fix(docker): make torch/sentence-transformers optional to unblock builds
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Move torch and sentence-transformers to requirements-reranker.txt so
the main Docker build succeeds even if these large packages fail to
install. The reranker code already handles missing imports gracefully
when RERANK_ENABLED=false (the default).

This fixes the production deployment — builds were failing because of
the ~800MB torch dependency, preventing ALL new code from deploying.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
Benjamin Admin
2026-03-21 15:06:51 +01:00
parent f2924a58ed
commit 71b8c33270
3 changed files with 11 additions and 6 deletions

View File

@@ -10,13 +10,15 @@ RUN apt-get update && apt-get install -y --no-install-recommends \
&& rm -rf /var/lib/apt/lists/*
# Copy requirements first for better caching
COPY requirements.txt .
COPY requirements.txt requirements-reranker.txt ./
# Create virtual environment and install dependencies
RUN python -m venv /opt/venv
ENV PATH="/opt/venv/bin:$PATH"
RUN pip install --no-cache-dir --upgrade pip && \
pip install --no-cache-dir -r requirements.txt
pip install --no-cache-dir -r requirements.txt && \
pip install --no-cache-dir -r requirements-reranker.txt || \
echo "WARNING: reranker dependencies not installed (torch/sentence-transformers)"
# ---- Runtime stage ----
FROM python:3.12-slim-bookworm

View File

@@ -0,0 +1,6 @@
# Optional: Cross-Encoder Re-Ranking (CPU-only PyTorch)
# Install separately: pip install -r requirements-reranker.txt
# Enable at runtime: RERANK_ENABLED=true
--extra-index-url https://download.pytorch.org/whl/cpu
torch
sentence-transformers>=3.0.0

View File

@@ -22,10 +22,7 @@ python-multipart>=0.0.22
# AI / Anthropic (compliance AI assistant)
anthropic==0.75.0
# Re-Ranking (cross-encoder, CPU-only PyTorch to keep image small)
--extra-index-url https://download.pytorch.org/whl/cpu
torch
sentence-transformers>=3.0.0
# Re-Ranking: see requirements-reranker.txt (optional, CPU-only PyTorch)
# PDF Generation (GDPR export, audit reports)
weasyprint>=68.0