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πŸš€ GenX FX Trading Platform

πŸ““ Knowledge Base

  • NotebookLM: Access here
  • Note: This notebook is available for reading and writing. AI agents must read it before starting work.

An advanced, AI-powered platform for Forex, Cryptocurrency, and Gold trading.

Python Docker License Open in Gitpod


🎯 Overview

GenX FX is a comprehensive, AI-powered trading system that combines machine learning, real-time market analysis, and automated execution capabilities. The platform is designed for both traders who want to use pre-built Expert Advisors (EAs) and for developers who want to build, test, and deploy their own automated strategies.

✨ Key Features

  • πŸ€– AI-Powered Signals: Utilizes advanced machine learning models, including an ensemble predictor, to generate high-quality trading signals.
  • πŸ“Š Professional Expert Advisors: Comes with pre-built EAs for MetaTrader 4 and 5, specializing in Gold and major Forex pairs, with sophisticated risk management.
  • 🌐 24/7 Cloud Operation: Designed for continuous, 24/7 operation and is ready for deployment on cloud platforms like Google Cloud and AWS.
  • ⚑ Real-Time Integration: Features live data feeds through WebSocket and REST APIs for instant trade execution and real-time analysis.
  • πŸ”— Multi-Broker Support: Integrates with various brokers via ForexConnect, FXCM, and Exness, providing flexibility and choice.
  • πŸ“ˆ Advanced Signal Generation: Generates ML-based trading signals and exports them to Excel, CSV, or JSON formats for consumption by EAs or other tools.
  • πŸ› οΈ Unified CLI: A powerful and unified command-line interface (genx) for all major operations, from system status checks to automated deployments and AI model training.

πŸš€ Getting Started

There are two main ways to get started with GenX FX, depending on your goals.

For Traders: Using a Pre-Built Expert Advisor

This is the fastest and easiest way to start trading, especially with the specialized Gold Master EA.

  1. Download the EA:

    • Navigate to the expert-advisors/ directory.
    • Download the GenX_Gold_Master_EA.mq4 file.
  2. Install in MetaTrader 4:

    • Open your MT4 terminal.
    • Go to File > Open Data Folder.
    • Navigate to the MQL4/Experts/ directory.
    • Copy the downloaded .mq4 file into this directory.
  3. Configure and Run:

    • Restart MT4 or refresh the "Expert Advisors" list in the Navigator panel.
    • Drag the "GenX_Gold_Master_EA" onto a chart (e.g., XAUUSD).
    • Configure the settings as described in the Gold Master EA Guide.
    • Enable "AutoTrading" on your MT4 terminal and start trading.

For Developers: Full System Setup

This option allows you to run the entire backend, API, and AI models for development and customization.

  1. Clone the Repository:

    git clone https://github.com/Mouy-leng/GenX_FX.git
    cd GenX_FX
  2. Install Dependencies: The project uses both Python and Node.js.

    pip install -r requirements.txt
    npm install
  3. Set Up Environment Variables:

    • Copy the .env.example file to a new file named .env.
    • Fill in the required API keys and configuration details for the services you plan to use (e.g., FXCM, Gemini, etc.). See the API Key Setup Guide for more details.
  4. Initialize the System: Use the unified CLI to initialize the system, which will create necessary directories and default configurations.

    python genx_cli.py init
  5. Run the System: The platform includes a concurrent runner for the frontend and backend services.

    npm run dev

    This command will start the FastAPI backend and the React frontend simultaneously. You can then access the platform at http://localhost:3000.


πŸ—οΈ System Architecture

The GenX FX platform is a monorepo containing several key components:

  • api/: The main backend powered by FastAPI. It serves REST endpoints for trading, predictions, and system management.
  • core/: The core trading logic, including strategies, indicators, pattern detection, risk management, and the main trading engine.
  • ai_models/: Contains the machine learning models (e.g., EnsemblePredictor) and the logic for generating predictions.
  • client/: The web-based frontend built with React and TypeScript.
  • services/: Contains various services for interacting with external APIs like FXCM, Reddit, and Google Gemini, as well as WebSocket and spreadsheet managers.
  • expert-advisors/: Contains the MetaTrader 4 (MQ4) and MetaTrader 5 (MQ5) Expert Advisor files.
  • utils/: Shared utilities for logging, configuration management, and model validation.
  • deploy/: Deployment scripts for various cloud platforms, including AWS and Exness VPS.

πŸ› οΈ Development and Testing

Running Tests

The repository includes a comprehensive test suite for both the Python backend and the frontend.

  • Python Tests (pytest):
    python run_tests.py
  • JavaScript/TypeScript Tests (Vitest):
    npm test

Code Style and Linting

  • Python: The project follows PEP 8 standards. We recommend using a formatter like Black.
  • TypeScript/JavaScript: The project uses Prettier and ESLint for code formatting and linting.
    npm run lint

πŸ“š Documentation

For more detailed information, please refer to the following guides in the repository:


🀝 Contributing

We welcome contributions from the community! Please follow these steps to contribute:

  1. Fork the repository.
  2. Create a new feature branch: git checkout -b feature/your-amazing-feature
  3. Commit your changes: git commit -m 'Add your amazing feature'
  4. Push to the branch: git push origin feature/your-amazing-feature
  5. Open a Pull Request.

Please make sure to read our Contributing Guidelines and Security Policy before submitting your changes.

πŸ“„ License

This project is licensed under the MIT License. See the LICENSE file for more details.

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