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| # vLLM 服务启动脚本 —— Qwen3-VL-8B-Instruct-FP8,OpenAI 兼容 API @ 127.0.0.1:8001 | |
| # (端口可用 EGODATA_VLLM_PORT 覆盖;deploy.py 避让端口占用时会设置它) | |
| # | |
| # 踩坑记录(2026-08-14 实测,勿删): | |
| # - VLLM_USE_DEEP_GEMM=0:RTX 5090(SM120)缺 DeepGEMM scale-factor 布局支持, | |
| # 否则加载 FP8 权重报 "Unknown SF transformation" 断言 | |
| # - VLLM_USE_FLASHINFER_SAMPLER=0:跳过 flashinfer 的 JIT CUDA 编译 | |
| # (依赖 ninja + 项目路径带空格会破坏 ninja 依赖解析) | |
| # - 必须 cd 到无空格目录启动(项目目录名 "processor" 含空格) | |
| # - venv bin 必须进 PATH(ninja 等工具在子进程里按 PATH 查找) | |
| # - 本地目录加载时 model 名 = 完整路径(客户端请求要用路径名) | |
| # - 视频输入用 base64 data URL 发送,不用 file:// 本地路径 | |
| # - 应用默认用 MP4 + media_io_kwargs.video.fps；如需兼容旧版可设置 | |
| # EGODATA_VLLM_MEDIA_MODE=frames 回退到客户端抽帧 | |
| set -euo pipefail | |
| SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" | |
| PROJECT_ROOT="$(cd "$SCRIPT_DIR/.." && pwd)" | |
| VENV="$PROJECT_ROOT/.venv-llm" | |
| MODEL="${EGODATA_VLLM_MODEL:-$PROJECT_ROOT/models/llm/Qwen3-VL-8B-Instruct-FP8}" | |
| if [[ ! -x "$VENV/bin/vllm" ]]; then | |
| echo "vLLM 环境不存在:$VENV(先安装 vllm)" >&2 | |
| exit 1 | |
| fi | |
| if [[ ! -f "$MODEL/config.json" ]]; then | |
| echo "模型不存在:$MODEL" >&2 | |
| exit 1 | |
| fi | |
| # Leave GPU headroom for the hand-processing Worker to load its detector. | |
| cd /tmp | |
| exec env PATH="$VENV/bin:$PATH" \ | |
| VLLM_USE_DEEP_GEMM=0 \ | |
| VLLM_USE_FLASHINFER_SAMPLER=0 \ | |
| "$VENV/bin/vllm" serve "$MODEL" \ | |
| --host 127.0.0.1 --port "${EGODATA_VLLM_PORT:-8001}" \ | |
| --gpu-memory-utilization 0.70 \ | |
| --max-model-len 16384 | |