[Bug]: qwen3-coder 偶现 IndexError

[slipfre]

Your current environment

The output of `python collect_env.py`

==============================
        System Info
==============================
OS                           : Ubuntu 22.04.5 LTS (aarch64)
GCC version                  : (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
Clang version                : Could not collect
CMake version                : version 4.1.0
Libc version                 : glibc-2.35

==============================
       PyTorch Info
==============================
PyTorch version              : 2.7.1+cpu
Is debug build               : False
CUDA used to build PyTorch   : None
ROCM used to build PyTorch   : N/A

==============================
      Python Environment
==============================
Python version               : 3.11.13 (main, Jul 26 2025, 07:27:32) [GCC 11.4.0] (64-bit runtime)
Python platform              : Linux-5.10.0-153.56.0.134.oe2203sp2.aarch64-aarch64-with-glibc2.35

==============================
       CUDA / GPU Info
==============================
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 Info
==============================
Architecture:                       aarch64
CPU op-mode(s):                     64-bit
Byte Order:                         Little Endian
CPU(s):                             192
On-line CPU(s) list:                0-191
Vendor ID:                          HiSilicon
Model name:                         Kunpeng-920
Model:                              0
Thread(s) per core:                 1
Core(s) per cluster:                48
Socket(s):                          -
Cluster(s):                         4
Stepping:                           0x1
Frequency boost:                    disabled
CPU max MHz:                        2600.0000
CPU min MHz:                        200.0000
BogoMIPS:                           200.00
Flags:                              fp asimd evtstrm aes pmull sha1 sha2 crc32 atomics fphp asimdhp cpuid asimdrdm jscvt fcma dcpop asimddp asimdfhm ssbs
L1d cache:                          12 MiB (192 instances)
L1i cache:                          12 MiB (192 instances)
L2 cache:                           96 MiB (192 instances)
L3 cache:                           192 MiB (8 instances)
NUMA node(s):                       8
NUMA node0 CPU(s):                  0-23
NUMA node1 CPU(s):                  24-47
NUMA node2 CPU(s):                  48-71
NUMA node3 CPU(s):                  72-95
NUMA node4 CPU(s):                  96-119
NUMA node5 CPU(s):                  120-143
NUMA node6 CPU(s):                  144-167
NUMA node7 CPU(s):                  168-191
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 Retbleed:             Not affected
Vulnerability Spec rstack overflow: Not affected
Vulnerability Spec store bypass:    Mitigation; Speculative Store Bypass disabled via prctl
Vulnerability Spectre v1:           Mitigation; __user pointer sanitization
Vulnerability Spectre v2:           Not affected
Vulnerability Srbds:                Not affected
Vulnerability Tsx async abort:      Not affected

==============================
Versions of relevant libraries
==============================
[pip3] numpy==1.26.4
[pip3] pyzmq==27.1.0
[pip3] torch==2.7.1+cpu
[pip3] torch_npu==2.7.1.dev20250724
[pip3] torchvision==0.22.1
[pip3] transformers==4.56.1
[conda] Could not collect

==============================
         vLLM Info
==============================
ROCM Version                 : Could not collect
vLLM Version                 : 0.10.2
vLLM Build Flags:
  CUDA Archs: Not Set; ROCm: Disabled
GPU Topology:
  Could not collect

==============================
     Environment Variables
==============================
PYTORCH_NPU_ALLOC_CONF=max_split_size_mb:256
LD_LIBRARY_PATH=/usr/local/Ascend/nnal/atb/latest/atb/cxx_abi_1/lib:/usr/local/Ascend/nnal/atb/latest/atb/cxx_abi_1/examples:/usr/local/Ascend/nnal/atb/latest/atb/cxx_abi_1/tests/atbopstest:/usr/local/Ascend/ascend-toolkit/latest/tools/aml/lib64:/usr/local/Ascend/ascend-toolkit/latest/tools/aml/lib64/plugin:/usr/local/Ascend/ascend-toolkit/latest/lib64:/usr/local/Ascend/ascend-toolkit/latest/lib64/plugin/opskernel:/usr/local/Ascend/ascend-toolkit/latest/lib64/plugin/nnengine:/usr/local/Ascend/ascend-toolkit/latest/opp/built-in/op_impl/ai_core/tbe/op_tiling/lib/linux/aarch64:/usr/local/Ascend/nnal/atb/latest/atb/cxx_abi_0/lib:/usr/local/Ascend/nnal/atb/latest/atb/cxx_abi_0/examples:/usr/local/Ascend/nnal/atb/latest/atb/cxx_abi_0/tests/atbopstest:/usr/local/Ascend/ascend-toolkit/latest/tools/aml/lib64:/usr/local/Ascend/ascend-toolkit/latest/tools/aml/lib64/plugin:/usr/local/Ascend/ascend-toolkit/latest/lib64:/usr/local/Ascend/ascend-toolkit/latest/lib64/plugin/opskernel:/usr/local/Ascend/ascend-toolkit/latest/lib64/plugin/nnengine:/usr/local/Ascend/ascend-toolkit/latest/opp/built-in/op_impl/ai_core/tbe/op_tiling:/usr/local/Ascend/driver/lib64/common/:/usr/local/Ascend/driver/lib64/driver/:
TORCH_DEVICE_BACKEND_AUTOLOAD=1
PYTORCH_NVML_BASED_CUDA_CHECK=1
TORCHINDUCTOR_COMPILE_THREADS=1

🐛 Describe the bug

Start with:

vllm serve /models/Qwen3-Coder-30B-A3B-Instruct/ --served-model-name qwen3-coder-30b-a3b-instruct --port 40410 --max-model-len 128000 --enable-expert-parallel --tensor-parallel-size 2 --enable-auto-tool-choice  --tool-call-parser qwen3_coder

Http request:

request.txt

Sometimes, there will be a IndexError when the final output is a batch of tokens. I add some logs which start with "=====", and it shows the tool_parser.streamed_args_for_tool is always empty. Is that a problem?