AI Devcontainer — Architecture & Setup

Tue, 07 Apr 2026 07:46:04 +0000

Overview

This devcontainer provides a self-contained, GPU-accelerated AI development environment running inside a DevPod workspace. It serves a full local LLM stack accessible publicly via a Cloudflare tunnel at https://ai.uclab.dev.

Internet
   │
   ▼
Cloudflare (ai.uclab.dev)
   │  Zero Trust Tunnel
   ▼
cloudflared (container)
   │  http://localhost:8080
   ▼
Open WebUI  ──────────────────►  Ollama API (localhost:11434)
(port 8080)                           │
                                       ▼
                                 GPU: RTX 5060 (8 GB VRAM)
                                 Models: llama3.1:8b, qwen2.5:7b,
                                         deepseek-coder-v2:16b-lite-instruct-q4_K_M,
                                         mistral-nemo

Host Requirements

Requirement	Details
Container runtime	Docker with nvidia-container-toolkit
GPU passthrough	CDI (`nvidia.com/gpu=all`)
DevPod workspace	Workspace ID: `ai`
Host directories	`~/.ollama` (model storage), `~/.cloudflared` (tunnel credentials)

File Structure

.devcontainer/
├── Dockerfile              # Image definition
├── devcontainer.json       # DevPod/VS Code container config
├── pull-models             # Script to pull Ollama models (idempotent)
├── supervisord.conf        # Reference config (not active — see note below)
├── supervisord/
│   ├── ollama.conf         # Supervisor program: Ollama
│   ├── open-webui.conf     # Supervisor program: Open WebUI
│   └── cloudflared.conf    # Supervisor program: Cloudflare tunnel
└── scripts/
    ├── setup               # Trusts and installs mise tools for workspace
    └── setup_project       # One-time project setup (commitizen, pre-commit)

Docker Image

Base: nvidia/cuda:12.8.0-runtime-ubuntu24.04

Open-Webui on DevOps von UCLAB

AI Devcontainer — Architecture & Setup

Overview

Host Requirements

File Structure

Docker Image