google-adk-basics

You build AI agents with Google ADK by setting up a Python environment, defining mandatory file conventions, and implementing LlmAgent patterns for Gemini models. This provides foundational knowledge for sophisticated applications.

The LlmAgent pattern is recommended over the Simple Agent pattern in ADK for building AI agents. LlmAgent provides advanced capabilities for integrating Gemini models and managing complex agent behaviors effectively.

You manage short-term memory for AI agents using the SessionService, and long-term data persistence using the MemoryBankService in Google ADK. This ensures proper context retention across different agent interactions and sessions.

Yes, you can design and coordinate complex interactions between multiple AI agents within a single ADK project. The framework provides patterns to manage multi-agent systems effectively for sophisticated task handling.

To set up an ADK project environment, you need Python and the `uv` package manager. Following the step-by-step setup instructions ensures your development environment is correctly configured for building AI agents.

You test AI agents built with the Agent Development Kit by implementing unit and integration tests. Following the provided testing methodologies ensures your agents are robust, safe, and efficient before deployment.