BNB AI Hack
February 14, 2025
Virtual
Schedule
10:00 UTC
Hackathon Begins
Virtual
10:00 UTC
Submission Period Starts
Virtual
23:59 UTC
Submission Period Ends
Virtual
12:00 UTC
Top 10 Demos
Virtual
12:00 UTC
Winners Announcement
Virtual
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 an agent using Fetch agent tech that performs on-chain actions. Utilize Fetch.ai's cutting-edge agent technology to create an AI agent that autonomously performs on-chain actions. Your agent should effectively interact with smart contracts, execute transactions, and demonstrate intelligent use of blockchain capabilities.
Key Features to Showcase:
- Agent Interaction: Enable the agent to autonomously communicate with other agents or external data sources.
- On-Chain Execution: Design the agent to perform blockchain actions such as token transfers, contract calls, or governance voting
- Smart Contract Integration: Create a scenario where the agent interacts with one or more smart contracts to accomplish a specific task.
- Autonomy and Intelligence: Showcase decision-making capabilities using AI techniques (e.g., optimizing gas fees, and selecting the best trades).
Example Use Cases:
- An agent that tracks token prices and executes trades based on predefined thresholds.
- An agent that optimizes yield farming strategies by interacting with DeFi protocols.
Deliverables:
- A fully functional Fetch.ai agent capable of performing at least one meaningful on-chain action.
- Agents should be registered/hosted on Agentverse.
- Comprehensive documentation explaining the agent’s design, setup, and functionality.
- A short demo video demonstrating the agent in action.
Additional Information:
Please submit your projects on Devpost
Complete the authorisation process and join the bnb-ai-hack-sponsor-challenge channel on the BNB Chain Discord Server.
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
- Fetch.ai Tech Utilization – How well does the solution leverage the Fetch.ai agent framework, ensure interoperability with other agents, and integrate with Agentverse?
- Technical Implementation – Is the code well-structured, efficient, and correctly handling on-chain interactions such as smart contract calls and transactions?
- Agent Autonomy & Intelligence – How effectively does the agent make autonomous decisions, such as optimizing gas fees, executing trades, or participating in governance?
- Impact & Use Case Viability– How relevant and useful is the agent in real-world blockchain applications such as DeFi, governance, or automation?
Prizes
Winner
$5000 USD USD Cash Prize
Best Smart Contract Integration
First Prize
$3000 USD USD Cash Prize
The On-Chain Innovator Award
Second Prize
$2000 USD USD Cash Prize
The Intelligent Automation Award
Sponsors
Collaborators
Judges
Sana Wajid
Senior Vice President
Chirag Maliwal
Technical Lead
Alex Blagirev
Strategic Initiatives Officer
Haley Lowy
Alignment & Coordination Officer at SingularityNET
Mentors
Kshipra Dhame
Developer Advocate
Abhi Gangani
Developer Advocate