[Bug]: TimeoutError: MQLLMEngine didn't reply within 10000ms

Your current environment

The output of `python collect_env.py`

```text Collecting environment information... INFO 09-26 04:45:26 importing.py:10] Triton not installed; certain GPU-related functions will not be available. PyTorch version: 2.4.0+cpu Is debug build: False CUDA used to build PyTorch: None ROCM used to build PyTorch: N/A OS: Ubuntu 22.04.5 LTS (x86_64) GCC version: (Ubuntu 12.3.0-1ubuntu1~22.04) 12.3.0 Clang version: Could not collect CMake version: version 3.30.3 Libc version: glibc-2.35 Python version: 3.10.12 (main, Sep 11 2024, 15:47:36) [GCC 11.4.0] (64-bit runtime) Python platform: Linux-6.8.0-1016-aws-x86_64-with-glibc2.35 Is CUDA available: False CUDA runtime version: No CUDA CUDA_MODULE_LOADING set to: N/A GPU models and configuration: No CUDA Nvidia driver version: No CUDA cuDNN version: No CUDA HIP runtime version: N/A MIOpen runtime version: N/A Is XNNPACK available: True CPU: Architecture: x86_64 CPU op-mode(s): 32-bit, 64-bit Address sizes: 48 bits physical, 48 bits virtual Byte Order: Little Endian CPU(s): 48 On-line CPU(s) list: 0-47 Vendor ID: AuthenticAMD Model name: AMD EPYC 7R32 CPU family: 23 Model: 49 Thread(s) per core: 2 Core(s) per socket: 24 Socket(s): 1 Stepping: 0 BogoMIPS: 5599.99 Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf tsc_known_freq pni pclmulqdq ssse3 fma cx16 sse4_1 sse4_2 movbe popcnt aes xsave avx f16c rdrand hypervisor lahf_lm cmp_legacy cr8_legacy abm sse4a misalignsse 3dnowprefetch topoext ssbd ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 clzero xsaveerptr rdpru wbnoinvd arat npt nrip_save rdpid Hypervisor vendor: KVM Virtualization type: full L1d cache: 768 KiB (24 instances) L1i cache: 768 KiB (24 instances) L2 cache: 12 MiB (24 instances) L3 cache: 96 MiB (6 instances) NUMA node(s): 1 NUMA node0 CPU(s): 0-47 Vulnerability Gather data sampling: Not affected Vulnerability Itlb multihit: Not affected Vulnerability L1tf: Not affected Vulnerability Mds: Not affected Vulnerability Meltdown: Not affected Vulnerability Mmio stale data: Not affected Vulnerability Reg file data sampling: Not affected Vulnerability Retbleed: Mitigation; untrained return thunk; SMT enabled with STIBP protection Vulnerability Spec rstack overflow: Vulnerable: Safe RET, no microcode Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization Vulnerability Spectre v2: Mitigation; Retpolines; IBPB conditional; STIBP always-on; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected Vulnerability Srbds: Not affected Vulnerability Tsx async abort: Not affected Versions of relevant libraries: [pip3] intel_extension_for_pytorch==2.4.0+gitfbaa4bc [pip3] numpy==1.26.4 [pip3] pyzmq==26.2.0 [pip3] torch==2.4.0+cpu [pip3] torchvision==0.19.0+cpu [pip3] transformers==4.44.2 [conda] Could not collect ROCM Version: Could not collect Neuron SDK Version: N/A vLLM Version: 0.6.1.post2@18ae428a0d8792d160d811a9cd5bb004d68ea8bd vLLM Build Flags: CUDA Archs: Not Set; ROCm: Disabled; Neuron: Disabled GPU Topology: Could not collect ```

Model Input Dumps

No response

🐛 Describe the bug

# docker-compose.yml
services:
  llm-vllm-cpu:
    image: vllm/vllm-openai:cpu
    container_name: llm-vllm-cpu
    restart: unless-stopped
    environment:
      HUGGING_FACE_HUB_TOKEN: <my-token>
    ports:
      - "8007:8007"
    deploy:
      resources:
        limits:
          cpus: "28"
          memory: 24GB
    ipc: host
    volumes:
      - ~/.cache/huggingface:/root/.cache/huggingface
    command: >
      --host 0.0.0.0
      --port 8007
      --api-key <my-api-key>
      --max-model-len 2048
      --served-model-name llama3.2
      --seed 42
      --device cpu
      --dtype bfloat16
      --disable-log-requests
      --model meta-llama/Llama-3.2-1B-Instruct

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vllm-project / vllm