Welcome to the AgentKit Samples repository!
AgentKit is an enterprise-level AI Agent development platform launched by Volcengine, providing developers with complete solutions for Agent construction, deployment, and operation. Through standardized development toolchains and cloud-native infrastructure, the platform significantly lowers the development and deployment threshold for complex intelligent agent applications.
This repository contains a collection of examples and tutorials to help you understand, implement, and integrate AgentKit functionalities into your applications.
.
├── 01-tutorials
│ └── README.md
├── 02-use-cases
│ ├── ai_coding
│ ├── beginner
│ │ ├── a2a_simple
│ │ ├── callback
│ │ ├── episode_generation
│ │ ├── hello_world
│ │ ├── mcp_simple
│ │ ├── multi_agents
│ │ ├── restaurant_ordering
│ │ ├── travel_concierge
│ │ ├── vikingdb
│ │ ├── vikingmem
│ │ └── README.md
│ ├── customer_support
│ └── video_gen
├── README.md
└── README.zh.mdThis folder will contain tutorial-based learning materials that teach AgentKit's core functionalities through practical examples.
Component Categories:
- Runtime: AgentKit runtime environment, providing secure and scalable agent deployment capabilities
- Gateway: Tool gateway, automatically converting APIs and external services into agent-usable tools
- Memory: Agent memory management, supporting cross-session, context-aware, and personalized interactions
- Identity: Agent identity authentication and permission control, building security trust mechanisms across the user→Agent→tool chain
- Tools: Built-in toolset, including code interpreter and browser tools
- Observability: Agent observability, providing tracing, debugging, and monitoring capabilities
These examples are perfect for beginners and users who want to understand core concepts before building actual agent applications.
Explore practical business scenario implementations that demonstrate how to apply AgentKit functionalities to solve real-world business problems.
Current Use Cases:
- ai_coding/: AI coding assistant, helping developers write and optimize code
- beginner/: Beginner-level examples, from basic to advanced agent development
- customer_support/: Customer support agent, providing automated after-sales consulting and pre-sales guidance
- video_gen/: Video generation agent, combining multiple tools for video content creation
Each use case includes complete implementations with detailed explanations on how to combine AgentKit components to build applications.
- Python 3.10+
- AgentKit SDK
- Optional: Docker (for containerized deployment)
All examples require you to first install the AgentKit SDK Installation Reference
Each example follows the standard AgentKit application structure:
Example Directory/
├── agent.py # Agent main program
├── requirements.txt # Dependency list
├── config/ # Configuration files
└── README.md # Detailed instructions
- Modular Design: Separate tools, agents, and configurations
- Error Handling: Implement comprehensive exception handling
- Logging: Use structured logging for easier debugging
- Configuration Management: Use environment variables and config files
We welcome community contributions! If you have new examples or improvement suggestions, please:
- Fork this repository
- Create a feature branch (
git checkout -b feature/amazing-example) - Commit your changes (
git commit -m 'Add amazing example') - Push to the branch (
git push origin feature/amazing-example) - Create a Pull Request
This project is licensed under the Apache 2.0 License
- Documentation: Check AgentKit Official Documentation
- Issues: Report problems in GitHub Issues
Start exploring the powerful capabilities of AgentKit! Choose an example that interests you, follow the tutorials, and build your own agent applications.