bytechef
Open-source platform that unifies AI agent orchestration and workflow automation — autonomy and precision in one platform.
GitHubスター
770
ユーザー評価
未評価
お気に入り
0
閲覧数
698
フォーク
139
イシュー
524
The open-source platform that unifies AI agent orchestration and workflow automation
Autonomy and precision — in one platform.
Documentation · Live Demo · Discord · Connect on X · Roadmap
AI Agents — built in, not bolted on
A drag-and-drop AI Agent component runs the full agent loop — model → tool selection → execution → observation → next step — with streaming and structured output.
Build Workflows with Ease using Copilot
Build AI agents and workflows by talking to ByteChef. The Copilot generates workflows from a sentence, drops in configured agent steps, explains failed runs and suggests fixes.
Quick Start
Docker Compose (Fastest Setup)
Requirement: Docker Desktop
This is the fastest way to start ByteChef. Download the docker-compose.yml file from the repository:
curl -O https://raw.githubusercontent.com/bytechefhq/bytechef/master/docker-compose.yml
docker compose -f docker-compose.yml up
Both PostgreSQL database and ByteChef containers will start automatically.
Open http://localhost:8080/login → Create Account → sign in.
Docker (Manual Setup)
If Docker Compose isn't supported in your environment, follow these steps:
1. Create Docker Network
docker network create -d bridge bytechef_network
2. Start PostgreSQL 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
3. Start ByteChef 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: Use -d flag instead of -it to run in detached mode.
Open http://localhost:8080/login → Create Account → sign in.
Build your first agent in 60 seconds
- New Project → New Workflow,
- Add a trigger
- Add the AI Agent component
- Pick a model, attach tools from 200+ connectors, optionally add a knowledge base and guardrails
- Fill the necessary credentials
- Configure each component's parameters in the properties panel
- Test your workflow
- Deploy
Workflow Automation
- Visual editor with JSON underneath, Git-friendly
- Flow controls —
condition·switch·loop·each·parallel·branch· sub-workflows - Triggers — webhook · schedule · polling · app-event · manual · form
- Polyglot code — Java · JavaScript · Python · Ruby on GraalVM
- Durable execution on the Atlas runtime, Postgres-backed, queue-mode for horizontal scale (memory · Redis · RabbitMQ · Kafka · JMS · AMQP · SQS)
- Workflows-as-APIs — workflows can be an authenticated HTTP endpoint
- Git-native — push from the UI, environments backed by branches
The Unification
- Agents inside workflows — an agent is a step; downstream branches react to its decisions
- Workflows as agent tools — a "refund order" workflow with retries and approvals becomes one tool
- Sub-agents — coordinator agents call specialist agents
- Human-in-the-loop — pause on approval, route to Slack/email, resume on response
- One audit log — agent decisions, tool calls, workflow runs, human approvals, all in one trail
180+ connectors
CRM · marketing · communication · e-commerce · cloud storage · databases · AI/ML · helpdesk · finance. Every connector is also an agent tool, also an MCP tool. Browse the full catalog.
Open core — Apache 2.0 + EE
| Capability | CE (Apache 2.0) | EE |
|---|---|---|
| Visual editor, AI agents, workflows, 200+ connectors | ✅ | ✅ |
| Polyglot code (Java/JS/Python/Ruby) | ✅ | ✅ |
| Knowledge bases, vector stores, guardrails, MCP server | ✅ | ✅ |
| Agent skills, agent evaluations | 🚧 in development | 🚧 in development |
| Self-host (Docker / Kubernetes / Helm) | ✅ | ✅ |
| Workflows-as-APIs | — | ✅ |
| Git-native | — | ✅ |
| Microservices deployment | — | 🚧 in development |
| AI Copilot | — | ✅ |
| SSO / SAML / OIDC, SCIM, advanced RBAC | — | 🚧 in development |
| Connection scope sharing (Workspace / Project / Organization) | — | 🚧 in development |
| Multi-environment promotion, audit log with correlation IDs | — | ✅ |
| AI Gateway - model routing, quotas, cost controls | — | 🚧 in development |
| Embedded iPaaS - ship integrations and AI agents inside your SaaS product | — | ✅ |
Contributing
If you would like to contribute to the software, read the contributing guide to get started.
License
This project is licenced under Apache 2.0 for the core (everything outside /ee/) and the ByteChef Enterprise License for code under /ee/ (microservices, embedded, AI Copilot, SSO/SCIM, advanced RBAC)
Contributors
Credits
ByteChef started as a fork of Piper.
0
フォロワー
0
リポジトリ
0
Gist
0
貢献数
LangChain4j is an open-source Java library that simplifies the integration of LLMs into Java applications through a unified API, providing access to popular LLMs and vector databases. It makes implementing RAG, tool calling (including support for MCP), and agents easy. LangChain4j integrates seamlessly with various enterprise Java frameworks.



