Coze Studio – ByteDance’s Open-Source AI Agent Development Platform

What is Coze Studio?

Coze Studio (also known as the Kouzi Development Platform) is an open-source AI agent development platform released by ByteDance. It empowers developers to rapidly build, deploy, and manage AI agents. The platform offers an all-in-one development environment that supports key technologies such as Prompts, RAG (Retrieval-Augmented Generation), Plugins, and Workflows. With visual workflow orchestration, developers can create complex AI applications with zero or minimal code.

Coze Studio features a built-in plugin framework, allowing developers to encapsulate third-party APIs or proprietary capabilities as plugins to extend agent functionality. Built with Golang and React, the platform follows Domain-Driven Design (DDD) principles and is easy to customize for secondary development. It supports both local and private deployment with low system requirements—only a dual-core CPU and 4GB of memory are needed—and includes one-click deployment scripts.

Key Features of Coze Studio

• All-in-One Development Environment:
  Covers the entire process from development to deployment. Supports core technologies like Prompting, RAG, Plugins, and Workflow orchestration.

• Visual Workflow Builder:
  Enables developers to build complex logic through drag-and-drop nodes. Supports low-code or no-code development.

• AI Agent Creation & Management:
  Offers robust templates and orchestration frameworks to quickly create, launch, and manage AI agents.

• Multi-Model Integration:
  Compatible with multiple mainstream large language models (e.g., OpenAI, Volcano Engine), and provides a unified model abstraction interface.

• Knowledge Base with RAG:
  Integrates RAG capabilities and vector search. Developers can upload documents or data to power knowledge-based agent responses.

• Plugin System:
  Supports creating, configuring, and managing plugins. Plugins can wrap third-party APIs or internal functions to enhance agent capabilities.

• Database Integration:
  Includes built-in support for databases to enable data storage and querying.

• API & SDK Integration:
  Offers APIs for chat and workflow operations, with SDKs for Python, JavaScript, Java, etc., to support secondary development.

• Real-Time Interaction:
  Supports real-time chat, speech synthesis, and transcription via WebSocket.

Project Repository for Coze Studio

• GitHub Repository: https://github.com/coze-dev/coze-studio

How to Use Coze Studio

1. Prepare Your Environment

   • Minimum requirements: Dual-core CPU and 4GB memory.

   • Install Docker and Docker Compose, and ensure the Docker service is running.

2. Clone the Source Code

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


3. Configure the Model

   • Navigate to the project directory:

     cd coze-studio


   • Copy the model configuration template:

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


   • Edit the config file:

     • Go to backend/conf/model

     • Open ark_doubao-seed-1.6.yaml and modify the following fields:

       • id: Model ID (must be a unique non-zero integer).

       • meta.conn_config.api_key: Your model’s API key.

       • meta.conn_config.model: Model identifier.

4. Deploy and Start the Service

   • Enter the docker directory, copy the environment variable templates, and start the service.

   • Initial deployment may take time to pull and build images. Once you see “Container coze-server Started,” the service is live.

5. Access the Platform

   • Visit http://localhost:8888/ in your browser to open the Coze Studio front-end.

6. Register and Log In

   • Sign up using your email or phone number.

7. Create an AI Agent

   • Click “Create Bot” in the top left, and enter basic info (e.g., name, avatar).

8. Configure the Agent

   • Set the bot’s role, abilities, and prompt constraints.

   • Add official or custom plugins.

   • Configure workflows, knowledge bases, and databases.

9. Test and Debug

   • Use the debug page to chat with your bot and test its capabilities.

10. Use Plugins in Bots and Workflows

    • In the bot editor, go to the plugin section, click “+” to add plugins, and configure parameters.

    • In the workflow editor, add plugin nodes, define inputs and outputs, and test.

11. Publish the Application

    • Once setup is complete, click “Publish” to release the agent to the Coze App Store.

Application Scenarios for Coze Studio

• Rapid Prototyping (POC):
  Quickly build and validate AI application ideas.

• SMB AI Solutions:
  Small and medium businesses can use Coze Studio to apply large model capabilities to real-world problems.

• Private Deployment:
  Ideal for organizations with high data privacy requirements. Supports deployment within private networks.

• Internal Enterprise Chatbots:
  Build intelligent agents based on company SOPs, incorporating approval flows, form-filling, email automation, etc.

• AI-Driven Interactive Surveys:
  Guide users through survey completion using workflows, generate charts with plugins, and sync data to backend BI systems.