We are proud to be the
Gold sponsor
HACK IT OUT
November 11, 2024
IIT Patna
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
Build a solid application using uAgents using custom frontend.
OR
Build a solid solution (chained integrations) that works on DeltaV.
Note: It's a must to include uAgents in your applications.
Additional Information : You can post all your queries in the #innovation-labs channel on Discord.
If you want to learn more about uAgents through articles, please Click Here.
Submission Link: Devpost
You can find more interesting integrations and example on our gitHub Repo.
Pre-built Fetch.ai Agents list
Hackathon Guide
Feel free to integrate the Pre-built Fetch.ai Agents into your applications.
Fetch.ai tech stack
Product Overview
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 ↗
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()
Examples to get you started:
Judging Criteria
Collaborators
Judges
Sana Wajid
Programme and Operations Director
Rishank Jhavar
Stream Lead, Dev Advocacy and Product Marketing
Kshipra Dhame
Developer Advocate
Abhimanyu Gangani
Developer Advocate
Mentors
Gautam Kumar
Developer Advocate
Dev Chauhan
Developer Advocate