Google's ADK-Go: Toolkit for Flexible AI Agents
Build, evaluate, and deploy model-agnostic AI agents in Go using Google's open-source ADK, leveraging concurrency for cloud-native apps while staying compatible with Gemini and other frameworks.
Toolkit Design for Agent Workflows
ADK-Go applies software engineering principles to AI agent development, enabling construction of workflows from simple tasks to complex multi-agent systems. Define agents via code with full control over components like memory, models, plugins, tools, runners, sessions, artifacts, and telemetry. Folders structure reflects this modularity: agent for core logic, memory for state management, model for LLM integration (optimized for Gemini but agnostic), plugin and tool for extensions, runner for execution, server for deployment, and telemetry for observability. Go's concurrency and performance make it ideal for cloud-native applications, avoiding lock-in to specific models or deployments.
Evaluation and Deployment Simplicity
The kit streamlines testing and production rollout through structured evaluation tools and runner abstractions, supporting orchestration across agents. Examples in /examples demonstrate practical use cases. Deployment-agnostic design integrates with existing stacks, and compatibility with other frameworks allows hybrid setups. Nightly CI checks ensure reliability, with 393 commits signaling active development.
Integration and Ecosystem
Install via Go modules (command in README: likely go get google.golang.org/adk). Access Go docs at pkg.go.dev/google.golang.org/adk for APIs. Apache 2.0 licensed (exception for internal/httprr), with CONTRIBUTING.md for involvement. Ecosystem includes Python/Java ports and ADK Web for broader language support. Reddit community at r/agentdevelopmentkit for discussion.