Manage Python dependencies in Ray — add/remove/upgrade packages, work with raydepsets lock files, debug dependency conflicts, and regenerate compiled requirements. Covers python/requirements, python/requirements/, python/deplocks/, and ci/raydepsets/configs/.depsets.yaml.
EnglishDistributed training orchestration across clusters. Scales PyTorch/TensorFlow/HuggingFace from laptop to 1000s of nodes.
EnglishIncludes Ray Dependencies and other workflows.
Supported by the Atlas install prompt. Skill-specific requirements vary.
Pack stats
What’s included
Ray Dependencies
Manage Python dependencies in Ray — add/remove/upgrade packages, work with raydepsets lock files, debug dependency conflicts, and regenerate compiled requirements. Covers python/requirements, python/requirements/, python/deplocks/, and ci/raydepsets/configs/.depsets.yaml.
Ray Train
Distributed training orchestration across clusters. Scales PyTorch/TensorFlow/HuggingFace from laptop to 1000s of nodes. Built-in hyperparameter tuning with Ray Tune, fau
Quick start
- Choose your skills. Select individual skills above, or choose the entire pack.
- Copy the install prompt. Use Copy install prompt above the list.
- Send it to your agent. Paste into your coding agent’s chat. Your agent reviews the source and guides the setup.
Try it with your agent
After installation, start with a request like:
Use the Ray Dependencies skill to help with my task.
Ask me for the context you need before getting started.Requirements & license
- A coding agent that can access your project files and install skills.
- Your agent checks each skill’s instructions, dependencies, and permissions during setup.
- Reported licenses for the skills shown: Apache-2.0, MIT. The author’s terms apply.