10 Docker Profiles

10 — Docker profiles

Updated: 2026-08-30

⚠️ Ports arrêtés cités dans cette page (note ajoutée le 2026-08-30 ; le corps ci-dessous n'a pas été réécrit) :

• brain_worker :5557 est arrete depuis le 2026-06-03 (OOM ONNX BGE-M3) — l'embedder vivant est :8099 (BGE-M3 GGUF llama.cpp).

Nokido's Docker setup uses Compose profiles to ship only the services you need. Five profiles (core, full, all, dev) and four image variants (core, hub, full, all).

Compose file : docker/nokido/docker-compose.yml. Dockerfile : docker/nokido/Dockerfile.

🎯 Profiles vs variants

• Profile = which services launch (docker compose --profile X up).
• Variant = which Python extras get baked into the laforge-hub image (BUILD_VARIANT=Y docker compose build).

You combine them : a small image variant + a minimal profile = lightest setup. A heavy image variant + the all profile = full stack.

🚀 Compose profiles

Profile	Services	Image size	Use case
core	ollama + laforge-hub	~1 GB	Daily dev, single-host.
full	+ deno-webhub + brain-worker	~2.5 GB	Production-like, with event bus + embedder.
all	+ netcfg-agent + searxng	~3.5 GB	Multi-vendor network management + local web search.
dev	+ adminer	+50 MB	Database browsing during development.

Profiles compose with --profile flags :

# Minimal
docker compose -f docker/nokido/docker-compose.yml --profile core up -d

# Production
docker compose --profile full up -d

# Everything including dev tools
docker compose --profile all --profile dev up -d

Service detail per profile

core profile

• ollama :11434 — LLM inference (Ollama). Pull models with docker exec laforge-ollama ollama pull <model>. Models persisted in ollama_data volume.
• laforge-hub :8766 — the hub itself. Built from docker/nokido/Dockerfile. Volumes : rag_data (/app/RAG), logs_data (/app/logs), sandbox_data (/app/sandbox), vault_data (/app/data).

full profile (adds)

• deno-webhub :7401 — Deno event bus (nervous system). Mounts proxy_deno/ read-only. Communicates with hub via the internal Docker network.
• brain-worker :5557 (ZMQ) — Rust + ONNX BGE-M3 embedder. Built from docker/brain_worker/Dockerfile (separate image). Mounts rag_data read-only + models_data for ONNX model cache.

all profile (adds)

• netcfg-agent :7500 (UI) + :8767 (MCP) — multi-vendor network config (Cisco, Huawei, Aruba, HPE…). Volume netcfg_data.
• searxng :8888 → :8080 — self-hosted SearXNG for web_search tool.

dev profile (adds)

• adminer :8080 — browse embeddings.db via web UI. Useful for inspecting rag_chunks, agent_messages, network_log.

🎁 Image variants (build-time)

Build the hub image with one of four extras combinations :

BUILD_VARIANT=core docker compose -f docker/nokido/docker-compose.yml build laforge-hub
BUILD_VARIANT=hub  docker compose build laforge-hub   # default
BUILD_VARIANT=full docker compose build laforge-hub
BUILD_VARIANT=all  docker compose build laforge-hub

VARIANT	pyproject extra	Includes	Image size
core	(core only)	httpx + requests + pydantic + psutil + rich	~80 MB
hub	[hub,rag,llm,docs,git]	+ FastAPI + FAISS + litellm + tree-sitter + gitpython	~450 MB
full	[hub,rag,llm,cloud,ui,git,docker,docs]	+ Anthropic/Groq/Cohere clients + Textual + PySide6 + Docker SDK	~900 MB
all	[all]	+ torch + jax + sentence-transformers + semgrep + pwntools + …everything	~5 GB

Default is hub — useful for the core and full compose profiles. If you run the all compose profile, set BUILD_VARIANT=full or all to make the heavy services usable.

🔧 Multi-stage build

The Dockerfile uses two stages for layer caching and small final images :

1. builder (Python 3.12-slim + apt build deps) :

   • Installs gcc, g++, libffi-dev, libssl-dev, git, curl.
   • Pre-downloads wheels into /wheels for the requested VARIANT.
   • Builds the laforge-agent wheel itself.

2. runtime (Python 3.12-slim, minimal apt) :

   • Only curl (healthcheck) + libgomp1 (faiss).
   • Installs from /wheels with --no-index --find-links=/wheels (offline, reproducible).
   • Non-root user UID 1000 (configurable via build ARG).
   • HEALTHCHECK on /health.
   • Sets LAFORGE_ROOT=/app, LAFORGE_ENV=prod.

🗄️ Volumes

Volume	Mount	Purpose
ollama_data	/root/.ollama (ollama container)	Persisted LLM model files.
rag_data	/app/RAG	embeddings.db + FAISS indexes + lessons.
logs_data	/app/logs	All log files.
sandbox_data	/app/sandbox	Scratch space + heartbeats.
vault_data	/app/data	machine_vault.dat (DPAPI-equivalent on Linux ≡ keyring file fallback).
models_data	/app/models (brain-worker)	ONNX BGE-M3 model cache.
netcfg_data	/app/netcfg (netcfg-agent)	Multi-vendor config + KeePass vault.
searxng_data	/etc/searxng	SearXNG config + custom plugins.

Backup : docker compose down && docker run --rm -v nokido_rag_data:/data -v $(pwd):/backup alpine tar czf /backup/rag.tar.gz /data.

🌐 Networking

• All services live in the default Compose network (laforge-default).
• Inter-service DNS : http://laforge-hub:8766, http://ollama:11434, http://laforge-deno-webhub:7401, etc.
• Host port mappings :
  • 8766 → laforge-hub
  • 11434 → ollama
  • 7401 → deno-webhub
  • 5557 → brain-worker (ZMQ)
  • 7500 / 8767 → netcfg-agent (UI / MCP)
  • 8888 → searxng
  • 8080 → adminer (dev)
• extra_hosts: ["host.docker.internal:host-gateway"] lets the hub reach services on your laptop (e.g. native LM Studio on :1234).

🚨 Healthchecks

Every service that exposes HTTP has a healthcheck :

• ollama : curl -sf http://localhost:11434/api/tags
• laforge-hub : curl -sf http://localhost:8766/health

Start-period : 15s for laforge-hub (warmup time : RAG load + ONNX init).

🏗️ Custom Dockerfile (advanced)

If you need to embed a custom skill or pre-pulled models, fork the Dockerfile :

FROM nokido:hub AS base

USER root
RUN apt-get update && apt-get install -y my-tool
USER nokido

COPY my-skill/ /app/skills/my-skill/

Build : docker build -f Dockerfile.custom -t nokido:my-build .. Override the image in compose : image: nokido:my-build.

⚡ Performance tips

• Use multi-CPU. Set OLLAMA_MAX_LOADED_MODELS=1 (default in compose) unless you're benchmarking — model swap is fast enough and saves RAM.
• For ML extras, build on the target host (CUDA wheels are arch-specific). Don't docker build on a non-GPU host and expect CUDA to work.
• For embeddings, brain-worker is CPU-bound by default. To use a GPU/NPU, set BRAIN_WORKER_BACKEND=directml|vulkan|openvino|cuda in the service's environment block.

🔒 Security notes for Docker

• The hub binds 0.0.0.0:8766 inside the container, but the port mapping uses 127.0.0.1:8766:8766 — only localhost reaches it. To expose remotely, wrap with Tailscale/WireGuard ; don't change the bind.
• Sandbox accounts for run/orchestrate Docker actions = the nokido UID 1000 inside the container. The container itself runs as non-root.
• vault_data contains decryptable secrets if the host is compromised — same threat model as a Nokido.env on disk. The DPAPI / Keychain protection is only meaningful in native installs.

For a full threat model, see 07 — Security model.