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coze-studio

coze-devApache-2.0活跃维护

一站式可视化 AI Agent 开发平台，用拖拽式工具完成智能体的创建、调试和部署，大幅降低搭建聊天机器人与多模态应用的门槛。

An AI agent development platform with all-in-one visual tools, simplifying agent creation, debugging, and deployment like never before. Coze your way to AI Agent creation.

v0.5.1发布于 2026-02-05 06:04 UTC21,813star +7 / 7 天3,135fork同步于 2026-11-10 11:23 UTC
智能体平台可视化编排低代码聊天机器人多模态
对比 GitHubagentagent-platformai-pluginschatbotchatbot-framework

怎么上手

由 README 提炼，执行前请确认
原文 
git clone https://github.com/coze-dev/coze-studio.git
cd coze-studio
make web
硬件要求按 README 说明

最低 2 核 CPU、4 GB 内存；需预装并启动 Docker 与 Docker Compose。README 未说明 GPU 或显存要求。

有 Docker 镜像
下载：源码 zip·GitHub Releases（安装包）本站不镜像安装包

项目说明

由 README 自动翻译提炼
没人工点评？写下你的经验

开源版 Coze 智能体开发平台，可视化搭建、调试和部署 AI Agent

一站式可视化 AI Agent 开发平台，用拖拽式工具完成智能体的创建、调试和部署，大幅降低搭建聊天机器人与多模态应用的门槛。

核心能力

  • 可视化画布拖拽搭建工作流
  • 支持提示词、RAG、插件、知识库、数据库等资源
  • 内置模型服务管理，可接入 OpenAI 与火山引擎
  • 提供 OpenAPI 与 Chat SDK 集成到自有业务
  • Go 微服务后端 + React/TypeScript 前端，DDD 架构

容易踩的坑

首次启动需拉取并构建镜像，耗时较长；部署后必须先在 admin 页面配置模型服务，否则搭建 Agent 时无法选择模型；公网部署存在账号注册、代码节点 Python 执行、SSRF 等安全风险，需自行评估防护；Windows 需先复制 .env.example 为 .env 再用 docker compose 启动。

内容由模型根据 README 生成，可能不完整或不准确，以官方文档为准。看原文 README

最近发版

5 个版本v0.5.1
全部 release
  1. v0.5.1V0.5.1最新正式版2026-02-05 · 2026-02-05 06:04 UTC

    Image Version

    cozedev/coze-studio-server:0.5.1 cozedev/coze-studio-web:0.5.1

    What's Changed

  2. v0.5.02025-10-29 · 2025-10-29 06:48 UTC
    查看更新说明

    Image Version

    cozedev/coze-studio-server:0.5.0 cozedev/coze-studio-web:0.5.0

    New Features

    What's Changed

  3. v0.5.0-betapre-release2025-10-21 · 2025-10-21 12:53 UTC
    查看更新说明

    Image Version

    cozedev/coze-studio-server:0.5.0.beta.5 cozedev/coze-studio-web:0.5.0.beta

    New Features

    What's Changed

  4. v0.3.02025-09-11 · 2025-09-11 12:47 UTC
    查看更新说明

    Image Version

    cozedev/coze-studio-server:0.3.16 cozedev/coze-studio-web:0.0.3

    New Features

    • Chatflow Support: We've support the chatflow feature in workflow, agent, and app scenarios.
    • ChatSDK Upgrade: Upgraded the usage method of ChatSDK and the function of conversation management
    • Infra: Elasticsearch supports multi-node setup
    • Infra: milvus support to use token as auth
    • Infra: Oceanbase Vector Sql Prevent SQL injection And Complementary helm deployment

    Fixes

    • Plugin: refresh oauth access token
    • Workflow: Remove the x-wf-file_name carried in the URL after file upload in the remove workflow.
    • CI/CD: When adding a new DDL, import it through Atlas.
    • Singleagent: Fix the shortcut command issue in chaksdk.

    What's Changed

  5. v0.3.0-beta.1pre-release2025-08-29 · 2025-08-29 09:00 UTC
    查看更新说明

    Image Version

    cozedev/coze-studio-server:0.3.14.beta cozedev/coze-studio-web:0.0.3.beta

    New Features

    • Chatflow Support: We've support the chatflow feature in workflow, agent, and app scenarios.
    • ChatSDK Upgrade: Upgraded the usage method of ChatSDK and the function of conversation management

    What's Changed

    New Contributors

    Full Changelog: https://github.com/coze-dev/coze-studio/compare/v0.2.5...v0.3.0-beta.1

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    README 原文

    未翻译
    在 GitHub 打开

    Image

    English | 中文

    What is Coze Studio?

    Coze Studio is an all-in-one AI agent development tool. Providing the latest large models and tools, various development modes and frameworks, Coze Studio offers the most convenient AI agent development environment, from development to deployment.

    • Provides all core technologies needed for AI agent development: prompt, RAG, plugin, workflow, enabling developers to focus on creating the core value of AI.
    • Ready to use for professional AI agent development at the lowest cost: Coze Studio provides developers with complete app templates and build frameworks, allowing you to quickly construct various AI agents and turn creative ideas into reality.

    Coze Studio, derived from the "Coze Development Platform" which has served tens of thousands of enterprises and millions of developers, we have made its core engine completely open. It is a one-stop visual development tool for AI Agents that makes creating, debugging, and deploying AI Agents unprecedentedly simple. Through Coze Studio's visual design and build tools, developers can quickly create and debug agents, apps, and workflows using no-code or low-code approaches, enabling powerful AI app development and more customized business logic. It's an ideal choice for building low-code AI products tailored . Coze Studio aims to lower the threshold for AI agent development and application, encouraging community co-construction and sharing for deeper exploration and practice in the AI field.

    The backend of Coze Studio is developed using Golang, the frontend uses React + TypeScript, and the overall architecture is based on microservices and built following domain-driven design (DDD) principles. Provide developers with a high-performance, highly scalable, and easy-to-customize underlying framework to help them address complex business needs.

    Feature list

    ModuleFeature
    Model serviceManage the model list, integrate services such as OpenAI and Volcengine
    Build agent* Build, publish, and manage agent * Support configuring workflows, knowledge bases, and other resources
    Build apps* Create and publish apps * Build business logic through workflows
    Build a workflowCreate, modify, publish, and delete workflows
    Develop resourcesSupport creating and managing the following resources: * Plugins * Knowledge bases * Databases * Prompts
    API and SDK* Create conversations, initiate chats, and other OpenAPI * Integrate agents or apps into your own app through Chat SDK

    Quickstart

    Learn how to obtain and deploy the open-source version of Coze Studio, quickly build projects, and experience Coze Studio's open-source version.

    Environment requirements:

    • Before installing Coze Studio, please ensure that your machine meets the following minimum system requirements: 2 Core、4 GB
    • Pre-install Docker and Docker Compose, and start the Docker service.

    Deployment steps:

    1. Retrieve the source code.

      # Clone code
git clone https://github.com/coze-dev/coze-studio.git

    2. Deploy and start the service. When deploying and starting Coze Studio for the first time, it may take a while to retrieve images and build local images. Please be patient. If you see the message "Container coze-server Started," it means the Coze Studio service has started successfully.

      cd coze-studio
# start service
# for macOS or Linux
make web  
# for windows
cp ./docker/.env.example ./docker/.env
docker compose -f ./docker/docker-compose.yml up

      For common startup failure issues, please refer to the FAQ.

    3. Register an account by visiting http://localhost:8888/sign, entering your username and password, and clicking the Register button.

    4. Configure the model at http://localhost:8888/admin/#model-management by adding a new model. (The image version must be greater than or equal to 0.5.0.)

    5. Visit Coze Studio at http://localhost:8888/.

    [!WARNING] If you want to deploy Coze Studio in a public network environment, it is recommended to assess security risks before you begin, and take corresponding protection measures. Possible security risks include account registration functions, Python execution environments in workflow code nodes, Coze Server listening address configurations, SSRF (Server - Side Request Forgery), and some horizontal privilege escalations in APIs. For more details, refer to Quickstart.

    Developer Guide

    • Project Configuration:
      • Model Configuration: Before deploying the open-source version of Coze Studio, you must configure the model service. Otherwise, you cannot select models when building agents, workflows, and apps.
      • Plugin Configuration: To use official plugins from the plugin store, you must first configure the plugins and add the authentication keys for third-party services.
      • Basic Component Configuration: Learn how to configure components such as image uploaders to use functions like image uploading in Coze Studio .
    • API Reference: The Coze Studio Community Edition API and Chat SDK are authenticated using Personal Access Token, providing APIs for conversations and workflows.
    • Development Guidelines:
      • Project Architecture: Learn about the technical architecture and core components of the open-source version of Coze Studio.
      • Code Development and Testing: Learn how to perform secondary development and testing based on the open-source version of Coze Studio.
      • Troubleshooting: Learn how to view container states and system logs.

    Using the open-source version of Coze Studio

    Regarding how to use Coze Studio, refer to the Coze Development Platform Official Documentation Center for more information. Please note that certain features, such as tone customization, are limited to the commercial version. Differences between the open-source and commercial versions can be found in the Feature List.

    • Quick Start: Quickly build an AI assistant agent with Coze Studio.
    • Developing Agents: Learn how to create, build, publish, and manage agents. You can use functions such as knowledge, plugins, etc., to resolve model hallucination and lack of expertise in professional fields. In addition, Coze Studio provides rich memory features that enable agents to generate more accurate responses based on a personal user's historical conversations during interactions.
    • Develop workflows: A workflow is a set of executable instructions used to implement business logic or complete specific tasks. It structures data flow and task processing for apps or agents. Coze Studio provides a visual canvas where you can quickly build workflows by dragging and dropping nodes.
    • Resources such as plugins: In Coze Studio, workflows, plugins, databases, knowledge bases, and variables are collectively referred to as resources.
    • API & SDK: Coze Studio supports API related to chat and workflows, and you can also integrate agents or apps with local business systems through Chat SDK.
    • Tutorials for practice: Learn how to use Coze Studio to implement various AI scenarios, such as building web-based online customer service using Chat SDK.

    License

    This project uses the Apache 2.0 license. For details, please refer to the LICENSE file.

    Community contributions

    We welcome community contributions. For contribution guidelines, please refer to CONTRIBUTING and Code of conduct. We look forward to your contributions!

    Security and privacy

    If you discover potential security issues in the project, or believe you may have found a security issue, please notify the ByteDance security team through our security center or vulnerability reporting email. Please do not create public GitHub Issues.

    Join Community

    We are committed to building an open and friendly developer community. All developers interested in AI Agent development are welcome to join us!

    🐛 Issue Reports & Feature Requests

    To efficiently track and resolve issues while ensuring transparency and collaboration, we recommend participating through:

    💬 Technical Discussion & Communication

    Join our technical discussion groups to share experiences with other developers and stay updated with the latest project developments:

    Feishu Group Chat
    Scan the QR code below with Feishu mobile app to join:

    Image

    Discord Server
    Click to join: Coze Community

    Telegram Group
    Click to join: Telegram Group Coze

    Acknowledgments

    Thank you to all the developers and community members who have contributed to the Coze Studio project. Special thanks:

    • The Eino framework team - providing powerful support for Coze Studio's agent and workflow runtime engines, model abstractions and implementations, and knowledge base indexing and retrieval
    • The FlowGram team - providing a high-quality workflow building engine for Coze Studio's frontend workflow canvas editor
    • The Hertz team - Go HTTP framework with high-performance and strong-extensibility for building micro-services
    • All users who participated in testing and feedback

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