In the rapidly evolving crypto market, identifying alpha, validating strategies, and executing trades in real time is critical. ⚡ SignalFlow is an all-in-one platform designed to streamline this process through a data-driven trading loop.

1. Signal Discovery

• Query any on-chain data using natural language (e.g. large transfers, DEX activity, active wallets).
• Visualize results instantly with interactive charts.
• Save and reuse signals in downstream strategies.

2. Strategy Backtesting

• Backtest any signal combination with historical data.
• Evaluate performance via key metrics like PnL, drawdown, and Sharpe ratio.
• Quantify edge and validate ideas before deployment.

3. Real-Time Execution

• Combine signals, define trigger conditions, and monitor live on-chain activity.
• Automatically execute buy/sell actions when criteria are met.
• Close the loop from insight to trade with full automation.

• Intelligent agents for processing and responding to user queries
• Natural language understanding and generation
• Integration with the chat interface
• MCP (Message Control Protocol) for managing agent responses

• Python-based server (>= 3.10)
• Handles communication between frontend and AI agents
• API endpoints for subscription and visualization data

• React-based web application
• Features:
  • Chat interface with AI agents
  • Subscription management
  • Visualization canvas
  • File management system
• Change theme color in src/constants/colors.js and tailwind.config.js

• Subscription NFT system
• Deployed on network:
  • BSC Testnet: https://testnet.bscscan.com/address/0x77EE0B4f2e96A369dC82B20834b50032921D8801

• Node.js >= 16
• Python >= 3.10
• Hardhat
• MetaMask or compatible Web3 wallet

1. Clone the repository

git clone <repository-url>
cd <project-directory>

2. Install AI Agents dependencies

cd agents
pip install -r requirements.txt

3. Install Backend dependencies

cd backend
pip install -r requirements.txt

4. Install Frontend dependencies

cd frontend
npm install

5. Install and compile contracts

cd hardhat
npm install
npx hardhat compile

1. Set up environment variables

# Create .env files in each component directory
cp .env.example .env

2. Configure the following in your .env files:

• AI API keys
• Backend server URLs
• Contract addresses
• Network configurations

1. Start the Backend server

uvicorn backend.main:app --reload

3. Start the Frontend development server

cd frontend
npm run dev

4. Deploy contracts (if needed)

cd hardhat
npx hardhat run scripts/deploy.js --network <network-name>

├── agents/ # AI agents implementation
├── backend/ # Python backend server
├── frontend/ # React frontend application
└── hardhat/ # Smart contract development