[Bug]: OpenAI batch file format pydantic validation error

[ArsalShakil]

Your current environment

Collecting environment information...
PyTorch version: 2.3.0+cu121
Is debug build: False
CUDA used to build PyTorch: 12.1
ROCM used to build PyTorch: N/A

OS: Ubuntu 22.04.4 LTS (x86_64)
GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
Clang version: Could not collect
CMake version: version 3.30.0
Libc version: glibc-2.35

Python version: 3.10.14 (main, May  6 2024, 19:42:50) [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-5.15.153.1-microsoft-standard-WSL2-x86_64-with-glibc2.35
Is CUDA available: True
CUDA runtime version: 12.1.105
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: GPU 0: NVIDIA GeForce RTX 4080 Laptop GPU
Nvidia driver version: 556.12
cuDNN version: Could not collect
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:                      39 bits physical, 48 bits virtual
Byte Order:                         Little Endian
CPU(s):                             32
On-line CPU(s) list:                0-31
Vendor ID:                          GenuineIntel
Model name:                         13th Gen Intel(R) Core(TM) i9-13900HX
CPU family:                         6
Model:                              183
Thread(s) per core:                 2
Core(s) per socket:                 16
Socket(s):                          1
Stepping:                           1
BogoMIPS:                           4838.39
Flags:                              fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ss ht syscall nx pdpe1gb rdtscp lm constant_tsc rep_good nopl xtopology tsc_reliable nonstop_tsc cpuid pni pclmulqdq vmx ssse3 fma cx16 sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand hypervisor lahf_lm abm 3dnowprefetch ssbd ibrs ibpb stibp ibrs_enhanced tpr_shadow vnmi ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves avx_vnni umip waitpkg gfni vaes vpclmulqdq rdpid movdiri movdir64b fsrm md_clear serialize flush_l1d arch_capabilities
Virtualization:                     VT-x
Hypervisor vendor:                  Microsoft
Virtualization type:                full
L1d cache:                          768 KiB (16 instances)
L1i cache:                          512 KiB (16 instances)
L2 cache:                           32 MiB (16 instances)
L3 cache:                           36 MiB (1 instance)
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:             Mitigation; Enhanced IBRS
Vulnerability Spec rstack overflow: Not affected
Vulnerability Spec store bypass:    Mitigation; Speculative Store Bypass disabled via prctl and seccomp
Vulnerability Spectre v1:           Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2:           Mitigation; Enhanced IBRS, IBPB conditional, RSB filling, PBRSB-eIBRS SW sequence
Vulnerability Srbds:                Not affected
Vulnerability Tsx async abort:      Not affected

Versions of relevant libraries:
[pip3] flashinfer==0.0.8+cu121torch2.3
[pip3] numpy==1.26.4
[pip3] nvidia-nccl-cu12==2.20.5
[pip3] torch==2.3.0
[pip3] torchvision==0.18.0
[pip3] transformers==4.42.3
[pip3] triton==2.3.0
[conda] flashinfer                0.0.8+cu121torch2.3          pypi_0    pypi
[conda] numpy                     1.26.4                   pypi_0    pypi
[conda] nvidia-nccl-cu12          2.20.5                   pypi_0    pypi
[conda] torch                     2.3.0                    pypi_0    pypi
[conda] torchvision               0.18.0                   pypi_0    pypi
[conda] transformers              4.42.3                   pypi_0    pypi
[conda] triton                    2.3.0                    pypi_0    pypi
ROCM Version: Could not collect
Neuron SDK Version: N/A
vLLM Version: 0.5.1
vLLM Build Flags:
CUDA Archs: Not Set; ROCm: Disabled; Neuron: Disabled
GPU Topology:
GPU0    CPU Affinity    NUMA Affinity   GPU NUMA ID
GPU0     X                              N/A

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

🐛 Describe the bug

Running this command to do batch inference through API, returns the following error. The input.jsonl is as per required format.

python -m vllm.entrypoints.openai.run_batch -i input.jsonl -o results.jsonl --model Granther/Gemma-2-9B-Instruct-4Bit-GPTQ --max_model_len 3000

Error Traceback:

[rank0]: Traceback (most recent call last):
[rank0]: File "/home/arsal/anaconda3/envs/vllm/lib/python3.10/runpy.py", line 196, in _run_module_as_main
[rank0]: return _run_code(code, main_globals, None,
[rank0]: File "/home/arsal/anaconda3/envs/vllm/lib/python3.10/runpy.py", line 86, in _run_code
[rank0]: exec(code, run_globals)
[rank0]: File "/home/arsal/anaconda3/envs/vllm/lib/python3.10/site-packages/vllm/entrypoints/openai/run_batch.py", line 146, in
[rank0]: asyncio.run(main(args))
[rank0]: File "/home/arsal/anaconda3/envs/vllm/lib/python3.10/asyncio/runners.py", line 44, in run
[rank0]: return loop.run_until_complete(main)
[rank0]: File "/home/arsal/anaconda3/envs/vllm/lib/python3.10/asyncio/base_events.py", line 649, in run_until_complete
[rank0]: return future.result()
[rank0]: File "/home/arsal/anaconda3/envs/vllm/lib/python3.10/site-packages/vllm/entrypoints/openai/run_batch.py", line 130, in main
[rank0]: responses = await asyncio.gather(*response_futures)
[rank0]: File "/home/arsal/anaconda3/envs/vllm/lib/python3.10/site-packages/vllm/entrypoints/openai/run_batch.py", line 93, in run_request
[rank0]: response=BatchResponseData(
[rank0]: File "/home/arsal/anaconda3/envs/vllm/lib/python3.10/site-packages/pydantic/main.py", line 193, in init
[rank0]: self.pydantic_validator.validate_python(data, self_instance=self)
[rank0]: pydantic_core._pydantic_core.ValidationError: 1 validation error for BatchResponseData
[rank0]: body
[rank0]: Field required [type=missing, input_value={'status_code': 400, 'req...5c4a7799ad445a114ebff4'}, input_type=dict]
[rank0]: For further information visit https://errors.pydantic.dev/2.8/v/missing

[zifeitong]

The "body" field should be Optional (e.g. when there are errors), let me send a fix.