You will learn how to move beyond simple LLM calls to build intelligent agents with Gemini 2.0. Learn how function calling, structured outputs, and async operations enable complex agent behavior and interactions. Discover how to create purpose-driven AI systems capable of a series of actions. The demo covers how a chat message activates the agentic experience, then agents utilize tools to achieve complex goals, and unlock the potential of multi-agent systems, where they collaborate to solve problems. Join us to discover how Gemini 2.0 empowers you to create multi turn agentic workflows for everyday developers.

1. AI Agents with Gemini 2.0
Beyond the Chatbot
Márton Kodok
Google Developer Expert at REEA.net
#geecon | Room 12

2. 1. Gemini - The Big Picture
2. Gemini - capabilities
3. Enabling the agentic era
4. Demos
5. Conclusions
Agenda
AI Agents with Gemini 2.0 - Beyond the Chatbot @martonkodok

3. Márton Kodok
AI Agents with Gemini 2.0 - Beyond the Chatbot @martonkodok
● 8x Google Developer Expert on Cloud technologies (2016-->)
● 3x Champion of Google Cloud Innovators program (2021-->)
● Among the Top 3 romanians on Stackoverflow 208k reputation
● Crafting Cloud Architecture+ML backends at REEA.net
Articles: martonkodok.medium.com
Twitter: @martonkodok
Slideshare:martonkodok
StackOverflow: pentium10
GitHub: pentium10

4. What LLMs are, and are not
AI Agents with Gemini 2.0 - Beyond the Chatbot @martonkodok
“Large Language
Models are not a
source of truth.”
– Noble Ackerson
What they are,
however, is a way to
transform one thing
into another.
● Phrases into code
fragments
● Structured data
into textual results
Combine them with
APIs that you already
know and work with,
and your applications
can have amazing
new capabilities.
A powerful new tool!

5. Gemini - The Big Picture
AI Agents with Gemini 2.0 - Beyond the Chatbot @martonkodok
Gemini Models
ML Other Models
Client Libs & SDK
Gemini API
Vertex AI
AI Studio
Local
Models
Gemma
ADK
AI Tools for
Business
AI assistant
Gemini for
Workspace
Gemini
chat app
Gemini Live
Notebook LM
Developers
"Consumers"

6. ✅ ✅
✅
✅
✅
@martonkodok
Gemini comes in different sizes
2.5 Pro
2.5 Flash
2.0 Pro
1.5 Flash
✅
❌
Multimodal Input
(text, img, video, audio, PDF)
Context Window + Output
Native Tool Use
(Search, Code Exec)
Thinking Mode
1M / 8K
❌ ❌
✅ ✅ ✅
2M / 8K 1M / 65K 1M / 65K
set Thinking Budget
10K free Search queries
Preview
Preview

7. AI Agents with Gemini 2.0 - Beyond the Chatbot @martonkodok
Texttoimagegeneration
withhighqualityandspeed
● Aspectratios
1:1, 9:16, 16:9, 3:4, 4:3
● Styles
photorealism, paintings, richly
textured, oil paintings, comic
● UseCases
Banners, Posters, Advertizing
A lone skateboarder glides through the echoing stillness of
an abandoned train station, bathed in the soft glow of a
single overhead lamp, creating a dramatic silhouette
against the vast, empty space.
A dynamic, high-energy animation of a superhero flying
across a busy metropolis with a blurred background
A watercolor painting of mt fuji A bright style- magazine shot of a woman putting on
mascara.
Imagen 3

8. Demo
Gemini: Native image generation
AI Agents with Gemini 2.0 - Beyond the Chatbot @martonkodok

9. AI Agents with Gemini 2.0 - Beyond the Chatbot @martonkodok
Veo 2
Veo2

10. Vision of abandoned Warsaw, capital of Poland @Tomek Porozynski
Veo 2
● Author: Tomek Porozynski
● GDE & Cloud Architect
● Made with Veo 2

11. AI Agents with Gemini 2.0 - Beyond the Chatbot @martonkodok
● Local model runs on 1 single GPU
● MultiLingual 140+ languages
● Function Calling
● 1b - 4b - 12b - 27b sizes
● Vision - interleaved image & text input
Gemma 3

12. Getting started with the
Gemini API
AI Agents with Gemini 2.0 - Beyond the Chatbot @martonkodok

13. AI Agents with Gemini 2.0 - Beyond the Chatbot @martonkodok
aistudio.google.com
AI Studio
➔ Generate API key
➔ Create, test, and save prompts
➔ SDK in Python/Go/JS+TS/Firebase
➔ Java via LangChain4j library

14. AI Agents with Gemini 2.0 - Beyond the Chatbot @martonkodok
AI Studio
➔ UI is free up to 5-10 RPM
➔ Prompt management
➔ Access to Gemma 3.
➔ Unified SDK references
AI Studio mostly as first
example

15. AI Agents with Gemini 2.0 - Beyond the Chatbot @martonkodok
console.cloud.google.com/vertex-ai/studio
Vertex AI Studio
➔ Service account key
➔ Vertex AI SDK
➔ Access to 120 models via Model Garden
➔ Available for individual/edu/business
➔ Java via google-cloud-vertexai Library

16. AI Agents with Gemini 2.0 - Beyond the Chatbot @martonkodok
console.cloud.google.com/vertex-ai/studio
Vertex AI Studio
➔ Project based use
➔ Access to preview models/increased quotas
➔ Help me write prompts
➔ Imagen 3 + Veo 2
➔ Prompt management

17. AI Agents with Gemini 2.0 - Beyond the Chatbot @martonkodok
gemini.google.com
aistudio.google.com
ai.google.dev/gemini-api
console.cloud.google.com/vertex-ai/studio
Consumers Enterprise
Developers

18. Unified SDK
AI Agents with Gemini 2.0 - Beyond the Chatbot @martonkodok

19. Gemini
Capabilities
AI Agents with Gemini 2.0 - Beyond the Chatbot @martonkodok

20. What makes Gemini unique?
AI Agents with Gemini 2.0 - Beyond the Chatbot @martonkodok
Native
Tool Use
Multimodal
in and out
Long context length
Context Caching
Multimodal
Live API
Thinking Mode
Budget driven
Spatial
Understanding

21. AI Agents with Gemini 2.0 - Beyond the Chatbot @martonkodok
Function Calling
API parameters Tools Execution
Processing
Model Output
Function Calls Function Responses
Data
User
Prompt
Generating
Live Info

22. AI Agents with Gemini 2.0 - Beyond the Chatbot @martonkodok
Google Search Tool
google_search_tool = Tool(google_search=GoogleSearch())
response = client.models.generate_content(
model="gemini-2.0-flash-001",
contents="How’s the weather like today in London?",
config=GenerateContentConfig(
tools=[google_search_tool]
))

23. AI Agents with Gemini 2.0 - Beyond the Chatbot @martonkodok
Code Execution Tool
code_execution_tool = Tool(code_execution=ToolCodeExecution())
response = client.models.generate_content(
model="gemini-2.0-flash-001",
contents="What is the sum of the first 50 prime numbers?",
config=GenerateContentConfig(
tools=[code_execution_tool],
temperature=0))

24. AI Agents with Gemini 2.0 - Beyond the Chatbot @martonkodok
Spatial Understanding
aistudio.google.com/starter-apps/spatial
➔ 2D and 3D spatial understanding
➔ Segmentations masks
➔ Points
➔ 2D and 3D bounding boxes
➔ Local modal alternative: PaliGemma 2

25. Gemini 2.0
Enabling the agentic era
AI Agents with Gemini 2.0 - Beyond the Chatbot @martonkodok

26. AI Agents with Gemini 2.0 - Beyond the Chatbot @martonkodok
Core Pillars of ADK
➔ Open Source
➔ Code agents like Google
➔ The only dependency is a model
➔ Run on your laptop deploy anywhere
➔ Orchestrate automatically in sequence/parallel
➔ OpenAPI tools
➔ Supports Toolbox, MCPs, A2A
Agent Development Kit

27. AI Agents with Gemini 2.0 - Beyond the Chatbot @martonkodok
Build multi-agent capabilities
➔ Function tools
➔ Built-in tools
➔ Third party tools
➔ Agent Garden on Google Cloud
➔ MCP Tools
➔ OpenAPI tools
➔ Agent2Agent Protocol (A2A)

28. AI Agents with Gemini 2.0 - Beyond the Chatbot @martonkodok
ADK vs Langgraph vs LLamaindex
➔ ADK has Gemini and LiteLLM support
Langgraph integrates with Langchain
➔ Agent workflow and delegation:
ADK uses LLM to decide agent routes
Langgraph controlled by stategraph/nodes
➔ Both support short- and long-term memory
ADK uses output key to manage state for multiple
agents - feels better.
➔ Guardrails:
ADK uses callback before/post LLM validation, which
can be more centralized control/cleaner
Langgraph needs you to manipulate state/LCEL
➔ Llamaindex focused on RAG knowledge assistants Multi-agent documentation from LangGraph.

29. AI Agents with Gemini 2.0 - Beyond the Chatbot @martonkodok
Flexibility in the way you interact with your agents

30. Demo 1
ADK agent
AI Agents with Gemini 2.0 - Beyond the Chatbot @martonkodok
Agent Development Kit

31. Gemini 2.0 use case
🍷wine collection into structured data
AI Agents with Gemini 2.0 - Beyond the Chatbot @martonkodok

32. AI Agents with Gemini 2.0 - Beyond the Chatbot @martonkodok
Dataset
➔ Thousands of professional photos
➔ Front + back side of the bottle(s)
➔ High detail photo quality

33. AI Agents with Gemini 2.0 - Beyond the Chatbot @martonkodok
Challenges with Gemini 2.0
➔ High quality dataset - clear text is visible on zoom
➔ Initial dry run produced ZERO success.
What could be the problem?
➔ LLMs works best with rectangle images
➔ Image greater > 384 pixels -> is cropped into tiles...
➔ Each tile is resized to 768x768
➔ and uses 258 tokens

34. AI Agents with Gemini 2.0 - Beyond the Chatbot @martonkodok
media_resolution config
➔ To control how input images are processed,
use the `media_resolution` config parameter:
➔ MEDIA_RESOLUTION_LOW:
the image is tokenized into 66 tokens (fixed).
➔ MEDIA_RESOLUTION_MEDIUM:
the image is tokenized into 258 tokens (fixed).
➔ MEDIA_RESOLUTION_HIGH:
the input image is split (if needed) into non-overlapping
crops, leading to X tiles of 258 tokens.

35. Gemini Spatial Understanding
returning segmentation masks
AI Agents with Gemini 2.0 - Beyond the Chatbot @martonkodok

36. AI Agents with Gemini 2.0 - Beyond the Chatbot @martonkodok
Gemini Spatial Understanding
➔ 2D bounding boxes
➔ Segmentation masks
➔ Points

37. AI Agents with Gemini 2.0 - Beyond the Chatbot @martonkodok
Extract info from images
You are an expert in text extraction
from images. Your task is to extract
all text from the wine bottle
label(s) in the **attached images**.
Combine the text from both images.
Return the text in markdown format,
preserving any formatting (e.g.,
bold, italics, lists) as closely as
possible.
Use headings (e.g., #, ##) to
organize the text if appropriate.
Using Gemini 2.0

38. AI Agents with Gemini 2.0 - Beyond the Chatbot @martonkodok
Results

39. Conclusions
AI Agents with Gemini 2.0 - Beyond the Chatbot @martonkodok

40. AI Agents with Gemini 2.0 - Beyond the Chatbot @martonkodok
Enable agentic era
➔ Delegate tasks to agents
➔ Think your ‘dev tasks’ as promptable
➔ Enable them in agentic experiences
➔ New open-source framework from Google designed to simplify the full stack end-to-end
development of agents and multi-agent systems
➔ Use ADK framework to leverage pre-built connectors
➔ Build Multi-Agent Applications

41. AI Agents with Gemini 2.0 - Beyond the Chatbot @martonkodok
Takeaways
➔ Agents Companion
➔ It extends the original whitepaper by focusing on key
areas needed for production-ready AI agents.
➔ There are insights on multi-agent systems, agent
evaluation techniques, Agent Ops, and Agentic RAG +
more.
➔ Read it here: https://bit.ly/3XIyFpS

42. AI Agents with Gemini 2.0 - Beyond the Chatbot @martonkodok
Architecting a Multi-Agent System
with Google A2A and ADK
➔ Author: Karl Weinmeister
➔ Youtube channel: Cloud with Karl
➔ Agentic Trading Simulator
➔ Simulator UI (FastAPI) - calls A2A AlphaBot service
➔ AlphaBot (ADK/Python) - receives A2A requests
➔ RiskGuard (ADK/Python) - receives A2A requests

43. AI Agents with Gemini 2.0 - Beyond the Chatbot @martonkodok
CodeLab - Do it yourself
➔ Google's Agent Stack in Action: ADK, A2A, MCP on Google Cloud
➔ codelabs.developers.google.com/instavibe-adk-multi-agents/instructions

44. Thank you.
Reea.net - Integrated web solutions driven by creativity
to deliver projects.
#geecon Room 12
Follow for articles:
martonkodok.medium.com
Slides available on:
slideshare.net/martonkodok
Q & A