Project Icon

covalent

跨平台执行AI、ML和科研代码的统一框架

Covalent是一个面向AI/ML工程师、开发者和研究人员的Python库,用于简化跨平台计算任务的执行。通过更改单行代码,用户可在云平台或本地集群上运行LLM、生成式AI和科学研究等任务。该库抽象了基础设施管理,实现无服务器化,并提供实时监控。Covalent支持AWS、Azure、GCP和SLURM等多种执行环境,为用户提供统一的界面和灵活的资源管理。

hero

version Static Badge Static Badge Static Badge Static Badge apache

Run AI, ML, and Scientific Research Code on Any Cloud or On-Prem Cluster with a Single Line

divider    divider    divider    divider

pip install covalent --upgrade

Check our Quick Start Guide for setup instructions or dive into your First Experiment. Learn more on the Concepts.

What is Covalent?

Covalent is a Python library for AI/ML engineers, developers, and researchers. It provides a straightforward approach to running compute jobs, like LLMs, generative AI, and scientific research, on various cloud platforms or on-prem clusters.

Run Code Anywhere: Execute Python functions in any cloud or on-prem cluster by changing just a single line of code.

It is as simple as swapping the decorator with our executor plugins. Choose from existing plugins or create custom ones for tailored interactions with any infrastructure.

Abstraction of Infrastructure Management: Abstract the complexities of cloud consoles, terraform, or IaC in the background.
Serverless Infrastructure: Automatically converts any infrastructure, including on-prem SLURM clusters or cloud compute, into a serverless setup.

If you find Covalent useful or interesting, feel free to give us a ⭐ on GitHub! Your support helps us to continue developing and improving this framework.


For AI/ML Practitioners and DevelopersFor Researchers
  • Robust Compute Backend: Ideal as a backend compute framework for AI/ML applications, Large Language Models (LLMs), Generative AI, and more.
  • Cloud-Agnostic Execution: Execute high-compute tasks seamlessly across different cloud environments.
  • Infrastructure Abstraction: Directly use computing resources while keeping your business code independent from the infrastructure/resource definitions.
  • Local-Like Access: Effortlessly connect to compute resources from your laptop, eliminating the need for SSH or complex scripts.
  • Unified Interface Across Environments: Consistent experience with on-prem HPC clusters and cloud platforms like SLURM, PBS, LSF, AWS, GCP, Azure.
  • Real-Time Monitoring Monitoring: User-friendly UI for real-time monitoring, enabling cost-effective and iterative R&D.

Out-of-box observability - Try out the demo

If you find Covalent useful or interesting, feel free to give us a ⭐ on GitHub! Your support helps us to continue developing and improving this framework.

video

Explore Covalent Through Examples

Jump right into practical examples to see Covalent in action. These tutorials cover a range of applications, giving you a hands-on experience:

Explore Our Extensive Plugin Ecosystem

Covalent integrates seamlessly with a variety of platforms. Discover our range of plugins to enhance your Covalent experience:


divider divider divider divider
divider divider divider divider

Key Features at a Glance

Get a quick overview of what Covalent offers. Our infographic summarizes the main features, providing you with a snapshot of our capabilities:


development


Know More About Covalent

For a more in-depth description of Covalent's features and how they work, see the Concepts page in the documentation.


divider divider divider divider

Installation

Covalent is developed using Python on Linux and macOS. The easiest way to install Covalent is by using the PyPI package manager.

pip install covalent --upgrade

For other methods of installation, please check the docs.

Deployments

Covalent offers flexible deployment options, from Docker image/AMIs for self-hosting to pip package for local installations, accommodating various use cases

divider divider divider


Contributing

To contribute to Covalent, refer to the Contribution Guidelines. We use GitHub's issue tracking to manage known issues, bugs, and pull requests. Get started by forking the develop branch and submitting a pull request with your contributions. Improvements to the documentation, including tutorials and how-to guides, are also welcome from the community. For more information on adding tutorials, check the Tutorial Guidelines. Participation in the Covalent community is governed by the Code of Conduct.

Citation

Please use the following citation in any publications.

https://doi.org/10.5281/zenodo.5903364

License

Covalent is licensed under the Apache 2.0 License. See the LICENSE file or contact the support team for more details.

For a detailed history of changes and new features, see the Changelog.

项目侧边栏1项目侧边栏2
推荐项目
Project Cover

豆包MarsCode

豆包 MarsCode 是一款革命性的编程助手,通过AI技术提供代码补全、单测生成、代码解释和智能问答等功能,支持100+编程语言,与主流编辑器无缝集成,显著提升开发效率和代码质量。

Project Cover

AI写歌

Suno AI是一个革命性的AI音乐创作平台,能在短短30秒内帮助用户创作出一首完整的歌曲。无论是寻找创作灵感还是需要快速制作音乐,Suno AI都是音乐爱好者和专业人士的理想选择。

Project Cover

有言AI

有言平台提供一站式AIGC视频创作解决方案,通过智能技术简化视频制作流程。无论是企业宣传还是个人分享,有言都能帮助用户快速、轻松地制作出专业级别的视频内容。

Project Cover

Kimi

Kimi AI助手提供多语言对话支持,能够阅读和理解用户上传的文件内容,解析网页信息,并结合搜索结果为用户提供详尽的答案。无论是日常咨询还是专业问题,Kimi都能以友好、专业的方式提供帮助。

Project Cover

阿里绘蛙

绘蛙是阿里巴巴集团推出的革命性AI电商营销平台。利用尖端人工智能技术,为商家提供一键生成商品图和营销文案的服务,显著提升内容创作效率和营销效果。适用于淘宝、天猫等电商平台,让商品第一时间被种草。

Project Cover

吐司

探索Tensor.Art平台的独特AI模型,免费访问各种图像生成与AI训练工具,从Stable Diffusion等基础模型开始,轻松实现创新图像生成。体验前沿的AI技术,推动个人和企业的创新发展。

Project Cover

SubCat字幕猫

SubCat字幕猫APP是一款创新的视频播放器,它将改变您观看视频的方式!SubCat结合了先进的人工智能技术,为您提供即时视频字幕翻译,无论是本地视频还是网络流媒体,让您轻松享受各种语言的内容。

Project Cover

美间AI

美间AI创意设计平台,利用前沿AI技术,为设计师和营销人员提供一站式设计解决方案。从智能海报到3D效果图,再到文案生成,美间让创意设计更简单、更高效。

Project Cover

AIWritePaper论文写作

AIWritePaper论文写作是一站式AI论文写作辅助工具,简化了选题、文献检索至论文撰写的整个过程。通过简单设定,平台可快速生成高质量论文大纲和全文,配合图表、参考文献等一应俱全,同时提供开题报告和答辩PPT等增值服务,保障数据安全,有效提升写作效率和论文质量。

投诉举报邮箱: service@vectorlightyear.com
@2024 懂AI·鲁ICP备2024100362号-6·鲁公网安备37021002001498号