535 lines
19 KiB
Python
535 lines
19 KiB
Python
"""
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美股交易智能体 - 主控制器（LLM 驱动版）
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只进行市场分析和通知，不执行模拟交易
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"""
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import asyncio
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from typing import Dict, Any, List, Optional
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from datetime import datetime, timedelta
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import pandas as pd
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from app.utils.logger import logger
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from app.config import get_settings
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from app.services.yfinance_service import get_yfinance_service
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from app.services.feishu_service import get_feishu_service
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from app.services.telegram_service import get_telegram_service
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from app.services.signal_database_service import get_signal_db_service
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from app.crypto_agent.llm_signal_analyzer import LLMSignalAnalyzer
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class StockAgent:
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"""美股交易信号智能体（LLM 驱动，仅分析通知）"""
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def __init__(self):
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"""初始化智能体"""
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self.settings = get_settings()
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self.yfinance = get_yfinance_service()
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self.feishu = get_feishu_service()
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self.telegram = get_telegram_service()
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self.llm_analyzer = LLMSignalAnalyzer(agent_type="stock") # 指定使用 stock 模型配置
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self.signal_db = get_signal_db_service() # 信号数据库服务
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# 状态管理
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self.last_signals: Dict[str, Dict[str, Any]] = {}
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self.signal_cooldown: Dict[str, datetime] = {}
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# 配置
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self.symbols = self.settings.stock_symbols.split(',')
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# 运行状态
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self.running = False
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self._event_loop = None
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self._task = None
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logger.info(f"美股智能体初始化完成，监控股票: {self.symbols}")
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async def start(self):
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"""启动智能体"""
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if self.running:
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logger.warning("美股智能体已在运行中")
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return
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self.running = True
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self._event_loop = asyncio.get_event_loop()
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logger.info("美股智能体已启动")
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# 启动分析任务
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self._task = asyncio.create_task(self._analysis_loop())
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async def stop(self):
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"""停止智能体"""
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self.running = False
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if self._task:
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self._task.cancel()
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try:
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await self._task
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except asyncio.CancelledError:
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pass
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logger.info("美股智能体已停止")
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async def _analysis_loop(self):
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"""分析循环 - 只在美股交易时间内运行，整点执行"""
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while self.running:
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try:
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# 计算距离下一个整点的时间
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now = datetime.now()
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next_hour = now.replace(minute=0, second=0, microsecond=0) + timedelta(hours=1)
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wait_seconds = (next_hour - now).total_seconds()
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logger.info(f"等待到下一个整点: {next_hour.strftime('%H:%M')} (等待 {int(wait_seconds)} 秒)")
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# 等待到整点
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await asyncio.sleep(wait_seconds)
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# 检查是否在美股交易时间
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if not self._is_market_hours():
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logger.debug("非美股交易时间，跳过本次分析")
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# 继续等待下一个整点
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continue
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# 在交易时间内，分析所有股票并收集结果
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logger.info(f"开始分析 {len(self.symbols)} 只股票")
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analysis_results = []
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for symbol in self.symbols:
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if not self.running:
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break
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result = await self.analyze_symbol(symbol)
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if result:
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analysis_results.append(result)
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# 生成并发送汇总报告
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await self._send_summary_report(analysis_results)
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logger.info("本次分析完成")
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except Exception as e:
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logger.error(f"分析循环出错: {e}")
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await asyncio.sleep(60) # 出错后等待 1 分钟再重试
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def _is_market_hours(self) -> bool:
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"""
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判断当前是否在美股交易时间
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美股交易时间: 周一至周五 9:30-16:00 (EST)
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北京时间:
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- 冬令时 (11月-3月): 22:30-05:00 (次日)
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- 夏令时 (3月-11月): 21:30-04:00 (次日)
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Returns:
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是否在交易时间
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"""
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from datetime import datetime
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# 获取当前时间
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now = datetime.now()
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# 检查是否为周末
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if now.weekday() >= 5: # 5=周六, 6=周日
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return False
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# 获取当前小时和分钟
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hour = now.hour
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minute = now.minute
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current_time = hour * 100 + minute # 转换为数字，如 2130 表示 21:30
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# 判断夏令时/冬令时（简单判断：3-11月为夏令时）
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is_summer = 3 <= now.month <= 11
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if is_summer:
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# 夏令时: 21:30-04:00 (次日)
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# 即 2130-2359 或 0000-0400
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if current_time >= 2130 or current_time < 400:
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return True
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else:
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# 冬令时: 22:30-05:00 (次日)
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# 即 2230-2359 或 0000-0500
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if current_time >= 2230 or current_time < 500:
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return True
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return False
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async def analyze_symbol(self, symbol: str) -> Optional[Dict[str, Any]]:
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"""
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分析单个股票
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Args:
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symbol: 股票代码
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Returns:
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分析结果字典，包含股票信息和信号
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"""
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result = {
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'symbol': symbol,
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'current_price': 0,
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'signals': [],
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'analysis_summary': '',
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'notified': False
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}
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try:
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# 1. 获取多时间周期数据
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data = self.yfinance.get_multi_timeframe_data(symbol)
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# 2. 验证数据完整性
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if not self._validate_data(data):
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logger.warning(f"{symbol} 数据不完整，跳过本次分析")
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return result
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# 3. 获取当前价格
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ticker = self.yfinance.get_ticker(symbol)
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if not ticker:
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logger.warning(f"无法获取 {symbol} 当前价格")
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return result
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current_price = ticker['lastPrice']
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result['current_price'] = current_price
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logger.info(f"\n{'='*60}")
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logger.info(f"📊 分析 {symbol} @ ${current_price:,.2f}")
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logger.info(f"{'='*60}")
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# 4. LLM 分析
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logger.info(f"\n🤖 【LLM 分析中...】")
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analysis = await self.llm_analyzer.analyze(
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symbol, data,
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symbols=self.symbols,
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position_info=None # 美股不跟踪持仓
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)
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# 输出分析摘要
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summary = analysis.get('analysis_summary', '无')
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result['analysis_summary'] = summary
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logger.info(f" 市场状态: {summary}")
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# 输出新闻情绪
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news_sentiment = analysis.get('news_sentiment', '')
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news_impact = analysis.get('news_impact', '')
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if news_sentiment:
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sentiment_icon = {'positive': '📈', 'negative': '📉', 'neutral': '➖'}.get(news_sentiment, '')
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logger.info(f" 新闻情绪: {sentiment_icon} {news_sentiment}")
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if news_impact:
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logger.info(f" 消息影响: {news_impact}")
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# 输出关键价位
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levels = analysis.get('key_levels', {})
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if levels.get('support') or levels.get('resistance'):
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support_str = ', '.join([f"${s:,.2f}" for s in levels.get('support', [])[:2]])
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resistance_str = ', '.join([f"${r:,.2f}" for r in levels.get('resistance', [])[:2]])
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logger.info(f" 支撑位: {support_str or '-'}")
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logger.info(f" 阻力位: {resistance_str or '-'}")
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# 5. 处理信号
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signals = analysis.get('signals', [])
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result['signals'] = signals
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if not signals:
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logger.info(f"\n⏸️ 结论: 无交易信号，继续观望")
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return result
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# 输出所有信号
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logger.info(f"\n🎯 【发现 {len(signals)} 个信号】")
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for sig in signals:
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signal_type = sig.get('type', 'unknown')
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type_map = {'short_term': '短线', 'medium_term': '中线', 'long_term': '长线'}
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type_text = type_map.get(signal_type, signal_type)
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action = sig.get('action', 'wait')
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action_map = {'buy': '🟢 做多', 'sell': '🔴 做空'}
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action_text = action_map.get(action, action)
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grade = sig.get('grade', 'D')
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confidence = sig.get('confidence', 0)
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grade_icon = {'A': '⭐⭐⭐', 'B': '⭐⭐', 'C': '⭐', 'D': ''}.get(grade, '')
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logger.info(f"\n {type_text} {action_text} [{grade}级{grade_icon}] {confidence}%")
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# 6. 过滤并通知最佳信号
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best_signal = self._get_best_signal(signals)
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if not best_signal:
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logger.info(f"\n⏸️ 信号质量不高，不发送通知")
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return result
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# 检查置信度阈值
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threshold = self.settings.stock_llm_threshold * 100
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if best_signal.get('confidence', 0) < threshold:
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logger.info(f"\n⏸️ 置信度不足 ({best_signal.get('confidence', 0)}% < {threshold}%)")
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return result
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# 检查冷却时间
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if not self._should_send_signal(symbol, best_signal):
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logger.info(f"\n⏸️ 信号冷却中，不发送通知")
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return result
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# 发送通知
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await self._send_signal_notification(symbol, best_signal, current_price)
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result['notified'] = True
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result['best_signal'] = best_signal
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# 更新状态
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self.last_signals[symbol] = best_signal
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self.signal_cooldown[symbol] = datetime.now()
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return result
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except Exception as e:
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logger.error(f"❌ 分析 {symbol} 出错: {e}")
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import traceback
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logger.error(traceback.format_exc())
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return result
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def _get_best_signal(self, signals: List[Dict[str, Any]]) -> Optional[Dict[str, Any]]:
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"""获取最佳信号"""
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# 过滤掉 D 级信号
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valid_signals = [s for s in signals if s.get('grade', 'D') != 'D']
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if not valid_signals:
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return None
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# 按等级和置信度排序
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grade_order = {'A': 0, 'B': 1, 'C': 2}
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valid_signals.sort(key=lambda x: (
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grade_order.get(x.get('grade', 'C'), 3),
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-x.get('confidence', 0)
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))
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return valid_signals[0]
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def _should_send_signal(self, symbol: str, signal: Dict[str, Any]) -> bool:
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"""判断是否应该发送信号"""
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action = signal.get('action', 'wait')
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if action == 'wait':
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return False
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# 检查冷却时间（60分钟内不重复发送相同方向的信号）
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if symbol in self.signal_cooldown:
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cooldown_end = self.signal_cooldown[symbol] + timedelta(minutes=60)
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if datetime.now() < cooldown_end:
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if symbol in self.last_signals:
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if self.last_signals[symbol].get('action') == action:
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logger.debug(f"{symbol} 信号冷却中，跳过")
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return False
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return True
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async def _send_signal_notification(
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self,
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symbol: str,
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signal: Dict[str, Any],
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current_price: float
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):
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"""发送信号通知"""
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try:
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# 使用正确的方法格式化信号
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card = self.llm_analyzer.format_feishu_card(signal, symbol)
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title = card['title']
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content = card['content']
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# 根据信号方向选择颜色
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color = "green" if signal.get('action') == 'buy' else "red"
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# 发送到飞书
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await self.feishu.send_card(title, content, color)
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# 发送到 Telegram
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await self.telegram.send_message(self.llm_analyzer.format_signal_message(signal, symbol))
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logger.info(f"✅ 信号通知已发送: {title}")
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# 保存信号到数据库
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signal_to_save = signal.copy()
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signal_to_save['signal_type'] = 'stock'
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signal_to_save['symbol'] = symbol
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signal_to_save['current_price'] = current_price
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self.signal_db.add_signal(signal_to_save)
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except Exception as e:
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logger.error(f"发送通知失败: {e}")
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def _validate_data(self, data: Dict[str, pd.DataFrame]) -> bool:
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"""验证数据完整性"""
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required_intervals = ['1d', '1h']
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for interval in required_intervals:
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if interval not in data or data[interval].empty:
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return False
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if len(data[interval]) < 20:
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return False
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return True
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async def analyze_once(self, symbol: str) -> Dict[str, Any]:
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"""单次分析（用于测试或手动触发）"""
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data = self.yfinance.get_multi_timeframe_data(symbol)
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if not self._validate_data(data):
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return {'error': '数据不完整'}
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result = await self.llm_analyzer.analyze(
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symbol, data,
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symbols=self.symbols,
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position_info=None
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)
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return result
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def get_status(self) -> Dict[str, Any]:
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"""获取智能体状态"""
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return {
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'running': self.running,
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'symbols': self.symbols,
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'mode': 'LLM 驱动（仅分析通知）',
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'last_signals': {
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symbol: {
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'type': sig.get('type'),
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'action': sig.get('action'),
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'confidence': sig.get('confidence'),
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'grade': sig.get('grade')
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}
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for symbol, sig in self.last_signals.items()
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}
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}
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async def _send_summary_report(self, results: List[Dict[str, Any]]):
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"""
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生成并发送分析汇总报告
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Args:
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results: 所有股票的分析结果列表
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"""
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try:
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now = datetime.now()
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total = len(results)
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with_signals = [r for r in results if r.get('signals')]
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notified = [r for r in results if r.get('notified')]
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# 统计信号
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buy_signals = []
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sell_signals = []
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high_quality_signals = [] # A/B级信号
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for r in with_signals:
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for sig in r.get('signals', []):
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sig['symbol'] = r['symbol']
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sig['current_price'] = r.get('current_price', 0)
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if sig.get('action') == 'buy':
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buy_signals.append(sig)
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elif sig.get('action') == 'sell':
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sell_signals.append(sig)
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if sig.get('grade') in ['A', 'B']:
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high_quality_signals.append(sig)
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# 按置信度排序
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high_quality_signals.sort(key=lambda x: x.get('confidence', 0), reverse=True)
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# 构建汇总报告
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logger.info(f"\n{'='*80}")
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logger.info(f"📊 美股分析汇总报告")
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logger.info(f"{'='*80}")
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logger.info(f"时间: {now.strftime('%Y-%m-%d %H:%M:%S')}")
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logger.info(f"分析数量: {total} 只股票")
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logger.info(f"有信号: {len(with_signals)} 只")
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logger.info(f"已通知: {len(notified)} 只")
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logger.info(f"")
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# 显示高等级信号
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if high_quality_signals:
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logger.info(f"⭐ 高等级信号 (A/B级): {len(high_quality_signals)} 个")
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for sig in high_quality_signals[:10]: # 最多显示10个
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symbol = sig['symbol']
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action = '🟢 做多' if sig.get('action') == 'buy' else '🔴 做空'
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grade = sig.get('grade', 'D')
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confidence = sig.get('confidence', 0)
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price = sig.get('current_price', 0)
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entry = sig.get('entry_price', 0)
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logger.info(f" {symbol} {action} [{grade}级] {confidence}% @ ${price:,.2f}")
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if entry > 0:
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logger.info(f" 入场: ${entry:,.2f}")
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logger.info(f"")
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# 统计汇总
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logger.info(f"📈 做多信号: {len(buy_signals)} 个")
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logger.info(f"📉 做空信号: {len(sell_signals)} 个")
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logger.info(f"{'='*80}\n")
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# 发送飞书汇总
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await self._send_feishu_summary(
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now, total, with_signals, notified,
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buy_signals, sell_signals, high_quality_signals
|
||
)
|
||
|
||
except Exception as e:
|
||
logger.error(f"生成汇总报告失败: {e}")
|
||
import traceback
|
||
logger.error(traceback.format_exc())
|
||
|
||
async def _send_feishu_summary(
|
||
self,
|
||
now: datetime,
|
||
total: int,
|
||
with_signals: List,
|
||
notified: List,
|
||
buy_signals: List,
|
||
sell_signals: List,
|
||
high_quality_signals: List
|
||
):
|
||
"""发送飞书汇总报告"""
|
||
try:
|
||
# 构建内容
|
||
content_parts = [
|
||
f"**美股分析汇总报告**",
|
||
f"",
|
||
f"⏰ 时间: {now.strftime('%Y-%m-%d %H:%M')}",
|
||
f"",
|
||
f"📊 **分析概况**",
|
||
f"• 分析总数: {total} 只",
|
||
f"• 发现信号: {len(with_signals)} 只",
|
||
f"• 已发通知: {len(notified)} 只",
|
||
f"",
|
||
]
|
||
|
||
# 高等级信号
|
||
if high_quality_signals:
|
||
content_parts.append(f"⭐ **高等级信号 (A/B级)**")
|
||
for sig in high_quality_signals[:5]:
|
||
symbol = sig['symbol']
|
||
action = '🟢 做多' if sig.get('action') == 'buy' else '🔴 做空'
|
||
grade = sig.get('grade', 'D')
|
||
confidence = sig.get('confidence', 0)
|
||
content_parts.append(f"• {symbol} {action} {grade}级 {confidence}%")
|
||
content_parts.append(f"")
|
||
|
||
# 信号统计
|
||
content_parts.extend([
|
||
f"📈 做多信号: {len(buy_signals)} 个",
|
||
f"📉 做空信号: {len(sell_signals)} 个",
|
||
f"",
|
||
f"*⚠️ 仅供参考，不构成投资建议*"
|
||
])
|
||
|
||
content = "\n".join(content_parts)
|
||
|
||
# 发送飞书
|
||
title = f"📊 美股分析汇总 ({now.strftime('%H:%M')})"
|
||
color = "blue"
|
||
|
||
await self.feishu.send_card(title, content, color)
|
||
logger.info("✅ 汇总报告已发送到飞书")
|
||
|
||
except Exception as e:
|
||
logger.error(f"发送飞书汇总失败: {e}")
|
||
|
||
|
||
# 全局单例
|
||
_stock_agent: Optional[StockAgent] = None
|
||
|
||
|
||
def get_stock_agent() -> StockAgent:
|
||
"""获取美股智能体单例"""
|
||
global _stock_agent
|
||
if _stock_agent is None:
|
||
_stock_agent = StockAgent()
|
||
return _stock_agent
|