Ocula Finance

Ocula Finance is an AI-assisted financial analytics platform designed to provide intelligent, real-time trading signals and portfolio insights. It leverages AI, automation, and modern web technologies to empower traders with actionable information delivered directly via a responsive dashboard and Telegram alerts.

🔗 Visit the platform:
🌐 https://oculafinance.com
🧪 Backup: https://oculafinance.netlify.app/

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🧠 Features

• AI Trading Assistant – Predictive models trained on market data (MetaTrader 5 required for AI usage).
• Real-Time Alerts – Browser & Telegram-based alerts for trading signals.
• Integrated Web Dashboard – Built using ReactJS for fast, responsive interaction.
• Secure Backend API – Python Flask-based backend connected to a MongoDB database.
• Email Integration – With Zoho and EmailJS for user communication.
• Environment-based Configurations – Easily switch between test and production environments.

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🗂️ Project Structure

Ocula-Finance/
│
├── client/            # ReactJS Frontend
├── server/            # Python Flask Backend + AI
└── README.md

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⚙️ Requirements

Software

Component	Version
Python	3.12
Node.js	20.11.1
MongoDB	Atlas or Local
MetaTrader 5	Required for AI
OS Compatibility	Backend – Any OS AI – Windows only

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🚀 Getting Started

1. Clone the Repository

git clone https://github.com/micpana/Ocula-Finance.git
cd Ocula-Finance

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2. Setup Environment Variables

Backend (Linux/macOS):

export LIVE_DB_URL="your_live_db_url"
export LIVE_DB_USERNAME="your_username"
export LIVE_DB_PASSWORD="your_password"
export TEST_DB_URL="your_test_db_url"
export TEST_DB_USERNAME="your_test_username"
export TEST_DB_PASSWORD="your_test_password"
export ZOHO_MAIL_API_KEY="your_zoho_key"
export ZOHO_MAIL_SECRET="your_zoho_secret"
export GMAIL_TEST_SMTP_EMAIL="your_gmail"
export GMAIL_TEST_SMTP_PASSWORD="your_password"
export TELEGRAM_BOT_TOKEN="your_bot_token"

Backend (Windows - PowerShell):

$env:LIVE_DB_URL="your_live_db_url"
$env:LIVE_DB_USERNAME="your_username"
$env:LIVE_DB_PASSWORD="your_password"
$env:TEST_DB_URL="your_test_db_url"
$env:TEST_DB_USERNAME="your_test_username"
$env:TEST_DB_PASSWORD="your_test_password"
$env:ZOHO_MAIL_API_KEY="your_zoho_key"
$env:ZOHO_MAIL_SECRET="your_zoho_secret"
$env:GMAIL_TEST_SMTP_EMAIL="your_gmail"
$env:GMAIL_TEST_SMTP_PASSWORD="your_password"
$env:TELEGRAM_BOT_TOKEN="your_bot_token"

Frontend (Create .env in client/):

REACT_APP_EmailJsServiceID=your_service_id
REACT_APP_EmailJsTemplateID=your_template_id
REACT_APP_EmailJsAPIKey=your_emailjs_api_key

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3. Install Dependencies

Frontend

cd client
npm install

Backend

cd ../server
pip install -r requirements.txt

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🖥️ Running the Application

Start the Frontend (ReactJS)

cd client
npm start

Start the Backend (Flask API)

cd server
python app.py

Developer Documentation

Developer Documentation is available in the PDF file stated below:

"Ocula Finance - Developer Documentation - Github.pdf"

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🧠 AI: Training & Prediction

🛡️ Note: The AI files are in the repository history are encrypted. Use this decryption key to run them (current AI files are no longer encrypted):
Be1XeaQaeJcel4TayW5i7mOiwTPQcl-hf0TmwmEyMBE=

AI Requirements

• Run on Windows only
• Requires MetaTrader5 software

Train the AI Model

cd server
python x_y_train.py

Run backtests using the training AI Model

python backtest.py

Run Predictions

python x_y_predict.py

Configuration

All AI and backend configurations are located in:

server/settings.py

All Symbol / Currency Pair configurations are located in:

server/symbol_config.py

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📬 Telegram Alerts

Ocula Finance includes a Telegram bot to send trading alerts alongside browser notifications.

Ensure you set the TELEGRAM_BOT_TOKEN environment variable before running the backend.

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🛡️ Security Notes

• All old AI files were encrypted during development to preserve intellectual property.
• The decryption key is now public as the project is open source.
• Current files are no longer encrypted
• Use environment variables to protect sensitive data in deployment.

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📄 License

This project is released under the MIT License.

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👤 Author

Michael Panashe Mudimbu
🔗 LinkedIn
🐦 Twitter / X
📧 michaelmudimbu@gmail.com

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⭐ Support

If you find this project useful, feel free to give it a ⭐ on GitHub!