Your current environment

Your current environment

Collecting environment information...

    System Info

============================== OS : Ubuntu 22.04.5 LTS (x86_64) GCC version : (Ubuntu 11.4.0-1ubuntu1~22.04.3) 11.4.0 Clang version : Could not collect CMake version : Could not collect Libc version : glibc-2.35

============================== PyTorch Info

PyTorch version : 2.10.0+cu129 Is debug build : False CUDA used to build PyTorch : 12.9 ROCM used to build PyTorch : N/A

============================== Python Environment

Python version : 3.12.13 (main, Mar 4 2026, 09:23:07) [GCC 11.4.0] (64-bit runtime) Python platform : Linux-6.14.0-35-generic-x86_64-with-glibc2.35

============================== CUDA / GPU Info

Is CUDA available : True CUDA runtime version : 12.9.86 CUDA_MODULE_LOADING set to : GPU models and configuration : GPU 0: NVIDIA H200 GPU 1: NVIDIA H200 GPU 2: NVIDIA H200 GPU 3: NVIDIA H200 GPU 4: NVIDIA H200 GPU 5: NVIDIA H200 GPU 6: NVIDIA H200 GPU 7: NVIDIA H200

Nvidia driver version : 570.172.08 cuDNN version : Could not collect HIP runtime version : N/A MIOpen runtime version : N/A Is XNNPACK available : True

============================== CPU Info

Architecture: x86_64 CPU op-mode(s): 32-bit, 64-bit Address sizes: 46 bits physical, 57 bits virtual Byte Order: Little Endian CPU(s): 192 On-line CPU(s) list: 0-191 Vendor ID: GenuineIntel Model name: INTEL(R) XEON(R) PLATINUM 8558 CPU family: 6 Model: 207 Thread(s) per core: 2 Core(s) per socket: 48 Socket(s): 2 Stepping: 2 CPU max MHz: 4000.0000 CPU min MHz: 800.0000 BogoMIPS: 4200.00 Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf tsc_known_freq pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l3 cat_l2 cdp_l3 intel_ppin cdp_l2 ssbd mba ibrs ibpb stibp ibrs_enhanced tpr_shadow flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb intel_pt avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local split_lock_detect user_shstk avx_vnni avx512_bf16 wbnoinvd dtherm ida arat pln pts hwp hwp_act_window hwp_epp hwp_pkg_req vnmi avx512vbmi umip pku ospke waitpkg avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg avx512_vpopcntdq la57 rdpid bus_lock_detect cldemote movdiri movdir64b enqcmd fsrm md_clear serialize tsxldtrk pconfig arch_lbr ibt amx_bf16 avx512_fp16 amx_tile amx_int8 flush_l1d arch_capabilities Virtualization: VT-x L1d cache: 4.5 MiB (96 instances) L1i cache: 3 MiB (96 instances) L2 cache: 192 MiB (96 instances) L3 cache: 520 MiB (2 instances) NUMA node(s): 4 NUMA node0 CPU(s): 0-23,96-119 NUMA node1 CPU(s): 24-47,120-143 NUMA node2 CPU(s): 48-71,144-167 NUMA node3 CPU(s): 72-95,168-191 Vulnerability Gather data sampling: Not affected Vulnerability Ghostwrite: Not affected Vulnerability Indirect target selection: 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: Not affected 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; Enhanced / Automatic IBRS; IBPB conditional; PBRSB-eIBRS SW sequence; BHI BHI_DIS_S Vulnerability Srbds: Not affected Vulnerability Tsa: Not affected Vulnerability Tsx async abort: Not affected Vulnerability Vmscape: Mitigation; IBPB before exit to userspace

============================== Versions of relevant libraries

[pip3] flashinfer-python==0.6.6 [pip3] numpy==2.2.6 [pip3] nvidia-cublas-cu12==12.9.1.4 [pip3] nvidia-cuda-cupti-cu12==12.9.79 [pip3] nvidia-cuda-nvrtc-cu12==12.9.86 [pip3] nvidia-cuda-runtime-cu12==12.9.79 [pip3] nvidia-cudnn-cu12==9.10.2.21 [pip3] nvidia-cudnn-frontend==1.18.0 [pip3] nvidia-cufft-cu12==11.4.1.4 [pip3] nvidia-cufile-cu12==1.14.1.1 [pip3] nvidia-curand-cu12==10.3.10.19 [pip3] nvidia-cusolver-cu12==11.7.5.82 [pip3] nvidia-cusparse-cu12==12.5.10.65 [pip3] nvidia-cusparselt-cu12==0.7.1 [pip3] nvidia-cutlass-dsl==4.4.2 [pip3] nvidia-cutlass-dsl-libs-base==4.4.2 [pip3] nvidia-ml-py==13.595.45 [pip3] nvidia-nccl-cu12==2.27.5 [pip3] nvidia-nvjitlink-cu12==12.9.86 [pip3] nvidia-nvshmem-cu12==3.4.5 [pip3] nvidia-nvtx-cu12==12.9.79 [pip3] pyzmq==27.1.0 [pip3] torch==2.10.0+cu129 [pip3] torch_c_dlpack_ext==0.1.5 [pip3] torchaudio==2.10.0+cu129 [pip3] torchvision==0.25.0+cu129 [pip3] transformers==5.4.0 [pip3] triton==3.6.0 [conda] Could not collect

============================== vLLM Info

ROCM Version : Could not collect vLLM Version : 0.19.1.dev1+g43a9b1afb (git sha: 43a9b1afb) vLLM Build Flags: CUDA Archs: 7.0 7.5 8.0 8.9 9.0 10.0 12.0; ROCm: Disabled GPU Topology: GPU0 GPU1 GPU2 GPU3 GPU4 GPU5 GPU6 GPU7 NIC0 NIC1 NIC2 NIC3 NIC4 NIC5 NIC6 NIC7 CPU Affinity NUMA Affinity GPU NUMA ID GPU0 X NV18 NV18 NV18 NV18 NV18 NV18 NV18 PIX NODE SYS SYS SYS SYS SYS SYS 0-23,96-119 0 N/A GPU1 NV18 X NV18 NV18 NV18 NV18 NV18 NV18 NODE PIX SYS SYS SYS SYS SYS SYS 0-23,96-119 0 N/A GPU2 NV18 NV18 X NV18 NV18 NV18 NV18 NV18 SYS SYS PIX NODE SYS SYS SYS SYS 24-47,120-143 1 N/A GPU3 NV18 NV18 NV18 X NV18 NV18 NV18 NV18 SYS SYS NODE PIX SYS SYS SYS SYS 24-47,120-143 1 N/A GPU4 NV18 NV18 NV18 NV18 X NV18 NV18 NV18 SYS SYS SYS SYS PIX NODE SYS SYS 48-71,144-167 2 N/A GPU5 NV18 NV18 NV18 NV18 NV18 X NV18 NV18 SYS SYS SYS SYS NODE PIX SYS SYS 48-71,144-167 2 N/A GPU6 NV18 NV18 NV18 NV18 NV18 NV18 X NV18 SYS SYS SYS SYS SYS SYS PIX NODE 72-95,168-191 3 N/A GPU7 NV18 NV18 NV18 NV18 NV18 NV18 NV18 X SYS SYS SYS SYS SYS SYS NODE PIX 72-95,168-191 3 N/A NIC0 PIX NODE SYS SYS SYS SYS SYS SYS X NODE SYS SYS SYS SYS SYS SYS NIC1 NODE PIX SYS SYS SYS SYS SYS SYS NODE X SYS SYS SYS SYS SYS SYS NIC2 SYS SYS PIX NODE SYS SYS SYS SYS SYS SYS X NODE SYS SYS SYS SYS NIC3 SYS SYS NODE PIX SYS SYS SYS SYS SYS SYS NODE X SYS SYS SYS SYS NIC4 SYS SYS SYS SYS PIX NODE SYS SYS SYS SYS SYS SYS X NODE SYS SYS NIC5 SYS SYS SYS SYS NODE PIX SYS SYS SYS SYS SYS SYS NODE X SYS SYS NIC6 SYS SYS SYS SYS SYS SYS PIX NODE SYS SYS SYS SYS SYS SYS X NODE NIC7 SYS SYS SYS SYS SYS SYS NODE PIX SYS SYS SYS SYS SYS SYS NODE 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 NIC1: mlx5_1 NIC2: mlx5_2 NIC3: mlx5_3 NIC4: mlx5_4 NIC5: mlx5_5 NIC6: mlx5_6 NIC7: mlx5_7

============================== Environment Variables

NVIDIA_VISIBLE_DEVICES=GPU-d2efa8a4-009d-effa-0bac-5dfbded376c0,GPU-2dde0d9c-c9f0-24d9-2a37-9dbd3bcf810f,GPU-70a6c6c7-1e47-a9c0-6a91-ff0bad2e0711,GPU-7c70fab2-fd2e-a5a5-d122-aafce9948a0c,GPU-417417a6-181f-77b4-e765-a0e8384ea784,GPU-cf1494d0-c5d0-f05a-f1ff-4071e5ee051f,GPU-f1060b4c-bb03-2bcd-5631-5118b1e97d16,GPU-e6d51986-a153-c8c6-e900-5c02ae0a266c NVIDIA_REQUIRE_CUDA=cuda>=12.9 brand=unknown,driver>=535,driver<536 brand=grid,driver>=535,driver<536 brand=tesla,driver>=535,driver<536 brand=nvidia,driver>=535,driver<536 brand=quadro,driver>=535,driver<536 brand=quadrortx,driver>=535,driver<536 brand=nvidiartx,driver>=535,driver<536 brand=vapps,driver>=535,driver<536 brand=vpc,driver>=535,driver<536 brand=vcs,driver>=535,driver<536 brand=vws,driver>=535,driver<536 brand=cloudgaming,driver>=535,driver<536 brand=unknown,driver>=550,driver<551 brand=grid,driver>=550,driver<551 brand=tesla,driver>=550,driver<551 brand=nvidia,driver>=550,driver<551 brand=quadro,driver>=550,driver<551 brand=quadrortx,driver>=550,driver<551 brand=nvidiartx,driver>=550,driver<551 brand=vapps,driver>=550,driver<551 brand=vpc,driver>=550,driver<551 brand=vcs,driver>=550,driver<551 brand=vws,driver>=550,driver<551 brand=cloudgaming,driver>=550,driver<551 brand=unknown,driver>=560,driver<561 brand=grid,driver>=560,driver<561 brand=tesla,driver>=560,driver<561 brand=nvidia,driver>=560,driver<561 brand=quadro,driver>=560,driver<561 brand=quadrortx,driver>=560,driver<561 brand=nvidiartx,driver>=560,driver<561 brand=vapps,driver>=560,driver<561 brand=vpc,driver>=560,driver<561 brand=vcs,driver>=560,driver<561 brand=vws,driver>=560,driver<561 brand=cloudgaming,driver>=560,driver<561 brand=unknown,driver>=565,driver<566 brand=grid,driver>=565,driver<566 brand=tesla,driver>=565,driver<566 brand=nvidia,driver>=565,driver<566 brand=quadro,driver>=565,driver<566 brand=quadrortx,driver>=565,driver<566 brand=nvidiartx,driver>=565,driver<566 brand=vapps,driver>=565,driver<566 brand=vpc,driver>=565,driver<566 brand=vcs,driver>=565,driver<566 brand=vws,driver>=565,driver<566 brand=cloudgaming,driver>=565,driver<566 brand=unknown,driver>=570,driver<571 brand=grid,driver>=570,driver<571 brand=tesla,driver>=570,driver<571 brand=nvidia,driver>=570,driver<571 brand=quadro,driver>=570,driver<571 brand=quadrortx,driver>=570,driver<571 brand=nvidiartx,driver>=570,driver<571 brand=vapps,driver>=570,driver<571 brand=vpc,driver>=570,driver<571 brand=vcs,driver>=570,driver<571 brand=vws,driver>=570,driver<571 brand=cloudgaming,driver>=570,driver<571 TORCH_CUDA_ARCH_LIST=7.0 7.5 8.0 8.9 9.0 10.0 12.0 CUDA_DEVICE_SM_LIMIT=0 NVIDIA_DRIVER_CAPABILITIES=compute,utility VLLM_USAGE_SOURCE=production-docker-image CUDA_VERSION=12.9.1 VLLM_ENABLE_CUDA_COMPATIBILITY=0 CUDA_DEVICE_MEMORY_LIMIT_0=143771m CUDA_DEVICE_MEMORY_LIMIT_1=143771m CUDA_DEVICE_MEMORY_LIMIT_2=143771m CUDA_DEVICE_MEMORY_LIMIT_3=143771m CUDA_DEVICE_MEMORY_LIMIT_4=143771m CUDA_DEVICE_MEMORY_LIMIT_5=143771m CUDA_DEVICE_MEMORY_LIMIT_6=143771m CUDA_DEVICE_MEMORY_LIMIT_7=143771m CUDA_DEVICE_MEMORY_SHARED_CACHE=/usr/local/vgpu/abe65350-30b9-4c9c-b381-bffe0fa7cc85.cache LD_LIBRARY_PATH=/usr/local/nvidia/lib64:/usr/local/cuda/lib64:/usr/local/cuda/lib64 PYTORCH_NVML_BASED_CUDA_CHECK=1 TORCHINDUCTOR_COMPILE_THREADS=1 TORCHINDUCTOR_CACHE_DIR=/tmp/torchinductor_root

🐛 Describe the bug

Test code

from zai import ZaiClient

# Initialize client
client = ZaiClient(api_key='**', base_url="**")

# Create streaming tool call request
response = client.chat.completions.create(
    model="glm5",  # Use model that supports tool calling
    messages=[
        {"role": "user", "content": "How's the weather in Beijing?"},
    ],
    tools=[
        {
            "type": "function",
            "function": {
                "name": "get_weather",
                "description": "Get current weather conditions for a specified location",
                "parameters": {
                    "type": "object",
                    "properties": {
                        "location": {"type": "string", "description": "City, e.g.: Beijing, Shanghai"},
                        "unit": {"type": "string", "enum": ["celsius", "fahrenheit"]}
                    },
                    "required": ["location"]
                }
            }
        }
    ],
    stream=True,        # Enable streaming output
)

# Initialize variables to collect streaming data
reasoning_content = ""      # Reasoning process content
content = ""               # Response content
final_tool_calls = {}      # Tool call information
reasoning_started = False  # Reasoning process start flag
content_started = False    # Content output start flag

# Process streaming response
for chunk in response:
    if not chunk.choices:
        continue

    delta = chunk.choices[0].delta

    # Handle streaming reasoning process output
    if hasattr(delta, 'reasoning_content') and delta.reasoning_content:
        if not reasoning_started and delta.reasoning_content.strip():
            print("\n🧠 Thinking Process:")
            reasoning_started = True
        reasoning_content += delta.reasoning_content
        print(delta.reasoning_content, end="", flush=True)

    # Handle streaming response content output
    if hasattr(delta, 'content') and delta.content:
        if not content_started and delta.content.strip():
            print("\n\n💬 Response Content:")
            content_started = True
        content += delta.content
        print(delta.content, end="", flush=True)

    # Handle streaming tool call information
    if delta.tool_calls:
        for tool_call in delta.tool_calls:
            index = tool_call.index
            if index not in final_tool_calls:
                # New tool call
                final_tool_calls[index] = tool_call
                final_tool_calls[index].function.arguments = tool_call.function.arguments
            else:
                # Append tool call parameters (streaming construction)
                final_tool_calls[index].function.arguments += tool_call.function.arguments

# Output final tool call information
if final_tool_calls:
    print("\n📋 Function Calls Triggered:")
    for index, tool_call in final_tool_calls.items():
        print(f"  {index}: Function Name: {tool_call.function.name}, Parameters: {tool_call.function.arguments}")

Result

🧠 Thinking Process:
The user is asking about the weather in Beijing. I have a weather function available that can get current weather conditions for a specified location. 

Looking at the function parameters:
- location: required, and the user specified "Beijing" 
- unit: optional, not specified by the user, so I won't include it (the instructions say not to make up values for or ask about optional parameters)

I have all the required parameters, so I can proceed with the function call.

💬 Response Content:
I'll check the current weather conditions in Beijing for you.
📋 Function Calls Triggered:
  0: Function Name: get, Parameters: {"location": "Beijing"}

Error

The Function Name is get_weather, But GLM5 output is get:

0: Function Name: get, Parameters: {"location": "Beijing"}

When stream=False, The Function Name is correct!

🐛 Describe the bug

Test code

from zai import ZaiClient

# Initialize client
client = ZaiClient(api_key='**', base_url="**")

# Create streaming tool call request
response = client.chat.completions.create(
    model="glm5",  # Use model that supports tool calling
    messages=[
        {"role": "user", "content": "How's the weather in Beijing?"},
    ],
    tools=[
        {
            "type": "function",
            "function": {
                "name": "get_weather",
                "description": "Get current weather conditions for a specified location",
                "parameters": {
                    "type": "object",
                    "properties": {
                        "location": {"type": "string", "description": "City, e.g.: Beijing, Shanghai"},
                        "unit": {"type": "string", "enum": ["celsius", "fahrenheit"]}
                    },
                    "required": ["location"]
                }
            }
        }
    ],
    stream=True,        # Enable streaming output
)

# Initialize variables to collect streaming data
reasoning_content = ""      # Reasoning process content
content = ""               # Response content
final_tool_calls = {}      # Tool call information
reasoning_started = False  # Reasoning process start flag
content_started = False    # Content output start flag

# Process streaming response
for chunk in response:
    if not chunk.choices:
        continue

    delta = chunk.choices[0].delta

    # Handle streaming reasoning process output
    if hasattr(delta, 'reasoning_content') and delta.reasoning_content:
        if not reasoning_started and delta.reasoning_content.strip():
            print("\n🧠 Thinking Process:")
            reasoning_started = True
        reasoning_content += delta.reasoning_content
        print(delta.reasoning_content, end="", flush=True)

    # Handle streaming response content output
    if hasattr(delta, 'content') and delta.content:
        if not content_started and delta.content.strip():
            print("\n\n💬 Response Content:")
            content_started = True
        content += delta.content
        print(delta.content, end="", flush=True)

    # Handle streaming tool call information
    if delta.tool_calls:
        for tool_call in delta.tool_calls:
            index = tool_call.index
            if index not in final_tool_calls:
                # New tool call
                final_tool_calls[index] = tool_call
                final_tool_calls[index].function.arguments = tool_call.function.arguments
            else:
                # Append tool call parameters (streaming construction)
                final_tool_calls[index].function.arguments += tool_call.function.arguments

# Output final tool call information
if final_tool_calls:
    print("\n📋 Function Calls Triggered:")
    for index, tool_call in final_tool_calls.items():
        print(f"  {index}: Function Name: {tool_call.function.name}, Parameters: {tool_call.function.arguments}")

Result

🧠 Thinking Process:
The user is asking about the weather in Beijing. I have a weather function available that can get current weather conditions for a specified location. 

Looking at the function parameters:
- location: required, and the user specified "Beijing" 
- unit: optional, not specified by the user, so I won't include it (the instructions say not to make up values for or ask about optional parameters)

I have all the required parameters, so I can proceed with the function call.

💬 Response Content:
I'll check the current weather conditions in Beijing for you.
📋 Function Calls Triggered:
  0: Function Name: get, Parameters: {"location": "Beijing"}

Error

The Function Name is get_weather, But GLM5 output is get :

0: Function Name: get, Parameters: {"location": "Beijing"}

When stream=False, The Function Name is correct !

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