WSQ — Develop Multi AI Agent Applications with Gemini Agent ADK

Course Code: TGS-2024042961 Conducted by: Tertiary Infotech Academy Pte Ltd (UEN 201200696W) Duration: 2 days · 16 training hours

Courseware and hands-on lab repository for the WSQ course Develop Multi AI Agent Applications with Gemini Agent ADK, built on Google's open-source Agent Development Kit (ADK) and the Gemini model family.

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Learning Outcomes

	Outcome
LO1	Analyze the range of LLM applications using Generative AI (GAI) and identify their industrial use cases
LO2	Establish Google Gemini GAI designs and assess improvements on engineering processes
LO3	Develop LLM applications and assess its feasibility
LO4	Evaluate the performance effectiveness of Retrieval Augmented Generation (RAG)

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Course Topics

Topic	Title	Labs
1	Overview of Agentic AI in Gemini ADK	1–4
2	Build A Multi Agent App with Gemini ADK	5–12
3	Build Agentic AI RAG in Gemini ADK	13–15
4	Build an Agentic AI App with Gemini Agent ADK and Streamlit	16–18

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Quick Start

Prerequisites: Python 3.13+, uv, and a free Gemini API key from Google AI Studio.

git clone https://github.com/tertiarycourses/TGS-2024042961-Develop-Multi-AI-Agent-Applications-with-Gemini-Agent-ADK.git
cd TGS-2024042961-Develop-Multi-AI-Agent-Applications-with-Gemini-Agent-ADK/labs
uv sync

Create a .env file in the labs/ folder:

GOOGLE_GENAI_USE_VERTEXAI=0
GOOGLE_API_KEY=your-google-api-key
OPENWEATHER_API_KEY=your-openweather-key   # optional, tool labs
TAVILY_API_KEY=your-tavily-key             # optional, search labs

Never commit your .env file or API keys. It is git-ignored in this repository.

Run any agent:

uv run adk run <agent_folder>   # terminal chat
uv run adk web                  # browser IDE at http://localhost:8000

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Labs

#	Lab	Agent folder	Topic
1	Set Up the Gemini ADK Environment and Get an API Key	lab01	1
2	Build Your First ADK Agent — A Retail Banking Assistant	lab02	1
3	Give an Agent Tools — Live Weather and Web Search	lab03	1
4	Swap the Model — Running an ADK Agent on a Non-Gemini LLM	lab04	1
5	Give an Agent Memory — Sessions, State and the Runner	lab05	2
6	Inspect the Agent Loop — Events, Tool Calls and Final Responses	lab06	2
7	Multi-Agent Handoff — Joke Generator to Translator	lab07	2
8	Hierarchical Multi-Agent System — The Tutor Agent	lab08	2
9	Sequential Workflow Agent — Singapore Transport Route Planner	lab09	2
10	Add a Guardrail — Blocking Unsafe Requests with a Callback	lab10	2
11	Structured Output — Forcing Valid JSON with Pydantic	lab11	2
12	Connect External Tools with MCP — StreamableHTTP and SSE	lab12	2
13	Load, Split and Embed Documents into a Vector Store	lab13	3
14	Build the Agentic RAG Agent — Retrieval as a Tool	lab14	3
15	Evaluate RAG Performance — Retrieval Quality and Groundedness	lab15	3
16	Declarative Agents — Configuring a Multi-Agent System in YAML	lab16	4
17	Ship the Agent as a Web App with Streamlit	lab17	4
18	Capstone — Design, Build and Assess Your Own Multi-Agent Application	lab18	4

Every lab is a self-contained folder holding its own agent script, data files and a README.md lab sheet. See labs/LABS.md for the full index.

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Core ADK Patterns

Define an agent

from google.adk.agents import Agent

root_agent = Agent(
    model='gemini-2.0-flash',
    name='root_agent',
    description='A helpful assistant for user questions.',
    instruction='Answer clearly and concisely.',
)

Add a tool — the docstring and type hints are the contract the model reads.

def get_weather(city: str) -> dict:
    """Retrieves the current weather for a specified city.

    Args:
        city (str): The name of the city.

    Returns:
        dict: status and result or error msg.
    """
    return {"status": "success", "report": "..."}

agent = Agent(..., tools=[get_weather])

Multi-agent handoff

root_agent = Agent(
    name='root_agent',
    sub_agents=[math_tutor_agent, physics_tutor_agent, history_tutor_agent],
    instruction='Route each question to the right specialist.',
)

Sequential workflow

from google.adk.agents import SequentialAgent

workflow = SequentialAgent(
    name='workflow_agent',
    sub_agents=[input_agent, research_agent, report_agent],
)

Guardrail — return None to allow, an LlmResponse to block.

def block_keyword_guardrail(callback_context, llm_request):
    if "BLOCK" in last_user_message.upper():
        return LlmResponse(content=types.Content(
            role="model", parts=[types.Part(text="I cannot process this request.")]))
    return None

agent = Agent(..., before_model_callback=block_keyword_guardrail)

Structured output — note an agent with output_schema cannot also use tools.

from pydantic import BaseModel

class Recipe(BaseModel):
    title: str
    ingredients: list[str]
    cooking_time: int

agent = Agent(..., output_schema=Recipe)

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Courseware

Artifact	File
Trainer Slides	courseware/Develop Multi AI Agent Applications with Gemini Agent ADK-v1.3.pptx
Learner Slides (PDF)	courseware/Develop Multi AI Agent Applications with Gemini Agent ADK-v1.3.pdf
Lesson Plan	courseware/LP-Develop Multi AI Agent Applications with Gemini Agent ADK.docx
Learner Guide	courseware/LG-Develop Multi AI Agent Applications with Gemini Agent ADK.docx
Learner Guide (Markdown)	LG-Develop Multi AI Agent Applications with Gemini Agent ADK.md

The Learner Guide carries the full step-by-step instructions for all 18 labs, plus reference sections on core ADK patterns, evaluating a RAG pipeline, and assessing the feasibility of an agent application.

The Trainer Slides (v1.3, 160 slides) teach each lab as a four-part unit — briefing → process map → procedure with the actual commands → verification with troubleshooting — alongside comparison matrices, decision maps, worked code examples and native charts. Slide transitions are deliberately restrained (content fades, section dividers push), with click-through reveals on the process maps so a stage can be discussed before the next appears.

The assessment set is confidential and is not published in this repository.

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Resources

• Google ADK Documentation
• Google AI Studio — free Gemini API keys
• Course page
• LMS / TMS

Support

Tertiary Infotech Academy Pte Ltd · UEN 201200696W Email: enquiry@tertiaryinfotech.com · Tel: +65 6100 0613 · tertiarycourses.com.sg

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