docker: add NVIDIA/AMD GPU overlays via COMPOSE_FILE (#254)

Opt-in overlays under docker/ that pass the host GPU into the odysseus
container. Pick one in .env:

  COMPOSE_FILE=docker-compose.yml:docker/gpu.nvidia.yml
  COMPOSE_FILE=docker-compose.yml:docker/gpu.amd.yml

Non-GPU users are unaffected (no default merge). README now points at
the overlays instead of the old ad-hoc `gpus: all` suggestion.

Each overlay header notes that it only exposes the GPU devices — the
slim image still needs vLLM / llama-cpp-python / etc. installed via
Cookbook -> Dependencies before models can serve on GPU.

Tested on Arch + Docker 29.5.1 + RTX 4090:
  docker compose exec odysseus nvidia-smi -L
  GPU 0: NVIDIA GeForce RTX 4090 (UUID: GPU-...)
Cookbook hardware scan reports the 24 GB GPU and recommends GPU-fit
models. `docker compose config` validates cleanly for all three
COMPOSE_FILE variants (base, +nvidia, +amd).

Builds on the structure proposed in #91 by @krllus with the path /
docs fixes from the review on that PR.

Closes #163.

Co-authored-by: krllus <krllus@users.noreply.github.com>

docker/gpu.amd.yml

@@ -0,0 +1,18 @@
+# AMD ROCm GPU overlay. Enable by setting COMPOSE_FILE in .env:
+#   COMPOSE_FILE=docker-compose.yml:docker/gpu.amd.yml
+#
+# Requires ROCm drivers on the host (kfd + DRI devices). The host user
+# running Docker must be in the `video` and `render` groups.
+#
+# This overlay only passes the host GPU through to the container.
+# The slim Odysseus image does not bundle ROCm userspace or inference
+# engines — install ROCm-compatible builds of vLLM / llama-cpp-python
+# via Cookbook -> Dependencies (or pip) before serving GPU models.
+services:
+  odysseus:
+    devices:
+      - /dev/kfd
+      - /dev/dri
+    group_add:
+      - video
+      - render

docker/gpu.nvidia.yml

@@ -0,0 +1,29 @@
+# NVIDIA GPU overlay. Enable by setting COMPOSE_FILE in .env:
+#   COMPOSE_FILE=docker-compose.yml:docker/gpu.nvidia.yml
+#
+# Requires the NVIDIA Container Toolkit on the host.
+#   Arch:    sudo pacman -S nvidia-container-toolkit
+#   Debian:  sudo apt install nvidia-container-toolkit
+#   Fedora:  sudo dnf install nvidia-container-toolkit
+# Then:
+#   sudo nvidia-ctk runtime configure --runtime=docker
+#   sudo systemctl restart docker
+# Verify with:
+#   docker info | grep -i nvidia
+#
+# This overlay only passes the host GPU through to the container.
+# The slim Odysseus image does not bundle CUDA userspace or inference
+# engines — install vLLM / llama-cpp-python / SGLang via
+# Cookbook -> Dependencies (or pip) before serving GPU models.
+services:
+  odysseus:
+    environment:
+      - NVIDIA_VISIBLE_DEVICES=all
+      - NVIDIA_DRIVER_CAPABILITIES=compute,utility
+    deploy:
+      resources:
+        reservations:
+          devices:
+            - driver: nvidia
+              count: all
+              capabilities: [gpu]