Dev Containers¶
Browse pre-configured VS Code devcontainer configurations for AI/ML development.
Auto-Generated Documentation
This documentation is automatically generated from devcontainer/ configurations. Pages are generated dynamically at MkDocs build time.
Statistics: 22 configurations across 8 variants
Base Images¶
| Variant | Description | Docker | Podman | GPU |
|---|---|---|---|---|
| Base | Minimal foundation container with dev... | - | ||
| Nvidia | NVIDIA CUDA base container | |||
| Nvidia Python | ML-focused Python environment with CUDA |
AI/ML Services¶
| Variant | Description | Docker | Podman | GPU |
|---|---|---|---|---|
| Jupyter | JupyterLab data science environment | |||
| Ollama | LLM inference engine with GPU acceler... | |||
| Comfyui | Stable Diffusion workflow editor |
DevOps¶
| Variant | Description | Docker | Podman | GPU |
|---|---|---|---|---|
| Sandbox | Container orchestration tools (Podman... | - | ||
| Githubrunner | GitHub Actions self-hosted runner | - |
Getting Started¶
For detailed setup instructions, see the Dev Containers deployment guide.
Prerequisites¶
- VS Code with Dev Containers extension
- Docker or Podman installed
- For GPU variants: NVIDIA Container Toolkit (CDI)
Quick Start¶
- Clone the repository
- Open in VS Code
- Select "Reopen in Container" when prompted
- Choose the appropriate variant for your needs