# MODELBEAST

Local-first web app that turns videos, images, and 3D files into meshes, splats, mocap, and rigged characters on the M3 Ultra. See [PLAN.md](PLAN.md) for the full verified tool matrix and roadmap, and [HANDOFF.md](HANDOFF.md) for the agent build brief (phases 1–4 instructions).

## Run

```bash
/opt/homebrew/bin/uv run uvicorn server.main:app --host 0.0.0.0 --port 8777
```

Open http://localhost:8777 (or `http://<tailscale-ip>:8777` from any device on the tailnet).

Drag/drop/paste any video, image, or 3D file; or drop files into `data/inbox/` for auto-ingest. Pick an operator, tune its parameters, run. Add API keys / HuggingFace token under ⚙ Settings. Use ⊞ Compare to view several outputs side by side.

## Develop

- Backend: `server/` — FastAPI + SQLite (`data/modelbeast.db`), job runner runs operators as subprocesses across concurrency lanes (gpu=1, cpu=3, net=6). Settings/secrets in `server/settings.py` (env-injected, log-redacted).
- Frontend: `web/` — React + Vite + three.js + `@mkkellogg/gaussian-splats-3d`. After editing: `cd web && npm run build` (the server serves `web/dist`).
- Data: `data/assets/` (store), `data/jobs/` (job workdirs), `data/inbox/` (watch folder). Delete `data/` to reset. Tests use `MODELBEAST_DATA=<tmp>`.
- Tests: `./tests/smoke.sh` (12 framework checks). Benchmarks in [BENCHMARKS.md](BENCHMARKS.md).
- Heavy tools live in `vendor/` (repos) + `venvs/` (per-tool envs), both gitignored. Reinstall with `scripts/install_*.sh`.

## Setup for the local mesh generators (one-time)

`sf3d` and `trellis_mac` are installed but their weights are HuggingFace-gated. Accept the licenses (stabilityai/stable-fast-3d, facebook/dinov3-vitl16-pretrain-lvd1689m, briaai/RMBG-2.0), then `huggingface-cli login` or paste an HF token in Settings. Cloud `fal_*` operators need `FAL_KEY` in Settings.

## Operators

Each subfolder of `server/operators/` with a `manifest.json` is an operator. The UI auto-renders its parameter form from `params_schema` (JSON Schema) and filters by the selected asset's kind (`accepts`).

Contract: the runner invokes `<python> run.py --input <asset> --outdir <jobdir> --params '<json>'`. Write outputs into the outdir; optionally write `result.json` (`{"outputs": [{"path": ..., "name": ..., "meta": ...}]}`) to control what gets registered as assets. stdout/stderr become the job log.

Manifest fields: `id, name, category, description, accepts, produces, resources` (gpu/cpu/net lane), `requires_env` (gates the operator until the key is set), `python` (absolute venv path for heavy tools), `params_schema`. Operators can tag output asset kind via `result.json` output `meta.kind` (e.g. `splat`, `colmap_dataset`).

Current operators:
| id | lane | what |
|---|---|---|
| `ffprobe` | cpu | media inspection |
| `ffmpeg_frames` | cpu | video → frames (fps, mpdecimate dedupe, blur cull, max cap) |
| `blender_convert` | cpu | universal 3D format conversion via headless Blender |
| `colmap_poses` | cpu | frames → camera poses + sparse cloud (COLMAP 4.x + GLOMAP) |
| `brush_train` | gpu | colmap dataset → 3D gaussian splat (Brush, native Metal) |
| `sf3d` | gpu | image → GLB locally (Stable-Fast-3D, MPS) *[HF-gated]* |
| `trellis_mac` | gpu | image → GLB+PBR locally (TRELLIS.2 MPS port) *[HF-gated]* |
| `fal_trellis` / `fal_trellis2` / `fal_hunyuan3d` / `fal_hunyuan3d_v21` / `fal_rodin` | net | image → mesh via fal.ai API *[needs FAL_KEY]* |
| `fal_bg_remove` | net | image → subject cutout (BiRefNet v2) — run before any image→3D for a big quality jump |
| `fal_upscale` | net | image → faithful upscale (SeedVR) |
| `fal_image_edit` | net | image + instruction → edited image (nano-banana) |
| `fal_text_image` | net | prompt → image (Ideogram v3, readable text) — no input asset needed |

Recommended fal chain for best image→3D: `fal_bg_remove` → (`fal_upscale` if thin) → `fal_trellis2` or `fal_hunyuan3d_v21`. Note: Hunyuan v21 **multi-view** is broken on fal (verified 2026-07) — v21 is single-image only; use v2 for multi-view.

Heavy operators get their own uv venv (`"python": "<abs venv path>"` in the manifest). Remaining roadmap (object_capture, freemocap, retargeting, tripo/meshy character APIs, workflow presets, LLM copilot) is in [HANDOFF.md](HANDOFF.md) §5–8.