Files
watermarks-remover/service/Dockerfile.markllm
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Guillaume Meyer (The Opinionated Man)andGitHub 55d4bdc9fc feat: split skill from service, add HTTP API and Docker distribution (#60)
* feat: split skill from service, add HTTP API and Docker distribution

The agent skill (skills/remove-ai-marks/) is now a code-free remote client:
all implementation moved to service/scripts/ and runs behind a stdlib HTTP
service (server.py) with /health, /capabilities, /inspect, /clean and a
dynamically generated OpenAPI 3.0.3 spec at /openapi.json.

- Move scripts/ and the backend Dockerfiles under service/
- server.py: JSON/base64 HTTP entrypoint with size caps, binary guard,
  atomic writes, loopback default, optional bearer auth
- Core Dockerfile (exiftool/qpdf/c2patool preinstalled) and a GHCR publish
  workflow for the core/markllm/markdiffusion images
- compose.yaml (wr-* services, harness/heavy profiles) + compose-check.sh
  to validate the running stack (exit code only)
- Fix markllm image build (tokenizers 0.22.2, CPU-only torch) and ctrlregen
  build (python:3.11 base for the 2023-era research pins)
- Fix markllm/markdiffusion harness images missing common.py at runtime

* docs: add .env.example and service configuration guide

* fix: disable chain-of-thought for openai-compatible Layer B rewrites

deepseek-v4-flash is a reasoning model: a one-line paraphrase burned 9,894
reasoning tokens (~100s) and hit the default timeout. Send
reasoning_effort=none by default for the openai-compatible backend
(--reasoning-effort / WATERMARKS_REWRITE_REASONING_EFFORT; 'off' omits the
parameter), cutting the same rewrite to ~1s / 12 tokens. Tested end-to-end
against api.deepseek.com.

* fix: sanitize client-supplied filename in HTTP service

CodeQL 'uncontrolled data in path expression' (server.py): a name like
'../../x' flowed into Path(tmpdir) / name, letting an upload escape the
request temp dir on write. Sanitize name to its basename in _decode_input
(_safe_name) and refuse any joined path whose parent is not the tmpdir at
the write sites (_tmp_path). Tests cover traversal names.

* chore: gitignore .env (contains local rewrite credentials)

* chore: deny-by-default gitignore and dockerignore; document compose env config

.gitignore and service/.dockerignore now exclude everything by default and
explicitly allow only what is publishable/needed: tracked source, docs,
tests, .github, and (for images) the service/scripts/ tree that every
Dockerfile COPYs. Root .dockerignore documents that all builds use service/
as context. README Configuration section now covers .env setup for docker
compose, host-side export for CLI runs, and the full variable table.
2026-08-14 15:42:48 -07:00

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2.8 KiB
Docker

# Optional local Docker image for the MarkLLM text-watermark harness.
#
# Build from the repository root (build context = service/):
# docker build -f service/Dockerfile.markllm -t watermarks-remover-markllm service/
#
# The upstream code is fetched from source at build time and is NOT
# redistributed by this repository. Upstream is Apache-2.0.
#
# Vendored fork hardening:
# - base image pinned by digest (no moving tag drift)
# - upstream checkout pinned to a commit SHA (no moving branch)
# - deps pinned exactly in requirements-markllm.txt
# - pip itself pinned (no unpinned bootstrap step)
# - runs as an unprivileged user (a parser bug in a crafted file can no
# longer write files as root inside the container)
# Pinned upstream commit (2026-07-10). Keep in sync with setup_markllm.sh.
ARG MARKLLM_REF=c45ddc40f7b761beabe55a1b8dc4690e531d1c6d
# python:3.14-slim linux/amd64 digest.
FROM python:3.14-slim@sha256:ce40764625a4ff50df3548277632e7f96c4e77fe75fa848aae9885476e7df5a4
ARG MARKLLM_REF
RUN apt-get update \
&& apt-get install -y --no-install-recommends \
git \
libgl1 \
libglib2.0-0 \
passwd \
&& rm -rf /var/lib/apt/lists/*
RUN git clone --depth 1 --filter=blob:none --sparse \
https://github.com/THU-BPM/MarkLLM.git /opt/markllm \
&& cd /opt/markllm \
&& git fetch --depth 1 origin "${MARKLLM_REF}" \
&& git checkout --detach "${MARKLLM_REF}" \
&& git sparse-checkout set --no-cone \
'/watermark/' \
'/config/' \
'/utils/' \
'/exceptions/' \
'/evaluation/dataset.py' \
'/LICENSE' \
'/README.md' \
&& test "$(git -C /opt/markllm rev-parse HEAD)" = "${MARKLLM_REF}"
COPY scripts/requirements-markllm.txt /app/requirements-markllm.txt
COPY scripts/detect_text_watermark.py /app/detect_text_watermark.py
COPY scripts/common.py /app/common.py
# torch is installed first from the CPU index (like Dockerfile.markdiffusion);
# the remaining pinned deps then resolve against it. No GPU wheel index inside
# the image — CUDA users should run setup_markllm.sh on the host instead.
RUN python3 -m pip install --no-cache-dir "pip==26.2.1" \
&& python3 -m pip install --no-cache-dir --index-url https://download.pytorch.org/whl/cpu "torch>=2.13,<2.14" \
&& python3 -m pip install --no-cache-dir -r /app/requirements-markllm.txt
# Unprivileged runtime user. The harness only reads input files and writes to
# stdout, so nothing under /opt, /app, or the mounted data dir needs root.
RUN useradd --create-home --uid 10001 --shell /usr/sbin/nologin markllm
USER markllm
ENV MARKLLM_DIR=/opt/markllm \
HOME=/home/markllm \
PYTHONUNBUFFERED=1 \
PYTHONDONTWRITEBYTECODE=1 \
HF_HOME=/home/markllm/.cache/huggingface
WORKDIR /app
ENTRYPOINT ["python3", "/app/detect_text_watermark.py"]