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docs: finalize v0.5.0 changelog and latest-release pointer

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Guillaume Meyer (The Opinionated Man)
2026-08-14 15:45:46 -07:00
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@@ -23,7 +23,7 @@ Agent skill + stdlib Python service to strip **multi-vendor AI provenance marks*
Vendors / ecosystems (class-level): **Claude**, **Gemini / SynthID-Text**, **OpenAI** provenance surfaces, **open-LLM** Kirchenbauer-style marks.
**Latest release:** [v0.4.0](https://github.com/guillaumemeyer/watermarks-remover/releases/tag/v0.4.0)
**Latest release:** [v0.5.0](https://github.com/guillaumemeyer/watermarks-remover/releases/tag/v0.5.0)
Skill path: [`skills/remove-ai-marks/`](skills/remove-ai-marks/)
Service path: [`service/`](service/)
@@ -627,33 +627,55 @@ make smoke # quick CLI smoke on fixtures
## Changelog
### Unreleased
### [v0.5.0](https://github.com/guillaumemeyer/watermarks-remover/releases/tag/v0.5.0) — service & Docker distribution, HTTP API, and verification harnesses
**Service / Docker distribution**
- **Repo hygiene**: `.gitignore` and `service/.dockerignore` are now deny-by-default — only explicitly allowed paths can be committed or sent in a build context (image contexts only ship `service/scripts/`, which is all the Dockerfiles COPY)
- **Layer B**: `rewrite_text.py` now sends `reasoning_effort: "none"` by default for `openai-compatible` backends (`--reasoning-effort` / `WATERMARKS_REWRITE_REASONING_EFFORT`; `off` omits it). Reasoning models like `deepseek-v4-flash` otherwise burn ~100s of chain-of-thought on a one-line rewrite (9,894 vs 12 completion tokens)
- **Fix markllm image build**: `requirements-markllm.txt` pinned `tokenizers==0.23.1`, which conflicts with `transformers==5.15.0` (caps `tokenizers<=0.23.0`; no 0.23.0 release exists) — now pinned `tokenizers==0.22.2`; torch moved to the CPU wheel index (`torch==2.13.0.*`) so the image is CPU-only like `Dockerfile.markdiffusion`
- **Fix ctrlregen image build**: the 2023-era research pins (`safetensors==0.4.3`, `transformers==4.37.2` → `tokenizers<0.19`) ship no Python 3.14 wheels, so the base image is now `python:3.11-slim` (digest-pinned, multi-arch)
- **Fix harness images at runtime**: `Dockerfile.markllm` and `Dockerfile.markdiffusion` never copied `common.py` into `/app` (pre-existing bug) — added
- **compose**: services are prefixed `wr-` (`wr-core`, `wr-markllm`, …); harness/heavy services default to `command: ["--help"]` so `docker compose up --profile harness --profile heavy` exits cleanly (one-shot CLIs are run with `docker compose run`); new `make compose-check` / `compose-check.sh` validates the running stack (exit code only)
- **Skill/service split**: the skill (`skills/remove-ai-marks/`) is now a code-free remote client over HTTP; all implementation moved to `service/scripts/` and runs behind `server.py`, a stdlib HTTP entrypoint (`/health`, `/inspect`, `/clean`, `/capabilities`)
- **HTTP service**: `service/scripts/server.py` exposes the cleaning pipeline over JSON/base64; hardening mirrors the CLIs (size caps, binary guard, atomic writes, loopback default, optional `WATERMARKS_SERVER_API_KEY` bearer auth)
- **OpenAPI**: `GET /openapi.json` serves a dynamically generated OpenAPI 3.0.3 spec (built from the route table + live config, so it never drifts from the real endpoints); CI validates it with `openapi-spec-validator`
- **Core Docker image** (`service/Dockerfile`): full cleaning service with exiftool / qpdf / c2patool preinstalled; any CLI stays runnable by overriding the command
- **Docker / compose**: `compose.yaml` brings up the whole infra (`core` always; `markllm` / `markdiffusion` behind `profile: harness`; `ctrlregen` / `synthid` behind `profile: heavy` as local-only builds)
- **Docker / compose**: `compose.yaml` brings up the whole infra (`core` always; `markllm` / `markdiffusion` behind `profile: harness`; `ctrlregen` / `synthid` behind `profile: heavy` as local-only builds); services are prefixed `wr-`; harness/heavy services default to `command: ["--help"]` so `docker compose up --profile harness --profile heavy` exits cleanly (one-shot CLIs are run with `docker compose run`); new `make compose-check` / `compose-check.sh` validates the running stack (exit code only)
- **GHCR publishing**: `.github/workflows/release-images.yml` publishes `core`, `markllm`, `markdiffusion` images on `v*` tags; `ctrlregen` / `synthid` are never published (upstream licensing)
- **Env configuration**: `.env.example` + service configuration guide; `docker compose` auto-loads `.env`; `.env` is gitignored (deny-by-default)
- **Repo hygiene**: `.gitignore` and `service/.dockerignore` are now deny-by-default — only explicitly allowed paths can be committed or sent in a build context (image contexts only ship `service/scripts/`, which is all the Dockerfiles COPY)
- Tests: `tests/test_http_server.py` (13 cases) for the HTTP service; all suites re-pointed at `service/scripts/`
- New optional MarkDiffusion image-watermark harness (external `THU-BPM/MarkDiffusion`, Apache-2.0): `markdiffusion_harness.py` with `watermark` / `detect` / `purify` subcommands for nine image schemes (Tree-Ring, Ring-ID, ROBIN, WIND, SFW, Gaussian-Shading, GaussMarker, PRC, SEAL)
**MarkDiffusion image-watermark harness (optional)**
- New optional harness (external `THU-BPM/MarkDiffusion`, Apache-2.0): `markdiffusion_harness.py` with `watermark` / `detect` / `purify` subcommands for nine image schemes (Tree-Ring, Ring-ID, ROBIN, WIND, SFW, Gaussian-Shading, GaussMarker, PRC, SEAL)
- `clean_image.py --remove-pixel diffusion` runs the MarkDiffusion `DiffusionPurification` regeneration attack as an alternative pixel-removal engine (conservative strength 0.3 default)
- `setup_markdiffusion.sh` bootstrap (PyPI pin `1.0.2`; `--checkout` editable clone at pinned commit) + `requirements-markdiffusion.txt` + `Dockerfile.markdiffusion` and Makefile `bootstrap-markdiffusion` / `smoke-markdiffusion` / `docker-markdiffusion-build` / `docker-markdiffusion-help`
- Mock-based tests (`tests/test_markdiffusion_harness.py`) — no torch in CI; `references/markdiffusion.md` reference doc
- Docs: same-scheme-only verification caveat (not a vendor-detector oracle) and blind-regeneration drift caveat in README, SKILL.md, `removal-matrix.md`, `markdiffusion.md`
- Add stdlib-only WebP inspection and metadata cleaning for RIFF `C2PA`, XMP, EXIF, and ICC profile chunks
- New optional MarkLLM harness (external `THU-BPM/MarkLLM` checkout, Apache-2.0): `detect_text_watermark.py` with `detect` / `watermark` subcommands for KGW and SynthID schemes
**MarkLLM text-watermark harness (optional)**
- New optional harness (external `THU-BPM/MarkLLM` checkout, Apache-2.0): `detect_text_watermark.py` with `detect` / `watermark` subcommands for KGW and SynthID schemes
- `rewrite_text.py --markllm-scheme` runs before/after detection around a Layer B rewrite (env-gated; reports `cleared`)
- `setup_markllm.sh` bootstrap + `requirements-markllm.txt` (pinned deps) + `Dockerfile.markllm` and Makefile `bootstrap-markllm` / `smoke-markllm` / `docker-markllm-build` / `docker-markllm-help`
- Mock-based tests (`tests/test_markllm_detect.py`, 21 cases) — no torch in CI
- Docs: verification-harness caveat (same-config-only, not a vendor-detector oracle) in README, SKILL.md, `removal-matrix.md`, `vendor-notes.md`
- Hardening: `--offline` cache-only model loading (no HF egress, no remote code), 1 MiB config cap, optional `WATERMARKS_MARKLLM_RLIMIT_AS` on the rewrite subprocess, pinned torch in the Dockerfile, and clone-SHA verification in `Dockerfile.markllm`
- Mock-based tests (`tests/test_markllm_detect.py`, 21 cases) — no torch in CI; verification-harness caveat (same-config-only, not a vendor-detector oracle) documented in README, SKILL.md, `removal-matrix.md`, `vendor-notes.md`
**Fixes and polish**
- **Layer B**: `rewrite_text.py` now sends `reasoning_effort: "none"` by default for `openai-compatible` backends (`--reasoning-effort` / `WATERMARKS_REWRITE_REASONING_EFFORT`; `off` omits it). Reasoning models like `deepseek-v4-flash` otherwise burn ~100s of chain-of-thought on a one-line rewrite (9,894 vs 12 completion tokens)
- **Fix markllm image build**: `requirements-markllm.txt` pinned `tokenizers==0.23.1`, which conflicts with `transformers==5.15.0` (caps `tokenizers<=0.23.0`; no 0.23.0 release exists) — now pinned `tokenizers==0.22.2`; torch moved to the CPU wheel index (`torch==2.13.0.*`) so the image is CPU-only like `Dockerfile.markdiffusion`
- **Fix ctrlregen image build**: the 2023-era research pins (`safetensors==0.4.3`, `transformers==4.37.2` → `tokenizers<0.19`) ship no Python 3.14 wheels, so the base image is now `python:3.11-slim` (digest-pinned, multi-arch)
- **Fix harness images at runtime**: `Dockerfile.markllm` and `Dockerfile.markdiffusion` never copied `common.py` into `/app` (pre-existing bug) — added
- **WebP**: stdlib-only inspection and metadata cleaning for RIFF `C2PA`, XMP, EXIF, and ICC profile chunks (#37)
- **Filename sanitization**: HTTP service refuses unsafe client-supplied output names
- **Fix markdown frontmatter cleaner** crashing on and leaking nested AI keys (#25)
- **Text tools refuse binary input**; `--force-text` overrides (#24)
- **`--json` no longer suppresses the residual-signal exit code** (#30)
- **`inspect_file` prints the filename** in its output (#50)
- **Preserve mixed-case CMS generator meta tags** (#42)
- **Preserve load-bearing script invisibles, strip PUA** in Layer A (#38, #52)
- **Preserve script joiners, flag emoji, and Arabic Cf marks** in Layer A (#28)
- **Harden website audit against SSRF and gzip bombs** (#49)
- **SECURITY.md** only references the private advisories channel (#51)
- **Windows**: PowerShell ports of the setup bootstraps (#40)
- **Docs**: add stars/forks shields and drop star-history chart; add MarkLLM to README references; pull request template; plan for Docker CLI + API deployment
### [v0.4.0](https://github.com/guillaumemeyer/watermarks-remover/releases/tag/v0.4.0) — pixel removal, finding confidence, Windows & false-positive fixes