We are proud to be the
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:
Agents - AI Agents are independent decision-makers that connect to the network and other agents. These agents can represent data, APIs, services, ML models and people.
Agentverse - serves as a development and hosting platform for these agents.
AI Engine – enables humans to interact with the dynamic agent marketplace using natural language to execute the objective.
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
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()Important links
Examples to get you started:
Judging Criteria
Support
Support will be available at the hackathon, and you can also reach out to the core dev team who will be able to support you via Discord ↗
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
Ready to get started with Fetch.ai Platform?
