Technical Theory
Building a Multi-Agent System using Gemini and Gemma models | Google Codelabs
Technical Stack
Language Model
Gemini API
3 / 5
Language Model
Gemma Models
3 / 5
Programming Language
Python
3 / 5
Generative AI
Generative AI Fundamentals
2 / 5
Executive Summary
This codelab guides you through building a multi-agent system using the Gemini and Gemma models. You'll learn how to design and implement a system where multiple AI agents collaborate to solve complex tasks. This is ideal for developers interested in exploring advanced AI concepts and practical applications of large language models.
Technical Breakdown
| Category | Technology | Experience | Resources |
|---|---|---|---|
| Language Model | Gemini API | 3 / 5 |
Documentation |
| Language Model | Gemma Models | 3 / 5 |
Documentation |
| Programming Language | Python | 3 / 5 |
Documentation |
| Generative AI | Generative AI Fundamentals | 2 / 5 |
Documentation |
Learning Objectives
- Design a multi-agent system for complex problem-solving.
- Implement agents using Gemini and Gemma models.
- Evaluate the performance of a collaborative AI system.
Key Learning Points
- Understand the architecture of multi-agent systems.
- Learn how to integrate different LLMs for optimal performance.
- Gain practical experience in building a collaborative AI environment.
Core Skills Gained
- Python
- Generative AI Fundamentals
- API Usage