Unified Llama 4 Scout/Maverick BI-V150 deployment bundle

entrypoint.sh

@@ -0,0 +1,71 @@
+#!/usr/bin/env bash
+#
+# Llama 4 Scout / Maverick 统一容器入口：
+#   1. 幂等应用 CoreX vLLM 的 Llama 4 补丁（Scout 只用 chunked attention，
+#      Maverick 额外使用 FP8 补丁；补丁脚本会按 marker 自动跳过已应用项）
+#   2. 检查模型目录
+#   3. exec vLLM（信号可直接传给 vLLM）
+#
+set -euo pipefail
+
+PATCH_SCRIPT="${LLAMA4_PATCH_SCRIPT:-/opt/llama4/apply_patch.py}"
+VLLM_BIN="${VLLM_BIN:-vllm}"
+
+python3 "${PATCH_SCRIPT}"
+
+MODEL_PATH="${MODEL_PATH:-/models/llama4}"
+SERVED_NAME="${SERVED_NAME:-llama4}"
+HOST="${HOST:-0.0.0.0}"
+PORT="${PORT:-8091}"
+TP="${TP:-8}"
+PP="${PP:-1}"
+MAX_MODEL_LEN="${MAX_MODEL_LEN:-4096}"
+MAX_NUM_SEQS="${MAX_NUM_SEQS:-1}"
+GPU_MEM_UTIL="${GPU_MEM_UTIL:-0.90}"
+ENFORCE_EAGER="${ENFORCE_EAGER:-1}"
+EXTRA_ARGS="${EXTRA_ARGS:-}"
+
+if [[ ! -f "${MODEL_PATH}/config.json" ]]; then
+  echo "ERROR: 模型目录不完整：${MODEL_PATH}/config.json 不存在" >&2
+  echo "请确认已挂载模型，例如：" >&2
+  echo "  -v /mnt/disk0/models/LLM-Research/Llama-4-Scout-17B-16E-Instruct:/models/llama4:ro" >&2
+  echo "  -v /mnt/disk0/models/LLM-Research/Llama-4-Maverick-17B-128E-Instruct-FP8:/models/llama4:ro" >&2
+  exit 1
+fi
+
+PP_ARGS=()
+if (( PP > 1 )); then
+  PP_ARGS=(--pipeline-parallel-size "${PP}")
+fi
+
+EAGER_ARGS=()
+if [[ "${ENFORCE_EAGER}" == "1" ]]; then
+  EAGER_ARGS=(--enforce-eager)
+fi
+
+echo "============================================================"
+echo "Llama 4 (BI-V150 unified image)"
+echo "  model      : ${MODEL_PATH}"
+echo "  served name: ${SERVED_NAME}"
+echo "  listen     : ${HOST}:${PORT}"
+echo "  TP / PP    : ${TP} / ${PP}  (total $((TP * PP)) GPUs)"
+echo "  max len    : ${MAX_MODEL_LEN}"
+echo "  max seqs   : ${MAX_NUM_SEQS}"
+echo "  gpu util   : ${GPU_MEM_UTIL}"
+echo "  eager      : ${ENFORCE_EAGER}"
+echo "  visible    : ${CUDA_VISIBLE_DEVICES:-all}"
+echo "  extra      : ${EXTRA_ARGS}"
+echo "============================================================"
+
+# shellcheck disable=SC2086
+exec "${VLLM_BIN}" serve "${MODEL_PATH}" \
+  --host "${HOST}" \
+  --port "${PORT}" \
+  --served-model-name "${SERVED_NAME}" \
+  --tensor-parallel-size "${TP}" \
+  "${PP_ARGS[@]}" \
+  --max-model-len "${MAX_MODEL_LEN}" \
+  --max-num-seqs "${MAX_NUM_SEQS}" \
+  --gpu-memory-utilization "${GPU_MEM_UTIL}" \
+  "${EAGER_ARGS[@]}" \
+  ${EXTRA_ARGS}