xiejiahao
daaf85f4e5
- run.sh: bridge + -p ${HOST_PORT:-24396}:80, health check uses host port
- entrypoint.sh: PORT defaults to 80, SERVED_NAME defaults to llm
detected port/served name become log hints only
- verify.sh: read host port from port bindings, expect model name llm
- docker-compose.yml: ports mapping instead of network_mode host
- README: update tables, commands and rationale
59 lines
1.7 KiB
YAML
59 lines
1.7 KiB
YAML
services:
|
||
llama4:
|
||
build:
|
||
context: .
|
||
dockerfile: Dockerfile
|
||
image: llama4-bi150:${TAG:-2026-10-26}
|
||
container_name: llama4
|
||
|
||
# 镜像本身不设置启动命令，启动方式全部由这里决定。
|
||
entrypoint: ["/usr/local/bin/llama4-entrypoint.sh"]
|
||
working_dir: /opt/llama4
|
||
|
||
# 容器内固定监听 80，宿主机端口由 HOST_PORT 决定（默认 24396）。
|
||
expose:
|
||
- "80"
|
||
ports:
|
||
- "${HOST_PORT:-24396}:80"
|
||
|
||
# bridge 网络 + 端口映射；ipc host 供 vLLM/PyTorch 多卡共享内存。
|
||
ipc: host
|
||
|
||
# Iluvatar 运行时要求
|
||
privileged: true
|
||
pid: host
|
||
|
||
volumes:
|
||
- /dev:/dev
|
||
- ${MODEL_HOST_DIR:-/mnt/disk0/models/LLM-Research/Llama-4-Scout-17B-16E-Instruct}:/models/llama4:ro
|
||
|
||
environment:
|
||
MODEL_PATH: /models/llama4
|
||
AUTO_DETECT: "${AUTO_DETECT:-1}"
|
||
HOST: "${HOST:-0.0.0.0}"
|
||
|
||
# 默认暴露全部 16 张卡；entrypoint 会根据模型选择实际 TP*PP。
|
||
CUDA_VISIBLE_DEVICES: "${GPUS:-0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15}"
|
||
|
||
# 容器内端口固定 80，模型名固定 llm（AGENTS.md 5.2 / 5.5）。
|
||
PORT: "80"
|
||
SERVED_NAME: "${SERVED_NAME:-llm}"
|
||
|
||
# 留空时由 entrypoint 根据 config.json 自动判断。
|
||
# 需要手动覆盖时直接设置同名环境变量即可。
|
||
TP: "${TP:-}"
|
||
PP: "${PP:-}"
|
||
|
||
MAX_MODEL_LEN: "${MAX_MODEL_LEN:-4096}"
|
||
MAX_NUM_SEQS: "${MAX_NUM_SEQS:-1}"
|
||
GPU_MEM_UTIL: "${GPU_MEM_UTIL:-0.90}"
|
||
ENFORCE_EAGER: "${ENFORCE_EAGER:-1}"
|
||
PYTHONUNBUFFERED: "1"
|
||
EXTRA_ARGS: "${EXTRA_ARGS:-}"
|
||
|
||
ulimits:
|
||
memlock: -1
|
||
stack: 67108864
|
||
|
||
restart: unless-stopped
|