Building AI Agents in Go with the Agent Development Kit (ADK)

Introducing the Agent Development Kit (ADK) Go

• 💡 The Agent Development Kit (ADK) Go is a new, idiomatic library for Go developers to build powerful generative AI applications.
• 🚀 It aims to simplify the development, deployment, and evaluation of AI agents by addressing complexities like state management, memory, tool calls, and control flow.

Core Agent Concepts in ADK Go

• 🧠 ADK categorizes agents into three types: LLM-based reasoning agents (decide tool calls/transfers), workflow agents (deterministic logic), and custom agents (arbitrary logic).
• 🛠️ An agent is defined by its name, description, LLM model, and instruction prompt.
• 🏃 Agents are run using a session service, creating a session to hold the conversation and a runner to execute the agent, producing an iterator of events.

Enhancing Agents with Tools

• 🌐 Tools augment agents with capabilities beyond LLM's text processing, such as internet browsing, database queries, or API calls.
• ⚙️ The ADK framework manages the process where an agent analyzes a request, determines if a tool is needed, and then executes the tool with appropriate arguments.
• 🔗 ADK Go offers three tool types: built-in tools (e.g., Google Search), third-party tools, and function tools which wrap arbitrary Go code.

Multi-Agent Patterns and Orchestration

• 🤝 ADK supports multi-agent scenarios where agents collaborate, either through interoperability for tools or via an agent-to-agent protocol.
• 🧩 A powerful pattern is using one agent as a tool for another, enabling hierarchical or collaborative systems.
• 🔄 Workflow agents like sequential, parallel, and loop agents orchestrate complex flows involving multiple agents, allowing for sequential execution, concurrent processing, or iterative refinement based on exit conditions.

State, Sessions, and Context Management

• 💬 A session represents a single ongoing conversation thread, storing history, a shared state map, and metadata like user ID and application name.
• 📝 The state acts as an agent's temporary scratchpad for conversation-specific data, allowing for dynamic customization of agent instructions.
• 💾 For knowledge that persists beyond a single conversation, ADK provides a memory service for long-term memory management.