Headless control: mb CLI, AGENTS.md handover, serve scripts; verified-current image models
- mb: zero-dependency python CLI for the full API (ops/upload/run/wait/follow/ download incl. folder assets, retry/cancel, settings). Schema-aware -p k=v coercion. Works from any tailnet machine via MB_HOST. Tested end-to-end (upload -> blender_convert -> download). - AGENTS.md: complete handover brief for other agents using this box as an asset factory — endpoints, CLI reference, catalog, recipes, lanes/etiquette. - scripts/serve.sh (headless start/restart) + scripts/install_launchagent.sh (optional boot persistence, owner-run) - flux_local upgraded to mflux 0.18 reality: flux2-klein-4b default (Apache, UNGATED — runs with zero keys), klein-9b, schnell/schnell-4bit community quant, dev/krea-dev. Research verdict: FLUX.1-dev no longer competitive (Elo ~1027) vs klein ~1083-1119 vs nano-banana ~1154. - openrouter_image rewritten to the dedicated Image API (POST /api/v1/images): b64_json parsing, seed, resolution/aspect, exact usage.cost logging; model enum: gemini-2.5-flash-image / 3.1-flash-image (NB2) / 3-pro-image Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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AGENTS.md
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AGENTS.md
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# AGENTS.md — Using the M3 Ultra asset factory (MODELBEAST)
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**Audience: any agent (or human) that needs 3D models, gaussian splats, camera-pose
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datasets, generated/cleaned images, or format conversions.** This machine — an
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M3 Ultra Mac Studio, 256GB unified memory — runs MODELBEAST, a job server that
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wraps local Apple-Silicon ML tools and cloud APIs behind one HTTP API. You send
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files and job requests; it returns finished assets.
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## 1. Reaching it
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- **Base URL (tailnet):** `http://100.89.131.57:8777` — from the machine itself, `http://localhost:8777`.
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- **No auth.** The tailnet is the security boundary. Do not expose this port publicly.
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- Web UI at the same URL (humans). Agents use the REST API or the `mb` CLI.
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- If the server is down (connection refused): on the M3 run `~/Documents/MODELBEAST/scripts/serve.sh` (or ask the owner to run `scripts/install_launchagent.sh` once for boot persistence).
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## 2. The `mb` CLI (recommended)
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One stdlib-only python3 file at repo root — copy it anywhere (`scp m3ultra:~/Documents/MODELBEAST/mb .`) and point it at the box:
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```bash
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export MB_HOST=http://100.89.131.57:8777
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./mb ops -v # operator catalog + every parameter (LIVE truth — trust this over any doc)
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./mb upload photo.jpg # -> prints asset id
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./mb run fal_trellis2 --asset <ID> -p resolution=1024 --wait --download out/
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./mb run flux_local -p prompt="a brass astrolabe" -p seed=7 --follow
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./mb jobs # recent jobs ./mb log <JOB> -f # stream a log
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./mb assets --kind model # browse assets ./mb get <ASSET> -o out/
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./mb retry <JOB> / ./mb cancel <JOB> / ./mb rm-job <JOB>
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```
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- `mb run --file local.png ...` uploads and runs in one step.
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- `--wait` blocks and prints output asset ids; `--download DIR` also fetches them; `--follow` streams the live log. Exit codes: 0 done, 2 error, 3 cancelled.
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- `-p k=v` is type-coerced against the operator's schema; `--params-json '{...}'` for anything complex.
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### Raw REST (if you can't run python)
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```
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GET /api/operators # catalog incl. params_schema (JSON Schema)
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POST /api/assets # multipart file upload -> asset
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GET /api/assets # list (outputs have parent_job=<job id>)
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GET /api/assets/{id}/file[?member=f] # download (folder assets: JSON listing, then ?member=)
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POST /api/jobs # {"operator": id, "asset_id": id|null, "params": {...}}
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GET /api/jobs/{id} # status: queued|running|done|error|cancelled + log
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POST /api/jobs/{id}/cancel | /retry # control
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```
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Poll `GET /api/jobs/{id}` every ~2s. When `done`, your outputs are the assets whose `parent_job` equals the job id.
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## 3. What it can make (operator catalog — run `mb ops -v` for live params)
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| Goal | Operator(s) | Notes |
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|---|---|---|
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| **image → 3D mesh (GLB)** | `fal_trellis2` (SOTA open, PBR, $0.25–0.35) · `fal_hunyuan3d_v21` (~90s, PBR) · `fal_rodin` (hero-grade, $0.40+) · `fal_trellis` ($0.02 draft) · local: `trellis_mac`, `sf3d` | **Best practice: run `fal_bg_remove` first** and feed the cutout — biggest quality lever. Local ops need the owner's HF token; fal ops need FAL_KEY (check `mb ops` for `[needs ...]` flags) |
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| **video → gaussian splat** | `ffmpeg_frames` → `colmap_poses` → `brush_train` | 100% local/free. Orbit video, 2–3 fps sampling, 150–300 frames. 30k steps = quality, 1500 = fast preview |
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| **video → camera poses** | `ffmpeg_frames` → `colmap_poses` | Outputs a COLMAP dataset folder (cameras/images/points3D) |
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| **prompt → image** | `flux_local` (on-device, free, seed-reproducible; `flux2-klein-4b` works with zero keys) · `openrouter_image` (nano-banana family, ~$0.04–0.24/img) · `fal_text_image` (Ideogram, readable text) | A/B: same prompt through several, then judge |
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| **image cleanup** | `fal_bg_remove` (cutout) · `fal_upscale` (faithful) · `fal_image_edit` (prompt edits: "remove the sticker") | All sub-cent to low-cent |
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| **3D format conversion** | `blender_convert` | GLB/GLTF/OBJ/FBX/STL/PLY/USD/BLEND in → glb/fbx/obj/usd/usdz/stl/ply/blend out |
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| **media inspection** | `ffprobe` | codec/resolution/fps/duration JSON |
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## 4. Recipes
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**Photo → clean game-ready mesh (the standard chain):**
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```bash
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CUT=$(./mb run fal_bg_remove --file product.jpg --wait | awk '/image/{print $1}' | tail -1)
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./mb run fal_trellis2 --asset $CUT -p resolution=1024 --wait --download out/
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```
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**Orbit video → splat:**
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```bash
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VID=$(./mb upload orbit.mp4 | awk '{print $1}')
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FRAMES=$(./mb run ffmpeg_frames --asset $VID -p fps=2.5 -p max_frames=250 --wait | awk '/frames/{print $1}' | tail -1)
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DS=$(./mb run colmap_poses --asset $FRAMES --wait | awk '/colmap_dataset/{print $1}' | tail -1)
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./mb run brush_train --asset $DS -p total_steps=30000 --wait --download out/
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```
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**Local vs cloud image A/B (fixed prompt):**
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```bash
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P="isometric low-poly tavern, warm lantern light"
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./mb run flux_local -p prompt="$P" -p model=flux2-klein-4b -p seed=7 --wait
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./mb run openrouter_image -p prompt="$P" -p model=google/gemini-2.5-flash-image --wait
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# then compare in the web UI (⊞ Compare) or download both
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```
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**Drop-folder ingest (no API needed):** copy files into `~/Documents/MODELBEAST/data/inbox/` on the M3 — they auto-register as assets within ~6s (size-stable check). Useful for rsync/UE/Blender exports.
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## 5. Job semantics you must respect
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- **Concurrency lanes:** `gpu` jobs run ONE at a time (Metal contention — trellis_mac, sf3d, brush_train, flux_local); `cpu` 3 at once; `net` (cloud APIs) 6 at once. Queued jobs wait their turn — don't spam retries because something is `queued`.
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- **First-run weight downloads** on local ML operators can take 10–30+ min (klein ~15GB, schnell ~24GB, TRELLIS ~15GB). The job log shows download progress; be patient, don't cancel.
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- Logs stream into the job record (`mb log ID -f`). Secrets are redacted server-side.
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- A job that ends `error` has the reason in `error` + last log lines. `mb retry ID` re-runs it with identical inputs.
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- Server restarts re-queue anything that was running. Jobs are cheap to re-run — assets are the durable artifacts.
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## 6. Keys, gating, and cost
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- Gated operators are visible but refuse to run with a clear error until the owner adds the key in ⚙ Settings (`fal_key`, `openrouter_key`, `hf_token`). Check gating live via `mb ops` (`[needs ...]`).
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- Rough costs when unlocked: fal_trellis $0.02 · hunyuan v21 ~$0.05–0.10 · trellis2 $0.25–0.35 · rodin $0.40+ · bg_remove/upscale sub-cent · nano-banana ~$0.039 · nano-banana-pro ~$0.134 · everything local = $0.
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- **Never ask for or handle the raw keys.** They live in the server's settings vault.
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## 7. Etiquette & limits (you are a guest on someone's workstation)
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- Don't delete assets/jobs you didn't create.
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- Big batches: stagger `gpu` work; the owner may be using the machine.
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- Disk: weights + assets are large; if you generate hundreds of assets, download what you need and `mb rm-asset` your intermediates.
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- The box also hosts Ollama (`http://100.89.131.57:11434`, qwen3:235b/32b/8b) if you need local LLM inference — separate service, same etiquette.
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- Benchmarks so far: `BENCHMARKS.md`. Architecture and roadmap: `README.md`, `HANDOFF.md`, `PLAN.md`.
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## 8. Ops runbook (on the M3)
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```bash
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cd ~/Documents/MODELBEAST
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./scripts/serve.sh # start/restart headless (log: data/server.log)
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./tests/smoke.sh # 12-check regression suite (~30s, isolated data dir)
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./mb jobs # what's running
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git pull && cd web && npm run build && cd .. && ./scripts/serve.sh # deploy an update
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```
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Repo: `ssh://git@100.71.119.27:222/monster/modelbeast.git`. Heavy tools reinstall via `scripts/install_*.sh` (vendor/, venvs/, bin/ are not in git).
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@ -12,6 +12,14 @@ Open http://localhost:8777 (or `http://<tailscale-ip>:8777` from any device on t
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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.
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## Headless / agents
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Everything is driveable without the UI via the zero-dependency [`mb`](mb) CLI (works from any tailnet machine with `MB_HOST=http://100.89.131.57:8777`) or raw REST. **[AGENTS.md](AGENTS.md) is the complete handover brief** — endpoints, `mb` reference, operator catalog, recipes, job semantics, etiquette. Server ops: `scripts/serve.sh` (start/restart headless), `scripts/install_launchagent.sh` (optional boot persistence, owner-run).
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```bash
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./mb run fal_trellis2 --file photo.jpg -p resolution=1024 --wait --download out/
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```
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## Develop
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- 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).
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256
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Executable file
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Executable file
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#!/usr/bin/env python3
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"""mb — headless CLI for MODELBEAST. Zero dependencies (python3 stdlib only),
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works from any machine that can reach the server (tailnet included).
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export MB_HOST=http://100.89.131.57:8777 # default: http://localhost:8777
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mb ops [-v] list operators (+params with -v)
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mb assets [--kind image] list assets
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mb upload FILE [FILE...] upload files, print asset ids
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mb run OP [--asset ID | --file F] [-p k=v ...] [--params-json J]
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[--wait] [--follow] [--download DIR]
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mb job ID job status json
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mb jobs [-n 20] recent jobs
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mb log ID [-f] print job log (-f = follow to completion)
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mb wait ID [--download DIR] block until job finishes (exit 0/2/3)
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mb get ASSET_ID [-o PATH] download an asset (folders: all members)
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mb rm-asset ID / mb rm-job ID delete
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mb retry ID / mb cancel ID job control
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mb settings show settings (secrets masked)
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mb set KEY VALUE set a setting (e.g. keys — value visible in
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shell history; prefer the web UI for secrets)
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Typical: mb run flux_local -p prompt="a brass astrolabe" -p seed=7 --wait --download out/
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Exit codes: 0 ok/done, 1 usage/HTTP error, 2 job error, 3 job cancelled.
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"""
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import argparse
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import json
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import mimetypes
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import os
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import sys
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import time
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import urllib.error
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import urllib.request
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import uuid
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from pathlib import Path
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HOST = os.environ.get("MB_HOST", "http://localhost:8777").rstrip("/")
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def http(method, path, body=None):
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req = urllib.request.Request(HOST + path, method=method)
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data = None
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if body is not None:
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data = json.dumps(body).encode()
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req.add_header("Content-Type", "application/json")
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try:
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with urllib.request.urlopen(req, data=data, timeout=120) as r:
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ct = r.headers.get("content-type", "")
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raw = r.read()
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return json.loads(raw) if "json" in ct else raw
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except urllib.error.HTTPError as e:
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sys.exit(f"HTTP {e.code} {method} {path}: {e.read().decode()[:500]}")
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except urllib.error.URLError as e:
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sys.exit(f"cannot reach {HOST} ({e.reason}) — is the server up? set MB_HOST?")
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def upload_file(path):
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p = Path(path)
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if not p.is_file():
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sys.exit(f"no such file: {p}")
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boundary = uuid.uuid4().hex
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ctype = mimetypes.guess_type(p.name)[0] or "application/octet-stream"
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body = (f"--{boundary}\r\nContent-Disposition: form-data; name=\"file\"; "
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f"filename=\"{p.name}\"\r\nContent-Type: {ctype}\r\n\r\n").encode()
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body += p.read_bytes() + f"\r\n--{boundary}--\r\n".encode()
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req = urllib.request.Request(HOST + "/api/assets", data=body, method="POST")
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req.add_header("Content-Type", f"multipart/form-data; boundary={boundary}")
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try:
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with urllib.request.urlopen(req, timeout=600) as r:
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return json.loads(r.read())
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except urllib.error.HTTPError as e:
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sys.exit(f"upload failed: HTTP {e.code}: {e.read().decode()[:300]}")
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def coerce(op, key, value):
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"""Coerce k=v strings using the operator's JSON schema, else best-effort JSON."""
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prop = (op.get("params_schema", {}).get("properties", {}) or {}).get(key, {})
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t = prop.get("type")
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try:
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if t == "integer":
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return int(value)
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if t == "number":
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return float(value)
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if t == "boolean":
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return value.lower() in ("1", "true", "yes", "on")
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if t == "string":
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return value
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return json.loads(value)
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except (ValueError, json.JSONDecodeError):
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return value
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def outputs_of(job_id):
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return [a for a in http("GET", "/api/assets") if a.get("parent_job") == job_id]
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def download_asset(asset, dest_dir):
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dest_dir = Path(dest_dir)
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dest_dir.mkdir(parents=True, exist_ok=True)
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url = f"{HOST}/api/assets/{asset['id']}/file"
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with urllib.request.urlopen(url, timeout=600) as r:
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ct = r.headers.get("content-type", "")
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data = r.read()
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if "json" in ct:
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listing = json.loads(data)
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if listing.get("folder"):
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sub = dest_dir / asset["name"]
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sub.mkdir(exist_ok=True)
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for member in listing["files"]:
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murl = url + "?member=" + urllib.request.quote(member)
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with urllib.request.urlopen(murl, timeout=600) as r:
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(sub / member).write_bytes(r.read())
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print(f" ↓ {sub} ({len(listing['files'])} files)")
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return
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out = dest_dir / asset["name"]
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out.write_bytes(data)
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print(f" ↓ {out} ({len(data)} bytes)")
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def wait_for(job_id, follow=False, download=None):
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printed = 0
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last_status = None
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while True:
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j = http("GET", f"/api/jobs/{job_id}")
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if follow:
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log = j.get("log") or ""
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if len(log) > printed:
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sys.stdout.write(log[printed:])
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sys.stdout.flush()
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printed = len(log)
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elif j["status"] != last_status:
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print(f"[{job_id}] {j['status']}")
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last_status = j["status"]
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if j["status"] in ("done", "error", "cancelled"):
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if j["status"] == "error":
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print(f"ERROR: {j.get('error')}\n--- last log ---\n{(j.get('log') or '')[-1500:]}",
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file=sys.stderr)
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sys.exit(2)
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if j["status"] == "cancelled":
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sys.exit(3)
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outs = outputs_of(job_id)
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print(f"done — {len(outs)} output(s):")
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for a in outs:
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print(f" {a['id']} {a['kind']:<14} {a['name']}")
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if download:
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for a in outs:
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download_asset(a, download)
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return
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time.sleep(2)
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def main():
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ap = argparse.ArgumentParser(prog="mb", add_help=True)
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sub = ap.add_subparsers(dest="cmd", required=True)
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sub.add_parser("ops").add_argument("-v", action="store_true")
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p = sub.add_parser("assets"); p.add_argument("--kind")
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p = sub.add_parser("upload"); p.add_argument("files", nargs="+")
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p = sub.add_parser("run")
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p.add_argument("operator")
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p.add_argument("--asset"); p.add_argument("--file")
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p.add_argument("-p", "--param", action="append", default=[])
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p.add_argument("--params-json")
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p.add_argument("--wait", action="store_true")
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p.add_argument("--follow", action="store_true")
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p.add_argument("--download")
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p = sub.add_parser("job"); p.add_argument("id")
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p = sub.add_parser("jobs"); p.add_argument("-n", type=int, default=20)
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p = sub.add_parser("log"); p.add_argument("id"); p.add_argument("-f", action="store_true")
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p = sub.add_parser("wait"); p.add_argument("id"); p.add_argument("--download")
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p = sub.add_parser("get"); p.add_argument("id"); p.add_argument("-o", default=".")
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p = sub.add_parser("rm-asset"); p.add_argument("id")
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p = sub.add_parser("rm-job"); p.add_argument("id")
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p = sub.add_parser("retry"); p.add_argument("id")
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p = sub.add_parser("cancel"); p.add_argument("id")
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sub.add_parser("settings")
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p = sub.add_parser("set"); p.add_argument("key"); p.add_argument("value")
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a = ap.parse_args()
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if a.cmd == "ops":
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for op in http("GET", "/api/operators"):
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gate = f" [needs {','.join(op['requires_env'])}]" if op.get("requires_env") else ""
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inputs = ",".join(op["accepts"]) or "none (prompt-driven)"
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print(f"{op['id']:<20} {op.get('category','?'):<11} in:{inputs:<18} "
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f"lane:{op.get('resources','cpu')}{gate}")
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if a.v:
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||||
for k, d in (op.get("params_schema", {}).get("properties", {}) or {}).items():
|
||||
dv = f" (default {d['default']})" if "default" in d else ""
|
||||
en = f" one of {d['enum']}" if "enum" in d else ""
|
||||
print(f" -p {k}=<{d.get('type','any')}>{en}{dv} {d.get('description','')}")
|
||||
elif a.cmd == "assets":
|
||||
for x in http("GET", "/api/assets"):
|
||||
if a.kind and x["kind"] != a.kind:
|
||||
continue
|
||||
print(f"{x['id']} {x['kind']:<14} {x['size']:>10} {x['name']}")
|
||||
elif a.cmd == "upload":
|
||||
for f in a.files:
|
||||
asset = upload_file(f)
|
||||
print(f"{asset['id']} {asset['kind']} {asset['name']}")
|
||||
elif a.cmd == "run":
|
||||
ops = {o["id"]: o for o in http("GET", "/api/operators")}
|
||||
if a.operator not in ops:
|
||||
sys.exit(f"unknown operator '{a.operator}'. Run: mb ops")
|
||||
op = ops[a.operator]
|
||||
asset_id = a.asset
|
||||
if a.file:
|
||||
asset_id = upload_file(a.file)["id"]
|
||||
print(f"uploaded → {asset_id}")
|
||||
if op["accepts"] and not asset_id:
|
||||
sys.exit(f"{a.operator} needs an input ({','.join(op['accepts'])}): --asset ID or --file F")
|
||||
params = {}
|
||||
if a.params_json:
|
||||
params.update(json.loads(a.params_json))
|
||||
for kv in a.param:
|
||||
if "=" not in kv:
|
||||
sys.exit(f"bad -p '{kv}' (want k=v)")
|
||||
k, v = kv.split("=", 1)
|
||||
params[k] = coerce(op, k, v)
|
||||
job = http("POST", "/api/jobs",
|
||||
{"operator": a.operator, "asset_id": asset_id, "params": params})
|
||||
print(f"job {job['id']} queued")
|
||||
if a.wait or a.follow or a.download:
|
||||
wait_for(job["id"], follow=a.follow, download=a.download)
|
||||
elif a.cmd == "job":
|
||||
print(json.dumps(http("GET", f"/api/jobs/{a.id}"), indent=2))
|
||||
elif a.cmd == "jobs":
|
||||
for j in http("GET", "/api/jobs")[: a.n]:
|
||||
print(f"{j['id']} {j['status']:<9} {j['operator']}")
|
||||
elif a.cmd == "log":
|
||||
if a.f:
|
||||
wait_for(a.id, follow=True)
|
||||
else:
|
||||
print(http("GET", f"/api/jobs/{a.id}").get("log") or "(empty)")
|
||||
elif a.cmd == "wait":
|
||||
wait_for(a.id, download=a.download)
|
||||
elif a.cmd == "get":
|
||||
assets = {x["id"]: x for x in http("GET", "/api/assets")}
|
||||
if a.id not in assets:
|
||||
sys.exit("no such asset")
|
||||
download_asset(assets[a.id], a.o)
|
||||
elif a.cmd == "rm-asset":
|
||||
http("DELETE", f"/api/assets/{a.id}"); print("deleted")
|
||||
elif a.cmd == "rm-job":
|
||||
http("DELETE", f"/api/jobs/{a.id}"); print("deleted")
|
||||
elif a.cmd == "retry":
|
||||
j = http("POST", f"/api/jobs/{a.id}/retry"); print(f"new job {j['id']}")
|
||||
elif a.cmd == "cancel":
|
||||
http("POST", f"/api/jobs/{a.id}/cancel"); print("cancel requested")
|
||||
elif a.cmd == "settings":
|
||||
print(json.dumps(http("GET", "/api/settings"), indent=2))
|
||||
elif a.cmd == "set":
|
||||
http("PUT", "/api/settings", {a.key: a.value}); print("saved")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
31
scripts/install_launchagent.sh
Executable file
31
scripts/install_launchagent.sh
Executable file
@ -0,0 +1,31 @@
|
||||
#!/usr/bin/env bash
|
||||
# OPTIONAL (owner runs this by hand): keep MODELBEAST running across reboots
|
||||
# via a per-user LaunchAgent. Remove with:
|
||||
# launchctl bootout gui/$(id -u)/com.modelbeast.server
|
||||
# rm ~/Library/LaunchAgents/com.modelbeast.server.plist
|
||||
set -euo pipefail
|
||||
cd "$(dirname "$0")/.."
|
||||
ROOT=$(pwd)
|
||||
PLIST="$HOME/Library/LaunchAgents/com.modelbeast.server.plist"
|
||||
mkdir -p "$HOME/Library/LaunchAgents" "$ROOT/data"
|
||||
cat > "$PLIST" <<EOF
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
|
||||
<plist version="1.0"><dict>
|
||||
<key>Label</key><string>com.modelbeast.server</string>
|
||||
<key>ProgramArguments</key><array>
|
||||
<string>/opt/homebrew/bin/uv</string>
|
||||
<string>run</string><string>uvicorn</string><string>server.main:app</string>
|
||||
<string>--host</string><string>0.0.0.0</string>
|
||||
<string>--port</string><string>8777</string>
|
||||
</array>
|
||||
<key>WorkingDirectory</key><string>$ROOT</string>
|
||||
<key>KeepAlive</key><true/>
|
||||
<key>RunAtLoad</key><true/>
|
||||
<key>StandardOutPath</key><string>$ROOT/data/server.log</string>
|
||||
<key>StandardErrorPath</key><string>$ROOT/data/server.log</string>
|
||||
</dict></plist>
|
||||
EOF
|
||||
launchctl bootout "gui/$(id -u)/com.modelbeast.server" 2>/dev/null || true
|
||||
launchctl bootstrap "gui/$(id -u)" "$PLIST"
|
||||
echo "LaunchAgent installed + started. Server will survive reboots."
|
||||
12
scripts/serve.sh
Executable file
12
scripts/serve.sh
Executable file
@ -0,0 +1,12 @@
|
||||
#!/usr/bin/env bash
|
||||
# Start (or restart) the MODELBEAST server headless on port 8777.
|
||||
set -euo pipefail
|
||||
cd "$(dirname "$0")/.."
|
||||
lsof -ti:8777 | xargs kill 2>/dev/null || true
|
||||
sleep 1
|
||||
nohup /opt/homebrew/bin/uv run uvicorn server.main:app --host 0.0.0.0 --port 8777 \
|
||||
> data/server.log 2>&1 &
|
||||
sleep 2
|
||||
curl -sf -o /dev/null http://localhost:8777/api/operators \
|
||||
&& echo "MODELBEAST up: http://$( /Applications/Tailscale.app/Contents/MacOS/Tailscale ip -4 2>/dev/null || echo localhost):8777 (log: data/server.log)" \
|
||||
|| { echo "FAILED to start — tail data/server.log:"; tail -20 data/server.log; exit 1; }
|
||||
@ -2,7 +2,7 @@
|
||||
"id": "flux_local",
|
||||
"name": "FLUX (local, MLX)",
|
||||
"category": "generate",
|
||||
"description": "Prompt → image entirely on this Mac via mflux (MLX-native FLUX). schnell = 2-4 steps fast draft; dev = higher quality, 20-28 steps. BOTH are HF-gated now (verified 2026-07): accept the license on huggingface.co/black-forest-labs, then set the HuggingFace token in Settings. First run downloads weights (~24GB). No API cost, no cloud.",
|
||||
"description": "Prompt → image entirely on this Mac via mflux 0.18 (MLX). flux2-klein-4b = Apache/UNGATED, works out of the box, better than FLUX.1-schnell (~15GB first download). schnell-4bit = ungated community quant. schnell/dev/krea-dev/klein-9b are HF-gated (license accept + HF token in Settings). No API cost, no cloud. Elo context: klein ~1083-1119, FLUX.1-dev ~1027, nano-banana ~1154.",
|
||||
"accepts": [],
|
||||
"produces": ["image"],
|
||||
"resources": "gpu",
|
||||
@ -12,13 +12,13 @@
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"prompt": {"type": "string", "default": "", "description": "What to generate"},
|
||||
"model": {"type": "string", "enum": ["schnell", "dev"], "default": "schnell", "description": "schnell = fast/ungated; dev = best quality, HF-gated"},
|
||||
"steps": {"type": "integer", "default": 4, "minimum": 1, "maximum": 50, "description": "Inference steps (schnell: 2-4, dev: 20-28)"},
|
||||
"model": {"type": "string", "enum": ["flux2-klein-4b", "flux2-klein-9b", "schnell", "schnell-4bit", "dev", "krea-dev"], "default": "flux2-klein-4b", "description": "klein-4b + schnell-4bit are ungated; the rest need the HF token"},
|
||||
"steps": {"type": "integer", "default": 4, "minimum": 1, "maximum": 50, "description": "klein/schnell: 2-4; dev/krea-dev: 20-28"},
|
||||
"width": {"type": "integer", "default": 1024, "minimum": 256, "maximum": 2048},
|
||||
"height": {"type": "integer", "default": 1024, "minimum": 256, "maximum": 2048},
|
||||
"seed": {"type": "integer", "default": 42, "description": "Random seed (fixed seed = reproducible A/B tests)"},
|
||||
"quantize": {"type": "string", "enum": ["none", "8", "4"], "default": "8", "description": "Weight quantization: 8-bit ≈ full quality, half the memory; none = bf16"},
|
||||
"guidance": {"type": "number", "default": 3.5, "minimum": 0, "maximum": 10, "description": "Guidance scale (dev only; schnell ignores it)"}
|
||||
"seed": {"type": "integer", "default": 42, "description": "Fixed seed = reproducible A/B tests"},
|
||||
"quantize": {"type": "string", "enum": ["none", "8", "4"], "default": "8", "description": "FLUX.1 models only: 8-bit ≈ full quality at half memory"},
|
||||
"guidance": {"type": "number", "default": 3.5, "minimum": 0, "maximum": 10, "description": "dev/krea-dev only"}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@ -16,45 +16,57 @@ if not p.get("prompt"):
|
||||
print("ERROR: prompt is required")
|
||||
sys.exit(1)
|
||||
|
||||
model = p.get("model", "schnell")
|
||||
model = p.get("model", "flux2-klein-4b")
|
||||
steps = int(p.get("steps", 4))
|
||||
outdir = Path(a.outdir)
|
||||
out_png = outdir / f"flux_{model}_s{p.get('seed', 42)}.png"
|
||||
out_png = outdir / f"flux_{model.replace('/', '_')}_s{p.get('seed', 42)}.png"
|
||||
bindir = Path(sys.executable).parent
|
||||
|
||||
if model.startswith("flux2-"):
|
||||
cli = bindir / "mflux-generate-flux2"
|
||||
model_args = ["--model", model]
|
||||
quant_args = [] # klein is small; skip quantization flags
|
||||
guidance_args = [] # distilled klein: guidance fixed at 1.0
|
||||
elif model == "schnell-4bit":
|
||||
cli = bindir / "mflux-generate"
|
||||
# ungated community pre-quantized weights (~10GB) — no HF license wall
|
||||
model_args = ["--model", "dhairyashil/FLUX.1-schnell-mflux-4bit",
|
||||
"--base-model", "schnell"]
|
||||
quant_args = []
|
||||
guidance_args = []
|
||||
else:
|
||||
cli = bindir / "mflux-generate"
|
||||
model_args = ["--model", model]
|
||||
quant = str(p.get("quantize", "8"))
|
||||
quant_args = ["--quantize", quant] if quant in ("4", "8") else []
|
||||
guidance_args = (["--guidance", str(p.get("guidance", 3.5))]
|
||||
if model in ("dev", "krea-dev") else [])
|
||||
|
||||
# mflux-generate lives next to this venv's python
|
||||
cli = Path(sys.executable).parent / "mflux-generate"
|
||||
if not cli.exists():
|
||||
print(f"ERROR: mflux not installed ({cli} missing). Run scripts/install_mflux.sh")
|
||||
sys.exit(1)
|
||||
|
||||
cmd = [
|
||||
str(cli),
|
||||
"--model", model,
|
||||
"--prompt", p["prompt"],
|
||||
"--steps", str(steps),
|
||||
"--width", str(p.get("width", 1024)),
|
||||
"--height", str(p.get("height", 1024)),
|
||||
"--seed", str(p.get("seed", 42)),
|
||||
"--output", str(out_png),
|
||||
]
|
||||
quant = str(p.get("quantize", "8"))
|
||||
if quant in ("4", "8"):
|
||||
cmd += ["--quantize", quant]
|
||||
if model == "dev":
|
||||
cmd += ["--guidance", str(p.get("guidance", 3.5))]
|
||||
cmd = [str(cli), *model_args,
|
||||
"--prompt", p["prompt"],
|
||||
"--steps", str(steps),
|
||||
"--width", str(p.get("width", 1024)),
|
||||
"--height", str(p.get("height", 1024)),
|
||||
"--seed", str(p.get("seed", 42)),
|
||||
"--output", str(out_png),
|
||||
*quant_args, *guidance_args]
|
||||
|
||||
print("+", " ".join(cmd), flush=True)
|
||||
print("(first run downloads weights from HuggingFace — can take a while)", flush=True)
|
||||
print("(first run per model downloads weights from HuggingFace)", flush=True)
|
||||
t0 = time.time()
|
||||
res = subprocess.run(cmd, stdout=sys.stdout, stderr=subprocess.STDOUT)
|
||||
if res.returncode != 0:
|
||||
print("HINT: if this failed with a gated-repo/auth error, the model needs an "
|
||||
"HF license accept + token (Settings → HuggingFace token). schnell is ungated.")
|
||||
print("HINT: gated-repo/auth errors mean this model needs an HF license accept "
|
||||
"+ token (Settings → HuggingFace token). flux2-klein-4b and schnell-4bit "
|
||||
"are ungated and need nothing.")
|
||||
sys.exit(res.returncode)
|
||||
elapsed = round(time.time() - t0, 1)
|
||||
|
||||
if not out_png.exists():
|
||||
# mflux may append suffixes; grab any png it wrote
|
||||
pngs = sorted(outdir.glob("*.png"))
|
||||
if not pngs:
|
||||
print("ERROR: no image produced")
|
||||
@ -64,5 +76,5 @@ if not out_png.exists():
|
||||
(outdir / "result.json").write_text(json.dumps({"outputs": [
|
||||
{"path": out_png.name,
|
||||
"meta": {"tool": "mflux", "model": model, "steps": steps,
|
||||
"seed": p.get("seed", 42), "quantize": quant, "seconds": elapsed}}]}))
|
||||
"seed": p.get("seed", 42), "seconds": elapsed}}]}))
|
||||
print(f"done in {elapsed}s: {out_png.name}", flush=True)
|
||||
|
||||
@ -2,7 +2,7 @@
|
||||
"id": "openrouter_image",
|
||||
"name": "OpenRouter · nano-banana",
|
||||
"category": "generate",
|
||||
"description": "Prompt → image via OpenRouter (Google nano-banana / Gemini image models). Use with the same prompt+seedless run as FLUX (local) and Compare mode for A/B tests. Needs OPENROUTER_API_KEY.",
|
||||
"description": "Prompt → image via OpenRouter's Image API. nano-banana ≈$0.039/img, nano-banana 2 ≈$0.05-0.08, nano-banana-pro ≈$0.134 (1-2K). Exact cost is reported in the job log. Pair with FLUX (local) on the same prompt + Compare mode for A/B tests. Needs OPENROUTER_API_KEY.",
|
||||
"accepts": [],
|
||||
"produces": ["image"],
|
||||
"resources": "net",
|
||||
@ -12,7 +12,11 @@
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"prompt": {"type": "string", "default": "", "description": "What to generate"},
|
||||
"model": {"type": "string", "enum": ["google/gemini-2.5-flash-image", "google/gemini-3-pro-image-preview"], "default": "google/gemini-2.5-flash-image", "description": "nano-banana (flash) or nano-banana-pro (gemini 3)"}
|
||||
"model": {"type": "string", "enum": ["google/gemini-2.5-flash-image", "google/gemini-3.1-flash-image", "google/gemini-3-pro-image"], "default": "google/gemini-2.5-flash-image", "description": "nano-banana / nano-banana-2 / nano-banana-pro"},
|
||||
"resolution": {"type": "string", "enum": ["1K", "2K", "4K"], "default": "1K", "description": "Output resolution tier (4K: pro/NB2 only, costs more)"},
|
||||
"aspect_ratio": {"type": "string", "enum": ["1:1", "16:9", "9:16", "4:3", "3:4", "3:2", "2:3"], "default": "1:1"},
|
||||
"seed": {"type": "integer", "description": "Seed (best-effort reproducibility)"},
|
||||
"n": {"type": "integer", "default": 1, "minimum": 1, "maximum": 4, "description": "Number of images"}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@ -4,6 +4,7 @@ import json
|
||||
import os
|
||||
import sys
|
||||
import time
|
||||
import urllib.error
|
||||
import urllib.request
|
||||
from pathlib import Path
|
||||
|
||||
@ -25,17 +26,22 @@ if not key:
|
||||
model = p.get("model", "google/gemini-2.5-flash-image")
|
||||
body = {
|
||||
"model": model,
|
||||
"messages": [{"role": "user", "content": p["prompt"]}],
|
||||
"modalities": ["image", "text"],
|
||||
"prompt": p["prompt"],
|
||||
"resolution": p.get("resolution", "1K"),
|
||||
"aspect_ratio": p.get("aspect_ratio", "1:1"),
|
||||
"n": int(p.get("n", 1)),
|
||||
}
|
||||
if p.get("seed") not in (None, ""):
|
||||
body["seed"] = int(p["seed"])
|
||||
|
||||
req = urllib.request.Request(
|
||||
"https://openrouter.ai/api/v1/chat/completions",
|
||||
"https://openrouter.ai/api/v1/images",
|
||||
data=json.dumps(body).encode(),
|
||||
headers={"Authorization": f"Bearer {key}", "Content-Type": "application/json",
|
||||
"X-Title": "MODELBEAST"},
|
||||
"X-OpenRouter-Title": "MODELBEAST"},
|
||||
method="POST",
|
||||
)
|
||||
print(f"calling {model} via OpenRouter ...", flush=True)
|
||||
print(f"calling {model} via OpenRouter Image API ...", flush=True)
|
||||
t0 = time.time()
|
||||
try:
|
||||
with urllib.request.urlopen(req, timeout=300) as resp:
|
||||
@ -46,44 +52,25 @@ except urllib.error.HTTPError as e:
|
||||
elapsed = round(time.time() - t0, 1)
|
||||
|
||||
outdir = Path(a.outdir)
|
||||
(outdir / "openrouter_result.json").write_text(json.dumps(
|
||||
{k: v for k, v in result.items() if k != "choices"} |
|
||||
{"note": "choices omitted here; images extracted below"}, indent=2))
|
||||
outputs = []
|
||||
for i, item in enumerate(result.get("data", [])):
|
||||
b64 = item.get("b64_json")
|
||||
if not b64:
|
||||
continue
|
||||
media = item.get("media_type", "image/png")
|
||||
ext = ".png" if "png" in media else ".webp" if "webp" in media else ".jpg"
|
||||
short = model.split("/")[-1]
|
||||
name = f"{short}_{i}{ext}" if len(result.get("data", [])) > 1 else f"{short}{ext}"
|
||||
(outdir / name).write_bytes(base64.b64decode(b64))
|
||||
outputs.append({"path": name, "meta": {"tool": "openrouter", "model": model,
|
||||
"seconds": elapsed,
|
||||
"cost_usd": result.get("usage", {}).get("cost")}})
|
||||
|
||||
|
||||
def data_urls(obj, acc):
|
||||
"""Collect data:image/... URLs from any nesting (message.images, content parts)."""
|
||||
if isinstance(obj, dict):
|
||||
for v in obj.values():
|
||||
data_urls(v, acc)
|
||||
elif isinstance(obj, list):
|
||||
for v in obj:
|
||||
data_urls(v, acc)
|
||||
elif isinstance(obj, str) and obj.startswith("data:image/"):
|
||||
acc.append(obj)
|
||||
|
||||
|
||||
urls: list[str] = []
|
||||
data_urls(result.get("choices", []), urls)
|
||||
if not urls:
|
||||
text = ""
|
||||
try:
|
||||
text = result["choices"][0]["message"].get("content") or ""
|
||||
except (KeyError, IndexError):
|
||||
pass
|
||||
print("ERROR: no image in response.", ("Model said: " + str(text)[:800]) if text else "")
|
||||
if not outputs:
|
||||
print("ERROR: no image in response:")
|
||||
print(json.dumps(result, indent=2)[:1500])
|
||||
sys.exit(1)
|
||||
|
||||
outputs = []
|
||||
for i, u in enumerate(urls):
|
||||
header, b64 = u.split(",", 1)
|
||||
ext = ".png" if "png" in header else ".webp" if "webp" in header else ".jpg"
|
||||
name = f"nano_banana_{i}{ext}" if len(urls) > 1 else f"nano_banana{ext}"
|
||||
(outdir / name).write_bytes(base64.b64decode(b64))
|
||||
outputs.append({"path": name, "meta": {"tool": "openrouter", "model": model,
|
||||
"seconds": elapsed}})
|
||||
|
||||
usage = result.get("usage", {})
|
||||
print(f"done in {elapsed}s — {len(outputs)} image(s); usage: {json.dumps(usage)}", flush=True)
|
||||
print(f"done in {elapsed}s — {len(outputs)} image(s), cost ${usage.get('cost', '?')}", flush=True)
|
||||
(outdir / "result.json").write_text(json.dumps({"outputs": outputs}))
|
||||
|
||||
Loading…
Reference in New Issue
Block a user