commit;

src/app.py

@@ -241,7 +241,7 @@ def initialize_stock_price_schedule():
         scheduler.add_job(
             func=update_stock_price,
             trigger='interval',
-            minutes=5,
+            minutes=60,
             id='stock_price_update',
             name='实时股价数据采集',
             replace_existing=True
@@ -249,7 +249,7 @@ def initialize_stock_price_schedule():
         
         # 启动调度器
         scheduler.start()
-        logger.info("实时股价数据采集定时任务已初始化，将在交易时间内每5分钟执行一次")
+        logger.info("实时股价数据采集定时任务已初始化，将在交易时间内每60分钟执行一次")
         return scheduler
         
     except Exception as e:
@@ -1452,6 +1452,22 @@ def comprehensive_analysis():
                     if 'db_session2' in locals() and db_session2 is not None:  # 确保 db_session 已定义
                         db_session2.close()  # <--- 关闭会话
 
+                # 获取企业市值信息
+                market_value_results = {}
+                try:
+                    from src.valuation_analysis.stock_price_collector import StockPriceCollector
+                    price_collector = StockPriceCollector()
+                    
+                    for stock_code in input_stock_codes:
+                        price_data = price_collector.get_stock_price_data(stock_code)
+                        if price_data and 'total_market_value' in price_data:
+                            market_value_results[stock_code] = price_data['total_market_value']
+                        else:
+                            market_value_results[stock_code] = None
+                except Exception as e:
+                    logger.error(f"获取企业市值信息失败: {str(e)}")
+                    market_value_results = {}
+
                 db_session = next(get_db())
                 # 筛选出传入列表中符合条件的股票
                 for code, name in all_stocks:
@@ -1475,7 +1491,8 @@ def comprehensive_analysis():
                             "industry_space": industry_space,  # 行业发展空间（2:高速增长, 1:稳定经营, 0:不确定性大, -1:不利经营）
                             "financial_report_level": financial_report_level,  # 经营质量（2:优秀, 1:较好, 0:一般, -1:存在隐患，-2：较大隐患）
                             "pe_industry": pe_industry,  # 个股在行业的PE水平（-1:高于行业, 0:接近行业, 1:低于行业）
-                            "tracks": track_results.get(code, [])  # 添加赛道信息
+                            "tracks": track_results.get(code, []),  # 添加赛道信息
+                            "market_value": market_value_results.get(code)  # 添加企业市值信息
                         })
                 
                 logger.info(f"筛选出 {len(filtered_stocks)} 个符合条件的股票")

src/fundamentals_llm/fundamental_analysis.py

@@ -1477,6 +1477,13 @@ class FundamentalAnalyzer:
                - 长期持有：公司具备长期稳定的盈利能力、行业地位稳固、长期成长性好
                - 不建议投资：存在明显风险因素、基本面恶化、估值过高、行业前景不佳或者存在退市风险
             
+            请注意：
+            1. 请完全基于提供的分析结果中的最新数据进行分析，不要使用任何历史数据或过时信息
+            2. 如果分析结果中包含2024年或2025年的数据，请优先使用这些最新数据
+            3. 避免使用"2023年"等历史时间点的数据，除非分析结果中明确提供了这些数据
+            4. 重点关注公司最新的业务发展、财务表现和市场定位
+            5. 在分析行业环境时，请使用最新的行业数据和竞争格局信息
+            
             请提供专业、客观的分析，突出关键信息，避免冗长描述。重点关注投资价值和风险。在输出投资建议时，请明确指出是短期持有、中期持有、长期持有还是不建议投资。
             
             各维度分析结果：

src/scripts/config.py

@@ -11,7 +11,7 @@ XUEQIU_HEADERS = {
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src/valuation_analysis/financial_analysis.py

@@ -11,6 +11,7 @@ from pymongo import MongoClient
 import logging
 from typing import Dict, List, Optional, Union, Tuple
 import json
+import requests
 
 from .config import DB_URL, MONGO_CONFIG, LOG_FILE
 from .stock_price_collector import StockPriceCollector
@@ -394,6 +395,69 @@ class FinancialAnalyzer:
                 'message': f'查询失败: {str(e)}'
             }
     
+    def get_momentum_indicators(self, stock_code: str, industry_codes: List[str]) -> Dict:
+        """
+        获取动量指标数据
+        
+        Args:
+            stock_code: 目标股票代码
+            industry_codes: 行业股票代码列表
+            
+        Returns:
+            动量指标数据字典
+        """
+        try:
+            url = "http://192.168.18.42:5000/api/dify/getStockMomentumIndex"
+            payload = {
+                "code_list": industry_codes,
+                "target_code": stock_code
+            }
+            
+            response = requests.post(url, json=payload)
+            if response.status_code != 200:
+                return {
+                    'success': False,
+                    'message': f'获取动量指标失败: HTTP {response.status_code}'
+                }
+                
+            data = response.json()
+            
+            # 计算OBV和NATR的rank_score
+            obv_rank_score = round((1 - data['obv_rank'] / len(industry_codes)) * 10, 3)
+            natr_rank_score = round((1 - data['natr_rank'] / len(industry_codes)) * 10, 3)
+            
+            return {
+                'success': True,
+                'indicators': [
+                    {
+                        'key': 'obv',
+                        'desc': '能量',
+                        'value': round(data['OBV'], 3),
+                        'rank_score': obv_rank_score
+                    },
+                    {
+                        'key': 'form',
+                        'desc': f'技术形态-{data["form"]}',
+                        'value': round(data['form_probability'], 3),
+                        'rank_score': round(data['form_probability'] * 10, 3)  # 将概率转换为0-10的分数
+                    },
+                    {
+                        'key': 'natr',
+                        'desc': '阶段位置',
+                        'value': round(data['NATR'], 3),
+                        'rank_score': natr_rank_score
+                    }
+                ],
+                'avg_score': round((obv_rank_score + natr_rank_score + round(data['form_probability'] * 10, 3)) / 3, 3)
+            }
+            
+        except Exception as e:
+            logger.error(f"获取动量指标失败: {str(e)}")
+            return {
+                'success': False,
+                'message': f'获取动量指标失败: {str(e)}'
+            }
+
     def analyze_financial_data(self, stock_code: str) -> Dict:
         """
         分析财务数据
@@ -413,6 +477,12 @@ class FinancialAnalyzer:
             industry_analyzer = IndustryAnalyzer()
             concepts = industry_analyzer.get_stock_concepts(stock_code)
             
+            # 获取同行业股票列表
+            industry_stocks = self.get_industry_stocks(stock_code)
+            
+            # 获取动量指标数据
+            momentum_result = self.get_momentum_indicators(stock_code, industry_stocks)
+            
             # 获取基础财务指标
             base_result = self.extract_financial_indicators(stock_code)
             if not base_result.get('success'):
@@ -578,6 +648,7 @@ class FinancialAnalyzer:
                 'growth': growth_data,
                 'value_rating': process_indicators(value_rating_indicators),
                 'liquidity': process_indicators(liquidity_indicators),
+                'momentum': momentum_result.get('indicators', []),  # 添加动量指标数据
                 'concepts': concepts,  # 添加概念板块数据
                 'price_data': price_data  # 添加实时股价数据
             }