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API integration and workflow automation platform

API integration and workflow automation platform

Website - Documentation - Discord - Twitter

UPDATE: ByteChef is under active development. We are in the alpha stage, and some features might be missing or disabled.

ByteChef Screenshot

What is ByteChef?

ByteChef is an open-source, low-code, extendable API integration and workflow automation platform. ByteChef can help you as:

  • An automation solution that allows you to integrate and build automation workflows across your SaaS apps, internal APIs, and databases.
  • An embedded solution targeted explicitly for SaaS products, allowing your customers to integrate applications they use with your product.

Key Features

  • Intuitive UI Workflow Editor: build and visualize workflows via the UI editor by dragging and dropping components and defining their relations.
  • Event-Driven & Scheduled Workflows: automate scheduled and real-time event-driven workflows via a simple trigger definition.
  • Multiple flow controls: use the range of various flow controls such as condition, switch, loop, each, parallel, etc.
  • Built-In Code Editor: if you need to go beyond no-code workflow definition, leverage our low-code capabilities and write workflow definitions in JSON format and blocks of the code executed during the workflow execution in one of the languages: Java, JavaScript, Python, and Ruby with syntax highlighting, auto-completion and real-time syntax validation.
  • Rich Component Ecosystem: hundreds of components built in to extract data from any database, SaaS applications, internal APIs, or cloud storage.
  • Extendable: develop custom connectors when no built-in connectors exist in the above-mentioned languages.
  • AI ready: built-in AI components that can run multiple AI models and other AI algorithms.
  • Developer ready: expose your workflows as APIs to be consumed by other applications or call directly APIs of targeted services. The platform handles authentication.
  • Version Control Friendly: write your workflows from the UI editor and push them to your preferred Git branch directly from ByteChef, enabling best practices with CI/CD pipelines and version control systems.
  • Self-hosted: install ByteChef on the premise to have complete control over execution and data, in addition to being able to use a hosted version.
  • Scalable: it is designed to handle millions of workflows with high availability and fault tolerance. Start with one instance only, and scale as required.
  • Structure & Resilience: bring resilience to your workflows with labels, sub-flows, retries, timeout, error handling, inputs, outputs that generate artifacts in the UI, variables, conditional branching, advanced scheduling, event triggers, dynamic tasks, sequential and parallel tasks, and skip tasks or triggers when needed by disabling them.

Getting Started

There are couple ways to give ByteChef a quick spin on your local machine. You can use this to test, learn or contribute.

Docker

Method 1 - Start Containers With Docker Compose

Requirement: Docker Desktop - Docker compose allows you to configure and run several dependent docker containers. Some OS environments may not support it. In that case follow Method 2 described later.

This is the fastest possible way to start Bytechef. There is docker-compose.yml in the repository root. Either checkout repository locally to your machine or download file. Make sure you execute this command taking care of correct path to docker-compose.yml file:

docker compose -f docker-compose.yml up

Both postgres database and bytechef docker container would start.

Method 2 - Start Containers With Classic Docker

This option demands pinch of focus as it allows user to profile containers. Run the following commands from your terminal to have ByteChef up and running right away.

Create Docker Network
docker network create -d bridge bytechef_network
Start Postgres Docker Container
docker run --name postgres -d -p 5432:5432 \
    --env POSTGRES_USER=postgres \
    --env POSTGRES_PASSWORD=postgres \
    --hostname postgres \
    --network bytechef_network \
    -v /opt/postgre/data:/var/lib/postgresql/data \
    postgres:15-alpine

NOTE: -v mount option is not mandatory. It mounts local DB storage to make easier access to DB infrastructure files.

Start ByteChef Docker Container
docker run --name bytechef -it -p 8080:8080 \
    --env BYTECHEF_DATASOURCE_URL=jdbc:postgresql://postgres:5432/bytechef \
    --env BYTECHEF_DATASOURCE_USERNAME=postgres \
    --env BYTECHEF_DATASOURCE_PASSWORD=postgres \
    --env BYTECHEF_SECURITY_REMEMBER_ME_KEY=e48612ba1fd46fa7089fe9f5085d8d164b53ffb2 \
    --network bytechef_network \
    docker.bytechef.io/bytechef/bytechef:latest

NOTE: -it (interactive) flag may be replaced with -d (detached). Keep it interactive if you want to track logs which can be handy for troubleshooting. Use -p 8080:8080 to customize port.

Access Bytechef

Use browser and open http://localhost:8080/login (please take care about port - if port setting is modified in docker compose file or docker run command, this URL should be updated). Chose Create Account link to setup user and than use same user and password to sign in.

Documentation

Documentation is available at docs.bytechef.io. It covers all the necessary information to get started with ByteChef, including installation, configuration, and usage.

Community support

For help, you can use one of these channels to ask a question:

  • Discord - Discussions with the community and the team.
  • GitHub - For bug reports and feature requests.
  • Twitter - Get the product updates easily.

Roadmap

Check out our roadmap to get informed of the latest features released and the upcoming ones.

Contributing

If you'd like to contribute, kindly read our Contributing Guide to learn and understand about our development process, how to propose bug fixes and improvements, and how to build and test your changes to ByteChef.

License

ByteChef is released under Apache License v2.0. See LICENSE for more information.

Contributors

Made by community 💛

Note

This project has started as a fork of Piper, an open-source, distributed workflow engine.

anl-readme-md