====== Google ADK ======

**Google Agent Development Kit (ADK)** is an open-source, code-first Python framework for building, evaluating, and deploying AI agents. With **18.6K GitHub stars**, ADK is Google's official agent framework — optimized for Gemini models but fully model-agnostic, supporting deployment from local development to Google Cloud at scale.

{{tag>framework python google gemini agents multi-agent cloud}}

===== Overview =====

Google ADK was released as part of Google's push to make agent development accessible through software engineering best practices rather than prompt-centric approaches. The framework emphasizes a code-first philosophy where agents are defined in Python with clear structure, tools are regular functions, and deployment scales from ''adk run'' on a laptop to Vertex AI Agent Engine in production. ADK 2.0 Alpha introduced graph-based orchestration for complex multi-agent workflows, signaling Google's commitment to the framework as a first-class development platform.

===== Key Features =====

  * **Code-First Development** — Agents defined in Python (''agent.py'') with tools as regular functions; also supports YAML config
  * **Gemini-Optimized** — Default models like ''gemini-3-flash-preview'' with native thinking capabilities
  * **Model-Agnostic** — Configurable authentication for any LLM provider
  * **Multi-Agent Orchestration** — Hierarchical agents, agents-as-tools, graph-based workflows (ADK 2.0 Alpha)
  * **Rich Tool Ecosystem** — Search, Code Execution, BigQuery forecast, GKECodeExecutor, OAuth flows
  * **ADK Web** — Open-source developer UI for interactive agent testing and debugging
  * **CLI Tools** — ''adk create'', ''adk run'', ''adk web'' for project lifecycle management
  * **Google Cloud Integration** — Vertex AI Agent Engine, Cloud Run, GKE deployment
  * **ADK Skills** — AI-powered coding assistance in development environments

===== Architecture =====

ADK follows a modular project structure with clear separation of concerns:

<mermaid>
graph TD
    subgraph Runtime["ADK Runtime"]
        subgraph RootAgent["Root Agent"]
            A[Model: Gemini / OpenAI]
            B[Instructions: System Prompt]
            C[Tools: Functions / Built-in]
        end
        D[Sub-Agents / Graph Orchestration: Hierarchical / Agents-as-Tools / DAG]
    end
    RootAgent --> D
    D --> E[adk run: CLI]
    D --> F[adk web: Dev UI]
    D --> G[Vertex AI: Cloud]
</mermaid>

===== Code Example =====

Building an agent with Google ADK:

<code python>
from google.adk.agents.llm_agent import Agent
from google.adk.runners import Runner
from google.adk.sessions import InMemorySessionService

# Define a tool as a regular Python function
def get_current_weather(city: str) -> dict:
    """Get the current weather for a city."""
    # Real API call would go here
    return {
        "city": city,
        "temperature": "22C",
        "condition": "Sunny",
        "humidity": "45%"
    }

def search_news(topic: str) -> dict:
    """Search for recent news on a topic."""
    return {
        "topic": topic,
        "articles": ["Article 1", "Article 2", "Article 3"]
    }

# Define the agent
root_agent = Agent(
    model="gemini-2.0-flash",
    name="assistant",
    description="A helpful assistant with weather and news tools.",
    instruction=(
        "You are a helpful assistant. Use available tools to "
        "answer questions about weather and current events."
    ),
    tools=[get_current_weather, search_news],
)

# Run interactively
session_service = InMemorySessionService()
runner = Runner(agent=root_agent, app_name="my_app", session_service=session_service)
</code>

===== Google Cloud Integration =====

ADK integrates deeply with Google Cloud services:

^ Service ^ Integration ^
| **Vertex AI Agent Engine** | Production deployment with CLI config |
| **Cloud Run** | Containerized agent deployment |
| **BigQuery** | Forecast tools, project/app naming |
| **GKE** | GKECodeExecutor for sandboxed code execution |
| **Bigtable** | Experimental toolset for database operations |
| **OAuth** | Configurable audience/prompt for Google services |

===== Recent Updates (2025-2026) =====

  * **ADK 2.0 Alpha** — Graph-based workflows for advanced multi-agent orchestration
  * **Agent Config** — YAML-based agent authoring with CLI deployment to Agent Engine
  * **ADK Web** — Open-sourced developer UI for interactive debugging
  * **ADK Skills** — AI-powered coding tools for development environments
  * **Tool Enhancements** — BigQuery forecast, GKECodeExecutor, tool confirmation flows, OAuth
  * **Multi-language** — Java, Go, and npm support alongside Python
  * **Samples Repository** — 54+ contributors with agents for RAG, financial advisor, travel concierge

===== References =====

  * [[https://github.com/google/adk-python|GitHub Repository (Python)]]
  * [[https://google.github.io/adk-docs/|Documentation]]
  * [[https://github.com/google/adk-samples|Samples Repository]]
  * [[https://github.com/google/adk-web|ADK Web UI]]

===== See Also =====

  * [[langchain]] — General-purpose LLM framework
  * [[pydantic_ai]] — Type-safe agent framework (uses Pydantic, like ADK)
  * [[agno]] — High-performance agent runtime
  * [[haystack]] — Pipeline-based AI orchestration