remove-ai-watermarks/docs/development.md

Development

Standalone evaluation, calibration, and release utilities are catalogued in scripts/README.md. They are maintainer tools rather than installed commands, and their local data inputs remain outside the repository.

Read this reference for environment setup, dependency recovery, CI behavior, and fixture policy. The always-loaded invariants remain in .claude/rules/development.md.

Local environment

• Use uv sync --frozen --extra dev and add only the feature extras needed for the task.
• Do not use uv pip install for development tools. It can re-resolve uv.lock outside the compatible ML dependency set.
• A default-only sync removes every pixel and model package by design. Package imports remain light through lazy exports.
• On an unreliable connection, sync dev plus only the required feature extras, such as diffusion, and run the checks directly instead of downloading every optional learned backend.
• Run uv from the repository root or it may create a bare environment without the project dependencies.

maintain.sh starts with uv sync --all-extras, so a lean environment is replaced whenever the gate runs. Syncing back down can leave opencv-python-headless half-removed: import cv2 then succeeds against an empty namespace while cv2.INTER_LINEAR is gone, which surfaces as a suite that stalls or reports hundreds of unrelated failures. Repair it with uv sync --frozen --extra dev --reinstall-package opencv-python-headless rather than re-reading the diff.

Pyright is only meaningful with the extras its imports need. Scoped to src/, a lean environment reports TrustMark, transformers and huggingface_hub as unresolved, which reads as a type error and is not one; add --extra trustmark --extra classify before believing it.

The optional TrustMark decoder downloads weights into its installed package directory. After pruning that extra, a leftover weights directory can make availability checks see an empty namespace package. If Pyright reports an unknown TrustMark import and find_spec("trustmark") returns a loader-less spec, remove that regenerable remnant from the active virtual environment and resync.

Known security-gate blocks

maintain.sh treats both vulnerability findings and scanner failures as fatal. A success sentence followed by a nonzero scanner exit is still a failed check; tests/test_maintenance.py exercises that case with isolated command stubs. Do not add advisory ignores or suppress the scanner's exit status. Run and report Ruff, Pyright scoped to src/, and tests separately when security blocks the gate.

Rechecked on 2026-09-10 against the locked versions and the advisory sources:

• lightning and pytorch-lightning, pulled by the optional trustmark extra, are pinned to 2.6.6. That release clears PYSEC-2026-3624 and PYSEC-2026-3967; do not reintroduce an older transitive resolution.
• accelerate, required by the diffusion stack, is affected by GHSA-4j2p-28q2-5m79 and PYSEC-2026-3804. The sharded-checkpoint loader accepts unsafe weight_map paths; neither advisory lists a patched release. 1.15.0 is on PyPI and is outside the advisory's <= 1.14.0 range, but its load_checkpoint_in_model still joins weight_map entries with no containment check, and the sanitizer PRs (#4138, #4214) did not land. Do not bump solely to silence the scanner. The project has no direct call to load_checkpoint_in_model or load_checkpoint_and_dispatch, but this does not prove indirect model-loading paths are unaffected.

Before carrying the remaining block forward, rerun uvx uv-secure uv.lock and check PyPI for a fixed release. Upgrade a fixed package with uv lock --upgrade-package <package> and rerun the gate. Removing the current dependency would remove a supported optional feature, so that is not a maintenance-only repair.

Minor-only lock refreshes must retain each package's current major and lower bound. Use version-qualified uv lock --upgrade-package arguments, inspect a --dry-run first, and compare the resulting package versions. NumPy has two Python-dependent branches, so apply separate constraints on either side of Python 3.13. A blanket upgrade can both cross a NumPy major and downgrade a neighboring OCR package to satisfy the new graph.

Dependency compatibility bounds

The published extras and Dependabot configuration carry matching bounds:

• Transformers stays below 5.16 while tokenizers stays on the verified 0.22 line. PyPI metadata for Transformers 5.16 and 5.17 requires tokenizers >=0.23.1,<0.24, so updating Transformers alone cannot resolve. Revalidate tokenizer construction and the model-loading paths before lifting both bounds.
• Hugging Face Hub stays below 2 in every extra that names it. Diffusers 0.40 requires huggingface-hub>=1.23,<2; a Hub-only extra must remain composable with the diffusion extra. Recheck Diffusers' declared requirements before lifting the Hub bound.
• C2PA requires 0.38.0 or newer and uses an explicit per-reader certificate profile. Its Rust SDK 0.91.0 clears the bundled EKUs when loading empty trust settings, which otherwise rejects the OpenAI and Microsoft signing certificates in five committed fixtures. The profile restores those EKUs without installing trust anchors or bypassing certificate validation. Cause, upstream sources, and regression guards are in Module internals, C2PA. Recheck both positive certificate acceptance and negative credential, signature, and asset-binding validation when upgrading the reader; retain every SDK validation status.

Dependabot ignore entries mirror these compatibility bounds. Its failed 2026-09-30 run named the active Python 3.11 interpreter in a generic resolver hint, but the actual conflicts were the tokenizer and Hub requirements above; reducing the supported Python range does not fix them.

CI

.github/workflows/test.yml runs Ruff, a test matrix over every supported Python minor with default plus development dependencies, cross-platform coverage at the oldest and newest minors, and a separate job that installs ffmpeg on Ubuntu to run the full-clip video test. Diffusion and model-running tests skip in that matrix; metadata, identification, visible removal, the DWT-DCT decoder, and the OpenCV eraser remain covered across operating systems.

Keep uv.lock compatible with uv sync --frozen. Dependency pull-request checks use GitHub's merge result against current main; if main moves, merge it locally and rerun the full gate because a newer linter can expose stale directives in later code.

test.yml runs one concurrency group per ref with cancel-in-progress: true, so a newer push cancels the previous run mid-flight. A cancelled run is not a failure verdict: the superseding run's head includes the cancelled commits as ancestors, so watch that run to completion instead of retrying the push.

Release and distribution behavior is canonical in release-and-distribution.md.

Fixture and data policy

../data/README.md is the source of truth:

• executable provenance fixtures live under data/fixtures/;
• minimal controlled detector inputs live under data/calibration/;
• canonical provider-oracle originals and their manifests live under data/synthid/;
• evaluation-only ground truth lives under data/evaluations/;
• runtime detector assets live in the package; unregistered research candidates remain outside the shipped wheel.

Store each binary once. Point tests and manifests at its canonical path. Keep generated and cleaned outputs outside the repository and retain only reproducible public records allowed by the data policy.

Use synthetic byte blobs for unsupported format paths and deterministic generated negatives where a real negative fixture is unnecessary. Detection and removal tests must preserve their format-specific invariants.