VLLM dependency Issues with DBR 17.0

nish7 — Mon, 15 Sep 2025 14:09:20 GMT

I am trying to install vllm and its appropriate dependencies on DataBricks Cluster DBR 17.0.

I have the vllm wheel and its dependent wheels within the databricks catalog in a Volumes folder.

I am running the following command below to install all the wheel files.

%pip install /Volumes/workspace/libs/artifacts/vllm-v0.10.1.1/*.whl

I keep finding myself running into this issue below

The conflict is caused by: The user requested numba 0.61.2 (from /Volumes/workspace/libs/artifacts/vllm-v0.10.1.1/numba-0.61.2-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl) vllm 0.10.1.1+cu118 depends on numba==0.61.2; python_version > "3.9" ydata-profiling 4.16.1 depends on numba<=0.61 and >=0.56.0

Downgrading numba<=0.61 causes vllm to fail as it depends on numba==0.61.2 but ydata-profiling throws an error when numba is not <0.61

I do not have a wheel for ydata-profiling being installed within the volumes folder

Here are all the wheels files located within the volumes that are being installed for vllm aiohappyeyeballs 2.6.1 aiohttp 3.12.15 aiosignal 1.4.0 annotated-types 0.7.0 anyio 4.10.0 astor 0.8.1 attrs 25.3.0 blake3 1.0.5 cachetools 6.2.0 cbor2 5.7.0 certifi 2025.8.3 cffi 2.0.0 charset-normalizer 3.4.3 click 8.2.1 cloudpickle 3.1.1 compressed-tensors 0.10.2 cupy-cuda12x 13.6.0 depyf 0.19.0 dill 0.4.0 diskcache 5.6.3 distro 1.9.0 dnspython 2.8.0 einops 0.8.1 email-validator 2.3.0 fastapi 0.116.1 fastapi-cli 0.0.11 fastapi-cloud-cli 0.1.5 fastrlock 0.8.3 filelock 3.19.1 frozenlist 1.7.0 fsspec 2025.9.0 gguf 0.17.1 h11 0.16.0 hf-xet 1.1.9 httpcore 1.0.9 httptools 0.6.4 httpx 0.28.1 huggingface-hub 0.34.4 idna 3.10 interegular 0.3.3 Jinja2 3.1.6 jiter 0.10.0 jsonschema 4.25.1 jsonschema-specifications 2025.9.1 lark 1.2.2 llguidance 0.7.30 llvmlite 0.44.0 lm-format-enforcer 0.10.12 markdown-it-py 4.0.0 MarkupSafe 3.0.2 mdurl 0.1.2 mistral_common 1.8.4 mpmath 1.3.0 msgpack 1.1.1 msgspec 0.19.0 multidict 6.6.4 networkx 3.5 ninja 1.13.0 numba 0.61.2 numpy 2.2.6 nvidia-cublas-cu12 12.6.4.1 nvidia-cuda-cupti-cu12 12.6.80 nvidia-cuda-nvrtc-cu12 12.6.77 nvidia-cuda-runtime-cu12 12.6.77 nvidia-cudnn-cu12 9.5.1.17 nvidia-cufft-cu12 11.3.0.4 nvidia-cufile-cu12 1.11.1.6 nvidia-curand-cu12 10.3.7.77 nvidia-cusolver-cu12 11.7.1.2 nvidia-cusparse-cu12 12.5.4.2 nvidia-cusparselt-cu12 0.6.3 nvidia-nccl-cu12 2.26.2 nvidia-nvjitlink-cu12 12.6.85 nvidia-nvtx-cu12 12.6.77 openai 1.107.0 openai-harmony 0.0.4 opencv-python-headless 4.12.0.88 outlines_core 0.2.10 packaging 25.0 partial-json-parser 0.2.1.1.post6 pillow 11.3.0 pip 25.2 prometheus_client 0.22.1 prometheus-fastapi-instrumentator 7.1.0 propcache 0.3.2 protobuf 6.32.0 psutil 7.0.0 py-cpuinfo 9.0.0 pybase64 1.4.2 pycountry 24.6.1 pycparser 2.23 pydantic 2.11.7 pydantic_core 2.33.2 pydantic-extra-types 2.10.5 Pygments 2.19.2 python-dotenv 1.1.1 python-json-logger 3.3.0 python-multipart 0.0.20 PyYAML 6.0.2 pyzmq 27.1.0 ray 2.49.1 referencing 0.36.2 regex 2025.9.1 requests 2.32.5 rich 14.1.0 rich-toolkit 0.15.1 rignore 0.6.4 rpds-py 0.27.1 safetensors 0.6.2 scipy 1.16.1 sentencepiece 0.2.1 sentry-sdk 2.37.1 setproctitle 1.3.7 setuptools 79.0.1 shellingham 1.5.4 six 1.17.0 sniffio 1.3.1 soundfile 0.13.1 soxr 1.0.0 starlette 0.47.3 sympy 1.14.0 tiktoken 0.11.0 tokenizers 0.22.0 torch 2.7.1 torchaudio 2.7.1 torchvision 0.22.1 tqdm 4.67.1 transformers 4.56.1 triton 3.3.1 typer 0.17.4 typing_extensions 4.15.0 typing-inspection 0.4.1 urllib3 2.5.0 uvicorn 0.35.0 uvloop 0.21.0 vllm 0.10.1.1 watchfiles 1.1.0 websockets 15.0.1 wget 3.2 xformers 0.0.31 xgrammar 0.1.21 yarl 1.20.1

What is causing the compatibility issues between numba & ydata-profiling which is not allowing vllm to be installed on databricks 17.0 cluster.

Thanks

Re: VLLM dependency Issues with DBR 17.0

Louis_Frolio — Thu, 18 Sep 2025 15:06:01 GMT

Hi @nish7 here are some helpful suggestions,

I did some digging and confirmed that the issue you’re encountering stems from conflicting dependencies. Specifically, there’s a hard version clash around the numba library:

=> vLLM 0.10.1.1 requires exactly numba==0.61.2

=> ydata-profiling 4.16.1 requires numba <0.61, but at least 0.56.0

Because Databricks Runtime 17.0 clusters run Python versions above 3.9, vLLM enforces numba==0.61.2. This version falls outside the range supported by ydata-profiling, which does not accept numba 0.61.2. As a result, the two packages cannot be installed together in the same environment.

Two possible mitigations are:

=> Remove ydata-profiling: If feasible, uninstall or prevent ydata-profiling (and its dependents) from being installed before adding vLLM. If you feel that you don’t need ydata-profiling, you can remove it directly at the notebook level with:

%pip uninstall ydata-profiling --yes

=> Custom Build: Currently, no version of ydata-profiling supports numba 0.61.2, and vLLM requires this version for compatibility with Python 3.12+. Neither package can be safely downgraded in this Databricks Runtime without breaking the other, so a custom build or fork would be required to reconcile the dependencies. Heads up, this is a going to be difficult.

Hope this helps.

Cheers, Louis.

topic VLLM dependency Issues with DBR 17.0 in Machine Learning

VLLM dependency Issues with DBR 17.0

Re: VLLM dependency Issues with DBR 17.0