AgentKit

Product Positioning

AgentKit is an enterprise-grade AI Agent development platform launched by Volcengine. It provides developers with a complete solution for building, deploying, and operating Agents. Through a standardized development toolchain and cloud-native infrastructure, the platform significantly lowers the barrier to developing and deploying complex intelligent agent applications.

Key Advantages

• Declarative application definition: Define the core components and configuration of an agent application through a concise YAML file, enabling “define once, run anywhere”.
• Modular and extensible: Includes rich built-in modules such as Tool, Memory, and Knowledge, and provides standardized interfaces to make customization and extension easy.
• Cloud-native deployment: Seamlessly integrates with AgentKit Platform, supporting one-click deployment to the cloud, with elastic scaling, continuous integration, and high availability guarantees.
• Multi-agent collaboration: Supports building complex systems where multiple Agents work together, enabling task decomposition, collaboration, and aggregation, and supports the A2A protocol Agent.
• Full lifecycle management: Provides a complete agentkit CLI toolchain covering project initialization, local debugging, cloud deployment, and online operations.
• Multi-language support: Supports Python and Golang development to meet different tech stack needs.
• Rich project templates: Provides multiple prebuilt templates, including basic apps, streaming output, A2A protocol, etc., to kickstart development quickly.

Architecture Concept

AgentKit’s core design concept is to separate the definition and execution of an Agent App.

• Application definition (Definition): Developers declaratively define application metadata, dependencies, runtime environment, and required platform services (such as knowledge base and memory modules) via the agentkit.yaml file.
• Application execution (Execution): The agentkit CLI and AgentKit Platform parse the definition file and automatically complete a series of tedious tasks such as environment preparation, code packaging, image building, continuous integration, and cloud deployment.

This separation allows developers to focus on implementing business logic while AgentKit handles complex engineering problems, enabling agile development and fast production delivery.

Applicable Scenarios

• Intelligent Q&A bots: Quickly build knowledge-base-integrated intelligent Q&A services.
• Automated workflows: Create automation flows that can execute a series of tasks (such as sending emails, generating reports, calling APIs).
• Complex data analysis: Build data analysis Agents that understand user intent, query databases, analyze data, and generate visual reports.
• Multi-agent systems: Design and deploy systems where multiple Agents collaborate to complete complex tasks, such as a “researcher–analyst–reporter” pattern.

Get Started

• Install AgentKit: Learn how to install AgentKit.
• Quick Start: Use a simple example to quickly experience the full process from development to deployment.