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SpartaHack X

Be a part of Michigan State University’s Annual Hackathon tailored for those who see opportunity in a challenge and seek to widen their horizons.

February 1, 2025

Michigan State University

Schedule

Wednesday, January 29

15:00 EST

Pre-Hackathon Workshop

Saturday, February 01

08:00 EST

Check-in and Breakfast

Michigan State University

10:00 EST

Opening Ceremony

Michigan State University

12:00 EST

Hacking Begins

Michigan State University

13:00 EST

Intro to Fetch.ai Tech

Michigan State University

14:00 EST

Lunch

Michigan State University

15:30 EST

Learn how to best utilise Fetch.ai to Build Solutions

Michigan State University

Sunday, February 02

24:00 EST

Midnight Snack

Michigan State University

08:00 EST

Caffeine Recharge

Michigan State University

12:00 EST

Hacking Ends

Michigan State University

12:00 EST

Brunch

Michigan State University

13:00 EST

Hacker Demos

Michigan State University

15:00 EST

Closing Ceremony

Michigan State University

Introduction

Fetch.ai’s vision is to create a marketplace of dynamic applications. We are empowering developers to build on our platform that can connect services and APIs without any domain knowledge.

Our infrastructure enables ‘search and discovery’ and ‘dynamic connectivity’. It offers an open, modular, UI agnostic, self-assembling of services.

Our technology is built on four key components:

uAgents - uAgents are autonomous AI agents built to connect seamlessly with networks and other agents. They can represent and interact with data, APIs, services, machine learning models, and individuals, enabling intelligent and dynamic decision-making in decentralized environments.

Agentverse - serves as a development and hosting platform for these agents.

Fetchai SDK – seamlessly integrates your AI Agent into Agentverse and empowers dynamic connectivity with the Fetch.ai SDK

Fetch Network - underpins the entire system, ensuring smooth operation and integration.

Challenge statement

Unleash your creativity by designing specialised AI Agents in any domain—whether it's Finance, Healthcare, Education, or Social Impact using any Agentic framework of your choice, register your agents on Agentverse, a dynamic central directory where agents seamlessly interact and collaborate to deliver powerful solutions.

Take it a step further by building a personalized assistant that leverages the Search and Discovery feature on Agentverse. Your assistant will intelligently connect with other agents to fulfil user needs, orchestrating tasks with precision and efficiency.

Picture a world where users can effortlessly engage with a network of AI Agents tailored to their unique requirements—this is your opportunity to make it a reality.

Are you ready to innovate, collaborate, and automate the future of intelligent systems? The challenge awaits!

Additional Information:

Pre-Hackathon Workshop Presentation

Please submit your projects on Devpost

What to Build

In this hackathon, participants are encouraged to showcase their skills by building innovative solutions centered around AI Agents. Here's what you'll create:

Specialized AI Agents Use your creativity to design AI Agents tailored for specific domains or tasks, such as customer support, data analysis, content creation, research assistance, or more. Leverage agentic frameworks like uAgents, LangChain, CrewAI, Autogen, or others to build these agents. Once your agents are ready, register them on Agentverse using the Fetch.ai SDK enabling them to interact with other agents in the ecosystem. Your goal is to contribute to a diverse and robust agent directory.

Personalized Assistant Agent Build a Personalised Assistant Agent that uses the Search and Discovery feature on Agentverse. This assistant will dynamically connect with the most relevant agents-whether created by you or other participants to fulfil user queries and coordinate tasks efficiently. The assistant should intelligently manage interactions to deliver seamless, user-centric experiences.

Fetch.ai tech stack

architecture

Product Overview

architecture

Quick start example

This file can be run on any platform supporting Python, with the necessary install permissions. This example shows two agents communicating with each other using the uAgent python library.
Read the guide for this code here ↗

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from uagents import Agent, Bureau, Context, Model
    class Message(Model):
        message: str
    
    sigmar = Agent(name="sigmar", seed="sigmar recovery phrase")
    slaanesh = Agent(name="slaanesh", seed="slaanesh recovery phrase")
        
    @sigmar.on_interval(period=3.0)
    async def send_message(ctx: Context):
       await ctx.send(slaanesh.address, Message(message="hello there slaanesh"))
        
    @sigmar.on_message(model=Message)
    async def sigmar_message_handler(ctx: Context, sender: str, msg: Message):
        ctx.logger.info(f"Received message from {sender}: {msg.message}")
    
    @slaanesh.on_message(model=Message)
    async def slaanesh_message_handler(ctx: Context, sender: str, msg: Message):
        ctx.logger.info(f"Received message from {sender}: {msg.message}")
        await ctx.send(sigmar.address, Message(message="hello there sigmar"))
        
    bureau = Bureau()
    bureau.add(sigmar)
    bureau.add(slaanesh)
    if __name__ == "__main__":
        bureau.run()
Video introduction
Video 1
Introduction to agents
Video 2
On Interval
Video 3
On Event
Video 4
Agent Messages

Judging Criteria

Each row is scored 1 to 5, with a total score being your final score.
Parameters
Definition
Functionality
How well do your AI Agents perform their intended tasks? How effectively are APIs and frameworks integrated into your solution?
Agentverse Integration
Have you registered all your AI Agents on Agentverse?
Quantity of Agents Created
How many AI Agents have you created for this project? Does your submission demonstrate creativity and diversity in your AI Agents?
Personal Assistant Development
Does your assistant utilize the Search and Discover feature on Agentverse to dynamically connect with and coordinate tasks between multiple agents?
Innovation and Impact
Does your project address a real-world problem or introduce novel ideas?

Prizes

Winner

$1000 USD Cash Prize

Fetch.ai Nexus Prize

Second Prize

$500 USD Cash Prize

Agentverse Champion

Third Prize

$500 USD Cash Prize

Fetch.ai AI Agent Trailblazer Prize

Judges

Profile picture of Sana Wajid

Sana Wajid

Senior Vice President

Profile picture of Mark Losey

Mark Losey

CTO at FlockX

Profile picture of Devon Bleibtrey

Devon Bleibtrey

CEO at FlockX

Profile picture of Abhimanyu Gangani

Abhimanyu Gangani

Developer Advocate

Profile picture of Kshipra Dhame

Kshipra Dhame

Developer Advocate

Mentors

Profile picture of Tanay Godse

Tanay Godse

Developer Advocate

Profile picture of Parth Joshi

Parth Joshi

Developer Advocate

Profile picture of Aneil Shah

Aneil Shah

Developer Advocate