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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
| Date | Stars |
|---|---|
| 2026-07-24 | 43337 |
| 2026-07-25 | 43350 |
| 2026-07-28 | 43350 |
| 2026-07-30 | 43350 |
| 2026-08-06 | 43350 |
Today
— stars today
This week
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This month
— stars this month
Momentum
35.0
growth rate 0.00%/day
.. image:: https://github.com/ray-project/ray/raw/master/doc/source/images/ray_header_logo.png
.. image:: https://readthedocs.org/projects/ray/badge/?version=master
:target: http://docs.ray.io/en/master/?badge=master
.. image:: https://img.shields.io/badge/Ray-Join%20Slack-blue
:target: https://www.ray.io/join-slack
.. image:: https://img.shields.io/badge/Discuss-Ask%20Questions-blue
:target: https://discuss.ray.io/
.. image:: https://img.shields.io/twitter/follow/raydistributed.svg?style=social&logo=twitter
:target: https://x.com/raydistributed
.. image:: https://img.shields.io/badge/Get_started_for_free-3C8AE9?logo=data%3Aimage%2Fpng%3Bbase64%2CiVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8%2F9hAAAAAXNSR0IArs4c6QAAAERlWElmTU0AKgAAAAgAAYdpAAQAAAABAAAAGgAAAAAAA6ABAAMAAAABAAEAAKACAAQAAAABAAAAEKADAAQAAAABAAAAEAAAAAA0VXHyAAABKElEQVQ4Ea2TvWoCQRRGnWCVWChIIlikC9hpJdikSbGgaONbpAoY8gKBdAGfwkfwKQypLQ1sEGyMYhN1Pd%2B6A8PqwBZeOHt%2FvsvMnd3ZXBRFPQjBZ9K6OY8ZxF%2B0IYw9PW3qz8aY6lk92bZ%2BVqSI3oC9T7%2FyCVnrF1ngj93us%2B540sf5BrCDfw9b6jJ5lx%2FyjtGKBBXc3cnqx0INN4ImbI%2Bl%2BPnI8zWfFEr4chLLrWHCp9OO9j19Kbc91HX0zzzBO8EbLK2Iv4ZvNO3is3h6jb%2BCwO0iL8AaWqB7ILPTxq3kDypqvBuYuwswqo6wgYJbT8XxBPZ8KS1TepkFdC79TAHHce%2F7LbVioi3wEfTpmeKtPRGEeoldSP%2FOeoEftpP4BRbgXrYZefsAI%2BP9JU7ImyEAAAAASUVORK5CYII%3D
:target: https://www.anyscale.com/ray-on-anyscale?utm_source=github&utm_medium=ray_readme&utm_campaign=get_started_badge
Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI libraries for simplifying ML compute:
.. image:: https://github.com/ray-project/ray/raw/master/doc/source/images/what-is-ray-padded.svg
..
https://docs.google.com/drawings/d/1Pl8aCYOsZCo61cmp57c7Sja6HhIygGCvSZLi_AuBuqo/edit
Learn more about `Ray AI Libraries`_:
- `Data`_: Scalable Datasets for ML
- `Train`_: Distributed Training
- `Tune`_: Scalable Hyperparameter Tuning
- `RLlib`_: Scalable Reinforcement Learning
- `Serve`_: Scalable and Programmable Serving
Or more about `Ray Core`_ and its key abstractions:
- `Tasks`_: Stateless functions executed in the cluster.
- `Actors`_: Stateful worker processes created in the cluster.
- `Objects`_: Immutable values accessible across the cluster.
Learn more about Monitoring and Debugging:
- Monitor Ray apps and clusters with the `Ray Dashboard <https://docs.ray.io/en/latest/ray-core/ray-dashboard.html>`__.
- Debug Ray apps with the `Ray Distributed Debugger <https://docs.ray.io/en/latest/ray-observability/ray-distributed-debugger.html>`__.
Ray runs on any machine, cluster, cloud provider, and Kubernetes, and features a growing
`ecosystem of community integrations`_.
Install Ray with: ``pip install ray``. For nightly wheels, see the
`Installation page <https://docs.ray.io/en/latest/ray-overview/installation.html>`__.
.. _`Serve`: https://docs.ray.io/en/latest/serve/index.html
.. _`Data`: https://docs.ray.io/en/latest/data/data.html
.. _`Workflow`: https://docs.ray.io/en/latest/workflows/
.. _`Train`: https://docs.ray.io/en/latest/train/train.html
.. _`Tune`: https://docs.ray.io/en/latest/tune/index.html
.. _`RLlib`: https://docs.ray.io/en/latest/rllib/index.html
.. _`ecosystem of community integrations`: https://docs.ray.io/en/latest/ray-overview/ray-libraries.html
Why Ray?
--------
Today's ML workloads are increasingly compute-intensive. As convenient as they are, single-node development environments such as your laptop cannot scale to meet these demands.
Ray is a unified way to scale Python and AI applications from a laptop to a cluster.
With Ray, you can seamlessly scale the same code from a laptop to a cluster. Ray is designed to be general-purpose, meaning that it can performantly run any kind of workload. If your application is written in Python, you can scale it with Ray, no other infrastructure required.
More Information
----------------
- `Documentation`_
- `Ray Architecture whitepaper`_
- `Exoshuffle: large-scale data shuffle in Ray`Excerpt of 6,506 characters
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:558c22903f511377, topic:deep-learning, topic:pytorch, topic:tensorflow
matched fp:558c22903f511377, topic:llm-inference, topic:llm-serving
matched fp:558c22903f511377, topic:large-language-models, topic:llm