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[Bug]: mistral tool choice error #10821

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warlockedward opened this issue Dec 2, 2024 · 9 comments · Fixed by #10979
Closed
1 task done

[Bug]: mistral tool choice error #10821

warlockedward opened this issue Dec 2, 2024 · 9 comments · Fixed by #10979
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bug Something isn't working

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@warlockedward
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Your current environment

The output of `python collect_env.py` 
Collecting environment information...
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: Could not collect
Libc version: glibc-2.35

Python version: 3.11.9 (main, Apr 19 2024, 16:48:06) [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-5.15.0-124-generic-x86_64-with-glibc2.35
Is CUDA available: True
CUDA runtime version: 12.4.131
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: 
GPU 0: Tesla V100-SXM2-32GB
GPU 1: Tesla V100-SXM2-32GB
GPU 2: Tesla V100-SXM2-32GB
GPU 3: Tesla V100-SXM2-32GB
GPU 4: Tesla V100-SXM2-32GB
GPU 5: Tesla V100-SXM2-32GB
GPU 6: Tesla V100-SXM2-32GB
GPU 7: Tesla V100-SXM2-32GB

Nvidia driver version: 550.120
cuDNN version: Probably one of the following:
/usr/lib/x86_64-linux-gnu/libcudnn.so.9.2.1
/usr/lib/x86_64-linux-gnu/libcudnn_adv.so.9.2.1
/usr/lib/x86_64-linux-gnu/libcudnn_cnn.so.9.2.1
/usr/lib/x86_64-linux-gnu/libcudnn_engines_precompiled.so.9.2.1
/usr/lib/x86_64-linux-gnu/libcudnn_engines_runtime_compiled.so.9.2.1
/usr/lib/x86_64-linux-gnu/libcudnn_graph.so.9.2.1
/usr/lib/x86_64-linux-gnu/libcudnn_heuristic.so.9.2.1
/usr/lib/x86_64-linux-gnu/libcudnn_ops.so.9.2.1
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:                        46 bits physical, 48 bits virtual
Byte Order:                           Little Endian
CPU(s):                               96
On-line CPU(s) list:                  0-95
Vendor ID:                            GenuineIntel
Model name:                           Intel(R) Xeon(R) Gold 6271C CPU @ 2.60GHz
CPU family:                           6
Model:                                85
Thread(s) per core:                   2
Core(s) per socket:                   24
Socket(s):                            2
Stepping:                             7
BogoMIPS:                             5200.00
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 pni pclmulqdq dtes64 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 cdp_l3 invpcid_single intel_ppin ssbd mba ibrs ibpb stibp ibrs_enhanced tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm mpx rdt_a avx512f avx512dq rdseed adx smap clflushopt clwb intel_pt avx512cd avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local dtherm ida arat pln pts hwp_epp pku ospke avx512_vnni md_clear flush_l1d arch_capabilities
Virtualization:                       VT-x
L1d cache:                            1.5 MiB (48 instances)
L1i cache:                            1.5 MiB (48 instances)
L2 cache:                             48 MiB (48 instances)
L3 cache:                             66 MiB (2 instances)
NUMA node(s):                         2
NUMA node0 CPU(s):                    0-23,48-71
NUMA node1 CPU(s):                    24-47,72-95
Vulnerability Gather data sampling:   Mitigation; Microcode
Vulnerability Itlb multihit:          KVM: Mitigation: VMX disabled
Vulnerability L1tf:                   Not affected
Vulnerability Mds:                    Not affected
Vulnerability Meltdown:               Not affected
Vulnerability Mmio stale data:        Mitigation; Clear CPU buffers; SMT vulnerable
Vulnerability Reg file data sampling: 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 / Automatic IBRS; IBPB conditional; RSB filling; PBRSB-eIBRS SW sequence; BHI SW loop, KVM SW loop
Vulnerability Srbds:                  Not affected
Vulnerability Tsx async abort:        Mitigation; TSX disabled

Versions of relevant libraries:
[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] torch==2.5.1
[pip3] torchvision==0.20.1
[pip3] transformers==4.46.2
[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] torch                     2.5.1                    pypi_0    pypi
[conda] torchvision               0.20.1                   pypi_0    pypi
[conda] transformers              4.46.2                   pypi_0    pypi
[conda] triton                    3.1.0                    pypi_0    pypi
ROCM Version: Could not collect
Neuron SDK Version: N/A
vLLM Version: 0.6.3.post2.dev338+gf0f2e563
vLLM Build Flags:
CUDA Archs: Not Set; ROCm: Disabled; Neuron: Disabled
GPU Topology:
GPU0    GPU1    GPU2    GPU3    GPU4    GPU5    GPU6    GPU7    NIC0    NIC1    NIC2    NIC3    CPU Affinity    NUMA Affinity   GPU NUMA ID
GPU0     X      NV1     NV2     NV1     SYS     SYS     SYS     NV2     NODE    NODE    SYS     SYS     0-23,48-71      0               N/A
GPU1    NV1      X      NV1     NV2     SYS     SYS     NV2     SYS     NODE    NODE    SYS     SYS     0-23,48-71      0               N/A
GPU2    NV2     NV1      X      NV2     SYS     NV1     SYS     SYS     PIX     PIX     SYS     SYS     0-23,48-71      0               N/A
GPU3    NV1     NV2     NV2      X      NV1     SYS     SYS     SYS     PIX     PIX     SYS     SYS     0-23,48-71      0               N/A
GPU4    SYS     SYS     SYS     NV1      X      NV2     NV2     NV1     SYS     SYS     PIX     PIX     24-47,72-95     1               N/A
GPU5    SYS     SYS     NV1     SYS     NV2      X      NV1     NV2     SYS     SYS     PIX     PIX     24-47,72-95     1               N/A
GPU6    SYS     NV2     SYS     SYS     NV2     NV1      X      NV1     SYS     SYS     NODE    NODE    24-47,72-95     1               N/A
GPU7    NV2     SYS     SYS     SYS     NV1     NV2     NV1      X      SYS     SYS     NODE    NODE    24-47,72-95     1               N/A
NIC0    NODE    NODE    PIX     PIX     SYS     SYS     SYS     SYS      X      PIX     SYS     SYS
NIC1    NODE    NODE    PIX     PIX     SYS     SYS     SYS     SYS     PIX      X      SYS     SYS
NIC2    SYS     SYS     SYS     SYS     PIX     PIX     NODE    NODE    SYS     SYS      X      PIX
NIC3    SYS     SYS     SYS     SYS     PIX     PIX     NODE    NODE    SYS     SYS     PIX      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

NCCL_P2P_DISABLE=0
VLLM_WORKER_MULTIPROC_METHOD=spawn
NCCL_NSOCKS_PERTHREAD=2
NCCL_SOCKET_NTHREADS=2
LD_LIBRARY_PATH=/model/anaconda3/envs/vllm/lib/python3.11/site-packages/cv2/../../lib64:/usr/local/cuda-12.4/lib64${LD_LIBRARY_PATH:+:}
NCCL_CROSS_NIC=0
CUDA_MODULE_LOADING=LAZY

Model Input Dumps

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "/model/anaconda3/envs/vllm/lib/python3.11/site-packages/uvicorn/protocols/http/httptools_impl.py", line 401, in run_asgi
result = await app( # type: ignore[func-returns-value]
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/model/anaconda3/envs/vllm/lib/python3.11/site-packages/uvicorn/middleware/proxy_headers.py", line 60, in call
return await self.app(scope, receive, send)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/model/anaconda3/envs/vllm/lib/python3.11/site-packages/fastapi/applications.py", line 1054, in call
await super().call(scope, receive, send)
File "/model/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/applications.py", line 113, in call
await self.middleware_stack(scope, receive, send)
File "/model/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/middleware/errors.py", line 187, in call
raise exc
File "/model/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/middleware/errors.py", line 165, in call
await self.app(scope, receive, _send)
File "/model/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/middleware/base.py", line 185, in call
with collapse_excgroups():
File "/model/anaconda3/envs/vllm/lib/python3.11/contextlib.py", line 158, in exit
self.gen.throw(typ, value, traceback)
File "/model/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/_utils.py", line 82, in collapse_excgroups
raise exc
File "/model/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/middleware/base.py", line 187, in call
response = await self.dispatch_func(request, call_next)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/model/anaconda3/envs/vllm/lib/python3.11/site-packages/vllm/entrypoints/openai/api_server.py", line 490, in add_request_id
response = await call_next(request)
^^^^^^^^^^^^^^^^^^^^^^^^
File "/model/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/middleware/base.py", line 163, in call_next
raise app_exc
File "/model/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/middleware/base.py", line 149, in coro
await self.app(scope, receive_or_disconnect, send_no_error)
File "/model/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/middleware/base.py", line 185, in call
with collapse_excgroups():
File "/model/anaconda3/envs/vllm/lib/python3.11/contextlib.py", line 158, in exit
self.gen.throw(typ, value, traceback)
File "/model/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/_utils.py", line 82, in collapse_excgroups
raise exc
File "/model/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/middleware/base.py", line 187, in call
response = await self.dispatch_func(request, call_next)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/model/anaconda3/envs/vllm/lib/python3.11/site-packages/vllm/entrypoints/openai/api_server.py", line 485, in authentication
return await call_next(request)
^^^^^^^^^^^^^^^^^^^^^^^^
File "/model/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/middleware/base.py", line 163, in call_next
raise app_exc
File "/model/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/middleware/base.py", line 149, in coro
await self.app(scope, receive_or_disconnect, send_no_error)
File "/model/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/middleware/cors.py", line 85, in call
await self.app(scope, receive, send)
File "/model/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/middleware/exceptions.py", line 62, in call
await wrap_app_handling_exceptions(self.app, conn)(scope, receive, send)
File "/model/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/_exception_handler.py", line 53, in wrapped_app
raise exc
File "/model/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/_exception_handler.py", line 42, in wrapped_app
await app(scope, receive, sender)
File "/model/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/routing.py", line 715, in call
await self.middleware_stack(scope, receive, send)
File "/model/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/routing.py", line 735, in app
await route.handle(scope, receive, send)
File "/model/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/routing.py", line 288, in handle
await self.app(scope, receive, send)
File "/model/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/routing.py", line 76, in app
await wrap_app_handling_exceptions(app, request)(scope, receive, send)
File "/model/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/_exception_handler.py", line 53, in wrapped_app
raise exc
File "/model/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/_exception_handler.py", line 42, in wrapped_app
await app(scope, receive, sender)
File "/model/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/routing.py", line 73, in app
response = await f(request)
^^^^^^^^^^^^^^^^
File "/model/anaconda3/envs/vllm/lib/python3.11/site-packages/fastapi/routing.py", line 301, in app
raw_response = await run_endpoint_function(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/model/anaconda3/envs/vllm/lib/python3.11/site-packages/fastapi/routing.py", line 212, in run_endpoint_function
return await dependant.call(**values)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/model/anaconda3/envs/vllm/lib/python3.11/site-packages/vllm/entrypoints/openai/api_server.py", line 347, in create_chat_completion
generator = await handler.create_chat_completion(request, raw_request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/model/anaconda3/envs/vllm/lib/python3.11/site-packages/vllm/entrypoints/openai/serving_chat.py", line 155, in create_chat_completion
) = await self._preprocess_chat(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/model/anaconda3/envs/vllm/lib/python3.11/site-packages/vllm/entrypoints/openai/serving_engine.py", line 458, in _preprocess_chat
request_prompt = apply_mistral_chat_template(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/model/anaconda3/envs/vllm/lib/python3.11/site-packages/vllm/entrypoints/chat_utils.py", line 767, in apply_mistral_chat_template
return tokenizer.apply_chat_template(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/model/anaconda3/envs/vllm/lib/python3.11/site-packages/vllm/transformers_utils/tokenizers/mistral.py", line 265, in apply_chat_template
encoded = self.mistral.encode_chat_completion(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/model/anaconda3/envs/vllm/lib/python3.11/site-packages/mistral_common/tokens/tokenizers/mistral.py", line 194, in encode_chat_completion
validated_request = self._chat_completion_request_validator.validate_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/model/anaconda3/envs/vllm/lib/python3.11/site-packages/mistral_common/protocol/instruct/validator.py", line 63, in validate_request
self.validate_messages(request.messages)
File "/model/anaconda3/envs/vllm/lib/python3.11/site-packages/mistral_common/protocol/instruct/validator.py", line 51, in validate_messages
self._validate_message_list_content(messages)
File "/model/anaconda3/envs/vllm/lib/python3.11/site-packages/mistral_common/protocol/instruct/validator.py", line 273, in _validate_message_list_content
self._validate_assistant_message(message, is_last_message=idx == len(messages) - 1)
File "/model/anaconda3/envs/vllm/lib/python3.11/site-packages/mistral_common/protocol/instruct/validator.py", line 155, in _validate_assistant_message
self._validate_tool_call(tool_call, is_last_message=is_last_message)
File "/model/anaconda3/envs/vllm/lib/python3.11/site-packages/mistral_common/protocol/instruct/validator.py", line 310, in _validate_tool_call
raise InvalidFunctionCallException(
mistral_common.exceptions.InvalidFunctionCallException: Tool call id was m0bqB5RX6Xqr but must be a-z, A-Z, 0-9, with a length of 9.

🐛 Describe the bug

vllm serve /model/models/Pixtral-Large-Instruct-2411 -tp 1 --served-model-name Pixtral-Large-Instruct-2411 --dtype float16 --gpu-memory-utilization 0.925 --max-model-len 16384 --max-num-seqs 16 --tokenizer_mode mistral --enable-auto-tool-choice --tool-call-parser mistral --chat-template /vllm/examples/tool_chat_template_mistral_parallel.jinja

mistral_common==1.5.0

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@warlockedward warlockedward added the bug Something isn't working label Dec 2, 2024
@DarkLight1337
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Can you try updating to latest version of vLLM and see if you still get this error?

@warlockedward
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Can you try updating to latest version of vLLM and see if you still get this error?
Yes, I'm using the latest VLLM version 0.6.4.post1, and this problem is happening with the latest version!

@DarkLight1337
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How are you generating your tool call IDs? As stated by the error message, they should be alphanumeric and exactly 9 characters long.

@warlockedward
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您如何生成工具调用 ID？如错误消息所述，它们应为字母数字，长度恰好为 9 个字符。

I looked at the tool ID and it's 6 digits of letters and numbers, is it possible that the new mistral's V3 has this length limitation, as running it on the original mistral-large-2407 didn't have this problem?

@DarkLight1337
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@patrickvonplaten might have more context on this.

@Iven2132
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Iven2132 commented Dec 3, 2024

getting the same issue when running "vllm serve mistralai/Pixtral-Large-Instruct-2411 --config-format mistral --load-format mistral --tokenizer_mode mistral --limit_mm_per_prompt 'image=10' --tensor-parallel-size 8"

with all the latest versions of the library

@DarkLight1337 DarkLight1337 mentioned this issue Dec 4, 2024
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@cedonley
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cedonley commented Dec 5, 2024

The mistral parser, when streaming, builds the tool_call_id in the following way:

                    delta = DeltaMessage(tool_calls=[
                        DeltaToolCall(index=self.current_tool_id,
                                      type="function",
                                      id=f"chatcmpl-tool-{random_uuid()}",
                                      function=DeltaFunctionCall(
                                          name=function_name).model_dump(
                                              exclude_none=True))
                    ])

This is not 9 alpha-numeric, which seems to be the template requirement. When returning with stream=False, the code is:

                MistralToolCall(
                    type="function",
                    function=FunctionCall(
                        name=raw_function_call["name"],
                        # function call args are JSON but as a string
                        arguments=json.dumps(raw_function_call["arguments"],
                                             ensure_ascii=False)))

The later generates the 9 alphanumeric when init'ing the MistralToolCall using this method:

    def generate_random_id():
        # Mistral Tool Call Ids must be alphanumeric with a maximum length of 9.
        # https://github.com/mistralai/mistral-common/blob/21ee9f6cee3441e9bb1e6ed2d10173f90bd9b94b/src/mistral_common/protocol/instruct/validator.py#L299
        return "".join(choices(ALPHANUMERIC, k=9))

So the fix would seem to be to change the streaming code random generator to the same one used for stream=False. I have a PR #10782 that fixes other streaming issues with mistral and Hermes parsers. I can easily add this minor change to the PR.

@cedonley cedonley mentioned this issue Dec 5, 2024
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@DarkLight1337
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cc @K-Mistele

@cedonley cedonley mentioned this issue Dec 7, 2024
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@K-Mistele
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I thought the tool ID length issue was fixed both in the streaming parser in a previous PR, and also in the chat template that we provided. If that's not the case though, then #10979 looks like a good answer.

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[Bugfix] Multiple fixes to tool streaming with hermes and mistral cedonley/vllm
5 participants
@warlockedward @K-Mistele @DarkLight1337 @Iven2132 @cedonley