google__adk-docs/docs/get-started/about.md

Agent Development Kit (ADK)

Build, Evaluate and Deploy agents, seamlessly!

ADK is designed to empower developers to build, manage, evaluate and deploy AI-powered agents. It provides a robust and flexible environment for creating both conversational and non-conversational agents, capable of handling complex tasks and workflows.

Core Concepts

ADK is built around a few key primitives and concepts that make it powerful and flexible. Here are the essentials:

• Agent: The fundamental worker unit designed for specific tasks. Agents can use language models (LlmAgent) for complex reasoning, or act as deterministic controllers of the execution, which are called "workflow agents" (SequentialAgent, ParallelAgent, LoopAgent).
• Tool: Gives agents abilities beyond conversation, letting them interact with external APIs, search information, run code, or call other services.
• Callbacks: Custom code snippets you provide to run at specific points in the agent's process, allowing for checks, logging, or behavior modifications.
• Session Management (Session & State): Handles the context of a single conversation (Session), including its history (Events) and the agent's working memory for that conversation (State).
• Memory: Enables agents to recall information about a user across multiple sessions, providing long-term context (distinct from short-term session State).
• Artifact Management (Artifact): Allows agents to save, load, and manage files or binary data (like images, PDFs) associated with a session or user.
• Code Execution: The ability for agents (usually via Tools) to generate and execute code to perform complex calculations or actions.
• Planning: An advanced capability where agents can break down complex goals into smaller steps and plan how to achieve them like a ReAct planner.
• Models: The underlying LLM that powers LlmAgents, enabling their reasoning and language understanding abilities.
• Event: The basic unit of communication representing things that happen during a session (user message, agent reply, tool use), forming the conversation history.
• Runner: The engine that manages the execution flow, orchestrates agent interactions based on Events, and coordinates with backend services.

Note: Features like Multimodal Streaming, Evaluation, Deployment, Debugging, and Trace are also part of the broader ADK ecosystem, supporting real-time interaction and the development lifecycle.

Key Capabilities

ADK offers several key advantages for developers building agentic applications:

1. Multi-Agent System Design: Easily build applications composed of multiple, specialized agents arranged hierarchically. Agents can coordinate complex tasks, delegate sub-tasks using LLM-driven transfer or explicit AgentTool invocation, enabling modular and scalable solutions.
2. Rich Tool Ecosystem: Equip agents with diverse capabilities. ADK supports integrating custom functions (FunctionTool), using other agents as tools (AgentTool), leveraging built-in functionalities like code execution, and interacting with external data sources and APIs (e.g., Search, Databases). Support for long-running tools allows handling asynchronous operations effectively.
3. Flexible Orchestration: Define complex agent workflows using built-in workflow agents (SequentialAgent, ParallelAgent, LoopAgent) alongside LLM-driven dynamic routing. This allows for both predictable pipelines and adaptive agent behavior.
4. Integrated Developer Tooling: Develop and iterate locally with ease. ADK includes tools like a command-line interface (CLI) and a Developer UI for running agents, inspecting execution steps (events, state changes), debugging interactions, and visualizing agent definitions.
5. Native Streaming Support: Build real-time, interactive experiences with live and voice agents that provide native support for bidirectional streaming (text and audio). This integrates seamlessly with underlying capabilities like the Gemini Live API for the Gemini Developer API (or for Agent Platform), often enabled with simple configuration changes.
6. Built-in Agent Evaluation: Assess agent performance systematically. The framework includes tools to create multi-turn evaluation datasets and run evaluations locally (via CLI or the dev UI) to measure quality and guide improvements.
7. Broad LLM Support: While optimized for Google's Gemini models, the framework is designed for flexibility, allowing integration with various LLMs (potentially including open-source or fine-tuned models) through its BaseLlm interface.
8. Artifact Management: Enable agents to handle files and binary data. The framework provides mechanisms (ArtifactService, context methods) for agents to save, load, and manage versioned artifacts like images, documents, or generated reports during their execution.
9. Extensibility and Interoperability: ADK promotes an open ecosystem. While providing core tools, it allows developers to easily integrate and reuse third-party tools and data connectors.
10. State and Memory Management: Automatically handles short-term conversational memory (State within a Session) managed by the SessionService. Provides integration points for longer-term Memory services, allowing agents to recall user information across multiple sessions.

Get Started

• Ready to build your first agent? Get started!