Coze Studio: Build and Deploy AI Agents with Golang and React

7月28日 Published inAI Agent Tools

Coze Studio is a unified development environment designed for building AI agents. It includes integrated support for modern large language models (LLMs), a comprehensive toolkit for various development patterns, and a streamlined path from initial prototype to production.

For developers creating complex AI agents, Coze Studio provides ready-made templates and a structured framework. This enables faster development cycles and lower overhead, allowing you to transform an idea into a functional agent without manually rebuilding underlying infrastructure for every project.

The platform simplifies the creation, debugging, and deployment of AI agents. Its visual design canvas supports low-code or no-code development, making it easy to assemble agents, applications, and workflows. You can also inject custom business logic where necessary. If your goal is to build low-code AI products, Coze Studio serves as an ideal starting point.

Coze Studio is powered by a Golang backend, while the frontend is built using React and TypeScript. The architecture relies on microservices and adheres to Domain-Driven Design (DDD) principles.

Feature Modules

Module	Function
Model Service	Manages model inventories; integrates with OpenAI, Volcano Engine, and other providers.
Agent Builder	Builds, publishes, and manages agents; configures workflows, knowledge bases, and resources.
App Builder	Creates and publishes applications; defines business logic through custom workflows.
Workflow Builder	Provides tools to create, modify, publish, and delete automated workflows.
Resource Development	Manages plugins, knowledge bases, databases, and prompt engineering.
API & SDK	Offers OpenAPI endpoints for chat and conversation; allows embedding via the Chat SDK.

System Requirements

Before installing Coze Studio, ensure your hardware meets the following minimum specifications: 2 CPU cores and 4 GB of RAM. Docker and Docker Compose must be installed and active on your system.

Installing Coze Studio

1. Clone the repository

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

2. Configure the model

Copy the configuration template for the Doubao-seed-1.6 model from the template directory into your active configuration folder.

cd coze-studio
cp backend/conf/model/template/model_template_ark_doubao-seed-1.6.yaml backend/conf/model/ark_doubao-seed-1.6.yaml

Next, edit the new file. Navigate to backend/conf/model and open ark_doubao-seed-1.6.yaml. Configure the following fields:

id: A unique model identifier within Coze Studio. Assign a non-zero integer. Do not modify this ID after the model has been deployed.
meta.conn_config.api_key: Your API key for the model service. If using Volcano Engine Ark, refer to their documentation to generate a key.
meta.conn_config.model: The endpoint ID for the model service. For Volcano Engine’s Doubao-seed-1.6, use the specific Endpoint ID found in your access point settings.

3. Deploy and start services

The initial launch will pull the necessary images and build local containers. This process takes several minutes, and logs will appear in your terminal. Wait until the message Container coze-server Started appears.

cd docker
cp .env.example .env
docker compose --profile "*" up -d

Following the startup, certain setup containers will show an exit 0 status. This is normal behavior for the following: coze-elasticsearch-setup, coze-minio-setup, coze-mysql-setup-init-sql, and coze-mysql-setup-schema.

Once all services are operational, access the interface at http://localhost:8888/ in your web browser.

Developer Guide

Project Configuration

Model Configuration: At least one model service must be configured prior to deployment. If no models are configured, they will not appear as options when building agents, workflows, or apps.
Plugin Configuration: To utilize official tools from the plugin store, you must first input the required third-party authentication keys.
Base Component Configuration: Configure essential components, such as the image uploader, to enable specific platform features.

API Reference

The open-source version of Coze Studio utilizes Personal Access Tokens (PAT) for authentication. It supports both chat and workflow APIs. Please note that commercial-grade features are not included in this version.

Using Coze Studio Open Source

For comprehensive usage instructions, please visit the official Coze documentation center. Note that certain capabilities—such as advanced tone customization—are reserved for the commercial edition. Refer to the feature comparison list for a full breakdown of differences.

Quick Start: Construct a functional AI assistant agent in just a few minutes.
Developing Agents: Learn how to create, build, and manage agents. Integrate knowledge bases and plugins to minimize hallucinations and bridge domain knowledge gaps. Coze Studio’s memory management helps agents retain context from previous interactions for higher accuracy.
Developing Workflows: A workflow consists of executable steps designed to handle specific business logic or tasks. You can build data processing pipelines for applications or agents using the visual canvas to drag and drop nodes into place.
Plugins and Resources: Within the Coze Studio environment, workflows, plugins, databases, knowledge bases, and variables are categorized together as resources.
API and SDK: Use the supported chat and workflow APIs along with the Chat SDK to embed agents or applications directly into your existing systems.
Tutorials: Access practical guides for various AI implementations, such as deploying a web-based customer service bot using the Chat SDK.