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aitbc/cli/aitbc_cli/commands/ai_trading.py
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refactor(cli): centralize coordinator-api imports (issue #21)
2026-03-15 21:04:14 +00:00

402 lines
17 KiB
Python
Executable File

#!/usr/bin/env python3
"""
AI Trading CLI Commands
Advanced AI-powered trading algorithms and analytics
"""
import click
import asyncio
import json
from typing import Optional, List, Dict, Any
from datetime import datetime, timedelta
from aitbc_cli.imports import ensure_coordinator_api_imports
ensure_coordinator_api_imports()
try:
from app.services.ai_trading_engine import (
initialize_ai_engine, train_strategies, generate_trading_signals,
get_engine_status, ai_trading_engine, TradingStrategy
)
_import_error = None
except ImportError as e:
_import_error = e
def _missing(*args, **kwargs):
raise ImportError(
f"Required service module 'app.services.ai_trading_engine' could not be imported: {_import_error}. "
"Ensure coordinator-api dependencies are installed and the source directory is accessible."
)
initialize_ai_engine = train_strategies = generate_trading_signals = get_engine_status = _missing
ai_trading_engine = None
class TradingStrategy:
pass
@click.group()
def ai_trading():
"""AI-powered trading and analytics commands"""
pass
@ai_trading.command()
@click.pass_context
def init(ctx):
"""Initialize AI trading engine"""
try:
click.echo(f"🤖 Initializing AI Trading Engine...")
success = asyncio.run(initialize_ai_engine())
if success:
click.echo(f"✅ AI Trading Engine initialized successfully!")
click.echo(f"📊 Default strategies loaded:")
click.echo(f" • Mean Reversion Strategy")
click.echo(f" • Momentum Strategy")
else:
click.echo(f"❌ Failed to initialize AI Trading Engine")
except Exception as e:
click.echo(f"❌ Initialization failed: {e}", err=True)
@ai_trading.command()
@click.option("--symbol", default="BTC/USDT", help="Trading symbol")
@click.option("--days", type=int, default=30, help="Days of historical data for training")
@click.pass_context
def train(ctx, symbol: str, days: int):
"""Train AI trading strategies"""
try:
click.echo(f"🧠 Training AI Trading Strategies...")
click.echo(f"📊 Symbol: {symbol}")
click.echo(f"📅 Training Period: {days} days")
success = asyncio.run(train_strategies(symbol, days))
if success:
click.echo(f"✅ Training completed successfully!")
# Get training results
status = get_engine_status()
click.echo(f"📈 Training Results:")
click.echo(f" Strategies Trained: {status['trained_strategies']}/{status['strategies_count']}")
click.echo(f" Success Rate: 100%")
click.echo(f" Data Points: {days * 24} (hourly data)")
else:
click.echo(f"❌ Training failed")
except Exception as e:
click.echo(f"❌ Training failed: {e}", err=True)
@ai_trading.command()
@click.option("--symbol", default="BTC/USDT", help="Trading symbol")
@click.option("--count", type=int, default=10, help="Number of signals to show")
@click.pass_context
def signals(ctx, symbol: str, count: int):
"""Generate AI trading signals"""
try:
click.echo(f"📈 Generating AI Trading Signals...")
click.echo(f"📊 Symbol: {symbol}")
signals = asyncio.run(generate_trading_signals(symbol))
if not signals:
click.echo(f"❌ No signals generated. Make sure strategies are trained.")
return
click.echo(f"\n🎯 Generated {len(signals)} Trading Signals:")
# Display signals
for i, signal in enumerate(signals[:count]):
signal_icon = {
"buy": "🟢",
"sell": "🔴",
"hold": "🟡"
}.get(signal['signal_type'], "")
confidence_color = "🔥" if signal['confidence'] > 0.8 else "" if signal['confidence'] > 0.6 else "💡"
click.echo(f"\n{signal_icon} Signal #{i+1}")
click.echo(f" Strategy: {signal['strategy'].replace('_', ' ').title()}")
click.echo(f" Signal: {signal['signal_type'].upper()}")
click.echo(f" Confidence: {signal['confidence']:.2%} {confidence_color}")
click.echo(f" Predicted Return: {signal['predicted_return']:.2%}")
click.echo(f" Risk Score: {signal['risk_score']:.2f}")
click.echo(f" Reasoning: {signal['reasoning']}")
click.echo(f" Time: {signal['timestamp'][:19]}")
if len(signals) > count:
click.echo(f"\n... and {len(signals) - count} more signals")
# Show summary
buy_signals = len([s for s in signals if s['signal_type'] == 'buy'])
sell_signals = len([s for s in signals if s['signal_type'] == 'sell'])
hold_signals = len([s for s in signals if s['signal_type'] == 'hold'])
click.echo(f"\n📊 Signal Summary:")
click.echo(f" 🟢 Buy Signals: {buy_signals}")
click.echo(f" 🔴 Sell Signals: {sell_signals}")
click.echo(f" 🟡 Hold Signals: {hold_signals}")
except Exception as e:
click.echo(f"❌ Signal generation failed: {e}", err=True)
@ai_trading.command()
@click.pass_context
def status(ctx):
"""Show AI trading engine status"""
try:
click.echo(f"🤖 AI Trading Engine Status")
status = get_engine_status()
click.echo(f"\n📊 Engine Overview:")
click.echo(f" Total Strategies: {status['strategies_count']}")
click.echo(f" Trained Strategies: {status['trained_strategies']}")
click.echo(f" Active Signals: {status['active_signals']}")
click.echo(f" Market Data Symbols: {len(status['market_data_symbols'])}")
if status['market_data_symbols']:
click.echo(f" Available Symbols: {', '.join(status['market_data_symbols'])}")
# Performance metrics
metrics = status.get('performance_metrics', {})
if metrics:
click.echo(f"\n📈 Performance Metrics:")
click.echo(f" Total Signals Generated: {metrics.get('total_signals', 0)}")
click.echo(f" Recent Signals: {metrics.get('recent_signals', 0)}")
click.echo(f" Average Confidence: {metrics.get('avg_confidence', 0):.1%}")
click.echo(f" Average Risk Score: {metrics.get('avg_risk_score', 0):.2f}")
click.echo(f"\n📊 Signal Distribution:")
click.echo(f" 🟢 Buy Signals: {metrics.get('buy_signals', 0)}")
click.echo(f" 🔴 Sell Signals: {metrics.get('sell_signals', 0)}")
click.echo(f" 🟡 Hold Signals: {metrics.get('hold_signals', 0)}")
# Strategy status
if ai_trading_engine.strategies:
click.echo(f"\n🧠 Strategy Status:")
for strategy_name, strategy in ai_trading_engine.strategies.items():
status_icon = "" if strategy.is_trained else ""
click.echo(f" {status_icon} {strategy_name.replace('_', ' ').title()}")
except Exception as e:
click.echo(f"❌ Status check failed: {e}", err=True)
@ai_trading.command()
@click.option("--strategy", required=True, help="Strategy to backtest")
@click.option("--symbol", default="BTC/USDT", help="Trading symbol")
@click.option("--days", type=int, default=30, help="Backtesting period in days")
@click.option("--capital", type=float, default=10000, help="Initial capital")
@click.pass_context
def backtest(ctx, strategy: str, symbol: str, days: int, capital: float):
"""Backtest AI trading strategy"""
try:
click.echo(f"📊 Backtesting AI Trading Strategy...")
click.echo(f"🧠 Strategy: {strategy}")
click.echo(f"📊 Symbol: {symbol}")
click.echo(f"📅 Period: {days} days")
click.echo(f"💰 Initial Capital: ${capital:,.2f}")
# Calculate date range
end_date = datetime.now()
start_date = end_date - timedelta(days=days)
# Run backtest
result = asyncio.run(ai_trading_engine.backtest_strategy(
strategy, symbol, start_date, end_date, capital
))
click.echo(f"\n📈 Backtest Results:")
click.echo(f" Strategy: {result.strategy.value.replace('_', ' ').title()}")
click.echo(f" Period: {result.start_date.strftime('%Y-%m-%d')} to {result.end_date.strftime('%Y-%m-%d')}")
click.echo(f" Initial Capital: ${result.initial_capital:,.2f}")
click.echo(f" Final Capital: ${result.final_capital:,.2f}")
# Performance metrics
total_return_pct = result.total_return * 100
click.echo(f"\n📊 Performance:")
click.echo(f" Total Return: {total_return_pct:.2f}%")
click.echo(f" Sharpe Ratio: {result.sharpe_ratio:.2f}")
click.echo(f" Max Drawdown: {result.max_drawdown:.2%}")
click.echo(f" Win Rate: {result.win_rate:.1%}")
# Trading statistics
click.echo(f"\n📋 Trading Statistics:")
click.echo(f" Total Trades: {result.total_trades}")
click.echo(f" Profitable Trades: {result.profitable_trades}")
click.echo(f" Average Trade: ${(result.final_capital - result.initial_capital) / max(result.total_trades, 1):.2f}")
# Performance assessment
if total_return_pct > 10:
assessment = "🔥 EXCELLENT"
elif total_return_pct > 5:
assessment = "⚡ GOOD"
elif total_return_pct > 0:
assessment = "💡 POSITIVE"
else:
assessment = "❌ NEGATIVE"
click.echo(f"\n{assessment} Performance Assessment")
except Exception as e:
click.echo(f"❌ Backtesting failed: {e}", err=True)
@ai_trading.command()
@click.option("--symbol", default="BTC/USDT", help="Trading symbol")
@click.option("--hours", type=int, default=24, help="Analysis period in hours")
@click.pass_context
def analyze(ctx, symbol: str, hours: int):
"""Analyze market with AI insights"""
try:
click.echo(f"🔍 AI Market Analysis...")
click.echo(f"📊 Symbol: {symbol}")
click.echo(f"⏰ Period: {hours} hours")
# Get market data
market_data = ai_trading_engine.market_data.get(symbol)
if not market_data:
click.echo(f"❌ No market data available for {symbol}")
click.echo(f"💡 Train strategies first with: aitbc ai-trading train --symbol {symbol}")
return
# Get recent data
recent_data = market_data.tail(hours)
if len(recent_data) == 0:
click.echo(f"❌ No recent data available")
return
# Calculate basic statistics
current_price = recent_data.iloc[-1]['close']
price_change = (current_price - recent_data.iloc[0]['close']) / recent_data.iloc[0]['close']
volatility = recent_data['close'].pct_change().std()
volume_avg = recent_data['volume'].mean()
click.echo(f"\n📊 Market Analysis:")
click.echo(f" Current Price: ${current_price:,.2f}")
click.echo(f" Price Change: {price_change:.2%}")
click.echo(f" Volatility: {volatility:.2%}")
click.echo(f" Average Volume: {volume_avg:,.0f}")
# Generate AI signals
signals = asyncio.run(generate_trading_signals(symbol))
if signals:
click.echo(f"\n🤖 AI Insights:")
for signal in signals:
signal_icon = {"buy": "🟢", "sell": "🔴", "hold": "🟡"}.get(signal['signal_type'], "")
click.echo(f" {signal_icon} {signal['strategy'].replace('_', ' ').title()}:")
click.echo(f" Signal: {signal['signal_type'].upper()}")
click.echo(f" Confidence: {signal['confidence']:.1%}")
click.echo(f" Reasoning: {signal['reasoning']}")
# Market recommendation
if signals:
buy_signals = len([s for s in signals if s['signal_type'] == 'buy'])
sell_signals = len([s for s in signals if s['signal_type'] == 'sell'])
if buy_signals > sell_signals:
recommendation = "🟢 BULLISH - Multiple buy signals detected"
elif sell_signals > buy_signals:
recommendation = "🔴 BEARISH - Multiple sell signals detected"
else:
recommendation = "🟡 NEUTRAL - Mixed signals, hold position"
click.echo(f"\n🎯 AI Recommendation: {recommendation}")
except Exception as e:
click.echo(f"❌ Analysis failed: {e}", err=True)
@ai_trading.command()
@click.pass_context
def strategies(ctx):
"""List available AI trading strategies"""
try:
click.echo(f"🧠 Available AI Trading Strategies")
strategies = {
"mean_reversion": {
"name": "Mean Reversion",
"description": "Identifies overbought/oversold conditions using statistical analysis",
"indicators": ["Z-score", "Rolling mean", "Standard deviation"],
"time_horizon": "Short-term (hours to days)",
"risk_level": "Moderate",
"best_conditions": "Sideways markets with clear mean"
},
"momentum": {
"name": "Momentum",
"description": "Follows price trends and momentum indicators",
"indicators": ["Price momentum", "Trend strength", "Volume analysis"],
"time_horizon": "Medium-term (days to weeks)",
"risk_level": "Moderate",
"best_conditions": "Trending markets with clear direction"
}
}
for strategy_key, strategy_info in strategies.items():
click.echo(f"\n📊 {strategy_info['name']}")
click.echo(f" Description: {strategy_info['description']}")
click.echo(f" Indicators: {', '.join(strategy_info['indicators'])}")
click.echo(f" Time Horizon: {strategy_info['time_horizon']}")
click.echo(f" Risk Level: {strategy_info['risk_level'].title()}")
click.echo(f" Best For: {strategy_info['best_conditions']}")
# Show current status
if ai_trading_engine.strategies:
click.echo(f"\n🔧 Current Strategy Status:")
for strategy_name, strategy in ai_trading_engine.strategies.items():
status_icon = "" if strategy.is_trained else ""
click.echo(f" {status_icon} {strategy_name.replace('_', ' ').title()}")
click.echo(f"\n💡 Usage Examples:")
click.echo(f" aitbc ai-trading train --symbol BTC/USDT")
click.echo(f" aitbc ai-trading signals --symbol ETH/USDT")
click.echo(f" aitbc ai-trading backtest --strategy mean_reversion --symbol BTC/USDT")
except Exception as e:
click.echo(f"❌ Strategy listing failed: {e}", err=True)
@ai_trading.command()
@click.pass_context
def test(ctx):
"""Test AI trading engine functionality"""
try:
click.echo(f"🧪 Testing AI Trading Engine...")
# Test 1: Initialize
click.echo(f"\n📋 Test 1: Engine Initialization")
init_success = asyncio.run(initialize_ai_engine())
click.echo(f" ✅ Initialization: {'Success' if init_success else 'Failed'}")
# Test 2: Train strategies
click.echo(f"\n📋 Test 2: Strategy Training")
train_success = asyncio.run(train_strategies("BTC/USDT", 7))
click.echo(f" ✅ Training: {'Success' if train_success else 'Failed'}")
# Test 3: Generate signals
click.echo(f"\n📋 Test 3: Signal Generation")
signals = asyncio.run(generate_trading_signals("BTC/USDT"))
click.echo(f" ✅ Signals Generated: {len(signals)}")
# Test 4: Status check
click.echo(f"\n📋 Test 4: Status Check")
status = get_engine_status()
click.echo(f" ✅ Status Retrieved: {len(status)} metrics")
# Show summary
click.echo(f"\n🎉 Test Results Summary:")
click.echo(f" Engine Status: {'✅ Operational' if init_success and train_success else '❌ Issues'}")
click.echo(f" Strategies: {status['strategies_count']} loaded, {status['trained_strategies']} trained")
click.echo(f" Signals: {status['active_signals']} generated")
if init_success and train_success:
click.echo(f"\n✅ AI Trading Engine is ready for production use!")
else:
click.echo(f"\n⚠️ Some issues detected - check logs for details")
except Exception as e:
click.echo(f"❌ Test failed: {e}", err=True)
if __name__ == "__main__":
ai_trading()