Coze Studio is a one-stop AI agent development tool that provides the latest large language models and tools, multiple development modes and frameworks, and offers a convenient AI agent development environment for the entire process from development to deployment.
Key Capabilities It provides all the core technologies required for AI agent development: prompts, RAG, plugins, and workflows, enabling developers to focus on creating the core value of AI. The platform provides complete application templates and building frameworks, supports professional AI agent development at the lowest cost, and enables rapid construction of various AI agents. Through visual design and building tools, developers can quickly create and debug agents, applications, and workflows using no-code or low-code methods, enabling powerful AI application development and more customized business logic.
Technical Architecture The Coze Studio backend is developed using Golang, and the frontend uses React + TypeScript. The overall architecture is based on microservices and follows the principles of Domain-Driven Design (DDD), providing a high-performance, highly scalable, and easily customizable underlying framework. Its agent and workflow runtime engine, model abstraction and implementation, and knowledge base indexing and retrieval are supported by the Eino framework team; the frontend workflow canvas editor is provided by the FlowGram team as the building engine; the HTTP framework is provided by the Hertz team.
Usage and Deployment Environment requirements: minimum 2-core CPU, 4 GB memory; Docker and Docker Compose must be pre-installed and the Docker service must be started. Deployment steps:
- Clone the code:
git clone https://github.com/coze-dev/coze-studio.git - Deploy and start the service: enter the directory
cd coze-studio; on macOS or Linux, runmake web; on Windows, runcp ./docker/.env.example ./docker/.envthendocker compose -f ./docker/docker-compose.yml up. The first startup requires pulling images and building local images, which takes a long time. Seeing "Container coze-server Started" indicates success. - Visit http://localhost:8888/sign to register an account.
- Visit http://localhost:8888/admin/#model-management to configure models (the image version must be >= 0.5.0).
- Visit http://localhost:8888/ to use Coze Studio. When deploying in a public network environment, it is recommended to first assess security risks and take protective measures, involving account registration functionality, the Python execution environment in workflow code nodes, the Coze Server listening address configuration, SSRF, and some horizontal privilege escalation in the API.
Developer Guide Model services must be configured; otherwise, models cannot be selected when building agents, workflows, and applications. To use the official plugins in the plugin store, you must first configure the plugins and add authentication keys for third-party services. Basic components such as the image uploader can be configured. The Community Edition API and Chat SDK use a Personal Access Token for authentication and provide conversation- and workflow-related APIs. The development guide includes project architecture, code development and testing, troubleshooting, and other content.
Applicable Scenarios It can be used to quickly build AI assistant agents, develop workflows (quickly built through a visual canvas by dragging and dropping nodes), and use resources such as plugins, databases, knowledge bases, and variables. Agents can combine knowledge, plugins, and other functions to solve the problems of model hallucination and insufficient professional domain knowledge, and provide memory functionality to generate more accurate replies based on the user's historical conversations. It supports integrating agents or applications with local business systems through the Chat SDK, for example, building a web-based online customer service.
Limitations Some features of the open source version (such as voice customization) are limited to the commercial version. For differences between the open source version and the commercial version, see the feature list. The project uses the Apache 2.0 license.
