add docker

This commit is contained in:
2026-08-12 20:02:49 +07:00
parent 7a3333b2f8
commit b01698e663
4 changed files with 256 additions and 14 deletions
+23 -14
View File
@@ -1,14 +1,22 @@
# llama.cpp + CUDA в Docker (Qwen3.x / крупные GGUF на 12 ГБ VRAM: гибрид GPU+CPU).
# Образ по умолчанию: server-cuda (CUDA 12 в контейнере) — совместим с большинством GPU и драйверов.
# Альтернатива: server-cuda13 — только если GPU/драйвер тянут CUDA 13; иначе ggml_cuda_init:
# «forward compatibility was attempted on non supported HW» → оставьте server-cuda.
# Нужны: драйвер NVIDIA, NVIDIA Container Toolkit, runtime nvidia в Docker.
# llama-cpp-turboquant + CUDA в Docker (Qwen3.x / крупные GGUF на 12 ГБ VRAM: гибрид GPU+CPU).
# Образы собираются локально из клона TheTom/llama-cpp-turboquant (см. docker/).
#
# Модель: ./models/ + MODEL_FILE в .env.
# Запуск: docker compose up -d или docker-compose up -d
# Podman (одна команда, те же флаги): ./podman-llama.sh
# CUDA 12 (дефолт) — RTX 30xx / драйвер CUDA 12.x
# CUDA 13 — Blackwell (RTX 50xx, sm_120), драйвер ≥ CUDA 13.1:
# LLAMA_IMAGE_TAG=server-cuda13 LLAMA_DOCKERFILE=../llama-space/docker/server-cuda13.Dockerfile \
# docker-compose build
#
# Источник: LLAMA_CPP_SRC (дефолт ../llama-cpp-turboquant).
# dockerfile — путь относительно context (так требует docker-compose 1.x).
#
# Сборка: docker-compose build
# Запуск: docker-compose up -d
# Podman: ./podman-llama.sh
# Проверка: curl http://localhost:8080/health
#
# Нужны: драйвер NVIDIA, NVIDIA Container Toolkit, runtime nvidia в Docker.
# Модель: ./models/ + MODEL_FILE в .env.
#
# OOM: уменьшите CTX_SIZE (дефолт 50000), -ngl и/или cache types; при «каше» попробуйте bf16/f16 для KV (больше VRAM).
# MoE: в .env CPU_MOE=1 при необходимости; число слоёв MoE на CPU — N_CPU_MOE (дефолт 99 в command); для dense оставьте CPU_MOE=0.
# --mlock + Docker: поднимите memlock ниже; если предупреждение остаётся — проверьте default-ulimits в /etc/docker/daemon.json и лимиты пользователя на хосте.
@@ -18,7 +26,12 @@ version: "3.8"
services:
llama-server:
image: ghcr.io/ggml-org/llama.cpp:server-cuda13
# image: ghcr.io/ggml-org/llama.cpp:server-cuda13
image: llama-turboquant:${LLAMA_IMAGE_TAG:-server-cuda12}
build:
context: ${LLAMA_CPP_SRC:-../llama-cpp-turboquant}
# Relative to context (sibling of llama-space). Override for CUDA 13 — см. шапку.
dockerfile: ${LLAMA_DOCKERFILE:-../llama-space/docker/server-cuda12.Dockerfile}
container_name: llama-server
ports:
# Явный IPv4 на хосте (избегаем привязки только к [::] в части окружений).
@@ -43,16 +56,12 @@ services:
- "0.0.0.0"
- "--port"
- "8080"
- "--spec-type"
- "draft-mtp"
- "--spec-draft-n-max"
- "3"
- "--n-cpu-moe"
- "${N_CPU_MOE:-99}"
- "-c"
- "${CTX_SIZE:-50000}"
- "-np"
- "1"
- "4"
- "-fa"
- "on"
- "--cache-type-k"
+53
View File
@@ -0,0 +1,53 @@
#!/usr/bin/env bash
# Сборка образов llama-cpp-turboquant (CUDA 12 / CUDA 13).
# Контекст — клон TheTom/llama-cpp-turboquant; Dockerfile'ы — в этом репозитории.
#
# ./docker/build.sh # CUDA 12 (RTX 30xx)
# ./docker/build.sh 13 # CUDA 13 / sm_120 (RTX 50xx)
# ./docker/build.sh 12 13 # оба
#
# Переменные: LLAMA_CPP_SRC, DOCKER (docker|podman)
set -euo pipefail
ROOT="$(cd "$(dirname "${BASH_SOURCE[0]}")/.." && pwd)"
SRC="${LLAMA_CPP_SRC:-$(cd "$ROOT/../llama-cpp-turboquant" && pwd)}"
DOCKER="${DOCKER:-docker}"
if [[ ! -f "$SRC/CMakeLists.txt" ]]; then
echo "llama.cpp source not found at: $SRC" >&2
echo "Set LLAMA_CPP_SRC to the TheTom/llama-cpp-turboquant checkout." >&2
exit 1
fi
build_one() {
local ver="$1"
local df tag
case "$ver" in
12)
df="$ROOT/docker/server-cuda12.Dockerfile"
tag="llama-turboquant:server-cuda12"
;;
13)
df="$ROOT/docker/server-cuda13.Dockerfile"
tag="llama-turboquant:server-cuda13"
;;
*)
echo "Unknown CUDA major: $ver (use 12 or 13)" >&2
exit 1
;;
esac
echo "==> Building $tag"
echo " Dockerfile: $df"
echo " Context: $SRC"
"$DOCKER" build -f "$df" -t "$tag" "$SRC"
}
if [[ $# -eq 0 ]]; then
set -- 12
fi
for ver in "$@"; do
build_one "$ver"
done
+90
View File
@@ -0,0 +1,90 @@
# llama-cpp-turboquant → llama-server (CUDA 12).
# Build context: root of https://github.com/TheTom/llama-cpp-turboquant
# docker build -f docker/server-cuda12.Dockerfile -t llama-turboquant:server-cuda12 ../llama-cpp-turboquant
#
# Для RTX 30xx (sm_86) и типичных драйверов с CUDA 12.x.
# Архитектуры — дефолт CMake (включая 86-real); не трогаем, чтобы не ломать
# CMAKE_CUDA_ARCHITECTURES со списком через «;» в shell RUN.
ARG UBUNTU_VERSION=24.04
ARG CUDA_VERSION=12.8.1
ARG GCC_VERSION=14
ARG BASE_CUDA_DEV_CONTAINER=docker.io/nvidia/cuda:${CUDA_VERSION}-devel-ubuntu${UBUNTU_VERSION}
ARG BASE_CUDA_RUN_CONTAINER=docker.io/nvidia/cuda:${CUDA_VERSION}-runtime-ubuntu${UBUNTU_VERSION}
ARG BUILD_DATE=N/A
ARG APP_VERSION=N/A
ARG APP_REVISION=N/A
ARG NODE_VERSION=24
FROM docker.io/node:$NODE_VERSION AS web
ARG APP_VERSION
WORKDIR /app/tools/ui
COPY tools/ui/package.json tools/ui/package-lock.json ./
RUN npm ci
COPY tools/ui/ ./
RUN LLAMA_BUILD_NUMBER="$APP_VERSION" npm run build
FROM ${BASE_CUDA_DEV_CONTAINER} AS build
ARG GCC_VERSION
ARG CUDA_DOCKER_ARCH=default
RUN apt-get update && \
apt-get install -y gcc-${GCC_VERSION} g++-${GCC_VERSION} build-essential cmake python3 python3-pip git libssl-dev libgomp1
ENV CC=gcc-${GCC_VERSION} CXX=g++-${GCC_VERSION} CUDAHOSTCXX=g++-${GCC_VERSION}
WORKDIR /app
COPY . .
COPY --from=web /app/tools/ui/dist tools/ui/dist
RUN if [ "${CUDA_DOCKER_ARCH}" != "default" ]; then \
export CMAKE_ARGS="-DCMAKE_CUDA_ARCHITECTURES=${CUDA_DOCKER_ARCH}"; \
fi && \
cmake -B build -DGGML_NATIVE=OFF -DGGML_CUDA=ON -DGGML_BACKEND_DL=ON -DGGML_CPU_ALL_VARIANTS=ON -DLLAMA_BUILD_TESTS=OFF ${CMAKE_ARGS} -DCMAKE_EXE_LINKER_FLAGS=-Wl,--allow-shlib-undefined . && \
cmake --build build --config Release -j"$(nproc)" --target llama-server
RUN mkdir -p /app/lib && \
find build -name "*.so*" -exec cp -P {} /app/lib \;
RUN mkdir -p /app/full \
&& cp build/bin/llama-server /app/full/
FROM ${BASE_CUDA_RUN_CONTAINER} AS server
ARG BUILD_DATE=N/A
ARG APP_VERSION=N/A
ARG APP_REVISION=N/A
LABEL org.opencontainers.image.created=$BUILD_DATE \
org.opencontainers.image.version=$APP_VERSION \
org.opencontainers.image.revision=$APP_REVISION \
org.opencontainers.image.title="llama-cpp-turboquant" \
org.opencontainers.image.description="llama-server with TurboQuant KV (CUDA 12)" \
org.opencontainers.image.source="https://github.com/TheTom/llama-cpp-turboquant"
RUN apt-get update \
&& apt-get install -y libgomp1 curl \
&& apt autoremove -y \
&& apt clean -y \
&& rm -rf /tmp/* /var/tmp/* \
&& find /var/cache/apt/archives /var/lib/apt/lists -not -name lock -type f -delete \
&& find /var/cache -type f -delete
ENV LLAMA_ARG_HOST=0.0.0.0
COPY --from=build /app/lib/ /app
COPY --from=build /app/full/llama-server /app/
WORKDIR /app
HEALTHCHECK CMD [ "curl", "-f", "http://localhost:8080/health" ]
ENTRYPOINT [ "/app/llama-server" ]
+90
View File
@@ -0,0 +1,90 @@
# llama-cpp-turboquant → llama-server (CUDA 13).
# Build context: root of https://github.com/TheTom/llama-cpp-turboquant
# docker build -f docker/server-cuda13.Dockerfile -t llama-turboquant:server-cuda13 ../llama-cpp-turboquant
#
# Для Blackwell (RTX 50xx, sm_120). Toolkit 13.1.x — под драйвер с nvidia-smi CUDA 13.1.
# Только 120a-real: быстрее сборка, FP4 tensor cores; не для карт старше Blackwell.
ARG UBUNTU_VERSION=24.04
ARG CUDA_VERSION=13.1.2
ARG GCC_VERSION=14
ARG BASE_CUDA_DEV_CONTAINER=docker.io/nvidia/cuda:${CUDA_VERSION}-devel-ubuntu${UBUNTU_VERSION}
ARG BASE_CUDA_RUN_CONTAINER=docker.io/nvidia/cuda:${CUDA_VERSION}-runtime-ubuntu${UBUNTU_VERSION}
ARG BUILD_DATE=N/A
ARG APP_VERSION=N/A
ARG APP_REVISION=N/A
ARG NODE_VERSION=24
FROM docker.io/node:$NODE_VERSION AS web
ARG APP_VERSION
WORKDIR /app/tools/ui
COPY tools/ui/package.json tools/ui/package-lock.json ./
RUN npm ci
COPY tools/ui/ ./
RUN LLAMA_BUILD_NUMBER="$APP_VERSION" npm run build
FROM ${BASE_CUDA_DEV_CONTAINER} AS build
ARG GCC_VERSION
# 120 → CMake подменит на 120a; явно 120a-real под Blackwell (не forwards-compatible).
ARG CUDA_DOCKER_ARCH=120a-real
RUN apt-get update && \
apt-get install -y gcc-${GCC_VERSION} g++-${GCC_VERSION} build-essential cmake python3 python3-pip git libssl-dev libgomp1
ENV CC=gcc-${GCC_VERSION} CXX=g++-${GCC_VERSION} CUDAHOSTCXX=g++-${GCC_VERSION}
WORKDIR /app
COPY . .
COPY --from=web /app/tools/ui/dist tools/ui/dist
RUN if [ "${CUDA_DOCKER_ARCH}" != "default" ]; then \
export CMAKE_ARGS="-DCMAKE_CUDA_ARCHITECTURES=${CUDA_DOCKER_ARCH}"; \
fi && \
cmake -B build -DGGML_NATIVE=OFF -DGGML_CUDA=ON -DGGML_BACKEND_DL=ON -DGGML_CPU_ALL_VARIANTS=ON -DLLAMA_BUILD_TESTS=OFF ${CMAKE_ARGS} -DCMAKE_EXE_LINKER_FLAGS=-Wl,--allow-shlib-undefined . && \
cmake --build build --config Release -j"$(nproc)" --target llama-server
RUN mkdir -p /app/lib && \
find build -name "*.so*" -exec cp -P {} /app/lib \;
RUN mkdir -p /app/full \
&& cp build/bin/llama-server /app/full/
FROM ${BASE_CUDA_RUN_CONTAINER} AS server
ARG BUILD_DATE=N/A
ARG APP_VERSION=N/A
ARG APP_REVISION=N/A
LABEL org.opencontainers.image.created=$BUILD_DATE \
org.opencontainers.image.version=$APP_VERSION \
org.opencontainers.image.revision=$APP_REVISION \
org.opencontainers.image.title="llama-cpp-turboquant" \
org.opencontainers.image.description="llama-server with TurboQuant KV (CUDA 13 / sm_120)" \
org.opencontainers.image.source="https://github.com/TheTom/llama-cpp-turboquant"
RUN apt-get update \
&& apt-get install -y libgomp1 curl \
&& apt autoremove -y \
&& apt clean -y \
&& rm -rf /tmp/* /var/tmp/* \
&& find /var/cache/apt/archives /var/lib/apt/lists -not -name lock -type f -delete \
&& find /var/cache -type f -delete
ENV LLAMA_ARG_HOST=0.0.0.0
COPY --from=build /app/lib/ /app
COPY --from=build /app/full/llama-server /app/
WORKDIR /app
HEALTHCHECK CMD [ "curl", "-f", "http://localhost:8080/health" ]
ENTRYPOINT [ "/app/llama-server" ]