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Nexa Port - AI Portfolio Management

Nexa Port is an advanced AI-powered Portfolio Management system designed to revolutionize your portfolio management experience through sophisticated analysis and intelligent recommendations.

Features

Core Features

  • Portfolio Analysis: Comprehensive analysis of your portfolio's performance, risk metrics, and returns using advanced AI algorithms
  • Investment Strategy: AI-driven investment recommendations based on market trends, risk tolerance, and investment goals
  • Real-time Monitoring: Continuous tracking of portfolio performance with instant alerts and updates
  • Risk Assessment: Advanced risk metrics including Sharpe ratio, Sortino ratio, and maximum drawdown analysis

Technical Features

  • AI Integration: Leverages GPT-4 and custom ML models for portfolio analysis
  • Security: Enhanced security features with optional local model processing
  • Data Visualization: Interactive charts and graphs powered by Recharts
  • Responsive Design: Full mobile and desktop compatibility

How to Deploy

Prerequisites

  • Docker and Docker Compose installed
  • Node.js 18+ for local development
  • Python 3.9+ for backend services
  • Ollama (required for security mode)

Security Mode Setup

When using security mode, Ollama needs to be installed and configured:

Install Ollama

macOS:

Linux:

curl -fsSL https://ollama.com/install.sh | sh

Windows:

Configure Ollama

  1. Start Ollama service:
ollama serve
  1. Pull required models:
ollama pull llama3.2

Deployment Steps

  1. Clone the repository:
git clone https://github.com/yourusername/nexa-port.git
cd nexa-port
  1. Set up environment variables:
cp .env.example .env
# Edit .env with your configuration
  1. Build and start services:
docker-compose up -d

Ports

Usage

  1. Access the web interface at http://localhost:3000
  2. Upload your portfolio CSV file with the required format
  3. Select your investment strategy and preferences
  4. Review the AI-generated analysis and recommendations

License

MIT License - see LICENSE file for details

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