OpenAgora 🏛️

The Meta Trading Engine — Stocks + Crypto + Prediction Markets

The Agora was the beating heart of ancient civilization — commerce, ideas, and power in one place. OpenAgora is that for the Pantheon.

Built by: The Forgemaster | Version: v2.0 Enhanced

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What It Is

OpenAgora is a self-evolving, Meta-recursive trading bot that operates across:

• 📈 Stocks — via Marketstack API + Alpaca (real trading ready)
• ₿ Crypto — via CoinGecko + Binance (real trading ready)
• 🎯 Prediction Markets — via Polymarket + Kalshi

It doesn't just trade. It watches itself trade, learns from every win and loss via EverOS memory, and evolves its own strategy weights over time.

Now with AI Training Strategy (Q-Learning):

• Uses reinforcement learning to improve decisions
• Learns from historical market data
• Self-adjusts based on outcomes
• Saves Q-table for persistence

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Architecture

OpenAgora v2.0
├── core/
│   ├── agora_engine.py       # Main orchestrator — Meta brain
│   ├── market_feed.py        # Unified data feed (stocks + crypto + predictions + training)
│   └── war_chest.py          # MidasPrime integration — logs all P&L
├── strategies/
│   ├── meta_strategy.py      # Meta layer — self-adjusting weights + training integration
│   └── training_strategy.py  # AI Q-learning strategy (NEW!)
├── memory/
│   ├── everos_bridge.py      # EverOS long-term memory integration
│   └── trade_log.json        # Persistent trade history
├── reporting/
│   └── telegram_bot.py       # Pantheon Deploy Rule — all vitals to Telegram
├── logs/
│   └── war_chest.json        # MidasPrime War Chest sync
│   └── q_table.json         # Training Q-table (NEW!)
├── .env.example              # All required keys
├── requirements.txt
└── README.md

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The Meta Layer + AI Training

OpenAgora is self-aware. After every trade cycle:

1. It logs the result to EverOS memory
2. It recalculates strategy win rates
3. It shifts capital weight toward winning strategies
4. NEW: It uses Q-learning to train and improve decisions
5. It broadcasts vitals to Telegram

This is not a static bot. It evolves.

AI Training Strategy

• Uses Q-learning (reinforcement learning)
• Tracks states: strong_bull, bull, neutral, bear, strong_bear
• Actions: BUY, SELL, HOLD (with exploration)
• Learns from actual trade outcomes
• Persists Q-table to disk

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Quick Start

git clone https://github.com/kevinleestites2-dev/OpenAgora
cd OpenAgora
pip install -r requirements.txt
cp .env.example .env
# Fill in your keys
python core/agora_engine.py --mode simulate

One-Click Commands

# Get crypto prices
python core/agora_engine.py --prices bitcoin ethereum solana --asset-type crypto

# Get stock prices  
python core/agora_engine.py --prices AAPL GOOGL MSFT --asset-type stock

# Trade a stock (simulated)
python core/agora_engine.py --trade-stock AAPL --buy --quantity 10

# Trade crypto (simulated)
python core/agora_engine.py --trade-crypto BTCUSDT --buy --quantity 1

# Run one training cycle
python core/agora_engine.py --once

Environment Variables

# Required for stock trading
ALPACA_API_KEY=your_alpaca_key
ALPACA_API_SECRET=your_alpaca_secret

# Required for crypto trading
BINANCE_API_KEY=your_binance_key  
BINANCE_API_SECRET=your_binance_secret

# Required for market data
MARKETSTACK_API_KEY=your_marketstack_key

# Telegram notifications
TELEGRAM_BOT_TOKEN=your_bot_token
TELEGRAM_CHAT_ID=your_chat_id

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Revenue Flow

All profits auto-sync to MidasPrime's War Chest:

• logs/war_chest.json — real-time P&L
• Telegram broadcasts every trade result
• ZapiaPrime can query status on demand

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Pantheon Role

Layer	Component
Data	OpenStock + CoinGecko + Polymarket + Kalshi
Memory	EverOS (long-term trade memory)
Training	Q-Learning Strategy
Trading	Alpaca (stocks) + Binance (crypto)
Reporting	Telegram (ZeusPrime bot token)
Treasury	MidasPrime War Chest

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"The Agora never closes." 🏛️🔱