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- sensahin 1y agoA couple of days ago I saw a post here where someone built a similar “add things into a room” demo. I wondered how hard it would be to recreate it without touching code. As an experiment, I used Codex with GPT‑5, gave it GitHub, Vercel, and GCP access, and asked it to build and deploy a minimal version. How it works Web: Next.js on Vercel. Users pick a room and type what to add (e.g., “add a lamp”). State: Firestore stores room docs (paths, status, version). Images: Google Cloud Storage holds original/current images. Queue: API publishes edit requests to Pub/Sub. Worker: Cloud Run worker fetches the current image, calls Gemini to add the requested object, writes back to GCS, and updates Firestore. Live updates: The UI listens via SSE and refreshes when the version changes. Admin: Panic switch (disable edits just in case if i go out of api credit or something), per‑room reset, “auto‑reset” with a countdown broadcast to rooms, and a banned‑words filter. Rate limiting per IP to avoid spam. Infra odds‑and‑ends: simple presence via Firebase RTDB; GCS URLs as CDN. I have some free Gemini credits from Google, so I’m keeping it open to see how it behaves in the wild: latency, error modes, costs, moderation edge cases, etc. This is my first time watching a fully AI‑written codebase under real usage and load. Happy to answer questions or share more if people are curious.
- gus_massa 1y agoIs it closed now?