diff --git a/CHANGELOG.md b/CHANGELOG.md index 46ed41604..0332913ae 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -11,6 +11,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0 - Updated RTD notebooks to fix their behavior - Changed the error being shown when drawing the transport graph of a lattice to a debug message instead +- Revamped README ### Removed diff --git a/README.md b/README.md index 85cf21d1b..780e10bd5 100644 --- a/README.md +++ b/README.md @@ -1,141 +1,202 @@ -  - +
+ hero +
+
- +[![version](https://img.shields.io/github/v/tag/AgnostiqHQ/covalent?color=%235552FF&include_prereleases&label=version&sort=semver)](https://github.com/AgnostiqHQ/covalent/blob/develop/CHANGELOG.md) +[![Static Badge](https://img.shields.io/badge/python-3.8_%7C_3.9_%7C_3.10-%235552FF)](#) +[![Static Badge](https://img.shields.io/badge/tests-passing-%235552FF?logo=github)](https://github.com/AgnostiqHQ/covalent/actions/workflows/tests.yml) +[![Static Badge](https://img.shields.io/badge/docs-passing-%235552FF)](https://docs.covalent.xyz/docs/) +[![Static Badge](https://img.shields.io/badge/codecov-88%25-%235552FF?logo=codecov)](https://codecov.io/gh/AgnostiqHQ/covalent) +[![apache](https://img.shields.io/badge/License-Apache_License_2.0-blue?color=%235552FF)](https://www.apache.org/licenses/LICENSE-2.0)
+ +
Run AI, ML, and Scientific Research Code on Any Cloud or On-Prem Cluster with a Single Line
+
+
+divider +   +divider +   +divider +   +divider +
+
-[![version](https://img.shields.io/github/v/tag/AgnostiqHQ/covalent?color=navy&include_prereleases&label=version&sort=semver)](https://github.com/AgnostiqHQ/covalent/blob/develop/CHANGELOG.md) -[![python](https://img.shields.io/pypi/pyversions/cova)](https://github.com/AgnostiqHQ/covalent) -[![tests](https://github.com/AgnostiqHQ/covalent/actions/workflows/tests.yml/badge.svg)](https://github.com/AgnostiqHQ/covalent/actions/workflows/tests.yml) -[![docs](https://readthedocs.org/projects/covalent/badge/?version=latest)](https://covalent.readthedocs.io/en/latest/?badge=latest) -[![codecov](https://codecov.io/gh/AgnostiqHQ/covalent/branch/master/graph/badge.svg?token=YGHCB3DE4P)](https://codecov.io/gh/AgnostiqHQ/covalent) -[![apache](https://img.shields.io/badge/License-Apache_License_2.0-blue)](https://www.apache.org/licenses/LICENSE-2.0) - +```bash +pip install covalent --upgrade +``` +Check our [Quick Start Guide](https://docs.covalent.xyz/docs/get-started/quick-start/) for setup instructions or dive into your [First Experiment](https://docs.covalent.xyz/docs/get-started/first-experiment/). Learn more on the [Concepts](https://docs.covalent.xyz/docs/user-documentation/concepts/concepts-index/). +### 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. -## 🤔 What is Covalent? -Covalent is a Pythonic workflow tool for computational scientists, AI/ML software engineers, and anyone who needs to run experiments on limited or expensive computing resources including quantum computers, HPC clusters, GPU arrays, and cloud services. +
+Run Code Anywhere: Execute Python functions in any cloud or on-prem cluster by changing just a single line of code. +
-Covalent enables a researcher to run computation tasks on an advanced hardware platform – such as a quantum computer or serverless HPC cluster – using a single line of code. -

-Covalent Executors -

+It is as simple as swapping the decorator with our executor plugins. Choose from [existing plugins](https://docs.covalent.xyz/docs/plugin) or [create custom ones](https://github.com/AgnostiqHQ/covalent-executor-template) for tailored interactions with any infrastructure. +
+
-## 💭 Why Covalent? +
+Abstraction of Infrastructure Management: Abstract the complexities of cloud consoles, terraform, or IaC in the background. +
+
+
-Covalent overcomes computational and operational challenges inherent in AI/ML experimentation. +
+Serverless Infrastructure: Automatically converts any infrastructure, including on-prem SLURM clusters or cloud compute, into a serverless setup. +
+
+
-| **Computational challenges** | **Operational challenges** | -| :------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | :----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -| | | -

-Covalent value -

+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. -With Covalent, you: -- Assign functions to appropriate resources: Use advanced hardware (quantum computers, HPC clusters) for the heavy lifting and commodity hardware for bookkeeping. -- Test functions on local servers before shipping them to advanced hardware. -- Let Covalent's services analyze functions for data independence and automatically parallelize them. -- Run experiments from a Jupyter notebook (or whatever your preferred interactive Python environment is). -- Track workflows and examine results in a browser-based GUI. +
+ + + + + + + + + +
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](http://demo.covalent.xyz/) -## 📦 Installation +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. -Covalent is developed using Python version 3.8 on Linux and macOS. The easiest way to install Covalent is using the PyPI package manager: + +
+ video +
-```console -pip install covalent -``` -Refer to the [Quick Start](https://docs.covalent.xyz/docs/get-started/quick-start) guide for quick setup instructions, or to the [First Experiment](https://docs.covalent.xyz/docs/get-started/first-experiment) guide for a more thorough approach. For a full list of supported platforms, see the Covalent [compatibility matrix](https://docs.covalent.xyz/docs/user-documentation/compatibility). -## 🚀 Getting started +### Explore Covalent Through Examples -Ready to try it? Go to the [First Experiment](https://docs.covalent.xyz/docs/get-started/first-experiment) guide in the documentation. +Jump right into practical examples to see Covalent in action. These tutorials cover a range of applications, giving you a hands-on experience: -For a more in-depth description of Covalent's features and how they work, see the [Concepts](https://docs.covalent.xyz/docs/user-documentation/concepts/concepts-index) page in the documentation. +
+ + AI Tutorial + + + MNIST Tutorial + + + Quantum Tutorial + +
- - - - - - - - - -
📚 Know more !                                                        ✍️ Tutorials and Examples                                                        
- - - [What is Covalent?](https://www.covalent.xyz/what-is-covalent/) - - [Covalent in the era of cloud-HPC](https://www.covalent.xyz/navigating-the-modern-hpc-landscape/) - - [Basic Concepts of Covalent](https://docs.covalent.xyz/docs/user-documentation/concepts/covalent-basics) - - [How does Covalent work?](#how-does-it-work) - - - - [Covalent with pytorch for classical machine learning](https://docs.covalent.xyz/docs/user-documentation/tutorials/mnist) - - [Covalent with pennylane for quantum machine learning](https://docs.covalent.xyz/docs/user-documentation/tutorials/quantumembedding) - - [Covalent with Qiskit for quantum-SVM](https://docs.covalent.xyz/docs/user-documentation/tutorials/svm/) - - [Covalent with Dask for scaling Ensemble classification](https://docs.covalent.xyz/docs/user-documentation/tutorials/ensemble/) - - [Covalent for Deep Neural Network on AWS](https://docs.covalent.xyz/docs/user-documentation/tutorials/dnn_comparison/) -
+### Explore Our Extensive Plugin Ecosystem +Covalent integrates seamlessly with a variety of platforms. Discover our range of plugins to enhance your Covalent experience: -## How Does It Work? -Covalent Architecture -Covalent has three main components: +
+
+divider +divider +divider +divider +
+
divider +divider +divider +divider
-- A Python module containing an API that you use to build manageable workflows out of new or existing Python functions. -- A set of services that run locally or on a server to dispatch and execute workflow tasks. -- A browser-based UI from which to manage workflows and view results. +### Key Features at a Glance -You compose workflows using the Covalent API by simply adding a single line of python decorator and submit them to the Covalent server. The server analyzes the workflow to determine dependencies between tasks, then dispatches each task to its specified execution backend. Independent tasks are executed concurrently if resources are available. +Get a quick overview of what Covalent offers. Our infographic summarizes the main features, providing you with a snapshot of our capabilities: -The Covalent UI displays the progress of each workflow at the level of individual tasks. +
+
+ development +
-
-

The Covalent API

-The Covalent API is a Python module containing a small collection of classes that implement server-based workflow management. The key elements are two decorators that wrap functions to create managed *tasks* and *workflows*. +
-The task decorator is called an *electron*. The electron decorator simply turns the function into a dispatchable task. +--- -The workflow decorator is called a *lattice*. The lattice decorator turns a function composed of electrons into a manageable workflow. -
-
-

Covalent Services

-The Covalent server is a lightweight service that runs on your local machine or a server. A dispatcher analyzes workflows (lattices) and hands its component functions (electrons) off to executors. Each executor is an adaptor to a backend hardware resource. Covalent has a growing list of turn-key executors for common compute backends. If no executor exists yet for your compute platform, Covalent supports writing your own. -
-
-

The Covalent GUI

-The Covalent user interface runs as a web server on the machine where the Covalent server is running. The GUI dashboard shows a list of dispatched workflows. From there, you can drill down to workflow details or a graphical view of the workflow. You can also view logs, settings, and result sets. -
+### Know More About Covalent + +For a more in-depth description of Covalent's features and how they work, see the [Concepts](https://docs.covalent.xyz/docs/user-documentation/concepts/concepts-index/) page in the documentation. -## 📚 Documentation +
-The official documentation includes tips on getting started, high-level concepts, tutorials, and the API documentation, and more. To learn more, see the [Covalent documentation](https://docs.covalent.xyz/docs). +
+divider +divider +divider +divider +
-## Troubleshooting +
-Solutions to common issues can be found in the [Troubleshooting Guide](https://docs.covalent.xyz/docs/user-documentation/troubleshooting). +### 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.](https://docs.covalent.xyz/docs/get-started/install/) + +**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 +### Contributing -To contribute to Covalent, refer to the [Contribution Guidelines](https://github.com/AgnostiqHQ/covalent/blob/master/CONTRIBUTING.md). We use GitHub's [issue tracking](https://github.com/AgnostiqHQ/covalent/issues) 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 more information on adding tutorials, check the [Tutorial Guidelines](https://github.com/AgnostiqHQ/covalent/blob/master/doc/TUTORIAL_GUIDELINES.md) Participation in the Covalent community is governed by the [Code of Conduct](https://github.com/AgnostiqHQ/covalent/blob/master/CODE_OF_CONDUCT.md). + -## ⚓ Citation +To contribute to Covalent, refer to the [Contribution Guidelines](https://github.com/AgnostiqHQ/covalent/blob/master/CONTRIBUTING.md). We use GitHub's [issue tracking](https://github.com/AgnostiqHQ/covalent/issues) 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](https://github.com/AgnostiqHQ/covalent/blob/master/doc/TUTORIAL_GUIDELINES.md). Participation in the Covalent community is governed by the [Code of Conduct](https://github.com/AgnostiqHQ/covalent/blob/master/CODE_OF_CONDUCT.md). -Please use the following citation in any publications: +### Citation -> https://doi.org/10.5281/zenodo.5903364 +Please use the following citation in any publications. -## 📃 License +[https://doi.org/10.5281/zenodo.5903364](https://zenodo.org/records/8369670) -Covalent is licensed under the Apache 2.0 License. See the [LICENSE](https://github.com/AgnostiqHQ/covalent/blob/master/LICENSE) file or contact the [support team](mailto:support@agnostiq.ai) for more details. +### License +Covalent is licensed under the Apache 2.0 License. See the [LICENSE](https://github.com/AgnostiqHQ/covalent/blob/master/LICENSE) file or contact the [support team](mailto:support@aqnostic.ai) for more details. ->For a detailed history of changes and new features, see the [Changelog](https://github.com/AgnostiqHQ/covalent/blob/master/CHANGELOG.md). +For a detailed history of changes and new features, see the [Changelog](https://github.com/AgnostiqHQ/covalent/blob/master/CHANGELOG.md). diff --git a/doc/source/_static/abstract_infra.png b/doc/source/_static/abstract_infra.png new file mode 100644 index 000000000..dfe3aefb7 Binary files /dev/null and b/doc/source/_static/abstract_infra.png differ diff --git a/doc/source/_static/ai.svg b/doc/source/_static/ai.svg new file mode 100644 index 000000000..dbcb403dc --- /dev/null +++ b/doc/source/_static/ai.svg @@ -0,0 +1,25 @@ + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/doc/source/_static/ai_tutorial.svg b/doc/source/_static/ai_tutorial.svg new file mode 100644 index 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