticated && authError && (
-              <p className="mt-3 text-xs text-red-400">{authError}</p>
-            )}
-          </div>
-          <form onSubmit={handleManualSubmit} className="border border-gray-800 rounded-xl p-5 bg-gray-900">
-            <h2 className="text-md font-semibold text-gray-100">Manual Token</h2>
-            <p className="text-sm text-gray-400 mt-1">
-              Paste an access token created at{' '}
-              <a href="https://huggingface.co/settings/tokens" target="_blank" rel="noreferrer" className="text-blue-400 hover:text-blue-300">
-                huggingface.co/settings/tokens
-              </a>
-              .
-            </p>
-            <div className="mt-4">
-              <input
-                type="password"
-                value={manualToken}
-                onChange={event => setManualTokenInput(event.target.value)}
-                className="w-full px-4 py-2 bg-gray-800 border border-gray-700 rounded-lg focus:ring-2 focus:ring-gray-600 focus:border-transparent"
-                placeholder="Enter Hugging Face token"
-              />
-            </div>
-            <div className="mt-4 flex items-center gap-3">
-              <button
-                type="submit"
-                className="px-4 py-2 rounded-md bg-blue-600 hover:bg-blue-500 text-sm text-white transition-colors disabled:opacity-50 disabled:cursor-not-allowed"
-                disabled={authStatus === 'checking' || manualToken.trim() === ''}
-              >
-                Validate Token
-              </button>
-              {isAuthenticated && authToken === manualToken && (
-                <span className="text-xs text-emerald-400">Active token</span>
-              )}
-            </div>
-            {authError && (
-              <p className="mt-3 text-xs text-red-400">{authError}</p>
-            )}
-          </form>
-        </div>
-        <form onSubmit={handleSubmit} className="space-y-6">
-          <div className="grid grid-cols-1 gap-6 sm:grid-cols-2">
-            <div>
-              <div className="space-y-4">
-                <div>
-                  <label htmlFor="TRAINING_FOLDER" className="block text-sm font-medium mb-2">
-                    Training Folder Path
-                    <div className="text-gray-500 text-sm ml-1">
-                      We will store your training information here. Must be an absolute path. If blank, it will default
-                      to the output folder in the project root.
-                    </div>
-                  </label>
-                  <input
-                    type="text"
-                    id="TRAINING_FOLDER"
-                    name="TRAINING_FOLDER"
-                    value={settings.TRAINING_FOLDER}
-                    onChange={handleChange}
-                    className="w-full px-4 py-2 bg-gray-800 border border-gray-700 rounded-lg focus:ring-2 focus:ring-gray-600 focus:border-transparent"
-                    placeholder="Enter training folder path"
-                  />
-                </div>
-                <div>
-                  <label htmlFor="DATASETS_FOLDER" className="block text-sm font-medium mb-2">
-                    Dataset Folder Path
-                    <div className="text-gray-500 text-sm ml-1">
-                      Where we store and find your datasets.{' '}
-                      <span className="text-orange-800">
-                        Warning: This software may modify datasets so it is recommended you keep a backup somewhere else
-                        or have a dedicated folder for this software.
-                      </span>
-                    </div>
-                  </label>
-                  <input
-                    type="text"
-                    id="DATASETS_FOLDER"
-                    name="DATASETS_FOLDER"
-                    value={settings.DATASETS_FOLDER}
-                    onChange={handleChange}
-                    className="w-full px-4 py-2 bg-gray-800 border border-gray-700 rounded-lg focus:ring-2 focus:ring-gray-600 focus:border-transparent"
-                    placeholder="Enter datasets folder path"
-                  />
-                </div>
-              </div>
-            </div>
-            <div>
-              <div className="space-y-4">
-                <h3 className="text-lg font-medium mb-4">Hugging Face Jobs (Cloud Training)</h3>
-                <div>
-                  <label htmlFor="HF_JOBS_NAMESPACE" className="block text-sm font-medium mb-2">
-                    HF Jobs Namespace (optional)
-                    <div className="text-gray-500 text-sm ml-1">
-                      Leave blank to default to the account associated with your Hugging Face token.
-                    </div>
-                  </label>
-                  <input
-                    type="text"
-                    id="HF_JOBS_NAMESPACE"
-                    name="HF_JOBS_NAMESPACE"
-                    value={settings.HF_JOBS_NAMESPACE}
-                    onChange={handleChange}
-                    className="w-full px-4 py-2 bg-gray-800 border border-gray-700 rounded-lg focus:ring-2 focus:ring-gray-600 focus:border-transparent"
-                    placeholder="e.g. your-username or your-org"
-                  />
-                </div>
-                <div>
-                  <label htmlFor="HF_JOBS_DEFAULT_HARDWARE" className="block text-sm font-medium mb-2">
-                    Default Hardware
-                    <div className="text-gray-500 text-sm ml-1">
-                      Default hardware configuration for cloud training jobs.
-                    </div>
-                  </label>
-                  <select
-                    id="HF_JOBS_DEFAULT_HARDWARE"
-                    name="HF_JOBS_DEFAULT_HARDWARE"
-                    value={settings.HF_JOBS_DEFAULT_HARDWARE}
-                    onChange={(e) => setSettings(prev => ({ ...prev, HF_JOBS_DEFAULT_HARDWARE: e.target.value }))}
-                    className="w-full px-4 py-2 bg-gray-800 border border-gray-700 rounded-lg focus:ring-2 focus:ring-gray-600 focus:border-transparent"
-                  >
-                    <option value="cpu-basic">CPU Basic</option>
-                    <option value="cpu-upgrade">CPU Upgrade</option>
-                    <option value="t4-small">T4 Small</option>
-                    <option value="t4-medium">T4 Medium</option>
-                    <option value="l4x1">L4x1</option>
-                    <option value="l4x4">L4x4</option>
-                    <option value="a10g-small">A10G Small</option>
-                    <option value="a10g-large">A10G Large</option>
-                    <option value="a10g-largex2">A10G Large x2</option>
-                    <option value="a10g-largex4">A10G Large x4</option>
-                    <option value="a100-large">A100 Large</option>
-                    <option value="v5e-1x1">TPU v5e-1x1</option>
-                    <option value="v5e-2x2">TPU v5e-2x2</option>
-                    <option value="v5e-2x4">TPU v5e-2x4</option>
-                  </select>
-                </div>
-              </div>
-            </div>
-          </div>
-          <button
-            type="submit"
-            disabled={status === 'saving'}
-            className="w-full px-4 py-2 bg-gray-700 hover:bg-gray-600 rounded-lg transition-colors disabled:opacity-50 disabled:cursor-not-allowed"
-          >
-            {status === 'saving' ? 'Saving...' : 'Save Settings'}
-          </button>
-          {status === 'success' && <p className="text-green-500 text-center">Settings saved successfully!</p>}
-          {status === 'error' && <p className="text-red-500 text-center">Error saving settings. Please try again.</p>}
-        </form>
-      </MainContent>
-    </>
-  );
-}

src/components/AddImagesModal.tsx DELETED Viewed

@@ -1,152 +0,0 @@
-'use client';
-import { createGlobalState } from 'react-global-hooks';
-import { Dialog, DialogBackdrop, DialogPanel, DialogTitle } from '@headlessui/react';
-import { FaUpload } from 'react-icons/fa';
-import { useCallback, useState } from 'react';
-import { useDropzone } from 'react-dropzone';
-import { apiClient } from '@/utils/api';
-export interface AddImagesModalState {
-  datasetName: string;
-  onComplete?: () => void;
-}
-export const addImagesModalState = createGlobalState<AddImagesModalState | null>(null);
-export const openImagesModal = (datasetName: string, onComplete: () => void) => {
-  addImagesModalState.set({ datasetName, onComplete });
-};
-export default function AddImagesModal() {
-  const [addImagesModalInfo, setAddImagesModalInfo] = addImagesModalState.use();
-  const [uploadProgress, setUploadProgress] = useState<number>(0);
-  const [isUploading, setIsUploading] = useState<boolean>(false);
-  const open = addImagesModalInfo !== null;
-  const onCancel = () => {
-    if (!isUploading) {
-      setAddImagesModalInfo(null);
-    }
-  };
-  const onDone = () => {
-    if (addImagesModalInfo?.onComplete && !isUploading) {
-      addImagesModalInfo.onComplete();
-      setAddImagesModalInfo(null);
-    }
-  };
-  const onDrop = useCallback(
-    async (acceptedFiles: File[]) => {
-      if (acceptedFiles.length === 0) return;
-      setIsUploading(true);
-      setUploadProgress(0);
-      const formData = new FormData();
-      acceptedFiles.forEach(file => {
-        formData.append('files', file);
-      });
-      formData.append('datasetName', addImagesModalInfo?.datasetName || '');
-      try {
-        await apiClient.post(`/api/datasets/upload`, formData, {
-          headers: {
-            'Content-Type': 'multipart/form-data',
-          },
-          onUploadProgress: progressEvent => {
-            const percentCompleted = Math.round((progressEvent.loaded * 100) / (progressEvent.total || 100));
-            setUploadProgress(percentCompleted);
-          },
-          timeout: 0, // Disable timeout
-        });
-        onDone();
-      } catch (error) {
-        console.error('Upload failed:', error);
-      } finally {
-        setIsUploading(false);
-        setUploadProgress(0);
-      }
-    },
-    [addImagesModalInfo],
-  );
-  const { getRootProps, getInputProps, isDragActive } = useDropzone({
-    onDrop,
-    accept: {
-      'image/*': ['.png', '.jpg', '.jpeg', '.gif', '.bmp', '.webp'],
-      'video/*': ['.mp4', '.avi', '.mov', '.mkv', '.wmv', '.m4v', '.flv'],
-      'text/*': ['.txt'],
-    },
-    multiple: true,
-  });
-  return (
-    <Dialog open={open} onClose={onCancel} className="relative z-10">
-      <DialogBackdrop
-        transition
-        className="fixed inset-0 bg-gray-900/75 transition-opacity data-closed:opacity-0 data-enter:duration-300 data-enter:ease-out data-leave:duration-200 data-leave:ease-in"
-      />
-      <div className="fixed inset-0 z-10 w-screen overflow-y-auto">
-        <div className="flex min-h-full items-end justify-center p-4 text-center sm:items-center sm:p-0">
-          <DialogPanel
-            transition
-            className="relative transform overflow-hidden rounded-lg bg-gray-800 text-left shadow-xl transition-all data-closed:translate-y-4 data-closed:opacity-0 data-enter:duration-300 data-enter:ease-out data-leave:duration-200 data-leave:ease-in sm:my-8 sm:w-full sm:max-w-lg data-closed:sm:translate-y-0 data-closed:sm:scale-95"
-          >
-            <div className="bg-gray-800 px-4 pt-5 pb-4 sm:p-6 sm:pb-4">
-              <div className="text-center">
-                <DialogTitle as="h3" className="text-base font-semibold text-gray-200 mb-4">
-                  Add Images to: {addImagesModalInfo?.datasetName}
-                </DialogTitle>
-                <div className="w-full">
-                  <div
-                    {...getRootProps()}
-                    className={`h-40 w-full flex flex-col items-center justify-center border-2 border-dashed rounded-lg cursor-pointer transition-colors duration-200
-                      ${isDragActive ? 'border-blue-500 bg-blue-50/10' : 'border-gray-600'}`}
-                  >
-                    <input {...getInputProps()} />
-                    <FaUpload className="size-8 mb-3 text-gray-400" />
-                    <p className="text-sm text-gray-200 text-center">
-                      {isDragActive ? 'Drop the files here...' : 'Drag & drop files here, or click to select files'}
-                    </p>
-                  </div>
-                  {isUploading && (
-                    <div className="mt-4">
-                      <div className="w-full bg-gray-700 rounded-full h-2.5">
-                        <div className="bg-blue-600 h-2.5 rounded-full" style={{ width: `${uploadProgress}%` }}></div>
-                      </div>
-                      <p className="text-sm text-gray-300 mt-2 text-center">Uploading... {uploadProgress}%</p>
-                    </div>
-                  )}
-                </div>
-              </div>
-            </div>
-            <div className="bg-gray-700 px-4 py-3 sm:flex sm:flex-row-reverse sm:px-6">
-              <button
-                type="button"
-                onClick={onDone}
-                disabled={isUploading}
-                className={`inline-flex w-full justify-center rounded-md bg-slate-600 px-3 py-2 text-sm font-semibold text-white shadow-xs sm:ml-3 sm:w-auto
-                  ${isUploading ? 'opacity-50 cursor-not-allowed' : ''}`}
-              >
-                Done
-              </button>
-              <button
-                type="button"
-                data-autofocus
-                onClick={onCancel}
-                disabled={isUploading}
-                className={`mt-3 inline-flex w-full justify-center rounded-md bg-gray-800 px-3 py-2 text-sm font-semibold text-gray-200 hover:bg-gray-800 sm:mt-0 sm:w-auto ring-0
-                  ${isUploading ? 'opacity-50 cursor-not-allowed' : ''}`}
-              >
-                Cancel
-              </button>
-            </div>
-          </DialogPanel>
-        </div>
-      </div>
-    </Dialog>
-  );
-}

src/components/AddSingleImageModal.tsx DELETED Viewed

@@ -1,141 +0,0 @@
-'use client';
-import { createGlobalState } from 'react-global-hooks';
-import { Dialog, DialogBackdrop, DialogPanel, DialogTitle } from '@headlessui/react';
-import { FaUpload } from 'react-icons/fa';
-import { useCallback, useState } from 'react';
-import { useDropzone } from 'react-dropzone';
-import { apiClient } from '@/utils/api';
-export interface AddSingleImageModalState {
-  onComplete?: (imagePath: string|null) => void;
-}
-export const addSingleImageModalState = createGlobalState<AddSingleImageModalState | null>(null);
-export const openAddImageModal = (onComplete: (imagePath: string|null) => void) => {
-  addSingleImageModalState.set({onComplete });
-};
-export default function AddSingleImageModal() {
-  const [addSingleImageModalInfo, setAddSingleImageModalInfo] = addSingleImageModalState.use();
-  const [uploadProgress, setUploadProgress] = useState<number>(0);
-  const [isUploading, setIsUploading] = useState<boolean>(false);
-  const open = addSingleImageModalInfo !== null;
-  const onCancel = () => {
-    if (!isUploading) {
-      setAddSingleImageModalInfo(null);
-    }
-  };
-  const onDone = (imagePath: string|null) => {
-    if (addSingleImageModalInfo?.onComplete && !isUploading) {
-      addSingleImageModalInfo.onComplete(imagePath);
-      setAddSingleImageModalInfo(null);
-    }
-  };
-  const onDrop = useCallback(
-    async (acceptedFiles: File[]) => {
-      if (acceptedFiles.length === 0) return;
-      setIsUploading(true);
-      setUploadProgress(0);
-      const formData = new FormData();
-      acceptedFiles.forEach(file => {
-        formData.append('files', file);
-      });
-      try {
-        const resp = await apiClient.post(`/api/img/upload`, formData, {
-          headers: {
-            'Content-Type': 'multipart/form-data',
-          },
-          onUploadProgress: progressEvent => {
-            const percentCompleted = Math.round((progressEvent.loaded * 100) / (progressEvent.total || 100));
-            setUploadProgress(percentCompleted);
-          },
-          timeout: 0, // Disable timeout
-        });
-        console.log('Upload successful:', resp.data);
-        onDone(resp.data.files[0] || null);
-      } catch (error) {
-        console.error('Upload failed:', error);
-      } finally {
-        setIsUploading(false);
-        setUploadProgress(0);
-      }
-    },
-    [addSingleImageModalInfo],
-  );
-  const { getRootProps, getInputProps, isDragActive } = useDropzone({
-    onDrop,
-    accept: {
-      'image/*': ['.png', '.jpg', '.jpeg', '.gif', '.bmp', '.webp'],
-    },
-    multiple: false,
-  });
-  return (
-    <Dialog open={open} onClose={onCancel} className="relative z-10">
-      <DialogBackdrop
-        transition
-        className="fixed inset-0 bg-gray-900/75 transition-opacity data-closed:opacity-0 data-enter:duration-300 data-enter:ease-out data-leave:duration-200 data-leave:ease-in"
-      />
-      <div className="fixed inset-0 z-10 w-screen overflow-y-auto">
-        <div className="flex min-h-full items-end justify-center p-4 text-center sm:items-center sm:p-0">
-          <DialogPanel
-            transition
-            className="relative transform overflow-hidden rounded-lg bg-gray-800 text-left shadow-xl transition-all data-closed:translate-y-4 data-closed:opacity-0 data-enter:duration-300 data-enter:ease-out data-leave:duration-200 data-leave:ease-in sm:my-8 sm:w-full sm:max-w-lg data-closed:sm:translate-y-0 data-closed:sm:scale-95"
-          >
-            <div className="bg-gray-800 px-4 pt-5 pb-4 sm:p-6 sm:pb-4">
-              <div className="text-center">
-                <DialogTitle as="h3" className="text-base font-semibold text-gray-200 mb-4">
-                  Add Control Image
-                </DialogTitle>
-                <div className="w-full">
-                  <div
-                    {...getRootProps()}
-                    className={`h-40 w-full flex flex-col items-center justify-center border-2 border-dashed rounded-lg cursor-pointer transition-colors duration-200
-                      ${isDragActive ? 'border-blue-500 bg-blue-50/10' : 'border-gray-600'}`}
-                  >
-                    <input {...getInputProps()} />
-                    <FaUpload className="size-8 mb-3 text-gray-400" />
-                    <p className="text-sm text-gray-200 text-center">
-                      {isDragActive ? 'Drop the image here...' : 'Drag & drop an image here, or click to select one'}
-                    </p>
-                  </div>
-                  {isUploading && (
-                    <div className="mt-4">
-                      <div className="w-full bg-gray-700 rounded-full h-2.5">
-                        <div className="bg-blue-600 h-2.5 rounded-full" style={{ width: `${uploadProgress}%` }}></div>
-                      </div>
-                      <p className="text-sm text-gray-300 mt-2 text-center">Uploading... {uploadProgress}%</p>
-                    </div>
-                  )}
-                </div>
-              </div>
-            </div>
-            <div className="bg-gray-700 px-4 py-3 sm:flex sm:flex-row-reverse sm:px-6">
-              <button
-                type="button"
-                data-autofocus
-                onClick={onCancel}
-                disabled={isUploading}
-                className={`mt-3 inline-flex w-full justify-center rounded-md bg-gray-800 px-3 py-2 text-sm font-semibold text-gray-200 hover:bg-gray-800 sm:mt-0 sm:w-auto ring-0
-                  ${isUploading ? 'opacity-50 cursor-not-allowed' : ''}`}
-              >
-                Cancel
-              </button>
-            </div>
-          </DialogPanel>
-        </div>
-      </div>
-    </Dialog>
-  );
-}

src/components/AuthWrapper.tsx DELETED Viewed

@@ -1,166 +0,0 @@
-'use client';
-import { useState, useEffect, useRef } from 'react';
-import { apiClient, isAuthorizedState } from '@/utils/api';
-import { createGlobalState } from 'react-global-hooks';
-interface AuthWrapperProps {
-  authRequired: boolean;
-  children: React.ReactNode | React.ReactNode[];
-}
-export default function AuthWrapper({ authRequired, children }: AuthWrapperProps) {
-  const [token, setToken] = useState('');
-  // start with true, and deauth if needed
-  const [isAuthorizedGlobal, setIsAuthorized] = isAuthorizedState.use();
-  const [isLoading, setIsLoading] = useState(false);
-  const [error, setError] = useState('');
-  const [isBrowser, setIsBrowser] = useState(false);
-  const inputRef = useRef<HTMLInputElement>(null);
-  const isAuthorized = authRequired ? isAuthorizedGlobal : true;
-  // Set isBrowser to true when component mounts
-  useEffect(() => {
-    setIsBrowser(true);
-    // Get token from localStorage only after component has mounted
-    const storedToken = localStorage.getItem('AI_TOOLKIT_AUTH') || '';
-    setToken(storedToken);
-    checkAuth();
-  }, []);
-  // auto focus on input when not authorized
-  useEffect(() => {
-    if (isAuthorized) {
-      return;
-    }
-    setTimeout(() => {
-      if (inputRef.current) {
-        inputRef.current.focus();
-      }
-    }, 100);
-  }, [isAuthorized]);
-  const checkAuth = async () => {
-    // always get current stored token here to avoid state race conditions
-    const currentToken = localStorage.getItem('AI_TOOLKIT_AUTH') || '';
-    if (!authRequired || isLoading || currentToken === '') {
-      return;
-    }
-    setIsLoading(true);
-    setError('');
-    try {
-      const response = await apiClient.get('/api/auth');
-      if (response.data.isAuthenticated) {
-        setIsAuthorized(true);
-      } else {
-        setIsAuthorized(false);
-        setError('Invalid token. Please try again.');
-      }
-    } catch (err) {
-      setIsAuthorized(false);
-      console.log(err);
-      setError('Invalid token. Please try again.');
-    }
-    setIsLoading(false);
-  };
-  const handleSubmit = async (e: React.FormEvent) => {
-    e.preventDefault();
-    setError('');
-    if (!token.trim()) {
-      setError('Please enter your token');
-      return;
-    }
-    if (isBrowser) {
-      localStorage.setItem('AI_TOOLKIT_AUTH', token);
-      checkAuth();
-    }
-  };
-  if (isAuthorized) {
-    return <>{children}</>;
-  }
-  return (
-    <div className="flex min-h-screen bg-gray-900 text-gray-100 absolute top-0 left-0 right-0 bottom-0 scroll-auto">
-      {/* Left side - decorative or brand area */}
-      <div className="hidden lg:flex lg:w-1/2 bg-gray-800 flex-col justify-center items-center p-12">
-        <div className="mb-4">
-          {/* Replace with your own logo */}
-          <div className="flex items-center justify-center">
-            <img src="/ostris_logo.png" alt="Ostris AI Toolkit" className="w-auto h-24 inline" />
-          </div>
-        </div>
-        <h1 className="text-4xl mb-6">AI Toolkit</h1>
-      </div>
-      {/* Right side - login form */}
-      <div className="w-full lg:w-1/2 flex flex-col justify-center items-center p-8 sm:p-12">
-        <div className="w-full max-w-md">
-          <div className="lg:hidden flex justify-center mb-4">
-            {/* Mobile logo */}
-            <div className="flex items-center justify-center">
-              <img src="/ostris_logo.png" alt="Ostris AI Toolkit" className="w-auto h-24 inline" />
-            </div>
-          </div>
-          <h2 className="text-3xl text-center mb-2 lg:hidden">AI Toolkit</h2>
-          <form onSubmit={handleSubmit} className="space-y-6">
-            <div>
-              <label htmlFor="token" className="block text-sm font-medium text-gray-400 mb-2">
-                Password
-              </label>
-              <input
-                id="token"
-                name="token"
-                type="password"
-                autoComplete="off"
-                required
-                value={token}
-                ref={inputRef}
-                onChange={e => setToken(e.target.value)}
-                className="w-full px-4 py-3 rounded-lg bg-gray-800 border border-gray-700 focus:border-blue-500 focus:ring-2 focus:ring-blue-500 focus:ring-opacity-50 text-gray-100 transition duration-200"
-                placeholder="Enter your password"
-              />
-              <div className='text-gray-500 text-xs mt-2'>
-                The password is set with the environment variable AI_TOOLKIT_AUTH, the default is the super secure secret word "password"
-              </div>
-            </div>
-            {error && (
-              <div className="p-3 bg-red-900/50 border border-red-800 rounded-lg text-red-200 text-sm">{error}</div>
-            )}
-            <button
-              type="submit"
-              disabled={isLoading}
-              className="w-full py-3 px-4 bg-blue-600 hover:bg-blue-700 rounded-lg text-white font-medium focus:outline-none focus:ring-2 focus:ring-blue-500 focus:ring-opacity-50 transition duration-200 flex items-center justify-center"
-            >
-              {isLoading ? (
-                <svg
-                  className="animate-spin h-5 w-5 text-white"
-                  xmlns="http://www.w3.org/2000/svg"
-                  fill="none"
-                  viewBox="0 0 24 24"
-                >
-                  <circle className="opacity-25" cx="12" cy="12" r="10" stroke="currentColor" strokeWidth="4"></circle>
-                  <path
-                    className="opacity-75"
-                    fill="currentColor"
-                    d="M4 12a8 8 0 018-8V0C5.373 0 0 5.373 0 12h4zm2 5.291A7.962 7.962 0 014 12H0c0 3.042 1.135 5.824 3 7.938l3-2.647z"
-                  ></path>
-                </svg>
-              ) : (
-                'Check Password'
-              )}
-            </button>
-          </form>
-        </div>
-      </div>
-    </div>
-  );
-}

src/components/Card.tsx DELETED Viewed

@@ -1,15 +0,0 @@
-interface CardProps {
-  title?: string;
-  children?: React.ReactNode;
-}
-const Card: React.FC<CardProps> = ({ title, children }) => {
-  return (
-    <section className="space-y-2 px-4 pb-4 pt-2 bg-gray-900 rounded-lg">
-      {title && <h2 className="text-lg mb-2 font-semibold uppercase text-gray-500">{title}</h2>}
-      {children ? children : null}
-    </section>
-  );
-};
-export default Card;