4c0aadbb5e
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>
30 lines
1.0 KiB
YAML
30 lines
1.0 KiB
YAML
# NVIDIA GPU overlay. Enable by setting COMPOSE_FILE in .env:
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# COMPOSE_FILE=docker-compose.yml:docker/gpu.nvidia.yml
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#
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# Requires the NVIDIA Container Toolkit on the host.
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# Arch: sudo pacman -S nvidia-container-toolkit
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# Debian: sudo apt install nvidia-container-toolkit
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# Fedora: sudo dnf install nvidia-container-toolkit
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# Then:
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# sudo nvidia-ctk runtime configure --runtime=docker
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# sudo systemctl restart docker
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# Verify with:
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# docker info | grep -i nvidia
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#
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# This overlay only passes the host GPU through to the container.
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# The slim Odysseus image does not bundle CUDA userspace or inference
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# engines — install vLLM / llama-cpp-python / SGLang via
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# Cookbook -> Dependencies (or pip) before serving GPU models.
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services:
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odysseus:
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environment:
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- NVIDIA_VISIBLE_DEVICES=all
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- NVIDIA_DRIVER_CAPABILITIES=compute,utility
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deploy:
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resources:
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reservations:
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devices:
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- driver: nvidia
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count: all
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capabilities: [gpu]
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