@ArchiveExplorer: Google just killed the agent framework industry. ADK 2.0: Open-source. Free. Better than $50K enterprise tools. What it…

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Summary

Google released ADK 2.0, an open-source, code-first Python framework for building AI agents with graph-based orchestration and agent-to-agent delegation, aiming to replace expensive enterprise agent frameworks.

Google just killed the agent framework industry. ADK 2.0: Open-source. Free. Better than $50K enterprise tools. What it does: → Graph-based execution with routing, fan-out/fan-in, loops, retry → Structured agent-to-agent delegation via Task API → State management, dynamic nodes, human-in-the-loop, nested workflows → Interactive CLI (adk run) and Web UI (adk web) for local dev → Multi-turn task mode with single-turn controlled output → Works with Gemini 2.5 Flash, extensions via pip What it replaces: → LangChain orchestration boilerplate → LangGraph state machines → Vertex AI Agent Builder lock-in → Custom agent-to-agent delegation code Define your Agent class with instructions and tools. Compose a Workflow class as a graph. Run it locally with adk run or adk web. No hosted platform. No vendor lock-in. Customer support bots, research agents, multi-agent pipelines - same library. This is what open-source from Google looks like. → https://github.com/google/adk-python…
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Google just killed the agent framework industry.

ADK 2.0: Open-source. Free. Better than $50K enterprise tools.

What it does:

→ Graph-based execution with routing, fan-out/fan-in, loops, retry → Structured agent-to-agent delegation via Task API → State management, dynamic nodes, human-in-the-loop, nested workflows → Interactive CLI (adk run) and Web UI (adk web) for local dev → Multi-turn task mode with single-turn controlled output → Works with Gemini 2.5 Flash, extensions via pip

What it replaces:

→ LangChain orchestration boilerplate → LangGraph state machines → Vertex AI Agent Builder lock-in → Custom agent-to-agent delegation code

Define your Agent class with instructions and tools. Compose a Workflow class as a graph. Run it locally with adk run or adk web.

No hosted platform. No vendor lock-in.

Customer support bots, research agents, multi-agent pipelines - same library.

This is what open-source from Google looks like.

→ https://github.com/google/adk-python…


google/adk-python

Source: https://github.com/google/adk-python

Agent Development Kit (ADK) 2.0

License PyPI version Python versions PyPI downloads Unit Tests Docs

An open-source, code-first Python framework for building, evaluating, and deploying sophisticated AI agents with flexibility and control.

Important Links: Docs, Samples & ADK Web.


⚠️ BREAKING CHANGES FROM 1.x

This release includes breaking changes to the agent API, event model, and session schema. Sessions generated by ADK 2.0 are readable by ADK 1.28+ (extra fields will be ignored), but are incompatible with older 1.x versions.


🔥 What’s New in 2.0

  • Workflow Runtime: A graph-based execution engine for composing deterministic execution flows for agentic apps, with support for routing, fan-out/fan-in, loops, retry, state management, dynamic nodes, human-in-the-loop, and nested workflows.

  • Task API: Structured agent-to-agent delegation with multi-turn task mode, single-turn controlled output, mixed delegation patterns, human-in-the-loop, and task agents as workflow nodes.

🚀 Installation

pip install google-adk

Requirements: Python 3.10+.

To install optional integrations, you can use the following command:

pip install "google-adk[extensions]"

The release cadence is roughly bi-weekly.

Quick Start

Beginner Note: ADK applications are built using two main classes: Agent (defines an AI’s instructions, tools, and behavior) and Workflow (orchestrates agents and tasks in a graph-based flow).

Agent

from google.adk import Agent

root_agent = Agent(
    name="greeting_agent",
    model="gemini-2.5-flash",
    instruction="You are a helpful assistant. Greet the user warmly.",
)

Workflow

from google.adk import Agent, Workflow

generate_fruit_agent = Agent(
    name="generate_fruit_agent",
    instruction="Return the name of a random fruit. Return only the name.",
)

generate_benefit_agent = Agent(
    name="generate_benefit_agent",
    instruction="Tell me a health benefit about the specified fruit.",
)

root_agent = Workflow(
    name="root_agent",
    edges=[("START", generate_fruit_agent, generate_benefit_agent)],
)

Run Locally

# Interactive CLI
adk run path/to/my_agent

# Web UI (supports multi-agent directories or pointing directly to a single agent folder)
adk web path/to/agents_dir

📚 Documentation

  • Getting Started: https://google.github.io/adk-docs/
  • Samples: See contributing/workflow_samples/ and contributing/task_samples/ for workflow and task API examples.

🤝 Contributing

See CONTRIBUTING.md for details.

📄 License

This project is licensed under the Apache 2.0 License — see the LICENSE file for details.

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