[Bug]: Guided Decoding Broken in Streaming mode

[JC1DA]

Your current environment

The output of `python collect_env.py`

PyTorch version: 2.5.1+cu124
Is debug build: False
CUDA used to build PyTorch: 12.4
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: 3.11.10 (main, Oct  3 2024, 07:29:13) [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-6.8.0-1017-azure-x86_64-with-glibc2.35
Is CUDA available: True
CUDA runtime version: Could not collect
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: 
GPU 0: NVIDIA A100 80GB PCIe
GPU 1: NVIDIA A100 80GB PCIe

Nvidia driver version: 550.127.05
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:                        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 7V13 64-Core Processor
CPU family:                           25
Model:                                1
Thread(s) per core:                   1
Core(s) per socket:                   48
Socket(s):                            1
Stepping:                             1
BogoMIPS:                             4890.87
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 tsc_reliable nonstop_tsc cpuid extd_apicid aperfmperf pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 movbe popcnt aes xsave avx f16c rdrand hypervisor lahf_lm cmp_legacy cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw topoext perfctr_core vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves user_shstk clzero xsaveerptr rdpru arat umip vaes vpclmulqdq rdpid fsrm
Hypervisor vendor:                    Microsoft
Virtualization type:                  full
L1d cache:                            1.5 MiB (48 instances)
L1i cache:                            1.5 MiB (48 instances)
L2 cache:                             24 MiB (48 instances)
L3 cache:                             192 MiB (6 instances)
NUMA node(s):                         2
NUMA node0 CPU(s):                    0-23
NUMA node1 CPU(s):                    24-47
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:               Not affected
Vulnerability Spec rstack overflow:   Vulnerable: Safe RET, no microcode
Vulnerability Spec store bypass:      Vulnerable
Vulnerability Spectre v1:             Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2:             Mitigation; Retpolines; STIBP disabled; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected
Vulnerability Srbds:                  Not affected
Vulnerability Tsx async abort:        Not affected

Versions of relevant libraries:
[pip3] mypy-extensions==1.0.0
[pip3] numpy==1.26.4
[pip3] nvidia-cublas-cu12==12.4.5.8
[pip3] nvidia-cuda-cupti-cu12==12.4.127
[pip3] nvidia-cuda-nvrtc-cu12==12.4.127
[pip3] nvidia-cuda-runtime-cu12==12.4.127
[pip3] nvidia-cudnn-cu12==9.1.0.70
[pip3] nvidia-cufft-cu12==11.2.1.3
[pip3] nvidia-curand-cu12==10.3.5.147
[pip3] nvidia-cusolver-cu12==11.6.1.9
[pip3] nvidia-cusparse-cu12==12.3.1.170
[pip3] nvidia-ml-py==12.560.30
[pip3] nvidia-nccl-cu12==2.21.5
[pip3] nvidia-nvjitlink-cu12==12.4.127
[pip3] nvidia-nvtx-cu12==12.4.127
[pip3] pyzmq==26.2.0
[pip3] sentence-transformers==3.2.1
[pip3] torch==2.5.1
[pip3] torchaudio==2.5.1+cu121
[pip3] torchvision==0.20.1
[pip3] transformers==4.45.2
[pip3] transformers-stream-generator==0.0.5
[pip3] triton==3.1.0
[conda] numpy                     1.26.4                   pypi_0    pypi
[conda] nvidia-cublas-cu12        12.4.5.8                 pypi_0    pypi
[conda] nvidia-cuda-cupti-cu12    12.4.127                 pypi_0    pypi
[conda] nvidia-cuda-nvrtc-cu12    12.4.127                 pypi_0    pypi
[conda] nvidia-cuda-runtime-cu12  12.4.127                 pypi_0    pypi
[conda] nvidia-cudnn-cu12         9.1.0.70                 pypi_0    pypi
[conda] nvidia-cufft-cu12         11.2.1.3                 pypi_0    pypi
[conda] nvidia-curand-cu12        10.3.5.147               pypi_0    pypi
[conda] nvidia-cusolver-cu12      11.6.1.9                 pypi_0    pypi
[conda] nvidia-cusparse-cu12      12.3.1.170               pypi_0    pypi
[conda] nvidia-ml-py              12.560.30                pypi_0    pypi
[conda] nvidia-nccl-cu12          2.21.5                   pypi_0    pypi
[conda] nvidia-nvjitlink-cu12     12.4.127                 pypi_0    pypi
[conda] nvidia-nvtx-cu12          12.4.127                 pypi_0    pypi
[conda] pyzmq                     26.2.0                   pypi_0    pypi
[conda] sentence-transformers     3.2.1                    pypi_0    pypi
[conda] torch                     2.5.1                    pypi_0    pypi
[conda] torchaudio                2.5.1+cu121              pypi_0    pypi
[conda] torchvision               0.20.1                   pypi_0    pypi
[conda] transformers              4.45.2                   pypi_0    pypi
[conda] transformers-stream-generator 0.0.5                    pypi_0    pypi
[conda] triton                    3.1.0                    pypi_0    pypi
ROCM Version: Could not collect
Neuron SDK Version: N/A
vLLM Version: 0.1.dev3367+g3b980c2 (git sha: 3b980c2
vLLM Build Flags:
CUDA Archs: Not Set; ROCm: Disabled; Neuron: Disabled
GPU Topology:
GPU0	GPU1	NIC0	CPU Affinity	NUMA Affinity	GPU NUMA ID
GPU0	 X 	NV12	NODE	0-23	0		N/A
GPU1	NV12	 X 	SYS	24-47	1		N/A
NIC0	NODE	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_0

Model Input Dumps

No response

🐛 Describe the bug

Guided decoding broken in streaming mode after this commit 04cef2c
Previous commits are working fine. Non-streaming mode works fine as well.

Dataset to test: https://raw.githubusercontent.com/JC1DA/SharedData/refs/heads/main/gsm8k_luca_input_prompts/dataset.json

Test script:

import json
from openai import OpenAI
from concurrent.futures import ThreadPoolExecutor
from tqdm import tqdm

json_schema = """
{
  "$schema": "http://json-schema.org/draft-07/schema#",
  "type": "object",
  "properties": {
    "thoughts": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "action": {
            "type": "string",
            "description": "Description of the step in the thought process"
          },
          "calculation": {
            "type": "string",
            "description": "Calculation performed in this step"
          },
          "result": {
            "type": "integer",
            "description": "Result of the calculation"
          }
        },
        "required": ["action", "calculation", "result"],
        "additionalProperties": false
      }
    },
    "answer": {
      "type": "integer",
      "description": "Final answer calculated from the thoughts"
    }
  },
  "required": ["thoughts", "answer"],
  "additionalProperties": false
}
""".strip()

model = "Qwen/Qwen2.5-7B-Instruct-GPTQ-Int4"

client = OpenAI(
    base_url="http://localhost:5006/v1",
    api_key="NOKEY",
)

data = json.load(open("dataset.json", "r", encoding="utf-8"))

def get_output(prompt):
    stream = client.chat.completions.create(
        model=model,
        messages=[
            {
                "role": "system",
                "content": f"""
You are a helpful assistant that can answer questions from the user and provide useful information.
Generate your answer based on the JSON schema below.
{json_schema}
""".strip(),
            },
            {
                "role": "user",
                "content": prompt,
            },
        ],
        max_tokens=1024,
        temperature=0.0,
        top_p=1.0,
        stream=True,
        extra_body={"guided_json": json.loads(json_schema), "guided_decoding_backend": "outlines"},
    )

    _data = ""
    for chunk in stream:
        if chunk.choices[0].delta.content is not None:
            _data += chunk.choices[0].delta.content

    return _data

futures = []
failed = 0
with ThreadPoolExecutor(max_workers=8) as executor:
    futures = [executor.submit(get_output, prompt) for prompt in data]

    for f in tqdm(futures):
        res = f.result()
        try:
          res = json.loads(res)
          # print(res)
        except:
            failed += 1

print(failed, "/", len(futures))

Result:
Commit 6e056bc: failed 1 / 1318
Commit 04cef2c: failed 263 / 1318

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