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Migrate workflow_templates/site into the frontend monorepo as apps/hub so the hub can use @comfyorg/design-system and shared packages. Changes to existing files: - pnpm-workspace.yaml: add @astrojs/sitemap, @astrojs/vercel, lucide-vue-next - eslint.config.ts: add hub ignores and i18n/import rule overrides - .oxlintrc.json: add hub scripts to ignore patterns - knip.config.ts: add hub workspace config apps/hub adaptations from source: - Replace local cn() with @comfyorg/tailwind-utils (19 files) - Integrate @comfyorg/design-system/css/base.css in global.css - Make TEMPLATES_DIR configurable via HUB_TEMPLATES_DIR env var - Add HUB_SKIP_SYNC flag for builds without template data - Remove Vite 8-incompatible rollupOptions.output.manualChunks - Fix stylelint violations (modern color notation, number precision) - Gitignore generated content (thumbnails, synced templates, AI cache)
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Qwen is Alibaba's family of vision-language and image generation models. Qwen2.5-VL is a multimodal vision-language model available in 3B (6-8GB VRAM), 7B (16GB), and 72B (multi-GPU 80GB+) sizes, capable of image understanding, hour-long video comprehension, visual localization, visual agent tasks (computer/phone use), and structured JSON output for document extraction. Qwen-Image-Edit provides instruction-based image editing with inpainting, outpainting, and style transfer. Qwen-Image handles text-to-image generation, while Qwen-Image-Layered produces composable foreground/background layer outputs. The family features native Chinese/English support, strong prompt following, and state-of-the-art visual understanding benchmarks. Key parameters include dynamic pixel budgets (256-1280 tokens per image), configurable frame rates for video input, and temperature for text diversity. Primary uses: image editing, visual QA, video comprehension, document OCR, and layered image generation.