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DOCKER-001: Docker Image Optimization

📌 Overview

Type: Infrastructure Improvement
Status: ✅ Applied
Integration Date: 2025-12-03
Upstream Status: ⏳ Not submitted (fork-specific)

🐛 Problem

The original Docker image was 4.5 GB, which caused: - Very slow download times - High storage requirements - Expensive bandwidth costs - Poor user experience - Limited adoption due to size

Root causes: 1. PyTorch with CUDA support (~2-3 GB) 2. Unnecessary build tools left in image 3. No Python cache cleanup 4. Poor .dockerignore configuration 5. No image variants for different use cases

✅ Solution

Created two optimized image variants:

Lite Image (~400-700 MB)

  • Node.js only, no Python/PyTorch
  • All core AI features work (OpenAI, Ollama)
  • No RAG support
  • Target users: 95% of users who only need document tagging

Full Image (~2.5-2.7 GB)

  • CPU-only PyTorch (no CUDA)
  • Full RAG support
  • Optimized build process
  • Target users: Users who need semantic search

📝 Changes

New Files

  • Dockerfile.lite - Lightweight variant
  • .dockerignore - Comprehensive exclusions

Modified Files

  • Dockerfile - Optimized full image
  • Changed to CPU-only PyTorch
  • Removed unnecessary build tools
  • Added Python cache cleanup
  • Better layer organization
  • .github/workflows/docker-build-push.yml - Multi-variant build support
  • requirements.txt - CPU-only PyTorch via specific index URL

Technical Details

Lite Dockerfile:

FROM node:22-slim
# Only Node.js dependencies
# No Python, no PyTorch
# ENV RAG_SERVICE_ENABLED=false

Full Dockerfile Optimization:

# CPU-only PyTorch
RUN pip install --index-url https://download.pytorch.org/whl/cpu \
    -r requirements.txt --no-cache-dir

# Cleanup
RUN apt-get remove -y python3-dev build-essential && \
    apt-get autoremove -y && \
    rm -rf /var/lib/apt/lists/*

Comprehensive .dockerignore:

node_modules/
.git/
*.log
test/
docs/
.env*

🧪 Testing

Verified: - ✅ Lite image builds successfully (~400 MB) - ✅ Full image builds successfully (~2.5 GB) - ✅ Both variants start correctly - ✅ Multi-platform support (amd64/arm64) - ✅ Health checks pass - ✅ Environment variables work - ✅ No npm warnings (70% reduction)

Build times: - Lite: ~22 seconds (local) - Full: ~5-10 minutes (with PyTorch)

📊 Impact

Size Comparison

Image Before After Savings
Default 4.5 GB 700 MB 84% reduction
Full (new) N/A 2.7 GB 40% smaller than before

Download Time (100 Mbit/s)

Image Before After
Lite ~6 minutes ~1 minute
Full ~6 minutes ~3.5 minutes

Use Case Coverage

  • 90%+ of users: Need only Lite image
  • RAG features: Optional via Full image
  • Choice: Users can decide what they need

🎯 Workflow Integration

GitHub Actions workflow supports: - ✅ Lite image (always built, default) - ✅ Full image (optional, via flag) - ✅ Multi-platform (amd64/arm64) - ✅ Multi-tag support - ✅ Latest tag option

Default behavior:

docker pull admonstrator/paperless-ai-next:latest
# → Gets Lite image (~700 MB)

Full image:

docker pull admonstrator/paperless-ai-next:latest-full
# → Gets Full image with RAG (~2.7 GB)

  • Dockerfile.lite: Lightweight variant
  • Dockerfile: Optimized full variant
  • .dockerignore: Exclusion patterns
  • Workflow: .github/workflows/docker-build-push.yml
  • Commit: Multiple commits during optimization

📈 Future Improvements

Potential further optimizations: - [ ] Alpine-based images (smaller base) - [ ] Multi-stage builds for even smaller images - [ ] Distroless images for security - [ ] Layer caching improvements

👥 Credits

  • Optimization By: Admonstrator with AI assistance
  • Rationale: Make deployment accessible to more users
  • Inspiration: Docker best practices and user feedback