python-ml
Recipe card from the charly-languages plugin (Images — the deployable catalog).
python-ml
Section titled “python-ml”GPU-accelerated Python environment with ML libraries — PyTorch, transformers, vLLM, llama.cpp.
Box Properties
Section titled “Box Properties”| Property | Value |
|---|---|
| Base | nvidia |
| Candies | agent-forwarding, python-ml |
| Platforms | linux/amd64 |
| Registry | ghcr.io/opencharly |
Candy Composition
Section titled “Candy Composition”The python-ml candy is a Tier 2 environment-owner meta-layer that:
- Owns the pixi.toml (core ML Python environment)
- Composes
llama-cpp(Tier 1 sub-candy) viacandy: [llama-cpp] - Installs vLLM 0.19 wheel via a cmd task (after pixi env is established)
Build order: pixi environment → llama-cpp (binaries) → vLLM 0.19 wheel
Full Candy Stack
Section titled “Full Candy Stack”fedora→nvidia(CUDA base)pixi→python(transitive)python-ml— ML pixi environment (Tier 2, owns pixi.toml)llama-cpp— llama.cpp binaries (Tier 1, viacandy:field)
Quick Start
Section titled “Quick Start”charly box build python-mlcharly shell python-ml# python -c "import torch; print(torch.cuda.is_available())"Key Candies
Section titled “Key Candies”/charly-languages:python-ml— ML Python packages via pixi (Tier 2 meta-layer)/charly-jupyter:llama-cpp— llama.cpp binaries (sub-candy)/charly-distros:cuda— GPU support (via nvidia base)
Related Boxes
Section titled “Related Boxes”/charly-distros:nvidia— parent (GPU without ML packages)/charly-jupyter:jupyter-ml— adds JupyterLab + collaboration + MCP + unsloth on top of ML stack/charly-jupyter:jupyter— legacy Jupyter with ML stack (monolithic)/charly-jupyter:unsloth-studio— fine-tuning UI with similar ML stack
Verification
Section titled “Verification”After charly box build:
charly shell python-ml -c "python -c 'import torch; print(torch.cuda.is_available())'"— CUDA OKcharly shell python-ml -c "python -c 'import vllm; print(vllm.__version__)'"— vLLM OKcharly shell python-ml -c "ls ~/llama.cpp/llama-quantize"— llama.cpp OK
When to Use This Skill
Section titled “When to Use This Skill”MUST be invoked when the task involves the python-ml box, ML training environments, or GPU-accelerated Python. Invoke this skill BEFORE reading source code or launching Explore agents.
Related
Section titled “Related”/charly-image:image— image family umbrella (candy:image entries — those carryingbase:/from:— incharly.yml, build/validate/inspect/list)/charly-build:build— the embedded build vocabulary (distros, builders, init-systems)