NeuroTrade Agents

⚠️IMPORTANT NOTE: force push causing previous commit histories to omit, please check repo activity for previous commits. This project is also only 30% completed due to my ineffective time management, however hopefully this project is unique and worth providing grants for.

ChainFusion Agents is a next-generation multi-agent platform that blends federated learning, blockchain incentives, and decentralized finance into a seamless framework for real-world collaboration.

At its core, ChainFusion Agents enables privacy-preserving federated learning (FL): participants train AI models locally and only submit encrypted updates (hashes) to the blockchain. A central coordinator agent aggregates these updates into a global model, ensuring fairness and transparency while keeping raw data private.

But ChainFusion goes further. By integrating with the Artificial Superintelligence Alliance (ASI), all components—clients, aggregator, and coordinator—become autonomous uAgents. This allows agents to negotiate, reason, and self-organize, enabling advanced scenarios like:

1.Dynamic agent onboarding & reputation tracking. 2.Automated dispute resolution if updates conflict. 3.Human–agent interaction via ASI:One chat protocol.

On the economic layer, Polygon x402 agentic payments power seamless micropayments and rewards. Clients are compensated automatically for valid contributions, unlocking real-world utility where even non-technical users can participate in federated AI systems without blockchain expertise.

To expand utility, ChainFusion leverages the graph API to fetch and display

The result is a trustless, agentic FL marketplace for domains like: 1.B2B energy trading (auction-style pricing for grid balancing). 2.Healthcare & IoT analytics (secure FL across hospitals or sensors). 3.Consumer apps (AI personalization with on-chain rewards).

ChainFusion Agents is designed for end-users first. With a minimal web dashboard, participants simply “join and earn,” while agents handle coordination, training, payments, and DeFi optimization in the background.

By uniting federated learning, multi-agent reasoning, and DeFi automation, ChainFusion Agents delivers a truly novel foundation for the future of autonomous collaboration—making AI and Web3 usable by everyone, not just blockchain experts.

Phase 1: ASI Alliance Agentification (Highest Impact) Goal: Transform client, aggregator, and coordinator into autonomous uAgents, enabling negotiation, reasoning, and chat (ASI:One).

Tasks: Agent Wrappers: Refactor client.py, aggregate.py, and blockchain coordinator into agent processes using ASI/uAgents framework (or similar Python agent libraries). Each agent exposes endpoints for: update submission, dispute negotiation, onboarding, and real-time chat.

Agent Registry: On-chain/JSON registry for agent metadata (address, endpoint, capabilities).

ASI:One Chat Protocol: Simple protocol for agents and humans to join, message, and coordinate in rounds.

Add basic negotiation mechanics: agents reject/accept updates, automatically escalate disputes, etc.

Human-Interaction Hooks: Agents can respond to human requests (e.g., join round, inquire about rewards, raise dispute).

Approach: Build minimal wrappers first. Use lightweight agent/event libraries (uAgents, FastAPI, or AIoT agent toolkits). Hard-code round roles for now; add chat/negotiation hooks after agents communicate.

Phase 2: Polygon x402 Micropayments Goal: Enable per-round AI streaming rewards, refunds, and auction settlements via Polygon's x402 flows.

Tasks: Integrate x402 SDK: Replace flat ERC20 mint() rewards in Coordinator.sol with x402 flows for streaming. Expose CLI and agent endpoints for creating, monitoring, and closing flows.

Implement Subscriptions/Refunds: Auto-stream per-round rewards to participants as flows. Allow easy “refund”/dispute settlement via a closing/adjusting flow. Use auction clearing price as input to settlement flow logic.

Approach: Use x402 testnet and mock flows initially for local/testing. UI should visualize active flows (“streaming income”).

Phase 3: 1inch Automated DeFi Hooks Goal: Let participants auto-swap/onboard tokens into desired assets/yield via 1inch API.

Tasks: Client/Agent Integration: On reward receipt, call 1inch API to swap to stablecoins/yield tokens. Let agent UI set limit order hooks: “auto-sell If price > target X”, “auto-yield deposit”.

Auto-Trade/Auto-Yield Logic: Simple strategy modules for “auto-sell,” “auto-HODL,” “auto-yield.” Payout bots can automate the process based on client config.

Approach: Start with manual CLI/API calls, then automate on agent consensus or user toggle.

Phase 4: Frontend Dashboard Goal: User-friendly live dashboard where anyone can join, track, and trade rewards easily.

Tasks: React/Next.js Dashboard: Basic live view: model rounds, accuracy, participant stats, received rewards.

Wallet & Flow Integration: Login with wallet or simple OAuth. Toggle trading/yield options visually.

Activity Feed/Chat: Show agent chat, negotiation, and on-chain events.

Approach: Build clean UI with hooks ready for future DeFi integrations. Focus on user onboarding and optimization. Flow EVM Deployment (Bonus) Deploy Coordinator, RewardToken, and possibly agent registry contract on Flow EVM testnet. Ensure Solidity/ABI compatibility (low friction).