Multi-stage CUDA build of the native dflash_server from Luce-Org/lucebox-hub (pinned at 42f36f1). Models are not baked into the image; mount /models at runtime. - Dockerfile: nvidia/cuda:12.6.0 devel -> runtime, CUDA_ARCH build-arg (default sm_86), libcuda.so.1 stub symlink + -rpath-link fix - docker-compose.yml: reference service with ./models:/models:ro - Makefile: submodules / doctor / build / run / shell / up-down-logs / push / clean. push targets gitea.va.reichard.io/evan - README + .dockerignore + .gitignore
109 lines
3.6 KiB
Markdown
109 lines
3.6 KiB
Markdown
# dflash-server-docker
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Docker packaging for the native C++/CUDA `dflash_server` from
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[Luce-Org/lucebox-hub](https://github.com/Luce-Org/lucebox-hub) (`dflash/`
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subtree). Produces an OpenAI-compatible HTTP server image suitable for port
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forwarding to OpenAI-compatible clients (Open WebUI, LM Studio, Cline, Codex,
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etc.).
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Models are **not** baked into the image — mount them as a volume at runtime.
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## Prerequisites
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- Host with an NVIDIA GPU + driver supporting CUDA 12.6.
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- [NVIDIA Container Toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html)
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configured for your container runtime.
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- `git`, `make`, and a working `docker` (or podman with `docker` alias).
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## Layout
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```
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dflash-server-docker/
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├── Dockerfile # multi-stage CUDA build, copies lucebox-hub/dflash
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├── docker-compose.yml # reference service (mounts ./models)
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├── Makefile # submodule init, build, run, push, compose
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├── .dockerignore
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├── README.md
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└── lucebox-hub/ # git submodule, pinned commit
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└── dflash/ # source built into the image
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└── deps/ # nested submodules (llama.cpp, Block-Sparse-Attention, cutlass)
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```
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## Quick start
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```bash
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git clone --recurse-submodules git@ssh.gitea.va.reichard.io:evan/dflash-server-docker.git
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cd dflash-server-docker
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# Build (slow: full CUDA compile, ~20–40 min on a fast machine; defaults to sm_86)
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make build
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# Place models under ./models (target + Lucebox GGUF draft)
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mkdir -p models/draft
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# ... copy Qwen3.6-27B-Q4_K_M.gguf to models/
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# ... copy dflash-draft-3.6-q8_0.gguf to models/draft/
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# Run with the reference flag set
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make run
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```
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Then point any OpenAI-compatible client at `http://<host>:18080/v1`.
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## Targets
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| Make target | What it does |
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|---|---|
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| `make doctor` | Sanity-check docker + submodules |
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| `make submodules` | `git submodule update --init --recursive` |
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| `make build` | Build `dflash-server:latest` for `CUDA_ARCH=86` (RTX 3090) |
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| `make rebuild` | Build with `--no-cache` |
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| `make run` | Run with the reference flag set, mounts `./models:/models:ro` |
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| `make shell` | Interactive shell in the built image |
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| `make up` / `down` / `logs` | docker compose lifecycle |
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| `make push` | Tag and push to `gitea.va.reichard.io/evan/dflash-server:latest` |
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| `make clean` | Remove built images |
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Common overrides:
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```bash
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make build CUDA_ARCH=89 # RTX 4090
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make build CUDA_VERSION=12.4.1 # match older host drivers
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make run MODELS_DIR=/srv/models
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make push REGISTRY=ghcr.io/evan
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```
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## Running on a GPU host
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```bash
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docker run --rm --gpus all \
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-v /path/to/models:/models:ro \
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-p 18080:18080 \
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gitea.va.reichard.io/evan/dflash-server:latest \
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/models/Qwen3.6-27B-Q4_K_M.gguf \
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--draft /models/draft/dflash-draft-3.6-q8_0.gguf \
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--host 0.0.0.0 --port 18080 \
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--max-ctx 32768 --max-tokens 512 \
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--fa-window 2048 \
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--ddtree --ddtree-budget 22 \
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--model-name luce-dflash
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```
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## Notes
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- The `lucebox-hub` submodule is pinned to a specific commit. Bumping it:
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```bash
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cd lucebox-hub
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git fetch
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git checkout <new-ref>
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git submodule update --init --recursive
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cd ..
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git add lucebox-hub
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git commit -m "bump lucebox-hub to <new-ref>"
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```
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- `--host 0.0.0.0` inside the container is required for port forwarding.
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- Mount `/models` read-only (`:ro`) — the server only reads model files.
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- See [`lucebox-hub/dflash/README.md`](lucebox-hub/dflash/README.md) for the
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full server flag reference, perf numbers, and architecture notes.
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