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python-ml

Version 2026.144.1443
Repo superproject

A CUDA-ready Python 3.13 ML environment with PyTorch, transformers, and a vLLM inference runtime The python-ml candy owns the pixi.toml that builds the core ML Python environment under ~/.pixi/envs/default: PyTorch (cu130), torchvision/torchaudio, transformers, accelerate and the full vLLM runtime-dependency closure. After the pixi environment is built, a user-phase task pip-installs the vLLM nightly wheel (–no-deps) into that same interpreter. Every interpreter and library lands at a fixed path under ~/.pixi/envs/default, so its presence and importability are directly checkable.

This candy’s plan: — the runnable spec charly check executes against a live deployment. check: steps are idempotent probes; run: steps change state.

Intent Step
run command=~/.pixi/envs/default/bin/python -m pip install –no-deps \ ‘https://wheels.vllm.ai/f53fa26e05c476a43f6db048a9e3b43bcb2b72fb/vllm-0.19.1rc1.dev39%2Bgf53fa26e0.cu130-cp38-abi3-manylinux_2_35_x86_64.whl
check the pixi default-environment Python interpreter is present
check PyTorch imports inside the pixi environment and prints its version
check the transformers library imports inside the pixi environment and prints its version
check the vLLM nightly wheel installed by the user-phase task imports and prints its version
check command=${HOME}/.pixi/envs/default/bin/python -c “import torch; print(torch.version)”
check command=${HOME}/.pixi/envs/default/bin/python -c “import vllm; print(vllm.version)”
check command=${HOME}/.pixi/envs/default/bin/python -c “import transformers; print(transformers.version)”