# Nikola Reljin

- **Event:** [Meta Global AI Developer Hackathon](https://cerebralvalley.ai/e/meta-ai-developer-hackathon)
- **When:** Oct 26, 12:00 PM – Nov 4, 9:00 PM (EST)
- **Where:** Online
- **Team:** [Nikola Reljin](https://cerebralvalley.ai/u/nikolareljin)
- **GitHub:** https://github.com/nikolareljin/orphan-parts
- **Demo video:** https://www.youtube.com/watch?v=3USMv4zCeD0
- **Gallery:** https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery
- **Page:** https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/2414

Orphan Parts Lens turns the drawer of old devices and loose parts most of us keep into a private inventory with evidence, and then into decisions: keep and fix it, reuse it in a build, sell it, give it away, or find the one missing piece that makes it work again.

The problem is one I live with: a frappé maker with a worn agitator, and a shelf of laptops, monitors and boards I couldn't price or place. Identifying a part, finding one that really fits, pricing it honestly and writing a listing each took an evening.

Photograph a label: SAM 3.1 finds it, Muse Spark reads it into fields you confirm, each with its source. A photo next to a ruler becomes a measurement with its uncertainty. When a part can't be tied to its device, the app asks for that device and reads its label (the agitator was traced to a Hamilton Beach 729).

What it does with the inventory:

- What should I do with it?: three cards for your skills (keep and fix, reuse, sell or give away), a recommendation, and a Muse Image drawing of the reuse idea. Answers are saved, never generated twice.

- Find a part: Marketplace search links plus Search the web, keeping only pages the search returned; rules check each candidate, and an unknown is never a pass. For the agitator it found the original part for $4.84.

- Sell or give away: price guidance from cited comparables and a Facebook Marketplace draft in Marketplace's own fields. Nothing is posted for you.

- Build and reuse: 11 projects from what you own (a photo NAS, a gaming coffee table, a smart desk calendar, a smart mirror, a kitchen dashboard...), each allocation checked by compatibility rules (memory generation, CPU socket, drive interface), with build packs and several drawings.

- Privacy: serials, product keys, MAC addresses and passwords in photos are blacked out on every shared copy.

- Checking the models' own work: Muse Spark reviews every Muse Image drawing against the real parts and every recommendation against the inventory; tuned parameters and best-of-N took matching drawings from 11/32 to 28/30 and halved the flagged recommendations. The loops ship as Muse Code skills.

Built during the hackathon (Oct 27 to Nov 4): FastAPI backend, React web app, Android capture app, docs with real examples, 900+ tests. The demo is 49 of my own parts, every model answer recorded, so it runs for free.

How to review (no sign-up, no key):

1. Video (2:52): https://www.youtube.com/watch?v=3USMv4zCeD0

2. Run it locally, about 10 minutes, Docker only: JUDGES.md
https://github.com/nikolareljin/orphan-parts/blob/main/JUDGES.md

3. Online, read-only (while up): https://orphan-parts.pages.dev

4. Docs and examples: https://nikolareljin.github.io/orphan-parts/

Optional: Android app (JUDGES.md, Part 2), or live models with your own Meta Model API key.

## More from Meta Global AI Developer Hackathon

- [KarLex AI](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/2411)
- [Vigilens](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/2412)
- [TeamHsain](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/2413)
- [Zyphers](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/2415)
- [Solo Team](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/2416)
- [Quoc Vu Junior](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/2417)

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