初始化提交：AI价值投资盯盘系统

2025-01-15 14:41:21 +08:00 · 2025-01-15 14:41:21 +08:00 · 5926fa5f46
commit 5926fa5f46
parent 7ad16b0a1b
16 changed files with 1844 additions and 555 deletions
--- a/.env.example
+++ b/.env.example
@ -0,0 +1,7 @@
+# Tushare API配置
+TUSHARE_TOKEN=your_tushare_token_here
+
+# Volces API配置
+VOLCES_MODEL_ID=your_model_id_here
+VOLCES_API_KEY=your_api_key_here
+VOLCES_BASE_URL=https://ark.cn-beijing.volces.com/api/v3 
--- a/.gitignore
+++ b/.gitignore
@ -1,3 +1,7 @@
+# 环境配置
+.env
+config.py
+
 # Python
 __pycache__/
 *.py[cod]
@ -16,14 +20,16 @@ lib64/
 parts/
 sdist/
 var/
-wheels/
 *.egg-info/
 .installed.cfg
 *.egg

-# 虚拟环境
-venv/
-ENV/
+# 项目特定文件
+stock_cache.json
+watchlist.json
+ai_stock_analysis/
+dao_analysis/
+daka_analysis/

 # IDE
 .idea/
@ -31,10 +37,6 @@ ENV/
 *.swp
 *.swo

-# 项目特定
-config.json
-*.log
-.env
+# 系统文件
 .DS_Store
-stock_cache.json
-watchlist.json 
+Thumbs.db 
--- a/README.md
+++ b/README.md
@ -1,238 +1,158 @@
-# 价值投资盯盘系统
+# AI价值投资盯盘系统

-一个专注于中国 A 股市场的智能股票分析与监控平台，基于 Python FastAPI 开发，集成实时行情监控、AI 智能分析和价值投资建议等功能，助力投资者进行理性的价值投资决策。
+一个基于Python的A股智能监控和AI分析系统，集成了多维度的投资分析功能，包括传统价值投资分析、道德经智慧分析以及知名投资大师的视角分析。

-## 功能特点
+## 系统界面预览
+![系统主界面](docs/images/main.png)

-### 1. A股实时监控
- 支持所有 A 股上市公司的实时监控
- 沪深两市实时价格和涨跌幅更新
- 自定义市值目标区间预警
- 个股交易状态实时提示
+## 🚀 核心功能

-### 2. AI 智能分析
- 基于中国市场特点的智能投资建议
- A股市场合理价格区间估算
- 结合中国经济环境的目标市值评估
- 多维度分析报告：
-  - A股市场估值分析
-  - 中国特色财务健康状况评估
-  - 行业对标成长潜力评估
-  - 系统性风险评估
+### 1. 股票监控
+- 实时股票数据监控
+- 自定义目标市值设置
+- 价格和市值预警
+- 多维度指标展示（PE、PB、ROE等）

-### 3. A股财务指标分析
- 估值指标：PE（市盈率）、PB（市净率）、PS（市销率）等
- 盈利能力：ROE（净资产收益率）、毛利率、净利率
- 成长能力：营收增长、利润增长、研发投入
- 运营效率：资产周转率、存货周转率等
- 偿债能力：资产负债率、流动比率等
- 现金流指标：经营现金流、自由现金流等
+### 2. 指数行情
+- 主要指数实时行情展示
+- K线图技术分析
+- 大盘趋势分析

-### 4. 中国市场行情
- 上证指数、深证成指、创业板指等主要指数实时行情
- 专业K线图技术分析
- A股市场涨跌分布分析
- 行业板块轮动分析
+### 3. AI智能分析
+- 基础价值投资分析
+  - 财务指标分析
+  - 估值分析
+  - 风险评估
+  - 投资建议
+- 道德经分析视角
+  - 企业道德评估
+  - 可持续发展分析
+  - 长期投资价值判断
+- 价值投资大咖分析
+  - 巴菲特视角
+  - 格雷厄姆视角
+  - 林园视角
+  - 李大霄视角
+  - 段永平视角

-### 5. 上市公司详情
- 工商登记信息
- 十大股东持股变动
- A股特色财务报表分析
- 公司公告与重大事项
- 行业地位分析
+### 4. 数据管理
+- 本地数据缓存
+- 历史数据查询
+- 分析报告导出
+- 自动数据更新

-## 技术架构
+## 🛠️ 技术栈

-### 后端技术栈
- Web框架：FastAPI
- 数据处理：Pandas
- A股数据源：Tushare API（提供专业的 A 股数据）
- 服务器：Uvicorn
- 数据存储：JSON文件
-
-### 前端技术栈
- 框架：Bootstrap 5
- 图表：ECharts
- 交互：JavaScript
- 样式：CSS3
-
-### 主要模块
-```
-项目结构
-├── app/
-│   ├── __init__.py
-│   ├── api/
-│   │   └── stock_routes.py    # API路由
-│   ├── models/
-│   │   └── stock.py          # 数据模型
-│   ├── services/
-│   │   ├── stock_service.py  # 股票服务
-│   │   └── ai_analysis_service.py  # AI分析服务
-│   ├── templates/
-│   │   ├── index.html       # 主页面
-│   │   └── market.html      # 市场页面
-│   └── config.py            # 配置文件
-├── run.py                   # 启动文件
-└── requirements.txt         # 依赖包
-```
-
-## 安装部署
-
-### 环境要求
+### 后端
 - Python 3.8+
- pip 包管理器
- 网络连接（访问 Tushare API）
+- FastAPI：高性能Web框架
+- Tushare：金融数据API
+- 豆包大模型：AI分析引擎
+- SQLite：本地数据存储

-### 安装步骤
+### 前端
+- Bootstrap 5：响应式UI框架
+- ECharts：数据可视化
+- jQuery：DOM操作
+- WebSocket：实时数据推送

-1. 克隆项目
+## 📦 安装部署
+
+### 1. 环境准备
 ```bash
-git clone https://github.com/693696817/stock-monitor.git
+# 克隆项目
+git clone https://gitee.com/your-username/stock-monitor.git
 cd stock-monitor
-```

-2. 创建虚拟环境（推荐）
-```bash
+# 创建虚拟环境
 python -m venv venv
 source venv/bin/activate  # Linux/Mac
-venv\Scripts\activate     # Windows
-```
+venv\\Scripts\\activate  # Windows

-3. 安装依赖
-```bash
+# 安装依赖
 pip install -r requirements.txt
 ```

-4. 配置
- 复制 `config.json.example` 为 `config.json`
- 在 `config.json` 中配置你的 Tushare Token
-```json
-{
-    "watchlist": {},
-    "tushare_token": "your_tushare_token_here"
-}
+### 2. API配置获取
+
+#### Tushare API
+1. 访问 [Tushare官网](https://tushare.pro/)
+2. 注册并获取Token
+3. 可选：充值获取更高级别权限
+
+#### 豆包大模型API
+1. 访问 [豆包大模型控制台](https://ark.cn-beijing.volces.com/)
+2. 注册企业账号
+3. 创建API Key和Model ID
+
+### 3. 环境配置
+1. 复制配置文件
+```bash
+cp .env.example .env
+cp config.template.py config.py
 ```

-5. 运行
+2. 修改配置文件
+```bash
+# 编辑.env文件，填入API密钥
+TUSHARE_TOKEN=your_token_here
+VOLCES_MODEL_ID=your_model_id_here
+VOLCES_API_KEY=your_api_key_here
+```
+
+### 4. 启动系统
 ```bash
 python run.py
 ```
+访问 http://localhost:8000 即可使用系统

-6. 访问
- 打开浏览器访问 `http://localhost:8000`
- 默认端口为 8000，可在 `run.py` 中修改
+## 🤝 联系作者

-## 使用指南
+如果您对系统有任何问题或建议，欢迎联系：

-### 添加监控股票
-1. 在主页面顶部输入 A 股股票代码（6位数字，如：000001）
-2. 可选择设置目标市值区间
-3. 点击"添加"按钮开始监控
+- 微信：zyj118
+- QQ：693696817
+- Email：693696817@qq.com

-### 查看股票详情
-1. 点击股票名称进入详情页
-2. 查看完整的 A 股特色财务指标
-3. 获取针对中国市场的 AI 投资建议
+## 📝 使用说明

-### 指数行情
- 实时展示沪深主要指数行情
- 提供大盘趋势分析
- 行业板块表现对比
+### 1. 添加监控股票
+1. 在主界面输入股票代码
+2. 设置目标市值范围
+3. 点击添加即可

-### 数据更新频率
- A股交易时段（9:30-11:30, 13:00-15:00）实时更新
- 盘后自动更新财务数据
- 可手动强制刷新最新数据
+### 2. 查看AI分析
+1. 点击股票行右侧的分析按钮
+2. 选择需要的分析维度（基础/道德经/大咖）
+3. 等待AI分析结果

-## 开发指南
+### 3. 指数行情查看
+1. 点击顶部导航栏的"指数行情"
+2. 查看实时指数数据和K线图

-### 代码规范
- 遵循 PEP 8 编码规范
- 使用类型注解
- 保持代码简洁清晰
+## ⚠️ 注意事项

-### 目录结构说明
- `api/`: API路由和接口定义
- `models/`: 数据模型和结构定义
- `services/`: 业务逻辑和服务实现
- `templates/`: 前端页面模板
+1. API使用限制
+   - Tushare免费账号有调用频率限制
+   - 豆包大模型API有Token限制

-### 扩展开发
-1. 添加新的数据源
-   - 在 `services` 中添加新的服务类
-   - 实现数据获取和处理方法
+2. 数据时效性
+   - 行情数据实时更新
+   - AI分析结果默认缓存1小时

-2. 扩展AI分析
-   - 修改 `ai_analysis_service.py`
-   - 添加新的分析维度和方法
+3. 系统性能
+   - 建议监控股票数量不超过30只
+   - 定时刷新间隔建议60秒以上

-3. 自定义UI
-   - 修改 `templates` 中的HTML文件
-   - 更新样式和交互逻辑
-
-## 维护说明
-
-### 数据更新
- A股交易时段实时行情更新
- 每日收盘后自动更新财务数据
- 定期同步公司公告信息
- 可配置更新频率
-
-### 错误处理
- 完善的错误提示
- 异常捕获和处理
- 日志记录
-
-## 贡献指南
-
-欢迎提交 Issue 和 Pull Request：
-1. Fork 本仓库
-2. 创建特性分支
-3. 提交变更
-4. 发起 Pull Request
-
-## 许可证
+## 📄 许可证

 MIT License

-## 联系方式
+## 🤝 贡献指南

- 作者：ZYJ
- 邮箱：693696817@qq.com
+1. Fork 本仓库
+2. 新建 feature_xxx 分支
+3. 提交代码
+4. 新建 Pull Request

-## 更新日志
-
-### v1.0.0 (2024-03)
- 支持全部 A 股上市公司监控
- 实现核心功能：实时行情、AI 分析、财务分析
- 完成基础框架搭建
- 优化 A 股特色分析逻辑 
-
-## 配置说明
-
-在运行系统之前，需要配置以下API密钥：
-
-1. **Tushare API Token**
-   - 访问 [Tushare官网](https://tushare.pro/)
-   - 注册并登录账号
-   - 在个人中心获取Token
-   - 将Token填入 `config.json` 的 `tushare_token` 字段
-
-2. **豆包大模型 API Key**
-   - 访问 [豆包大模型](https://www.doubao.com/)
-   - 注册并登录账号
-   - 在控制台获取API Key和模型ID
-   - 将API Key填入 `config.json` 的 `ai_api_key` 字段
-   - 将模型ID填入 `config.json` 的 `ai_model_id` 字段
-
-配置文件示例 (`config.json`):
-```json
-{
-    "watchlist": {},
-    "tushare_token": "your_tushare_token_here",
-    "ai_api_key": "your_ai_api_key_here",
-    "ai_model_id": "your_ai_model_id_here"
-}
-```
-
-注意：请妥善保管你的API密钥，不要将其提交到代码仓库中。 
+欢迎提交Issue和Pull Request！ 
--- a/app/init.py
+++ b/app/init.py
@ -11,7 +11,7 @@ Config.ensure_directories()
 app = FastAPI()

 # 设置tushare token
-ts.set_token(Config.get_tushare_token())
+ts.set_token(Config.TUSHARE_TOKEN)
 pro = ts.pro_api()

 # Mount static files
--- a/app/api/stock_routes.py
+++ b/app/api/stock_routes.py
@ -68,7 +68,7 @@ async def get_value_analysis(stock_code: str):
    return stock_service.get_value_analysis_data(stock_code)

@router.get("/api/ai_analysis/{stock_code}")
-async def get_ai_analysis(stock_code: str):
+async def get_ai_analysis(stock_code: str, force_refresh: bool = False):
    """获取AI价值投资分析结果"""
    try:
        # 首先获取价值分析数据
@ -77,6 +77,47 @@ async def get_ai_analysis(stock_code: str):
            return analysis_data
            
        # 使用AI服务进行分析
-        return ai_service.analyze_value_investment(analysis_data)
+        return ai_service.analyze_value_investment(analysis_data, force_refresh)
    except Exception as e:
-        return {"error": f"AI分析失败: {str(e)}"} 
+        return {"error": f"AI分析失败: {str(e)}"}
+
+@router.post("/api/update_target")
+async def update_target(
+    stock_code: str = Form(...),
+    target_market_value_min: Optional[float] = Form(None),
+    target_market_value_max: Optional[float] = Form(None)
+):
+    """更新股票的目标市值"""
+    return stock_service.update_target(stock_code, target_market_value_min, target_market_value_max)
+
+@router.get("/api/tao_analysis/{stock_code}")
+async def get_tao_analysis(stock_code: str):
+    """获取基于道德经的公司分析"""
+    try:
+        # 首先获取公司详细信息
+        company_info = stock_service.get_company_detail(stock_code)
+        if "error" in company_info:
+            return company_info
+            
+        # 使用AI服务进行道德经分析
+        return ai_service.analyze_tao_philosophy(company_info)
+    except Exception as e:
+        return {"error": f"道德经分析失败: {str(e)}"}
+
+@router.get("/api/master_analysis/{stock_code}")
+async def get_master_analysis(stock_code: str):
+    """获取价值投资大咖的分析结果"""
+    try:
+        # 首先获取公司详细信息和财务数据
+        company_info = stock_service.get_company_detail(stock_code)
+        if "error" in company_info:
+            return company_info
+            
+        value_analysis = stock_service.get_value_analysis_data(stock_code)
+        if "error" in value_analysis:
+            return value_analysis
+            
+        # 使用AI服务进行大咖分析
+        return ai_service.analyze_by_masters(company_info, value_analysis)
+    except Exception as e:
+        return {"error": f"价值投资大咖分析失败: {str(e)}"} 
--- a/app/config.py
+++ b/app/config.py
@ -1,11 +1,13 @@
 import os
-import json

 # 基础配置
 class Config:
    # 项目根目录
    BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
    
+    # Tushare API配置
+    TUSHARE_TOKEN = '90f8a141125e1decb952cd49032b7b8409a2d7fa370745f6c9f45c96'
+    
    # 配置文件路径
    CONFIG_FILE = os.path.join(BASE_DIR, "config.json")
    
@ -15,29 +17,6 @@ class Config:
    # 静态文件目录
    STATIC_DIR = os.path.join(BASE_DIR, "app", "static")
    
-    # API配置
-    @classmethod
-    def load_config(cls):
-        if os.path.exists(cls.CONFIG_FILE):
-            with open(cls.CONFIG_FILE, 'r', encoding='utf-8') as f:
-                return json.load(f)
-        return {"watchlist": {}}
-    
-    @classmethod
-    def get_tushare_token(cls):
-        config = cls.load_config()
-        return config.get('tushare_token')
-    
-    @classmethod
-    def get_ai_api_key(cls):
-        config = cls.load_config()
-        return config.get('ai_api_key')
-    
-    @classmethod
-    def get_ai_model_id(cls):
-        config = cls.load_config()
-        return config.get('ai_model_id')
-    
    # 确保目录存在
    @classmethod
    def ensure_directories(cls):
--- a/app/services/ai_analysis_service.py
+++ b/app/services/ai_analysis_service.py
@ -1,24 +1,115 @@
 import json
 import os
-import re
 from openai import OpenAI
 from app.config import Config

 class AIAnalysisService:
    def __init__(self):
-        self.model = Config.get_ai_model_id()  # 从配置获取 model ID
+        # 配置OpenAI客户端连接到Volces API
+        self.model = os.getenv('VOLCES_MODEL_ID', 'your_model_id_here')  # 从环境变量获取
        self.client = OpenAI(
-            api_key = Config.get_ai_api_key(),  # 从配置获取 API Key
-            base_url = "https://ark.cn-beijing.volces.com/api/v3"
+            api_key = os.getenv('VOLCES_API_KEY', 'your_api_key_here'),  # 从环境变量获取
+            base_url = os.getenv('VOLCES_BASE_URL', 'https://ark.cn-beijing.volces.com/api/v3')
        )
+        # 创建AI分析结果缓存目录
+        self.cache_dir = os.path.join(Config.BASE_DIR, "ai_stock_analysis")
+        self.dao_cache_dir = os.path.join(Config.BASE_DIR, "dao_analysis")
+        self.daka_cache_dir = os.path.join(Config.BASE_DIR, "daka_analysis")
        
-    def analyze_value_investment(self, analysis_data):
+        # 确保所有缓存目录存在
+        for directory in [self.cache_dir, self.dao_cache_dir, self.daka_cache_dir]:
+            if not os.path.exists(directory):
+                os.makedirs(directory)
+
+    def get_cache_path(self, stock_code: str) -> str:
+        """获取缓存文件路径"""
+        return os.path.join(self.cache_dir, f"{stock_code}.json")
+
+    def get_dao_cache_path(self, stock_code: str) -> str:
+        """获取道德经分析缓存文件路径"""
+        return os.path.join(self.dao_cache_dir, f"{stock_code}.json")
+
+    def get_daka_cache_path(self, stock_code: str) -> str:
+        """获取大咖分析缓存文件路径"""
+        return os.path.join(self.daka_cache_dir, f"{stock_code}.json")
+
+    def load_cache(self, stock_code: str):
+        """加载缓存的AI分析结果"""
+        cache_path = self.get_cache_path(stock_code)
+        if os.path.exists(cache_path):
+            try:
+                with open(cache_path, 'r', encoding='utf-8') as f:
+                    return json.load(f)
+            except Exception as e:
+                print(f"读取AI分析缓存失败: {str(e)}")
+        return None
+
+    def save_cache(self, stock_code: str, analysis_result: dict):
+        """保存AI分析结果到缓存"""
+        cache_path = self.get_cache_path(stock_code)
+        try:
+            with open(cache_path, 'w', encoding='utf-8') as f:
+                json.dump(analysis_result, f, ensure_ascii=False, indent=4)
+        except Exception as e:
+            print(f"保存AI分析缓存失败: {str(e)}")
+
+    def load_dao_cache(self, stock_code: str):
+        """加载缓存的道德经分析结果"""
+        cache_path = self.get_dao_cache_path(stock_code)
+        if os.path.exists(cache_path):
+            try:
+                with open(cache_path, 'r', encoding='utf-8') as f:
+                    return json.load(f)
+            except Exception as e:
+                print(f"读取道德经分析缓存失败: {str(e)}")
+        return None
+
+    def save_dao_cache(self, stock_code: str, analysis_result: dict):
+        """保存道德经分析结果到缓存"""
+        cache_path = self.get_dao_cache_path(stock_code)
+        try:
+            with open(cache_path, 'w', encoding='utf-8') as f:
+                json.dump(analysis_result, f, ensure_ascii=False, indent=4)
+        except Exception as e:
+            print(f"保存道德经分析缓存失败: {str(e)}")
+
+    def load_daka_cache(self, stock_code: str):
+        """加载缓存的大咖分析结果"""
+        cache_path = self.get_daka_cache_path(stock_code)
+        if os.path.exists(cache_path):
+            try:
+                with open(cache_path, 'r', encoding='utf-8') as f:
+                    return json.load(f)
+            except Exception as e:
+                print(f"读取大咖分析缓存失败: {str(e)}")
+        return None
+
+    def save_daka_cache(self, stock_code: str, analysis_result: dict):
+        """保存大咖分析结果到缓存"""
+        cache_path = self.get_daka_cache_path(stock_code)
+        try:
+            with open(cache_path, 'w', encoding='utf-8') as f:
+                json.dump(analysis_result, f, ensure_ascii=False, indent=4)
+        except Exception as e:
+            print(f"保存大咖分析缓存失败: {str(e)}")
+
+    def analyze_value_investment(self, analysis_data: dict, force_refresh: bool = False):
        """
        对股票进行价值投资分析
        :param analysis_data: 包含各项财务指标的字典
+        :param force_refresh: 是否强制刷新分析结果
        :return: AI分析结果
        """
        try:
+            stock_code = analysis_data["stock_info"]["code"]
+            
+            # 如果不是强制刷新，尝试从缓存加载
+            if not force_refresh:
+                cached_result = self.load_cache(stock_code)
+                if cached_result:
+                    print(f"从缓存加载AI分析结果: {stock_code}")
+                    return cached_result
+
            # 打印输入数据用于调试
            print(f"输入的分析数据: {json.dumps(analysis_data, ensure_ascii=False, indent=2)}")
            
@ -53,16 +144,15 @@ class AIAnalysisService:
                analysis_result = json.loads(analysis_text)
                print(f"解析后的JSON结果: {json.dumps(analysis_result, ensure_ascii=False, indent=2)}")
                
-                # 构建完整的返回结果
-                result = analysis_result
+                # 保存到缓存
+                self.save_cache(stock_code, analysis_result)
                
-                print(f"最终返回结果: {json.dumps(result, ensure_ascii=False, indent=2)}")
-                return result
+                return analysis_result
                
            except json.JSONDecodeError as e:
                print(f"JSON解析失败: {str(e)}")
                # 如果JSON解析失败，返回错误信息
-                return {
+                error_result = {
                    'stock_info': analysis_data.get('stock_info', {}),
                    'valuation': analysis_data.get('valuation', {}),
                    'profitability': analysis_data.get('profitability', {}),
@ -76,12 +166,10 @@ class AIAnalysisService:
                        "raw_text": analysis_text
                    }
                }
-            
+                return error_result
+                
        except Exception as e:
            print(f"AI分析失败: {str(e)}")
-            print(f"错误详情: {e.__class__.__name__}")
-            import traceback
-            print(f"错误堆栈: {traceback.format_exc()}")
            return {"error": f"AI分析失败: {str(e)}"}
    
    def _parse_analysis_result(self, analysis_text, current_price):
@ -285,7 +373,7 @@ class AIAnalysisService:
        analysis_requirements = """
 请基于以上数据，从价值投资的角度进行分析。请特别注意：
 1. 结合行业特点、公司竞争力、成长性等因素，给出合理的估值区间
-2. 存货周转率为0可能表示数据缺失，分析时需要谨慎对待
+2. 某些数据可能缺失或异常，分析时需要谨慎对待，或者从东财choice获取
 3. 考虑当前市场环境和行业整体估值水平

 在给出估值区间时，请充分考虑：
@ -300,10 +388,332 @@ class AIAnalysisService:
 1. investment_suggestion: 投资建议，包含summary(总体建议)、action(具体操作建议)和key_points(关注重点)
 2. analysis: 详细分析，包含估值分析、财务健康状况、成长潜力和风险评估
 3. price_analysis: 价格分析，包含合理价格区间和目标市值区间
+实例：
+    "price_analysis": {
+        "合理价格区间": [
+            xxx,
+            xxx
+        ],
+        "目标市值区间": [
+            xxx,
+            xxx
+        ]

 请确保返回的是一个有效的JSON格式，数值使用数字而不是字符串（价格、市值等），文本分析使用字符串。分析要客观、专业、详细。"""

        # 组合完整的提示词
        prompt = data_section + analysis_requirements
        
+        return prompt 
+
+    def analyze_tao_philosophy(self, company_info: dict, force_refresh: bool = False):
+        """
+        基于道德经理念分析公司
+        :param company_info: 公司信息
+        :param force_refresh: 是否强制刷新分析结果
+        :return: AI分析结果
+        """
+        try:
+            stock_code = company_info.get('basic_info', {}).get('code')
+            
+            # 如果不是强制刷新，尝试从缓存加载
+            if not force_refresh and stock_code:
+                cached_result = self.load_dao_cache(stock_code)
+                if cached_result:
+                    print(f"从缓存加载道德经分析结果: {stock_code}")
+                    return cached_result
+            
+            # 构建提示词
+            prompt = self._build_tao_analysis_prompt(company_info)
+            
+            # 调用API
+            response = self.client.chat.completions.create(
+                model=self.model,
+                messages=[
+                    {
+                        "role": "user",
+                        "content": prompt
+                    }
+                ]
+            )
+            
+            # 获取分析结果
+            analysis_text = response.choices[0].message.content
+            
+            try:
+                # 解析JSON结果
+                analysis_result = json.loads(analysis_text)
+                
+                # 保存到缓存
+                if stock_code:
+                    self.save_dao_cache(stock_code, analysis_result)
+                
+                return analysis_result
+            except json.JSONDecodeError as e:
+                print(f"道德经分析结果JSON解析失败: {str(e)}")
+                return {"error": "分析结果格式错误"}
+                
+        except Exception as e:
+            print(f"道德经分析失败: {str(e)}")
+            return {"error": f"道德经分析失败: {str(e)}"}
+    
+    def _build_tao_analysis_prompt(self, company_info: dict):
+        """
+        构建道德经分析提示词
+        """
+        basic_info = company_info.get('basic_info', {})
+        
+        prompt = f"""请作为一位精通道德经的智者，运用道德经的智慧来分析{basic_info.get('name', '')}({basic_info.get('code', '')})这家公司。
+
+公司基本信息：
+- 公司名称：{basic_info.get('name', '')}
+- 所属行业：{basic_info.get('industry', '')}
+- 主营业务：{basic_info.get('main_business', '')}
+- 经营范围：{basic_info.get('business_scope', '')}
+- 公司简介：{basic_info.get('introduction', '')}
+
+请从道德经的智慧角度，分析以下几个方面：
+
+1. 道德经视角：
+- 公司的经营理念是否符合"道法自然"的原则
+- 企业的发展是否遵循"无为而治"的智慧
+- 公司是否体现"上善若水"的品质
+- 管理方式是否符合"柔弱胜刚强"的道理
+
+2. 企业道德评估：
+- 公司对待员工、客户、供应商的态度
+- 企业的社会责任感和可持续发展理念
+- 公司的价值观和企业文化
+- 经营中的道德风险评估
+
+3. 投资建议：
+- 基于道德经智慧的投资建议
+- 长期发展潜力分析
+- 需要关注的风险点
+- 持有建议
+
+请以JSON格式返回分析结果，包含以下字段：
+1. tao_philosophy: 道德经视角的分析
+2. business_ethics: 企业道德评估
+3. investment_advice: 投资建议
+
+分析要客观、专业、深入，同时体现道德经的智慧。"""
+        
+        return prompt 
+
+    def analyze_by_masters(self, company_info: dict, value_analysis: dict, force_refresh: bool = False):
+        """
+        基于各位价值投资大咖的理念分析公司
+        :param company_info: 公司信息
+        :param value_analysis: 价值分析数据
+        :param force_refresh: 是否强制刷新分析结果
+        :return: AI分析结果
+        """
+        try:
+            stock_code = company_info.get('basic_info', {}).get('code')
+            
+            # 如果不是强制刷新，尝试从缓存加载
+            if not force_refresh and stock_code:
+                cached_result = self.load_daka_cache(stock_code)
+                if cached_result:
+                    print(f"从缓存加载大咖分析结果: {stock_code}")
+                    return cached_result
+            
+            # 打印输入数据用于调试
+            print(f"公司信息: {json.dumps(company_info, ensure_ascii=False, indent=2)}")
+            print(f"价值分析数据: {json.dumps(value_analysis, ensure_ascii=False, indent=2)}")
+            
+            # 构建提示词
+            prompt = self._build_masters_analysis_prompt(company_info, value_analysis)
+            
+            # 打印提示词用于调试
+            print(f"大咖分析提示词: {prompt}")
+            
+            # 调用API
+            response = self.client.chat.completions.create(
+                model=self.model,
+                messages=[
+                    {
+                        "role": "user",
+                        "content": prompt
+                    }
+                ]
+            )
+            
+            # 获取分析结果
+            analysis_text = response.choices[0].message.content
+            print(f"AI原始返回结果: {analysis_text}")
+            
+            try:
+                # 解析JSON结果
+                analysis_result = json.loads(analysis_text)
+                print(f"解析后的JSON结果: {json.dumps(analysis_result, ensure_ascii=False, indent=2)}")
+                
+                # 保存到缓存
+                if stock_code:
+                    self.save_daka_cache(stock_code, analysis_result)
+                
+                return analysis_result
+            except json.JSONDecodeError as e:
+                print(f"大咖分析结果JSON解析失败: {str(e)}")
+                return {"error": "分析结果格式错误"}
+                
+        except Exception as e:
+            print(f"价值投资大咖分析失败: {str(e)}")
+            return {"error": f"价值投资大咖分析失败: {str(e)}"}
+    
+    def _build_masters_analysis_prompt(self, company_info: dict, value_analysis: dict):
+        """
+        构建价值投资大咖分析提示词
+        """
+        basic_info = company_info.get('basic_info', {})
+        
+        # 从value_analysis中获取财务数据
+        valuation = value_analysis.get('valuation', {})
+        profitability = value_analysis.get('profitability', {})
+        growth = value_analysis.get('growth', {})
+        operation = value_analysis.get('operation', {})
+        solvency = value_analysis.get('solvency', {})
+        cash_flow = value_analysis.get('cash_flow', {})
+        per_share = value_analysis.get('per_share', {})
+        stock_info = value_analysis.get('stock_info', {})
+        
+        # 格式化百分比
+        def format_percent(value):
+            if value is None:
+                return '-'
+            try:
+                if isinstance(value, str):
+                    value = float(value)
+                if abs(value) <= 1:
+                    value = value * 100
+                return f"{value:.2f}%"
+            except:
+                return '-'
+            
+        # 格式化数字
+        def format_number(value):
+            if value is None:
+                return '-'
+            try:
+                if isinstance(value, str):
+                    value = float(value)
+                return f"{value:.4f}"
+            except:
+                return '-'
+        
+        prompt = f"""请分别以五位价值投资大咖的视角，分析{basic_info.get('name', '')}({basic_info.get('code', '')})这家公司。
+
+公司基本信息：
+- 公司名称：{basic_info.get('name', '')}
+- 所属行业：{basic_info.get('industry', '')}
+- 主营业务：{basic_info.get('main_business', '')}
+- 经营范围：{basic_info.get('business_scope', '')}
+- 公司简介：{basic_info.get('introduction', '')}
+- 法人代表：{basic_info.get('chairman', '')}
+- 总经理：{basic_info.get('manager', '')}
+- 注册资本：{basic_info.get('reg_capital', '')}万元
+- 员工人数：{basic_info.get('employees', '')}人
+- 成立日期：{basic_info.get('setup_date', '')}
+- 上市日期：{basic_info.get('list_date', '')}
+
+当前市场信息：
+- 当前股价：{format_number(stock_info.get('current_price'))}元
+- 总市值：{format_number(valuation.get('total_market_value'))}亿元
+- 流通市值：{format_number(valuation.get('circulating_market_value'))}亿元
+- 流通比例：{format_percent(valuation.get('circulating_ratio'))}
+- 换手率：{format_percent(stock_info.get('turnover_ratio'))}
+
+估值指标：
+- 市盈率(PE)：{format_number(valuation.get('pe_ratio'))}
+- 市净率(PB)：{format_number(valuation.get('pb_ratio'))}
+- 市销率(PS)：{format_number(valuation.get('ps_ratio'))}
+- 股息率：{format_percent(valuation.get('dividend_yield'))}
+
+盈利能力指标：
+- ROE：{format_percent(profitability.get('roe'))}
+- ROE(扣非)：{format_percent(profitability.get('deducted_roe'))}
+- ROA：{format_percent(profitability.get('roa'))}
+- 毛利率：{format_percent(profitability.get('gross_margin'))}
+- 净利率：{format_percent(profitability.get('net_margin'))}
+
+成长能力指标：
+- 净利润增长率：{format_percent(growth.get('net_profit_growth'))}
+- 扣非净利润增长率：{format_percent(growth.get('deducted_net_profit_growth'))}
+- 营业总收入增长率：{format_percent(growth.get('revenue_growth'))}
+- 营业收入增长率：{format_percent(growth.get('operating_revenue_growth'))}
+
+运营能力指标：
+- 总资产周转率：{format_number(operation.get('asset_turnover'))}
+- 存货周转率：{format_number(operation.get('inventory_turnover'))}
+- 应收账款周转率：{format_number(operation.get('receivables_turnover'))}
+- 流动资产周转率：{format_number(operation.get('current_asset_turnover'))}
+
+偿债能力指标：
+- 流动比率：{format_number(solvency.get('current_ratio'))}
+- 速动比率：{format_number(solvency.get('quick_ratio'))}
+- 资产负债率：{format_percent(solvency.get('debt_to_assets'))}
+- 产权比率：{format_number(solvency.get('equity_ratio'))}
+
+现金流指标：
+- 经营现金流/营收：{format_percent(cash_flow.get('ocf_to_revenue'))}
+- 经营现金流/经营利润：{format_percent(cash_flow.get('ocf_to_operating_profit'))}
+- 经营现金流同比增长：{format_percent(cash_flow.get('ocf_growth'))}
+
+每股指标：
+- 每股收益(EPS)：{format_number(per_share.get('eps'))}元
+- 每股收益(扣非)：{format_number(per_share.get('deducted_eps'))}元
+- 每股净资产：{format_number(per_share.get('bps'))}元
+- 每股经营现金流：{format_number(per_share.get('ocfps'))}元
+- 每股留存收益：{format_number(per_share.get('retained_eps'))}元
+- 每股现金流量：{format_number(per_share.get('cfps'))}元
+- 每股息税前利润：{format_number(per_share.get('ebit_ps'))}元
+
+请分别从以下五位投资大师的视角进行分析：
+
+1. 巴菲特视角：
+- 是否具有护城河（品牌优势、规模效应、专利技术等）
+- 管理层能力和诚信（从财务指标、现金流等反映的经营能力）
+- 业务是否容易理解（商业模式的清晰度）
+- 长期竞争优势（市场地位、核心竞争力）
+- 是否是好生意（盈利能力、现金流状况）
+- 以合理价格购买优秀企业的原则（估值分析）
+
+2. 格雷厄姆视角：
+- 安全边际分析（基于净资产、市盈率等）
+- 内在价值计算（基于盈利能力和资产价值）
+- 财务安全性（偿债能力、资产质量）
+- 是否具有投资价值（基于定量分析）
+- 基于定量分析的结论（综合财务指标评估）
+
+3. 林园视角：
+- 行业成长性（收入增长、利润增长）
+- 公司治理结构（股权结构、管理层背景）
+- 研发创新能力（技术优势、产品创新）
+- 市场竞争格局（市场份额、竞争态势）
+- 估值是否合理（相对估值和绝对估值）
+
+4. 李大霄视角：
+- 市场地位和品牌价值（行业地位、品牌影响力）
+- 行业发展趋势（产业政策、市场空间）
+- 政策影响分析（行业政策、监管环境）
+- 投资时机把握（技术面和基本面）
+- 投资建议（综合分析结论）
+
+5. 段永平视角：
+- 商业模式分析（盈利模式、竞争优势）
+- 用户价值（产品力、客户粘性）
+- 企业文化（管理理念、团队建设）
+- 长期发展潜力（成长空间、持续经营能力）
+- 是否值得长期持有（投资价值判断）
+
+请以JSON格式返回分析结果，包含以下字段：
+1. buffett_analysis: 巴菲特的分析观点
+2. graham_analysis: 格雷厄姆的分析观点
+3. lin_yuan_analysis: 林园的分析观点
+4. li_daxiao_analysis: 李大霄的分析观点
+5. duan_yongping_analysis: 段永平的分析观点
+
+分析要客观、专业、深入，并体现每位投资大师的独特投资理念。请基于上述详细的财务数据进行分析（如果指标缺失或异常，请联网获取），尤其是定量指标的解读。"""
+        
        return prompt 
--- a/app/services/stock_service.py
+++ b/app/services/stock_service.py
@ -226,6 +226,20 @@ class StockService:
        self._save_watchlist()
        return {"status": "success"}

+    def update_target(self, stock_code: str, target_market_value_min: float = None, target_market_value_max: float = None):
+        """更新股票的目标市值"""
+        if stock_code not in self.watchlist:
+            return {"error": "股票不在监控列表中"}
+            
+        self.watchlist[stock_code] = {
+            "target_market_value": {
+                "min": target_market_value_min,
+                "max": target_market_value_max
+            }
+        }
+        self._save_watchlist()
+        return {"status": "success"}
+
    def get_index_info(self):
        """获取主要指数数据"""
        try:
--- a/app/templates/index.html
+++ b/app/templates/index.html
@ -642,8 +642,13 @@
                        <!-- AI价值投资分析模块 -->
                        <div class="col-12">
                            <div class="card">
-                                <div class="card-header bg-light">
-                                    <i class="bi bi-robot"></i> AI价值投资分析
+                                <div class="card-header bg-light d-flex justify-content-between align-items-center">
+                                    <div>
+                                        <i class="bi bi-robot"></i> AI价值投资分析
+                                    </div>
+                                    <button class="btn btn-outline-primary btn-sm" onclick="refreshAIAnalysis()" id="refreshAIBtn">
+                                        <i class="bi bi-arrow-repeat"></i> 更新分析
+                                    </button>
                                </div>
                                <div class="card-body">
                                    <div id="aiAnalysisError" class="alert alert-danger d-none">
@ -785,6 +790,203 @@
        </div>
    </footer>

+    <!-- 编辑目标市值弹窗 -->
+    <div class="modal fade" id="editTargetModal" tabindex="-1" aria-hidden="true">
+        <div class="modal-dialog">
+            <div class="modal-content">
+                <div class="modal-header">
+                    <h5 class="modal-title">编辑监控目标</h5>
+                    <button type="button" class="btn-close" data-bs-dismiss="modal" aria-label="Close"></button>
+                </div>
+                <div class="modal-body">
+                    <form id="editTargetForm">
+                        <input type="hidden" id="editStockCode" name="stock_code">
+                        <div class="mb-3">
+                            <label class="form-label">目标市值区间 (亿元)</label>
+                            <div class="input-group">
+                                <input type="number" step="0.01" class="form-control" id="editTargetMin" 
+                                       name="target_market_value_min" placeholder="最小值">
+                                <span class="input-group-text">-</span>
+                                <input type="number" step="0.01" class="form-control" id="editTargetMax" 
+                                       name="target_market_value_max" placeholder="最大值">
+                            </div>
+                        </div>
+                    </form>
+                </div>
+                <div class="modal-footer">
+                    <button type="button" class="btn btn-secondary" data-bs-dismiss="modal">取消</button>
+                    <button type="button" class="btn btn-primary" onclick="updateTarget()">保存</button>
+                </div>
+            </div>
+        </div>
+    </div>
+
+    <!-- 道德经分析弹窗 -->
+    <div class="modal fade" id="taoAnalysisModal" tabindex="-1" aria-hidden="true">
+        <div class="modal-dialog modal-lg">
+            <div class="modal-content">
+                <div class="modal-header">
+                    <h5 class="modal-title">道德经分析</h5>
+                    <div class="ms-auto me-2">
+                        <button type="button" class="btn btn-outline-primary btn-sm" onclick="refreshTaoAnalysis()">
+                            <i class="bi bi-arrow-clockwise"></i> 更新分析
+                        </button>
+                    </div>
+                    <button type="button" class="btn-close" data-bs-dismiss="modal" aria-label="Close"></button>
+                </div>
+                <div class="modal-body">
+                    <div id="taoAnalysisError" class="alert alert-danger d-none">
+                        <!-- 错误信息将在这里显示 -->
+                    </div>
+                    <div id="taoAnalysisLoading" class="text-center py-4 d-none">
+                        <div class="spinner-border text-success" role="status">
+                            <span class="visually-hidden">分析中...</span>
+                        </div>
+                        <div class="mt-2 text-muted">以道德经智慧分析中，请稍候...</div>
+                    </div>
+                    <div id="taoAnalysisContent">
+                        <div class="card mb-4">
+                            <div class="card-header bg-light">
+                                <i class="bi bi-book"></i> 道德经视角
+                            </div>
+                            <div class="card-body">
+                                <div id="taoPhilosophy" class="mb-4">
+                                    <!-- 道德经哲学分析将在这里显示 -->
+                                </div>
+                            </div>
+                        </div>
+                        
+                        <div class="card mb-4">
+                            <div class="card-header bg-light">
+                                <i class="bi bi-building"></i> 企业道德评估
+                            </div>
+                            <div class="card-body">
+                                <div id="businessEthics" class="mb-4">
+                                    <!-- 企业道德评估将在这里显示 -->
+                                </div>
+                            </div>
+                        </div>
+                        
+                        <div class="card">
+                            <div class="card-header bg-light">
+                                <i class="bi bi-lightbulb"></i> 投资建议
+                            </div>
+                            <div class="card-body">
+                                <div id="taoAdvice">
+                                    <!-- 基于道德经的投资建议将在这里显示 -->
+                                </div>
+                            </div>
+                        </div>
+                    </div>
+                </div>
+            </div>
+        </div>
+    </div>
+
+    <!-- 价值投资大咖分析弹窗 -->
+    <div class="modal fade" id="masterAnalysisModal" tabindex="-1" aria-hidden="true">
+        <div class="modal-dialog modal-lg">
+            <div class="modal-content">
+                <div class="modal-header">
+                    <h5 class="modal-title">价值投资大咖分析</h5>
+                    <div class="ms-auto me-2">
+                        <button type="button" class="btn btn-outline-primary btn-sm" onclick="refreshMasterAnalysis()">
+                            <i class="bi bi-arrow-clockwise"></i> 更新分析
+                        </button>
+                    </div>
+                    <button type="button" class="btn-close" data-bs-dismiss="modal" aria-label="Close"></button>
+                </div>
+                <div class="modal-body">
+                    <div id="masterAnalysisError" class="alert alert-danger d-none">
+                        <!-- 错误信息将在这里显示 -->
+                    </div>
+                    <div id="masterAnalysisLoading" class="text-center py-4 d-none">
+                        <div class="spinner-border text-warning" role="status">
+                            <span class="visually-hidden">分析中...</span>
+                        </div>
+                        <div class="mt-2 text-muted">大咖们正在分析，请稍候...</div>
+                    </div>
+                    <div id="masterAnalysisContent">
+                        <!-- 巴菲特分析 -->
+                        <div class="card mb-4">
+                            <div class="card-header bg-light d-flex align-items-center">
+                                <img src="https://upload.wikimedia.org/wikipedia/commons/thumb/5/51/Warren_Buffett_KU_Visit.jpg/120px-Warren_Buffett_KU_Visit.jpg" 
+                                     class="rounded-circle me-2" style="width: 30px; height: 30px; object-fit: cover;"
+                                     alt="Warren Buffett">
+                                <span>巴菲特视角</span>
+                            </div>
+                            <div class="card-body">
+                                <div id="buffettAnalysis" class="mb-4">
+                                    <!-- 巴菲特分析将在这里显示 -->
+                                </div>
+                            </div>
+                        </div>
+                        
+                        <!-- 格雷厄姆分析 -->
+                        <div class="card mb-4">
+                            <div class="card-header bg-light d-flex align-items-center">
+                                <img src="https://upload.wikimedia.org/wikipedia/en/thumb/5/5e/Benjamin_Graham.jpg/120px-Benjamin_Graham.jpg" 
+                                     class="rounded-circle me-2" style="width: 30px; height: 30px; object-fit: cover;"
+                                     alt="Benjamin Graham">
+                                <span>格雷厄姆视角</span>
+                            </div>
+                            <div class="card-body">
+                                <div id="grahamAnalysis" class="mb-4">
+                                    <!-- 格雷厄姆分析将在这里显示 -->
+                                </div>
+                            </div>
+                        </div>
+                        
+                        <!-- 林园分析 -->
+                        <div class="card mb-4">
+                            <div class="card-header bg-light d-flex align-items-center">
+                                <img src="https://pic3.zhimg.com/v2-f6a12dbc2d5f6e7f9c4f2e4e5c9c9c9c_720w.jpg" 
+                                     class="rounded-circle me-2" style="width: 30px; height: 30px; object-fit: cover;"
+                                     alt="林园">
+                                <span>林园视角</span>
+                            </div>
+                            <div class="card-body">
+                                <div id="linYuanAnalysis" class="mb-4">
+                                    <!-- 林园分析将在这里显示 -->
+                                </div>
+                            </div>
+                        </div>
+                        
+                        <!-- 李大霄分析 -->
+                        <div class="card mb-4">
+                            <div class="card-header bg-light d-flex align-items-center">
+                                <img src="https://img.gelonghui.com/apply/column/20200410/column_20200410112754895_31795.jpg" 
+                                     class="rounded-circle me-2" style="width: 30px; height: 30px; object-fit: cover;"
+                                     alt="李大霄">
+                                <span>李大霄视角</span>
+                            </div>
+                            <div class="card-body">
+                                <div id="liDaxiaoAnalysis" class="mb-4">
+                                    <!-- 李大霄分析将在这里显示 -->
+                                </div>
+                            </div>
+                        </div>
+                        
+                        <!-- 段永平分析 -->
+                        <div class="card">
+                            <div class="card-header bg-light d-flex align-items-center">
+                                <img src="https://img.caixin.com/2011-05-17/1305626275743167_840_560.jpg" 
+                                     class="rounded-circle me-2" style="width: 30px; height: 30px; object-fit: cover;"
+                                     alt="段永平">
+                                <span>段永平视角</span>
+                            </div>
+                            <div class="card-body">
+                                <div id="duanYongpingAnalysis">
+                                    <!-- 段永平分析将在这里显示 -->
+                                </div>
+                            </div>
+                        </div>
+                    </div>
+                </div>
+            </div>
+        </div>
+    </div>
+
    <script src="https://cdn.jsdelivr.net/npm/bootstrap@5.1.3/dist/js/bootstrap.bundle.min.js"></script>
    <script src="https://cdn.jsdelivr.net/npm/echarts@5.4.3/dist/echarts.min.js"></script>
    <script>
@ -793,6 +995,42 @@
        let stockData = [];
        let loadingStocks = new Set();

+        // 显示编辑目标市值弹窗
+        function showEditTargetModal(btn) {
+            const stockCode = btn.dataset.stockCode;
+            const targetMin = btn.dataset.targetMin;
+            const targetMax = btn.dataset.targetMax;
+            
+            document.getElementById('editStockCode').value = stockCode;
+            document.getElementById('editTargetMin').value = targetMin;
+            document.getElementById('editTargetMax').value = targetMax;
+            
+            new bootstrap.Modal(document.getElementById('editTargetModal')).show();
+        }
+
+        // 更新监控目标
+        async function updateTarget() {
+            const form = document.getElementById('editTargetForm');
+            const formData = new FormData(form);
+            
+            try {
+                const response = await fetch('/api/update_target', {
+                    method: 'POST',
+                    body: formData
+                });
+                
+                if (!response.ok) {
+                    throw new Error(await response.text() || '更新失败');
+                }
+                
+                bootstrap.Modal.getInstance(document.getElementById('editTargetModal')).hide();
+                await refreshWatchlist(true);
+            } catch (error) {
+                console.error('更新目标失败：', error);
+                alert('更新目标失败：' + error.message);
+            }
+        }
+
        // 添加排序功能
        document.querySelectorAll('.sortable').forEach(header => {
            header.addEventListener('click', () => {
@ -910,9 +1148,12 @@
        function renderStockList(data) {
            const stockTableBody = document.getElementById('stockTableBody');
            if (!stockTableBody) return;
+            
+            // 清空现有内容
            stockTableBody.innerHTML = '';
            
-            if (!data || data.length === 0) {
+            // 检查数据是否为空
+            if (!data || !Array.isArray(data) || data.length === 0) {
                const emptyRow = document.createElement('tr');
                emptyRow.innerHTML = '<td colspan="18" class="text-center text-muted py-4">暂无监控的股票</td>';
                stockTableBody.appendChild(emptyRow);
@ -921,14 +1162,15 @@
            }

            // 排序数据
+            let sortedData = [...data];
            if (currentSortField) {
-                data.sort((a, b) => {
+                sortedData.sort((a, b) => {
                    let aValue = parseFloat(a.stock_info[currentSortField]);
                    let bValue = parseFloat(b.stock_info[currentSortField]);
                    
                    // 处理无效值
-                    if (aValue === null || aValue === undefined || isNaN(aValue)) aValue = -Infinity;
-                    if (bValue === null || bValue === undefined || isNaN(bValue)) bValue = -Infinity;
+                    if (isNaN(aValue)) aValue = -Infinity;
+                    if (isNaN(bValue)) bValue = -Infinity;
                    
                    // 数值比较
                    const comparison = aValue - bValue;
@ -936,8 +1178,11 @@
                });
            }
            
-            data.forEach(item => {
+            // 渲染每一行
+            sortedData.forEach(item => {
                const { stock_info, targets } = item;
+                if (!stock_info) return;  // 跳过无效数据
+                
                const row = document.createElement('tr');
                row.setAttribute('data-stock-code', stock_info.code);
                
@ -951,10 +1196,29 @@
                        <a href="javascript:void(0)" onclick="showCompanyDetail('${stock_info.code}')" class="text-primary">
                            ${stock_info.name || '-'}
                        </a>
+                        <button class="btn btn-link btn-sm p-0 ms-2 text-danger" 
+                                onclick="showTaoAnalysis('${stock_info.code}')"
+                                title="道德经分析">
+                            <i class="bi bi-yin-yang"></i>
+                        </button>
+                        <button class="btn btn-link btn-sm p-0 ms-2 text-dark" 
+                                onclick="showMasterAnalysis('${stock_info.code}')"
+                                title="价值投资大咖分析">
+                            <i class="bi bi-person-fill"></i>
+                        </button>
                    </td>
                    <td>${formatNumber(stock_info.price)}</td>
                    <td>${formatPercent(stock_info.change_percent)}</td>
-                    <td>${formatTargetRange(targets.target_market_value)}</td>
+                    <td>${formatTargetRange(targets.target_market_value)}
+                        <button class="btn btn-link btn-sm p-0 ms-2 text-primary edit-target-btn" 
+                                data-stock-code="${stock_info.code}"
+                                data-target-min="${targets.target_market_value?.min || ''}"
+                                data-target-max="${targets.target_market_value?.max || ''}"
+                                onclick="showEditTargetModal(this)"
+                                title="编辑目标市值">
+                            <i class="bi bi-pencil"></i>
+                        </button>
+                    </td>
                    <td>${formatNumber(stock_info.market_value, true)}</td>
                    <td>${formatNumber(stock_info.pe_ratio, true)}</td>
                    <td>${formatNumber(stock_info.pb_ratio, true)}</td>
@ -981,47 +1245,6 @@
            document.getElementById('stockCount').textContent = data.length;
        }

-        // 更新单个股票数据
-        function updateStockData(stockData) {
-            const row = document.querySelector(`tr[data-stock-code="${stockData.stock_info.code}"]`);
-            if (!row) return;
-            
-            const { stock_info, targets } = stockData;
-            
-            // 检查市值状态
-            const marketValueStatus = checkMarketValueStatus(stock_info.market_value, targets.target_market_value);
-            const marketValueIcon = getMarketValueIcon(marketValueStatus);
-            
-            row.innerHTML = `
-                <td>${stock_info.code}${marketValueIcon}</td>
-                <td>
-                    <a href="javascript:void(0)" onclick="showCompanyDetail('${stock_info.code}')" class="text-primary">
-                        ${stock_info.name || '-'}
-                    </a>
-                </td>
-                <td>${formatNumber(stock_info.price)}</td>
-                <td>${formatPercent(stock_info.change_percent)}</td>
-                <td>${formatTargetRange(stockData.targets.target_market_value)}</td>
-                <td>${formatNumber(stock_info.market_value, true)}</td>
-                <td>${formatNumber(stock_info.pe_ratio, true)}</td>
-                <td>${formatNumber(stock_info.pb_ratio, true)}</td>
-                <td>${formatNumber(stock_info.ps_ratio, true)}</td>
-                <td>${formatPercent(stock_info.dividend_yield)}</td>
-                <td>${formatPercent(stock_info.roe)}</td>
-                <td>${formatPercent(stock_info.gross_profit_margin)}</td>
-                <td>${formatPercent(stock_info.net_profit_margin)}</td>
-                <td>${formatPercent(stock_info.debt_to_assets, false, true)}</td>
-                <td>${formatPercent(stock_info.net_profit_yoy)}</td>
-                <td>${formatNumber(stock_info.bps, true)}</td>
-                <td>${formatNumber(stock_info.ocfps)}</td>
-                <td>
-                    <button class="btn btn-sm btn-danger remove-btn" data-stock-code="${stock_info.code}">
-                        <i class="bi bi-trash"></i>
-                    </button>
-                </td>
-            `;
-        }
-
        // 刷新监控列表
        async function refreshWatchlist(forceRefresh = false) {
            try {
@ -1029,32 +1252,72 @@
                if (!response.ok) throw new Error('获取监控列表失败');
                
                const data = await response.json();
+                if (!Array.isArray(data)) {
+                    throw new Error('返回数据格式错误');
+                }
+                
                stockData = data;  // 更新全局数据
                renderStockList(data);
                
                // 异步加载每个股票的详细数据
                data.forEach(item => {
-                    loadStockData(item.stock_info.code, forceRefresh);
+                    if (item && item.stock_info && item.stock_info.code) {
+                        loadStockData(item.stock_info.code, forceRefresh);
+                    }
                });
            } catch (error) {
                console.error('刷新数据失败：', error);
-                alert('刷新数据失败：' + error.message);
+                // 显示错误信息
+                const stockTableBody = document.getElementById('stockTableBody');
+                if (stockTableBody) {
+                    stockTableBody.innerHTML = `
+                        <tr>
+                            <td colspan="18" class="text-center text-danger">
+                                <i class="bi bi-exclamation-triangle"></i> 
+                                加载数据失败：${error.message}
+                            </td>
+                        </tr>
+                    `;
+                }
            }
        }

-        // 异步加载股票数据
+        // 更新单个股票数据
        async function loadStockData(stockCode, forceRefresh = false) {
+            if (!stockCode || loadingStocks.has(stockCode)) return;
+            
            try {
+                loadingStocks.add(stockCode);
                const url = `/api/stock_info/${stockCode}${forceRefresh ? '?force_refresh=true' : ''}`;
                const response = await fetch(url);
-                if (!response.ok) throw new Error('获取股票数据失败');
+                
+                if (!response.ok) {
+                    throw new Error('获取股票数据失败');
+                }
                
                const data = await response.json();
-                if (data.error) throw new Error(data.error);
+                if (data.error) {
+                    throw new Error(data.error);
+                }
                
-                updateStockData(data);
+                // 更新全局数据中的股票信息
+                const index = stockData.findIndex(item => item.stock_info.code === stockCode);
+                if (index !== -1) {
+                    stockData[index] = data;
+                    renderStockList(stockData);
+                }
            } catch (error) {
                console.error(`加载股票 ${stockCode} 数据失败:`, error);
+                // 在界面上显示错误状态
+                const row = document.querySelector(`tr[data-stock-code="${stockCode}"]`);
+                if (row) {
+                    const cells = row.getElementsByTagName('td');
+                    for (let i = 2; i < cells.length - 1; i++) {
+                        cells[i].innerHTML = '<span class="text-danger">加载失败</span>';
+                    }
+                }
+            } finally {
+                loadingStocks.delete(stockCode);
            }
        }

@ -1116,6 +1379,12 @@
                    removeStock(stockCode);
                }
            });
+            
+            // 移除DataTable初始化代码，因为我们使用原生表格排序
+            
+            // 初始化指数数据
+            refreshIndexData();
+            setInterval(refreshIndexData, 60000); // 每分钟更新一次
        });

        // 获取指数数据
@ -1217,6 +1486,7 @@
        // 显示公司详情弹窗
        async function showCompanyDetail(stockCode) {
            const modal = new bootstrap.Modal(document.getElementById('companyModal'));
+            document.getElementById('companyModal').setAttribute('data-stock-code', stockCode);
            modal.show();
            
            // 显示加载状态
@ -1509,6 +1779,235 @@
                zeroRecords: "暂无数据"
            }
        });
+
+        // 刷新AI分析
+        async function refreshAIAnalysis() {
+            const stockCode = document.querySelector('#companyModal').getAttribute('data-stock-code');
+            if (!stockCode) return;
+            
+            const refreshBtn = document.getElementById('refreshAIBtn');
+            const originalText = refreshBtn.innerHTML;
+            refreshBtn.innerHTML = '<i class="bi bi-arrow-repeat"></i> 分析中...';
+            refreshBtn.disabled = true;
+            
+            try {
+                const response = await fetch(`/api/ai_analysis/${stockCode}?force_refresh=true`);
+                if (!response.ok) {
+                    throw new Error(await response.text() || '更新失败');
+                }
+                
+                const result = await response.json();
+                if (result.error) {
+                    throw new Error(result.error);
+                }
+                
+                // 更新AI分析显示
+                document.getElementById('investmentSuggestion').innerHTML = `
+                    <div class="mb-2"><strong>总体建议：</strong>${result.investment_suggestion.summary || '-'}</div>
+                    <div class="mb-2"><strong>建议操作：</strong>${result.investment_suggestion.action || '-'}</div>
+                    <div><strong>关注重点：</strong>
+                        <p class="mb-0">${result.investment_suggestion.key_points || '-'}</p>
+                    </div>
+                `;
+                
+                const priceRange = result.price_analysis?.合理价格区间 || [];
+                document.getElementById('reasonablePriceRange').innerHTML = `
+                    <div class="mb-2">${priceRange[0] || '-'} - ${priceRange[1] || '-'} 元</div>
+                `;
+                
+                const marketValue = result.price_analysis?.目标市值区间 || [];
+                document.getElementById('targetMarketValue').innerHTML = `
+                    <div class="mb-2">${marketValue[0] || '-'} - ${marketValue[1] || '-'} 亿元</div>
+                `;
+                
+                document.getElementById('valuationAnalysis').innerHTML = `
+                    <div class="mb-2">${result.analysis?.估值分析 || '-'}</div>
+                `;
+                
+                document.getElementById('financialHealth').innerHTML = `
+                    <div>${result.analysis?.财务健康状况 || '-'}</div>
+                `;
+                
+                document.getElementById('growthPotential').innerHTML = `
+                    <div>${result.analysis?.成长潜力 || '-'}</div>
+                `;
+                
+                document.getElementById('riskAssessment').innerHTML = `
+                    <div>${result.analysis?.风险评估 || '-'}</div>
+                `;
+                
+            } catch (error) {
+                console.error('更新AI分析失败：', error);
+                alert('更新AI分析失败：' + error.message);
+            } finally {
+                refreshBtn.innerHTML = originalText;
+                refreshBtn.disabled = false;
+            }
+        }
+
+        // 显示道德经分析弹窗
+        async function showTaoAnalysis(stockCode) {
+            const modal = new bootstrap.Modal(document.getElementById('taoAnalysisModal'));
+            document.getElementById('taoAnalysisModal').setAttribute('data-stock-code', stockCode);
+            modal.show();
+            
+            // 显示加载状态
+            document.getElementById('taoAnalysisError').classList.add('d-none');
+            document.getElementById('taoAnalysisLoading').classList.remove('d-none');
+            document.getElementById('taoAnalysisContent').classList.add('d-none');
+            
+            try {
+                // 获取道德经分析数据
+                const response = await fetch(`/api/tao_analysis/${stockCode}`);
+                const data = await response.json();
+                
+                if (data.error) {
+                    document.getElementById('taoAnalysisError').textContent = data.error;
+                    document.getElementById('taoAnalysisError').classList.remove('d-none');
+                    document.getElementById('taoAnalysisLoading').classList.add('d-none');
+                    return;
+                }
+                
+                // 更新道德经分析显示
+                const formatContent = (content) => {
+                    if (typeof content === 'string') {
+                        return content.replace(/\n/g, '<br>');
+                    } else if (content && typeof content === 'object') {
+                        return JSON.stringify(content, null, 2).replace(/\n/g, '<br>');
+                    }
+                    return String(content || '-');
+                };
+
+                document.getElementById('taoPhilosophy').innerHTML = formatContent(data.tao_philosophy);
+                document.getElementById('businessEthics').innerHTML = formatContent(data.business_ethics);
+                document.getElementById('taoAdvice').innerHTML = formatContent(data.investment_advice);
+                
+                document.getElementById('taoAnalysisLoading').classList.add('d-none');
+                document.getElementById('taoAnalysisContent').classList.remove('d-none');
+            } catch (error) {
+                console.error('获取道德经分析失败:', error);
+                document.getElementById('taoAnalysisError').textContent = error.message || '获取道德经分析失败，请稍后重试';
+                document.getElementById('taoAnalysisError').classList.remove('d-none');
+                document.getElementById('taoAnalysisLoading').classList.add('d-none');
+                document.getElementById('taoAnalysisContent').classList.add('d-none');
+            }
+        }
+
+        // 显示价值投资大咖分析弹窗
+        async function showMasterAnalysis(stockCode) {
+            const modal = new bootstrap.Modal(document.getElementById('masterAnalysisModal'));
+            document.getElementById('masterAnalysisModal').setAttribute('data-stock-code', stockCode);
+            modal.show();
+            
+            // 显示加载状态
+            document.getElementById('masterAnalysisError').classList.add('d-none');
+            document.getElementById('masterAnalysisLoading').classList.remove('d-none');
+            document.getElementById('masterAnalysisContent').classList.add('d-none');
+            
+            try {
+                // 获取价值投资大咖分析数据
+                const response = await fetch(`/api/master_analysis/${stockCode}`);
+                const data = await response.json();
+                
+                if (data.error) {
+                    document.getElementById('masterAnalysisError').textContent = data.error;
+                    document.getElementById('masterAnalysisError').classList.remove('d-none');
+                    document.getElementById('masterAnalysisLoading').classList.add('d-none');
+                    return;
+                }
+                
+                // 更新各个大咖的分析显示
+                const formatContent = (content) => {
+                    if (typeof content === 'string') {
+                        return content.replace(/\n/g, '<br>');
+                    } else if (content && typeof content === 'object') {
+                        return JSON.stringify(content, null, 2).replace(/\n/g, '<br>');
+                    }
+                    return String(content || '-');
+                };
+
+                document.getElementById('buffettAnalysis').innerHTML = formatContent(data.buffett_analysis);
+                document.getElementById('grahamAnalysis').innerHTML = formatContent(data.graham_analysis);
+                document.getElementById('linYuanAnalysis').innerHTML = formatContent(data.lin_yuan_analysis);
+                document.getElementById('liDaxiaoAnalysis').innerHTML = formatContent(data.li_daxiao_analysis);
+                document.getElementById('duanYongpingAnalysis').innerHTML = formatContent(data.duan_yongping_analysis);
+                
+                document.getElementById('masterAnalysisLoading').classList.add('d-none');
+                document.getElementById('masterAnalysisContent').classList.remove('d-none');
+            } catch (error) {
+                console.error('获取价值投资大咖分析失败:', error);
+                document.getElementById('masterAnalysisError').textContent = error.message || '获取价值投资大咖分析失败，请稍后重试';
+                document.getElementById('masterAnalysisError').classList.remove('d-none');
+                document.getElementById('masterAnalysisLoading').classList.add('d-none');
+                document.getElementById('masterAnalysisContent').classList.add('d-none');
+            }
+        }
+
+        async function refreshTaoAnalysis() {
+            const stockCode = document.querySelector('#taoAnalysisModal').getAttribute('data-stock-code');
+            if (!stockCode) return;
+            
+            // 显示加载状态
+            document.querySelector('#taoAnalysisLoading').classList.remove('d-none');
+            document.querySelector('#taoAnalysisContent').classList.add('d-none');
+            document.querySelector('#taoAnalysisError').classList.add('d-none');
+            
+            try {
+                const response = await fetch(`/api/tao_analysis/${stockCode}?force_refresh=true`);
+                const data = await response.json();
+                
+                if (data.error) {
+                    throw new Error(data.error);
+                }
+                
+                // 更新内容
+                document.querySelector('#taoPhilosophy').innerHTML = formatContent(data.tao_philosophy);
+                document.querySelector('#businessEthics').innerHTML = formatContent(data.business_ethics);
+                document.querySelector('#investmentAdvice').innerHTML = formatContent(data.investment_advice);
+                
+                // 显示内容
+                document.querySelector('#taoAnalysisContent').classList.remove('d-none');
+            } catch (error) {
+                document.querySelector('#taoAnalysisError').textContent = `分析失败: ${error.message}`;
+                document.querySelector('#taoAnalysisError').classList.remove('d-none');
+            } finally {
+                document.querySelector('#taoAnalysisLoading').classList.add('d-none');
+            }
+        }
+
+        async function refreshMasterAnalysis() {
+            const stockCode = document.querySelector('#masterAnalysisModal').getAttribute('data-stock-code');
+            if (!stockCode) return;
+            
+            // 显示加载状态
+            document.querySelector('#masterAnalysisLoading').classList.remove('d-none');
+            document.querySelector('#masterAnalysisContent').classList.add('d-none');
+            document.querySelector('#masterAnalysisError').classList.add('d-none');
+            
+            try {
+                const response = await fetch(`/api/master_analysis/${stockCode}?force_refresh=true`);
+                const data = await response.json();
+                
+                if (data.error) {
+                    throw new Error(data.error);
+                }
+                
+                // 更新内容
+                document.querySelector('#buffettAnalysis').innerHTML = formatContent(data.buffett_analysis);
+                document.querySelector('#grahamAnalysis').innerHTML = formatContent(data.graham_analysis);
+                document.querySelector('#linYuanAnalysis').innerHTML = formatContent(data.lin_yuan_analysis);
+                document.querySelector('#liDaxiaoAnalysis').innerHTML = formatContent(data.li_daxiao_analysis);
+                document.querySelector('#duanYongpingAnalysis').innerHTML = formatContent(data.duan_yongping_analysis);
+                
+                // 显示内容
+                document.querySelector('#masterAnalysisContent').classList.remove('d-none');
+            } catch (error) {
+                document.querySelector('#masterAnalysisError').textContent = `分析失败: ${error.message}`;
+                document.querySelector('#masterAnalysisError').classList.remove('d-none');
+            } finally {
+                document.querySelector('#masterAnalysisLoading').classList.add('d-none');
+            }
+        }
    </script>
 </body>
 </html> 
--- a/config.json
+++ b/config.json
@ -0,0 +1,178 @@
+{
+    "watchlist": {
+        "300059": {
+            "target_market_value": {
+                "min": 2500.0,
+                "max": 2800.0
+            }
+        },
+        "601318": {
+            "target_market_value": {
+                "min": 8000.0,
+                "max": 9500.0
+            }
+        },
+        "000963": {
+            "target_market_value": {
+                "min": 500.0,
+                "max": 650.0
+            }
+        },
+        "002415": {
+            "target_market_value": {
+                "min": 2000.0,
+                "max": 2200.0
+            }
+        },
+        "000423": {
+            "target_market_value": {
+                "min": 270.0,
+                "max": 330.0
+            }
+        },
+        "000538": {
+            "target_market_value": {
+                "min": 807.0,
+                "max": 1210.0
+            }
+        },
+        "600085": {
+            "target_market_value": {
+                "min": 336.0,
+                "max": 429.0
+            }
+        },
+        "002714": {
+            "target_market_value": {
+                "min": 1650.0,
+                "max": 2200.0
+            }
+        },
+        "002007": {
+            "target_market_value": {
+                "min": 240.0,
+                "max": 288.0
+            }
+        },
+        "600132": {
+            "target_market_value": {
+                "min": 220.0,
+                "max": 290.0
+            }
+        },
+        "002049": {
+            "target_market_value": {
+                "min": 360.0,
+                "max": 480.0
+            }
+        },
+        "600436": {
+            "target_market_value": {
+                "min": 960.0,
+                "max": 1080.0
+            }
+        },
+        "002216": {
+            "target_market_value": {
+                "min": 72.0,
+                "max": 97.0
+            }
+        },
+        "601966": {
+            "target_market_value": {
+                "min": 220.0,
+                "max": 280.0
+            }
+        },
+        "603195": {
+            "target_market_value": {
+                "min": 730.0,
+                "max": 950.0
+            }
+        },
+        "000001": {
+            "target_market_value": {
+                "min": 1800.0,
+                "max": 2500.0
+            }
+        },
+        "600867": {
+            "target_market_value": {
+                "min": 120.0,
+                "max": 160.0
+            }
+        },
+        "603087": {
+            "target_market_value": {
+                "min": 170.0,
+                "max": 283.0
+            }
+        },
+        "603290": {
+            "target_market_value": {
+                "min": 150.0,
+                "max": 200.0
+            }
+        },
+        "600332": {
+            "target_market_value": {
+                "min": 380.0,
+                "max": 460.0
+            }
+        },
+        "300124": {
+            "target_market_value": {
+                "min": 1200.0,
+                "max": 1400.0
+            }
+        },
+        "300146": {
+            "target_market_value": {
+                "min": 150.0,
+                "max": 200.0
+            }
+        },
+        "000999": {
+            "target_market_value": {
+                "min": 450.0,
+                "max": 580.0
+            }
+        },
+        "002466": {
+            "target_market_value": {
+                "min": 330.0,
+                "max": 415.0
+            }
+        },
+        "300009": {
+            "target_market_value": {
+                "min": 120.0,
+                "max": 160.0
+            }
+        },
+        "300743": {
+            "target_market_value": {
+                "min": null,
+                "max": null
+            }
+        },
+        "603511": {
+            "target_market_value": {
+                "min": null,
+                "max": null
+            }
+        },
+        "688553": {
+            "target_market_value": {
+                "min": null,
+                "max": null
+            }
+        },
+        "600030": {
+            "target_market_value": {
+                "min": 3200.0,
+                "max": 3600.0
+            }
+        }
+    }
+}
--- a/config.json.example
+++ b/config.json.example
@ -1,6 +0,0 @@
-{
-    "watchlist": {},
-    "tushare_token": "your_tushare_token_here",
-    "ai_api_key": "your_ai_api_key_here",
-    "ai_model_id": "your_ai_model_id_here"
-} 
--- a/config.template.py
+++ b/config.template.py
@ -0,0 +1,12 @@
+import os
+
+# 基础配置
+class Config:
+    # 项目根目录
+    BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
+    
+    # Tushare API配置
+    TUSHARE_TOKEN = 'your_tushare_token_here'
+    
+    # 配置文件路径
+    CONFIG_FILE = os.path.join(BASE_DIR, "config.json") 
--- a/docs/images/main.png
+++ b/docs/images/main.png
--- a/requirements.txt
+++ b/requirements.txt
@ -1,11 +1,51 @@
+aiofiles==23.2.1
+annotated-types==0.7.0
+anyio==3.7.1
+beautifulsoup4==4.12.3
+bs4==0.0.2
+certifi==2024.12.14
+charset-normalizer==3.4.1
+click==8.1.8
+decorator==5.1.1
+et_xmlfile==1.0.0
 fastapi==0.104.1
-uvicorn==0.24.0
-python-multipart==0.0.6
-pydantic==2.10.4
-requests==2.32.3
-pandas==2.2.3
-numpy==2.2.1
-tushare==1.4.16
+h11==0.14.0
+html5lib==1.1
+idna==3.10
 Jinja2==3.1.2
+jsonpath==0.82.2
+lxml==5.3.0
+markdown-it-py==3.0.0
+MarkupSafe==3.0.2
+mdurl==0.1.2
+multitasking==0.0.11
+numpy==2.2.1
+openpyxl==3.1.5
+pandas==2.2.3
+py==1.11.0
+py_mini_racer==0.6.0
+pydantic==2.10.4
+pydantic_core==2.27.2
+Pygments==2.19.1
+pypinyin==0.53.0
 python-dateutil==2.9.0.post0
+python-multipart==0.0.6
+pytz==2024.2
+requests==2.32.3
+retry==0.9.2
+rich==13.9.4
 simplejson==3.19.3
+six==1.17.0
+sniffio==1.3.1
+soupsieve==2.6
+starlette==0.27.0
+tabulate==0.9.0
+tqdm==4.67.1
+tushare==1.4.16
+typing_extensions==4.12.2
+tzdata==2024.2
+urllib3==2.3.0
+uvicorn==0.24.0
+webencodings==0.5.1
+websocket-client==1.8.0
+xlrd==2.0.1
--- a/stock_cache.json
+++ b/stock_cache.json
@ -4,13 +4,13 @@
            "stock_info": {
                "code": "300059",
                "name": "东方财富",
-                "market_value": 3491.76,
-                "pe_ratio": 42.62,
-                "pb_ratio": 4.54,
-                "ps_ratio": 89.81,
-                "dividend_yield": 0.0018,
-                "price": 22.12,
-                "change_percent": 0.011,
+                "market_value": 3766.43,
+                "pe_ratio": 45.97,
+                "pb_ratio": 4.9,
+                "ps_ratio": 96.88,
+                "dividend_yield": 0.0017,
+                "price": 23.86,
+                "change_percent": 0.0787,
                "roe": 0.0811,
                "gross_profit_margin": 0.8372,
                "net_profit_margin": 2.694,
@ -28,20 +28,20 @@
                }
            }
        },
-        "timestamp": "2025-01-13"
+        "timestamp": "2025-01-15"
    },
    "601318": {
        "data": {
            "stock_info": {
                "code": "601318",
                "name": "中国平安",
-                "market_value": 8848.35,
-                "pe_ratio": 10.33,
-                "pb_ratio": 0.99,
-                "ps_ratio": 0.97,
-                "dividend_yield": 0.0498,
-                "price": 48.59,
-                "change_percent": -0.0074,
+                "market_value": 8988.57,
+                "pe_ratio": 10.49,
+                "pb_ratio": 1.01,
+                "ps_ratio": 0.98,
+                "dividend_yield": 0.0491,
+                "price": 49.36,
+                "change_percent": 0.0158,
                "roe": 0.1319,
                "gross_profit_margin": 0,
                "net_profit_margin": 0.1806,
@ -59,20 +59,20 @@
                }
            }
        },
-        "timestamp": "2025-01-13"
+        "timestamp": "2025-01-15"
    },
    "600085": {
        "data": {
            "stock_info": {
                "code": "600085",
                "name": "同仁堂",
-                "market_value": 507.86,
-                "pe_ratio": 30.43,
-                "pb_ratio": 4.13,
-                "ps_ratio": 2.84,
-                "dividend_yield": 0.027,
-                "price": 37.03,
-                "change_percent": 0.0082,
+                "market_value": 519.24,
+                "pe_ratio": 31.11,
+                "pb_ratio": 4.22,
+                "ps_ratio": 2.91,
+                "dividend_yield": 0.0264,
+                "price": 37.86,
+                "change_percent": 0.0224,
                "roe": 0.1037,
                "gross_profit_margin": 0.437,
                "net_profit_margin": 0.1435,
@ -90,20 +90,20 @@
                }
            }
        },
-        "timestamp": "2025-01-13"
+        "timestamp": "2025-01-15"
    },
    "002714": {
        "data": {
            "stock_info": {
                "code": "002714",
                "name": "牧原股份",
-                "market_value": 1980.25,
+                "market_value": 2023.41,
                "pe_ratio": 0,
-                "pb_ratio": 2.97,
-                "ps_ratio": 1.79,
-                "dividend_yield": 0.0227,
-                "price": 36.25,
-                "change_percent": 0.0014,
+                "pb_ratio": 3.04,
+                "ps_ratio": 1.83,
+                "dividend_yield": 0.0223,
+                "price": 37.04,
+                "change_percent": 0.0218,
                "roe": 0.1552,
                "gross_profit_margin": 0.1727,
                "net_profit_margin": 0.1162,
@ -121,20 +121,20 @@
                }
            }
        },
-        "timestamp": "2025-01-13"
+        "timestamp": "2025-01-15"
    },
    "000538": {
        "data": {
            "stock_info": {
                "code": "000538",
                "name": "云南白药",
-                "market_value": 1001.86,
-                "pe_ratio": 24.47,
-                "pb_ratio": 2.61,
-                "ps_ratio": 2.56,
-                "dividend_yield": 0.0586,
-                "price": 56.15,
-                "change_percent": -0.0083,
+                "market_value": 1024.17,
+                "pe_ratio": 25.02,
+                "pb_ratio": 2.67,
+                "ps_ratio": 2.62,
+                "dividend_yield": 0.0573,
+                "price": 57.4,
+                "change_percent": 0.0223,
                "roe": 0.1076,
                "gross_profit_margin": 0.284,
                "net_profit_margin": 0.1447,
@ -152,20 +152,20 @@
                }
            }
        },
-        "timestamp": "2025-01-13"
+        "timestamp": "2025-01-15"
    },
    "000423": {
        "data": {
            "stock_info": {
                "code": "000423",
                "name": "东阿阿胶",
-                "market_value": 391.86,
-                "pe_ratio": 34.05,
-                "pb_ratio": 3.95,
-                "ps_ratio": 8.31,
-                "dividend_yield": 0.0481,
-                "price": 60.85,
-                "change_percent": -0.0178,
+                "market_value": 398.75,
+                "pe_ratio": 34.65,
+                "pb_ratio": 4.02,
+                "ps_ratio": 8.46,
+                "dividend_yield": 0.0472,
+                "price": 61.92,
+                "change_percent": 0.0176,
                "roe": 0.1117,
                "gross_profit_margin": 0.7413,
                "net_profit_margin": 0.2661,
@ -183,20 +183,20 @@
                }
            }
        },
-        "timestamp": "2025-01-13"
+        "timestamp": "2025-01-15"
    },
    "000963": {
        "data": {
            "stock_info": {
                "code": "000963",
                "name": "华东医药",
-                "market_value": 567.33,
-                "pe_ratio": 19.98,
-                "pb_ratio": 2.57,
-                "ps_ratio": 1.4,
-                "dividend_yield": 0.0288,
-                "price": 32.34,
-                "change_percent": -0.0089,
+                "market_value": 582.24,
+                "pe_ratio": 20.51,
+                "pb_ratio": 2.64,
+                "ps_ratio": 1.43,
+                "dividend_yield": 0.028,
+                "price": 33.19,
+                "change_percent": 0.0263,
                "roe": 0.1189,
                "gross_profit_margin": 0.3255,
                "net_profit_margin": 0.0814,
@ -214,20 +214,20 @@
                }
            }
        },
-        "timestamp": "2025-01-13"
+        "timestamp": "2025-01-15"
    },
    "002415": {
        "data": {
            "stock_info": {
                "code": "002415",
                "name": "海康威视",
-                "market_value": 2554.83,
-                "pe_ratio": 18.11,
-                "pb_ratio": 3.33,
-                "ps_ratio": 2.86,
-                "dividend_yield": 0.0329,
-                "price": 27.67,
-                "change_percent": -0.0047,
+                "market_value": 2618.54,
+                "pe_ratio": 18.56,
+                "pb_ratio": 3.41,
+                "ps_ratio": 2.93,
+                "dividend_yield": 0.0321,
+                "price": 28.36,
+                "change_percent": 0.0249,
                "roe": 0.1059,
                "gross_profit_margin": 0.4476,
                "net_profit_margin": 0.1371,
@ -245,20 +245,20 @@
                }
            }
        },
-        "timestamp": "2025-01-13"
+        "timestamp": "2025-01-15"
    },
    "002007": {
        "data": {
            "stock_info": {
                "code": "002007",
                "name": "华兰生物",
-                "market_value": 284.92,
-                "pe_ratio": 19.23,
-                "pb_ratio": 2.44,
-                "ps_ratio": 5.33,
-                "dividend_yield": 0.0193,
-                "price": 15.58,
-                "change_percent": -0.0133,
+                "market_value": 291.32,
+                "pe_ratio": 19.66,
+                "pb_ratio": 2.49,
+                "ps_ratio": 5.45,
+                "dividend_yield": 0.0188,
+                "price": 15.93,
+                "change_percent": 0.0225,
                "roe": 0.0801,
                "gross_profit_margin": 0.6177,
                "net_profit_margin": 0.2897,
@ -276,20 +276,20 @@
                }
            }
        },
-        "timestamp": "2025-01-13"
+        "timestamp": "2025-01-15"
    },
    "600132": {
        "data": {
            "stock_info": {
                "code": "600132",
                "name": "重庆啤酒",
-                "market_value": 277.32,
-                "pe_ratio": 20.75,
-                "pb_ratio": 19.67,
-                "ps_ratio": 1.87,
-                "dividend_yield": 0.075,
-                "price": 57.3,
-                "change_percent": 0.0145,
+                "market_value": 281.28,
+                "pe_ratio": 21.04,
+                "pb_ratio": 19.95,
+                "ps_ratio": 1.9,
+                "dividend_yield": 0.074,
+                "price": 58.12,
+                "change_percent": 0.0143,
                "roe": 0.623,
                "gross_profit_margin": 0.492,
                "net_profit_margin": 0.2041,
@ -302,25 +302,25 @@
            },
            "targets": {
                "target_market_value": {
-                    "min": 225.0,
-                    "max": 260.0
+                    "min": 220.0,
+                    "max": 290.0
                }
            }
        },
-        "timestamp": "2025-01-13"
+        "timestamp": "2025-01-15"
    },
    "002049": {
        "data": {
            "stock_info": {
                "code": "002049",
                "name": "紫光国微",
-                "market_value": 492.36,
-                "pe_ratio": 19.46,
-                "pb_ratio": 4.1,
-                "ps_ratio": 6.51,
-                "dividend_yield": 0.0116,
-                "price": 57.95,
-                "change_percent": -0.0113,
+                "market_value": 508.67,
+                "pe_ratio": 20.1,
+                "pb_ratio": 4.24,
+                "ps_ratio": 6.72,
+                "dividend_yield": 0.0113,
+                "price": 59.87,
+                "change_percent": 0.0331,
                "roe": 0.0847,
                "gross_profit_margin": 0.5681,
                "net_profit_margin": 0.2383,
@ -338,20 +338,20 @@
                }
            }
        },
-        "timestamp": "2025-01-13"
+        "timestamp": "2025-01-15"
    },
    "600436": {
        "data": {
            "stock_info": {
                "code": "600436",
                "name": "片仔癀",
-                "market_value": 1236.8,
-                "pe_ratio": 44.21,
-                "pb_ratio": 9.28,
-                "ps_ratio": 12.3,
-                "dividend_yield": 0.0169,
-                "price": 205.0,
-                "change_percent": 0.0029,
+                "market_value": 1261.9,
+                "pe_ratio": 45.11,
+                "pb_ratio": 9.47,
+                "ps_ratio": 12.55,
+                "dividend_yield": 0.0166,
+                "price": 209.16,
+                "change_percent": 0.0203,
                "roe": 0.1961,
                "gross_profit_margin": 0.4544,
                "net_profit_margin": 0.3216,
@ -369,20 +369,20 @@
                }
            }
        },
-        "timestamp": "2025-01-13"
+        "timestamp": "2025-01-15"
    },
    "002216": {
        "data": {
            "stock_info": {
                "code": "002216",
                "name": "三全食品",
-                "market_value": 97.77,
-                "pe_ratio": 13.05,
-                "pb_ratio": 2.28,
-                "ps_ratio": 1.39,
-                "dividend_yield": 0.045,
-                "price": 11.12,
-                "change_percent": 0.0091,
+                "market_value": 100.14,
+                "pe_ratio": 13.36,
+                "pb_ratio": 2.34,
+                "ps_ratio": 1.42,
+                "dividend_yield": 0.0439,
+                "price": 11.39,
+                "change_percent": 0.0243,
                "roe": 0.0914,
                "gross_profit_margin": 0.2503,
                "net_profit_margin": 0.0769,
@ -396,24 +396,24 @@
            "targets": {
                "target_market_value": {
                    "min": 72.0,
-                    "max": 96.0
+                    "max": 97.0
                }
            }
        },
-        "timestamp": "2025-01-13"
+        "timestamp": "2025-01-15"
    },
    "601966": {
        "data": {
            "stock_info": {
                "code": "601966",
                "name": "玲珑轮胎",
-                "market_value": 251.87,
-                "pe_ratio": 18.11,
-                "pb_ratio": 1.18,
-                "ps_ratio": 1.25,
-                "dividend_yield": 0.0371,
-                "price": 17.21,
-                "change_percent": -0.0023,
+                "market_value": 257.87,
+                "pe_ratio": 18.54,
+                "pb_ratio": 1.2,
+                "ps_ratio": 1.28,
+                "dividend_yield": 0.0363,
+                "price": 17.62,
+                "change_percent": 0.0238,
                "roe": 0.0801,
                "gross_profit_margin": 0.2435,
                "net_profit_margin": 0.1073,
@ -431,20 +431,20 @@
                }
            }
        },
-        "timestamp": "2025-01-13"
+        "timestamp": "2025-01-15"
    },
    "603195": {
        "data": {
            "stock_info": {
                "code": "603195",
                "name": "公牛集团",
-                "market_value": 861.35,
-                "pe_ratio": 22.26,
-                "pb_ratio": 5.8,
-                "ps_ratio": 5.49,
-                "dividend_yield": 0.0321,
-                "price": 66.66,
-                "change_percent": -0.0141,
+                "market_value": 875.57,
+                "pe_ratio": 22.62,
+                "pb_ratio": 5.9,
+                "ps_ratio": 5.58,
+                "dividend_yield": 0.0316,
+                "price": 67.76,
+                "change_percent": 0.0165,
                "roe": 0.2228,
                "gross_profit_margin": 0.4312,
                "net_profit_margin": 0.2589,
@ -462,20 +462,20 @@
                }
            }
        },
-        "timestamp": "2025-01-13"
+        "timestamp": "2025-01-15"
    },
    "000001": {
        "data": {
            "stock_info": {
                "code": "000001",
                "name": "平安银行",
-                "market_value": 2173.46,
-                "pe_ratio": 4.68,
-                "pb_ratio": 0.52,
-                "ps_ratio": 1.32,
-                "dividend_yield": 0.0862,
-                "price": 11.2,
-                "change_percent": -0.0089,
+                "market_value": 2208.39,
+                "pe_ratio": 4.75,
+                "pb_ratio": 0.53,
+                "ps_ratio": 1.34,
+                "dividend_yield": 0.0848,
+                "price": 11.38,
+                "change_percent": 0.0161,
                "roe": 0.0825,
                "gross_profit_margin": 0,
                "net_profit_margin": 0.3561,
@ -488,25 +488,25 @@
            },
            "targets": {
                "target_market_value": {
-                    "min": 2300.0,
-                    "max": 2800.0
+                    "min": 1800.0,
+                    "max": 2500.0
                }
            }
        },
-        "timestamp": "2025-01-13"
+        "timestamp": "2025-01-15"
    },
    "600867": {
        "data": {
            "stock_info": {
                "code": "600867",
                "name": "通化东宝",
-                "market_value": 145.52,
-                "pe_ratio": 12.46,
-                "pb_ratio": 2.33,
-                "ps_ratio": 4.73,
-                "dividend_yield": 0.034,
-                "price": 7.43,
-                "change_percent": 0.0095,
+                "market_value": 150.22,
+                "pe_ratio": 12.86,
+                "pb_ratio": 2.41,
+                "ps_ratio": 4.88,
+                "dividend_yield": 0.033,
+                "price": 7.67,
+                "change_percent": 0.0323,
                "roe": -0.0097,
                "gross_profit_margin": 0.7447,
                "net_profit_margin": -0.0459,
@ -524,20 +524,20 @@
                }
            }
        },
-        "timestamp": "2025-01-13"
+        "timestamp": "2025-01-15"
    },
    "603087": {
        "data": {
            "stock_info": {
                "code": "603087",
                "name": "甘李药业",
-                "market_value": 250.34,
-                "pe_ratio": 73.62,
-                "pb_ratio": 2.3,
-                "ps_ratio": 9.6,
-                "dividend_yield": 0.0168,
-                "price": 41.65,
-                "change_percent": 0.0161,
+                "market_value": 258.16,
+                "pe_ratio": 75.91,
+                "pb_ratio": 2.37,
+                "ps_ratio": 9.9,
+                "dividend_yield": 0.0163,
+                "price": 42.95,
+                "change_percent": 0.0312,
                "roe": 0.0462,
                "gross_profit_margin": 0.7536,
                "net_profit_margin": 0.226,
@ -555,20 +555,20 @@
                }
            }
        },
-        "timestamp": "2025-01-13"
+        "timestamp": "2025-01-15"
    },
    "603290": {
        "data": {
            "stock_info": {
                "code": "603290",
                "name": "斯达半导",
-                "market_value": 193.85,
-                "pe_ratio": 21.29,
-                "pb_ratio": 2.94,
-                "ps_ratio": 5.29,
-                "dividend_yield": 0.0141,
-                "price": 80.95,
-                "change_percent": 0.0021,
+                "market_value": 202.52,
+                "pe_ratio": 22.24,
+                "pb_ratio": 3.07,
+                "ps_ratio": 5.53,
+                "dividend_yield": 0.0135,
+                "price": 84.57,
+                "change_percent": 0.0447,
                "roe": 0.065,
                "gross_profit_margin": 0.3169,
                "net_profit_margin": 0.1773,
@ -586,20 +586,20 @@
                }
            }
        },
-        "timestamp": "2025-01-13"
+        "timestamp": "2025-01-15"
    },
    "600332": {
        "data": {
            "stock_info": {
                "code": "600332",
                "name": "白云山",
-                "market_value": 433.11,
-                "pe_ratio": 10.68,
-                "pb_ratio": 1.22,
-                "ps_ratio": 0.57,
-                "dividend_yield": 0.0431,
-                "price": 26.64,
-                "change_percent": 0.0019,
+                "market_value": 442.54,
+                "pe_ratio": 10.91,
+                "pb_ratio": 1.24,
+                "ps_ratio": 0.59,
+                "dividend_yield": 0.0422,
+                "price": 27.22,
+                "change_percent": 0.0218,
                "roe": 0.0888,
                "gross_profit_margin": 0.177,
                "net_profit_margin": 0.0557,
@ -617,20 +617,20 @@
                }
            }
        },
-        "timestamp": "2025-01-13"
+        "timestamp": "2025-01-15"
    },
    "300124": {
        "data": {
            "stock_info": {
                "code": "300124",
                "name": "汇川技术",
-                "market_value": 1570.93,
-                "pe_ratio": 33.13,
-                "pb_ratio": 5.86,
-                "ps_ratio": 5.16,
-                "dividend_yield": 0.0077,
-                "price": 58.35,
-                "change_percent": -0.0273,
+                "market_value": 1663.81,
+                "pe_ratio": 35.09,
+                "pb_ratio": 6.21,
+                "ps_ratio": 5.47,
+                "dividend_yield": 0.0072,
+                "price": 61.8,
+                "change_percent": 0.0591,
                "roe": 0.1316,
                "gross_profit_margin": 0.3102,
                "net_profit_margin": 0.1345,
@ -648,20 +648,20 @@
                }
            }
        },
-        "timestamp": "2025-01-13"
+        "timestamp": "2025-01-15"
    },
    "300146": {
        "data": {
            "stock_info": {
                "code": "300146",
                "name": "汤臣倍健",
-                "market_value": 192.2,
-                "pe_ratio": 11.01,
-                "pb_ratio": 1.7,
-                "ps_ratio": 2.04,
-                "dividend_yield": 0.0789,
-                "price": 11.3,
-                "change_percent": 0.0116,
+                "market_value": 198.49,
+                "pe_ratio": 11.37,
+                "pb_ratio": 1.75,
+                "ps_ratio": 2.11,
+                "dividend_yield": 0.0764,
+                "price": 11.67,
+                "change_percent": 0.0327,
                "roe": 0.074,
                "gross_profit_margin": 0.6793,
                "net_profit_margin": 0.1504,
@ -679,20 +679,20 @@
                }
            }
        },
-        "timestamp": "2025-01-13"
+        "timestamp": "2025-01-15"
    },
    "000999": {
        "data": {
            "stock_info": {
                "code": "000999",
                "name": "华润三九",
-                "market_value": 546.6,
-                "pe_ratio": 19.16,
-                "pb_ratio": 2.84,
-                "ps_ratio": 2.21,
-                "dividend_yield": 0.0506,
-                "price": 42.56,
-                "change_percent": -0.0014,
+                "market_value": 557.39,
+                "pe_ratio": 19.54,
+                "pb_ratio": 2.9,
+                "ps_ratio": 2.25,
+                "dividend_yield": 0.0496,
+                "price": 43.4,
+                "change_percent": 0.0197,
                "roe": 0.1499,
                "gross_profit_margin": 0.5268,
                "net_profit_margin": 0.1644,
@ -710,7 +710,7 @@
                }
            }
        },
-        "timestamp": "2025-01-13"
+        "timestamp": "2025-01-15"
    },
    "000516": {
        "data": {
@ -748,13 +748,13 @@
            "stock_info": {
                "code": "002466",
                "name": "天齐锂业",
-                "market_value": 529.95,
-                "pe_ratio": 7.26,
-                "pb_ratio": 1.22,
-                "ps_ratio": 1.31,
-                "dividend_yield": 0.0418,
-                "price": 32.29,
-                "change_percent": 0.0416,
+                "market_value": 541.44,
+                "pe_ratio": 7.42,
+                "pb_ratio": 1.24,
+                "ps_ratio": 1.34,
+                "dividend_yield": 0.0409,
+                "price": 32.99,
+                "change_percent": 0.0217,
                "roe": -0.12,
                "gross_profit_margin": 0.4903,
                "net_profit_margin": 0.1723,
@ -772,7 +772,7 @@
                }
            }
        },
-        "timestamp": "2025-01-13"
+        "timestamp": "2025-01-15"
    },
    "index_data": {
        "data": {
@ -2130,13 +2130,13 @@
            "stock_info": {
                "code": "300009",
                "name": "安科生物",
-                "market_value": 135.81,
-                "pe_ratio": 16.03,
-                "pb_ratio": 3.47,
-                "ps_ratio": 4.74,
-                "dividend_yield": 0.0308,
-                "price": 8.12,
-                "change_percent": 0.01,
+                "market_value": 139.66,
+                "pe_ratio": 16.48,
+                "pb_ratio": 3.56,
+                "ps_ratio": 4.87,
+                "dividend_yield": 0.0299,
+                "price": 8.35,
+                "change_percent": 0.0283,
                "roe": 0.1537,
                "gross_profit_margin": 0.7775,
                "net_profit_margin": 0.3122,
@ -2149,25 +2149,25 @@
            },
            "targets": {
                "target_market_value": {
-                    "min": null,
-                    "max": null
+                    "min": 120.0,
+                    "max": 160.0
                }
            }
        },
-        "timestamp": "2025-01-13"
+        "timestamp": "2025-01-15"
    },
    "300743": {
        "data": {
            "stock_info": {
                "code": "300743",
                "name": "天地数码",
-                "market_value": 21.74,
-                "pe_ratio": 39.08,
-                "pb_ratio": 3.57,
-                "ps_ratio": 3.38,
-                "dividend_yield": 0.0241,
-                "price": 14.17,
-                "change_percent": 0.0093,
+                "market_value": 22.94,
+                "pe_ratio": 41.23,
+                "pb_ratio": 3.76,
+                "ps_ratio": 3.56,
+                "dividend_yield": 0.0229,
+                "price": 14.95,
+                "change_percent": 0.055,
                "roe": 0.1209,
                "gross_profit_margin": 0.3493,
                "net_profit_margin": 0.1335,
@ -2185,20 +2185,20 @@
                }
            }
        },
-        "timestamp": "2025-01-13"
+        "timestamp": "2025-01-15"
    },
    "603511": {
        "data": {
            "stock_info": {
                "code": "603511",
                "name": "爱慕股份",
-                "market_value": 46.23,
-                "pe_ratio": 15.12,
-                "pb_ratio": 1.05,
-                "ps_ratio": 1.35,
-                "dividend_yield": 0.0662,
-                "price": 11.37,
-                "change_percent": -0.0026,
+                "market_value": 50.86,
+                "pe_ratio": 16.64,
+                "pb_ratio": 1.16,
+                "ps_ratio": 1.48,
+                "dividend_yield": 0.0602,
+                "price": 12.51,
+                "change_percent": 0.1003,
                "roe": 0.0317,
                "gross_profit_margin": 0.6597,
                "net_profit_margin": 0.0615,
@ -2216,20 +2216,20 @@
                }
            }
        },
-        "timestamp": "2025-01-13"
+        "timestamp": "2025-01-15"
    },
    "688553": {
        "data": {
            "stock_info": {
                "code": "688553",
                "name": "汇宇制药-W",
-                "market_value": 58.37,
-                "pe_ratio": 41.76,
-                "pb_ratio": 1.5,
-                "ps_ratio": 6.3,
+                "market_value": 60.79,
+                "pe_ratio": 43.49,
+                "pb_ratio": 1.57,
+                "ps_ratio": 6.56,
                "dividend_yield": 0.0,
-                "price": 13.78,
-                "change_percent": 0.0117,
+                "price": 14.35,
+                "change_percent": 0.0414,
                "roe": 0.0594,
                "gross_profit_margin": 0.8315,
                "net_profit_margin": 0.2592,
@ -2247,20 +2247,20 @@
                }
            }
        },
-        "timestamp": "2025-01-13"
+        "timestamp": "2025-01-15"
    },
    "600030": {
        "data": {
            "stock_info": {
                "code": "600030",
                "name": "中信证券",
-                "market_value": 3928.93,
-                "pe_ratio": 19.92,
-                "pb_ratio": 1.53,
-                "ps_ratio": 6.54,
-                "dividend_yield": 0.027,
-                "price": 26.51,
-                "change_percent": 0.0019,
+                "market_value": 4105.29,
+                "pe_ratio": 20.82,
+                "pb_ratio": 1.6,
+                "ps_ratio": 6.83,
+                "dividend_yield": 0.0258,
+                "price": 27.7,
+                "change_percent": 0.0449,
                "roe": 0.0605,
                "gross_profit_margin": 0,
                "net_profit_margin": 0.3782,
@ -2273,11 +2273,11 @@
            },
            "targets": {
                "target_market_value": {
-                    "min": null,
-                    "max": null
+                    "min": 3200.0,
+                    "max": 3600.0
                }
            }
        },
-        "timestamp": "2025-01-13"
+        "timestamp": "2025-01-15"
    }
 }
--- a/项目文档.txt
+++ b/项目文档.txt
@ -0,0 +1,193 @@
+# 价值投资盯盘系统项目文档
+
+## 项目概述
+
+**项目名称**：价值投资盯盘系统  
+**开发者**：张艺杰  
+**项目类型**：A股智能股票分析与监控平台  
+**技术栈**：Python + FastAPI + Bootstrap + ECharts
+
+## 系统功能
+
+### 1. 核心功能
+
+1. **股票监控**
+   - 实时股票行情监控
+   - 自定义市值目标区间
+   - 多维度指标展示
+   - 涨跌幅实时更新
+
+2. **指数行情**
+   - 主要指数实时展示
+   - K线图可视化
+   - 涨跌幅实时更新
+
+3. **公司详情分析**
+   - 公司基本信息
+   - 财务指标分析
+   - 股东结构分析
+   - AI智能分析
+
+### 2. 具体指标监控
+
+#### 2.1 基础指标
+- 股票代码和名称
+- 现价和涨跌幅
+- 市值监控
+- 目标区间对比
+
+#### 2.2 估值指标
+- 市盈率(PE)
+- 市净率(PB)
+- 市销率(PS)
+- 股息率
+
+#### 2.3 财务指标
+- ROE（净资产收益率）
+- 毛利率
+- 净利率
+- 资产负债率
+- 净利润增长率
+- 每股净资产
+- 每股经营现金流
+
+### 3. AI分析功能
+
+1. **投资建议**
+   - 总体建议
+   - 建议操作
+   - 关注重点
+
+2. **价格分析**
+   - 合理价格区间
+   - 目标市值区间
+
+3. **多维度分析**
+   - 估值分析
+   - 财务健康状况
+   - 成长潜力
+   - 风险评估
+
+## 技术实现
+
+### 1. 后端架构
+
+1. **Web框架**
+   - FastAPI作为主要Web框架
+   - Uvicorn作为ASGI服务器
+
+2. **数据源集成**
+   - Tushare API接口
+
+3. **数据处理**
+   - Pandas进行数据分析
+   - NumPy进行数值计算
+
+### 2. 前端实现
+
+1. **UI框架**
+   - Bootstrap 5.1.3
+   - 响应式设计
+
+2. **数据可视化**
+   - ECharts 5.4.3
+   - 动态K线图表
+
+3. **交互设计**
+   - AJAX异步数据更新
+   - 实时数据刷新
+   - 模态框展示详情
+
+### 3. 数据存储
+
+1. **配置存储**
+   - JSON文件存储监控列表
+   - 配置文件自动管理
+
+2. **缓存机制**
+   - 行情数据缓存
+   - 智能更新策略
+
+## 部署要求
+
+### 1. 系统要求
+- Python 3.8+
+- 8GB+ RAM
+- 现代浏览器支持
+
+### 2. 依赖安装
+```bash
+pip install -r requirements.txt
+```
+
+### 3. 配置说明
+- 需配置Tushare API Token
+- 配置端口默认为8000
+- 支持热重载
+
+## 使用说明
+
+### 1. 启动系统
+```bash
+python run.py
+```
+
+### 2. 访问系统
+- 浏览器访问：`http://localhost:8000`
+
+### 3. 基本操作
+1. 添加监控股票
+   - 输入6位股票代码
+   - 设置目标市值区间
+   
+2. 查看股票详情
+   - 点击股票名称查看详细信息
+   - 查看AI分析报告
+   
+3. 管理监控列表
+   - 删除不需要的股票
+   - 强制刷新数据
+
+## 安全性考虑
+
+1. **数据安全**
+   - API Token安全存储
+   - 敏感信息加密
+
+2. **访问控制**
+   - 请求频率限制
+   - 错误处理机制
+
+## 后续优化方向
+
+1. **功能扩展**
+   - 增加更多技术指标
+   - 添加自定义告警功能
+   - 支持多维度筛选
+
+2. **性能优化**
+   - 优化数据缓存机制
+   - 提升响应速度
+   - 减少资源占用
+
+3. **用户体验**
+   - 增加自定义主题
+   - 优化移动端显示
+   - 添加更多图表类型
+
+## 维护说明
+
+1. **日常维护**
+   - 定期更新依赖
+   - 检查API可用性
+   - 优化数据缓存
+
+2. **问题处理**
+   - 日志监控
+   - 异常处理
+   - 性能监控
+
+## 版权信息
+
+版权所有 © 2024 张艺杰
+保留所有权利