Investment Prediction Agent

AI-powered multi-agent trading system for comprehensive stock market analysis and automated trading decisions.

🚀 Overview

The Investment Prediction Agent is a sophisticated platform combining 8 specialized AI agents to analyze markets, debate strategies, and execute trades. It features real-time data processing, a "Bull vs. Bear" debate engine, and a modern dashboard for visualization.

✨ Key Features

• Multi-Agent Architecture: 8 agents including Fundamentals, News, Technical, and Risk Managers.
• Top Traders Leaderboard: Real-time tracking of top performers from ZuluTrade and Polymarket.
• Interactive Dashboard: Modern UI with specific agent reports, history tracking, and technical charts.
• "Bull vs. Bear" Debates: Automated debates to assess risk and reward before every trade.
• Groq Integration: High-speed inference using llama-3.3-70b-versatile.

🛠️ Quick Start

Prerequisites: Node.js 18+, Python 3.9+, and API Keys (Groq, OpenAI, etc.).

1. Clone & Install

   git clone https://github.com/vtempest/investment-prediction-agent.git
   cd investment-prediction-agent
   npm install             # Install frontend deps
   npm run db:push         # Initialize database

2. Setup Python Agents

   cd agents
   # Setup venv and install dependencies for specific agents as needed
   # See agents/README.md for detailed setup
   pip install -r requirements.txt

3. Run Services

   # Terminal 1: Frontend
   npm run dev
   
   # Terminal 2: Unified Backend
   cd agents && python unified_api_server.py

4. Explore: Open http://localhost:3000.

🤖 AI Agents & Strategies

Agent/Team	Role
Analyst Team	Gathers data: Fundamentals, Sentiment (Social), News, & Technical Analysis.
Researcher Team	Conducts "Bull vs. Bear" debates; assesses risk.
Trader Agent	Synthesizes reports to propose trades.
Portfolio Manager	Final decision maker; manages risk and position sizing.

Strategies: Momentum (Trend Following), Mean Reversion, Breakout (Volatility), and Day Trading Scalp.

📂 Project Ecosystem

• Documentation: Full architecture and API details.
• Lightweight Charts: Deep dive into the AI stack.
• LangChain Integration: Deep dive into the AI stack.
• API Docs: Interactive Scalar documentation (when running).

📦 Project Structure

├── agents/             # Python AI services (News, Debate, etc.)
├── app/                # Next.js App Router
├── components/         # React UI (Dashboard, Charts)
├── lib/                # Shared utilities & Database schema
└── docs/               # Detailed documentation

🤝 Contributing & License

Contributions are welcome! Please open an issue or PR. Licensed under MIT.