🤖 Autonomous Multi-Model AI Trading System

A professional-grade, autonomous trading system connecting Interactive Brokers (IBKR) and Multiple Crypto Exchanges (Binance, Coinbase, Kraken) with state-of-the-art LLMs (GPT-4, Mistral, Gemini) via OpenRouter.

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🚀 Zero-to-Hero Tutorial

Step 1: Prerequisites

1. Python 3.11+: Ensure Python is installed.
2. IBKR Gateway / TWS: For stock trading, you need IBKR software running.
   • Enable "Enable ActiveX and Socket Clients".
   • Port: 7497 (Paper) or 7496 (Live).
3. Crypto API Keys: Get API Key & Secret from your exchange (Binance, Coinbase, etc.).

Step 2: Installation

git clone <repository_url>
cd trading-system
pip install -r requirements.txt

Step 3: Configuration

Create a .env file in the root directory (copy .env.example if available) and configure your keys.

Required Environment Variables:

# --- AI Configuration ---
OPENROUTER_KEY=sk-or-v1-YOUR-KEY...
OPENROUTER_MODEL=mistralai/mistral-7b-instruct

# --- Dashboard Security ---
DASHBOARD_USERNAME=admin
DASHBOARD_PASSWORD=supersecurepassword

# --- IBKR (Stocks) ---
IB_ACCOUNT=DU12345
IB_HOST=127.0.0.1
IB_PORT=7497
IB_CLIENT_ID=1

# --- Crypto Exchanges ---
# Binance
BINANCE_API_KEY=your_binance_key
BINANCE_SECRET_KEY=your_binance_secret

# Coinbase Advanced Trade
COINBASE_API_KEY=your_coinbase_key
COINBASE_SECRET_KEY=your_coinbase_secret

# Kraken
KRAKEN_API_KEY=your_kraken_key
KRAKEN_SECRET_KEY=your_kraken_secret

# Generic (Other)
CRYPTO_API_KEY=...
CRYPTO_SECRET_KEY=...
CRYPTO_PASSPHRASE=... # If required (e.g. KuCoin, Coinbase Pro)

Step 4: Run the System

You have two modes: Headless Loop (CLI) or Dashboard (UI).

Option A: Streamlit Dashboard (Recommended)

streamlit run dashboard/app.py

• Open http://localhost:8501.
• Login with your configured credentials.
• Select "Unified Portfolio" to view all assets.
• Select "Crypto (Generic)" or "IBKR" to execute trades.

Option B: Headless CLI

# Trade Crypto on Binance
python main.py --mode CRYPTO --exchange binance --symbols BTC/USDT ETH/USDT --loop

# Trade Stocks on IBKR
python main.py --mode IBKR --symbols AAPL TSLA --loop

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🏗 Architecture Overview

The system follows a modular Strategy Pattern architecture:

1. Data Layer (engine/):
   • IBKRConnector: Uses ib_insync for async communication with TWS/Gateway.
   • CCXTConnector: Uses ccxt to unify 100+ crypto exchanges.
   • PortfolioManager: Aggregates data from all active connectors into a single view.
2. Analysis Layer (ai/):
   • AIWrapper: Standardizes communication with OpenRouter.
   • Tool Use: LLMs are forced to use structured tools (buy_stock, sell_stock, hold_position) to prevent hallucinations.
3. Risk Layer (engine/risk_manager.py):
   • Validates every trade against MAX_RISK_PER_TRADE_PCT and MAX_DAILY_LOSS_PCT.
4. Presentation Layer (dashboard/):
   • Streamlit-based UI for real-time monitoring and manual intervention.

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📂 Module Guide

File	Description
main.py	CLI Entry point for the autonomous loop.
config.py	Pydantic-based configuration and validation.
dashboard/app.py	The web interface. Connects to PortfolioManager.
engine/base_connector.py	Abstract Interface for all exchanges.
engine/ib_connector.py	IBKR implementation.
engine/ccxt_connector.py	Unified Crypto implementation (Binance, Coinbase, Kraken, etc.).
engine/portfolio_manager.py	Aggregates accounts and positions.
engine/risk_manager.py	Safety checks (Stop Loss, Position Sizing).
ai/ai_wrapper.py	Handles LLM prompting and JSON parsing.

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⚠️ Security & Risk Warning

• Paper Trading First: ALWAYS test on Paper Trading (IBKR) or Testnets (Binance) before using real money.
• API Keys: Never commit your .env file. It is in .gitignore by default.
• Stop Losses: The system attempts to place Stop Loss orders immediately after entry. However, exchange outages or API failures can prevent this. Monitor your positions.
• AI Hallucinations: While we use "Tool Calling" to minimize errors, LLMs can still behave unpredictably. The RiskManager is the final gatekeeper, but it is not infallible.

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🧪 Testing

Run the full test suite to verify system integrity:

pytest tests/

Tests cover:

• API Connectivity (Mocked)
• Portfolio Aggregation
• AI Decision Parsing
• Stop Loss Logic

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Maintained by: Senior Quantitative Architect Last Update: 2026-02-08