chore(#254): slim latest-local image (multi-stage + opt-in reasoning)
- Move docling-agent + mellea out of requirements.txt into a dedicated requirements-reasoning.txt. They are no longer pulled into latest-remote (regression fix) nor into latest-local by default. - Dockerfile: split into builder-remote / builder-local / runtime-base stages. The runtime image carries no pip and no build cache; the source is COPYed only in the final stages so a code-only change reuses every pip-install layer. - Add WITH_REASONING build-arg (default false) on the local target. Set to true to bundle the R&D reasoning-trace deps for a local-reasoning image. - Harden .dockerignore: tests/, data/, uploads/, IDE files, stray node_modules / package-lock.json, the one-shot migrate_06.py utility. - Set HF_HOME so the Docling/HF model cache lands in a deterministic appuser-owned path that compose can mount as a volume.
This commit is contained in:
Pier-Jean Malandrino
parent
38da579103
commit
0b544bdaef
4 changed files with 108 additions and 36 deletions
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@ -10,3 +10,25 @@ __pycache__/
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.mypy_cache/
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.pytest_cache/
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.ruff_cache/
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# Test + dev assets — never needed in the runtime image.
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tests/
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conftest.py
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pytest.ini
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requirements-test.txt
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# Local runtime data — must not leak into the image.
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data/
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uploads/
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# One-shot migration utility — runs out-of-band, not from the image.
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tools/migrate_06.py
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# IDE / editor metadata.
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*.iml
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.idea/
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.vscode/
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# Stray frontend artefacts that have no business inside document-parser/.
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package-lock.json
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node_modules/
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@ -1,56 +1,101 @@
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# syntax=docker/dockerfile:1
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# =============================================================================
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# Docling Studio — backend image (multi-target: remote / local)
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# Docling Studio — backend image (multi-stage, multi-target: remote / local)
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#
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# Usage:
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# Standard usage:
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# docker build --target remote -t docling-studio-backend:remote .
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# docker build --target local -t docling-studio-backend:local .
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#
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# R&D variant — opt in to the reasoning-trace runner (docling-agent + mellea,
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# heavy transitive deps; runtime-gated by REASONING_ENABLED):
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# docker build --target local --build-arg WITH_REASONING=true \
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# -t docling-studio-backend:local-reasoning .
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#
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# Cache notes:
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# - Source is COPYed only in the final stages, never in the builders.
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# A code-only change reuses every pip-install layer.
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# - Each builder owns a venv at /opt/venv that the final stage copies in
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# wholesale (no pip in the runtime image).
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# =============================================================================
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# --- Base: common deps for both targets ---
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FROM python:3.12-slim AS base
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# --- Builder: remote (lightweight HTTP-only deps) ----------------------------
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FROM python:3.12-slim AS builder-remote
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ENV PIP_NO_CACHE_DIR=1 \
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PIP_DISABLE_PIP_VERSION_CHECK=1
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WORKDIR /build
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RUN python -m venv /opt/venv
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ENV PATH="/opt/venv/bin:$PATH"
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COPY requirements.txt .
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RUN pip install -r requirements.txt
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# --- Builder: local (torch CPU + full Docling, optional reasoning deps) ------
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FROM python:3.12-slim AS builder-local
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ENV PIP_NO_CACHE_DIR=1 \
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PIP_DISABLE_PIP_VERSION_CHECK=1
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WORKDIR /build
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RUN python -m venv /opt/venv
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ENV PATH="/opt/venv/bin:$PATH"
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COPY requirements.txt requirements-local.txt requirements-reasoning.txt ./
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# torch CPU wheels in their own layer — pinned to the CPU-only index so the
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# transitive resolution of docling does not re-pull a CUDA build.
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RUN pip install torch torchvision --index-url https://download.pytorch.org/whl/cpu
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# Full local stack (requirements-local.txt re-includes requirements.txt).
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RUN pip install -r requirements-local.txt
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# Reasoning is opt-in; off by default keeps the standard image lean.
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ARG WITH_REASONING=false
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RUN if [ "$WITH_REASONING" = "true" ]; then \
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pip install -r requirements-reasoning.txt; \
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fi
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# --- Runtime base (no pip, no source — shared by both final targets) ---------
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FROM python:3.12-slim AS runtime-base
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RUN apt-get update && apt-get install -y --no-install-recommends \
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poppler-utils \
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poppler-utils \
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&& rm -rf /var/lib/apt/lists/*
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RUN useradd --create-home --shell /bin/bash appuser \
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&& mkdir -p /app/uploads /app/data /home/appuser/.cache/huggingface \
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&& chown -R appuser:appuser /app /home/appuser/.cache
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WORKDIR /app
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COPY requirements.txt .
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RUN pip install --no-cache-dir -r requirements.txt
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COPY . .
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RUN useradd --create-home --shell /bin/bash appuser \
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&& mkdir -p /app/uploads /app/data \
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&& chown -R appuser:appuser /app
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ENV PATH="/opt/venv/bin:$PATH" \
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PYTHONDONTWRITEBYTECODE=1 \
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PYTHONUNBUFFERED=1 \
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UPLOAD_DIR=/app/uploads \
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DB_PATH=/app/data/docling_studio.db \
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HF_HOME=/home/appuser/.cache/huggingface
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EXPOSE 8000
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ENV UPLOAD_DIR=/app/uploads
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ENV DB_PATH=/app/data/docling_studio.db
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USER appuser
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CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000"]
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# --- Remote: lightweight, delegates to Docling Serve ---
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FROM base AS remote
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# --- Final: remote -----------------------------------------------------------
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FROM runtime-base AS remote
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COPY --from=builder-remote --chown=appuser:appuser /opt/venv /opt/venv
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COPY --chown=appuser:appuser . /app
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ENV CONVERSION_ENGINE=remote
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# --- Local: full Docling in-process ---
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FROM base AS local
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# --- Final: local ------------------------------------------------------------
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FROM runtime-base AS local
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USER root
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RUN apt-get update && apt-get install -y --no-install-recommends \
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libgl1 \
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libglib2.0-0 \
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libgl1 \
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libglib2.0-0 \
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&& rm -rf /var/lib/apt/lists/*
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COPY requirements-local.txt .
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RUN pip install --no-cache-dir torch torchvision --index-url https://download.pytorch.org/whl/cpu \
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&& pip install --no-cache-dir -r requirements-local.txt
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RUN chown -R appuser:appuser /app \
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&& chown -R appuser:appuser /usr/local/lib/python3.12/site-packages/rapidocr/models
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USER appuser
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COPY --from=builder-local --chown=appuser:appuser /opt/venv /opt/venv
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COPY --chown=appuser:appuser . /app
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ENV CONVERSION_ENGINE=local
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11
document-parser/requirements-reasoning.txt
Normal file
11
document-parser/requirements-reasoning.txt
Normal file
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@ -0,0 +1,11 @@
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# R&D reasoning-trace live runner — calls docling-agent's `_rag_loop` over
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# an Ollama backend. Gated server-side by `REASONING_ENABLED`; pulls a
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# heavy transitive set (mellea + pydantic-ai + several LLM SDKs).
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#
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# Opt in at build time with `--build-arg WITH_REASONING=true` on the
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# `local` Dockerfile target. Default off keeps the standard image lean.
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#
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# See https://github.com/docling-project/docling-agent/issues/26 for the
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# public-API replacement of `_rag_loop`.
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docling-agent==0.1.0
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mellea==0.4.2
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@ -9,9 +9,3 @@ httpx>=0.27.0,<1.0.0
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pypdfium2>=4.0.0,<5.0.0
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opensearch-py[async]>=2.6.0,<3.0.0
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neo4j>=5.15.0,<6.0.0
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# R&D reasoning-trace live runner — calls docling-agent's `_rag_loop` over
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# an Ollama backend. Gated server-side by `REASONING_ENABLED`; pulls ~60MB
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# of deps. See https://github.com/docling-project/docling-agent/issues/26 for
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# the public-API replacement of `_rag_loop`.
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docling-agent==0.1.0
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mellea==0.4.2
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