支持 us stock
This commit is contained in:
aaron
parent
49adf5da6a
commit
29b2fad1d6
@ -12,6 +12,7 @@ from app.skills.technical_analysis import TechnicalAnalysisSkill
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from app.skills.fundamental import FundamentalSkill
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from app.skills.visualization import VisualizationSkill
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from app.skills.advanced_data import AdvancedDataSkill
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from app.skills.us_stock_skill import USStockSkill
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from app.services.llm_service import llm_service
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from app.services.tushare_service import tushare_service
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from app.utils.logger import logger
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@ -43,7 +44,8 @@ class SmartStockAgent:
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skill_manager.register(FundamentalSkill())
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skill_manager.register(VisualizationSkill())
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skill_manager.register(AdvancedDataSkill())
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logger.info("技能注册完成（Tushare Pro高级数据）")
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skill_manager.register(USStockSkill())
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logger.info("技能注册完成（Tushare Pro高级数据 + 美股支持）")
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async def process_message(
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self,
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@ -1000,6 +1002,7 @@ MA60：{f"{ma['ma60']:.2f}" if ma['ma60'] else '计算中'}
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1. **stock_specific** - 针对特定股票或指数的问题
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例如："贵州茅台怎么样"、"分析一下比亚迪"、"600519的技术指标"、"帮我看看这只股票"
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**重要**：指数查询也属于此类，例如："上证指数怎么样"、"分析大盘"、"A股指数走势"、"深证成指"
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**美股支持**：美股查询也属于此类，例如："苹果股票怎么样"、"AAPL分析"、"特斯拉走势"、"TSLA技术指标"
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2. **macro_finance** - 宏观金融/市场问题（不针对特定股票或指数）
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例如："最近有什么投资机会"、"现在适合买股票吗"、"市场情绪如何"
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@ -1014,6 +1017,7 @@ MA60：{f"{ma['ma60']:.2f}" if ma['ma60'] else '计算中'}
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- 如果用户问题不明确，但可能与金融相关，优先归类为 general_chat，以便引导用户
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- 如果用户提到"这只股票"、"它"等代词，查看对话历史判断是否指特定股票
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- **如果用户提到"大盘"、"上证"、"深证"、"A股指数"等，归类为 stock_specific，并在stock_names中填入对应的指数名称**
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- **如果用户提到美股公司名称（如苹果、特斯拉、微软）或美股代码（如AAPL、TSLA、MSFT），归类为 stock_specific，并在stock_names中填入对应的股票名称或代码**
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- 对于模糊的问题，不要强行归类，使用 general_chat 类型
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请以JSON格式返回分析结果：
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@ -1021,7 +1025,8 @@ MA60：{f"{ma['ma60']:.2f}" if ma['ma60'] else '计算中'}
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"type": "问题类型",
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"description": "问题的简要描述（用一句话概括用户想了解什么）",
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"keywords": ["关键词1", "关键词2"],
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"stock_names": ["股票名称或指数名称"] (仅当type为stock_specific时，如果有的话)
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"stock_names": ["股票名称或指数名称或美股代码"] (仅当type为stock_specific时，如果有的话),
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"market": "A股" 或 "美股" (仅当type为stock_specific时，根据股票类型判断)
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}}
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只返回JSON，不要有任何其他内容。"""
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@ -1071,6 +1076,7 @@ MA60：{f"{ma['ma60']:.2f}" if ma['ma60'] else '计算中'}
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) -> Dict[str, Any]:
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"""处理针对特定股票或指数的问题"""
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stock_names = intent_analysis.get('stock_names', [])
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market = intent_analysis.get('market', 'A股') # 默认A股
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if not stock_names:
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return {
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@ -1081,6 +1087,14 @@ MA60：{f"{ma['ma60']:.2f}" if ma['ma60'] else '计算中'}
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# 提取第一个股票或指数
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stock_keyword = stock_names[0]
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# 检测是否为美股
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is_us_stock = self._is_us_stock(stock_keyword, market)
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if is_us_stock:
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# 处理美股
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return await self._handle_us_stock(stock_keyword, message)
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# 处理A股和指数
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# 指数映射表
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index_mapping = {
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"上证指数": "000001.SH",
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@ -1332,6 +1346,285 @@ MA60：{f"{ma['ma60']:.2f}" if ma['ma60'] else '计算中'}
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"metadata": {"type": "chat"}
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}
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def _is_us_stock(self, keyword: str, market: str) -> bool:
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"""
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判断是否为美股
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Args:
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keyword: 股票关键词
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market: 市场类型（从LLM意图分析中获取）
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Returns:
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是否为美股
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"""
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# 如果LLM已经判断为美股
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if market == "美股":
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return True
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# 检查是否为全大写字母（美股代码特征）
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if keyword.isupper() and keyword.isalpha() and len(keyword) <= 5:
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return True
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# 常见美股公司名称映射
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us_stock_names = {
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"苹果": "AAPL",
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"特斯拉": "TSLA",
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"微软": "MSFT",
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"谷歌": "GOOGL",
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"亚马逊": "AMZN",
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"Meta": "META",
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"脸书": "META",
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"英伟达": "NVDA",
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"奈飞": "NFLX",
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"网飞": "NFLX",
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"迪士尼": "DIS",
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"可口可乐": "KO",
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"麦当劳": "MCD",
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"星巴克": "SBUX",
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"耐克": "NKE",
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"波音": "BA",
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"英特尔": "INTC",
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"AMD": "AMD",
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"高通": "QCOM",
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"推特": "TWTR",
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"优步": "UBER",
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"Uber": "UBER",
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"Airbnb": "ABNB",
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"爱彼迎": "ABNB",
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}
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if keyword in us_stock_names:
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return True
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return False
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def _get_us_stock_symbol(self, keyword: str) -> str:
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"""
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获取美股代码
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Args:
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keyword: 股票关键词
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Returns:
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美股代码
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"""
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# 如果已经是代码格式，直接返回
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if keyword.isupper() and keyword.isalpha():
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return keyword
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# 中文名称映射
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us_stock_names = {
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"苹果": "AAPL",
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"特斯拉": "TSLA",
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"微软": "MSFT",
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"谷歌": "GOOGL",
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"亚马逊": "AMZN",
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"Meta": "META",
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"脸书": "META",
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"英伟达": "NVDA",
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"奈飞": "NFLX",
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"网飞": "NFLX",
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"迪士尼": "DIS",
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"可口可乐": "KO",
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"麦当劳": "MCD",
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"星巴克": "SBUX",
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"耐克": "NKE",
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"波音": "BA",
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"英特尔": "INTC",
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"AMD": "AMD",
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"高通": "QCOM",
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"推特": "TWTR",
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"优步": "UBER",
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"Uber": "UBER",
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"Airbnb": "ABNB",
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"爱彼迎": "ABNB",
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}
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return us_stock_names.get(keyword, keyword.upper())
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async def _handle_us_stock(self, keyword: str, message: str) -> Dict[str, Any]:
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"""
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处理美股查询
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Args:
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keyword: 股票关键词
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message: 用户消息
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Returns:
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分析结果
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"""
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# 获取美股代码
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symbol = self._get_us_stock_symbol(keyword)
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logger.info(f"处理美股查询: {keyword} -> {symbol}")
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try:
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# 调用美股分析技能
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result = await skill_manager.execute_skill(
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"us_stock_analysis",
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symbol=symbol,
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analysis_type="comprehensive"
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)
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if not result.get("success"):
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return {
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"message": f"抱歉，未找到美股 {symbol}。请确认股票代码是否正确。\n\n提示：美股代码通常为大写字母，如 AAPL（苹果）、TSLA（特斯拉）、MSFT（微软）等。",
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"metadata": {"type": "error"}
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}
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# 使用LLM分析美股数据
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if self.use_llm:
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analysis = await self._llm_us_stock_analysis(result["data"], message)
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else:
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analysis = self._format_us_stock_data(result["data"])
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return {
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"message": analysis,
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"metadata": {
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"type": "us_stock_analysis",
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"data": result["data"]
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}
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}
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except Exception as e:
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logger.error(f"美股查询失败: {e}")
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return {
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"message": f"查询美股 {symbol} 时出错：{str(e)}",
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"metadata": {"type": "error"}
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}
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async def _llm_us_stock_analysis(self, data: Dict[str, Any], user_message: str) -> str:
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"""使用LLM分析美股数据"""
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from datetime import datetime
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current_time = datetime.now().strftime("%Y-%m-%d %H:%M")
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# 提取关键数据
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symbol = data.get("symbol", "")
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name = data.get("name", "")
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sector = data.get("sector", "")
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industry = data.get("industry", "")
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current_price = data.get("current_price", 0)
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change = data.get("change", 0)
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change_pct = data.get("change_percent", 0)
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volume = data.get("volume", 0)
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market_cap = data.get("market_cap", 0)
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pe_ratio = data.get("pe_ratio", 0)
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pb_ratio = data.get("pb_ratio", 0)
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dividend_yield = data.get("dividend_yield", 0)
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week_52_high = data.get("52_week_high", 0)
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week_52_low = data.get("52_week_low", 0)
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technical = data.get("technical_indicators", {})
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description = data.get("description", "")
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# 格式化市值
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market_cap_str = f"${market_cap / 1e9:.2f}B" if market_cap > 1e9 else f"${market_cap / 1e6:.2f}M"
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# 构建分析提示
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prompt = f"""你是一位专业的美股分析师。请基于以下数据对 {name} ({symbol}) 进行全面分析。
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【基本信息】
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股票代码：{symbol}
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公司名称：{name}
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所属行业：{sector} - {industry}
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公司简介：{description[:300] if description else '暂无'}
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【实时行情】（数据时间：{current_time}）
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当前价格：${current_price:.2f}
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涨跌额：${change:.2f}
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涨跌幅：{change_pct:.2f}%
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成交量：{volume:,}
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市值：{market_cap_str}
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【估值指标】
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市盈率(PE)：{f"{pe_ratio:.2f}" if pe_ratio else '暂无'}
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市净率(PB)：{f"{pb_ratio:.2f}" if pb_ratio else '暂无'}
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股息率：{f"{dividend_yield * 100:.2f}%" if dividend_yield else '暂无'}
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52周最高：${week_52_high:.2f}
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52周最低：${week_52_low:.2f}
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【技术指标】
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MA5：{f"${technical.get('ma5'):.2f}" if technical.get('ma5') else '计算中'}
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MA10：{f"${technical.get('ma10'):.2f}" if technical.get('ma10') else '计算中'}
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MA20：{f"${technical.get('ma20'):.2f}" if technical.get('ma20') else '计算中'}
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MA60：{f"${technical.get('ma60'):.2f}" if technical.get('ma60') else '计算中'}
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RSI：{f"{technical.get('rsi'):.2f}" if technical.get('rsi') else '计算中'}
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MACD：{f"{technical.get('macd'):.4f}" if technical.get('macd') else '计算中'}
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用户问题：{user_message}
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请提供专业的分析报告，包括：
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## 📊 行情概览
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简要总结当前股价表现和市场表现（2-3句话）
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## 💼 公司基本面
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- 行业地位和竞争优势
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- 估值水平分析（PE、PB是否合理）
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- 盈利能力和成长性
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## 📈 技术面分析
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- 当前趋势判断（基于均线系统）
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- 关键支撑位和压力位
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- RSI和MACD信号解读
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## 💡 投资建议
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- 短期操作建议（1-2周）
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- 中期投资价值（1-3个月）
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- 风险提示
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写作要求：
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1. 语言专业但易懂，避免过度修饰
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2. 分析客观理性，基于数据和事实
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3. 每个部分独立成段，段落间用空行分隔
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4. 控制在500-600字
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5. 最后声明："以上分析仅供参考，不构成投资建议。美股投资有风险，请谨慎决策。"
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"""
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try:
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analysis = llm_service.chat(
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messages=[{"role": "user", "content": prompt}],
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temperature=0.7,
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max_tokens=2000
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)
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if analysis:
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return f"【美股分析】{name} ({symbol})\n\n{analysis}"
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else:
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return self._format_us_stock_data(data)
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except Exception as e:
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logger.error(f"LLM美股分析失败: {e}")
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return self._format_us_stock_data(data)
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def _format_us_stock_data(self, data: Dict[str, Any]) -> str:
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"""格式化美股数据（降级方案）"""
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symbol = data.get("symbol", "")
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name = data.get("name", "")
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current_price = data.get("current_price", 0)
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change = data.get("change", 0)
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change_pct = data.get("change_percent", 0)
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market_cap = data.get("market_cap", 0)
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pe_ratio = data.get("pe_ratio", 0)
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technical = data.get("technical_indicators", {})
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market_cap_str = f"${market_cap / 1e9:.2f}B" if market_cap > 1e9 else f"${market_cap / 1e6:.2f}M"
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change_emoji = "📈" if change >= 0 else "📉"
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return f"""【美股行情】{name} ({symbol})
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{change_emoji} 当前价格：${current_price:.2f}
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涨跌：${change:.2f} ({change_pct:+.2f}%)
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市值：{market_cap_str}
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市盈率：{pe_ratio:.2f if pe_ratio else '暂无'}
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【技术指标】
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MA5：${technical.get('ma5', 0):.2f if technical.get('ma5') else '计算中'}
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MA20：${technical.get('ma20', 0):.2f if technical.get('ma20') else '计算中'}
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RSI：{technical.get('rsi', 0):.2f if technical.get('rsi') else '计算中'}
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以上数据仅供参考，不构成投资建议。"""
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# 创建全局实例
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smart_agent = SmartStockAgent()
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282
backend/app/services/us_stock_service.py
Normal file
282
backend/app/services/us_stock_service.py
Normal file
@ -0,0 +1,282 @@
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"""
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美股数据服务 - 使用 yfinance 获取美股数据
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"""
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from typing import Optional, Dict, Any, List
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import yfinance as yf
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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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class USStockService:
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"""美股数据服务类"""
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def __init__(self):
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"""初始化美股数据服务"""
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self.cache = {} # 简单的内存缓存
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def get_stock_info(self, symbol: str) -> Optional[Dict[str, Any]]:
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"""
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获取美股基本信息
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Args:
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symbol: 股票代码（如 AAPL, TSLA）
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Returns:
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股票基本信息字典
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"""
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try:
|
||||
stock = yf.Ticker(symbol)
|
||||
info = stock.info
|
||||
|
||||
if not info or 'symbol' not in info:
|
||||
logger.warning(f"未找到股票: {symbol}")
|
||||
return None
|
||||
|
||||
# 提取关键信息
|
||||
result = {
|
||||
"symbol": symbol,
|
||||
"name": info.get("longName", info.get("shortName", symbol)),
|
||||
"sector": info.get("sector", "未知"),
|
||||
"industry": info.get("industry", "未知"),
|
||||
"market_cap": info.get("marketCap", 0),
|
||||
"current_price": info.get("currentPrice", info.get("regularMarketPrice", 0)),
|
||||
"previous_close": info.get("previousClose", 0),
|
||||
"open": info.get("open", 0),
|
||||
"day_high": info.get("dayHigh", 0),
|
||||
"day_low": info.get("dayLow", 0),
|
||||
"volume": info.get("volume", 0),
|
||||
"avg_volume": info.get("averageVolume", 0),
|
||||
"pe_ratio": info.get("trailingPE", 0),
|
||||
"forward_pe": info.get("forwardPE", 0),
|
||||
"pb_ratio": info.get("priceToBook", 0),
|
||||
"dividend_yield": info.get("dividendYield", 0),
|
||||
"52_week_high": info.get("fiftyTwoWeekHigh", 0),
|
||||
"52_week_low": info.get("fiftyTwoWeekLow", 0),
|
||||
"50_day_avg": info.get("fiftyDayAverage", 0),
|
||||
"200_day_avg": info.get("twoHundredDayAverage", 0),
|
||||
"beta": info.get("beta", 0),
|
||||
"eps": info.get("trailingEps", 0),
|
||||
"description": info.get("longBusinessSummary", ""),
|
||||
}
|
||||
|
||||
logger.info(f"获取美股信息成功: {symbol}")
|
||||
return result
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"获取美股信息失败 {symbol}: {e}")
|
||||
return None
|
||||
|
||||
def get_historical_data(
|
||||
self,
|
||||
symbol: str,
|
||||
period: str = "1mo",
|
||||
interval: str = "1d"
|
||||
) -> Optional[pd.DataFrame]:
|
||||
"""
|
||||
获取美股历史K线数据
|
||||
|
||||
Args:
|
||||
symbol: 股票代码
|
||||
period: 时间周期 (1d, 5d, 1mo, 3mo, 6mo, 1y, 2y, 5y, 10y, ytd, max)
|
||||
interval: K线间隔 (1m, 2m, 5m, 15m, 30m, 60m, 90m, 1h, 1d, 5d, 1wk, 1mo, 3mo)
|
||||
|
||||
Returns:
|
||||
包含OHLCV数据的DataFrame
|
||||
"""
|
||||
try:
|
||||
stock = yf.Ticker(symbol)
|
||||
hist = stock.history(period=period, interval=interval)
|
||||
|
||||
if hist.empty:
|
||||
logger.warning(f"未找到历史数据: {symbol}")
|
||||
return None
|
||||
|
||||
logger.info(f"获取美股历史数据成功: {symbol}, 周期: {period}")
|
||||
return hist
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"获取美股历史数据失败 {symbol}: {e}")
|
||||
return None
|
||||
|
||||
def get_financial_data(self, symbol: str) -> Optional[Dict[str, Any]]:
|
||||
"""
|
||||
获取美股财务数据
|
||||
|
||||
Args:
|
||||
symbol: 股票代码
|
||||
|
||||
Returns:
|
||||
财务数据字典
|
||||
"""
|
||||
try:
|
||||
stock = yf.Ticker(symbol)
|
||||
|
||||
# 获取财务报表
|
||||
financials = stock.financials
|
||||
balance_sheet = stock.balance_sheet
|
||||
cashflow = stock.cashflow
|
||||
|
||||
result = {
|
||||
"symbol": symbol,
|
||||
"income_statement": financials.to_dict() if not financials.empty else {},
|
||||
"balance_sheet": balance_sheet.to_dict() if not balance_sheet.empty else {},
|
||||
"cash_flow": cashflow.to_dict() if not cashflow.empty else {},
|
||||
}
|
||||
|
||||
# 获取关键财务指标
|
||||
info = stock.info
|
||||
result["key_metrics"] = {
|
||||
"revenue": info.get("totalRevenue", 0),
|
||||
"gross_profit": info.get("grossProfits", 0),
|
||||
"ebitda": info.get("ebitda", 0),
|
||||
"net_income": info.get("netIncomeToCommon", 0),
|
||||
"total_assets": info.get("totalAssets", 0),
|
||||
"total_debt": info.get("totalDebt", 0),
|
||||
"total_cash": info.get("totalCash", 0),
|
||||
"operating_cash_flow": info.get("operatingCashflow", 0),
|
||||
"free_cash_flow": info.get("freeCashflow", 0),
|
||||
"roe": info.get("returnOnEquity", 0),
|
||||
"roa": info.get("returnOnAssets", 0),
|
||||
"profit_margin": info.get("profitMargins", 0),
|
||||
"operating_margin": info.get("operatingMargins", 0),
|
||||
}
|
||||
|
||||
logger.info(f"获取美股财务数据成功: {symbol}")
|
||||
return result
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"获取美股财务数据失败 {symbol}: {e}")
|
||||
return None
|
||||
|
||||
def calculate_technical_indicators(self, hist: pd.DataFrame) -> Dict[str, Any]:
|
||||
"""
|
||||
计算技术指标
|
||||
|
||||
Args:
|
||||
hist: 历史数据DataFrame
|
||||
|
||||
Returns:
|
||||
技术指标字典
|
||||
"""
|
||||
try:
|
||||
if hist.empty or len(hist) < 20:
|
||||
return {}
|
||||
|
||||
close = hist['Close']
|
||||
|
||||
# 计算移动平均线
|
||||
ma5 = close.rolling(window=5).mean().iloc[-1] if len(close) >= 5 else None
|
||||
ma10 = close.rolling(window=10).mean().iloc[-1] if len(close) >= 10 else None
|
||||
ma20 = close.rolling(window=20).mean().iloc[-1] if len(close) >= 20 else None
|
||||
ma60 = close.rolling(window=60).mean().iloc[-1] if len(close) >= 60 else None
|
||||
|
||||
# 计算RSI
|
||||
delta = close.diff()
|
||||
gain = (delta.where(delta > 0, 0)).rolling(window=14).mean()
|
||||
loss = (-delta.where(delta < 0, 0)).rolling(window=14).mean()
|
||||
rs = gain / loss
|
||||
rsi = 100 - (100 / (1 + rs))
|
||||
rsi_value = rsi.iloc[-1] if len(rsi) >= 14 else None
|
||||
|
||||
# 计算MACD
|
||||
exp1 = close.ewm(span=12, adjust=False).mean()
|
||||
exp2 = close.ewm(span=26, adjust=False).mean()
|
||||
macd = exp1 - exp2
|
||||
signal = macd.ewm(span=9, adjust=False).mean()
|
||||
macd_value = macd.iloc[-1] if len(macd) >= 26 else None
|
||||
signal_value = signal.iloc[-1] if len(signal) >= 26 else None
|
||||
|
||||
# 计算布林带
|
||||
bb_middle = close.rolling(window=20).mean()
|
||||
bb_std = close.rolling(window=20).std()
|
||||
bb_upper = bb_middle + (bb_std * 2)
|
||||
bb_lower = bb_middle - (bb_std * 2)
|
||||
|
||||
result = {
|
||||
"ma5": float(ma5) if ma5 and not pd.isna(ma5) else None,
|
||||
"ma10": float(ma10) if ma10 and not pd.isna(ma10) else None,
|
||||
"ma20": float(ma20) if ma20 and not pd.isna(ma20) else None,
|
||||
"ma60": float(ma60) if ma60 and not pd.isna(ma60) else None,
|
||||
"rsi": float(rsi_value) if rsi_value and not pd.isna(rsi_value) else None,
|
||||
"macd": float(macd_value) if macd_value and not pd.isna(macd_value) else None,
|
||||
"macd_signal": float(signal_value) if signal_value and not pd.isna(signal_value) else None,
|
||||
"bb_upper": float(bb_upper.iloc[-1]) if len(bb_upper) >= 20 and not pd.isna(bb_upper.iloc[-1]) else None,
|
||||
"bb_middle": float(bb_middle.iloc[-1]) if len(bb_middle) >= 20 and not pd.isna(bb_middle.iloc[-1]) else None,
|
||||
"bb_lower": float(bb_lower.iloc[-1]) if len(bb_lower) >= 20 and not pd.isna(bb_lower.iloc[-1]) else None,
|
||||
}
|
||||
|
||||
return result
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"计算技术指标失败: {e}")
|
||||
return {}
|
||||
|
||||
def get_comprehensive_analysis(self, symbol: str) -> Optional[Dict[str, Any]]:
|
||||
"""
|
||||
获取美股综合分析数据
|
||||
|
||||
Args:
|
||||
symbol: 股票代码
|
||||
|
||||
Returns:
|
||||
综合分析数据字典
|
||||
"""
|
||||
try:
|
||||
# 获取基本信息
|
||||
info = self.get_stock_info(symbol)
|
||||
if not info:
|
||||
return None
|
||||
|
||||
# 获取历史数据
|
||||
hist = self.get_historical_data(symbol, period="6mo", interval="1d")
|
||||
if hist is None or hist.empty:
|
||||
return {
|
||||
"success": False,
|
||||
"error": "无法获取历史数据"
|
||||
}
|
||||
|
||||
# 计算技术指标
|
||||
technical = self.calculate_technical_indicators(hist)
|
||||
|
||||
# 获取最近的价格数据
|
||||
latest = hist.iloc[-1]
|
||||
prev = hist.iloc[-2] if len(hist) > 1 else latest
|
||||
|
||||
# 计算涨跌幅
|
||||
change = latest['Close'] - prev['Close']
|
||||
change_pct = (change / prev['Close'] * 100) if prev['Close'] != 0 else 0
|
||||
|
||||
result = {
|
||||
"success": True,
|
||||
"symbol": symbol,
|
||||
"name": info["name"],
|
||||
"sector": info["sector"],
|
||||
"industry": info["industry"],
|
||||
"current_price": float(latest['Close']),
|
||||
"change": float(change),
|
||||
"change_percent": float(change_pct),
|
||||
"volume": int(latest['Volume']),
|
||||
"market_cap": info["market_cap"],
|
||||
"pe_ratio": info["pe_ratio"],
|
||||
"pb_ratio": info["pb_ratio"],
|
||||
"dividend_yield": info["dividend_yield"],
|
||||
"52_week_high": info["52_week_high"],
|
||||
"52_week_low": info["52_week_low"],
|
||||
"technical_indicators": technical,
|
||||
"description": info["description"][:500] if info["description"] else "",
|
||||
}
|
||||
|
||||
logger.info(f"获取美股综合分析成功: {symbol}")
|
||||
return result
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"获取美股综合分析失败 {symbol}: {e}")
|
||||
return {
|
||||
"success": False,
|
||||
"error": str(e)
|
||||
}
|
||||
|
||||
|
||||
# 创建全局实例
|
||||
us_stock_service = USStockService()
|
||||
118
backend/app/skills/us_stock_skill.py
Normal file
118
backend/app/skills/us_stock_skill.py
Normal file
@ -0,0 +1,118 @@
|
||||
"""
|
||||
美股分析技能
|
||||
"""
|
||||
from typing import Dict, Any
|
||||
from app.skills.base import BaseSkill, SkillParameter
|
||||
from app.services.us_stock_service import us_stock_service
|
||||
from app.utils.logger import logger
|
||||
|
||||
|
||||
class USStockSkill(BaseSkill):
|
||||
"""美股分析技能"""
|
||||
|
||||
def __init__(self):
|
||||
super().__init__()
|
||||
self.name = "us_stock_analysis"
|
||||
self.description = "分析美股（如 AAPL, TSLA, MSFT 等），获取实时行情、技术指标、基本面数据"
|
||||
self.parameters = [
|
||||
SkillParameter(
|
||||
name="symbol",
|
||||
type="string",
|
||||
description="美股代码（如 AAPL, TSLA, MSFT）",
|
||||
required=True
|
||||
),
|
||||
SkillParameter(
|
||||
name="analysis_type",
|
||||
type="string",
|
||||
description="分析类型：basic（基本信息）、technical（技术分析）、fundamental（基本面）、comprehensive（综合分析）",
|
||||
required=False,
|
||||
default="comprehensive"
|
||||
)
|
||||
]
|
||||
|
||||
async def execute(self, **kwargs) -> Dict[str, Any]:
|
||||
"""
|
||||
执行美股分析
|
||||
|
||||
Args:
|
||||
symbol: 美股代码
|
||||
analysis_type: 分析类型
|
||||
|
||||
Returns:
|
||||
分析结果字典
|
||||
"""
|
||||
try:
|
||||
symbol = kwargs.get("symbol", "").upper()
|
||||
analysis_type = kwargs.get("analysis_type", "comprehensive")
|
||||
|
||||
if not symbol:
|
||||
return {
|
||||
"success": False,
|
||||
"error": "请提供美股代码"
|
||||
}
|
||||
|
||||
logger.info(f"开始分析美股: {symbol}, 类型: {analysis_type}")
|
||||
|
||||
if analysis_type == "basic":
|
||||
# 基本信息
|
||||
info = us_stock_service.get_stock_info(symbol)
|
||||
if not info:
|
||||
return {
|
||||
"success": False,
|
||||
"error": f"未找到股票 {symbol}"
|
||||
}
|
||||
return {
|
||||
"success": True,
|
||||
"data": info
|
||||
}
|
||||
|
||||
elif analysis_type == "technical":
|
||||
# 技术分析
|
||||
hist = us_stock_service.get_historical_data(symbol, period="6mo")
|
||||
if hist is None or hist.empty:
|
||||
return {
|
||||
"success": False,
|
||||
"error": "无法获取历史数据"
|
||||
}
|
||||
|
||||
technical = us_stock_service.calculate_technical_indicators(hist)
|
||||
latest = hist.iloc[-1]
|
||||
|
||||
return {
|
||||
"success": True,
|
||||
"data": {
|
||||
"symbol": symbol,
|
||||
"current_price": float(latest['Close']),
|
||||
"volume": int(latest['Volume']),
|
||||
"technical_indicators": technical
|
||||
}
|
||||
}
|
||||
|
||||
elif analysis_type == "fundamental":
|
||||
# 基本面分析
|
||||
financial = us_stock_service.get_financial_data(symbol)
|
||||
if not financial:
|
||||
return {
|
||||
"success": False,
|
||||
"error": "无法获取财务数据"
|
||||
}
|
||||
return {
|
||||
"success": True,
|
||||
"data": financial
|
||||
}
|
||||
|
||||
else:
|
||||
# 综合分析（默认）
|
||||
result = us_stock_service.get_comprehensive_analysis(symbol)
|
||||
return result
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"美股分析失败: {e}")
|
||||
return {
|
||||
"success": False,
|
||||
"error": str(e)
|
||||
}
|
||||
|
||||
|
||||
# 创建全局实例
|
||||
us_stock_skill = USStockSkill()
|
||||
@ -10,8 +10,9 @@ pydantic==2.5.3
|
||||
pydantic-settings==2.1.0
|
||||
python-dotenv==1.0.0
|
||||
slowapi==0.1.9
|
||||
websockets==12.0
|
||||
websockets>=13.0
|
||||
pandas>=2.2.0
|
||||
numpy>=1.26.0
|
||||
python-multipart==0.0.6
|
||||
aiohttp==3.9.1
|
||||
yfinance>=0.2.36
|
||||
|
||||
@ -153,11 +153,11 @@ html, body {
|
||||
align-items: center;
|
||||
justify-content: center;
|
||||
text-align: center;
|
||||
padding: 40px;
|
||||
padding: 40px 20px;
|
||||
}
|
||||
|
||||
.welcome-icon {
|
||||
margin-bottom: 32px;
|
||||
margin-bottom: 20px;
|
||||
opacity: 0.3;
|
||||
}
|
||||
|
||||
@ -169,14 +169,56 @@ html, body {
|
||||
font-size: 28px;
|
||||
font-weight: 300;
|
||||
letter-spacing: 1px;
|
||||
margin-bottom: 12px;
|
||||
margin-bottom: 8px;
|
||||
color: var(--text-primary);
|
||||
}
|
||||
|
||||
.welcome p {
|
||||
.welcome-subtitle {
|
||||
font-size: 14px;
|
||||
color: var(--text-secondary);
|
||||
letter-spacing: 0.5px;
|
||||
margin-bottom: 40px;
|
||||
}
|
||||
|
||||
.guide-section {
|
||||
width: 100%;
|
||||
max-width: 700px;
|
||||
margin-bottom: 24px;
|
||||
}
|
||||
|
||||
.example-queries {
|
||||
display: flex;
|
||||
flex-wrap: wrap;
|
||||
gap: 10px;
|
||||
justify-content: center;
|
||||
}
|
||||
|
||||
.example-btn {
|
||||
padding: 10px 16px;
|
||||
background: rgba(255, 255, 255, 0.03);
|
||||
border: 1px solid rgba(255, 255, 255, 0.1);
|
||||
border-radius: 6px;
|
||||
color: var(--text-secondary);
|
||||
font-size: 13px;
|
||||
cursor: pointer;
|
||||
transition: all 0.2s ease;
|
||||
}
|
||||
|
||||
.example-btn:hover {
|
||||
background: rgba(255, 255, 255, 0.05);
|
||||
border-color: var(--accent);
|
||||
color: var(--accent);
|
||||
transform: translateY(-1px);
|
||||
}
|
||||
|
||||
.welcome-footer {
|
||||
margin-top: 20px;
|
||||
}
|
||||
|
||||
.welcome-footer p {
|
||||
font-size: 13px;
|
||||
color: var(--text-secondary);
|
||||
letter-spacing: 0.5px;
|
||||
}
|
||||
|
||||
/* Messages */
|
||||
|
||||
@ -53,12 +53,27 @@
|
||||
<!-- Welcome Screen -->
|
||||
<div v-if="messages.length === 0" class="welcome">
|
||||
<div class="welcome-icon">
|
||||
<svg width="80" height="80" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="1">
|
||||
<svg width="60" height="60" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="1">
|
||||
<path d="M21 15a2 2 0 0 1-2 2H7l-4 4V5a2 2 0 0 1 2-2h14a2 2 0 0 1 2 2z"/>
|
||||
</svg>
|
||||
</div>
|
||||
<h1>开始对话</h1>
|
||||
<p>输入股票代码或名称，获取实时分析</p>
|
||||
<h1>AI 金融智能体</h1>
|
||||
<p class="welcome-subtitle">支持 A股 + 美股双市场分析</p>
|
||||
|
||||
<div class="guide-section">
|
||||
<div class="example-queries">
|
||||
<button class="example-btn" @click="sendExample('分析贵州茅台')">分析贵州茅台</button>
|
||||
<button class="example-btn" @click="sendExample('比亚迪怎么样')">比亚迪怎么样</button>
|
||||
<button class="example-btn" @click="sendExample('上证指数走势')">上证指数走势</button>
|
||||
<button class="example-btn" @click="sendExample('分析特斯拉')">分析特斯拉</button>
|
||||
<button class="example-btn" @click="sendExample('苹果股票')">苹果股票</button>
|
||||
<button class="example-btn" @click="sendExample('NVDA基本面')">NVDA基本面</button>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div class="welcome-footer">
|
||||
<p>💬 输入股票名称或代码开始分析</p>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<!-- Messages -->
|
||||
@ -116,7 +131,7 @@
|
||||
<textarea
|
||||
v-model="userInput"
|
||||
@keydown.enter.exact.prevent="sendMessage"
|
||||
placeholder="输入消息..."
|
||||
placeholder="输入股票名称或代码..."
|
||||
rows="1"
|
||||
:disabled="loading"
|
||||
ref="textarea"
|
||||
|
||||
@ -94,6 +94,12 @@ createApp({
|
||||
}
|
||||
},
|
||||
|
||||
sendExample(exampleText) {
|
||||
// Set the example text to input and send
|
||||
this.userInput = exampleText;
|
||||
this.sendMessage();
|
||||
},
|
||||
|
||||
renderMarkdown(content) {
|
||||
if (!content) return '';
|
||||
|
||||
|
||||
Loading…
Reference in New Issue
Block a user