843 lines
31 KiB
Python
843 lines
31 KiB
Python
"""
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美股交易智能体 - 主控制器（新架构版）
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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_stock_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.services.fundamental_service import get_fundamental_service
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from app.services.news_service import get_news_service
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from app.stock_agent.market_signal_analyzer import StockMarketSignalAnalyzer
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from app.utils.system_status import get_system_monitor, AgentStatus
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# 股票名称映射表
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STOCK_NAMES = {
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# 美股 - 科技龙头
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'AAPL': '苹果',
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'MSFT': '微软',
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'GOOGL': '谷歌',
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'META': 'Meta',
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'AMZN': '亚马逊',
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'NVDA': '英伟达',
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'AMD': 'AMD',
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'AVGO': '博通',
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'ARM': 'ARM',
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'PLTR': 'Palantir',
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'SNOW': 'Snowflake',
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# 美股 - 生物医疗
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'LLY': '礼来',
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'NVO': '诺和诺德',
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'VRTX': 'Vertex',
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# 美股 - 新能源/汽车
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'TSLA': '特斯拉',
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'ENPH': 'Enphase',
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# 美股 - 金融
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'V': 'Visa',
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'MA': 'Mastercard',
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# 美股 - 消费
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'HD': 'Home Depot',
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'COST': 'Costco',
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# 美股 - 其他
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'RKLB': 'Relativity Space',
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'HOOD': 'Robinhood',
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'DXYZ': 'DEX',
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'GLW': '康宁',
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'UNTY': 'Unity',
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'CRM': 'Salesforce',
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'ADBE': 'Adobe',
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'INTC': '英特尔',
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'FSLR': 'First Solar',
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'CRWD': 'CrowdStrike',
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'SHOP': 'Shopify',
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'NET': 'Cloudflare',
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'COIN': 'Coinbase',
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'MSTR': 'MicroStrategy',
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# 港股
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'0700.HK': '腾讯',
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'9988.HK': '阿里巴巴',
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'1810.HK': '小米',
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'2015.HK': '理想汽车',
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'9866.HK': '蔚来',
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'9992.HK': '泡泡玛特',
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'9626.HK': '哔哩哔哩',
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'9880.HK': '优必选',
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}
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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_stock_service()
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self.telegram = get_telegram_service()
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self.market_analyzer = StockMarketSignalAnalyzer() # 使用新的市场信号分析器
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self.signal_db = get_signal_db_service() # 信号数据库服务
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self.fundamental = get_fundamental_service() # 基本面数据服务
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self.news = get_news_service() # 新闻服务
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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 - 分别读取美股和港股
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us_symbols = self.settings.stock_symbols_us.split(',') if self.settings.stock_symbols_us else []
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hk_symbols = self.settings.stock_symbols_hk.split(',') if self.settings.stock_symbols_hk else []
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self.symbols = us_symbols + hk_symbols
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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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# 注册到系统监控
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monitor = get_system_monitor()
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self._monitor_info = monitor.register_agent(
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agent_id="stock_agent",
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name="股票智能体",
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agent_type="stock"
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)
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# 分类美股和港股数量
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us_count = len([s for s in self.symbols if not s.endswith('.HK')])
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hk_count = len([s for s in self.symbols if s.endswith('.HK')])
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monitor.update_config("stock_agent", {
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"us_symbols": us_symbols,
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"hk_symbols": hk_symbols,
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"total_symbols": len(self.symbols),
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"us_count": us_count,
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"hk_count": hk_count,
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"analysis_interval": f"{self.settings.stock_analysis_interval}秒"
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})
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logger.info(f"股票智能体初始化完成 - 美股: {us_count}只, 港股: {hk_count}只, 总计: {len(self.symbols)}只")
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@staticmethod
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def get_stock_name(symbol: str) -> str:
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"""获取股票中文名称"""
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return STOCK_NAMES.get(symbol, symbol)
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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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# 更新状态为启动中
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monitor = get_system_monitor()
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monitor.update_status("stock_agent", AgentStatus.STARTING)
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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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# 更新状态为运行中
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monitor.update_status("stock_agent", AgentStatus.RUNNING)
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# 发送启动通知（卡片格式）
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us_stocks = [s for s in self.symbols if not s.endswith('.HK')]
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hk_stocks = [s for s in self.symbols if s.endswith('.HK')]
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title = "📈 股票智能体已启动"
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content_parts = [
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f"🤖 **驱动引擎**: LLM 三维分析",
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f"📊 **监控股票**: {len(self.symbols)} 只",
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]
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if us_stocks:
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content_parts.append(f" 🇺🇸 美股 ({len(us_stocks)}): {', '.join(us_stocks[:3])}{'...' if len(us_stocks) > 3 else ''}")
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if hk_stocks:
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content_parts.append(f" 🇭🇰 港股 ({len(hk_stocks)}): {', '.join(hk_stocks[:3])}{'...' if len(hk_stocks) > 3 else ''}")
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content_parts.extend([
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f"⏰ **运行频率**: 每小时整点",
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f"🎯 **分析维度**: 技术面(40%) + 基本面(35%) + 新闻(25%)",
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f"📢 **当前模式**: 仅市场分析",
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])
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content = "\n".join(content_parts)
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await self.feishu.send_card(title, content, "green")
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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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# 更新状态为已停止
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monitor = get_system_monitor()
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monitor.update_status("stock_agent", AgentStatus.STOPPED)
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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 - 根据交易时间分析对应市场的股票"""
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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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# 分类股票：美股和港股
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us_stocks = [s for s in self.symbols if not s.endswith('.HK')]
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hk_stocks = [s for s in self.symbols if s.endswith('.HK')]
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# 检查各市场交易时间
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us_market_open = self._is_market_hours('US')
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hk_market_open = self._is_market_hours('0700.HK')
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# 检查是否是盘后分析时间
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us_after_hours = self._is_after_hours('US')
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hk_after_hours = self._is_after_hours('0700.HK')
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# 确定要分析的股票列表
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stocks_to_analyze = []
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analysis_type = "盘中" # 默认为盘中分析
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# 盘后分析：优先级更高，用于日线级别分析
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if us_after_hours or hk_after_hours:
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analysis_type = "盘后"
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if us_after_hours:
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stocks_to_analyze.extend(us_stocks)
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logger.info(f"美股盘后分析，分析 {len(us_stocks)} 只美股（日线级别）")
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if hk_after_hours:
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stocks_to_analyze.extend(hk_stocks)
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logger.info(f"港股盘后分析，分析 {len(hk_stocks)} 只港股（日线级别）")
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else:
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# 盘中分析
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if us_market_open:
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stocks_to_analyze.extend(us_stocks)
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logger.info(f"美股交易时间，分析 {len(us_stocks)} 只美股")
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if hk_market_open:
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stocks_to_analyze.extend(hk_stocks)
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logger.info(f"港股交易时间，分析 {len(hk_stocks)} 只港股")
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# 如果没有需要分析的股票
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if not stocks_to_analyze:
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logger.debug("没有需要分析的股票")
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continue
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# 分析股票并收集结果
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logger.info(f"开始{analysis_type}分析 {len(stocks_to_analyze)} 只股票")
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analysis_results = []
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for symbol in stocks_to_analyze:
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if not self.running:
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break
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result = await self.analyze_symbol(symbol, is_after_hours=(analysis_type == "盘后"))
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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, analysis_type)
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logger.info(f"本次{analysis_type}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, symbol: str = None) -> bool:
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"""
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判断当前是否在交易时间
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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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港股交易时间: 周一至周五
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北京时间:
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- 上午: 09:30-12:00
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- 下午: 13:00-16:00
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Args:
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symbol: 股票代码（用于判断是美股还是港股）
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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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# 判断是港股还是美股
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is_hk_stock = symbol and symbol.endswith('.HK') if symbol else 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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if is_hk_stock:
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# 港股交易时间: 09:30-12:00 或 13:00-16:00
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return (930 <= current_time < 1200) or (1300 <= current_time < 1600)
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else:
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# 美股交易时间
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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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def _is_any_market_hours(self) -> bool:
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"""判断当前是否在任一市场的交易时间（美股或港股）"""
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return self._is_market_hours('US') or self._is_market_hours('0700.HK')
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def _is_after_hours(self, symbol: str) -> bool:
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"""
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判断当前是否是盘后分析时间（收盘后2小时内）
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美股收盘时间:
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- 夏令时: 北京时间 04:00 收盘
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- 冬令时: 北京时间 05:00 收盘
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港股收盘时间: 北京时间 16:00 收盘
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盘后分析时间: 收盘后 2 小时内
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Args:
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symbol: 股票代码（用于判断是美股还是港股）
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Returns:
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是否是盘后分析时间
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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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# 判断是港股还是美股
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is_hk_stock = symbol and symbol.endswith('.HK') if symbol else 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 1630 表示 16:30
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if is_hk_stock:
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# 港股盘后: 16:00-18:00 (收盘后2小时)
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return 1600 <= current_time < 1800
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else:
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# 美股盘后
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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: 04:00-06:00 (收盘后2小时)
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return 400 <= current_time < 600
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else:
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# 冬令时: 05:00-07:00 (收盘后2小时)
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return 500 <= current_time < 700
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return False
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async def analyze_symbol(self, symbol: str, is_after_hours: bool = False) -> 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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is_after_hours: 是否是盘后分析（盘后会更关注日线级别机会）
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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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# 更新活动时间
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monitor = get_system_monitor()
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monitor.update_activity("stock_agent")
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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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# 获取股票中文名称
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stock_name = STOCK_NAMES.get(symbol, '')
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symbol_display = f"{stock_name}({symbol})" if stock_name else symbol
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logger.info(f"\n{'='*60}")
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logger.info(f"📊 分析 {symbol_display} @ ${current_price:,.2f}")
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logger.info(f"{'='*60}")
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# 4. 获取基本面数据
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logger.info(f"\n📈 【基本面分析】")
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fundamental_data = None
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fundamental_summary = ""
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try:
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fundamental_data = self.fundamental.get_fundamental_data(symbol)
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if fundamental_data:
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# 传递已获取的数据，避免重复调用
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fundamental_summary = self.fundamental.get_fundamental_summary(symbol, fundamental_data)
|
||
# 基本面评分已经在 fundamental_service 中输出
|
||
else:
|
||
logger.warning(f" ⚠️ 无法获取基本面数据")
|
||
except Exception as e:
|
||
logger.warning(f" ⚠️ 获取基本面数据失败: {e}")
|
||
|
||
# 5. 获取新闻数据
|
||
logger.info(f"\n📰 【新闻分析】")
|
||
news_data = None
|
||
try:
|
||
stock_name = STOCK_NAMES.get(symbol, '')
|
||
news_data = await self.news.search_stock_news(symbol, stock_name, max_results=5)
|
||
if news_data:
|
||
logger.info(f" 获取到 {len(news_data)} 条相关新闻")
|
||
else:
|
||
logger.info(f" 暂无相关新闻")
|
||
except Exception as e:
|
||
logger.warning(f" ⚠️ 获取新闻数据失败: {e}")
|
||
|
||
# 6. 市场信号分析（使用新架构 - 技术面 + 基本面 + 新闻）
|
||
logger.info(f"\n🤖 【市场信号分析中...】")
|
||
market_signal = await self.market_analyzer.analyze(
|
||
symbol, data,
|
||
symbols=self.symbols,
|
||
fundamental_data=fundamental_data,
|
||
news_data=news_data
|
||
)
|
||
|
||
# 输出分析摘要
|
||
summary = market_signal.get('analysis_summary', '无')
|
||
result['analysis_summary'] = summary
|
||
logger.info(f" 市场状态: {summary}")
|
||
|
||
# 输出新闻情绪（如果有）
|
||
# 注：新的分析器不包含新闻分析，可以跳过或从其他地方获取
|
||
|
||
# 输出关键价位
|
||
levels = market_signal.get('key_levels', {})
|
||
if levels.get('support') or levels.get('resistance'):
|
||
support_str = ', '.join([f"${s:,.2f}" for s in levels.get('support', [])[:2]])
|
||
resistance_str = ', '.join([f"${r:,.2f}" for r in levels.get('resistance', [])[:2]])
|
||
logger.info(f" 支撑位: {support_str or '-'}")
|
||
logger.info(f" 阻力位: {resistance_str or '-'}")
|
||
|
||
# 5. 处理信号
|
||
signals = market_signal.get('signals', [])
|
||
result['signals'] = signals
|
||
|
||
if not signals:
|
||
logger.info(f"\n⏸️ 结论: 无交易信号，继续观望")
|
||
return result
|
||
|
||
# 输出所有信号
|
||
logger.info(f"\n🎯 【发现 {len(signals)} 个信号】")
|
||
|
||
for sig in signals:
|
||
signal_type = sig.get('type', 'unknown')
|
||
type_map = {'short_term': '短线', 'medium_term': '中线', 'long_term': '长线'}
|
||
type_text = type_map.get(signal_type, signal_type)
|
||
|
||
action = sig.get('action', 'wait')
|
||
action_map = {'buy': '🟢 做多', 'sell': '🔴 做空'}
|
||
action_text = action_map.get(action, action)
|
||
|
||
grade = sig.get('grade', 'D')
|
||
confidence = sig.get('confidence', 0)
|
||
grade_icon = {'A': '⭐⭐⭐', 'B': '⭐⭐', 'C': '⭐', 'D': ''}.get(grade, '')
|
||
|
||
logger.info(f"\n {type_text} {action_text} [{grade}级{grade_icon}] {confidence}%")
|
||
|
||
# 6. 过滤并通知最佳信号
|
||
best_signal = self._get_best_signal(signals)
|
||
|
||
if not best_signal:
|
||
logger.info(f"\n⏸️ 信号质量不高，不发送通知")
|
||
return result
|
||
|
||
# 检查置信度阈值
|
||
threshold = self.settings.stock_llm_threshold * 100
|
||
if best_signal.get('confidence', 0) < threshold:
|
||
logger.info(f"\n⏸️ 置信度不足 ({best_signal.get('confidence', 0)}% < {threshold}%)")
|
||
return result
|
||
|
||
# 检查冷却时间
|
||
if not self._should_send_signal(symbol, best_signal):
|
||
logger.info(f"\n⏸️ 信号冷却中，不发送通知")
|
||
return result
|
||
|
||
# 发送通知
|
||
await self._send_signal_notification(symbol, best_signal, current_price)
|
||
result['notified'] = True
|
||
result['best_signal'] = best_signal
|
||
|
||
# 更新状态
|
||
self.last_signals[symbol] = best_signal
|
||
self.signal_cooldown[symbol] = datetime.now()
|
||
|
||
return result
|
||
|
||
except Exception as e:
|
||
logger.error(f"❌ 分析 {symbol} 出错: {e}")
|
||
import traceback
|
||
logger.error(traceback.format_exc())
|
||
return result
|
||
|
||
def _get_best_signal(self, signals: List[Dict[str, Any]]) -> Optional[Dict[str, Any]]:
|
||
"""获取最佳信号"""
|
||
# 过滤掉 D 级信号
|
||
valid_signals = [s for s in signals if s.get('grade', 'D') != 'D']
|
||
|
||
if not valid_signals:
|
||
return None
|
||
|
||
# 按等级和置信度排序
|
||
grade_order = {'A': 0, 'B': 1, 'C': 2}
|
||
valid_signals.sort(key=lambda x: (
|
||
grade_order.get(x.get('grade', 'C'), 3),
|
||
-x.get('confidence', 0)
|
||
))
|
||
|
||
return valid_signals[0]
|
||
|
||
def _should_send_signal(self, symbol: str, signal: Dict[str, Any]) -> bool:
|
||
"""判断是否应该发送信号"""
|
||
action = signal.get('action', 'wait')
|
||
if action == 'wait':
|
||
return False
|
||
|
||
# 检查冷却时间（60分钟内不重复发送相同方向的信号）
|
||
if symbol in self.signal_cooldown:
|
||
cooldown_end = self.signal_cooldown[symbol] + timedelta(minutes=60)
|
||
if datetime.now() < cooldown_end:
|
||
if symbol in self.last_signals:
|
||
if self.last_signals[symbol].get('action') == action:
|
||
logger.debug(f"{symbol} 信号冷却中，跳过")
|
||
return False
|
||
|
||
return True
|
||
|
||
async def _send_signal_notification(
|
||
self,
|
||
symbol: str,
|
||
signal: Dict[str, Any],
|
||
current_price: float
|
||
):
|
||
"""发送信号通知"""
|
||
try:
|
||
from app.utils.signal_formatter import get_signal_formatter
|
||
formatter = get_signal_formatter()
|
||
|
||
# 使用格式化工具格式化信号
|
||
card = formatter.format_feishu_card(signal, symbol, agent_type='stock')
|
||
title = card['title']
|
||
content = card['content']
|
||
|
||
# 根据信号方向选择颜色
|
||
color = "green" if signal.get('action') == 'buy' else "red"
|
||
|
||
# 发送到飞书
|
||
await self.feishu.send_card(title, content, color)
|
||
|
||
# 发送到 Telegram
|
||
await self.telegram.send_message(formatter.format_signal_message(signal, symbol, agent_type='stock'))
|
||
|
||
logger.info(f"✅ 信号通知已发送: {title}")
|
||
|
||
# 保存信号到数据库
|
||
signal_to_save = signal.copy()
|
||
signal_to_save['signal_type'] = 'stock'
|
||
signal_to_save['symbol'] = symbol
|
||
signal_to_save['current_price'] = current_price
|
||
self.signal_db.add_signal(signal_to_save)
|
||
|
||
except Exception as e:
|
||
logger.error(f"发送通知失败: {e}")
|
||
|
||
def _validate_data(self, data: Dict[str, pd.DataFrame]) -> bool:
|
||
"""验证数据完整性"""
|
||
required_intervals = ['1d', '1h']
|
||
for interval in required_intervals:
|
||
if interval not in data or data[interval].empty:
|
||
return False
|
||
if len(data[interval]) < 20:
|
||
return False
|
||
return True
|
||
|
||
async def analyze_once(self, symbol: str) -> Dict[str, Any]:
|
||
"""单次分析（用于测试或手动触发）"""
|
||
data = self.yfinance.get_multi_timeframe_data(symbol)
|
||
|
||
if not self._validate_data(data):
|
||
return {'error': '数据不完整'}
|
||
|
||
# 获取基本面数据
|
||
fundamental_data = None
|
||
fundamental_summary = ""
|
||
try:
|
||
fundamental_data = self.fundamental.get_fundamental_data(symbol)
|
||
if fundamental_data:
|
||
# 传递已获取的数据，避免重复调用
|
||
fundamental_summary = self.fundamental.get_fundamental_summary(symbol, fundamental_data)
|
||
except Exception as e:
|
||
logger.warning(f"获取基本面数据失败: {e}")
|
||
|
||
result = await self.market_analyzer.analyze(
|
||
symbol, data,
|
||
symbols=self.symbols
|
||
)
|
||
return result
|
||
|
||
def get_status(self) -> Dict[str, Any]:
|
||
"""获取智能体状态"""
|
||
return {
|
||
'running': self.running,
|
||
'symbols': self.symbols,
|
||
'mode': 'LLM 驱动（仅分析通知）',
|
||
'last_signals': {
|
||
symbol: {
|
||
'type': sig.get('type'),
|
||
'action': sig.get('action'),
|
||
'confidence': sig.get('confidence'),
|
||
'grade': sig.get('grade')
|
||
}
|
||
for symbol, sig in self.last_signals.items()
|
||
}
|
||
}
|
||
|
||
async def _send_summary_report(self, results: List[Dict[str, Any]], analysis_type: str = "盘中"):
|
||
"""
|
||
生成并发送分析汇总报告
|
||
|
||
Args:
|
||
results: 所有股票的分析结果列表
|
||
analysis_type: 分析类型 ("盘中" 或 "盘后")
|
||
"""
|
||
try:
|
||
now = datetime.now()
|
||
total = len(results)
|
||
with_signals = [r for r in results if r.get('signals')]
|
||
notified = [r for r in results if r.get('notified')]
|
||
|
||
# 区分美股和港股
|
||
us_results = [r for r in results if not r['symbol'].endswith('.HK')]
|
||
hk_results = [r for r in results if r['symbol'].endswith('.HK')]
|
||
us_with_signals = [r for r in us_results if r.get('signals')]
|
||
hk_with_signals = [r for r in hk_results if r.get('signals')]
|
||
|
||
# 统计信号
|
||
buy_signals = []
|
||
sell_signals = []
|
||
high_quality_signals = [] # A/B级信号
|
||
|
||
for r in with_signals:
|
||
for sig in r.get('signals', []):
|
||
sig['symbol'] = r['symbol']
|
||
sig['current_price'] = r.get('current_price', 0)
|
||
sig['is_hk'] = r['symbol'].endswith('.HK')
|
||
sig['stock_name'] = STOCK_NAMES.get(r['symbol'], '')
|
||
|
||
if sig.get('action') == 'buy':
|
||
buy_signals.append(sig)
|
||
elif sig.get('action') == 'sell':
|
||
sell_signals.append(sig)
|
||
|
||
if sig.get('grade') in ['A', 'B']:
|
||
high_quality_signals.append(sig)
|
||
|
||
# 按置信度排序
|
||
high_quality_signals.sort(key=lambda x: x.get('confidence', 0), reverse=True)
|
||
|
||
# 构建汇总报告
|
||
analysis_tag = f"【{analysis_type}分析】"
|
||
logger.info(f"\n{'='*80}")
|
||
logger.info(f"📊 股票分析汇总报告 {analysis_tag}")
|
||
logger.info(f"{'='*80}")
|
||
logger.info(f"时间: {now.strftime('%Y-%m-%d %H:%M:%S')}")
|
||
logger.info(f"分析总数: {total} 只 (美股: {len(us_results)}, 港股: {len(hk_results)})")
|
||
logger.info(f"有信号: {len(with_signals)} 只 (美股: {len(us_with_signals)}, 港股: {len(hk_with_signals)})")
|
||
logger.info(f"已通知: {len(notified)} 只")
|
||
logger.info(f"")
|
||
|
||
# 显示高等级信号
|
||
if high_quality_signals:
|
||
logger.info(f"⭐ 高等级信号 (A/B级): {len(high_quality_signals)} 个")
|
||
for sig in high_quality_signals[:10]: # 最多显示10个
|
||
symbol = sig['symbol']
|
||
stock_name = sig.get('stock_name', '')
|
||
market_tag = '[港股]' if sig.get('is_hk') else '[美股]'
|
||
action = '🟢 做多' if sig.get('action') == 'buy' else '🔴 做空'
|
||
grade = sig.get('grade', 'D')
|
||
confidence = sig.get('confidence', 0)
|
||
price = sig.get('current_price', 0)
|
||
entry = sig.get('entry_price', 0)
|
||
|
||
# 构建带名称的股票显示
|
||
symbol_display = f"{stock_name}({symbol})" if stock_name else symbol
|
||
|
||
logger.info(f" {market_tag} {symbol_display} {action} [{grade}级] {confidence}% @ ${price:,.2f}")
|
||
if entry > 0:
|
||
logger.info(f" 入场: ${entry:,.2f}")
|
||
logger.info(f"")
|
||
|
||
# 统计汇总
|
||
logger.info(f"📈 做多信号: {len(buy_signals)} 个")
|
||
logger.info(f"📉 做空信号: {len(sell_signals)} 个")
|
||
logger.info(f"{'='*80}\n")
|
||
|
||
# 发送飞书汇总
|
||
await self._send_feishu_summary(
|
||
now, total, with_signals, notified,
|
||
buy_signals, sell_signals, high_quality_signals,
|
||
len(us_results), len(hk_results),
|
||
analysis_type
|
||
)
|
||
|
||
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,
|
||
us_count: int = 0,
|
||
hk_count: int = 0,
|
||
analysis_type: str = "盘中"
|
||
):
|
||
"""发送飞书汇总报告"""
|
||
try:
|
||
# 构建内容
|
||
analysis_tag = f"【{analysis_type}分析】"
|
||
content_parts = [
|
||
f"**📊 股票分析汇总报告 {analysis_tag}**",
|
||
f"",
|
||
f"⏰ 时间: {now.strftime('%Y-%m-%d %H:%M')}",
|
||
f"",
|
||
f"📊 **分析概况**",
|
||
f"• 美股: {us_count} 只 | 港股: {hk_count} 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']
|
||
stock_name = sig.get('stock_name', '')
|
||
market_tag = '[港股]' if sig.get('is_hk') else '[美股]'
|
||
action = '🟢 做多' if sig.get('action') == 'buy' else '🔴 做空'
|
||
grade = sig.get('grade', 'D')
|
||
confidence = sig.get('confidence', 0)
|
||
|
||
# 构建带名称的股票显示
|
||
symbol_display = f"{stock_name}({symbol})" if stock_name else symbol
|
||
|
||
content_parts.append(f"• {market_tag} {symbol_display} {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 - 标题包含分析类型
|
||
type_tag = "盘后" if analysis_type == "盘后" else "分析"
|
||
title = f"📊 股票{type_tag}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
|