[Bug] gradio界面对话报错

[tuncha]

Checklist

• [X] 1. I have searched related issues but cannot get the expected help.
• [ ] 2. The bug has not been fixed in the latest version.
• [ ] 3. Please note that if the bug-related issue you submitted lacks corresponding environment info and a minimal reproducible demo, it will be challenging for us to reproduce and resolve the issue, reducing the likelihood of receiving feedback.

Describe the bug

您好，我正在使用intern2VL-40B进行服务器部署gradio服务测试，但是我在测试中发现如果我进行了一轮上传图像对话后，想使用Reset重置界面上传新图像，此时报错RuntimeError: Current event loop is different from the one bound to loop task! 同样的，这个问题也会出现在对一张图像进行多轮对话的情况下，这是因为历史信息堆积导致错误还是操作有问题？

Reproduction

CUDA_VISIBLE_DEVICES=1,2 lmdeploy serve gradio /OpenGVLab/InternVL2-40B --model-name InternVL2-40B --backend turbomind --server-port 23333 --tp 2 --chat-template /data/personal/fengtianyi/code/MLLM/InternVL-main/chat.json

Environment

sys.platform: linux
Python: 3.9.19 | packaged by conda-forge | (main, Mar 20 2024, 12:50:21) [GCC 12.3.0]
CUDA available: True
MUSA available: False
numpy_random_seed: 2147483648
GPU 0,1,2,3,4,5,6,7: NVIDIA A800 80GB PCIe
CUDA_HOME: /usr/local/cuda-11.7
NVCC: Cuda compilation tools, release 11.7, V11.7.64
GCC: gcc (Ubuntu 9.4.0-1ubuntu1~20.04.2) 9.4.0
PyTorch: 2.0.1
PyTorch compiling details: PyTorch built with:
  - GCC 9.3
  - C++ Version: 201703
  - Intel(R) oneAPI Math Kernel Library Version 2022.1-Product Build 20220311 for Intel(R) 64 architecture applications
  - Intel(R) MKL-DNN v2.7.3 (Git Hash 6dbeffbae1f23cbbeae17adb7b5b13f1f37c080e)
  - OpenMP 201511 (a.k.a. OpenMP 4.5)
  - LAPACK is enabled (usually provided by MKL)
  - NNPACK is enabled
  - CPU capability usage: AVX2
  - CUDA Runtime 11.7
  - NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_61,code=sm_61;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86;-gencode;arch=compute_37,code=compute_37
  - CuDNN 8.5
  - Magma 2.6.1
  - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.7, CUDNN_VERSION=8.5.0, CXX_COMPILER=/opt/rh/devtoolset-9/root/usr/bin/c++, CXX_FLAGS= -D_GLIBCXX_USE_CXX11_ABI=0 -fabi-version=11 -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -DNDEBUG -DUSE_KINETO -DLIBKINETO_NOROCTRACER -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -O2 -fPIC -Wall -Wextra -Werror=return-type -Werror=non-virtual-dtor -Werror=bool-operation -Wnarrowing -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wunused-local-typedefs -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_DISABLE_GPU_ASSERTS=ON, TORCH_VERSION=2.0.1, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF, 

TorchVision: 0.15.2
LMDeploy: 0.5.3+
transformers: 4.37.2
gradio: 4.41.0
fastapi: 0.112.0
pydantic: 2.8.2
triton: 2.3.1
NVIDIA Topology: 
        GPU0    GPU1    GPU2    GPU3    GPU4    GPU5    GPU6    GPU7    NIC0    CPU Affinity    NUMA Affinity   GPU NUMA ID
GPU0     X      NV8     PXB     PXB     PXB     PXB     PXB     PXB     SYS     0-31,64-95      0               N/A
GPU1    NV8      X      PXB     PXB     PXB     PXB     PXB     PXB     SYS     0-31,64-95      0               N/A
GPU2    PXB     PXB      X      PXB     PXB     PXB     PXB     NV8     SYS     0-31,64-95      0               N/A
GPU3    PXB     PXB     PXB      X      NV8     PXB     PXB     PXB     SYS     0-31,64-95      0               N/A
GPU4    PXB     PXB     PXB     NV8      X      PXB     PXB     PXB     SYS     0-31,64-95      0               N/A
GPU5    PXB     PXB     PXB     PXB     PXB      X      NV8     PXB     SYS     0-31,64-95      0               N/A
GPU6    PXB     PXB     PXB     PXB     PXB     NV8      X      PXB     SYS     0-31,64-95      0               N/A
GPU7    PXB     PXB     NV8     PXB     PXB     PXB     PXB      X      SYS     0-31,64-95      0               N/A
NIC0    SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS      X 

Legend:

  X    = Self
  SYS  = Connection traversing PCIe as well as the SMP interconnect between NUMA nodes (e.g., QPI/UPI)
  NODE = Connection traversing PCIe as well as the interconnect between PCIe Host Bridges within a NUMA node
  PHB  = Connection traversing PCIe as well as a PCIe Host Bridge (typically the CPU)
  PXB  = Connection traversing multiple PCIe bridges (without traversing the PCIe Host Bridge)
  PIX  = Connection traversing at most a single PCIe bridge
  NV#  = Connection traversing a bonded set of # NVLinks

NIC Legend:

  NIC0: mlx5_bond_0

Error traceback

No response

[G-z-w]

This may be a problem with the lmdeploy server. You can try upgrading your lmdeploy. If the problem persists, please refer to this issue. link