mirror of
https://github.com/Anil-matcha/Open-Generative-AI.git
synced 2026-05-07 01:17:18 +00:00
Merge pull request #11 from Ahoum-Dev/feat/worker-and-ui
feat: background worker, prompt template, section switcher, home hub
This commit is contained in:
Anurag Pappula
GitHub
commit
ac6f4efd6a
17 changed files with 633 additions and 38 deletions
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@ -32,6 +32,7 @@ COPY --from=builder /app/node_modules ./node_modules
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COPY --from=builder /app/packages ./packages
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COPY --from=builder /app/prisma ./prisma
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COPY --from=builder /app/lib ./lib
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COPY --from=builder /app/worker ./worker
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COPY --from=builder /app/package.json ./
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COPY --from=builder /app/next.config.mjs ./
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@ -1,5 +1,10 @@
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import { redirect } from 'next/navigation';
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import HomeHub from '@/components/HomeHub';
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export const metadata = {
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title: 'Open Generative AI',
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description: 'Pick a workspace — Studio for one-off creations, Batch for CSV-driven automation.',
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};
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export default function Home() {
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redirect('/studio');
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return <HomeHub />;
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}
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138
components/HomeHub.jsx
Normal file
138
components/HomeHub.jsx
Normal file
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@ -0,0 +1,138 @@
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'use client';
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import { useEffect, useState } from 'react';
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const CARDS = [
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{
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id: 'batch',
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title: 'Batch',
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tagline: 'CSV in. 255 videos out.',
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description:
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'Upload a CSV, map trainers and studios once, hit Start, and a background worker submits every row to MuAPI seedance-v2.0-i2v with retries, pause/resume, and per-row results.',
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href: '/batch',
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accent: 'bg-[#d9ff00] text-black hover:bg-[#e5ff33]',
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badge: 'CSV-driven automation',
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icon: (
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<svg width="28" height="28" viewBox="0 0 24 24" fill="none" stroke="currentColor" strokeWidth="2" strokeLinecap="round" strokeLinejoin="round">
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<rect x="3" y="3" width="7" height="7" rx="1" />
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<rect x="14" y="3" width="7" height="7" rx="1" />
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<rect x="3" y="14" width="7" height="7" rx="1" />
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<rect x="14" y="14" width="7" height="7" rx="1" />
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</svg>
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),
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bullets: ['CSV upload + auto-mapping', 'Live progress + retry', 'Results CSV export'],
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},
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{
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id: 'studio',
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title: 'Studio',
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tagline: 'One generation at a time.',
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description:
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'200+ MuAPI models for ad-hoc image, video, lip-sync, and cinema generations. Use this when you want to experiment with a single prompt rather than run a CSV.',
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href: '/studio',
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accent: 'bg-white/10 text-white hover:bg-white/20 border border-white/20',
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badge: 'For one-offs and exploration',
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icon: (
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<svg width="28" height="28" viewBox="0 0 24 24" fill="none" stroke="currentColor" strokeWidth="2" strokeLinecap="round" strokeLinejoin="round">
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<polygon points="13 2 3 14 12 14 11 22 21 10 12 10 13 2" />
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</svg>
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),
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bullets: ['Image / Video / Lip Sync / Cinema', 'Bring-your-own MuAPI key', 'Live preview + history'],
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},
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];
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const LAST_KEY = 'lastSection';
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export default function HomeHub() {
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const [lastSection, setLastSection] = useState(null);
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useEffect(() => {
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try {
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setLastSection(localStorage.getItem(LAST_KEY));
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} catch {}
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}, []);
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return (
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<div className="min-h-screen bg-[#030303] text-white flex flex-col">
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<header className="flex-shrink-0 h-14 border-b border-white/[0.03] flex items-center px-6 bg-black/20 backdrop-blur-md">
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<div className="flex items-center gap-2">
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<div className="w-8 h-8 bg-white rounded-lg flex items-center justify-center">
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<svg width="20" height="20" viewBox="0 0 24 24" fill="none" stroke="black" strokeWidth="2.5" strokeLinecap="round" strokeLinejoin="round">
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<path d="M12 2L2 7l10 5 10-5-10-5zM2 17l10 5 10-5M2 12l10 5 10-5" />
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</svg>
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</div>
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<span className="text-sm font-bold tracking-tight">OpenGenerativeAI</span>
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</div>
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</header>
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<main className="flex-1 flex items-center justify-center px-6 py-12">
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<div className="max-w-5xl w-full">
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<div className="text-center mb-10">
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<h1 className="text-3xl md:text-4xl font-bold tracking-tight">Pick a workspace</h1>
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<p className="text-white/50 text-sm mt-2">
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Use Batch for the CSV pipeline. Use Studio for ad-hoc generations.
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</p>
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</div>
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<div className="grid grid-cols-1 md:grid-cols-2 gap-5">
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{CARDS.map((c) => {
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const isLast = lastSection === c.id;
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return (
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<a
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key={c.id}
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href={c.href}
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onClick={() => {
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try { localStorage.setItem(LAST_KEY, c.id); } catch {}
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}}
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className={`group relative bg-[#0a0a0a] border rounded-xl p-7 flex flex-col transition-all hover:translate-y-[-2px] hover:border-white/15 ${
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isLast ? 'border-[#d9ff00]/40 ring-1 ring-[#d9ff00]/20' : 'border-white/[0.05]'
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}`}
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>
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{isLast && (
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<span className="absolute top-3 right-3 text-[10px] uppercase tracking-wide font-bold text-[#d9ff00]">
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Last used
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</span>
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)}
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<div className="flex items-start gap-4 mb-4">
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<div className={`w-12 h-12 rounded-lg flex items-center justify-center ${
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c.id === 'batch' ? 'bg-[#d9ff00]/10 text-[#d9ff00]' : 'bg-white/5 text-white/80'
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}`}>
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{c.icon}
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</div>
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<div>
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<p className="text-[10px] uppercase tracking-wide text-white/40 font-semibold">{c.badge}</p>
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<h2 className="text-2xl font-bold mt-0.5">{c.title}</h2>
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<p className="text-white/60 text-sm">{c.tagline}</p>
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</div>
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</div>
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<p className="text-white/50 text-[13px] leading-relaxed mb-5">{c.description}</p>
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<ul className="space-y-1.5 mb-6">
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{c.bullets.map((b) => (
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<li key={b} className="text-[12px] text-white/60 flex items-start gap-2">
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<span className="text-[#d9ff00] mt-0.5">·</span>
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<span>{b}</span>
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</li>
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))}
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</ul>
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<div className="mt-auto">
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<span className={`inline-flex items-center gap-2 px-4 py-2 rounded-md text-xs font-semibold transition-all ${c.accent}`}>
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Open {c.title} →
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</span>
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</div>
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</a>
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);
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})}
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</div>
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<p className="text-center text-[11px] text-white/30 mt-8">
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<a href="/batch" className="hover:text-white/60">/batch</a>{' '}·{' '}
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<a href="/studio" className="hover:text-white/60">/studio</a>
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</p>
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</div>
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</main>
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</div>
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);
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}
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46
components/SectionSwitcher.jsx
Normal file
46
components/SectionSwitcher.jsx
Normal file
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@ -0,0 +1,46 @@
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'use client';
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// Two-pill switcher between the Studio (image/video/etc) and the Batch
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// (CSV-driven automation) sections. Rendered in the header of every
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// shell so wherever you are, you can jump to the other side.
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const SECTIONS = [
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{ id: 'studio', label: 'Studio', href: '/studio' },
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{ id: 'batch', label: 'Batch', href: '/batch' },
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];
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export default function SectionSwitcher({ active }) {
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return (
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<nav
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role="tablist"
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aria-label="Section"
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className="flex items-center gap-0.5 bg-white/5 border border-white/[0.04] rounded-md p-0.5"
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>
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{SECTIONS.map((s) => {
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const isActive = active === s.id;
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return (
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<a
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key={s.id}
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href={s.href}
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aria-selected={isActive}
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role="tab"
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className={`px-3 py-1 rounded text-[11px] font-semibold uppercase tracking-wide transition-colors ${
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isActive
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? 'bg-[#d9ff00] text-black'
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: 'text-white/60 hover:text-white hover:bg-white/5'
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}`}
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onClick={(e) => {
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try {
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if (typeof window !== 'undefined') {
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localStorage.setItem('lastSection', s.id);
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}
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} catch {}
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}}
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>
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{s.label}
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</a>
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);
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})}
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</nav>
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);
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}
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@ -5,6 +5,7 @@ import { useParams, useRouter } from 'next/navigation';
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import { ImageStudio, VideoStudio, LipSyncStudio, CinemaStudio, WorkflowStudio, AgentStudio, getUserBalance } from 'studio';
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import axios from 'axios';
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import ApiKeyModal from './ApiKeyModal';
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import SectionSwitcher from './SectionSwitcher';
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const TABS = [
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{ id: 'image', label: 'Image Studio' },
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@ -240,14 +241,17 @@ export default function StandaloneShell() {
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{/* Header */}
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{isHeaderVisible && (
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<header className="flex-shrink-0 h-14 border-b border-white/[0.03] flex items-center justify-between px-6 bg-black/20 backdrop-blur-md z-40">
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{/* Left: Logo */}
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<div className="flex items-center gap-2">
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<div className="w-8 h-8 bg-white rounded-lg flex items-center justify-center">
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<svg width="20" height="20" viewBox="0 0 24 24" fill="none" stroke="black" strokeWidth="2.5" strokeLinecap="round" strokeLinejoin="round">
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<path d="M12 2L2 7l10 5 10-5-10-5zM2 17l10 5 10-5M2 12l10 5 10-5"/>
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</svg>
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</div>
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<span className="text-sm font-bold tracking-tight hidden sm:block">OpenGenerativeAI</span>
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{/* Left: Logo + section switcher */}
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<div className="flex items-center gap-3">
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<a href="/" className="flex items-center gap-2 hover:opacity-80 transition-opacity" title="Home">
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<div className="w-8 h-8 bg-white rounded-lg flex items-center justify-center">
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<svg width="20" height="20" viewBox="0 0 24 24" fill="none" stroke="black" strokeWidth="2.5" strokeLinecap="round" strokeLinejoin="round">
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<path d="M12 2L2 7l10 5 10-5-10-5zM2 17l10 5 10-5M2 12l10 5 10-5"/>
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</svg>
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</div>
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<span className="text-sm font-bold tracking-tight hidden sm:block">OpenGenerativeAI</span>
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</a>
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<SectionSwitcher active="studio" />
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</div>
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{/* Center: Navigation */}
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@ -60,7 +60,7 @@ export default function AddAssetModal({ apiKey, endpoint, label, onClose, onCrea
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type="text"
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value={name}
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onChange={(e) => setName(e.target.value)}
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placeholder={label === 'Trainer' ? 'e.g. Raj' : 'e.g. Ahoum studio'}
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placeholder={label === 'Trainer' ? 'e.g. Raj' : 'e.g. Main studio'}
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className="w-full bg-white/5 border border-white/[0.03] rounded-md px-4 py-2 text-white placeholder-white/20 focus:outline-none focus:ring-1 focus:ring-[#d9ff00]/30"
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required
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/>
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@ -1,6 +1,7 @@
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'use client';
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import { useEffect, useState, useCallback, useMemo } from 'react';
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import SectionSwitcher from '@/components/SectionSwitcher';
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const STATUS_STYLES = {
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draft: 'bg-white/5 text-white/60 border-white/10',
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@ -115,6 +116,8 @@ export default function BatchDetail({ batchId, apiKey }) {
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{/* Top header */}
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<header className="flex-shrink-0 h-14 border-b border-white/[0.03] flex items-center justify-between px-6 bg-black/20 backdrop-blur-md">
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<div className="flex items-center gap-3">
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<SectionSwitcher active="batch" />
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<span className="text-white/20">·</span>
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<a href="/batch" className="text-white/40 hover:text-white text-[12px]">← Back to batches</a>
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<span className="text-white/20">/</span>
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<span className="text-sm font-bold tracking-tight">{batch.name}</span>
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@ -2,6 +2,7 @@
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import { useEffect, useState } from 'react';
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import ApiKeyModal from '@/components/ApiKeyModal';
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import SectionSwitcher from '@/components/SectionSwitcher';
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import TrainersTab from './TrainersTab';
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import StudiosTab from './StudiosTab';
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import BatchesTab from './BatchesTab';
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@ -56,13 +57,15 @@ export default function BatchShell() {
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<div className="min-h-screen bg-[#030303] text-white flex flex-col">
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<header className="flex-shrink-0 h-14 border-b border-white/[0.03] flex items-center justify-between px-6 bg-black/20 backdrop-blur-md">
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<div className="flex items-center gap-3">
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<div className="w-8 h-8 bg-white rounded-lg flex items-center justify-center">
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<svg width="20" height="20" viewBox="0 0 24 24" fill="none" stroke="black" strokeWidth="2.5" strokeLinecap="round" strokeLinejoin="round">
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<path d="M12 2L2 7l10 5 10-5-10-5zM2 17l10 5 10-5M2 12l10 5 10-5" />
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</svg>
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</div>
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<span className="text-sm font-bold tracking-tight">Batch</span>
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<span className="text-white/30 text-sm">/ Open Generative AI</span>
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<a href="/" className="flex items-center gap-3 hover:opacity-80 transition-opacity" title="Home">
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<div className="w-8 h-8 bg-white rounded-lg flex items-center justify-center">
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<svg width="20" height="20" viewBox="0 0 24 24" fill="none" stroke="black" strokeWidth="2.5" strokeLinecap="round" strokeLinejoin="round">
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<path d="M12 2L2 7l10 5 10-5-10-5zM2 17l10 5 10-5M2 12l10 5 10-5" />
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</svg>
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</div>
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<span className="text-sm font-bold tracking-tight hidden sm:block">OpenGenerativeAI</span>
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</a>
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<SectionSwitcher active="batch" />
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</div>
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<nav className="flex items-center gap-6">
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@ -83,12 +86,6 @@ export default function BatchShell() {
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</nav>
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<div className="flex items-center gap-3">
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<a
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href="/studio"
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className="text-[12px] text-white/50 hover:text-white/80 transition-colors"
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>
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← Studio
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</a>
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<button
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onClick={handleKeyChange}
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className="text-[11px] text-white/40 hover:text-red-400 transition-colors"
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|
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@ -18,7 +18,7 @@ services:
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worker:
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user: root
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command: ["sh", "-c", "echo 'worker placeholder — replaced in slice 4'; tail -f /dev/null"]
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command: ["sh", "-c", "npx prisma generate && node worker/index.js"]
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volumes:
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- ./:/app
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- worker_node_modules:/app/node_modules
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|
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@ -54,7 +54,11 @@ function normaliseRow(raw, idx) {
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practiceName,
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characterLabel: character,
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studioLabel: studio || null,
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prompt: composePrompt({ description, startPosition, cameraAngle }),
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// Worker renders the full template (lib/promptTemplate.js) at submit
|
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// time using trainer, studio, and the structured fields below. We just
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// store the raw practice description here so the prompt-builder has
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// clean inputs to work with.
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prompt: description,
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rawDescription: description,
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startPosition: startPosition || null,
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cameraAngle: cameraAngle || null,
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|
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@ -63,14 +67,6 @@ function normaliseRow(raw, idx) {
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};
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}
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function composePrompt({ description, startPosition, cameraAngle }) {
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const parts = [];
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if (description) parts.push(description);
|
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if (startPosition) parts.push(`Start position: ${startPosition}.`);
|
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if (cameraAngle) parts.push(`Camera: ${cameraAngle}.`);
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return parts.join(' ');
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}
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function parseDuration(s) {
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if (!s) return 15;
|
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const m = s.match(/(\d+)/);
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|
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78
lib/promptTemplate.js
Normal file
78
lib/promptTemplate.js
Normal file
|
|
@ -0,0 +1,78 @@
|
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// Hard-coded prompt template for the seedance-v2.0-i2v batch generations.
|
||||
// Duration, aspect_ratio, and quality are intentionally NOT in the prompt —
|
||||
// they're separate fields in the MuAPI request body.
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//
|
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// Inputs:
|
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// trainer — { name, csvLabel, ... } from the trainers table
|
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// studio — { name, csvLabel, ... } from the studios table (may be null)
|
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// job — { practiceName, prompt (raw description),
|
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// startPosition, cameraAngle }
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//
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// Returns a single multi-line string ready to drop into payload.prompt.
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export function renderPrompt({ trainer, studio, job }) {
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const trainerName = (trainer?.name || trainer?.csvLabel || 'the trainer').trim();
|
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const studioName = (studio?.name || studio?.csvLabel || 'the studio').trim();
|
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const practice = job?.practiceName?.trim() || 'the practice';
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const camera = job?.cameraAngle?.trim() || 'eye-level tripod shot';
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const startPosition = job?.startPosition?.trim() || 'a relaxed neutral standing position';
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const description = job?.prompt?.trim() || '';
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return [
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`Single continuous take of @${trainerName} performing ${practice} inside @${studioName}.`,
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`Camera: ${camera}, static tripod shot, no camera movement.`,
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||||
`@${trainerName} starts in ${startPosition}.`,
|
||||
``,
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`Step-by-step movement:`,
|
||||
description,
|
||||
``,
|
||||
`Movement style:`,
|
||||
`- Controlled and instructional`,
|
||||
`- clearly demonstrates correct form`,
|
||||
`- no abrupt or unnatural motion`,
|
||||
``,
|
||||
`Biomechanics constraints:`,
|
||||
`- correct joint alignment at all times`,
|
||||
`- natural range of motion (no overextension)`,
|
||||
`- stable base and grounded contact with floor`,
|
||||
`- balanced weight distribution`,
|
||||
`- spine remains neutral unless specified`,
|
||||
`Movement must follow real human biomechanics, no artificial motion.`,
|
||||
``,
|
||||
`Identity constraints:`,
|
||||
`- @${trainerName} must remain 100% consistent (face, body, proportions)`,
|
||||
`- no identity drift`,
|
||||
``,
|
||||
`Environment constraints:`,
|
||||
`- keep studio layout exactly unchanged`,
|
||||
`- maintain plant positions, lighting, textures`,
|
||||
`- yoga mat remains centered and stable`,
|
||||
``,
|
||||
`Lighting:`,
|
||||
`- soft natural daylight (from studio windows)`,
|
||||
`- stable shadows`,
|
||||
`- no flicker or exposure shifts`,
|
||||
``,
|
||||
`Clothing:`,
|
||||
`- off-white / beige relaxed yoga wear`,
|
||||
`- natural fabric, no logos`,
|
||||
``,
|
||||
`Expression:`,
|
||||
`- calm, focused, slightly warm and approachable`,
|
||||
``,
|
||||
`Video style:`,
|
||||
`- real-world recording`,
|
||||
`- no stylization`,
|
||||
`- no cinematic effects`,
|
||||
`- no artificial smoothing`,
|
||||
``,
|
||||
`Constraints:`,
|
||||
`- no camera movement`,
|
||||
`- no cuts or transitions`,
|
||||
`- no limb warping`,
|
||||
`- no pose distortion`,
|
||||
`- no speed ramping`,
|
||||
`- no background changes`,
|
||||
`- no added props`,
|
||||
].join('\n');
|
||||
}
|
||||
|
|
@ -1,7 +1,7 @@
|
|||
{
|
||||
"name": "ai-agent",
|
||||
"version": "0.0.0-stub",
|
||||
"description": "Local stub. Upstream submodule (jaiprasad04/ai-agent) is unavailable. Provides no-op exports so the build succeeds; the /agents routes will render a 'feature unavailable' notice at runtime.",
|
||||
"description": "Local stub. Upstream submodule is unavailable. Provides no-op exports so the build succeeds; the /agents routes render a 'feature unavailable' notice at runtime.",
|
||||
"main": "src/index.js",
|
||||
"module": "src/index.js",
|
||||
"exports": {
|
||||
|
|
|
|||
|
|
@ -21,7 +21,7 @@ const Unavailable = ({ feature }) =>
|
|||
React.createElement(
|
||||
'p',
|
||||
{ style: { color: '#ffffff80', maxWidth: 480 } },
|
||||
`The ai-agent package is not bundled with this Ahoum-Dev fork. The /agents/${feature} route is a no-op. See packages/ai-agent/package.json for context.`
|
||||
`The ai-agent package is not bundled in this fork. The /agents/${feature} route is a no-op. See packages/ai-agent/package.json for context.`
|
||||
)
|
||||
);
|
||||
|
||||
|
|
|
|||
|
|
@ -1,7 +1,7 @@
|
|||
{
|
||||
"name": "workflow-builder",
|
||||
"version": "0.0.0-stub",
|
||||
"description": "Local stub. Upstream submodule (Anil-matcha/workflow-ui) is unavailable. Provides no-op exports so the build succeeds; the Workflows tab will render a 'feature unavailable' notice at runtime.",
|
||||
"description": "Local stub. Upstream submodule is unavailable. Provides no-op exports so the build succeeds; the Workflows tab renders a 'feature unavailable' notice at runtime.",
|
||||
"main": "src/index.js",
|
||||
"module": "src/index.js",
|
||||
"exports": {
|
||||
|
|
|
|||
|
|
@ -21,6 +21,6 @@ export const WorkflowBuilder = () =>
|
|||
React.createElement(
|
||||
'p',
|
||||
{ style: { color: '#ffffff80', maxWidth: 480 } },
|
||||
'The workflow-builder package is not bundled with this Ahoum-Dev fork. The Workflows tab is a no-op. See packages/workflow-ui/package.json for context.'
|
||||
'The workflow-builder package is not bundled in this fork. The Workflows tab is a no-op. See packages/workflow-ui/package.json for context.'
|
||||
)
|
||||
);
|
||||
|
|
|
|||
324
worker/index.js
Normal file
324
worker/index.js
Normal file
|
|
@ -0,0 +1,324 @@
|
|||
// Long-lived worker process. Polls Postgres for queued jobs, submits
|
||||
// them to MuAPI's seedance-v2.0-i2v endpoint, polls for results, applies
|
||||
// retry/backoff on failure, and updates batch counters.
|
||||
//
|
||||
// Run inside the `worker` docker-compose service. One process per
|
||||
// deployment is enough for typical batch volumes; the claim query
|
||||
// uses FOR UPDATE SKIP LOCKED so scaling to N workers is a one-line
|
||||
// change later.
|
||||
|
||||
import { PrismaClient } from '@prisma/client';
|
||||
import { readFile, writeFile, mkdir } from 'node:fs/promises';
|
||||
import path from 'node:path';
|
||||
import { renderPrompt } from '../lib/promptTemplate.js';
|
||||
|
||||
const prisma = new PrismaClient({ log: ['error'] });
|
||||
|
||||
const MUAPI_BASE = process.env.MUAPI_BASE_URL || 'https://api.muapi.ai';
|
||||
const API_KEY = process.env.MUAPI_API_KEY || '';
|
||||
const TICK_MS = parseInt(process.env.WORKER_TICK_MS || '2000', 10);
|
||||
const UPLOAD_DIR = process.env.UPLOAD_DIR || '/data/uploads';
|
||||
|
||||
const TERMINAL_OK = new Set(['completed', 'succeeded', 'success']);
|
||||
const TERMINAL_FAIL = new Set(['failed', 'error']);
|
||||
|
||||
let stopping = false;
|
||||
process.on('SIGINT', () => { stopping = true; });
|
||||
process.on('SIGTERM', () => { stopping = true; });
|
||||
|
||||
log('starting', {
|
||||
base: MUAPI_BASE,
|
||||
hasApiKey: !!API_KEY,
|
||||
tickMs: TICK_MS,
|
||||
uploadDir: UPLOAD_DIR,
|
||||
});
|
||||
|
||||
await recoverOrphans();
|
||||
|
||||
while (!stopping) {
|
||||
try {
|
||||
await tick();
|
||||
} catch (err) {
|
||||
log('tick.error', { err: err.message });
|
||||
}
|
||||
await sleep(TICK_MS);
|
||||
}
|
||||
|
||||
log('stopping');
|
||||
await prisma.$disconnect();
|
||||
|
||||
// ────────────────────────────────────────────────────────────────────────────
|
||||
async function tick() {
|
||||
if (!API_KEY) return; // can't do anything useful without a key
|
||||
|
||||
const batches = await prisma.batch.findMany({
|
||||
where: { status: 'running' },
|
||||
orderBy: { createdAt: 'asc' },
|
||||
});
|
||||
|
||||
for (const batch of batches) {
|
||||
await advanceBatch(batch);
|
||||
}
|
||||
|
||||
// Polling jobs may belong to running OR paused batches (we let in-flight
|
||||
// calls finish even on pause to avoid wasting credits).
|
||||
await pollPending();
|
||||
}
|
||||
|
||||
async function advanceBatch(batch) {
|
||||
// Count in-flight slots
|
||||
const inflight = await prisma.job.count({
|
||||
where: { batchId: batch.id, status: { in: ['submitting', 'polling'] } },
|
||||
});
|
||||
const slots = batch.concurrency - inflight;
|
||||
if (slots <= 0) return;
|
||||
|
||||
// Claim queued jobs atomically with SKIP LOCKED
|
||||
const ids = await claimJobs(batch.id, slots);
|
||||
if (ids.length === 0) {
|
||||
await maybeMarkCompleted(batch);
|
||||
return;
|
||||
}
|
||||
|
||||
await Promise.all(ids.map(submitJob));
|
||||
}
|
||||
|
||||
async function claimJobs(batchId, slots) {
|
||||
return prisma.$transaction(async (tx) => {
|
||||
const rows = await tx.$queryRaw`
|
||||
SELECT id FROM jobs
|
||||
WHERE batch_id = ${batchId}
|
||||
AND status = 'queued'
|
||||
AND (next_attempt_at IS NULL OR next_attempt_at <= NOW())
|
||||
ORDER BY row_index ASC
|
||||
LIMIT ${slots}
|
||||
FOR UPDATE SKIP LOCKED
|
||||
`;
|
||||
const ids = rows.map((r) => r.id);
|
||||
if (ids.length === 0) return [];
|
||||
await tx.job.updateMany({
|
||||
where: { id: { in: ids } },
|
||||
data: { status: 'submitting', startedAt: new Date(), error: null },
|
||||
});
|
||||
return ids;
|
||||
});
|
||||
}
|
||||
|
||||
async function submitJob(jobId) {
|
||||
const job = await prisma.job.findUnique({
|
||||
where: { id: jobId },
|
||||
include: {
|
||||
trainer: true,
|
||||
studio: true,
|
||||
batch: { select: { model: true } },
|
||||
},
|
||||
});
|
||||
if (!job) return;
|
||||
|
||||
try {
|
||||
if (!job.trainer) throw new Error('Job has no trainer');
|
||||
const trainerCdnUrl = await ensureMuapiUrl('trainer', job.trainer);
|
||||
|
||||
const fullPrompt = renderPrompt({
|
||||
trainer: job.trainer,
|
||||
studio: job.studio,
|
||||
job,
|
||||
});
|
||||
|
||||
const payload = {
|
||||
prompt: fullPrompt,
|
||||
images_list: [trainerCdnUrl],
|
||||
aspect_ratio: job.aspectRatio,
|
||||
duration: job.duration,
|
||||
quality: job.quality,
|
||||
};
|
||||
|
||||
const submitRes = await fetch(`${MUAPI_BASE}/api/v1/${job.batch.model}`, {
|
||||
method: 'POST',
|
||||
headers: { 'Content-Type': 'application/json', 'x-api-key': API_KEY },
|
||||
body: JSON.stringify(payload),
|
||||
});
|
||||
|
||||
if (!submitRes.ok) {
|
||||
const text = await submitRes.text().catch(() => '');
|
||||
throw new Error(`MuAPI ${submitRes.status}: ${text.slice(0, 200)}`);
|
||||
}
|
||||
|
||||
const data = await submitRes.json();
|
||||
const requestId = data.request_id || data.id;
|
||||
if (!requestId) throw new Error(`No request_id in response: ${JSON.stringify(data).slice(0, 200)}`);
|
||||
|
||||
await prisma.job.update({
|
||||
where: { id: job.id },
|
||||
data: { status: 'polling', muapiRequestId: requestId },
|
||||
});
|
||||
log('submit.ok', { jobId: job.id, requestId });
|
||||
} catch (err) {
|
||||
log('submit.fail', { jobId: job.id, err: err.message });
|
||||
await markFailureWithBackoff(job.id, err.message);
|
||||
}
|
||||
}
|
||||
|
||||
async function pollPending() {
|
||||
const polling = await prisma.job.findMany({
|
||||
where: { status: 'polling', muapiRequestId: { not: null } },
|
||||
take: 50,
|
||||
});
|
||||
await Promise.all(polling.map(pollJob));
|
||||
}
|
||||
|
||||
async function pollJob(job) {
|
||||
try {
|
||||
const res = await fetch(`${MUAPI_BASE}/api/v1/predictions/${job.muapiRequestId}/result`, {
|
||||
headers: { 'x-api-key': API_KEY },
|
||||
});
|
||||
if (!res.ok) {
|
||||
// 5xx — transient, leave for next tick. 4xx — fail with backoff.
|
||||
if (res.status >= 500) return;
|
||||
const text = await res.text().catch(() => '');
|
||||
await markFailureWithBackoff(job.id, `Poll ${res.status}: ${text.slice(0, 200)}`);
|
||||
return;
|
||||
}
|
||||
const data = await res.json();
|
||||
const status = data.status?.toLowerCase();
|
||||
if (TERMINAL_OK.has(status)) {
|
||||
const videoUrl = data.outputs?.[0] || data.url || data.output?.url || data.video_url || null;
|
||||
await prisma.$transaction([
|
||||
prisma.job.update({
|
||||
where: { id: job.id },
|
||||
data: { status: 'done', videoUrl, completedAt: new Date() },
|
||||
}),
|
||||
prisma.batch.update({
|
||||
where: { id: job.batchId },
|
||||
data: { done: { increment: 1 } },
|
||||
}),
|
||||
]);
|
||||
log('poll.done', { jobId: job.id, videoUrl });
|
||||
return;
|
||||
}
|
||||
if (TERMINAL_FAIL.has(status)) {
|
||||
await markFailureWithBackoff(job.id, data.error || `MuAPI status: ${status}`);
|
||||
return;
|
||||
}
|
||||
// pending / in_progress — leave it
|
||||
} catch (err) {
|
||||
log('poll.error', { jobId: job.id, err: err.message });
|
||||
}
|
||||
}
|
||||
|
||||
async function markFailureWithBackoff(jobId, errorMsg) {
|
||||
const job = await prisma.job.findUnique({ where: { id: jobId } });
|
||||
if (!job) return;
|
||||
|
||||
const nextRetries = job.retries + 1;
|
||||
if (nextRetries > 3) {
|
||||
await prisma.$transaction([
|
||||
prisma.job.update({
|
||||
where: { id: jobId },
|
||||
data: {
|
||||
status: 'failed',
|
||||
retries: nextRetries,
|
||||
error: errorMsg.slice(0, 1000),
|
||||
completedAt: new Date(),
|
||||
},
|
||||
}),
|
||||
prisma.batch.update({
|
||||
where: { id: job.batchId },
|
||||
data: { failed: { increment: 1 } },
|
||||
}),
|
||||
]);
|
||||
log('job.failed', { jobId, retries: nextRetries });
|
||||
return;
|
||||
}
|
||||
|
||||
const backoffMs = Math.min(10 * Math.pow(3, job.retries), 300) * 1000;
|
||||
await prisma.job.update({
|
||||
where: { id: jobId },
|
||||
data: {
|
||||
status: 'queued',
|
||||
retries: nextRetries,
|
||||
error: errorMsg.slice(0, 1000),
|
||||
nextAttemptAt: new Date(Date.now() + backoffMs),
|
||||
muapiRequestId: null,
|
||||
},
|
||||
});
|
||||
log('job.retry', { jobId, retries: nextRetries, backoffMs });
|
||||
}
|
||||
|
||||
async function maybeMarkCompleted(batch) {
|
||||
const counts = await prisma.job.groupBy({
|
||||
by: ['status'],
|
||||
where: { batchId: batch.id },
|
||||
_count: { _all: true },
|
||||
});
|
||||
const map = Object.fromEntries(counts.map((c) => [c.status, c._count._all]));
|
||||
const finished = (map.done || 0) + (map.failed || 0) + (map.cancelled || 0);
|
||||
if (finished >= batch.total) {
|
||||
await prisma.batch.update({
|
||||
where: { id: batch.id },
|
||||
data: { status: 'completed' },
|
||||
});
|
||||
log('batch.completed', { batchId: batch.id });
|
||||
}
|
||||
}
|
||||
|
||||
// If the imageUrl is local (/api/uploads/...), upload the file to MuAPI
|
||||
// and persist the resulting CDN URL so we only pay the round-trip once.
|
||||
async function ensureMuapiUrl(kind, asset) {
|
||||
const url = asset.imageUrl || '';
|
||||
if (url.startsWith('http://') || url.startsWith('https://')) return url;
|
||||
|
||||
// Local URL — re-upload from disk to MuAPI.
|
||||
const fileName = url.split('/').pop();
|
||||
if (!fileName) throw new Error(`Invalid asset url: ${url}`);
|
||||
const folder = kind === 'trainer' ? 'trainers' : 'studios';
|
||||
const filePath = path.join(UPLOAD_DIR, folder, decodeURIComponent(fileName));
|
||||
const buf = await readFile(filePath);
|
||||
|
||||
const form = new FormData();
|
||||
form.append('file', new Blob([buf]), fileName);
|
||||
|
||||
const res = await fetch(`${MUAPI_BASE}/api/v1/upload_file`, {
|
||||
method: 'POST',
|
||||
headers: { 'x-api-key': API_KEY },
|
||||
body: form,
|
||||
});
|
||||
if (!res.ok) {
|
||||
const text = await res.text().catch(() => '');
|
||||
throw new Error(`MuAPI upload_file ${res.status}: ${text.slice(0, 200)}`);
|
||||
}
|
||||
const data = await res.json();
|
||||
const cdnUrl = data.url || data.file_url || data?.data?.url;
|
||||
if (!cdnUrl) throw new Error('MuAPI upload returned no URL');
|
||||
|
||||
// Persist back to DB so we don't re-upload for future jobs.
|
||||
if (kind === 'trainer') {
|
||||
await prisma.trainer.update({ where: { id: asset.id }, data: { imageUrl: cdnUrl } });
|
||||
} else {
|
||||
await prisma.studio.update({ where: { id: asset.id }, data: { imageUrl: cdnUrl } });
|
||||
}
|
||||
log('reupload.ok', { kind, assetId: asset.id });
|
||||
return cdnUrl;
|
||||
}
|
||||
|
||||
async function recoverOrphans() {
|
||||
// Re-queue anything left in 'submitting' from a crashed previous run.
|
||||
const submitting = await prisma.job.updateMany({
|
||||
where: { status: 'submitting' },
|
||||
data: { status: 'queued', muapiRequestId: null },
|
||||
});
|
||||
if (submitting.count > 0) log('recover.submitting', { count: submitting.count });
|
||||
|
||||
// 'polling' jobs can keep going — we have their muapiRequestId.
|
||||
const stillPolling = await prisma.job.count({ where: { status: 'polling' } });
|
||||
if (stillPolling > 0) log('recover.polling', { count: stillPolling });
|
||||
}
|
||||
|
||||
function sleep(ms) {
|
||||
return new Promise((r) => setTimeout(r, ms));
|
||||
}
|
||||
|
||||
function log(event, fields = {}) {
|
||||
const ts = new Date().toISOString();
|
||||
process.stdout.write(`[${ts}] ${event} ${JSON.stringify(fields)}\n`);
|
||||
}
|
||||
3
worker/package.json
Normal file
3
worker/package.json
Normal file
|
|
@ -0,0 +1,3 @@
|
|||
{
|
||||
"type": "module"
|
||||
}
|
||||
Loading…
Add table
Add a link
Reference in a new issue