AGENTS.md

AGENTS.md

Tool-agnostic agent guidance for the ACE Music Studio repo. If you're driving Claude Code, Cursor, Aider, Codex, or anything else with file-edit + shell access, start here.

This file is the authoritative project rulebook. CLAUDE.md is Claude-specific extensions; SKILLS.md is workflow rules. README.md is the public-facing project intro — different audience.

---

TL;DR — the five rules

1. Mayank Gupta is sole author on every commit. No agent co-author trailers. No "generated with…" footers. No --author= flag. Strip any tool-suggested attribution.
2. Backend = ACE-Step 1.5 XL SFT, not ComfyUI. Don't add a ComfyUI dependency under any guise.
3. One pipeline instance for all modes. Generate / Cover / Extend / Edit call different entry points on the same pipeline object. Don't instantiate per-mode — it doubles memory and breaks LoRA state.
4. Don't pin spaces in requirements.txt. HF Spaces' ZeroGPU build injects its own version. A pin causes pip-resolve failure.
5. Locally is the source of truth. All changes restart python app.py and verify on http://127.0.0.1:7860 BEFORE pushing to HF. The Space rebuild is ~5–10 min; iterate locally.

If you can't satisfy these without changing architectural shape, ask the user before proceeding.

---

Project shape

Single-process Gradio 5.50 app, flat top-level Python layout.

app.py            Gradio Blocks entry + bootstrap + event handlers
backend.py        AceMusicBackend; @spaces.GPU; duration_for; generate_with_retry
modes.py          call_generate / call_cover / call_extend / call_edit (pure handlers)
models.py         auto_device, MODEL_CONFIGS, vram_limit_for, HF symlink helper
lora.py           safetensors header sniff + applied_lora context manager
lyrics.py         Qwen 2.5 7B inference (MLX on Mac, transformers on CUDA)
stems.py          Demucs htdemucs_ft stem separation wrapper
postprocess.py    loudness normalisation + fade in/out
ui.py             Five per-tab builders
theme.py          Soft Dark Restraint palette + minimal CSS
tooltips.py       Centralised info= strings — single source of truth
tests/            L1+L2 tests + GPU-deselected smoke
docs/superpowers/ spec + plan + brainstorm artifacts

Same code path locally (MPS / CUDA) and on HF Spaces. The only branching is whether _bootstrap() does the cache-mirror dance (Spaces) or just the symlink step (local).

---

Locked architecture decisions

These came out of brainstorming + spec design. Do not relitigate.

Decision	Why	Code reference
One AceMusicBackend instance, lazy init	Avoids ~60 s pipeline rebuild per request; LoRA revert is cleaner	backend.get_backend
Mode dispatch = separate call_* functions	Clean handler boundaries; easy to test with mocked pipe	modes.py
MPS vram_limit = None	torch.mps has no mem_get_info; any VRAM gate raises AttributeError otherwise	models.vram_limit_for
PYTORCH_ENABLE_MPS_FALLBACK=1 set at app import	A few MPS-unsupported ops crash mid-pipeline without it	app.py top-of-file
HF cache → ./models/<repo>/ symlink at boot	ACE-Step's loader looks at local paths, NOT the HF cache snapshot layout	app._bootstrap
MLX path for Qwen on Mac	mlx-lm is 3-4x faster than transformers on Apple Silicon for text inference	lyrics.py
Stacked LoRA with safetensors sniff	4 bundled presets + arbitrary uploads; header check avoids corrupt-file crashes	lora.py

---

Commit rules

• Conventional Commits: <type>(<scope>): <subject>
  • types: feat, fix, chore, docs, test, refactor, ci, perf
• Subject is imperative, lowercase, no trailing period.
• Body explains why when not obvious. Reference plan task IDs (Task 7, Task A, etc.) when the change implements a specific plan step.
• Frequent small commits; one logical change per commit.
• No agent attribution in commit message or body. See rule 1.
• Don't git push --force to main unless the user explicitly says so.

---

Verification rules

• Tests must pass before committing. python -m pytest tests/ -q from the project root.
• Ruff must be clean. ruff check . && ruff format --check .
• The local app must boot. python app.py → http://127.0.0.1:7860 reachable, no import error in /tmp/ace-music-studio.log.
• For UI changes: open the URL in a browser (or Playwright eval) and verify the change is rendered. Don't trust a clean test run + clean ruff as proof that the UI works.
• For deployment changes: push to HF Space, watch the build, verify the runtime stage transitions to RUNNING before claiming success.

If a change requires breaking these rules, write the reason in the commit body.

---

Testing conventions

• TDD per the plan. Failing test first, then implementation.
• L1 + L2 in CI (no GPU). The mode handlers are tested with a mocked pipeline. We do NOT mock ACE-Step internals.
• L3 GPU smoke is opt-in (pytest -m gpu). Lives in tests/test_smoke_gpu.py. Loads the real pipeline (~32 GB cache hit on a warm machine).
• L4 HF Space smoke is manual. Push, wait, click each tab, verify audio renders.

pyproject.toml has addopts = -m 'not gpu' so the default pytest invocation skips GPU. Add the marker before any test that touches ACE-Step weights.

---

Out of scope (v1 cap — don't add without asking)

Per spec §13. If you find yourself "while I'm here"-ing into one of them, stop.

• Multi-prompt batch queue
• Persistent generation history
• User accounts
• Telemetry dashboard
• Voice cloning (RVC)
• LoRA training in-app
• ControlNet-style conditioning
• Spectrogram visualization
• Multi-language UI strings
• Watermarking output audio
• Browser audio editing
• Multi-tenant rate limiting
• DAW export

If a feature you're adding requires one of these as a sub-step, ask the user before proceeding.

---

When you're not sure

1. Read docs/superpowers/specs/2026-05-18-ace-music-studio-design.md — that's the architectural source of truth.
2. Read docs/superpowers/plans/2026-05-18-ace-music-studio.md — the task-by-task breakdown.
3. Read SKILLS.md — process rules, debugging patterns, deployment workflow.
4. git log --oneline — every non-obvious decision has a fix-commit explaining the reasoning.
5. Ask the user. A clarifying question costs the user ten seconds. A wrong implementation costs everyone an hour.