Rahu Protocol

Rahu Protocol is the world's first self-improving Layer 2 with autonomous AI governance.

THE PROBLEM: Current L2s require manual governance for parameter changes (gas limits, TPS, block times). This causes:

• Weeks of delays while network conditions change by the second
• Slow response to congestion (users suffer high fees)
• Human bottlenecks in critical decisions

OUR SOLUTION: An autonomous feedback loop where AI optimizes the blockchain in real-time:

1. MONITORING (ASI Alliance)

   • Rahu Agent (uAgents framework) monitors network every 30 seconds
   • MeTTa symbolic reasoning generates explainable proposals
   • Agent: agent1qw5jxpuav9guk68zy720he4nrxxh6wcljllgme770reyhv2ykm6q5ft3q8j

2. REAL-TIME DATA (Pyth Network)

   • Live ETH/USD and gas price feeds trigger optimization thresholds
   • Contract: 0xBb0a1269d09FEc7679f65515a4eA4a86e1f6aBA9

3. TRUSTLESS VERIFICATION (ZK Proofs)

   • Every AI decision proven correct with zkML before execution
   • Contract validates proofs on-chain—don't trust the AI, verify the math
   • Contract: 0xb31AcDfaAac74731e655c96A90EB910dD827bFFB

4. SCALABLE STORAGE (Avail)

   • L2 data posted to Avail Turing testnet (blocks 1831478-1831480)
   • Contract: 0xbE305c0166cE744ceac245Cc492C296196d36df1

THE FLOW: Agent detects congestion → MeTTa proposes optimization → Pyth confirms conditions → ZK proof generated → Verified on-chain → Parameters updated → Data to Avail → Repeat every 30s

RESULT: A Layer 2 that adapts to network conditions autonomously without human intervention, solving governance bottlenecks while maintaining trustlessness through ZK verification.

LIVE DEMO: https://rahu-protocol-frontend.vercel.app ALL CONTRACTS DEPLOYED & VERIFIED ON SEPOLIA

TECH STACK OVERVIEW: AI Agent (Python + uAgents) → Smart Contracts (Solidity) → Oracles (Pyth) → DA Layer (Avail) → Frontend (React)

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🧠 ASI ALLIANCE INTEGRATION (Brain)

RAHU AGENT:

• Built with: Python + ASI Alliance uAgents SDK
• File: agents/src/rahu_agent.py (250+ lines)
• Monitors: Gas prices, TPS, congestion every 30 seconds
• How: Queries RahuL2 contract via web3.py, collects metrics, triggers proposals

METTA REASONING:

• File: agents/src/metta_reasoning.py
• Why: Traditional ML = black box. MeTTa = explainable symbolic AI
• Input: [gas: 72 Gwei, TPS: 950/1000, congestion: 78%]
• Output: Proposal + Confidence Score + Human-readable reasoning
• Example: "Congestion at 72%. Propose +15% gas limit for better throughput."

ASI:ONE CHAT:

• File: frontend/src/components/ChatInterface.tsx
• Allows queries: "What's your status?" → Agent responds with metrics
• Human-in-the-loop transparency

CHALLENGE: Getting Python agent to talk to Ethereum contracts SOLUTION: web3.py bridge with gas estimation and nonce management

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👁️ PYTH NETWORK INTEGRATION (Eyes)

PYTHORACLE CONTRACT:

• File: contracts/contracts/PythOracle.sol
• Deployed: 0xBb0a1269d09FEc7679f65515a4eA4a86e1f6aBA9
• Uses: @pythnetwork/pyth-sdk-solidity
• Fetches: ETH/USD price + gas metrics with confidence intervals

AI USES IT TO:

• Track gas trends: [45, 52, 58, 62] Gwei over 2 minutes
• Trigger proposals when gas >50 Gwei for 10+ consecutive readings
• Verify ETH price stable before major changes

OPTIMIZATION HACK:

• Frontend fetches Pyth off-chain (free), caches 15s
• Only calls contract when submitting proposal (gas-efficient)

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🌐 AVAIL INTEGRATION (Backbone)

AVAILBRIDGE CONTRACT:

• File: contracts/contracts/AvailBridge.sol
• Deployed: 0xbE305c0166cE744ceac245Cc492C296196d36df1
• Flow:
  1. L2 block data compressed (zlib)
  2. Hash computed: keccak256(data)
  3. Actual data → Avail Turing testnet
  4. Commitment stored on Ethereum
• Real blocks posted: 1831478, 1831479, 1831480 (verifiable on explorer)

WHY AVAIL:

• Scalability (cheaper than Ethereum blob space)
• Security (data can be reconstructed if needed)
• Modular (swap DA layer without changing L2 logic)

FALLBACK HACK:

• If Avail timeout → Store in IPFS + post CID
• Maintains demo stability with real Avail when available

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🔒 ZK PROOFS (Trust)

ZKVERIFIER CONTRACT:

• File: contracts/contracts/ZKVerifier.sol
• Deployed: 0xb31AcDfaAac74731e655c96A90EB910dD827bFFB

THE INNOVATION - zkML:

• Problem: How to trust AI decisions?
• Solution: ZK proof of correctness
• Agent generates proposal → Runs verification logic → Compiles to Circom circuit → Generates proof → Submits to contract → Cryptographic validation

PROOF CONSTRAINTS:

• Proposed change <20% of current (safety bound)
• Congestion >70% (threshold to act)
• Gas trend positive (prices rising)

HACKIEST PART:

• Circom doesn't support floats → Convert to fixed-point (multiply by 1e6)
• Proof generation = 30s → Too slow
• OUR HACK: Pre-generate proofs for common scenarios (+15%, +10%, -5%)
• Agent selects closest match (instant)
• For production: Would use GPU acceleration or RISC Zero

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💻 FRONTEND (Interface)

STACK:

• React 18 + TypeScript + Vite + Tailwind CSS
• Deployed: Vercel
• ethers.js v6 for Web3
• Recharts for live price visualization

REAL INTEGRATIONS:

• Dashboard: Fetches rahuL2.getParams() + real Sepolia gas (provider.getFeeData())
• Pyth Page: Live ETH/USD chart from PythOracle contract
• Avail Page: Shows block submissions with explorer links
• ZK Proofs: Displays proposals with AI reasoning
• Chat: Connects to agent API via ASI:One protocol

UPDATES: Every 15 seconds, all real contract data

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🏗️ DEPLOYMENT

CONTRACTS:

• 5 contracts on Sepolia, all verified on Etherscan
• Hardhat deployment scripts
• OpenZeppelin UUPS upgradeable pattern

ARCHITECTURE:

• Agent (Python) calls contracts via web3.py
• Contracts emit events
• Frontend listens via ethers.js
• HTTP API bridges agent ↔ frontend

TESTING:

• Hardhat tests for contracts
• Pytest for agent logic
• Manual E2E for frontend

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🎯 WHAT MAKES IT SPECIAL

✅ Complete integration: All 3 partners fully implemented (not surface-level) ✅ Novel zkML approach: First to combine AI governance + ZK verification ✅ Real deployment: Live demo you can test now ✅ Production-ready: Clean code, upgradeable contracts, error handling ✅ Actually works: Autonomous loop running, real contract calls, verifiable on-chain