ML Server Docker Builder

VerifiedCaution

Builds Docker containers for ML server components (FinRL, StockMixer, etc.). Supports options like --no-cache, --push, --cpu, or building a specific model.

Sby Skills Guide Bot
DevelopmentIntermediate
706/2/2026
Claude Code
#ml#docker#container#build

Recommended for

Our review

Builds Docker containers for ML server components.

Strengths

  • Automates building multiple ML containers.
  • Supports options like --no-cache, --push, --cpu.
  • Allows building specific model containers.

Limitations

  • Requires Docker and registry access.
  • Works with a specific project structure.
  • Does not handle deployment or advanced orchestration.
When to use it

When you need to build and optionally push Docker images for multiple ML models.

When not to use it

For simple single-container builds without advanced options.

Security analysis

Caution
Quality score88/100

The skill orchestrates Docker builds and pushes, which requires trust in the compose files and registry credentials. While the skill itself doesn't contain destructive commands, the power of Docker warrants caution.

Findings
  • Uses Docker commands, which can access the host's Docker daemon and could potentially be exploited if the compose files are malicious.
  • Involves pushing to a container registry, which may expose credentials if not handled securely.
  • No declared allowed-tools, but the skill executes docker compose commands.

Examples

Build all ML containers with no cache
/build-ml --no-cache
Build and push FinRL model
/build-ml --push finrl
Build CPU-only containers
/build-ml --cpu

name: build-ml description: Build ML server Docker containers argument-hint: "[--push|--no-cache|model]"

ML Server Builder

Build Docker containers for ML server components.

Usage

  • /build-ml - Build all ML containers
  • /build-ml --no-cache - Build without cache
  • /build-ml --push - Build and push to registry
  • /build-ml finrl - Build specific model container
  • /build-ml --cpu - Build CPU-only versions

ML Server Structure

services/ml-server/
├── docker-compose.yml      # ML services orchestration
├── docker-compose.dev.yml  # Development config
├── Dockerfile              # Base ML image
├── finrl/                  # FinRL deep learning
├── stockmixer/             # Stock mixing models
├── master/                 # Master orchestrator
├── samba/                  # Samba models
├── macrohft/               # Macro HFT models
└── src/                    # Shared ML code

Available Models

  • finrl - Deep reinforcement learning (FinRL)
  • stockmixer - Multi-asset mixing
  • master - Model orchestration
  • samba - Samba-based models
  • macrohft - Macro HFT strategies

Instructions

When this skill is invoked:

  1. Parse arguments:

    • --no-cache: Add --no-cache to docker build
    • --push: Push to container registry after build
    • --cpu: Use CPU-only base images
    • Model name: Build only that model's container
  2. Navigate to ML server directory:

    cd services/ml-server
    
  3. Build containers:

    # All containers
    docker compose build $NO_CACHE
    
    # Specific model
    docker compose build $MODEL $NO_CACHE
    
  4. If --push specified:

    • Verify registry credentials
    • Tag images appropriately
    • Push to registry:
      docker compose push $MODEL
      
  5. Report build results:

    • Build time per container
    • Final image sizes
    • Any build warnings
    • Layer cache efficiency
  6. Common build issues:

    • CUDA not found: Use --cpu flag or install NVIDIA container toolkit
    • Out of memory: Increase Docker memory limit
    • Pip install fails: Check requirements.txt for version conflicts
    • Model weights missing: Download from model registry first

Image Tags

  • latest - Most recent build
  • v{version} - Release versions
  • {git-sha} - Specific commit builds
  • cpu - CPU-only builds
Related skills