gerev VS specification

https://github.com/gerevai/gerev to see for yourself.

Or you could try our sweet little demo: https://demo.gerev.ai

Some legit funny stuff is hiding here.

You can use gerev to host your own workplace search engine: <https://github.com/gerevai/gerev>

Disclaimer: no I didn't leak YC's internal intranet! all output by partners was generated by ChatGPT. don't sue me!

gerev - self hosted search engine

Or easily bring up important docs in real-time during meetings.

I believe private data should remain private. All too often, AI products send private data to cloud-based LLMs. I believe that AI should assist users without breaching their privacy.

Feel free to check it out <https://github.com/gerevai/gerev>

https://github.com/gerevai/gerev - growing super fast.

Here's a discussion with more comparisons: https://github.com/serverlessworkflow/specification/issues/2...

Once you have defined the workflow on a diagram, a JSON, following the Serverless workflow specification, is stored in KuFlow. With this specification, we can use all the great tools/libs that are developed.

Among workflow languages out there, we choose Serverless Workflow. It's a vendor-neutral, open-source and community-driven workflow ecosystem. The workflow definition can be written in JSON or YAML format. And then there are SDKs available in various programming languanges, like Java, Go, TypeScript, .NET, Python.

This example happens to be from Google, but you can compare similar config-driven syntaxes from Argo, Amazon, and Airflow. The bottom line is you ultimately find yourself hand-writing the Abstract Syntax Tree of something you can read much better in code anyway: