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Delete every knob the fixed profiles cannot honor
The CLI still advertised --model, --steps, --guidance-scale, --device and a deprecated --auto. Each pinned a value the two surviving profiles fix -- the model stack, the per-stage distilled schedule, CFG 1.0, CUDA -- so the only outcome any of them had was an error raised several frames below the caller, under a message naming an internal profile. A flag whose sole result is a refusal is worse than no flag: it advertises a capability that does not exist, and it lets a wrapper thread a value that will silently do nothing. They are gone from the parser, from InvisibleEngine, and from WatermarkRemover, so the failure is now a TypeError or a Click "No such option" at the point the caller can act on. The install hint was wrong in the same way. is_available() checked torch and diffusers, then told the user to install [diffusion] -- which contains neither DiffSynth nor the Z-Image face stage both profiles run. Following the advice produced a second, different failure. The module list and the extra name now live once in watermark_profiles (REMOVAL_MODULES, INVISIBLE_EXTRA) and are read by both the CLI gate and the remover's precondition, which cannot drift apart because they are the same tuple. The adaptive-polish default moved out of the argument parser. It was resolved by reading Click's parameter source, which put per-profile data in the CLI layer, left the engine declaring the opposite default (False vs True) so a library caller and a CLI caller on one profile got different output, and lost the polish entirely for anything that supplies the flag non-interactively. The flag is now tri-state (default=None) and resolve_adaptive_polish owns the per-profile answer. The seed follows the same rule: the CLI stopped pre-resolving it. Dead code removed with it: six scan_*_video wrappers and the _scan_video helper none of them had a caller for, PNG_METADATA_KEYS, feather_region_composite and the remover region path that was only reachable from a no-caller convenience wrapper, remove_watermark_batch on both layers, try_empty_device_cache, the _generate/_run_qwen_zimage pass-through pair, self.model_id, and the _internal PEP 562 shim that no caller ever went through. get_device now answers cuda or cpu only: mps and xpu travelled one frame to the same CUDA-only refusal while costing a device probe each, and that refusal now names the resolved device, so device=None on a CUDA-less host says 'cpu' rather than 'None'. The XPU wheel index went with them. Docs: README, cli, installation, python-api, supported-signals, known-limitations and module-internals all still described the removed profiles, the CPU/MPS/XPU ladder, a `default`->`sdxl` alias, and the wrong extra. known-limitations still listed the retired SDXL strength ladder as current. scripts/smoke_matrix.py and real_examples_e2e.py drove --device mps. Next release is 0.25.0, not a patch: this removes public parameters and narrows a published extra on top of the released 0.24.0. pre-commit: 1) maintain.sh - exit 0 (1091 tests, Pyright 0 errors, no vulnerabilities); 2) /simplify - 4 agents, 11 findings applied, 2 skipped (dropping the `device` parameter entirely, which raiw-app pins; folding diffsynth into the `diffusion` extra, which video-only callers do not need); 3) docs sync - grepped every removed identifier across README, docs/, scripts/, .claude/; updated 9 docs; 4) CLAUDE.md - added the no-error-only-knobs rule to .claude/rules/development.md Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
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co-authored by
Claude Opus 5
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@@ -6,8 +6,9 @@ and pipeline modules are intended for maintainers and specialized workflows.
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Dependency groups are identical for the CLI and Python API. The default install
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covers metadata extraction, normalization, verdict logic, and stripping.
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Array/pixel APIs use `pixels`; visible removal uses `visible`; DWT-DCT detection
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uses `detect`; diffusion removal uses `diffusion`; and visible video processing
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uses `video`. Video SynthID removal combines `video` and `diffusion`. Add `heif`
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uses `detect`; invisible image removal uses `qwen-zimage` and an NVIDIA GPU; and
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visible video processing uses `video`. Video SynthID removal is a separate VAE
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path that still runs on CPU and combines `video` and `diffusion`. Add `heif`
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independently when path-based pixel APIs must decode HEIC, HEIF, or AVIF. See
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the complete [feature-extra matrix](installation.md#feature-extras).
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@@ -380,8 +381,8 @@ to 8-bit SDR.
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## Remove invisible watermarks
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Install `remove-ai-watermarks[diffusion]` for the standard pipelines or
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`remove-ai-watermarks[qwen-zimage]` for the CUDA-only high-fidelity profile.
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Install `remove-ai-watermarks[qwen-zimage]`. Both profiles need it, and both
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need an NVIDIA GPU.
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```python
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from pathlib import Path
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@@ -400,8 +401,9 @@ engine.remove_watermark(
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)
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```
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`device=None` selects the device automatically. Supported explicit values are
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defined by the CLI and runtime device resolver.
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`device=None` detects CUDA. The only other accepted value is `"cuda"`; anything
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else raises at construction rather than deferring a guaranteed failure to model
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load time.
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For limited CUDA memory:
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@@ -412,18 +414,22 @@ engine = InvisibleEngine(
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)
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```
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Both profiles are CUDA-only, so `device=None` resolving to CPU or MPS cannot run
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invisible-watermark removal at all. For the SDXL global stage instead of Qwen:
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Both profiles are CUDA-only, so on a machine without an NVIDIA GPU `device=None`
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resolves to `cpu` and construction raises. For the SDXL global stage instead of
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Qwen:
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```python
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engine = InvisibleEngine(pipeline="sdxl-zimage")
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```
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The `qwen-zimage` extra must be installed for that profile.
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The `qwen-zimage` extra is required for both profiles: each runs the same
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DiffSynth Z-Image face stage.
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The full `remove_watermark` signature includes strength, steps, guidance,
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seeding, tiling, resolution, and postprocessing controls. Read the
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method signature in
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`remove_watermark` takes strength, seed, tiling, resolution, and postprocessing
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controls. It takes no model id, step count or guidance scale, and neither does the
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constructor: each profile pins its model stack, its per-stage schedule and CFG
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1.0, so passing one raises `TypeError` at the call rather than being accepted and
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refused several layers down. Read the method signature in
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[`invisible_engine.py`](../src/remove_ai_watermarks/invisible_engine.py) or use
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the CLI guide for the concepts.
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Defaults can differ between the Python method and CLI profile resolution, so
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