📚 用户指南

# 1. 克隆项目
git clone https://github.com/pe0ny9-a/AI-Lottery-Predictor.git
cd AI-Lottery-Predictor

# 2. 创建虚拟环境 (推荐)
python -m venv venv
source venv/bin/activate  # Linux/Mac
# 或
venv\Scripts\activate  # Windows

# 3. 安装基础依赖
pip install -r requirements.txt

# 4. 验证安装
python test_advanced_features_simple.py

# 量子计算支持
pip install qiskit qiskit-aer cirq

# 高级可视化
pip install plotly matplotlib seaborn

# AI助手增强
pip install nltk spacy transformers

# 智能调优
pip install optuna scikit-optimize

# 实时处理
pip install websockets aiohttp

# 交互模式启动
python main.py --mode interactive

# 演示模式启动
python main.py --mode demo

# 服务模式启动
python main.py --mode service

from src.streaming.realtime_processor import get_stream_engine

# 获取流处理引擎
engine = await get_stream_engine()

# 发送事件
await engine.emit_event(lottery_data_event)

# 查看统计信息
stats = engine.get_system_stats()
print(f"处理速率: {stats['system']['processing_rate']} events/sec")

from src.visualization.enhanced_charts import get_visualization_engine, ChartType

# 获取可视化引擎
engine = get_visualization_engine()

# 创建3D趋势图
chart = engine.create_chart(
    ChartType.SCATTER_3D,
    "trend_analysis",
    data={'history_data': lottery_data},
    config={'title': '双色球3D趋势分析'}
)

# 导出图表
engine.export_chart("trend_analysis", "output/trend.html")

from src.optimization.intelligent_tuner import get_intelligent_tuner, ParameterSpace, OptimizationMethod

# 获取调优器
tuner = get_intelligent_tuner()

# 定义参数空间
param_spaces = [
    ParameterSpace('learning_rate', 'float', bounds=(0.001, 0.1), log_scale=True),
    ParameterSpace('n_estimators', 'int', bounds=(50, 500))
]

# 执行优化
result = tuner.optimize_model_parameters(
    model_class=RandomForestRegressor,
    parameter_spaces=param_spaces,
    X_train=X_train, y_train=y_train,
    X_val=X_val, y_val=y_val,
    method=OptimizationMethod.BAYESIAN
)

from src.quantum.quantum_algorithms import get_quantum_ml

# 获取量子机器学习实例
qml = get_quantum_ml()

# 量子优化彩票选择
result = qml.optimize_lottery_selection(
    historical_data=lottery_history,
    num_selections=6
)

print(f"量子预测号码: {result['selected_numbers']}")
print(f"置信度: {result['confidence']:.2%}")
print(f"量子优势: {result['quantum_advantage']}")

from src.ai_assistant.intelligent_assistant import get_intelligent_assistant

# 获取AI助手
assistant = get_intelligent_assistant()

# 处理用户消息
response = assistant.process_message("预测双色球下期号码")

print(f"助手回复: {response.content}")
print(f"置信度: {response.confidence:.2%}")

# 获取对话历史
history = assistant.get_conversation_history()
for msg in history[-5:]:  # 显示最近5条消息
    print(f"{msg['role']}: {msg['content'][:50]}...")

# 创建 .env 文件
LOG_LEVEL=INFO
CACHE_ENABLED=true
QUANTUM_ENABLED=false  # 是否启用量子功能
GPU_ENABLED=false      # 是否启用GPU加速
WEBSOCKET_PORT=8765    # WebSocket端口
DATABASE_PATH=data/lottery.db

# 查看所有可用参数
python main.py --help

# 常用参数示例
python main.py --mode interactive --log-level DEBUG
python main.py --mode service --port 8000