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Split vLLM requirements by CUDA version (#469)
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# These requirements were generated by running steps 1-3 of scripts/build_wheels.sh
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# then running pip freeze and manually removing the vllm dependency.
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# The intention of this file is to use these known requirements for a fixed
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# vLLM build to supplement a vLLM install from download.pytorch.org without
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# resorting to --extra-index-url https://download.pytorch.org/whl/nightly to find
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# vLLM dependencies (as this results in a ResolutionTooDeep error from pip).
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# See the file .github/workflows/gpu_test.yaml for an E2E forge installation using this approach.
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# TODO: this should be done way less hackily
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aiohappyeyeballs==2.6.1
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aiohttp==3.13.0
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aiosignal==1.4.0
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annotated-types==0.7.0
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anyio==4.11.0
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astor==0.8.1
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async-timeout==5.0.1
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attrs==25.4.0
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blake3==1.0.7
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cachetools==6.2.0
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cbor2==5.7.0
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certifi==2025.10.5
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cffi==2.0.0
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charset-normalizer==3.4.3
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click==8.3.0
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cloudpickle==3.1.1
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cmake==4.1.0
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compressed-tensors==0.10.2
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cupy-cuda12x==13.6.0
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depyf==0.19.0
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dill==0.4.0
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diskcache==5.6.3
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distro==1.9.0
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dnspython==2.8.0
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einops==0.8.1
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email-validator==2.3.0
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exceptiongroup==1.3.0
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fastapi==0.118.3
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fastapi-cli==0.0.13
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fastapi-cloud-cli==0.3.1
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fastrlock==0.8.3
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filelock==3.19.1
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frozenlist==1.8.0
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fsspec==2025.9.0
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gguf==0.17.1
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h11==0.16.0
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hf-xet==1.1.10
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httpcore==1.0.9
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httptools==0.7.1
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httpx==0.28.1
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huggingface-hub==0.35.3
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idna==3.10
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interegular==0.3.3
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Jinja2==3.1.6
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jiter==0.11.0
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jsonschema==4.25.1
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jsonschema-specifications==2025.9.1
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lark==1.2.2
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llguidance==0.7.30
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llvmlite==0.44.0
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lm-format-enforcer==0.10.12
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markdown-it-py==4.0.0
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MarkupSafe==3.0.2
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mdurl==0.1.2
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mistral_common==1.8.5
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mpmath==1.3.0
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msgpack==1.1.2
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msgspec==0.19.0
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multidict==6.7.0
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networkx==3.4.2
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ninja==1.13.0
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numba==0.61.2
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numpy==2.2.6
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nvidia-cublas-cu12==12.9.1.4
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nvidia-cuda-cupti-cu12==12.9.79
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nvidia-cuda-nvrtc-cu12==12.9.86
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nvidia-cuda-runtime-cu12==12.9.79
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nvidia-cudnn-cu12==9.10.2.21
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nvidia-cufft-cu12==11.4.1.4
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nvidia-cufile-cu12==1.14.1.1
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nvidia-curand-cu12==10.3.10.19
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nvidia-cusolver-cu12==11.7.5.82
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nvidia-cusparse-cu12==12.5.10.65
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nvidia-cusparselt-cu12==0.7.1
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nvidia-nccl-cu12==2.27.5
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nvidia-nvjitlink-cu12==12.9.86
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nvidia-nvshmem-cu12==3.3.20
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nvidia-nvtx-cu12==12.9.79
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openai==1.90.0
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opencv-python-headless==4.12.0.88
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outlines_core==0.2.10
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packaging==25.0
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partial-json-parser==0.2.1.1.post6
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pillow==11.3.0
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prometheus-fastapi-instrumentator==7.1.0
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prometheus_client==0.23.1
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propcache==0.4.1
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protobuf==6.32.1
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psutil==7.1.0
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py-cpuinfo==9.0.0
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pybase64==1.4.2
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pycountry==24.6.1
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pycparser==2.23
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pydantic==2.12.0
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pydantic-extra-types==2.10.6
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pydantic_core==2.41.1
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Pygments==2.19.2
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python-dotenv==1.1.1
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python-json-logger==4.0.0
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python-multipart==0.0.20
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pytorch-triton==3.4.0+gitf7888497
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PyYAML==6.0.3
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pyzmq==27.1.0
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ray==2.49.2
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referencing==0.36.2
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regex==2025.9.18
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requests==2.32.5
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rich==14.2.0
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rich-toolkit==0.15.1
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rignore==0.7.0
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rpds-py==0.27.1
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safetensors==0.6.2
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scipy==1.15.3
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sentencepiece==0.2.1
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sentry-sdk==2.41.0
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setuptools-scm==9.2.0
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shellingham==1.5.4
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sniffio==1.3.1
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soundfile==0.13.1
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soxr==1.0.0
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starlette==0.48.0
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sympy==1.14.0
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tiktoken==0.12.0
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tokenizers==0.22.1
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tomli==2.3.0
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torch==2.9.0.dev20250905+cu129
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tqdm==4.67.1
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transformers==4.57.0
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triton==3.4.0
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typer==0.19.2
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typing-inspection==0.4.2
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typing_extensions==4.15.0
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urllib3==2.5.0
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uvicorn==0.37.0
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uvloop==0.21.0
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watchfiles==1.1.0
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websockets==15.0.1
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xgrammar==0.1.21
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yarl==1.22.0

.github/workflows/gpu_test.yaml

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- name: Download and install vLLM and its dependencies
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# TODO: this honestly could not be hackier if I tried
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run: |
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python -m pip install -r .github/packaging/vllm_reqs.txt
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python -m pip install -r .github/packaging/vllm_reqs_12_9.txt
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python -m pip install vllm==0.10.1.dev0+g6d8d0a24c.d20251009.cu129 --no-cache-dir --index-url https://download.pytorch.org/whl/preview/forge
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- name: Install Monarch
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run: pip install torchmonarch==0.1.0rc1

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