Package: covalent
Run AI, ML, and Scientific Research Code on Any Cloud or On-Prem Cluster with a Single Linepipinstallcovalent--upgradeCheck ourQuick Start Guidefor setup instructions or dive into yourFirst Experiment. Learn more on theConcepts.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 fromexisting pluginsorcreate custom onesfor 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 ResearchersRobust 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 UIfor real-time monitoring, enabling cost-effective and iterative R&D.Out-of-box observability -Try out the demoIf 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.Explore Covalent Through ExamplesJump 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 EcosystemCovalent integrates seamlessly with a variety of platforms. Discover our range of plugins to enhance your Covalent experience:Key Features at a GlanceGet a quick overview of what Covalent offers. Our infographic summarizes the main features, providing you with a snapshot of our capabilities:Know More About CovalentFor a more in-depth description of Covalent's features and how they work, see theConceptspage in the documentation.InstallationCovalent is developed using Python on Linux and macOS. The easiest way to install Covalent is by using the PyPI package manager.pip install covalent --upgradeFor other methods of installation, pleasecheck the docs.DeploymentsCovalent offers flexible deployment options, from Docker image/AMIs for self-hosting to pip package for local installations, accommodating various use casesContributingTo contribute to Covalent, refer to theContribution Guidelines. We use GitHub'sissue trackingto manage known issues, bugs, and pull requests. Get started by forking thedevelopbranch 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 theTutorial Guidelines. Participation in the Covalent community is governed by theCode of Conduct.CitationPlease use the following citation in any publications.https://doi.org/10.5281/zenodo.5903364LicenseCovalent is licensed under the Apache 2.0 License. See theLICENSEfile or contact thesupport teamfor more details.For a detailed history of changes and new features, see theChangelog.