An open-source, code-first Python framework for building, evaluating, and deploying sophisticated AI agents with flexibility and control.
⚠️ BREAKING CHANGES FROM 1.xThis 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.
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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.
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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.
pip install google-adkRequirements: Python 3.11+.
To install optional integrations, you can use the following command:
pip install "google-adk[extensions]"The release cadence is roughly bi-weekly.
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.",
)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)],
)# Interactive CLI
adk run path/to/my_agent
# Web UI
adk web path/to/agents_dir- Getting Started: https://google.github.io/adk-docs/
- Samples: See
contributing/workflow_samples/andcontributing/task_samples/for workflow and task API examples.
See CONTRIBUTING.md for details.
This project is licensed under the Apache 2.0 License — see the LICENSE file for details.
