: Custom Python functions or external APIs that agents use for interactions, such as searching the web or querying a database.
: A specialized toolset that allows agents to load domain expertise on demand rather than bloating the main prompt. Agentic Workflow Management
ADK coordinates multiple agents through structured design patterns: 1. Sequential Workflows
The is a modern, open-source framework developed by Google to streamline the building, testing, and deployment of AI agents at an enterprise scale. Unlike simple chatbots, ADK-powered agents are autonomous systems capable of reasoning , planning , and using tools to complete complex tasks. Core Components of ADK ADK's architecture uses several key components:
: These are powered by Large Language Models (LLMs) like Gemini.
These are best for tasks that require a linear, step-by-step order. 2. Parallel Processing
These are ideal for iterative tasks where the agent repeatedly refines its output until it meets a specific goal or quality standard. 4. Graph-Based Workflows Remember this: Agent state and memory with ADK
: Custom Python functions or external APIs that agents use for interactions, such as searching the web or querying a database.
: A specialized toolset that allows agents to load domain expertise on demand rather than bloating the main prompt. Agentic Workflow Management : Custom Python functions or external APIs that
ADK coordinates multiple agents through structured design patterns: 1. Sequential Workflows Sequential Workflows The is a modern, open-source framework
The is a modern, open-source framework developed by Google to streamline the building, testing, and deployment of AI agents at an enterprise scale. Unlike simple chatbots, ADK-powered agents are autonomous systems capable of reasoning , planning , and using tools to complete complex tasks. Core Components of ADK ADK's architecture uses several key components: These are best for tasks that require a
: These are powered by Large Language Models (LLMs) like Gemini.
These are best for tasks that require a linear, step-by-step order. 2. Parallel Processing
These are ideal for iterative tasks where the agent repeatedly refines its output until it meets a specific goal or quality standard. 4. Graph-Based Workflows Remember this: Agent state and memory with ADK