357 lines
13 KiB
Python
357 lines
13 KiB
Python
"""
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数据源管理服务
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处理数据源配置和切换逻辑
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"""
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from typing import Dict, Any, Optional, List
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import asyncio
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from datetime import datetime
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from .data_fetcher import DataFetcher, DataFetcherFactory
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from .ai_analyzer import GeminiAnalyzer, AIAnalyzerFactory
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from ..core.exceptions import (
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DataSourceError,
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ConfigurationError,
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AIAnalysisError
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)
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from ..schemas.data import (
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FinancialDataResponse,
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MarketDataResponse,
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SymbolValidationResponse,
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DataSourceStatus,
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DataSourcesStatusResponse
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)
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from ..schemas.report import AIAnalysisResponse
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class DataSourceManager:
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"""数据源管理器"""
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def __init__(self, config: Dict[str, Any]):
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self.config = config
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self._data_fetchers: Dict[str, DataFetcher] = {}
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self._ai_analyzer: Optional[GeminiAnalyzer] = None
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self._market_source_mapping = {
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"china": "tushare",
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"中国": "tushare",
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"hongkong": "yahoo",
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"香港": "yahoo",
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"usa": "yahoo",
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"美国": "yahoo",
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"japan": "yahoo",
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"日本": "yahoo"
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}
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# 初始化数据获取器
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self._initialize_data_fetchers()
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# 初始化AI分析器
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self._initialize_ai_analyzer()
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def _initialize_data_fetchers(self):
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"""初始化数据获取器"""
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data_sources_config = self.config.get("data_sources", {})
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for source_name, source_config in data_sources_config.items():
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try:
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if source_config.get("enabled", True):
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fetcher = DataFetcherFactory.create_fetcher(source_name, source_config)
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self._data_fetchers[source_name] = fetcher
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except Exception as e:
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print(f"警告: 初始化数据源 {source_name} 失败: {str(e)}")
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def _initialize_ai_analyzer(self):
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"""初始化AI分析器"""
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ai_config = self.config.get("ai_services", {})
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gemini_config = ai_config.get("gemini", {})
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if gemini_config.get("enabled", True) and gemini_config.get("api_key"):
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try:
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self._ai_analyzer = AIAnalyzerFactory.create_gemini_analyzer(
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gemini_config["api_key"],
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gemini_config
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)
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except Exception as e:
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print(f"警告: 初始化Gemini分析器失败: {str(e)}")
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def get_data_source_for_market(self, market: str) -> str:
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"""根据市场获取数据源"""
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market_lower = market.lower()
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# 首先检查配置中的映射
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market_mapping = self.config.get("market_mapping", {})
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if market_lower in market_mapping:
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return market_mapping[market_lower]
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# 使用默认映射
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return self._market_source_mapping.get(market_lower, "tushare")
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def get_data_fetcher(self, data_source: str) -> DataFetcher:
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"""获取数据获取器"""
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if data_source not in self._data_fetchers:
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raise DataSourceError(f"数据源 {data_source} 未配置或不可用", data_source)
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return self._data_fetchers[data_source]
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def get_ai_analyzer(self) -> GeminiAnalyzer:
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"""获取AI分析器"""
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if not self._ai_analyzer:
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raise AIAnalysisError("AI分析器未配置或不可用", "gemini")
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return self._ai_analyzer
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async def fetch_financial_data(self, symbol: str, market: str, preferred_source: Optional[str] = None) -> FinancialDataResponse:
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"""获取财务数据（支持数据源切换）"""
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data_source = preferred_source or self.get_data_source_for_market(market)
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try:
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fetcher = self.get_data_fetcher(data_source)
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return await fetcher.fetch_financial_data(symbol, market)
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except DataSourceError as e:
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# 尝试备用数据源
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fallback_sources = self._get_fallback_sources(data_source)
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for fallback_source in fallback_sources:
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try:
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fallback_fetcher = self.get_data_fetcher(fallback_source)
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return await fallback_fetcher.fetch_financial_data(symbol, market)
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except Exception:
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continue
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# 所有数据源都失败了
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raise e
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async def fetch_market_data(self, symbol: str, market: str, preferred_source: Optional[str] = None) -> MarketDataResponse:
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"""获取市场数据（支持数据源切换）"""
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data_source = preferred_source or self.get_data_source_for_market(market)
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try:
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fetcher = self.get_data_fetcher(data_source)
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return await fetcher.fetch_market_data(symbol, market)
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except DataSourceError as e:
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# 尝试备用数据源
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fallback_sources = self._get_fallback_sources(data_source)
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for fallback_source in fallback_sources:
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try:
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fallback_fetcher = self.get_data_fetcher(fallback_source)
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return await fallback_fetcher.fetch_market_data(symbol, market)
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except Exception:
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continue
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# 所有数据源都失败了
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raise e
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async def validate_symbol(self, symbol: str, market: str, preferred_source: Optional[str] = None) -> SymbolValidationResponse:
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"""验证证券代码（支持数据源切换）"""
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data_source = preferred_source or self.get_data_source_for_market(market)
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try:
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fetcher = self.get_data_fetcher(data_source)
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return await fetcher.validate_symbol(symbol, market)
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except DataSourceError as e:
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# 尝试备用数据源
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fallback_sources = self._get_fallback_sources(data_source)
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for fallback_source in fallback_sources:
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try:
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fallback_fetcher = self.get_data_fetcher(fallback_source)
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return await fallback_fetcher.validate_symbol(symbol, market)
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except Exception:
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continue
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# 所有数据源都失败了
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raise e
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async def analyze_with_ai(self, analysis_type: str, symbol: str, market: str, context_data: Dict[str, Any]) -> AIAnalysisResponse:
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"""使用AI进行分析"""
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analyzer = self.get_ai_analyzer()
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if analysis_type == "business_info":
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return await analyzer.analyze_business_info(symbol, market, context_data)
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elif analysis_type == "fundamental_analysis":
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business_info = context_data.get("business_info", {})
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financial_data = context_data.get("financial_data", {})
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return await analyzer.analyze_fundamental(symbol, market, financial_data, business_info)
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elif analysis_type == "bullish_analysis":
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return await analyzer.analyze_bullish_case(symbol, market, context_data)
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elif analysis_type == "bearish_analysis":
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return await analyzer.analyze_bearish_case(symbol, market, context_data)
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elif analysis_type == "market_analysis":
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return await analyzer.analyze_market_sentiment(symbol, market, context_data)
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elif analysis_type == "news_analysis":
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return await analyzer.analyze_news_catalysts(symbol, market, context_data)
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elif analysis_type == "trading_analysis":
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return await analyzer.analyze_trading_dynamics(symbol, market, context_data)
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elif analysis_type == "insider_analysis":
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return await analyzer.analyze_insider_institutional(symbol, market, context_data)
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elif analysis_type == "final_conclusion":
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all_analyses = context_data.get("all_analyses", [])
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return await analyzer.generate_final_conclusion(symbol, market, all_analyses)
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else:
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raise AIAnalysisError(f"不支持的分析类型: {analysis_type}", "gemini")
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async def check_all_sources_status(self) -> DataSourcesStatusResponse:
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"""检查所有数据源状态"""
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status_tasks = []
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# 检查数据获取器状态
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for source_name, fetcher in self._data_fetchers.items():
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status_tasks.append(fetcher.check_status())
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# 检查AI分析器状态
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if self._ai_analyzer:
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status_tasks.append(self._check_ai_analyzer_status())
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# 并发执行状态检查
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statuses = await asyncio.gather(*status_tasks, return_exceptions=True)
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source_statuses = []
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healthy_count = 0
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for i, status in enumerate(statuses):
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if isinstance(status, Exception):
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# 处理异常情况
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if i < len(self._data_fetchers):
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source_name = list(self._data_fetchers.keys())[i]
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else:
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source_name = "gemini"
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source_statuses.append(DataSourceStatus(
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name=source_name,
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is_available=False,
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last_check=datetime.now(),
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error_message=str(status)
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))
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else:
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source_statuses.append(status)
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if status.is_available:
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healthy_count += 1
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# 确定整体状态
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total_sources = len(source_statuses)
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if healthy_count == total_sources:
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overall_status = "healthy"
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elif healthy_count > 0:
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overall_status = "degraded"
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else:
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overall_status = "down"
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return DataSourcesStatusResponse(
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sources=source_statuses,
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overall_status=overall_status
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)
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async def _check_ai_analyzer_status(self) -> DataSourceStatus:
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"""检查AI分析器状态"""
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start_time = datetime.now()
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try:
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# 简单的健康检查 - 尝试生成一个很短的测试内容
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test_prompt = "请回答：1+1等于几？"
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await self._ai_analyzer._call_gemini_api(test_prompt)
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end_time = datetime.now()
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response_time = int((end_time - start_time).total_seconds() * 1000)
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return DataSourceStatus(
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name="gemini",
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is_available=True,
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last_check=end_time,
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response_time_ms=response_time
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)
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except Exception as e:
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end_time = datetime.now()
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return DataSourceStatus(
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name="gemini",
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is_available=False,
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last_check=end_time,
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error_message=str(e)
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)
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def _get_fallback_sources(self, primary_source: str) -> List[str]:
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"""获取备用数据源列表"""
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fallback_config = self.config.get("fallback_sources", {})
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if primary_source in fallback_config:
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return fallback_config[primary_source]
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# 默认备用策略
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all_sources = list(self._data_fetchers.keys())
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return [source for source in all_sources if source != primary_source]
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def update_config(self, new_config: Dict[str, Any]):
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"""更新配置"""
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self.config.update(new_config)
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# 重新初始化数据获取器
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self._data_fetchers.clear()
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self._initialize_data_fetchers()
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# 重新初始化AI分析器
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self._ai_analyzer = None
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self._initialize_ai_analyzer()
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def get_supported_sources(self) -> List[str]:
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"""获取支持的数据源列表"""
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return DataFetcherFactory.get_supported_sources()
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def get_available_sources(self) -> List[str]:
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"""获取当前可用的数据源列表"""
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return list(self._data_fetchers.keys())
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def is_ai_analyzer_available(self) -> bool:
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"""检查AI分析器是否可用"""
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return self._ai_analyzer is not None
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def create_data_source_manager(config: Dict[str, Any]) -> DataSourceManager:
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"""创建数据源管理器"""
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return DataSourceManager(config)
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# 默认配置示例
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DEFAULT_CONFIG = {
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"data_sources": {
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"tushare": {
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"enabled": True,
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"api_key": "", # 需要从环境变量或配置文件获取
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"base_url": "http://api.tushare.pro",
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"timeout": 30,
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"max_retries": 3,
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"retry_delay": 1
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},
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"yahoo": {
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"enabled": True,
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"base_url": "https://query1.finance.yahoo.com",
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"timeout": 30,
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"max_retries": 3,
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"retry_delay": 1
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}
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},
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"ai_services": {
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"gemini": {
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"enabled": True,
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"api_key": "", # 需要从环境变量或配置文件获取
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"model": "gemini-pro",
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"timeout": 60,
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"max_retries": 3,
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"retry_delay": 2,
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"temperature": 0.7,
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"max_output_tokens": 8192
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}
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},
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"market_mapping": {
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"china": "tushare",
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"中国": "tushare",
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"hongkong": "yahoo",
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"香港": "yahoo",
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"usa": "yahoo",
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"美国": "yahoo",
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"japan": "yahoo",
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"日本": "yahoo"
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},
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"fallback_sources": {
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"tushare": ["yahoo"],
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"yahoo": ["tushare"]
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}
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} |