Google Agent Development Kit Overview

The Google Agent Development Kit (ADK) is a comprehensive toolset designed for developers to build, test, evaluate, and deploy intelligent agents. It features various components that facilitate the creation of both deterministic and non-deterministic agents, enabling seamless integration with Google Cloud services and third-party tools.

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Key Components of the Agent Development Kit

1. Agents

• Types of Agents:
  • Non-Deterministic Agents: Utilize Large Language Models (LLMs) for coordination.
  • Deterministic Agents: Follow defined workflows (sequential, parallel, loop).
  • Custom Agents: Combine both non-deterministic and deterministic elements.

2. Tools

• Function Tools: Defined as functions with specific configurations (dock strings).
• Built-in Tools: Include Google Search, code execution, and RAG (Retrieval-Augmented Generation).
• Third-Party Tools: Integration with LangChain and Crew AI.
• Authentication: Supports API key, OpenID Connect, OAuth 2.0, etc.

3. Callbacks and Guardrails

• Purpose: Protect the system from unwanted queries and ensure quality control.
• Types of Guardrails:
  • Agent callbacks
  • Tool callbacks
  • Model callbacks

4. Session and Memory Services

• Session Services: Manage session state and parameters.
• Memory Services: Include short-term (session-based) and long-term (persistent) memory.

5. Deployment and Evaluation

• Deployment Options: Cloud environment (e.g., Google Cloud) or self-managed.
• Evaluation: Assess the quality of agents.

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Building Agent Workflows

1. Workflow Components

• Tools: Essential for task accomplishment.
• Agents: Self-contained execution blocks that perform specific tasks.
• Callbacks: Conditions set before and after component usage to ensure quality.

2. Agent Types and Workflows

• Deterministic Workflows:

  • Sequential Agents: Execute tasks in a specified order.
  • Loop Agents: Run tasks in a loop for a defined number of iterations.
  • Parallel Agents: Execute multiple tasks simultaneously.

• Custom Agents: Combine both deterministic and non-deterministic workflows for complex scenarios.

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Runtime and Execution Flow

1. Execution Process

• User Interaction: User poses a question.
• Runner: Establishes a session and manages the workflow.
• Agent Logic: Uses LLM to determine actions and call tools as needed.
• Event Logging: Records all actions and responses for tracking.

2. Multi-Agent Systems

• Coordination Agents: Manage interactions between multiple agents.
• Sub-Agents: Operate under a parent agent, returning outputs as needed.

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Example Implementations

1. Quick Start Example

• Setup: Create a folder structure, set up a virtual environment, and install the ADK.
• Testing: Use a simple agent with hardcoded values to demonstrate functionality.

2. Streamlit Applications

• Multi-Agent Systems: Develop applications that utilize multiple agents for different tasks (e.g., math and translation).
• Guardrails: Implement callbacks to manage input and output effectively.

3. Deterministic Workflows

• Sequential Agents: Create a code pipeline that generates, reviews, and executes code.
• Loop Agents: Build a pitch enhancement tool that critiques and refines user pitches.
• Parallel Agents: Conduct research by generating subtopics and collecting data simultaneously.

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Deployment Options

1. Google Cloud Deployment

• Vert.x AI Agent Engine: A fully managed service for deploying agents.
• Deployment Steps:
  • Set up Google Cloud SDK.
  • Create and configure agent definitions.
  • Deploy agents using Docker and Google Cloud services.

2. Pricing and Availability

• Regions: Currently available in US Central 1 and West 1.
• Cost Structure: Based on CPU and memory usage.

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Conclusion

The Google Agent Development Kit empowers developers to create sophisticated agents that can be deployed in various environments. With its robust features, including multi-agent capabilities and seamless integration with Google Cloud, the ADK is a valuable tool for building intelligent applications.

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Component	Description
Agents	Self-contained execution blocks (deterministic, non-deterministic, custom)
Tools	Function tools, built-in tools, third-party integrations
Callbacks	Guardrails for quality control at various levels
Session Services	Manage session state and parameters
Memory Services	Short-term and long-term memory management
Deployment Options	Cloud-based (Vert.x AI) or self-managed environments
Evaluation	Assess agent quality and performance

These notes provide a structured overview of the Google Agent Development Kit, highlighting its components, functionalities, and practical applications.