[](https://github.com/google/adk-python/actions/workflows/python-unit-tests.yml)
Agent Development Kit (ADK) is a flexible and modular framework for developing and deploying AI agents. While optimized for Gemini and the Google ecosystem, ADK is model-agnostic, deployment-agnostic, and is built for compatibility with other frameworks. ADK was designed to make agent development feel more like software development, to make it easier for developers to create, deploy, and orchestrate agentic architectures that range from simple tasks to complex workflows.
- **Context compaction**: Supports context compaction to reduce context length. Here is a [sample](https://github.com/google/adk-python/blob/main/contributing/samples/hello_world_app/agent.py#L156) and [compaction config](https://github.com/google/adk-python/blob/main/src/google/adk/apps/app.py#L51).
- **Resumability**: Support pause and resume an invocation in ADK.
- **ReflectRetryToolPlugin**: Add [`ReflectRetryToolPlugin`](https://github.com/google/adk-python/blob/main/src/google/adk/plugins/reflect_retry_tool_plugin.py) to reflect from errors and retry with different arguments when tool errors.
- **Search tool**: Support using Google built-in search and built-in `VertexAiSearchTool` with other tools in the same agent.
- **Tool Confirmation**: A [tool confirmation flow(HITL)](https://google.github.io/adk-docs/tools/confirmation/) that can guard tool execution with explicit confirmation and custom input.
This version is recommended for most users as it represents the most recent official release.
### Development Version
Bug fixes and new features are merged into the main branch on GitHub first. If you need access to changes that haven't been included in an official PyPI release yet, you can install directly from the main branch:
Note: The development version is built directly from the latest code commits. While it includes the newest fixes and features, it may also contain experimental changes or bugs not present in the stable release. Use it primarily for testing upcoming changes or accessing critical fixes before they are officially released.
Define a multi-agent system with coordinator agent, greeter agent, and task execution agent. Then ADK engine and the model will guide the agents works together to accomplish the task.
We welcome contributions from the community! Whether it's bug reports, feature requests, documentation improvements, or code contributions, please see our
If you are to develop agent via vibe coding the [llms.txt](./llms.txt) and the [llms-full.txt](./llms-full.txt) can be used as context to LLM. While the former one is a summarized one and the later one has the full information in case your LLM has big enough context window.