🚀 Intelligent Contract API (GenLayer Testnet)

AI-powered, verifiable smart contract simulation built for GenLayer

📌 Overview

This project implements an Intelligent Contract System using FastAPI, designed for the GenLayer ecosystem.

It combines AI-based evaluation with a deterministic verification layer to simulate verifiable computation.

Key capabilities include:

• Evaluating user input through an AI logic module
• Recomputing outputs for deterministic verification
• Maintaining contract state and execution history for auditability

👉 This demonstrates how intelligent contracts can operate in a scalable, transparent, and verifiable way.

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🧠 Key Features

• 🤖 AI-powered evaluation (ai.py)
• ✅ Deterministic verification layer (verifier.py)
• 🧾 State management (pending → verified / rejected)
• 📜 Execution history tracking (audit log)
• 🔐 SHA-256 hashing for integrity
• ⚡ Modular FastAPI architecture
• 🧪 Unit testing included

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🏗️ Project Structure

intelligent-contract/
│
├── app/
│   ├── __init__.py
│   ├── contract.py        # Core intelligent contract logic
│   ├── ai.py              # AI evaluation logic
│   ├── verifier.py        # Verification logic
│   ├── models.py          # Data models (Pydantic)
│   ├── config.py          # Environment config
│
├── api/
│   ├── main.py            # FastAPI entry point
│   ├── routes/
│   │   └── contract.py    # API routes
│
├── tests/
│   ├── test_contract.py   # Unit tests
│
├── .env.example
├── requirements.txt
├── README.md
└── run.py

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⚙️ Installation & Run

1. Clone repository

git clone https://github.com/mrtrangith2023/intelligent-contract.git
cd intelligent-contract

2. Install dependencies

pip install -r requirements.txt

3. Run server

uvicorn api.main:app --reload

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🌐 API Endpoints

Base URL:

http://localhost:8000/api

🔹 POST /submit

Submit request for AI evaluation

Request

{
  "user": "alice",
  "amount": 100
}

Response

{
  "request_id": "uuid",
  "result": {
    "score": 0.9,
    "decision": "approved"
  },
  "status": "pending"
}

🔍 Example Output

👉 This output demonstrates AI evaluation + verifiable execution.

{
  "request_id": "abc123",
  "result": {
    "score": 0.9,
    "decision": "approved"
  },
  "status": "pending"
}

---

🔹 GET /verify/{request_id}

Verify result deterministically

Response

{
  "valid": true,
  "status": "verified"
}

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🔹 GET /history

View execution logs (audit trail)

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🔹 GET /state/{request_id}

Get stored contract state

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🧠 Intelligent Logic

• AI evaluates input data (e.g., scoring logic)
• Decision is generated (approved / rejected)
• Verification recomputes result to ensure correctness

👉 This simulates verifiable computation in smart contracts

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🔐 Security & Integrity

• SHA-256 hashing ensures data integrity
• Every action is logged with hash + timestamp
• History acts like a blockchain audit log

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🧪 Testing

Run tests:

pytest

Example:

def test_submit_and_verify():
    contract = IntelligentContract("0xADMIN")
    res = contract.submit_request("user", {"amount": 100})
    assert contract.verify(res["request_id"])["valid"] is True

---

📸 Demo

Swagger UI:

http://localhost:8000/docs

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🚀 Future Improvements

• Database persistence (PostgreSQL / Redis)
• Authentication (JWT)
• Advanced AI models
• On-chain integration (GenLayer L1)

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🏆 Why This Project?

This project demonstrates:

• AI + Smart Contract integration
• Verifiable execution model
• Modular backend architecture
• Real-world scalable design

👉 Aligned with GenLayer vision of intelligent, verifiable computation

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👤 Author

TAM Web3 Builder | Exploring AI x Blockchain 🚀

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📎 Submission

• GitHub Repo: https://github.com/mrtrangith2023/intelligent-contract
• Demo: Swagger UI (/docs)

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🔥 Built for GenLayer Testnet Mission