adk-python
ADK (Agent Development Kit) is Google's open-source Python framework for building, evaluating, and deploying AI agents using a code-first approach. It provides a workflow runtime with graph-based execution, task delegation between agents, and local/web-based tooling for development and testing.
Key facts
Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.
| Field | Value |
|---|---|
| Repository | google/adk-python |
| Owner | |
| Primary language | Python |
| License | Apache-2.0 — OSI-approved |
| Stars | 20.5k |
| Forks | 3.7k |
| Open issues | 703 |
| Latest release | v2.4.0 (2026-07-07) |
| Last updated | 2026-07-08 |
| Source | https://github.com/google/adk-python |
What adk-python is
ADK 2.0 introduces a graph-based workflow execution engine supporting routing, fan-out/fan-in, loops, retry logic, and nested workflows alongside a Task API for structured agent-to-agent delegation. Built in Python 3.10+, it integrates with LLMs (e.g., Gemini) and provides CLI and web UI for local development and multi-agent orchestration.
Get the adk-python source
Clone the repository and explore it locally.
git clone https://github.com/google/adk-python.gitcd adk-python# follow the project's README for install & configurationNeed it deployed, integrated, or customized instead? DEV.co ships production installs.
Best use cases
Implementation considerations
- Plan migration from ADK 1.x if running production agents; sessions are forward-compatible to 1.28+ but breaking API changes require code refactoring.
- Verify Python 3.10+ availability in target deployment environment; no older version support.
- Configure LLM credentials and model selection upfront (e.g., Gemini-2.5-flash); model availability and billing model impact agent behavior and cost.
- Design workflow graph structure early; complex nested workflows and large fan-out patterns may require optimization for latency and token usage.
- Evaluate optional extensions (pip install google-adk[extensions]) to determine which integrations are needed for your agent tasks and tools.
When to avoid it — and what to weigh
- Python < 3.10 Required — If your infrastructure is locked to Python 3.9 or earlier, this toolkit cannot be used without upgrading your runtime environment.
- Simple Chatbot Only — For single-agent, stateless chatbot use cases, ADK's workflow and task infrastructure introduces unnecessary complexity; a lighter LLM library may suffice.
- Breaking Change Constraints — If you are running ADK 1.x agents in production with strict backward compatibility requirements, ADK 2.0's API and schema changes require migration planning.
- Offline-Only or Closed-Network Deployments — ADK's typical usage integrates with Google LLMs (e.g., Gemini) and cloud services; air-gapped or entirely local inference requires custom integration effort.
License & commercial use
Apache License 2.0 (SPDX: Apache-2.0). Permissive OSI-approved license allowing commercial use, modification, and redistribution with attribution and disclaimer of liability.
Apache 2.0 permits commercial use, but review your own legal terms regarding use of Google-maintained code, any bundled dependencies, and LLM API cost structures. Consult your counsel for production deployment in regulated industries.
DEV.co evaluation signals
Editorial assessment — not user reviews. Directional, with an explicit confidence level.
| Signal | Assessment |
|---|---|
| Maintenance | Active |
| Documentation | Adequate |
| License clarity | Clear |
| Deployment complexity | Moderate |
| DEV.co fit | Strong |
| Assessment confidence | High |
LLM API credentials (keys, model selection) must be secured via environment variables or secrets management. Workflow execution with external tools (agent tools defined by users) should validate inputs to prevent prompt injection. State and session data handling should follow data residency and privacy policies (Google servers). No explicit security audit or threat model documented.
Alternatives to consider
LangChain / LangGraph
Broader ecosystem, multi-LLM support (OpenAI, Anthropic, etc.), larger community. More flexible but also steeper learning curve; not Google-specific.
Semantic Kernel (Microsoft)
Azure/Copilot integration, plugins, enterprise support. Better for organizations already in Microsoft ecosystem; less workflow-native than ADK.
CrewAI
Role-based agent framework with simpler multi-agent setup. Lighter-weight alternative if you do not need complex workflow graphs or task APIs.
Build on adk-python with DEV.co software developers
Start with ADK's quick-start guide, explore sample workflows, and deploy locally. For production orchestration and integrations, contact our engineers.
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adk-python FAQ
Can I use ADK with non-Google LLMs?
What is the difference between Agent and Workflow?
Is ADK 2.0 backward compatible with 1.x?
How is state managed across workflow nodes?
Software developers & web developers for hire
Need help beyond evaluating adk-python? DEV.co is a software development agency offering software development services and web development for teams of every size. Our software developers and web developers build custom software, web applications, APIs, and ai frameworks integrations — and maintain them long-term.
Ready to Build AI Agents?
Start with ADK's quick-start guide, explore sample workflows, and deploy locally. For production orchestration and integrations, contact our engineers.