Feast PyTorch Ecosystem Application

[franciscojavierarceo]

Contact emails

arceofrancisco@gmail.com, sduxuhao@gmail.com

Project summary

Feast is an open source feature store that delivers structured data to AI and LLM applications at scale for training and inference

Project description

Feast (Feature Store) is an open-source feature store that helps teams operate production ML systems at scale by allowing them to define, manage, validate, and serve features for production AI/ML.

Feast's feature store is composed of two foundational components: (1) an offline store for historical feature extraction used in model training and an (2) online store for serving features at low-latency in production systems and applications.

Feast is a configurable operational data system that re-uses existing infrastructure to manage and serve machine learning features to realtime models.

Are there any other projects in the PyTorch Ecosystem similar to yours? If, yes, what are they?

No.

Project repo URL

https://github.com/feast-dev/feast

Additional repos in scope of the application

N/A

Project license

Apache License 2.0

GitHub handles of the project maintainer(s)

franciscojavierarceo, HaoXuAI, shuchu, woop, zhilingc, tokoko, achals,

Is there a corporate or academic entity backing this project? If so, please provide the name and URL of the entity.

Red Hat https://www.redhat.com/en (there are others as well)

Website URL

https://feast.dev/

Documentation

Yes, we have extensive documentation available here: https://docs.feast.dev/

How do you build and test the project today (continuous integration)? Please describe.

We use a robust CI/CD and release process which is available in our repo: https://github.com/feast-dev/feast

Version of PyTorch

Torch 2.7.1

Components of PyTorch

At the moment, it is required for embedding data for scaling RAG applications. As feature engineering and data transformations become more enriched with small models, we expect more and more feature engineering to use more components of torch tensors and torch model inference.

How long do you expect to maintain the project?

The project is successful with wide adoption and has been maintained since 2018.

Additional information

No response

[HaoXuAI]

Hi team, Hao Xu from Apple and maintainer of Feast is interested in contributing.

[shuchu]

same here. Very happy to work with the PyTorch project.

[lantiga]

Thank you @franciscojavierarceo for the submission!

You seem to tick all the boxes in terms of requirements : )

The only nit is that the code of conduct is mentioned in community.md as opposed to being in a code_of_conduct.md file. Up to you if you want to highlight it more clearly.

Functional Requirements:

✅ 1. PyTorch Support: Project must demonstrate benefit to the pytorch community and be validated with the latest versions of PyTorch.
✅ 2. Working CI: Projects must have a demonstrable working CI workflow for all declared architectures
✅ 3. Governance: Projects must have documented technical governance defined and implemented and it must be represented in their Github or Gitlab repository. Example: Review the LF’s Minimum Viable Governance framework.
✅ 4. User experience: The value proposition should be made clear for the project and documented in the README of the project repository.
✅ 5. Quick start: Project should have a working and demonstrable quick start.
✅ 6. Documentation: Projects must have clear and comprehensive documentation.
✅ 7. Permissive licensing: Users must be able to utilize ecosystem projects without licensing concerns. e.g. BSD-3, Apache-2 and MIT licenses
✅ 8. Functional Testing: Users should have developed tests submitted as a part of their project, and be confident that the project will work well with the latest releases of PyTorch.
✅ 9. Packages: Projects need to have support for binary installation options (pip/Conda).
✅ 10. Ongoing maintenance: Project maintainers must be committed to supporting and maintaining their projects for the next 12 months at a minimum. Projects must commit to updating their projects to the latest two releases of PyTorch (e.g. versions 2.6, 2.5.1).

Measurable Requirements:

✅ 1. Core Maintainers: The project must have a minimum of 2 core maintainers
✅ 2. Contributors: The project should have a minimum of 5 total contributors active in the last 90 days.
✅ 3. Commits: The project must have 30 commits in the last 90 days.
✅ 4. Stars: The project must have a minimum of 200 stars on github

Github Layout Requirements:

✅ 1. LICENSE.md at the root of the repository specifying the terms and conditions for using, distributing, and modifying the software. In addition, you should provide information on the license of any third-party code included in the project.
✅ 2. README.md welcomes new community members to the project and explains why the project is useful and how to get started. Should include information about release methodology, cadence, and criteria in the README.
✅ 3. CONTRIBUTING.md explains how to contribute to the project. The file explains the types of contributions needed and how the development process works.
✅ 4. CODEOWNERS that define individuals or teams responsible for code in a repository; document current project owners and Retired committers.
🟡 5. CODE_OF_CONDUCT.md sets the ground rules for participants’ behavior and helps facilitate a friendly, welcoming environment. By default, projects should leverage the [Linux](https://lfprojects.org/policies/code-of-conduct/) [[Foundation](https://lfprojects.org/policies/code-of-conduct/)](https://lfprojects.org/policies/code-of-conduct/) [[Code](https://lfprojects.org/policies/code-of-conduct/)](https://lfprojects.org/policies/code-[of](https://lfprojects.org/policies/code-of-conduct/)-conduct/) [of](https://lfprojects.org/policies/code-of-conduct/) [[Conduct](https://lfprojects.org/policies/code-of-conduct/)](https://lfprojects.org/policies/code-of-conduct/) unless an alternate Code of Conduct is approved prior.

[franciscojavierarceo]

Thank you @lantiga I have updated our repo to link to the LF Projects code of conduct. You can see it here: https://github.com/feast-dev/feast/blob/master/CODE_OF_CONDUCT.md

let me know if you need anything else!

[michellearoth]

Approved!

[franciscojavierarceo]

Thank you @michellearoth !!!