xiejiahao
ade41407d7
- run.sh: bridge + -p ${HOST_PORT:-24396}:80, health check uses host port
- entrypoint.sh: PORT defaults to 80, SERVED_NAME defaults to llm
detected port/served name become log hints only
- verify.sh: read host port from port bindings, expect model name llm
- docker-compose.yml: ports mapping instead of network_mode host
- README: update tables, commands and rationale
62 lines
1.8 KiB
YAML
62 lines
1.8 KiB
YAML
services:
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gemma4:
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build:
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context: .
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dockerfile: Dockerfile
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image: gemma4-bi150:${TAG:-2026-10-27}
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container_name: gemma4
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# 镜像本身不设置启动命令，启动方式全部由这里决定。
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entrypoint: ["/usr/local/bin/gemma4-entrypoint.sh"]
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working_dir: /opt/gemma4
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# 容器内固定监听 80，宿主机端口由 HOST_PORT 决定（默认 24396）。
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expose:
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- "80"
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ports:
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- "${HOST_PORT:-24396}:80"
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# bridge 网络 + 端口映射；ipc host 供 vLLM/PyTorch 多卡共享内存。
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ipc: host
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# Iluvatar 运行时需要 privileged + /dev 绑定。
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# 只给 --device=/dev/iluvatar* 会在 worker init 时报
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# cudaGetDeviceCount() ... Error 1001
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privileged: true
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pid: host
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volumes:
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- /dev:/dev
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- ${MODEL_HOST_DIR:-/mnt/disk0/models/google/gemma-4-31B-it}:/models/gemma4:ro
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environment:
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MODEL_PATH: /models/gemma4
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AUTO_DETECT: "${AUTO_DETECT:-1}"
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HOST: "${HOST:-0.0.0.0}"
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# 默认给 4 张（Gemma-4-31B 的 TP4）；GEV 只需要 2 张，
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# entrypoint 按检测出的 TP 使用前 TP 张。
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CUDA_VISIBLE_DEVICES: "${GPUS:-15,14,13,12}"
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# 容器内端口固定 80，模型名固定 llm（AGENTS.md 5.2 / 5.5）。
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PORT: "80"
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SERVED_NAME: "${SERVED_NAME:-llm}"
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# 留空时由 entrypoint 根据 config.json 自动判断。
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# 需要手动覆盖时直接设置同名环境变量即可。
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TP: "${TP:-}"
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MAX_NUM_SEQS: "${MAX_NUM_SEQS:-}"
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GPU_MEM_UTIL: "${GPU_MEM_UTIL:-}"
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ENFORCE_EAGER: "${ENFORCE_EAGER:-}"
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MAX_MODEL_LEN: "${MAX_MODEL_LEN:-8192}"
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MAX_IMAGES: "${MAX_IMAGES:-4}"
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PYTHONUNBUFFERED: "1"
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EXTRA_ARGS: "${EXTRA_ARGS:-}"
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ulimits:
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memlock: -1
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stack: 67108864
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restart: unless-stopped
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