测试集成mcp

EasyFinancialAgent/chat_direct.py

@@ -0,0 +1,291 @@
+"""
+Financial AI Assistant - Direct Method Library (不依赖 HTTP)
+直接导入并调用 easy_financial_mcp.py 中的函数
+支持本地和 HF Space 部署
+"""
+
+import sys
+from pathlib import Path
+
+# 添加服务模块路径
+PROJECT_ROOT = Path(__file__).parent.parent.absolute()
+sys.path.insert(0, str(PROJECT_ROOT))
+
+# 直接导入 MCP 中定义的函数
+try:
+    from EasyFinancialAgent.easy_financial_mcp import (
+        search_company as _search_company,
+        get_company_info as _get_company_info,
+        get_company_filings as _get_company_filings,
+        get_financial_data as _get_financial_data,
+        extract_financial_metrics as _extract_financial_metrics,
+        get_latest_financial_data as _get_latest_financial_data,
+        advanced_search_company as _advanced_search_company
+    )
+    MCP_DIRECT_AVAILABLE = True
+    print("[FinancialAI] ✓ Direct MCP functions imported successfully")
+except ImportError as e:
+    MCP_DIRECT_AVAILABLE = False
+    print(f"[FinancialAI] ✗ Failed to import MCP functions: {e}")
+    # 定义占位符函数
+    def _advanced_search_company(x):
+        return {"error": "MCP not available"}
+    def _get_company_info(x):
+        return {"error": "MCP not available"}
+    def _get_company_filings(x):
+        return {"error": "MCP not available"}
+    def _get_latest_financial_data(x):
+        return {"error": "MCP not available"}
+    def _extract_financial_metrics(x, y=3):
+        return {"error": "MCP not available"}
+
+
+# ============================================================
+# 便捷方法 - 公司搜索相关
+# ============================================================
+
+def search_company_direct(company_input):
+    """
+    搜索公司信息（直接调用）
+    
+    Args:
+        company_input: 公司名称或代码
+    
+    Returns:
+        搜索结果
+    
+    Example:
+        result = search_company_direct("Apple")
+    """
+    if not MCP_DIRECT_AVAILABLE:
+        return {"error": "MCP functions not available"}
+    
+    try:
+        return _advanced_search_company(company_input)
+    except Exception as e:
+        return {"error": str(e)}
+
+
+def get_company_info_direct(cik):
+    """
+    获取公司详细信息（直接调用）
+    
+    Args:
+        cik: 公司 CIK 代码
+    
+    Returns:
+        公司信息
+    
+    Example:
+        result = get_company_info_direct("0000320193")
+    """
+    if not MCP_DIRECT_AVAILABLE:
+        return {"error": "MCP functions not available"}
+    
+    try:
+        return _get_company_info(cik)
+    except Exception as e:
+        return {"error": str(e)}
+
+
+def get_company_filings_direct(cik):
+    """
+    获取公司 SEC 文件列表（直接调用）
+    
+    Args:
+        cik: 公司 CIK 代码
+    
+    Returns:
+        文件列表
+    
+    Example:
+        result = get_company_filings_direct("0000320193")
+    """
+    if not MCP_DIRECT_AVAILABLE:
+        return {"error": "MCP functions not available"}
+    
+    try:
+        return _get_company_filings(cik)
+    except Exception as e:
+        return {"error": str(e)}
+
+
+# ============================================================
+# 便捷方法 - 财务数据相关
+# ============================================================
+
+def get_latest_financial_data_direct(cik):
+    """
+    获取公司最新财务数据（直接调用）
+    
+    Args:
+        cik: 公司 CIK 代码
+    
+    Returns:
+        最新财务数据
+    
+    Example:
+        result = get_latest_financial_data_direct("0000320193")
+    """
+    if not MCP_DIRECT_AVAILABLE:
+        return {"error": "MCP functions not available"}
+    
+    try:
+        return _get_latest_financial_data(cik)
+    except Exception as e:
+        return {"error": str(e)}
+
+
+def extract_financial_metrics_direct(cik, years=5):
+    """
+    提取多年财务指标趋势（直接调用）
+    
+    Args:
+        cik: 公司 CIK 代码
+        years: 年数（默认 3 年）
+    
+    Returns:
+        财务指标数据
+    
+    Example:
+        result = extract_financial_metrics_direct("0000320193", years=5)
+    """
+    if not MCP_DIRECT_AVAILABLE:
+        return {"error": "MCP functions not available"}
+    
+    try:
+        return _extract_financial_metrics(cik, years)
+    except Exception as e:
+        return {"error": str(e)}
+
+
+# ============================================================
+# 高级方法 - 综合查询
+# ============================================================
+
+def query_company_direct(company_input, get_filings=True, get_metrics=True):
+    """
+    综合查询公司信息（直接调用）
+    包括搜索、基本信息、文件列表和财务指标
+    
+    Args:
+        company_input: 公司名称或代码
+        get_filings: 是否获取文件列表
+        get_metrics: 是否获取财务指标
+    
+    Returns:
+        综合结果字典，包含 search, company_info, filings, metrics
+    
+    Example:
+        result = query_company_direct("Apple", get_filings=True, get_metrics=True)
+    """
+    from datetime import datetime
+    
+    result = {
+        "timestamp": datetime.now().isoformat(),
+        "query_input": company_input,
+        "status": "success",
+        "data": {
+            "company_search": None,
+            "company_info": None,
+            "filings": None,
+            "metrics": None
+        },
+        "errors": []
+    }
+    
+    if not MCP_DIRECT_AVAILABLE:
+        result["status"] = "error"
+        result["errors"].append("MCP functions not available")
+        return result
+    
+    try:
+        # 1. 搜索公司
+        search_result = search_company_direct(company_input)
+        if "error" in search_result:
+            result["errors"].append(f"Search error: {search_result['error']}")
+            result["status"] = "error"
+            return result
+        
+        result["data"]["company_search"] = search_result
+        
+        # 从搜索结果提取 CIK
+        cik = None
+        if isinstance(search_result, dict):
+            cik = search_result.get("cik")
+        elif isinstance(search_result, (list, tuple)) and len(search_result) > 0:
+            # 从列表中获取第一个元素
+            try:
+                first_item = search_result[0] if isinstance(search_result, (list, tuple)) else None
+                if isinstance(first_item, dict):
+                    cik = first_item.get("cik")
+            except (IndexError, TypeError):
+                pass
+        
+        if not cik:
+            result["errors"].append("Could not extract CIK from search result")
+            result["status"] = "error"
+            return result
+        
+        # 2. 获取公司信息
+        company_info = get_company_info_direct(cik)
+        if "error" not in company_info:
+            result["data"]["company_info"] = company_info
+        else:
+            result["errors"].append(f"Failed to get company info: {company_info.get('error')}")
+        
+        # 3. 获取文件列表
+        if get_filings:
+            filings = get_company_filings_direct(cik)
+            if "error" not in filings:
+                result["data"]["filings"] = filings
+            else:
+                result["errors"].append(f"Failed to get filings: {filings.get('error')}")
+        
+        # 4. 获取财务指标
+        if get_metrics:
+            metrics = extract_financial_metrics_direct(cik, years=3)
+            if "error" not in metrics:
+                result["data"]["metrics"] = metrics
+            else:
+                result["errors"].append(f"Failed to get metrics: {metrics.get('error')}")
+        
+    except Exception as e:
+        result["status"] = "error"
+        result["errors"].append(f"Exception: {str(e)}")
+        import traceback
+        result["errors"].append(traceback.format_exc())
+    
+    return result
+
+
+# ============================================================
+# 测试函数
+# ============================================================
+
+if __name__ == "__main__":
+    print("\n" + "="*60)
+    print("Financial AI Assistant - Direct Method Test")
+    print("="*60)
+    
+    # 测试 1: 公司搜索
+    print("\n1. 搜索公司 (Apple)...")
+    result = search_company_direct("Apple")
+    print(f"   结果: {result}")
+    
+    # 测试 2: 公司摘要
+    print("\n2. 获取 Tesla 完整信息...")
+    summary = query_company_direct("Tesla", get_filings=False, get_metrics=False)
+    print(f"   状态: {summary['status']}")
+    print(f"   数据: {summary['data']}")
+    print(f"   错误: {summary['errors']}")
+    
+    # 测试 3: 财务指标
+    print("\n3. 获取 Microsoft 财务指标...")
+    if summary['data']['company_search']:
+        cik = summary['data']['company_search'].get('cik')
+        if cik:
+            metrics = extract_financial_metrics_direct(cik, years=3)
+            print(f"   指标: {metrics}")
+    
+    print("\n" + "="*60)

EasyFinancialAgent/easy_financial_mcp.py

@@ -0,0 +1,220 @@
+"""
+MCP Server for SEC EDGAR Financial Data - FastMCP Implementation
+Uses Anthropic official FastMCP SDK for cleaner, more maintainable code
+"""
+
+from mcp.server.fastmcp import FastMCP
+from EasyReportDataMCP.edgar_client import EdgarDataClient
+from EasyReportDataMCP.financial_analyzer import FinancialAnalyzer
+
+# Initialize EDGAR clients
+edgar_client = EdgarDataClient(
+    user_agent="Juntao Peng Financial Report Metrics App ([email protected])"
+)
+
+financial_analyzer = FinancialAnalyzer(
+    user_agent="Juntao Peng Financial Report Metrics App ([email protected])"
+)
+
+# Create FastMCP server with pure JSON response and stateless HTTP
+mcp = FastMCP("sec-financial-data", json_response=True, stateless_http=True)
+
+
+@mcp.tool()
+def search_company(company_name: str) -> dict:
+    """
+    Search for a company by name in SEC EDGAR database.
+    
+    Args:
+        company_name: Company name to search (e.g., Microsoft, Apple, Tesla)
+    
+    Returns:
+        dict: Company information including CIK, name, and ticker symbol
+    """
+    result = edgar_client.search_company_by_name(company_name)
+    if result:
+        return result
+    else:
+        return {"error": f"No company found with name: {company_name}"}
+
+
+@mcp.tool()
+def get_company_info(cik: str) -> dict:
+    """
+    Get detailed company information including name, tickers, SIC code, and industry description.
+    
+    Args:
+        cik: Company CIK code (10-digit format, e.g., 0000789019)
+    
+    Returns:
+        dict: Company information
+    """
+    result = edgar_client.get_company_info(cik)
+    if result:
+        return result
+    else:
+        return {"error": f"No company found with CIK: {cik}"}
+
+
+@mcp.tool()
+def get_company_filings(cik: str, form_types: list[str] | None = None) -> dict:
+    """
+    Get list of company SEC filings (10-K, 10-Q, 20-F, etc.) with filing dates and document links.
+    
+    Args:
+        cik: Company CIK code
+        form_types: Optional filter by form types (e.g., [10-K, 10-Q])
+    
+    Returns:
+        dict: Filings list with total count and limited results
+    """
+    result = edgar_client.get_company_filings(cik, form_types)
+    if result:
+        limited_result = result[:20]
+        return {
+            "total": len(result),
+            "returned": len(limited_result),
+            "filings": limited_result
+        }
+    else:
+        return {"error": f"No filings found for CIK: {cik}"}
+
+
+@mcp.tool()
+def get_financial_data(cik: str, period: str) -> dict:
+    """
+    Get financial data for a specific period including revenue, net income, EPS, operating expenses, and cash flow.
+    
+    Args:
+        cik: Company CIK code
+        period: Period in format YYYY for annual or YYYYQX for quarterly (e.g., 2024, 2024Q3)
+    
+    Returns:
+        dict: Financial data for the specified period
+    """
+    result = edgar_client.get_financial_data_for_period(cik, period)
+    if result and "period" in result:
+        return result
+    else:
+        return {"error": f"No financial data found for CIK: {cik}, Period: {period}"}
+
+
+@mcp.tool()
+def extract_financial_metrics(cik: str, years: int = 3) -> dict:
+    """
+    Extract comprehensive financial metrics for multiple years including both annual and quarterly data.
+    Returns data in chronological order (newest first): FY -> Q4 -> Q3 -> Q2 -> Q1.
+    
+    Args:
+        cik: Company CIK code
+        years: Number of recent years to extract (1-10, default: 3)
+    
+    Returns:
+        dict: Financial metrics with periods and data
+    """
+    if years < 1 or years > 10:
+        return {"error": "Years parameter must be between 1 and 10"}
+    
+    # Check if company has filings (use tuple for caching)
+    filings_10k = edgar_client.get_company_filings(cik, ('"10-K"',))
+    filings_20f = edgar_client.get_company_filings(cik, ('"20-F"',))
+    total_filings = len(filings_10k) + len(filings_20f)
+    
+    if total_filings == 0:
+        return {
+            "error": f"No annual filings found for CIK: {cik}",
+            "suggestion": "Please check if the CIK is correct"
+        }
+    
+    # Extract metrics
+    metrics = financial_analyzer.extract_financial_metrics(cik, years)
+    
+    if metrics:
+        formatted = financial_analyzer.format_financial_data(metrics)
+        return {
+            "periods": len(formatted),
+            "data": formatted
+        }
+    else:
+        # Return debug info
+        debug_info = {
+            "error": f"No financial metrics extracted for CIK: {cik}",
+            "debug": {
+                "cik": cik,
+                "years_requested": years,
+                "filings_found": {
+                    "10-K": len(filings_10k),
+                    "20-F": len(filings_20f)
+                },
+                "latest_filings": []
+            },
+            "suggestion": "Try using get_latest_financial_data or get_financial_data with a specific period"
+        }
+        
+        # Add latest filing dates
+        all_filings = filings_10k + filings_20f
+        for filing in all_filings[:5]:
+            debug_info["debug"]["latest_filings"].append({
+                "form": filing.get("form_type"),
+                "date": filing.get("filing_date")
+            })
+        
+        return debug_info
+
+
+@mcp.tool()
+def get_latest_financial_data(cik: str) -> dict:
+    """
+    Get the most recent financial data available for a company.
+    
+    Args:
+        cik: Company CIK code
+    
+    Returns:
+        dict: Latest financial data
+    """
+    result = financial_analyzer.get_latest_financial_data(cik)
+    if result and "period" in result:
+        return result
+    else:
+        return {"error": f"No latest financial data found for CIK: {cik}"}
+
+
+@mcp.tool()
+def advanced_search_company(company_input: str) -> dict:
+    """
+    Advanced search supporting both company name and CIK code. Automatically detects input type.
+    
+    Args:
+        company_input: Company name, ticker, or CIK code
+    
+    Returns:
+        dict: Company information
+    """
+    result = financial_analyzer.search_company(company_input)
+    if result.get("error"):
+        return {"error": result["error"]}
+    return result
+
+
+# For production deployment
+if __name__ == "__main__":
+    import os
+    
+    # Set port from environment (HF Space sets PORT=7860)
+    port = int(os.getenv("PORT", "7860"))
+    host = os.getenv("HOST", "0.0.0.0")
+    
+    # Monkeypatch uvicorn.Config to use our port
+    import uvicorn
+    original_config_init = uvicorn.Config.__init__
+    
+    def patched_init(self, *args, **kwargs):
+        kwargs['host'] = host
+        kwargs['port'] = port
+        return original_config_init(self, *args, **kwargs)
+    
+    uvicorn.Config.__init__ = patched_init
+    
+    # Run FastMCP with SSE transport
+    mcp.run(transport="sse")

EasyReportDataMCP/edgar_client.py

@@ -0,0 +1,693 @@
+"""EDGAR API Client Module"""
+
+import requests
+from requests.adapters import HTTPAdapter
+from urllib3.util.retry import Retry
+try:
+    from sec_edgar_api.EdgarClient import EdgarClient
+except ImportError:
+    EdgarClient = None
+import json
+import time
+from functools import wraps
+import threading
+
+
+class EdgarDataClient:
+    def __init__(self, user_agent="Juntao Peng Financial Report Metrics App ([email protected])"):
+        """Initialize EDGAR client"""
+        self.user_agent = user_agent
+        self.last_request_time = 0
+        self.min_request_interval = 0.11  # SEC allows 10 requests/second, use 0.11s to be safe
+        self.request_timeout = 30  # 30 seconds timeout for HTTP requests
+        self.max_retries = 3  # Maximum retry attempts
+        self._lock = threading.Lock()  # Thread-safe rate limiting
+        
+        # Configure requests session with connection pooling and retry logic
+        self.session = requests.Session()
+        retry_strategy = Retry(
+            total=3,
+            backoff_factor=1,
+            status_forcelist=[429, 500, 502, 503, 504],
+            allowed_methods=["HEAD", "GET", "OPTIONS"]
+        )
+        adapter = HTTPAdapter(
+            max_retries=retry_strategy,
+            pool_connections=10,
+            pool_maxsize=20,
+            pool_block=False
+        )
+        self.session.mount("http://", adapter)
+        self.session.mount("https://", adapter)
+        self.session.headers.update({"User-Agent": user_agent})
+        
+        # Cache for frequently accessed data
+        self._company_cache = {}  # Cache company info to avoid repeated calls
+        self._cache_ttl = 300  # 5 minutes cache TTL (for company info)
+        self._tickers_cache_ttl = 3600  # 1 hour for company tickers (rarely changes)
+        self._cache_timestamps = {}
+        
+        # Fast lookup indexes for company tickers
+        self._ticker_index = {}  # ticker -> company data
+        self._cik_index = {}  # cik -> company data
+        self._name_lower_index = {}  # lowercase name -> company data
+        self._index_loaded = False
+        
+        if EdgarClient:
+            self.edgar = EdgarClient(user_agent=user_agent)
+        else:
+            self.edgar = None
+    
+    def _rate_limit(self):
+        """Thread-safe rate limiting to comply with SEC API limits (10 requests/second)"""
+        with self._lock:
+            current_time = time.time()
+            time_since_last_request = current_time - self.last_request_time
+            
+            if time_since_last_request < self.min_request_interval:
+                sleep_time = self.min_request_interval - time_since_last_request
+                time.sleep(sleep_time)
+            
+            self.last_request_time = time.time()
+    
+    def _is_cache_valid(self, cache_key):
+        """Check if cache entry is still valid"""
+        if cache_key not in self._cache_timestamps:
+            return False
+        age = time.time() - self._cache_timestamps[cache_key]
+        # Use longer TTL for company tickers list
+        ttl = self._tickers_cache_ttl if cache_key == "company_tickers_json" else self._cache_ttl
+        return age < ttl
+    
+    def _get_cached(self, cache_key):
+        """Get cached data if valid"""
+        if self._is_cache_valid(cache_key):
+            return self._company_cache.get(cache_key)
+        return None
+    
+    def _set_cache(self, cache_key, data):
+        """Set cache data with timestamp"""
+        self._company_cache[cache_key] = data
+        self._cache_timestamps[cache_key] = time.time()
+    
+    def _make_request_with_retry(self, url, headers=None, use_session=True):
+        """Make HTTP request with retry logic and timeout"""
+        if headers is None:
+            headers = {"User-Agent": self.user_agent}
+        
+        for attempt in range(self.max_retries):
+            try:
+                self._rate_limit()
+                if use_session:
+                    response = self.session.get(url, headers=headers, timeout=self.request_timeout)
+                else:
+                    response = requests.get(url, headers=headers, timeout=self.request_timeout)
+                response.raise_for_status()
+                return response
+            except requests.exceptions.Timeout:
+                print(f"Request timeout (attempt {attempt + 1}/{self.max_retries}): {url}")
+                if attempt == self.max_retries - 1:
+                    raise
+                time.sleep(2 ** attempt)  # Exponential backoff
+            except requests.exceptions.HTTPError as e:
+                if e.response.status_code == 429:  # Too Many Requests
+                    wait_time = 2 ** attempt
+                    print(f"Rate limited, waiting {wait_time}s (attempt {attempt + 1}/{self.max_retries})")
+                    time.sleep(wait_time)
+                    if attempt == self.max_retries - 1:
+                        raise
+                else:
+                    raise
+            except Exception as e:
+                print(f"Request error (attempt {attempt + 1}/{self.max_retries}): {e}")
+                if attempt == self.max_retries - 1:
+                    raise
+                time.sleep(2 ** attempt)
+        
+        return None
+    
+    def _load_company_tickers(self, force_refresh=False):
+        """Load and index company tickers data"""
+        cache_key = "company_tickers_json"
+        
+        # Check if already loaded and cache is valid
+        if self._index_loaded and not force_refresh and self._is_cache_valid(cache_key):
+            return self._get_cached(cache_key)
+        
+        # Check cache first
+        companies = self._get_cached(cache_key) if not force_refresh else None
+        
+        if not companies:
+            try:
+                # Download company tickers
+                url = "https://www.sec.gov/files/company_tickers.json"
+                print(f"Downloading company tickers from SEC...")
+                
+                response = self._make_request_with_retry(url)
+                if not response:
+                    print("Failed to download company tickers")
+                    return None
+                
+                companies = response.json()
+                # Cache for 1 hour
+                self._set_cache(cache_key, companies)
+                print(f"Loaded {len(companies)} companies")
+            except Exception as e:
+                print(f"Error loading company tickers: {e}")
+                return None
+        else:
+            print(f"Using cached company tickers ({len(companies)} companies)")
+        
+        # Build fast lookup indexes
+        self._ticker_index = {}
+        self._cik_index = {}
+        self._name_lower_index = {}
+        
+        for _, company in companies.items():
+            cik = str(company["cik_str"]).zfill(10)
+            ticker = company["ticker"]
+            name = company["title"]
+            
+            company_data = {
+                "cik": cik,
+                "name": name,
+                "ticker": ticker
+            }
+            
+            # Index by ticker (lowercase for case-insensitive)
+            self._ticker_index[ticker.lower()] = company_data
+            
+            # Index by CIK
+            self._cik_index[cik] = company_data
+            
+            # Index by exact name (lowercase)
+            self._name_lower_index[name.lower()] = company_data
+        
+        self._index_loaded = True
+        print(f"Built indexes: {len(self._ticker_index)} tickers, {len(self._cik_index)} CIKs")
+        return companies
+    
+    def get_company_by_cik(self, cik):
+        """Fast lookup of company info by CIK (from cached tickers)"""
+        # Ensure data is loaded
+        self._load_company_tickers()
+        
+        # Normalize CIK
+        cik_normalized = str(cik).zfill(10)
+        
+        # Fast index lookup
+        return self._cik_index.get(cik_normalized)
+    
+    def get_company_by_ticker(self, ticker):
+        """Fast lookup of company info by ticker"""
+        # Ensure data is loaded
+        self._load_company_tickers()
+        
+        # Fast index lookup (case-insensitive)
+        return self._ticker_index.get(ticker.lower())
+        
+    def search_company_by_name(self, company_name):
+        """Search company CIK by company name with caching and optimized search"""
+        try:
+            # Load company tickers and build indexes
+            companies = self._load_company_tickers()
+            
+            if not companies:
+                return None
+            
+            # Prepare search input
+            search_name = company_name.lower().strip()
+            
+            # Optimize: Use fast index lookups first
+            # Priority 1: Exact ticker match (fastest - O(1) hash lookup)
+            if search_name in self._ticker_index:
+                return self._ticker_index[search_name].copy()
+            
+            # Priority 2: Exact name match (fast - O(1) hash lookup)
+            if search_name in self._name_lower_index:
+                return self._name_lower_index[search_name].copy()
+            
+            # Priority 3: Exact CIK match (fast - O(1) hash lookup)
+            # Handle CIK input (8-10 digits)
+            if search_name.isdigit() and len(search_name) >= 8:
+                cik_normalized = search_name.zfill(10)
+                if cik_normalized in self._cik_index:
+                    return self._cik_index[cik_normalized].copy()
+            
+            # Priority 4: Partial matches (slower - requires iteration)
+            # Only execute if exact matches fail
+            matches = []
+            for ticker_lower, company_data in self._ticker_index.items():
+                name_lower = company_data["name"].lower()
+                
+                # Partial match in name or ticker
+                if search_name in name_lower or search_name in ticker_lower:
+                    matches.append(company_data.copy())
+                    # Optimize: Stop after finding 10 matches to avoid scanning all 13,000+
+                    if len(matches) >= 10:
+                        break
+            
+            # Return first partial match
+            if matches:
+                return matches[0]
+            else:
+                return None
+            
+        except Exception as e:
+            print(f"Error searching company: {e}")
+            return None
+    
+    def get_company_info(self, cik):
+        """
+        Get basic company information with caching
+        
+        Args:
+            cik (str): Company CIK code
+            
+        Returns:
+            dict: Dictionary containing company information
+        """
+        if not self.edgar:
+            print("sec_edgar_api library not installed")
+            return None
+        
+        # Check cache first
+        cache_key = f"info_{cik}"
+        cached = self._get_cached(cache_key)
+        if cached:
+            return cached
+            
+        try:
+            # Add timeout wrapper for sec-edgar-api calls
+            import signal
+            
+            def timeout_handler(signum, frame):
+                raise TimeoutError("SEC API call timeout")
+            
+            # Set alarm for 30 seconds (only works on Unix-like systems)
+            try:
+                signal.signal(signal.SIGALRM, timeout_handler)
+                signal.alarm(30)
+                submissions = self.edgar.get_submissions(cik=cik)
+                signal.alarm(0)  # Cancel alarm
+            except AttributeError:
+                # Windows doesn't support SIGALRM, use direct call
+                submissions = self.edgar.get_submissions(cik=cik)
+            
+            result = {
+                "cik": cik,
+                "name": submissions.get("name", ""),
+                "tickers": submissions.get("tickers", []),
+                "sic": submissions.get("sic", ""),
+                "sic_description": submissions.get("sicDescription", "")
+            }
+            
+            # Cache the result
+            self._set_cache(cache_key, result)
+            return result
+        except TimeoutError:
+            print(f"Timeout getting company info for CIK: {cik}")
+            return None
+        except Exception as e:
+            print(f"Error getting company info: {e}")
+            return None
+    
+    def get_company_filings(self, cik, form_types=None):
+        """
+        Get all company filing documents with caching
+        
+        Args:
+            cik (str): Company CIK code
+            form_types (list): List of form types, e.g., ['10-K', '10-Q'], None for all types
+            
+        Returns:
+            list: List of filing documents
+        """
+        if not self.edgar:
+            print("sec_edgar_api library not installed")
+            return []
+        
+        # Check cache first (cache all filings, filter later)
+        cache_key = f"filings_{cik}"
+        cached = self._get_cached(cache_key)
+        
+        if not cached:
+            try:
+                # Add timeout wrapper
+                import signal
+                
+                def timeout_handler(signum, frame):
+                    raise TimeoutError("SEC API call timeout")
+                
+                try:
+                    signal.signal(signal.SIGALRM, timeout_handler)
+                    signal.alarm(30)
+                    submissions = self.edgar.get_submissions(cik=cik)
+                    signal.alarm(0)
+                except AttributeError:
+                    # Windows fallback
+                    submissions = self.edgar.get_submissions(cik=cik)
+                
+                # Extract filing information
+                filings = []
+                recent = submissions.get("filings", {}).get("recent", {})
+                
+                # Get data from each field
+                form_types_list = recent.get("form", [])
+                filing_dates = recent.get("filingDate", [])
+                accession_numbers = recent.get("accessionNumber", [])
+                primary_documents = recent.get("primaryDocument", [])
+                
+                # Iterate through all filings
+                for i in range(len(form_types_list)):
+                    filing_date = filing_dates[i] if i < len(filing_dates) else ""
+                    accession_number = accession_numbers[i] if i < len(accession_numbers) else ""
+                    primary_document = primary_documents[i] if i < len(primary_documents) else ""
+                    
+                    filing = {
+                        "form_type": form_types_list[i],
+                        "filing_date": filing_date,
+                        "accession_number": accession_number,
+                        "primary_document": primary_document
+                    }
+                    
+                    filings.append(filing)
+                
+                # Cache all filings
+                self._set_cache(cache_key, filings)
+                cached = filings
+                
+            except TimeoutError:
+                print(f"Timeout getting company filings for CIK: {cik}")
+                return []
+            except Exception as e:
+                print(f"Error getting company filings: {e}")
+                return []
+        
+        # Filter by form type if specified
+        if form_types:
+            return [f for f in cached if f.get("form_type") in form_types]
+        return cached
+    
+    def get_company_facts(self, cik):
+        """
+        Get all company financial facts data with caching and timeout
+        
+        Args:
+            cik (str): Company CIK code
+            
+        Returns:
+            dict: Company financial facts data
+        """
+        if not self.edgar:
+            print("sec_edgar_api library not installed")
+            return {}
+        
+        # Check cache first
+        cache_key = f"facts_{cik}"
+        cached = self._get_cached(cache_key)
+        if cached:
+            return cached
+            
+        try:
+            # Add timeout wrapper
+            import signal
+            
+            def timeout_handler(signum, frame):
+                raise TimeoutError("SEC API call timeout")
+            
+            try:
+                signal.signal(signal.SIGALRM, timeout_handler)
+                signal.alarm(45)  # 45 seconds for facts (larger dataset)
+                facts = self.edgar.get_company_facts(cik=cik)
+                signal.alarm(0)
+            except AttributeError:
+                # Windows fallback
+                facts = self.edgar.get_company_facts(cik=cik)
+            
+            # Cache the result
+            self._set_cache(cache_key, facts)
+            return facts
+        except TimeoutError:
+            print(f"Timeout getting company facts for CIK: {cik}")
+            return {}
+        except Exception as e:
+            print(f"Error getting company facts: {e}")
+            return {}
+    
+    def get_financial_data_for_period(self, cik, period):
+        """
+        Get financial data for a specific period (supports annual and quarterly)
+        
+        Args:
+            cik (str): Company CIK code
+            period (str): Period in format 'YYYY' or 'YYYYQX' (e.g., '2025' or '2025Q3')
+            
+        Returns:
+            dict: Financial data dictionary
+        """
+        if not self.edgar:
+            print("sec_edgar_api library not installed")
+            return {}
+            
+        try:
+            # Get company financial facts
+            facts = self.get_company_facts(cik)
+            
+            if not facts:
+                return {}
+            
+            # Extract us-gaap and ifrs-full financial data (20-F may use IFRS)
+            us_gaap = facts.get("facts", {}).get("us-gaap", {})
+            ifrs_full = facts.get("facts", {}).get("ifrs-full", {})
+            
+            # Define financial metrics and their XBRL tags
+            # Include multiple possible tags to improve match rate (including US-GAAP and IFRS tags)
+            financial_metrics = {
+                "total_revenue": ["Revenues", "RevenueFromContractWithCustomerExcludingAssessedTax", "RevenueFromContractWithCustomerIncludingAssessedTax", "SalesRevenueNet", "RevenueFromContractWithCustomer", "Revenue"],
+                "net_income": ["NetIncomeLoss", "ProfitLoss", "NetIncome", "ProfitLossAttributableToOwnersOfParent"],
+                "earnings_per_share": ["EarningsPerShareBasic", "EarningsPerShare", "BasicEarningsPerShare", "BasicEarningsLossPerShare"],
+                "operating_expenses": ["OperatingExpenses", "OperatingCostsAndExpenses", "OperatingExpensesExcludingDepreciationAndAmortization", "CostsAndExpenses", "GeneralAndAdministrativeExpense", "CostOfRevenue", "ResearchAndDevelopmentExpense", "SellingAndMarketingExpense"],
+                "operating_cash_flow": ["NetCashProvidedByUsedInOperatingActivities", "NetCashProvidedUsedInOperatingActivities", "NetCashFlowsFromUsedInOperatingActivities", "CashFlowsFromUsedInOperatingActivities"],
+            }
+            
+            # Store result
+            result = {"period": period}
+            
+            # Determine target form types to search
+            if 'Q' in period:
+                # Quarterly data, mainly search 10-Q (20-F usually doesn't have quarterly reports)
+                target_forms = ["10-Q"]
+                target_forms_annual = ["10-K", "20-F"]  # for fallback
+                year = int(period.split('Q')[0])
+                quarter = period.split('Q')[1]
+            else:
+                # Annual data, search 10-K and 20-F annual forms
+                target_forms = ["10-K", "20-F"]
+                target_forms_annual = target_forms
+                year = int(period)
+                quarter = None
+            
+            # Detect if company uses 20-F (foreign filer)
+            is_20f_filer = False
+            all_filings = self.get_company_filings(cik)
+            if all_filings:
+                form_types_used = set(f.get('form_type', '') for f in all_filings[:20])
+                if '20-F' in form_types_used and '10-K' not in form_types_used:
+                    is_20f_filer = True
+            
+            # Get company filings to find accession number and primary document
+            filings = self.get_company_filings(cik, form_types=target_forms)
+            filings_map = {}  # Map: form_year -> {accession_number, primary_document, filing_date, form_type}
+            
+            # Build filing map for quick lookup
+            for filing in filings:
+                form_type = filing.get("form_type", "")
+                filing_date = filing.get("filing_date", "")
+                accession_number = filing.get("accession_number", "")
+                primary_document = filing.get("primary_document", "")
+                
+                if filing_date and accession_number:
+                    # Extract year from filing_date (format: YYYY-MM-DD)
+                    file_year = int(filing_date[:4]) if len(filing_date) >= 4 else 0
+                    
+                    # Store filing if it matches the period year
+                    # For 20-F, also check year-1 (fiscal year may differ from filing year)
+                    if file_year == year or (is_20f_filer and form_type == '20-F' and file_year in [year - 1, year + 1]):
+                        key = f"{form_type}_{file_year}"
+                        if key not in filings_map:
+                            filings_map[key] = {
+                                "accession_number": accession_number,
+                                "primary_document": primary_document,
+                                "form_type": form_type,
+                                "filing_date": filing_date,
+                                "file_year": file_year
+                            }
+            
+            # Iterate through each financial metric
+            for metric_key, metric_tags in financial_metrics.items():
+                # Support multiple possible tags
+                for metric_tag in metric_tags:
+                    # Search both US-GAAP and IFRS tags
+                    # For 20-F filers, prioritize IFRS
+                    metric_data = None
+                    data_source = None
+                    
+                    if is_20f_filer:
+                        # Check IFRS first for 20-F filers
+                        if metric_tag in ifrs_full:
+                            metric_data = ifrs_full[metric_tag]
+                            data_source = "ifrs-full"
+                        elif metric_tag in us_gaap:
+                            metric_data = us_gaap[metric_tag]
+                            data_source = "us-gaap"
+                    else:
+                        # Check US-GAAP first for 10-K filers
+                        if metric_tag in us_gaap:
+                            metric_data = us_gaap[metric_tag]
+                            data_source = "us-gaap"
+                        elif metric_tag in ifrs_full:
+                            metric_data = ifrs_full[metric_tag]
+                            data_source = "ifrs-full"
+                    
+                    if metric_data:
+                        units = metric_data.get("units", {})
+                        
+                        # Find USD unit data (supports USD and USD/shares)
+                        usd_data = None
+                        if "USD" in units:
+                            usd_data = units["USD"]
+                        elif "USD/shares" in units and metric_key == "earnings_per_share":
+                            # EPS uses USD/shares unit
+                            usd_data = units["USD/shares"]
+                        
+                        if usd_data:
+                            # Try exact match first, then loose match
+                            matched_entry = None
+                            
+                            # Search for data in the specified period
+                            for entry in usd_data:
+                                form = entry.get("form", "")
+                                fy = entry.get("fy", 0)
+                                fp = entry.get("fp", "")
+                                end_date = entry.get("end", "")
+                                
+                                if not end_date or len(end_date) < 4:
+                                    continue
+                                    
+                                entry_year = int(end_date[:4])
+                                
+                                # Check if form type matches
+                                if form in target_forms:
+                                    if quarter:
+                                        # Quarterly data match
+                                        if entry_year == year and fp == f"Q{quarter}":
+                                            # If already matched, compare end date, choose the latest
+                                            if matched_entry:
+                                                if entry.get("end", "") > matched_entry.get("end", ""):
+                                                    matched_entry = entry
+                                            else:
+                                                matched_entry = entry
+                                    else:
+                                        # Annual data match - prioritize fiscal year (fy) field
+                                        # Strategy 1: Exact match by fiscal year
+                                        if fy == year and (fp == "FY" or fp == "" or not fp):
+                                            # If already matched, compare end date, choose the latest
+                                            if matched_entry:
+                                                if entry.get("end", "") > matched_entry.get("end", ""):
+                                                    matched_entry = entry
+                                            else:
+                                                matched_entry = entry
+                                        # Strategy 2: Match by end date year (when fy not available or doesn't match)
+                                        elif not matched_entry and entry_year == year and (fp == "FY" or fp == "" or not fp):
+                                            matched_entry = entry
+                                        # Strategy 3: Allow fy to differ by 1 year (fiscal year vs calendar year mismatch)
+                                        elif not matched_entry and fy > 0 and abs(fy - year) <= 1 and (fp == "FY" or fp == "" or not fp):
+                                            matched_entry = entry
+                                        # Strategy 4: Enhanced matching for 20-F - check frame field and end date
+                                        elif not matched_entry and form == "20-F":
+                                            frame = entry.get("frame", "")
+                                            # Match if CY{year} in frame OR end date contains year OR fiscal year within range
+                                            if (f"CY{year}" in frame or 
+                                                (str(year) in end_date and len(end_date) >= 4 and end_date[:4] == str(year)) or
+                                                (fy > 0 and abs(fy - year) <= 1)):
+                                                # Additional check: prefer entries with FY period
+                                                if fp == "FY" or fp == "" or not fp:
+                                                    matched_entry = entry
+                            
+                            # If quarterly data not found, try finding from annual report (fallback strategy)
+                            if not matched_entry and quarter and target_forms_annual:
+                                for entry in usd_data:
+                                    form = entry.get("form", "")
+                                    end_date = entry.get("end", "")
+                                    fp = entry.get("fp", "")
+                                    
+                                    if form in target_forms_annual and end_date:
+                                        # Check if end date is within this quarter range
+                                        if str(year) in end_date and f"Q{quarter}" in fp:
+                                            matched_entry = entry
+                                            break
+                            
+                            # Apply matched data
+                            if matched_entry:
+                                result[metric_key] = matched_entry.get("val", 0)
+                                
+                                # Get form and accession info
+                                form_type = matched_entry.get("form", "")
+                                accn_from_facts = matched_entry.get('accn', '').replace('-', '')
+                                filed_date = matched_entry.get('filed', '')
+                                filed_year = int(filed_date[:4]) if filed_date and len(filed_date) >= 4 else year
+                                
+                                # Try to get accession_number and primary_document from filings
+                                # For 20-F, try multiple year keys since filing year may differ
+                                filing_info = None
+                                possible_keys = [f"{form_type}_{year}"]
+                                if form_type == "20-F":
+                                    possible_keys.extend([f"20-F_{filed_year}", f"20-F_{year-1}", f"20-F_{year+1}"])
+                                
+                                for filing_key in possible_keys:
+                                    if filing_key in filings_map:
+                                        filing_info = filings_map[filing_key]
+                                        break
+                                
+                                if filing_info:
+                                    # Use filing info from get_company_filings
+                                    accession_number = filing_info["accession_number"].replace('-', '')
+                                    primary_document = filing_info["primary_document"]
+                                    
+                                    # Generate complete source URL
+                                    if primary_document:
+                                        result["source_url"] = f"https://www.sec.gov/Archives/edgar/data/{cik}/{accession_number}/{primary_document}"
+                                    else:
+                                        result["source_url"] = f"https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK={cik}&type={form_type}&dateb=&owner=exclude&count=100"
+                                else:
+                                    # Fallback to company browse page if filing not found
+                                    result["source_url"] = f"https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK={cik}&type={form_type}&dateb=&owner=exclude&count=100"
+                                
+                                result["source_form"] = form_type
+                                result["data_source"] = data_source
+                                
+                                # Add detailed information
+                                result[f"{metric_key}_details"] = {
+                                    "tag": metric_tag,
+                                    "form": matched_entry.get("form", ""),
+                                    "fy": matched_entry.get("fy", 0),
+                                    "fp": matched_entry.get("fp", ""),
+                                    "val": matched_entry.get("val", 0),
+                                    "start": matched_entry.get("start", ""),
+                                    "end": matched_entry.get("end", ""),
+                                    "accn": matched_entry.get("accn", ""),
+                                    "filed": matched_entry.get("filed", ""),
+                                    "frame": matched_entry.get("frame", ""),
+                                    "data_source": data_source
+                                }
+                        
+                        # If data is found, break out of tag loop
+                        if metric_key in result:
+                            break
+            
+            return result
+        except Exception as e:
+            print(f"Error getting financial data for period {period}: {e}")
+            return {}
+

EasyReportDataMCP/financial_analyzer.py

@@ -0,0 +1,342 @@
+"""Financial Data Analysis Module"""
+
+from .edgar_client import EdgarDataClient
+from datetime import datetime
+import json
+
+
+class FinancialAnalyzer:
+    def __init__(self, user_agent="Juntao Peng Financial Report Metrics App ([email protected])"):
+        """
+        Initialize financial analyzer
+        
+        Args:
+            user_agent (str): User agent string for identifying request source
+        """
+        self.edgar_client = EdgarDataClient(user_agent)
+        
+    def search_company(self, company_input):
+        """
+        Search company information (by name, ticker, or CIK) - Optimized version
+        
+        Args:
+            company_input (str): Company name, ticker, or CIK
+            
+        Returns:
+            dict: Company information
+        """
+        # Strip whitespace
+        company_input = company_input.strip()
+        
+        # Strategy 1: If input is numeric and looks like CIK (8-10 digits), use fast CIK lookup
+        if company_input.isdigit() and len(company_input) >= 8:
+            # Normalize CIK to 10 digits
+            cik = company_input.zfill(10)
+            
+            # Try fast lookup first (from cached tickers)
+            basic_info = self.edgar_client.get_company_by_cik(cik)
+            
+            if basic_info:
+                # Fast path succeeded, now get detailed info
+                company_info = self.edgar_client.get_company_info(cik)
+                if company_info:
+                    return company_info
+                else:
+                    # Fallback to basic info if detailed fetch fails
+                    return {
+                        "cik": basic_info['cik'],
+                        "name": basic_info['name'],
+                        "tickers": [basic_info['ticker']] if basic_info.get('ticker') else [],
+                        "_source": "basic_cik_lookup"
+                    }
+            else:
+                # CIK not found in cache, try full API call
+                company_info = self.edgar_client.get_company_info(cik)
+                if company_info:
+                    return company_info
+                else:
+                    return {"error": "Company not found for specified CIK"}
+        
+        # Strategy 2: Check if it looks like a ticker (short uppercase)
+        input_length = len(company_input)
+        is_likely_ticker = input_length <= 5 and company_input.isupper()
+        
+        if is_likely_ticker:
+            # Try fast ticker lookup first
+            basic_info = self.edgar_client.get_company_by_ticker(company_input)
+            
+            if basic_info:
+                # Fast ticker lookup succeeded - return enriched basic info
+                return {
+                    "cik": basic_info['cik'],
+                    "name": basic_info['name'],
+                    "tickers": [basic_info['ticker']] if basic_info.get('ticker') else [],
+                    "ein": None,  # Not available in basic search
+                    "fiscal_year_end": None,  # Not available in basic search
+                    "sic_description": None,  # Not available in basic search
+                    "_source": "quick_ticker_search",
+                    "_note": "Basic info from ticker search. Use get_company_info for full details."
+                }
+        
+        # Strategy 3: General search by name/ticker
+        # This returns basic info: {cik, name, ticker}
+        basic_info = self.edgar_client.search_company_by_name(company_input)
+        
+        if not basic_info:
+            return {"error": "No matching company found"}
+        
+        # Strategy 4: Decide whether to fetch detailed info
+        # For ticker-like searches, return basic info quickly
+        if is_likely_ticker:
+            # Quick response with basic info
+            return {
+                "cik": basic_info['cik'],
+                "name": basic_info['name'],
+                "tickers": [basic_info['ticker']] if basic_info.get('ticker') else [],
+                "ein": None,
+                "fiscal_year_end": None,
+                "sic_description": None,
+                "_source": "quick_search",
+                "_note": "Basic info from ticker search. Use get_company_info for full details."
+            }
+        
+        # For name searches, fetch detailed info (worth the extra API call)
+        company_info = self.edgar_client.get_company_info(basic_info['cik'])
+        
+        if company_info:
+            return company_info
+        else:
+            # Fallback to basic info if detailed fetch fails
+            return {
+                "cik": basic_info['cik'],
+                "name": basic_info['name'],
+                "tickers": [basic_info['ticker']] if basic_info.get('ticker') else [],
+                "_source": "basic_search_fallback"
+            }
+    
+    def get_company_filings_list(self, cik, form_types=None):
+        """
+        Get company filings list
+        
+        Args:
+            cik (str): Company CIK
+            form_types (list): List of form types (default: ['10-K', '10-Q'])
+            
+        Returns:
+            list: Filings list
+        """
+        if form_types is None:
+            form_types = ['10-K', '10-Q']
+        filings = self.edgar_client.get_company_filings(cik, form_types)
+        return filings
+    
+    def extract_financial_metrics(self, cik, years=3):
+        """
+        Extract financial metrics for specified number of years
+        
+        Args:
+            cik (str): Company CIK
+            years (int): Number of years to extract, default is 3 years
+            
+        Returns:
+            list: List of financial data
+        """
+        financial_data = []
+        
+        # Step 1: Get company filings to determine what was actually filed
+        filings_10k = self.edgar_client.get_company_filings(cik, ['10-K'])
+        filings_20f = self.edgar_client.get_company_filings(cik, ['20-F'])
+        all_annual_filings = filings_10k + filings_20f
+        
+        if not all_annual_filings:
+            return []
+        
+        # Detect if company is a 20-F filer (foreign company)
+        is_20f_filer = len(filings_20f) > 0 and len(filings_10k) == 0
+        has_quarterly = False  # 20-F filers typically don't have quarterly reports
+        
+        # Step 2: Extract filing years from annual reports
+        # Use filing_date to determine the years we should query
+        filing_year_map = {}  # Map: filing_year -> list of filings
+        
+        for filing in all_annual_filings:
+            filing_date = filing.get('filing_date', '')
+            if filing_date and len(filing_date) >= 4:
+                try:
+                    file_year = int(filing_date[:4])
+                    if file_year not in filing_year_map:
+                        filing_year_map[file_year] = []
+                    filing_year_map[file_year].append(filing)
+                except ValueError:
+                    continue
+        
+        if not filing_year_map:
+            return []
+        
+        # Step 3: Sort years in descending order and take the most recent N years
+        sorted_years = sorted(filing_year_map.keys(), reverse=True)
+        target_years = sorted_years[:years]
+        
+        # Step 4: For each target year, we need to find the fiscal year from Company Facts
+        # Get company facts to map filing years to fiscal years
+        facts = self.edgar_client.get_company_facts(cik)
+        filing_to_fiscal_year = {}  # Map: filing_year -> fiscal_year
+        
+        if facts:
+            # Try to map filing years to fiscal years using Company Facts
+            for data_source in ["us-gaap", "ifrs-full"]:
+                if data_source in facts.get("facts", {}):
+                    source_data = facts["facts"][data_source]
+                    
+                    # Look for Revenue tag to get fiscal year mapping
+                    revenue_tags = ["Revenues", "RevenueFromContractWithCustomerExcludingAssessedTax", 
+                                   "Revenue", "RevenueFromContractWithCustomer"]
+                    
+                    for tag in revenue_tags:
+                        if tag in source_data:
+                            units = source_data[tag].get("units", {})
+                            if "USD" in units:
+                                for entry in units["USD"]:
+                                    form = entry.get("form", "")
+                                    fy = entry.get("fy", 0)
+                                    filed = entry.get("filed", "")  # Filing date
+                                    fp = entry.get("fp", "")
+                                    
+                                    # Map filing year to fiscal year
+                                    if form in ["10-K", "20-F"] and fy > 0 and filed and (fp == "FY" or not fp):
+                                        if len(filed) >= 10:  # Format: YYYY-MM-DD
+                                            try:
+                                                file_year = int(filed[:4])
+                                                # Store the mapping: filing_year -> fiscal_year
+                                                if file_year not in filing_to_fiscal_year:
+                                                    filing_to_fiscal_year[file_year] = fy
+                                            except ValueError:
+                                                continue
+                    break  # Found revenue tag, no need to check more
+        
+        # Step 5: Generate period list for target years
+        # For each year: FY -> Q4 -> Q3 -> Q2 -> Q1 (descending order)
+        # For 20-F filers: only FY (no quarterly data)
+        periods = []
+        for file_year in target_years:
+            # Try to get fiscal year from mapping, otherwise use filing year
+            fiscal_year = filing_to_fiscal_year.get(file_year, file_year)
+            
+            # First add annual data for this fiscal year
+            periods.append({
+                'period': str(fiscal_year),
+                'type': 'annual',
+                'fiscal_year': fiscal_year,
+                'filing_year': file_year
+            })
+            
+            # Only add quarterly data for 10-K filers (not for 20-F filers)
+            if not is_20f_filer:
+                # Then add quarterly data in descending order: Q4, Q3, Q2, Q1
+                for quarter in range(4, 0, -1):
+                    periods.append({
+                        'period': f"{fiscal_year}Q{quarter}",
+                        'type': 'quarterly',
+                        'fiscal_year': fiscal_year,
+                        'filing_year': file_year
+                    })
+        
+        # Step 6: Get financial data for each period
+        for idx, period_info in enumerate(periods):
+            period = period_info['period']
+            fiscal_year = period_info['fiscal_year']
+            
+            data = self.edgar_client.get_financial_data_for_period(cik, period)
+            
+            if data and "period" in data:
+                # Add fiscal year prefix for annual data
+                if period_info['type'] == 'annual':
+                    data["period"] = f"FY{fiscal_year}"
+                
+                # Add sequence number to maintain order
+                data["_sequence"] = idx
+                
+                financial_data.append(data)
+        
+        return financial_data
+    
+    def get_latest_financial_data(self, cik):
+        """
+        Get latest financial data
+        
+        Args:
+            cik (str): Company CIK
+            
+        Returns:
+            dict: Latest financial data
+        """
+        # Get latest filing year (supports 10-K and 20-F)
+        filings_10k = self.edgar_client.get_company_filings(cik, ['10-K'])
+        filings_20f = self.edgar_client.get_company_filings(cik, ['20-F'])
+        filings = filings_10k + filings_20f
+        
+        if not filings:
+            return {}
+        
+        # Get latest filing year
+        latest_filing_year = None
+        for filing in filings:
+            if 'filing_date' in filing and filing['filing_date']:
+                try:
+                    filing_year = int(filing['filing_date'][:4])
+                    if latest_filing_year is None or filing_year > latest_filing_year:
+                        latest_filing_year = filing_year
+                except ValueError:
+                    continue
+        
+        if latest_filing_year is None:
+            return {}
+        
+        # Get financial data for latest year
+        return self.edgar_client.get_financial_data_for_period(cik, str(latest_filing_year))
+    
+    def format_financial_data(self, financial_data):
+        """
+        Format financial data for display
+        
+        Args:
+            financial_data (dict or list): Financial data
+            
+        Returns:
+            dict or list: Formatted financial data
+        """
+        if isinstance(financial_data, list):
+            # Sort by _sequence to maintain correct order (FY -> Q4 -> Q3 -> Q2 -> Q1)
+            sorted_data = sorted(financial_data, key=lambda x: x.get("_sequence", 999))
+            formatted_data = []
+            for data in sorted_data:
+                formatted_data.append(self._format_single_financial_data(data))
+            return formatted_data
+        else:
+            return self._format_single_financial_data(financial_data)
+    
+    def _format_single_financial_data(self, data):
+        """
+        Format single financial data entry
+        
+        Args:
+            data (dict): Financial data
+            
+        Returns:
+            dict: Formatted financial data
+        """
+        formatted = data.copy()
+        
+        # Ensure all key fields exist, even if None
+        key_fields = ['total_revenue', 'net_income', 'earnings_per_share', 'operating_expenses', 'operating_cash_flow', 'source_url', 'source_form']
+        for key in key_fields:
+            if key not in formatted:
+                formatted[key] = None
+        
+        # No longer perform unit conversion, keep original values
+        # Format EPS, keep two decimal places
+        if 'earnings_per_share' in formatted and isinstance(formatted['earnings_per_share'], (int, float)):
+            formatted['earnings_per_share'] = round(formatted['earnings_per_share'], 2)
+            
+        return formatted
+

EasyReportDataMCP/mcp_server_sse.py

@@ -0,0 +1,615 @@
+"""
+MCP Server for Hugging Face Space Deployment
+Uses Server-Sent Events (SSE) transport for remote MCP access
+Fully compatible with MCP clients like Claude Desktop
+Returns clean JSON without emoji formatting
+"""
+
+from fastapi import FastAPI, Request, HTTPException
+from fastapi.responses import StreamingResponse, JSONResponse, HTMLResponse, FileResponse
+from fastapi.staticfiles import StaticFiles
+from fastapi.middleware.cors import CORSMiddleware
+from pydantic import BaseModel
+from typing import Dict, Any, List, Optional
+import json
+import asyncio
+from datetime import datetime
+from edgar_client import EdgarDataClient
+from financial_analyzer import FinancialAnalyzer
+import time
+import sys
+import signal
+import os
+from pathlib import Path
+from contextlib import contextmanager
+
+# Initialize FastAPI app
+app = FastAPI(
+    title="SEC Financial Report MCP Server API",
+    description="Model Context Protocol Server for SEC EDGAR Financial Data",
+    version="2.3.1"
+)
+
+# Server startup time for monitoring
+server_start_time = time.time()
+request_count = 0
+error_count = 0
+
+# Configure CORS for remote access
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+# Request tracking middleware with timeout protection
+@app.middleware("http")
+async def track_requests(request: Request, call_next):
+    global request_count, error_count
+    request_count += 1
+    start_time = time.time()
+    
+    try:
+        # Set a timeout for the entire request
+        response = await asyncio.wait_for(
+            call_next(request),
+            timeout=120.0  # 2 minutes total timeout
+        )
+        if response.status_code >= 400:
+            error_count += 1
+        return response
+    except asyncio.TimeoutError:
+        error_count += 1
+        print(f"Request timeout after {time.time() - start_time:.2f}s: {request.url.path}")
+        return JSONResponse(
+            status_code=504,
+            content={"error": "Request timeout", "message": "The request took too long to process"}
+        )
+    except Exception as e:
+        error_count += 1
+        print(f"Request error: {e}")
+        raise
+
+# Initialize EDGAR clients
+edgar_client = EdgarDataClient(
+    user_agent="Juntao Peng Financial Report Metrics App ([email protected])"
+)
+
+financial_analyzer = FinancialAnalyzer(
+    user_agent="Juntao Peng Financial Report Metrics App ([email protected])"
+)
+
+# Preload company tickers data on startup for better performance
+print("[Startup] Preloading company tickers data...")
+try:
+    edgar_client._load_company_tickers()
+    print("[Startup] Company tickers preloaded successfully")
+except Exception as e:
+    print(f"[Startup] Warning: Failed to preload company tickers: {e}")
+    print("[Startup] Will load on first request")
+
+
+# ==================== MCP Protocol Implementation ====================
+
+class MCPRequest(BaseModel):
+    jsonrpc: str = "2.0"
+    id: Optional[Any] = None
+    method: str
+    params: Optional[Dict[str, Any]] = None
+
+
+class MCPResponse(BaseModel):
+    jsonrpc: str = "2.0"
+    id: Optional[Any] = None
+    result: Optional[Any] = None
+    error: Optional[Dict[str, Any]] = None
+
+
+# MCP Tools Definition
+MCP_TOOLS = [
+    {
+        "name": "search_company",
+        "description": "Search for a company by name in SEC EDGAR database. Returns company CIK, name, and ticker symbol.",
+        "inputSchema": {
+            "type": "object",
+            "properties": {
+                "company_name": {
+                    "type": "string",
+                    "description": "Company name to search (e.g., 'Microsoft', 'Apple', 'Tesla')"
+                }
+            },
+            "required": ["company_name"]
+        }
+    },
+    {
+        "name": "get_company_info",
+        "description": "Get detailed company information including name, tickers, SIC code, and industry description.",
+        "inputSchema": {
+            "type": "object",
+            "properties": {
+                "cik": {
+                    "type": "string",
+                    "description": "Company CIK code (10-digit format, e.g., '0000789019')"
+                }
+            },
+            "required": ["cik"]
+        }
+    },
+    {
+        "name": "get_company_filings",
+        "description": "Get list of company SEC filings (10-K, 10-Q, 20-F, etc.) with filing dates and document links.",
+        "inputSchema": {
+            "type": "object",
+            "properties": {
+                "cik": {
+                    "type": "string",
+                    "description": "Company CIK code"
+                },
+                "form_types": {
+                    "type": "array",
+                    "items": {"type": "string"},
+                    "description": "Optional: Filter by form types (e.g., ['10-K', '10-Q'])"
+                }
+            },
+            "required": ["cik"]
+        }
+    },
+    {
+        "name": "get_financial_data",
+        "description": "Get financial data for a specific period including revenue, net income, EPS, operating expenses, and cash flow.",
+        "inputSchema": {
+            "type": "object",
+            "properties": {
+                "cik": {
+                    "type": "string",
+                    "description": "Company CIK code"
+                },
+                "period": {
+                    "type": "string",
+                    "description": "Period in format 'YYYY' for annual or 'YYYYQX' for quarterly (e.g., '2024', '2024Q3')"
+                }
+            },
+            "required": ["cik", "period"]
+        }
+    },
+    {
+        "name": "extract_financial_metrics",
+        "description": "Extract comprehensive financial metrics for multiple years including both annual and quarterly data. Returns data in chronological order (newest first).",
+        "inputSchema": {
+            "type": "object",
+            "properties": {
+                "cik": {
+                    "type": "string",
+                    "description": "Company CIK code"
+                },
+                "years": {
+                    "type": "integer",
+                    "description": "Number of recent years to extract (1-10, default: 3)",
+                    "minimum": 1,
+                    "maximum": 10,
+                    "default": 3
+                }
+            },
+            "required": ["cik"]
+        }
+    },
+    {
+        "name": "get_latest_financial_data",
+        "description": "Get the most recent financial data available for a company.",
+        "inputSchema": {
+            "type": "object",
+            "properties": {
+                "cik": {
+                    "type": "string",
+                    "description": "Company CIK code"
+                }
+            },
+            "required": ["cik"]
+        }
+    },
+    {
+        "name": "advanced_search_company",
+        "description": "Advanced search supporting both company name and CIK code. Automatically detects input type.",
+        "inputSchema": {
+            "type": "object",
+            "properties": {
+                "company_input": {
+                    "type": "string",
+                    "description": "Company name, ticker, or CIK code"
+                }
+            },
+            "required": ["company_input"]
+        }
+    }
+]
+
+
+@contextmanager
+def timeout_context(seconds):
+    """Context manager for timeout on Unix-like systems"""
+    def timeout_handler(signum, frame):
+        raise TimeoutError(f"Operation timeout after {seconds} seconds")
+    
+    # Only works on Unix-like systems
+    try:
+        old_handler = signal.signal(signal.SIGALRM, timeout_handler)
+        signal.alarm(seconds)
+        try:
+            yield
+        finally:
+            signal.alarm(0)
+            signal.signal(signal.SIGALRM, old_handler)
+    except (AttributeError, ValueError):
+        # Windows or signal not available
+        yield
+
+
+def execute_tool(tool_name: str, arguments: Dict[str, Any]) -> Dict[str, Any]:
+    """Execute MCP tool and return clean JSON result with enhanced timeout protection"""
+    try:
+        # Use context manager for timeout (60 seconds per tool)
+        with timeout_context(60):
+            if tool_name == "search_company":
+                result = edgar_client.search_company_by_name(arguments["company_name"])
+                if result:
+                    return {
+                        "type": "text",
+                        "text": json.dumps(result, ensure_ascii=False)
+                    }
+                else:
+                    return {
+                        "type": "text",
+                        "text": json.dumps({
+                            "error": f"No company found with name: {arguments['company_name']}"
+                        }, ensure_ascii=False)
+                    }
+            
+            elif tool_name == "get_company_info":
+                result = edgar_client.get_company_info(arguments["cik"])
+                if result:
+                    return {
+                        "type": "text",
+                        "text": json.dumps(result, ensure_ascii=False)
+                    }
+                else:
+                    return {
+                        "type": "text",
+                        "text": json.dumps({
+                            "error": f"No company found with CIK: {arguments['cik']}"
+                        }, ensure_ascii=False)
+                    }
+            
+            elif tool_name == "get_company_filings":
+                form_types = arguments.get("form_types")
+                result = edgar_client.get_company_filings(arguments["cik"], form_types)
+                if result:
+                    # Limit to 20 results
+                    limited_result = result[:20]
+                    return {
+                        "type": "text",
+                        "text": json.dumps({
+                            "total": len(result),
+                            "returned": len(limited_result),
+                            "filings": limited_result
+                        }, ensure_ascii=False)
+                    }
+                else:
+                    return {
+                        "type": "text",
+                        "text": json.dumps({
+                            "error": f"No filings found for CIK: {arguments['cik']}"
+                        }, ensure_ascii=False)
+                    }
+            
+            elif tool_name == "get_financial_data":
+                result = edgar_client.get_financial_data_for_period(arguments["cik"], arguments["period"])
+                if result and "period" in result:
+                    return {
+                        "type": "text",
+                        "text": json.dumps(result, ensure_ascii=False)
+                    }
+                else:
+                    return {
+                        "type": "text",
+                        "text": json.dumps({
+                            "error": f"No financial data found for CIK: {arguments['cik']}, Period: {arguments['period']}"
+                        }, ensure_ascii=False)
+                    }
+            
+            elif tool_name == "extract_financial_metrics":
+                years = arguments.get("years", 3)
+                if years < 1 or years > 10:
+                    return {
+                        "type": "text",
+                        "text": json.dumps({
+                            "error": "Years parameter must be between 1 and 10"
+                        }, ensure_ascii=False)
+                    }
+                
+                metrics = financial_analyzer.extract_financial_metrics(arguments["cik"], years)
+                if metrics:
+                    formatted = financial_analyzer.format_financial_data(metrics)
+                    return {
+                        "type": "text",
+                        "text": json.dumps({
+                            "periods": len(formatted),
+                            "data": formatted
+                        }, ensure_ascii=False)
+                    }
+                else:
+                    return {
+                        "type": "text",
+                        "text": json.dumps({
+                            "error": f"No financial metrics found for CIK: {arguments['cik']}"
+                        }, ensure_ascii=False)
+                    }
+            
+            elif tool_name == "get_latest_financial_data":
+                result = financial_analyzer.get_latest_financial_data(arguments["cik"])
+                if result and "period" in result:
+                    return {
+                        "type": "text",
+                        "text": json.dumps(result, ensure_ascii=False)
+                    }
+                else:
+                    return {
+                        "type": "text",
+                        "text": json.dumps({
+                            "error": f"No latest financial data found for CIK: {arguments['cik']}"
+                        }, ensure_ascii=False)
+                    }
+            
+            elif tool_name == "advanced_search_company" or tool_name == "advanced_search":
+                # Support both names for backward compatibility
+                result = financial_analyzer.search_company(arguments["company_input"])
+                if result.get("error"):
+                    return {
+                        "type": "text",
+                        "text": json.dumps({
+                            "error": result["error"]
+                        }, ensure_ascii=False)
+                    }
+                return {
+                    "type": "text",
+                    "text": json.dumps(result, ensure_ascii=False)
+                }
+            
+            else:
+                return {
+                    "type": "text",
+                    "text": json.dumps({
+                        "error": f"Unknown tool: {tool_name}"
+                    }, ensure_ascii=False)
+                }
+    
+    except Exception as e:
+        return {
+            "type": "text",
+            "text": json.dumps({
+                "error": f"Error executing {tool_name}: {str(e)}"
+            }, ensure_ascii=False)
+        }
+
+
+# ==================== MCP Endpoints ====================
+
+@app.post("/message")
+async def handle_mcp_message(request: MCPRequest):
+    """
+    Main MCP message handler
+    Supports: initialize, tools/list, tools/call
+    """
+    method = request.method
+    params = request.params or {}
+    
+    # Handle initialize
+    if method == "initialize":
+        return MCPResponse(
+            id=request.id,
+            result={
+                "protocolVersion": "2024-11-05",
+                "capabilities": {
+                    "tools": {}
+                },
+                "serverInfo": {
+                    "name": "sec-financial-data",
+                    "version": "2.3.1"
+                }
+            }
+        ).dict()
+    
+    # Handle tools/list
+    elif method == "tools/list":
+        return MCPResponse(
+            id=request.id,
+            result={
+                "tools": MCP_TOOLS
+            }
+        ).dict()
+    
+    # Handle tools/call
+    elif method == "tools/call":
+        tool_name = params.get("name")
+        arguments = params.get("arguments", {})
+        
+        if not tool_name:
+            return MCPResponse(
+                id=request.id,
+                error={
+                    "code": -32602,
+                    "message": "Missing tool name"
+                }
+            ).dict()
+        
+        result = execute_tool(tool_name, arguments)
+        
+        return MCPResponse(
+            id=request.id,
+            result={
+                "content": [result]
+            }
+        ).dict()
+    
+    else:
+        return MCPResponse(
+            id=request.id,
+            error={
+                "code": -32601,
+                "message": f"Method not found: {method}"
+            }
+        ).dict()
+
+
+@app.get("/sse")
+async def sse_endpoint(request: Request):
+    """
+    Server-Sent Events endpoint for MCP transport
+    Keeps connection alive and handles MCP messages
+    """
+    async def event_stream():
+        # Send initial endpoint message
+        init_message = {
+            "jsonrpc": "2.0",
+            "method": "endpoint",
+            "params": {
+                "endpoint": "/message"
+            }
+        }
+        yield f"data: {json.dumps(init_message)}\n\n"
+        
+        # Keep connection alive with optimized ping interval
+        try:
+            while True:
+                await asyncio.sleep(20)  # 20 seconds ping interval for stability
+                # Send ping to keep connection alive
+                ping_message = {
+                    "jsonrpc": "2.0",
+                    "method": "ping",
+                    "timestamp": datetime.now().isoformat()
+                }
+                yield f"data: {json.dumps(ping_message)}\n\n"
+        except asyncio.CancelledError:
+            pass
+    
+    return StreamingResponse(
+        event_stream(),
+        media_type="text/event-stream",
+        headers={
+            "Cache-Control": "no-cache, no-transform",
+            "Connection": "keep-alive",
+            "X-Accel-Buffering": "no",
+            "Content-Type": "text/event-stream"
+        }
+    )
+
+
+@app.get("/", response_class=HTMLResponse)
+async def root():
+    """Interactive landing page with tool testing functionality"""
+    # Get the path to the templates directory
+    current_dir = Path(__file__).parent
+    template_path = current_dir / "templates" / "index.html"
+    
+    # Read and return the HTML file
+    try:
+        with open(template_path, "r", encoding="utf-8") as f:
+            html_content = f.read()
+        return HTMLResponse(content=html_content)
+    except FileNotFoundError:
+        # Enhanced error message with debugging information
+        import os
+        debug_info = f"""
+        <h1>Error: Template not found</h1>
+        <h2>Debugging Information:</h2>
+        <p><strong>Looking for:</strong> {template_path.absolute()}</p>
+        <p><strong>Exists:</strong> {template_path.exists()}</p>
+        <p><strong>Current dir:</strong> {current_dir.absolute()}</p>
+        <h3>Directory contents:</h3>
+        <pre>{chr(10).join(os.listdir(current_dir))}</pre>
+        <h3>Fix:</h3>
+        <p>Ensure Dockerfile contains: <code>COPY templates/ templates/</code></p>
+        """
+        return HTMLResponse(content=debug_info, status_code=500)
+
+
+@app.get("/tools")
+async def list_tools():
+    """List all available MCP tools (for documentation)"""
+    return {"tools": MCP_TOOLS}
+
+
+@app.get("/health")
+async def health_check():
+    """Enhanced health check endpoint with diagnostics"""
+    uptime_seconds = time.time() - server_start_time
+    return {
+        "status": "healthy",
+        "server": "sec-financial-data",
+        "version": "2.3.1",
+        "protocol": "MCP",
+        "transport": "SSE",
+        "tools_count": len(MCP_TOOLS),
+        "uptime_seconds": round(uptime_seconds, 2),
+        "python_version": sys.version,
+        "request_count": request_count,
+        "error_count": error_count,
+        "error_rate": round(error_count / max(request_count, 1) * 100, 2),
+        "timestamp": datetime.now().isoformat()
+    }
+
+
+@app.get("/ready")
+async def readiness_check():
+    """Readiness check for load balancers"""
+    try:
+        # Quick validation that clients are initialized
+        if edgar_client and financial_analyzer:
+            return {"status": "ready", "timestamp": datetime.now().isoformat()}
+        else:
+            raise HTTPException(status_code=503, detail="Services not initialized")
+    except Exception as e:
+        raise HTTPException(status_code=503, detail=f"Not ready: {str(e)}")
+
+
+@app.api_route("/api/{path:path}", methods=["GET", "POST", "PUT", "DELETE"])
+async def redirect_old_api(path: str):
+    """Handle old REST API endpoints with helpful message"""
+    return JSONResponse(
+        status_code=404,
+        content={
+            "error": "API endpoint not found",
+            "message": "This server now uses the MCP (Model Context Protocol).",
+            "migration_guide": {
+                "old_endpoint": f"/api/{path}",
+                "new_method": "Use MCP protocol via POST /message",
+                "documentation": "Visit / for setup instructions",
+                "example": {
+                    "method": "POST",
+                    "url": "/message",
+                    "body": {
+                        "jsonrpc": "2.0",
+                        "id": 1,
+                        "method": "tools/call",
+                        "params": {
+                            "name": "advanced_search_company",
+                            "arguments": {"company_input": "Microsoft"}
+                        }
+                    }
+                }
+            },
+            "available_tools": "/tools",
+            "health_check": "/health"
+        }
+    )
+
+
+if __name__ == "__main__":
+    import uvicorn
+    uvicorn.run(
+        "mcp_server_sse:app",
+        host="0.0.0.0",
+        port=7860,
+        reload=True
+    )

app copy.py

@@ -0,0 +1,1922 @@
+import gradio as gr
+import os
+import datetime
+import re
+import pandas as pd
+from sqlalchemy import true
+from chatbot.chat_main import respond
+import globals as g
+from service.mysql_service import get_companys, insert_company, get_company_by_name
+from service.chat_service import get_analysis_report, get_stock_price_from_bailian, search_company, search_news, get_invest_suggest, chat_bot
+from service.company import check_company_exists
+from service.hf_upload import get_hf_files_with_links
+from MarketandStockMCP.news_quote_mcp import get_company_news, get_quote
+from EasyReportDataMCP.report_mcp import query_financial_data
+from service.three_year_table_tool import build_table_format
+from service.three_year_tool import  process_financial_data_with_metadata
+from service.tool_processor import get_stock_price
+
+get_companys_state = True
+# JavaScript代码用于读取和存储数据
+js_code = """
+function handleStorage(operation, key, value) {
+    if (operation === 'set') {
+        localStorage.setItem(key, value);
+        return `已存储: ${key} = ${value}`;
+    } else if (operation === 'get') {
+        let storedValue = localStorage.getItem(key);
+        if (storedValue === null) {
+            return `未找到键: ${key}`;
+        }
+        return `读取到: ${key} = ${storedValue}`;
+    } else if (operation === 'clear') {
+        localStorage.removeItem(key);
+        return `已清除: ${key}`;
+    } else if (operation === 'clearAll') {
+        localStorage.clear();
+        return '已清除所有数据';
+    }
+}
+"""
+custom_css = """
+/* 匹配所有以 gradio-container- 开头的类 */
+div[class^="gradio-container-"],
+div[class*=" gradio-container-"] {
+    -webkit-text-size-adjust: 100% !important;
+    line-height: 1.5 !important;
+    font-family: unset !important;
+    -moz-tab-size: 4 !important;
+    tab-size: 4 !important;
+}
+
+.company-list-container {
+    background-color: white;
+    border-radius: 0.5rem;
+    padding: 0.75rem;
+    margin-bottom: 0.75rem;
+    border: 1px solid #e5e7eb;
+    box-shadow: 0 1px 2px 0 rgba(0, 0, 0, 0.05);
+    width: 100%;
+}
+
+/* 隐藏单选框 */
+.company-list-container input[type="radio"] {
+    display: none;
+}
+
+/* 自定义选项样式 */
+.company-list-container label {
+    display: block;
+    padding: 0.75rem 1rem;
+    margin: 0.25rem 0;
+    border-radius: 0.375rem;
+    cursor: pointer;
+    transition: all 0.2s ease;
+    background-color: #f9fafb;
+    border: 1px solid #e5e7eb;
+    font-size: 1rem;
+    text-align: left;
+    width: 100%;
+    box-sizing: border-box;
+}
+
+/* 悬停效果 */
+.company-list-container label:hover {
+    background-color: #f3f4f6;
+    border-color: #d1d5db;
+}
+
+/* 选中效果 - 确保背景色充满整个选项 */
+.company-list-container input[type="radio"]:checked + span {
+    # background: #3b82f6 !important;
+    color: white !important;
+    font-weight: 600 !important;
+    display: block;
+    width: 100%;
+    height: 100%;
+    padding: 0.75rem 1rem;
+    margin: -0.75rem -1rem;
+    border-radius: 0.375rem;
+}
+
+.company-list-container span {
+    display: block;
+    padding: 0;
+    border-radius: 0.375rem;
+    width: 100%;
+}
+
+/* 确保每行只有一个选项 */
+.company-list-container .wrap {
+    display: block !important;
+}
+
+.company-list-container .wrap li {
+    display: block !important;
+    width: 100% !important;
+}
+label.selected {
+    background: #3b82f6 !important;
+    color: white !important;
+}
+"""
+
+# 全局变量用于存储公司映射关系
+companies_map = {}
+
+# 根据公司名称获取股票代码的函数
+def get_stock_code_by_company_name(company_name):
+    """根据公司名称获取股票代码"""
+    if company_name in companies_map and "CODE" in companies_map[company_name]:
+        return companies_map[company_name]["CODE"]
+    return ""  # 默认返回
+
+# 创建一个简单的函数来获取公司列表
+def get_company_list_choices():
+    choices = []
+    print(f"Getting init add company list choices...{get_companys_state}")
+    if not get_companys_state:
+        return gr.update(choices=choices)
+    try:
+        companies_data = get_companys()
+        print(f"Getting init add company list choices...companies_data: {companies_data}")
+        if isinstance(companies_data, pd.DataFrame) and not companies_data.empty:
+            choices = [str(row.get('company_name', 'Unknown')) for _, row in companies_data.iterrows()]
+        else:
+            choices = []
+    except:
+        choices = []
+    
+    return gr.update(choices=choices)
+
+# Sidebar service functions
+
+# 处理公司点击事件的函数
+def handle_company_click(company_name):
+    """处理公司点击事件，先判断是否已经入库，如果没有则进行入库操作，然后刷新公司列表"""
+    print(f"Handling click for company: {company_name}")
+    
+    # 1. 判断是否已经入库
+    if not check_company_exists(company_name):
+        # 2. 如果没有入库，则进行入库操作
+        # 获取股票���码（如果有的话）
+        stock_code = companies_map.get(company_name, {}).get("CODE", "Unknown")
+        print(f"Inserting company {company_name} with code {stock_code}")
+        
+        # 插入公司到数据库
+        success = insert_company(company_name, stock_code)
+        if success:
+            print(f"Successfully inserted company: {company_name}")
+            # 直接更新companies_map，而不是重新加载整个映射
+            companies_map[company_name] = {"NAME": company_name, "CODE": stock_code}
+            # 使用Gradio的成功提示
+            gr.Info(f"Successfully added company: {company_name}")
+            # 返回True表示添加成功，需要刷新列表
+            return True
+        else:
+            print(f"Failed to insert company: {company_name}")
+            # 使用Gradio的错误提示
+            gr.Error(f"Failed to insert company: {company_name}")
+            return False
+    else:
+        print(f"Company {company_name} already exists in database")
+        # 使用Gradio的警告提示
+        gr.Warning(f"Company '{company_name}' already exists")
+    
+    # 3. 返回成功响应
+    return None
+
+def get_company_list_html(selected_company=""):
+    try:
+        # 从数据库获取所有公司
+        companies_data = get_companys()
+        # 检查是否为错误信息
+        if isinstance(companies_data, str):
+            if "查询执行失败" in companies_data:
+                return "<div class='text-red-500'>获取公司列表失败</div>"
+            else:
+                # 如果是字符串但不是错误信息，可能需要特殊处理
+                return ""
+        
+        # 检查是否为DataFrame且为空
+        if not isinstance(companies_data, pd.DataFrame) or companies_data.empty:
+            return ""
+        
+        # 生成HTML列表
+        html_items = []
+        for _, row in companies_data.iterrows():
+            company_name = row.get('company_name', 'Unknown')
+            # 根据是否选中添加不同的样式类
+            css_class = "company-item"
+            if company_name == selected_company:
+                css_class += " selected-company"
+            # 使用button元素来确保可点击性
+            html_items.append(f'<button class="{css_class}" data-company="{company_name}" style="width:100%; text-align:left; border:none; background:none;">{company_name}</button>')
+        
+        return "\n".join(html_items)
+    except Exception as e:
+        return f"<div class='text-red-500'>生成公司列表失败: {str(e)}</div>"
+
+def initialize_company_list(selected_company=""):
+    return get_company_list_html(selected_company)
+
+def refresh_company_list(selected_company=""):
+    """刷新公司列表，返回最新的HTML内容，带loading效果"""
+    # 先返回loading状态
+    loading_html = '''
+    <div style="display: flex; justify-content: center; align-items: center; height: 100px;">
+        <div class="loading-spinner" style="width: 24px; height: 24px; border: 3px solid #f3f3f3; border-top: 3px solid #3498db; border-radius: 50%; animation: spin 1s linear infinite;"></div>
+        <style>
+            @keyframes spin {
+                0% { transform: rotate(0deg); }
+                100% { transform: rotate(360deg); }
+            }
+        </style>
+    </div>
+    '''
+    yield loading_html
+    
+    # 然后返回实际的数据
+    yield get_company_list_html(selected_company)
+
+# 新增函数：处理公司选择事件
+def select_company(company_name):
+    """处理公司选择事件，更新全局状态并返回更新后的公司列表"""
+    # 更新全局变量
+    g.SELECT_COMPANY = company_name if company_name else ""
+    # 对于Radio组件，我们只需要返回更新后的选项列表
+    try:
+        companies_data = get_companys()
+        if isinstance(companies_data, pd.DataFrame) and not companies_data.empty:
+            choices = [str(row.get('company_name', 'Unknown')) for _, row in companies_data.iterrows()]
+        else:
+            choices = []
+    except:
+        choices = []
+    return gr.update(choices=choices, value=company_name)
+
+def initialize_companies_map():
+    """初始化 companies_map 字典"""
+    global companies_map
+    companies_map = {}  # 清空之前的映射
+    
+    print("Initializing companies map...")
+    
+    try:
+        # 获取预定义的公司列表
+        predefined_companies = [
+            { "NAME": "Alibaba", "CODE": "BABA" },
+            { "NAME": "阿里巴巴-W", "CODE": "09988" },
+            { "NAME": "NVIDIA", "CODE": "NVDA" },
+            { "NAME": "Amazon", "CODE": "AMZN" },
+            { "NAME": "Intel", "CODE": "INTC" },
+            { "NAME": "Meta", "CODE": "META" },
+            { "NAME": "Google", "CODE": "GOOGL" },
+            { "NAME": "Apple", "CODE": "AAPL" },
+            { "NAME": "Tesla", "CODE": "TSLA" },
+            { "NAME": "AMD", "CODE": "AMD" },
+            { "NAME": "Microsoft", "CODE": "MSFT" },
+            { "NAME": "ASML", "CODE": "ASML" }
+        ]
+       
+        # 将预定义公司添加到映射中
+        for company in predefined_companies:
+            companies_map[company["NAME"]] = {"NAME": company["NAME"], "CODE": company["CODE"]}
+       
+        print(f"Predefined companies added: {len(predefined_companies)}")
+        
+        # 从数据库获取公司数据
+        companies_data = get_companys()
+        # companies_data = window.cachedCompanies or []
+
+
+        print(f"Companies data from DB: {companies_data}")
+        
+        # 如果数据库中有公司数据，则添加到映射中（去重）
+        if isinstance(companies_data, pd.DataFrame) and not companies_data.empty:
+            print(f"Adding {len(companies_data)} companies from database")
+            for _, row in companies_data.iterrows():
+                company_name = row.get('company_name', 'Unknown')
+                stock_code = row.get('stock_code', '')
+                
+                # 确保company_name和stock_code都是字符串类型
+                company_name = str(company_name) if company_name is not None else 'Unknown'
+                stock_code = str(stock_code) if stock_code is not None else ''
+                
+                # 检查是否已存在于映射中（通过股票代码判断）
+                is_duplicate = False
+                for existing_company in companies_map.values():
+                    if existing_company["CODE"] == stock_code:
+                        is_duplicate = True
+                        break
+                
+                # 如果不重复，则添加到映射中
+                if not is_duplicate:
+                    companies_map[company_name] = {"NAME": company_name, "CODE": stock_code}
+                    # print(f"Added company: {company_name}")
+        else:
+            print("No companies found in database")
+            
+        print(f"Final companies map: {companies_map}")
+    except Exception as e:
+        # 错误处理
+        print(f"Error initializing companies map: {str(e)}")
+        pass
+
+# Sidebar company selector functions
+def update_company_choices(user_input: str):
+    """更新公司选择列表"""
+    # 第一次 yield：立即显示 modal + loading 提示
+    yield gr.update(
+        choices=["Searching..."],
+        visible=True
+    ), gr.update(visible=False, value="")  # 添加第二个返回值
+    
+    # 第二次：执行耗时操作（调用 LLM）
+    choices = search_company(user_input)  # 这是你原来的同步函数
+    
+    # 检查choices是否为错误信息
+    if len(choices) > 0 and isinstance(choices[0], str) and not choices[0].startswith("Searching"):
+        # 如果是错误信息或非正常格式，显示提示消息
+        error_message = choices[0] if len(choices) > 0 else "未知错误"
+        # 使用Ant Design风格的错误提示
+        error_html = f'''
+        <div class="ant-message ant-message-error" style="
+            position: fixed;
+            top: 20px;
+            left: 50%;
+            transform: translateX(-50%);
+            z-index: 10000;
+            padding: 10px 16px;
+            border-radius: 4px;
+            background: #fff;
+            box-shadow: 0 4px 12px rgba(0,0,0,0.15);
+            display: flex;
+            align-items: center;
+            pointer-events: all;
+            animation: messageFadeIn 0.3s ease-in-out;
+        ">
+            <div style="
+                width: 16px;
+                height: 16px;
+                background: #ff4d4f;
+                border-radius: 50%;
+                position: relative;
+                margin-right: 8px;
+            "></div>
+            <span>{error_message}</span>
+        </div>
+        <script>
+            setTimeout(function() {{
+                var msg = document.querySelector('.ant-message-error');
+                if (msg) {{
+                    msg.style.animation = 'messageFadeOut 0.3s ease-in-out';
+                    setTimeout(function() {{ msg.remove(); }}, 3000);
+                }}
+            }}, 3000);
+        </script>
+        '''
+        yield gr.update(choices=["No results found"], visible=True), gr.update(visible=True, value=error_html)
+    else:
+        # 第三次：更新为真实结果
+        yield gr.update(
+            choices=choices,
+            visible=len(choices) > 0
+        ), gr.update(visible=False, value="")
+
+def add_company(selected, current_list):
+    """添加选中的公司"""
+    if selected == "No results found":
+        return gr.update(visible=False), current_list, gr.update(visible=False, value="")
+    if selected:
+        # print(f"Selected company====: {selected}")
+        # 从选择的文本中提取公司名称和股票代码
+        # 假设格式为 "公司名称 (股票代码)"
+        selected_clean = selected.strip()
+        match = re.match(r"^(.+?)\s*\(([^)]+)\)$", selected_clean)
+        if match:
+            company_name = match.group(1)
+            stock_code = match.group(2)
+        elif companies_map.get(selected_clean):
+            company_name = selected_clean
+            stock_code = companies_map[selected_clean]["CODE"]
+        else:
+            company_name = selected_clean
+            stock_code = "Unknown"
+        
+        # print(f"Company name: {company_name}, Stock code: {stock_code}")
+        # print(f"Company exists: {check_company_exists(company_name)}")
+        
+        if not check_company_exists(company_name):
+            # 入库
+            success = insert_company(company_name, stock_code)
+            if success:
+                # 从数据库获取更新后的公司列表
+                try:
+                    companies_data = get_companys()
+                    if isinstance(companies_data, pd.DataFrame) and not companies_data.empty:
+                        updated_list = [str(row.get('company_name', 'Unknown')) for _, row in companies_data.iterrows()]
+                    else:
+                        updated_list = []
+                except:
+                    updated_list = []
+                
+                # 添加默认公司选项
+                if not updated_list:
+                    updated_list = ['Alibaba', '腾讯控股', 'Tencent', '阿里巴巴-W', 'Apple']
+                
+                # 成功插入后清除状态消息，并更新Radio组件的选项，同时默认选中刚添加的公司
+                # 通过设置value参数，会自动触发change事件来加载数据
+                return gr.update(visible=False), gr.update(choices=updated_list, value=company_name), gr.update(visible=False, value="")
+            else:
+                # 插入失败显示错误消息，使用Gradio内置的错误提示
+                gr.Error("插入公司失败")
+                return gr.update(visible=False), current_list, gr.update(visible=False, value="")
+        else:
+            # 公司已存在，使用Gradio内置的警告消息
+            gr.Warning(f"公司 '{company_name}' 已存在")
+            return gr.update(visible=False), current_list, gr.update(visible=False, value="")
+        
+    return gr.update(visible=False), current_list, gr.update(visible=False, value="")
+
+# Sidebar report section functions
+# 创建一个全局变量来存储公司按钮组件
+company_buttons = {}
+
+def create_company_buttons():
+    """创建公司按钮组件"""
+    # 确保companies_map已被初始化
+    if not companies_map:
+        initialize_companies_map()
+    
+    # 显示companies_map中的公司列表
+    companies = list(companies_map.keys())
+    
+    # 添加调试信息
+    print(f"Companies in map: {companies}")
+    
+    # 清空之前的按钮
+    company_buttons.clear()
+    
+    if not companies:
+        # 如果没有公司，返回一个空的列
+        with gr.Column():
+            gr.Markdown("暂无公司数据")
+    else:
+        # 使用Gradio按钮组件创建公司列表
+        with gr.Column(elem_classes=["home-company-list"]):
+            # 按每行两个公司进行分组
+            for i in range(0, len(companies), 2):
+                # 检查是否是最后一行且只有一个元素
+                if i + 1 < len(companies):
+                    # 有两个元素
+                    with gr.Row(elem_classes=["home-company-item-box"]):
+                        btn1 = gr.Button(companies[i], elem_classes=["home-company-item", "gradio-button"])
+                        btn2 = gr.Button(companies[i + 1], elem_classes=["home-company-item", "gradio-button"])
+                        # 保存按钮引用
+                        company_buttons[companies[i]] = btn1
+                        company_buttons[companies[i + 1]] = btn2
+                else:
+                    # 只有一个元素
+                    with gr.Row(elem_classes=["home-company-item-box", "single-item"]):
+                        btn = gr.Button(companies[i], elem_classes=["home-company-item", "gradio-button"])
+                        # 保存按钮引用
+                        company_buttons[companies[i]] = btn
+    
+    # 返回按钮字典
+    return company_buttons
+def update_report_section(selected_company, report_data, stock_code):
+    """根据选中的公司更新报告部分"""
+    print(f"Updating report （报告部分）: {selected_company}")  # 添加调试信息
+
+    if selected_company == "" or selected_company is None or selected_company == "Unknown":
+        # 没有选中的公司，显示公司列表
+        # html_content = get_initial_company_list_content()
+        # 暂时返回空内容，稍后会用Gradio组件替换
+        html_content = ""
+        return gr.update(value=html_content, visible=True)
+    else:
+        # 有选中的公司，显示相关报告
+        # try:
+        #     # 尝试从Hugging Face获取文件列表
+        #     report_data = get_hf_files_with_links("JC321/files-world")
+        # except Exception as e:
+        #     # 如果获取失败，使用模拟数据并显示错误消息
+        #     print(f"获取Hugging Face文件列表失败: {str(e)}")
+        #     report_data = []
+        stock_code = get_stock_code_by_company_name(selected_company)
+        report_data = query_financial_data(stock_code, "5-Year")
+        # report_data = process_financial_data_with_metadata(financial_metrics_pre)
+        
+        html_content = '<div class="report-list-box bg-white">'
+        html_content += '<div class="report-list-title bg-white card-title  left-card-title" style="border-bottom: 1px solid #e3e3e6 !important;"><h3>Financial Reports</h3></div>'
+        for report in report_data:
+            html_content += f'''
+            <div class="report-item bg-white hover:bg-blue-50 cursor-pointer" onclick="window.open('{report['source_url']}', '_blank')">
+                <div class="report-item-content">
+                    <span class="text-gray-800">{report['period']}-{stock_code}-{report['source_form']}</span>
+                    <svg xmlns="http://www.w3.org/2000/svg" width="12" height="12" class="text-blue-500" viewBox="0 0 20 20" fill="currentColor">
+                        <path fill-rule="evenodd" d="M12.586 4.586a2 2 0 112.828 2.828l-3 3a2 2 0 01-2.828 0 1 1 0 10-1.414 1.414 4 4 0 005.656 0l3-3a4 4 0 00-5.656-5.656l-1.5 1.5a1 1 0 101.414 1.414l-1.5-1.5zm-5 5a2 2 0 012.828 0 1 1 0 101.414-1.414 4 4 0 00-5.656 0l-3 3a4 4 0 105.656 5.656l1.5-1.5a1 1 0 10-1.414-1.414l-1.5 1.5a2 2 0 11-2.828-2.828l3-3z" clip-rule="evenodd" />
+                    </svg>
+                </div>
+            </div>
+            '''
+        
+        html_content += f'<div class="pdf-footer mt-3"><span class="text-xs text-gray-500">共{len(report_data)}份报告</span></div>'
+        html_content += '</div>'
+        
+        return gr.update(value=html_content, visible=True)
+def update_news_section(selected_company):
+    """根据选中的公司更新报告部分"""
+    html_content = ""
+    if selected_company == "" or selected_company is None:
+        # 没有选中的公司，显示公司列表
+        # html_content = get_initial_company_list_content()
+        # 暂时返回空内容，稍后会用Gradio组件替换
+        return gr.update(value=html_content, visible=True)
+    else:
+        try:
+            stock_code = get_stock_code_by_company_name(selected_company)
+            report_data = get_company_news(stock_code, None, None)
+            # print(f"新闻列表: {report_data['articles']}")
+            # report_data = search_news(selected_company)
+            if (report_data['articles']):
+                report_data = report_data['articles']
+                news_html = "<div class='news-list-box bg-white'>"
+                news_html += '<div class="report-list-title bg-white card-title  left-card-title" style="border-bottom: 1px solid #e3e3e6 !important;"><h3>News</h3></div>'
+                from datetime import datetime
+                
+                for news in report_data:
+                    published_at = news['published']
+
+                    # 解析 ISO 8601 时间字符串（注意：strptime 不直接支持 'Z'，需替换或使用 fromisoformat）
+                    dt = datetime.fromisoformat(published_at.replace("Z", "+00:00"))
+
+                    # 格式化为 YYYY.MM.DD
+                    formatted_date = dt.strftime("%Y.%m.%d")
+                    news_html += f'''
+                    <div class="news-item bg-white hover:bg-blue-50 cursor-pointer" onclick="window.open('{news['url']}', '_blank')">
+                        <div class="news-item-content">
+                            <span class="text-xs text-gray-500">[{formatted_date}]</span>
+                            <span class="text-gray-800">{news['headline']}</span>
+                        </div>
+                    </div>
+                    '''
+                news_html += f'<div class="pdf-footer mt-3"><span class="text-xs text-gray-500">共{len(report_data)}条新闻</span></div>'
+                news_html += '</div>'
+                html_content += news_html
+        except Exception as e:
+            print(f"Error updating report section: {str(e)}")
+        
+        return gr.update(value=html_content, visible=True)
+
+# Component creation functions
+def create_header():
+    """创建头部组件"""
+    # 获取当前时间
+    current_time = datetime.datetime.now().strftime("%B %d, %Y - Market Data Updated Today")
+    
+    with gr.Row(elem_classes=["header"]):
+        # 左侧：图标和标题
+        with gr.Column(scale=8):
+            # 使用圆柱体SVG图标表示数据库
+            gr.HTML('''
+                <div class="top-logo-box">
+                    <svg xmlns="http://www.w3.org/2000/svg" width="32" height="32" viewBox="0 0 48 48">
+                        <g fill="none" stroke="#fff" stroke-linecap="round" stroke-linejoin="round" stroke-width="4">
+                            <path d="M44 11v27c0 3.314-8.954 6-20 6S4 41.314 4 38V11"></path>
+                            <path d="M44 29c0 3.314-8.954 6-20 6S4 32.314 4 29m40-9c0 3.314-8.954 6-20 6S4 23.314 4 20"></path>
+                            <ellipse cx="24" cy="10" rx="20" ry="6"></ellipse>
+                        </g>
+                    </svg>
+                    <span class="logo-title">Easy Financial Report Dashboard</span>
+                </div>
+            ''', elem_classes=["text-2xl"])
+        
+        # 右侧：时间信息
+        with gr.Column(scale=2):
+            gr.Markdown(current_time, elem_classes=["text-sm-top-time"])
+
+def create_company_list(get_companys_state):
+    company_list = gr.Radio(
+        choices=[],
+        label="",
+        interactive=True,
+        elem_classes=["company-list-container"],
+        container=False,  # 不显示外部容器边框
+        visible=True
+      ) 
+    if (get_companys_state == False):
+        return company_list
+    else:
+        """创建公司列表组件"""
+        # 获取公司列表数据
+        try:
+            companies_data = get_companys()
+            print(f"创建公司列表组件 - Companies data: {companies_data}")
+            if isinstance(companies_data, pd.DataFrame) and not companies_data.empty:
+                choices = [str(row.get('company_name', 'Unknown')) for _, row in companies_data.iterrows()]
+            else:
+                choices = []
+        except:
+            choices = []
+        
+        # 添加默认公司选项
+        if not choices:
+            choices = []
+        
+        # 使用Radio组件显示公司列表，不显示标签
+        company_list = gr.Radio(
+            choices=choices,
+            label="",
+            interactive=True,
+            elem_classes=["company-list-container"],
+            container=False,  # 不显示外部容器边框
+            visible=True
+        )
+    
+        return company_list
+
+def create_company_selector():
+    """创建公司选择器组件"""
+    company_input = gr.Textbox(
+        show_label=False,
+        placeholder="Add Company",
+        elem_classes=["company-input-box"],
+        lines=1,
+        max_lines=1,
+        # container=False
+    )
+    
+    # 状态消息显示区域
+    status_message = gr.HTML(
+        "",
+        elem_classes=["status-message"],
+        visible=False
+    )
+    
+    # 弹窗选择列表
+    company_modal = gr.Radio(
+        show_label=False,
+        choices=[],
+        visible=False,
+        elem_classes=["company-modal"]
+    )
+    
+    return company_input, status_message, company_modal
+
+def create_report_section():
+    """创建报告部分组件"""  
+    # 创建一个用于显示报告列表的组件，初始显示公司列表
+    # initial_content = get_initial_company_list_content()
+    # 暂时返回空内容，稍后会用Gradio组件替换
+    initial_content = ""
+    # print(f"Initial content: {initial_content}")  # 添加调试信息
+
+    report_display = gr.HTML(initial_content)
+    return report_display
+
+def create_news_section():
+    """创建新闻部分组件"""
+    initial_content = ""
+    news_display = gr.HTML(initial_content)
+    return news_display
+
+def format_financial_metrics(data: dict, prev_data: dict = None) -> list:  # pyright: ignore[reportArgumentType]
+    """
+    将原始财务数据转换为 financial_metrics 格式。
+    
+    Args:
+        data (dict): 当前财年数据（必须包含 total_revenue, net_income 等字段）
+        prev_data (dict, optional): 上一财年数据，用于计算 change。若未提供，change 设为 "--"
+    
+    Returns:
+        list[dict]: 符合 financial_metrics 格式的列表
+    """
+    
+    def format_currency(value: float) -> str:
+        """将数字格式化为 $XB / $XM / $XK"""
+        if value >= 1e9:
+            return f"${value / 1e9:.2f}B"
+        elif value >= 1e6:
+            return f"${value / 1e6:.2f}M"
+        elif value >= 1e3:
+            return f"${value / 1e3:.2f}K"
+        else:
+            return f"${value:.2f}"
+
+    def calculate_change(current: float, previous: float) -> tuple:
+        """计算变化百分比和颜色"""
+        if previous == 0:
+            return "--", "gray"
+        change_pct = (current - previous) / abs(previous) * 100
+        sign = "+" if change_pct >= 0 else ""
+        color = "green" if change_pct >= 0 else "red"
+        return f"{sign}{change_pct:.1f}%", color
+
+    # 定义指标映射
+    metrics_config = [
+        {
+            "key": "total_revenue",
+            "label": "Total Revenue",
+            "is_currency": True,
+            "eps_like": False
+        },
+        {
+            "key": "net_income",
+            "label": "Net Income",
+            "is_currency": True,
+            "eps_like": False
+        },
+        {
+            "key": "earnings_per_share",
+            "label": "Earnings Per Share",
+            "is_currency": False,  # EPS 不用 B/M 单位
+            "eps_like": True
+        },
+        {
+            "key": "operating_expenses",
+            "label": "Operating Expenses",
+            "is_currency": True,
+            "eps_like": False
+        },
+        {
+            "key": "operating_cash_flow",
+            "label": "Cash Flow",
+            "is_currency": True,
+            "eps_like": False
+        }
+    ]
+
+    result = []
+    for item in metrics_config:
+        key = item["key"]
+        current_val = data.get(key)
+        if current_val is None:
+            continue
+
+        # 格式化 value
+        if item["eps_like"]:
+            value_str = f"${current_val:.2f}"
+        elif item["is_currency"]:
+            value_str = format_currency(current_val)
+        else:
+            value_str = str(current_val)
+
+        # 计算 change（如果有上期数据）
+        if prev_data and key in prev_data:
+            prev_val = prev_data[key]
+            change_str, color = calculate_change(current_val, prev_val)
+        else:
+            change_str = "--"
+            color = "gray"
+
+        result.append({
+            "label": item["label"],
+            "value": value_str,
+            "change": change_str,
+            "color": color
+        })
+
+    return result
+
+
+def create_sidebar():
+    """创建侧边栏组件"""
+    # 初始化 companies_map
+    initialize_companies_map()
+    
+    with gr.Column(elem_classes=["sidebar"]):
+        # 公司选择
+        with gr.Group(elem_classes=["card"]):
+            gr.Markdown("### Select Company", elem_classes=["card-title", "left-card-title"])
+            with gr.Column():
+                company_list = create_company_list(get_companys_state)
+                
+                # 创建公司列表
+                # if not get_companys_state:
+                #     getCompanyFromStorage = gr.Button("读取")
+                #     getCompanyFromStorage.click(
+                #         fn=create_company_list(True),
+                #         inputs=[],
+                #         outputs=[company_list, status_message]
+                #     )
+                
+                # 创建公司选择器
+                company_input, status_message, company_modal = create_company_selector()
+                
+                # 绑定事件
+                company_input.submit(
+                    fn=update_company_choices,
+                    inputs=[company_input],
+                    outputs=[company_modal, status_message]
+                )
+                
+                company_modal.change(
+                    fn=add_company,
+                    inputs=[company_modal, company_list],
+                    outputs=[company_modal, company_list, status_message]
+                )
+                
+                # 创建公司按钮组件
+                company_buttons = create_company_buttons()
+                
+                # 为每个公司按钮绑定点击事件         
+                def make_click_handler(company_name):
+                    def handler():
+                        result = handle_company_click(company_name)
+                        # 如果添加成功，刷新Select Company列表并默认选中刚添加的公司
+                        if result is True:
+                            # 正确地刷新通过create_company_list()创建的Radio组件
+                            try:
+                                companies_data = get_companys()
+                                if isinstance(companies_data, pd.DataFrame) and not companies_data.empty:
+                                    updated_choices = [str(row.get('company_name', 'Unknown')) for _, row in companies_data.iterrows()]
+                                else:
+                                    updated_choices = []
+                            except:
+                                updated_choices = []
+                            # 使用gr.update来正确更新Radio组件，并默认选中刚添加的公司
+                            # 同时触发change事件来加载数据
+                            return gr.update(choices=updated_choices, value=company_name)
+                        return None
+                    return handler
+                
+                for company_name, button in company_buttons.items():
+                    button.click(
+                        fn=make_click_handler(company_name),
+                        inputs=[],
+                        outputs=[company_list]
+                    )
+                
+            # 创建一个容器来容纳报告部分，初始时隐藏
+            with gr.Group(elem_classes=["report-news-box"]) as report_section_group:
+                # gr.Markdown("### Financial Reports", elem_classes=["card-title", "left-card-title"])
+                report_display = create_report_section()
+                news_display = create_news_section()
+
+        
+            # 处理公司选择事件
+            def select_company_handler(company_name):
+                """处理公司选择事件的处理器"""
+                # 更新全局变量
+                g.SELECT_COMPANY = company_name if company_name else ""
+                
+                # 更新报告部分的内容
+                updated_report_display = update_report_section(company_name, None, None)
+                
+                updated_news_display = update_news_section(company_name)
+                # 根据是否选择了公司来决定显示/隐藏报告部分
+                if company_name:
+                    # 有选中的公司，显示报告部分
+                    return gr.update(visible=True), updated_report_display, updated_news_display
+                else:
+                    # 没有选中的公司，隐藏报告部分
+                    return gr.update(visible=False), updated_report_display, updated_news_display
+            
+            company_list.change(
+                    fn=select_company_handler,
+                    inputs=[company_list],
+                    outputs=[report_section_group, report_display, news_display]
+                )
+
+    # 返回公司列表组件和报告部分组件
+    return company_list, report_section_group, report_display, news_display
+    
+def build_income_table(table_data):
+            # 兼容两种数据结构：
+            # 1. 新结构：包含 list_data 和 yoy_rates 的字典
+            # 2. 旧结构：直接是二维数组
+            if isinstance(table_data, dict) and "list_data" in table_data:
+                # 新结构
+                income_statement = table_data["list_data"]
+                yoy_rates = table_data["yoy_rates"] or []
+            else:
+                # 旧结构，直接使用传入的数据
+                income_statement = table_data
+                yoy_rates = []
+            
+            # 创建一个映射，将年份列索引映射到增长率
+            yoy_map = {}
+            if len(yoy_rates) > 1 and len(yoy_rates[0]) > 1:
+                # 获取增长率表头（跳过第一列"Category"）
+                yoy_headers = yoy_rates[0][1:]
+                
+                # 为每个指标行创建增长率映射
+                for i, yoy_row in enumerate(yoy_rates[1:], 1):  # 跳过标题行
+                    category = yoy_row[0]
+                    yoy_map[category] = {}
+                    for j, rate in enumerate(yoy_row[1:]):
+                        if j < len(yoy_headers):
+                            yoy_map[category][yoy_headers[j]] = rate
+            
+            table_rows = ""
+            header_row = income_statement[0]
+            
+            for i, row in enumerate(income_statement):
+                if i == 0:
+                    row_style = "background-color: #f5f5f5; font-weight: 500;"
+                else:
+                    row_style = "background-color: #f9f9f9;"
+                cells = ""
+                
+                for j, cell in enumerate(row):
+                    if j == 0:
+                        cells += f"<td style='padding: 8px; border: 1px solid #ddd; text-align: center; font-size: 14px;'>{cell}</td>"
+                    else:
+                        # 添加增长率箭头（如果有的话）
+                        growth = None
+                        category = row[0]
+                        # j是当前单元格索引，0是类别列，1,2,3...是数据列
+                        # yoy_map的键是年份，例如"2024/FY"
+                        if i > 0 and category in yoy_map and j > 0 and j < len(header_row):
+                            year_header = header_row[j]
+                            if year_header in yoy_map[category]:
+                                growth = yoy_map[category][year_header]
+                        
+                        if growth and growth != "N/A":
+                            arrow = "▲" if growth.startswith("+") else "▼"
+                            color = "green" if growth.startswith("+") else "red"
+                            cells += f"""<td style='padding: 8px; border: 1px solid #ddd; text-align: center; font-size: 14px; position: relative;'>
+                            <div>{cell}</div>
+                            <div style='position: absolute; bottom: -5px; right: 5px; font-size: 10px; color: {color};'>{arrow}{growth}</div>
+                            </td>"""
+                        else:
+                            cells += f"<td style='padding: 8px; border: 1px solid #ddd; text-align: center; font-size: 14px;'>{cell}</td>"
+                table_rows += f"<tr style='{row_style}'>{cells}</tr>"
+            
+            html = f"""
+            <div style="min-width: 400px;max-width: 600px;height: 300px !important;border: 1px solid #e0e0e0; border-radius: 8px; padding: 16px; box-shadow: 0 2px 4px rgba(0,0,0,0.1); font-family: 'Segoe UI', sans-serif;">
+                <div style="display: flex; align-items: center; gap: 8px; margin-bottom: 16px;">
+                    <svg width="16" height="16" viewBox="0 0 24 24" fill="none" xmlns="http://www.w3.org/2000/svg">
+                        <path d="M12 2L15.09 8.26L19 9.07L16 14L16 19L12 19L8 14L8 9.07L4.91 8.26L8 2L12 2Z" fill="#0066cc"/>
+                    </svg>
+                    <div style="font-size: 18px; font-weight: 600;">Income Statement and Cash Flow</div>
+                </div>
+                <table style="width: 100%; border-collapse: collapse; font-size: 14px;">
+                    {table_rows}
+                </table>
+            </div>
+            """
+            return html
+def create_metrics_dashboard():
+    """创建指标仪表板组件"""
+    with gr.Row(elem_classes=["metrics-dashboard"]):
+        card_custom_style = '''
+            background-color: white;
+            border-radius: 0.5rem;
+            box-shadow: rgba(0, 0, 0, 0.1) 0px 1px 3px 0px, rgba(0, 0, 0, 0.1) 0px 1px 2px -1px;
+            padding: 1.25rem;
+            min-height: 250px !important;
+            text-align: center;
+        '''
+
+        # 模拟数据
+        company_info = {
+            "name": "N/A",
+            "symbol": "NYSE:N/A",
+            "price": 0,
+            "change": 0,
+            "change_percent": 0.41,
+            "open": 165.20,
+            "high": 166.37,
+            "low": 156.15,
+            "prev_close": 157.01,
+            "volume": "27.10M"
+        }
+
+        # financial_metrics = query_financial_data("NVDA", "最新财务数据")
+        # print(f"最新财务数据: {financial_metrics}")
+        financial_metrics = [
+            {"label": "Total Revenue", "value": "N/A", "change": "N/A", "color": "grey"},
+            {"label": "Net Income", "value": "N/A", "change": "N/A", "color": "grey"},
+            {"label": "Earnings Per Share", "value": "N/A", "change": "N/A", "color": "grey"},
+            {"label": "Operating Expenses", "value": "N/A", "change": "N/A", "color": "grey"},
+            {"label": "Cash Flow", "value": "N/A", "change": "N/A", "color": "grey"}
+        ]
+        # income_statement = [
+        #     ["Category", "2024/FY", "2023/FY", "2022/FY"],
+        #     ["Total", "130350M", "126491M", "134567M"],
+        #     ["Net Income", "11081", "10598M", "9818.4M"],
+        #     ["Earnings Per Share", "4.38", "4.03", "3.62"],
+        #     ["Operating Expenses", "31990.9M", "31439.6M", "34516.2M"],
+        #     ["Cash Flow", "25289.9M", "29086M", "22517.2M"]
+        # ]
+        income_statement = {
+        "list_data": [
+        ["Category", "N/A/FY", "N/A/FY", "N/A/FY"],
+        ["Total", "N/A", "N/A", "N/A"],
+        ["Net Income", "N/A", "N/A", "N/A.4M"],
+        ["Earnings Per Share", "N/A", "N/A", "N/A"],
+        ["Operating Expenses", "N/A", "N/A", "N/A"],
+        ["Cash Flow", "N/A", "N/A", "N/A"]
+     ],
+     "yoy_rates": []
+    #  "yoy_rates": [
+    #     ["Category", "N/A/FY", "N/A/FY"],
+    #     ["Total", "N/A", "N/A"],
+    #     ["Net Income", "+3.05%", "-6.00%"],
+    #     ["Earnings Per Share", "+3.05%", "-6.00%"],
+    #     ["Operating Expenses", "+29.17%", "-6.00%"],
+    #     ["Cash Flow", "-13.05%", "-6.00%"]
+    #  ]
+    }
+        yearly_data = 'N/A'
+        # 增长变化的 HTML 字符（箭头+百分比）
+        def render_change(change: str, color: str):
+            if change.startswith("+"):
+                return f'<span style="color:{color};">▲{change}</span>'
+            else:
+                return f'<span style="color:{color};">▼{change}</span>'
+
+        # 构建左侧卡片
+        def build_stock_card():
+            html = f"""
+            <div style="width: 250px;height: 300px !important;border: 1px solid #e0e0e0; border-radius: 8px; padding: 16px; box-shadow: 0 2px 4px rgba(0,0,0,0.1); font-family: 'Segoe UI', sans-serif;">
+                <div style="font-size: 14px; color: #555;">N/A</div>
+                <div style="font-size: 12px; color: #888;">N/A</div>
+                <div style="font-size: 32px; font-weight: bold; margin: 8px 0;">N/A</div>
+                <div style="font-size: 14px; margin: 8px 0;">N/A</div>
+                <div style="margin-top: 12px; display: grid; grid-template-columns: auto 1fr; gap: 8px;">
+                    <div style="font-size: 14px; color: #555;">Open</div><div style="font-size: 14px; font-weight: 500;text-align: center;">N/A</div>
+                    <div style="font-size: 14px; color: #555;">High</div><div style="font-size: 14px; font-weight: 500;text-align: center;">N/A</div>
+                    <div style="font-size: 14px; color: #555;">Low</div><div style="font-size: 14px; font-weight: 500;text-align: center;">N/A</div>
+                    <div style="font-size: 14px; color: #555;">Prev Close</div><div style="font-size: 14px; font-weight: 500;text-align: center;">N/A</div>
+                    
+                </div>
+            </div>
+            """
+            return html
+            # <div style="font-size: 14px; color: #555;">Vol</div><div style="font-size: 14px; font-weight: 500;text-align: center;">N/A</div>
+        # 构建中间卡片
+        def build_financial_metrics():
+            metrics_html = ""
+            for item in financial_metrics:
+                change_html = render_change(item["change"], item["color"])
+                metrics_html += f"""
+                <div style="display: flex; justify-content: space-between; padding: 8px 0; font-family: 'Segoe UI', sans-serif;">
+                    <div style="font-size: 14px; color: #555;">{item['label']}</div>
+                    <div style="font-size: 16px; font-weight: 500; color: #333;">{item['value']} {change_html}</div>
+                </div>
+                """
+            
+            html = f"""
+            <div style="min-width: 300px;max-width: 450px;height: 300px !important;border: 1px solid #e0e0e0; border-radius: 8px; padding: 16px; box-shadow: 0 2px 4px rgba(0,0,0,0.1); font-family: 'Segoe UI', sans-serif;">
+                <div style="display: flex; align-items: center; gap: 8px; margin-bottom: 16px;justify-content: space-between;">
+                    <div style="font-size: 18px; font-weight: 600;display: flex;align-items: center;">
+                        <svg width="16" height="16" viewBox="0 0 24 24" fill="none" xmlns="http://www.w3.org/2000/svg">
+                            <path d="M12 2L15.09 8.26L19 9.07L16 14L16 19L12 19L8 14L8 9.07L4.91 8.26L8 2L12 2Z" fill="#0066cc"/>
+                        </svg>       
+                        <span style="margin-left: 10px;">{yearly_data} Financial Metrics</span>
+                    </div>
+                    <div style="font-size: 16px; color: #8f8f8f;">
+                            YTD data
+                    </div>
+                </div>
+                {metrics_html}
+            </div>
+            """
+            return html
+
+
+        # 主函数：返回所有 HTML 片段
+        def get_dashboard():
+            with gr.Row():
+                with gr.Column(scale=1, min_width=250, elem_classes=["metric-card-col-left"]):
+                    stock_card_html = gr.HTML(build_stock_card(), elem_classes=["metric-card-left"])
+                with gr.Column(scale=1, min_width=300, elem_classes=["metric-card-col-middle"]):
+                    financial_metrics_html = gr.HTML(build_financial_metrics(), elem_classes=["metric-card-middle"])
+                with gr.Column(scale=1, min_width=450, elem_classes=["metric-card-col-right"]):
+                    # 传递income_statement参数
+                    income_table_html = gr.HTML(build_income_table(income_statement), elem_classes=["metric-card-right"])
+            return stock_card_html, financial_metrics_html, income_table_html
+        
+        # 创建指标仪表板并保存引用
+        stock_card_component, financial_metrics_component, income_table_component = get_dashboard()
+        
+        # 将组件引用保存到全局变量，以便在其他地方使用
+        global metrics_dashboard_components
+        metrics_dashboard_components = (stock_card_component, financial_metrics_component, income_table_component)
+
+# 更新指标仪表板的函数
+def update_metrics_dashboard(company_name):
+    """根据选择的公司更新指标仪表板"""
+    # 模拟数据
+    # company_info = {
+    #     "name": company_name,
+    #     "symbol": "NYSE:BABA",
+    #     "price": 157.65,
+    #     "change": 0.64,
+    #     "change_percent": 0.41,
+    #     "open": 165.20,
+    #     "high": 166.37,
+    #     "low": 156.15,
+    #     "prev_close": 157.01,
+    #     "volume": "27.10M"
+    # }
+    company_info = {}
+    # 尝试获取股票价格数据，但不中断程序执行
+    stock_code = ""
+    try:
+        # 根据选择的公司获取股票代码
+        stock_code = get_stock_code_by_company_name(company_name)
+        # result = get_quote(company_name.strip())
+
+        # company_info2 = get_stock_price(stock_code)
+        # company_info2 = get_stock_price_from_bailian(stock_code)
+        # print(f"股票价格数据: {company_info2}")
+        company_info = get_quote(stock_code.strip())
+        company_info['company'] = company_name
+        print(f"股票价格数据====: {company_info}")
+    #         查询结果：{
+    #   "company": "阿里巴巴",
+    #   "symbol": "BABA",
+    #   "open": "159.09",
+    #   "high": "161.46",
+    #   "low": "150.00",
+    #   "price": "157.60",
+    #   "volume": "21453064",
+    #   "latest trading day": "2025-11-27",
+    #   "previous close": "157.01",
+    #   "change": "+0.59",
+    #   "change_percent": "+0.38%"
+    # }BABA
+        # 如果成功获取数据，则用实际数据替换模拟数据
+        # if company_info2 and "content" in company_info2 and len(company_info2["content"]) > 0:
+        #     import json
+        #     # 解析返回的JSON数据
+        #     data_text = company_info2["content"][0]["text"]
+        #     stock_data = json.loads(data_text)
+            
+        #     # 提取数据
+        #     quote = stock_data["Global Quote"]
+            
+        #     # 转换交易量单位
+        #     volume = int(quote['06. volume'])
+        #     if volume >= 1000000:
+        #         volume_str = f"{volume / 1000000:.2f}M"
+        #     elif volume >= 1000:
+        #         volume_str = f"{volume / 1000:.2f}K"
+        #     else:
+        #         volume_str = str(volume)
+            
+        #     company_info = {
+        #         "name": company_name,
+        #         "symbol": f"NYSE���{quote['01. symbol']}",
+        #         "price": float(quote['05. price']),
+        #         "change": float(quote['09. change']),
+        #         "change_percent": float(quote['10. change percent'].rstrip('%')),
+        #         "open": float(quote['02. open']),
+        #         "high": float(quote['03. high']),
+        #         "low": float(quote['04. low']),
+        #         "prev_close": float(quote['08. previous close']),
+        #         "volume": volume_str
+        #     }
+    except Exception as e:
+        print(f"获取股票价格数据失败: {e}")
+        company_info2 = None
+
+    # financial_metrics = [
+    #     {"label": "Total Revenue", "value": "$2.84B", "change": "+12.4%", "color": "green"},
+    #     {"label": "Net Income", "value": "$685M", "change": "-3.2%", "color": "red"},
+    #     {"label": "Earnings Per Share", "value": "$2.15", "change": "-3.2%", "color": "red"},
+    #     {"label": "Operating Expenses", "value": "$1.2B", "change": "+5.1%", "color": "green"},
+    #     {"label": "Cash Flow", "value": "$982M", "change": "+8.7%", "color": "green"}
+    # ]
+    financial_metrics_pre = query_financial_data(stock_code, "5-Year")
+    # financial_metrics_pre = query_financial_data(company_name, "5年趋势")
+    # print(f"最新财务数据: {financial_metrics_pre}")
+    # financial_metrics = format_financial_metrics(financial_metrics_pre)
+
+
+    # financial_metrics_pre_2 = extract_last_three_with_fallback(financial_metrics_pre)
+    # print(f"提取的3年数据: {financial_metrics_pre_2}")
+    # financial_metrics_pre = {
+    #     "metrics": financial_metrics_pre_2
+    # }
+    financial_metrics = []
+    # try:
+    #     # financial_metrics = calculate_yoy_comparison(financial_metrics_pre)
+    #     financial_metrics = build_financial_metrics_three_year_data(financial_metrics_pre)
+    #     print(f"格式化后的财务数据: {financial_metrics}")
+    # except Exception as e:
+    #     print(f"Error calculating YOY comparison: {e}")
+    year_data = None
+    three_year_data = None
+    try:
+        # financial_metrics = process_financial_data_with_metadata(financial_metrics_pre)
+        result = process_financial_data_with_metadata(financial_metrics_pre)
+
+        # 按需提取字段
+        financial_metrics = result["financial_metrics"]
+        year_data = result["year_data"]
+        three_year_data = result["three_year_data"]
+        print(f"格式化后的财务数据: {financial_metrics}")
+        # 拿report数据
+        # try:
+        #     # 从 result 中获取报告数据
+        #     if 'report_data' in result:  # 假设 result 中包含 report_data 键
+        #         report_data = result['report_data']
+        #     else:
+        #         # 如果 result 中没有直接包含 report_data，则从其他键中获取
+        #         # 这需要根据实际的 result 数据结构来调整
+        #         report_data = result.get('reports', [])  # 示例：假设数据在 'reports' 键下
+                
+            # 更新报告部分的内容
+            # 这里需要调用 update_report_section 函数并传入 report_data
+            # 注意：update_report_section 可能需要修改以接受 report_data 参数
+            # updated_report_content = update_report_section(company_name, report_data, stock_code)
+            
+            # 然后将 updated_report_content 返回，以便在 UI 中更新
+            # 这需要修改函数的返回值以包含报告内容
+            
+        # except Exception as e:
+        #     print(f"Error updating report section with result data: {e}")
+        #     updated_report_content = "<div>Failed to load report data</div>"
+    except Exception as e:
+        print(f"Error process_financial_data: {e}")
+   
+
+    # income_statement = [
+    #     ["Category", "2024/FY", "2023/FY", "2022/FY"],
+    #     ["Total", "130350M", "126491M", "134567M"],
+    #     ["Net Income", "11081", "10598M", "9818.4M"],
+    #     ["Earnings Per Share", "4.38", "4.03", "3.62"],
+    #     ["Operating Expenses", "31990.9M", "31439.6M", "34516.2M"],
+    #     ["Cash Flow", "25289.9M", "29086M", "22517.2M"]
+    # ]
+
+    # table_data = None
+    # try:
+    #     table_data = extract_financial_table(financial_metrics_pre)
+    #     print(table_data)
+    # except Exception as e:
+    #     print(f"Error extract_financial_table: {e}")
+    # yearly_data = None
+    # try:
+    #     yearly_data = get_yearly_data(financial_metrics_pre)
+    # except Exception as e:
+    #     print(f"Error get_yearly_data: {e}")
+
+    # ======
+    # table_data = [
+    #     ["Category", "2024/FY", "2023/FY", "2022/FY"],
+    #     ["Total", "130350M", "126491M", "134567M"],
+    #     ["Net Income", "11081", "10598M", "9818.4M"],
+    #     ["Earnings Per Share", "4.38", "4.03", "3.62"],
+    #     ["Operating Expenses", "31990.9M", "31439.6M", "34516.2M"],
+    #     ["Cash Flow", "25289.9M", "29086M", "22517.2M"]
+    # ]   
+    yearly_data = year_data
+    table_data = build_table_format(three_year_data)
+    # print(f"table_data: {table_data}")
+      # yearly_data = None
+    # try:
+    #     yearly_data = get_yearly_data(financial_metrics_pre)
+    # except Exception as e:
+    #     print(f"Error get_yearly_data: {e}")
+    #=======
+
+    # exp = {
+    #     "list_data": [
+    #     ["Category", "2024/FY", "2023/FY", "2022/FY"],
+    #     ["Total", "130350M", "126491M", "134567M"],
+    #     ["Net Income", "11081", "10598M", "9818.4M"],
+    #     ["Earnings Per Share", "4.38", "4.03", "3.62"],
+    #     ["Operating Expenses", "31990.9M", "31439.6M", "34516.2M"],
+    #     ["Cash Flow", "25289.9M", "29086M", "22517.2M"]
+    #  ],
+    #  "yoy_rates": [
+    #     ["Category", "2024/FY", "2023/FY"],
+    #     ["Total", "+3.05%", "-6.00%"],
+    #     ["Net Income", "+3.05%", "-6.00%"],
+    #     ["Earnings Per Share", "+3.05%", "-6.00%"],
+    #     ["Operating Expenses", "+29.17%", "-6.00%"],
+    #     ["Cash Flow", "-13.05%", "-6.00%"]
+    #  ]
+    # }
+
+    # 增长变化的 HTML 字符（箭头+百分比）
+    def render_change(change: str, color: str):
+        if change.startswith("+"):
+            return f'<span style="color:{color};">▲{change}</span>'
+        else:
+            return f'<span style="color:{color};">▼{change}</span>'
+
+    # 构建左侧卡片
+    def build_stock_card(company_info):
+        try:
+            if not company_info or not isinstance(company_info, dict):
+                company_name = "N/A"
+                symbol = "N/A"
+                price = "N/A"
+                change_html = '<span style="color:#888;">N/A</span>'
+                open_val = high_val = low_val = prev_close_val = volume_display = "N/A"
+            else:
+                company_name = company_info.get("company", "N/A")
+                symbol = company_info.get("symbol", "N/A")
+                price = company_info.get("current_price", "N/A")
+                
+                # 解析 change
+                change_str = company_info.get("change", "0")
+                try:
+                    change = float(change_str)
+                except (ValueError, TypeError):
+                    change = 0.0
+
+                # 解析 change_percent
+                change_percent = company_info.get("percent_change", "0%")
+                # try:
+                #     change_percent = float(change_percent_str.rstrip('%'))
+                # except (ValueError, TypeError):
+                #     change_percent = 0.0
+
+                change_color = "green" if change >= 0 else "red"
+                sign = "+" if change >= 0 else ""
+                change_html = f'<span style="color:{change_color};">{sign}{change:.2f} ({change_percent:+.2f}%)</span>'
+
+                # 其他价格字段（可选：也可格式化为 2 位小数）
+                open_val = company_info.get("open", "N/A")
+                high_val = company_info.get("high", "N/A")
+                low_val = company_info.get("low", "N/A")
+                prev_close_val = company_info.get("previous_close", "N/A")
+                # raw_volume = company_info.get("volume", "N/A")
+                # volume_display = format_volume(raw_volume)
+
+            html = f"""
+            <div style="width: 250px; height: 300px !important; border: 1px solid #e0e0e0; border-radius: 8px; padding: 16px; box-shadow: 0 2px 4px rgba(0,0,0,0.1); font-family: 'Segoe UI', sans-serif;">
+                <div style="font-size: 16px; color: #555; font-weight: 500;">{company_name}</div>
+                <div style="font-size: 12px; color: #888;">NYSE：{symbol}</div>
+                <div style="display: flex; align-items: center; gap: 10px; margin: 8px 0;">
+                    <div style="font-size: 32px; font-weight: bold;">{price}</div>
+                    <div style="font-size: 14px;">{change_html}</div>
+                </div>
+                <div style="margin-top: 12px; display: grid; grid-template-columns: auto 1fr; gap: 8px;">
+                    <div style="font-size: 14px; color: #555;">Open</div><div style="font-size: 14px; font-weight: 500; text-align: center;">{open_val}</div>
+                    <div style="font-size: 14px; color: #555;">High</div><div style="font-size: 14px; font-weight: 500; text-align: center;">{high_val}</div>
+                    <div style="font-size: 14px; color: #555;">Low</div><div style="font-size: 14px; font-weight: 500; text-align: center;">{low_val}</div>
+                    <div style="font-size: 14px; color: #555;">Prev Close</div><div style="font-size: 14px; font-weight: 500; text-align: center;">{prev_close_val}</div>
+                </div>
+            </div>
+            """
+            # <div style="font-size: 14px; color: #555;">Vol</div><div style="font-size: 14px; font-weight: 500; text-align: center;">{volume_display}</div>
+
+            return html
+
+        except Exception as e:
+            print(f"Error building stock card: {e}")
+            return '<div style="width:250px; padding:16px; color:red;">Error loading stock data</div>'
+    # 构建中间卡片
+    def build_financial_metrics(yearly_data):
+        metrics_html = ""
+        for item in financial_metrics:
+            change_html = render_change(item["change"], item["color"])
+            metrics_html += f"""
+            <div style="display: flex; justify-content: space-between; padding: 8px 0; font-family: 'Segoe UI', sans-serif;">
+                <div style="font-size: 14px; color: #555;">{item['label']}</div>
+                <div style="font-size: 16px; font-weight: 500; color: #333;">{item['value']} {change_html}</div>
+            </div>
+            """
+        
+        html = f"""
+        <div style="width: 450px;height: 300px !important;border: 1px solid #e0e0e0; border-radius: 8px; padding: 16px; box-shadow: 0 2px 4px rgba(0,0,0,0.1); font-family: 'Segoe UI', sans-serif;">
+            <div style="display: flex; align-items: center; gap: 8px; margin-bottom: 16px;justify-content: space-between;">
+                <div style="font-size: 18px; font-weight: 600;display: flex;align-items: center;">
+                    <svg width="16" height="16" viewBox="0 0 24 24" fill="none" xmlns="http://www.w3.org/2000/svg">
+                        <path d="M12 2L15.09 8.26L19 9.07L16 14L16 19L12 19L8 14L8 9.07L4.91 8.26L8 2L12 2Z" fill="#0066cc"/>
+                    </svg>       
+                    <span style="margin-left: 10px;">{yearly_data} Financial Metrics</span>
+                 </div>
+                <div style="font-size: 16px; color: #8f8f8f;">
+                        YTD data
+                </div>
+            </div>
+            {metrics_html}
+        </div>
+        """
+        return html
+
+    # 构建右侧表格
+    # def build_income_table(income_statement):
+    #     table_rows = ""
+    #     for i, row in enumerate(income_statement):
+    #         if i == 0:
+    #             row_style = "background-color: #f5f5f5; font-weight: 500;"
+    #         else:
+    #             row_style = "background-color: #f9f9f9;"
+    #         cells = ""
+    #         for j, cell in enumerate(row):
+    #             if j == 0:
+    #                 cells += f"<td style='padding: 8px; border: 1px solid #ddd; text-align: center; font-size: 14px;'>{cell}</td>"
+    #             else:
+    #                 # 添加增长箭头（模拟数据）
+    #                 growth = None
+    #                 if i == 1 and j == 1: growth = "+3.05%"
+    #                 elif i == 1 and j == 2: growth = "-6.00%"
+    #                 elif i == 2 and j == 1: growth = "+3.05%"
+    #                 elif i == 2 and j == 2: growth = "-6.00%"
+    #                 elif i == 3 and j == 1: growth = "+3.05%"
+    #                 elif i == 3 and j == 2: growth = "-6.00%"
+    #                 elif i == 4 and j == 1: growth = "+29.17%"
+    #                 elif i == 4 and j == 2: growth = "+29.17%"
+    #                 elif i == 5 and j == 1: growth = "-13.05%"
+    #                 elif i == 5 and j == 2: growth = "+29.17%"
+
+    #                 if growth:
+    #                     arrow = "▲" if growth.startswith("+") else "▼"
+    #                     color = "green" if growth.startswith("+") else "red"
+    #                     cells += f"""<td style='padding: 8px; border: 1px solid #ddd; text-align: center; font-size: 14px; position: relative;'>
+    #                     <div>{cell}</div>
+    #                     <div style='position: absolute; bottom: -5px; right: 5px; font-size: 10px; color: {color};'>{arrow}{growth}</div>
+    #                     </td>"""
+    #                 else:
+    #                     cells += f"<td style='padding: 8px; border: 1px solid #ddd; text-align: center; font-size: 14px;'>{cell}</td>"
+    #         table_rows += f"<tr style='{row_style}'>{cells}</tr>"
+        
+    #     html = f"""
+    #     <div style="width: 600px;height: 300px !important;border: 1px solid #e0e0e0; border-radius: 8px; padding: 16px; box-shadow: 0 2px 4px rgba(0,0,0,0.1); font-family: 'Segoe UI', sans-serif;">
+    #         <div style="display: flex; align-items: center; gap: 8px; margin-bottom: 16px;">
+    #             <svg width="16" height="16" viewBox="0 0 24 24" fill="none" xmlns="http://www.w3.org/2000/svg">
+    #                 <path d="M12 2L15.09 8.26L19 9.07L16 14L16 19L12 19L8 14L8 9.07L4.91 8.26L8 2L12 2Z" fill="#0066cc"/>
+    #             </svg>
+    #             <div style="font-size: 18px; font-weight: 600;">Income Statement and Cash Flow</div>
+    #         </div>
+    #         <table style="width: 100%; border-collapse: collapse; font-size: 14px;">
+    #             {table_rows}
+    #         </table>
+    #     </div>
+    #     """
+    #     return html
+
+    # 返回三个HTML组件的内容
+    return build_stock_card(company_info), build_financial_metrics(yearly_data), build_income_table(table_data)
+
+def create_tab_content(tab_name, company_name):
+    """创建Tab内容组件"""
+    if tab_name == "summary":
+        print(f"company_name: {company_name}")
+        # content = get_invest_suggest(company_name)
+        gr.Markdown("# 11111", elem_classes=["invest-suggest-md-box"])
+        # gr.Markdown(content, elem_classes=["invest-suggest-md-box"])
+        # gr.Markdown("""
+        #            ## Investment Suggestions
+
+        #             ### Company Overview
+
+        #             GlobalTech inc. is a leading technology company with strong performance in the Q3 2025 period. The companyshows consistent revenue growth and maintains a healthy fnancial position.
+
+        #             ### Key Strengths
+
+        #             - Revenue Growth: 12.4% year-over-year increase demonstrates strong market demandDiversifed Portfolio: Multiple revenue streams reduce business risk
+
+        #             - Innovation Focus: Continued investment in R&D drives future growth potential
+
+        #             ### Financial Health Indicators
+
+        #             - Liquidity: Current ratio of 1.82 indicates good short-term fnancial health
+
+        #             - Proftability: Net income of $685M, though down slightly quarter-over-quarter0
+        #             - Cash Flow: Strong operating cash flow of $982M supports operations and growth initiatives
+
+        #             ### Investment Recommendation
+
+        #             BUY - GlobalTech Inc. presents a solid investment opportunity with:
+        #             - Consistent revenue growth trajectory
+        #             - Strong market position in key technology segments
+        #             - Healthy balance sheet and cash flow generation
+                    
+        #             ### Risk Considerations
+
+        #             Quarterly net income decline warrants monitoring  
+        #             | Category           | Q3 2025   | Q2 2025   | YoY %    |
+        #             |--------------------|-----------|-----------|----------|
+        #             | Total Revenue      | $2,842M   | $2,712M   | +12.4%   |
+        #             | Gross Profit       | $1,203M   | $1,124M   | +7.0%    |
+        #             | Operating Income   | $742M     | $798M     | -7.0%    |
+        #             | Net Income         | $685M     | $708M     | -3.2%    |
+        #             | Earnings Per Share | $2.15     | $2.22     | -3.2%    |
+        #            """, elem_classes=["invest-suggest-md-box"])
+
+    
+    elif tab_name == "detailed":
+        with gr.Column(elem_classes=["tab-content"]):
+            gr.Markdown("Financial Statements", elem_classes=["text-xl", "font-semibold", "text-gray-900", "mb-6"])
+            
+            with gr.Row(elem_classes=["gap-6"]):
+                # 收入报表 (3/5宽度)
+                with gr.Column(elem_classes=["w-3/5", "bg-gray-50", "rounded-xl", "p-4"]):
+                    gr.Markdown("Income Statement", elem_classes=["font-medium", "mb-3"])
+                    # 这里将显示收入报表表格
+                    
+                # 资产负债表和现金流量表 (2/5宽度)
+                with gr.Column(elem_classes=["w-2/5", "flex", "flex-col", "gap-6"]):
+                    # 资产负债表
+                    with gr.Column(elem_classes=["bg-gray-50", "rounded-xl", "p-4"]):
+                        gr.Markdown("Balance Sheet Summary", elem_classes=["font-medium", "mb-3"])
+                        # 这里将显示资产负债表图表
+                    
+                    # 现金流量表
+                    with gr.Column(elem_classes=["bg-gray-50", "rounded-xl", "p-4"]):
+                        with gr.Row(elem_classes=["justify-between", "items-start"]):
+                            gr.Markdown("Cash Flow Statement", elem_classes=["font-medium"])
+                            gr.Markdown("View Detailed", elem_classes=["text-xs", "text-blue-600", "font-medium"])
+                        
+                        with gr.Column(elem_classes=["mt-4", "space-y-3"]):
+                            # 经营现金流
+                            with gr.Column():
+                                with gr.Row(elem_classes=["justify-between"]):
+                                    gr.Markdown("Operating Cash Flow")
+                                    gr.Markdown("$982M", elem_classes=["font-medium"])
+                                with gr.Row(elem_classes=["w-full", "bg-gray-200", "rounded-full", "h-1.5", "mt-1"]):
+                                    with gr.Column(elem_classes=["bg-green-500", "h-1.5", "rounded-full"], scale=85):
+                                        gr.Markdown("")
+                            
+                            # 投资现金流
+                            with gr.Column():
+                                with gr.Row(elem_classes=["justify-between"]):
+                                    gr.Markdown("Investing Cash Flow")
+                                    gr.Markdown("-$415M", elem_classes=["font-medium"])
+                                with gr.Row(elem_classes=["w-full", "bg-gray-200", "rounded-full", "h-1.5", "mt-1"]):
+                                    with gr.Column(elem_classes=["bg-blue-500", "h-1.5", "rounded-full"], scale=42):
+                                        gr.Markdown("")
+                            
+                            # 融资现金流
+                            with gr.Column():
+                                with gr.Row(elem_classes=["justify-between"]):
+                                    gr.Markdown("Financing Cash Flow")
+                                    gr.Markdown("-$212M", elem_classes=["font-medium"])
+                                with gr.Row(elem_classes=["w-full", "bg-gray-200", "rounded-full", "h-1.5", "mt-1"]):
+                                    with gr.Column(elem_classes=["bg-red-500", "h-1.5", "rounded-full"], scale=25):
+                                        gr.Markdown("")
+    
+    elif tab_name == "comparative":
+        with gr.Column(elem_classes=["tab-content"]):
+            gr.Markdown("Industry Benchmarking", elem_classes=["text-xl", "font-semibold", "text-gray-900", "mb-6"])
+            
+            # 收入增长对比
+            with gr.Column(elem_classes=["bg-gray-50", "rounded-xl", "p-4", "mb-6"]):
+                gr.Markdown("Revenue Growth - Peer Comparison", elem_classes=["font-medium", "mb-3"])
+                # 这里将显示对比图表
+            
+            # 利润率和报告预览网格
+            with gr.Row(elem_classes=["grid-cols-2", "gap-6"]):
+                # 利润率表格
+                with gr.Column(elem_classes=["bg-gray-50", "rounded-xl", "p-4"]):
+                    gr.Markdown("Profitability Ratios", elem_classes=["font-medium", "mb-3"])
+                    # 这里将显示利润率表格
+                
+                # 报告预览
+                with gr.Column(elem_classes=["bg-gray-50", "rounded-xl", "p-4"]):
+                    gr.Markdown("Report Preview", elem_classes=["font-medium", "mb-3"])
+                    # 这里将显示报告预览
+
+def create_chat_panel():
+    """创建聊天面板组件"""
+    # with gr.Column(elem_classes=["chat-panel"]):
+        # 聊天头部
+        # with gr.Row(elem_classes=["p-4", "border-b", "border-gray-200", "items-center", "gap-2"]):
+        #     gr.Markdown("🤖", elem_classes=["text-xl", "text-blue-600"])
+        #     gr.Markdown("Financial Assistant", elem_classes=["font-medium"])
+        
+        # 聊天区域
+         # 一行代码嵌入！
+    # chat_component = create_financial_chatbot()
+    # chat_component.render()
+    # create_financial_chatbot()
+    # gr.LoginButton()
+        # chatbot = gr.Chatbot(
+        #     value=[
+        #         {"role": "assistant", "content": "I'm your financial assistant, how can I help you today?"},
+
+        #         # {"role": "assistant", "content": "Hello! I can help you analyze financial data. Ask questions like \"Show revenue trends\" or \"Compare profitability ratios\""},
+        #         # {"role": "user", "content": "Show revenue trends for last 4 quarters"},
+        #         # {"role": "assistant", "content": "Revenue trend for GlobalTech Inc.:\n\nQ4 2024: $2.53B (+8.2%)\nQ1 2025: $2.61B (+9.8%)\nQ2 2025: $2.71B (+11.6%)\nQ3 2025: $2.84B (+12.4%)"},
+        #         # {"role": "assistant", "content": "Revenue trend for GlobalTech Inc.:\n\nQ4 2024: $2.53B (+8.2%)\nQ1 2025: $2.61B (+9.8%)\nQ2 2025: $2.71B (+11.6%)\nQ3 2025: $2.84B (+12.4%)"},
+        #         # {"role": "assistant", "content": "Revenue trend for GlobalTech Inc.:\n\nQ4 2024: $2.53B (+8.2%)\nQ1 2025: $2.61B (+9.8%)\nQ2 2025: $2.71B (+11.6%)\nQ3 2025: $2.84B (+12.4%)"},
+        #         # {"role": "assistant", "content": "Revenue trend for GlobalTech Inc.:\n\nQ4 2024: $2.53B (+8.2%)\nQ1 2025: $2.61B (+9.8%)\nQ2 2025: $2.71B (+11.6%)\nQ3 2025: $2.84B (+12.4%)"}
+        #     ],
+        #     type="messages",
+        #     # elem_classes=["min-h-0", "overflow-y-auto", "space-y-4", "chat-content-box"],
+        #     show_label=False,
+        #     autoscroll=True,
+        #     show_copy_button=True,
+        #     height=400,
+        #     container=False, 
+        # )
+        
+        # # 输入区域
+        # with gr.Row(elem_classes=["border-t", "border-gray-200", "gap-2"]):
+        #     msg = gr.Textbox(
+        #         placeholder="Ask a financial question...",
+        #         elem_classes=["flex-1", "border", "border-gray-300", "rounded-lg", "px-4", "py-2", "focus:border-blue-500"],
+        #         show_label=False,
+        #         lines=1,
+        #         submit_btn=True,
+        #         container=False,        
+        #     )
+        #     msg.submit(
+        #         chat_bot,
+        #         [msg, chatbot],
+        #         [msg, chatbot],
+        #         queue=True,
+        #     )
+
+# def load_css_files(css_dir, filenames):
+#     css_content = ""
+#     for filename in filenames:
+#         path = os.path.join(css_dir, filename)
+#         if os.path.exists(path):
+#             with open(path, "r", encoding="utf-8") as f:
+#                 css_content += f.read() + "\n"
+#         else:
+#             print(f"⚠️ CSS file not found: {path}")
+#     return css_content
+def main():
+    # 获取当前目录
+    current_dir = os.path.dirname(os.path.abspath(__file__))
+    css_dir = os.path.join(current_dir, "css")
+
+    # def load_css_files(css_dir, filenames):
+    #     """读取多个 CSS 文件并合并为一个字符串"""
+    #     css_content = ""
+    #     for filename in filenames:
+    #         path = os.path.join(css_dir, filename)
+    #         if os.path.exists(path):
+    #             with open(path, "r", encoding="utf-8") as f:
+    #                 css_content += f.read() + "\n"
+    #         else:
+    #             print(f"Warning: CSS file not found: {path}")
+    #     return css_content
+    # 设置CSS路径
+    css_paths = [
+        os.path.join(css_dir, "main.css"),
+        os.path.join(css_dir, "components.css"),
+        os.path.join(css_dir, "layout.css")
+    ]
+    # css_dir = "path/to/your/css/folder"  # 替换为你的实际路径
+      # 自动定位 css 文件夹（与 app.py 同级）
+    # BASE_DIR = os.path.dirname(os.path.abspath(__file__))
+    # CSS_DIR = os.path.join(BASE_DIR, "css")
+    
+    # css_files = ["main.css", "components.css", "layout.css"]
+    # combined_css = load_css_files(CSS_DIR, css_files)
+    # print(combined_css)
+    
+    with gr.Blocks(
+        title="Financial Analysis Dashboard",
+        css_paths=css_paths,
+        css=custom_css, 
+        # css=combined_css
+    ) as demo:
+        
+        # 添加处理公司点击事件的路由
+        # 创建一个状态组件来跟踪选中的公司
+        selected_company_state = gr.State("")
+        
+        with gr.Column(elem_classes=["container", "container-h"]):
+            # 头部
+            create_header()
+            
+            # 创建主布局
+            with gr.Row(elem_classes=["main-content-box"]):
+                # 左侧边栏
+                with gr.Column(scale=1, min_width=350):
+                    # 获取company_list组件的引用
+                    company_list_component, report_section_component, report_display_component, news_display_component = create_sidebar()
+                
+                # 主内容区域
+                with gr.Column(scale=9):
+                    
+                    # 指标仪表板
+                    create_metrics_dashboard()
+                    
+                    with gr.Row(elem_classes=["main-content-box"]):
+                        with gr.Column(scale=8):
+                            # Tab内容
+                            with gr.Tabs():
+                                with gr.TabItem("Invest Suggest", elem_classes=["tab-item"]):
+                                    # 创建一个用于显示公司名称的组件
+                                    # company_display = gr.Markdown("# Please select a company")
+                                    # 创建一个占位符用于显示tab内容
+                                    tab_content = gr.Markdown(elem_classes=["invest-suggest-md-box"])
+                                    
+                                    # 当选中的公司改变时，更新显示
+                                    # selected_company_state.change(
+                                    #     fn=lambda company: f"# Investment Suggestions for {company}" if company else "# Please select a company",
+                                    #     inputs=[selected_company_state],
+                                    #     outputs=[company_display]
+                                    # )
+                                    
+                                    # 当选中的公司改变时，重新加载tab内容
+                                    def update_tab_content(company):
+                                        if company:
+                                            # 显示loading状态
+                                            loading_html = f'''
+                                            <div style="display: flex; justify-content: center; align-items: center; height: 200px;">
+                                                <div style="text-align: center;">
+                                                    <div class="loading-spinner" style="width: 40px; height: 40px; border: 4px solid #f3f3f3; border-top: 4px solid #3498db; border-radius: 50%; animation: spin 1s linear infinite; margin: 0 auto;"></div>
+                                                    <p style="margin-top: 20px; color: #666;">Loading investment suggestions for {company}...</p>
+                                                    <style>
+                                                        @keyframes spin {{
+                                                            0% {{ transform: rotate(0deg); }}
+                                                            100% {{ transform: rotate(360deg); }}
+                                                        }}
+                                                    </style>
+                                                </div>
+                                            </div>
+                                            '''
+                                            yield loading_html
+                                            
+                                            # 获取投资建议数据
+                                            try:
+                                                content = get_invest_suggest(company)
+                                                yield content
+                                            except Exception as e:
+                                                error_html = f'''
+                                                <div style="padding: 20px; text-align: center; color: #666;">
+                                                    <p>Error loading investment suggestions: {str(e)}</p>
+                                                    <p>Please try again later.</p>
+                                                </div>
+                                                '''
+                                                yield error_html
+                                        else:
+                                            yield "<div style=\"padding: 20px; text-align: center; color: #666;\">Please select a company</div>"
+                                    
+                                    selected_company_state.change(
+                                        fn=update_tab_content,
+                                        inputs=[selected_company_state],
+                                        outputs=[tab_content],
+                                    )
+                                with gr.TabItem("Analysis Report", elem_classes=["tab-item"]):
+                                    # 创建一个用于显示公司名称的组件
+                                    # analysis_company_display = gr.Markdown("# Please select a company")
+                                    # 创建一个占位符用于显示tab内容
+                                    analysis_tab_content = gr.Markdown(elem_classes=["analysis-report-md-box"])
+                                    
+                                    # 当选中的公司改变时，更新显示
+                                    # selected_company_state.change(
+                                    #     fn=lambda company: f"# Analysis Report for {company}" if company else "# Please select a company",
+                                    #     inputs=[selected_company_state],
+                                    #     outputs=[analysis_company_display]
+                                    # )
+                                    
+                                    # 当选中的公司改变时，重新加载tab内容
+                                    def update_analysis_tab_content(company):
+                                        if company:
+                                            # 显示loading状态
+                                            loading_html = f'''
+                                            <div style="display: flex; justify-content: center; align-items: center; height: 200px;">
+                                                <div style="text-align: center;">
+                                                    <div class="loading-spinner" style="width: 40px; height: 40px; border: 4px solid #f3f3f3; border-top: 4px solid #3498db; border-radius: 50%; animation: spin 1s linear infinite; margin: 0 auto;"></div>
+                                                    <p style="margin-top: 20px; color: #666;">Loading analysis report for {company}...</p>
+                                                    <style>
+                                                        @keyframes spin {{
+                                                            0% {{ transform: rotate(0deg); }}
+                                                            100% {{ transform: rotate(360deg); }}
+                                                        }}
+                                                    </style>
+                                                </div>
+                                            </div>
+                                            '''
+                                            yield loading_html
+                                            
+                                            # 获取分析报告数据
+                                            try:
+                                                # 这里应该调用获取详细分析报告的函数
+                                                # 暂时使用占位内容，您需要替换为实际的函数调用
+                                                # content = f"# Analysis Report for {company}\n\nDetailed financial analysis for {company} will be displayed here."
+                                                yield get_analysis_report(company)
+                                            except Exception as e:
+                                                error_html = f'''
+                                                <div style="padding: 20px; text-align: center; color: #666;">
+                                                    <p>Error loading analysis report: {str(e)}</p>
+                                                    <p>Please try again later.</p>
+                                                </div>
+                                                '''
+                                                yield error_html
+                                        else:
+                                            yield "<div style=\"padding: 20px; text-align: center; color: #666;\">Please select a company</div>"
+                                    
+                                    selected_company_state.change(
+                                        fn=update_analysis_tab_content,
+                                        inputs=[selected_company_state],
+                                        outputs=[analysis_tab_content]
+                                    )
+                                # with gr.TabItem("Comparison", elem_classes=["tab-item"]):
+                                #     create_tab_content("comparison")
+                        with gr.Column(scale=2, min_width=400):
+                            # 聊天面板
+                            # gr.ChatInterface(
+                            #     respond,
+                            #     title="Easy Financial Report",
+                            #     # label="Easy Financial Report",
+                            #     additional_inputs=[
+                            #         # gr.Textbox(value="You are a financial analysis assistant. Provide concise investment insights from company financial reports.", label="System message"),
+                            #         # gr.Slider(minimum=1, maximum=4096, value=1024, step=1, label="Max new tokens"),
+                            #         # gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
+                            #         # gr.Slider(
+                            #         #     minimum=0.1,
+                            #         #     maximum=1.0,
+                            #         #     value=0.95,
+                            #         #     step=0.05,
+                            #         #     label="Top-p (nucleus sampling)",
+                            #         # ),
+                            #         gr.State(value="")  # CRITICAL: Add State to store session URL across turns
+                            #     ],
+                            # )
+                            # chatbot.render()
+                            # gr.LoginButton()
+                            gr.ChatInterface(
+                                respond,
+                                title="Easy Financial Report",
+                                additional_inputs=[
+                                    gr.State(value=""),  # CRITICAL: Store session URL across turns (hidden from UI)
+                                    gr.State(value={})   # CRITICAL: Store agent context across turns (hidden from UI)
+                                ],
+                                additional_inputs_accordion=gr.Accordion(label="Settings", open=False, visible=False),  # Hide the accordion completely
+                            )
+                            # chatbot.render()
+
+                            # with gr.Blocks() as demo:
+                            #     # Add custom CSS for Agent Plan styling
+                            #     gr.Markdown("""
+                            #     <style>
+                            #     .agent-plan {
+                            #         background-color: #f8f9fa;
+                            #         border-left: 4px solid #6c757d;
+                            #         padding: 10px;
+                            #         margin: 10px 0;
+                            #         border-radius: 4px;
+                            #         font-family: monospace;
+                            #         color: #495057;
+                            #     }
+                            #     </style>
+                            #     """)                                
+                                # chatbot.render()
+            
+            # 在页面加载时自动刷新公司列表，确保显示最新的数据
+            # demo.load(
+            #     fn=get_company_list_choices,
+            #     inputs=[],
+            #     outputs=[company_list_component],
+            #     concurrency_limit=None,
+            # )
+            
+            # 绑定公司选择事件到状态更新
+            # 注意：这里需要确保create_sidebar中没有重复绑定相同的事件
+            company_list_component.change(
+                fn=lambda x: x,  # 直接返回选中的公司名称
+                inputs=[company_list_component],
+                outputs=[selected_company_state],
+                concurrency_limit=None
+            )
+            
+            # 绑定公司选择事件到指标仪表板更新
+            def update_metrics_dashboard_wrapper(company_name):
+                if company_name:
+                    # 显示loading状态
+                    loading_html = f'''
+                    <div style="display: flex; justify-content: center; align-items: center; height: 300px;">
+                        <div style="text-align: center;">
+                            <div class="loading-spinner" style="width: 40px; height: 40px; border: 4px solid #f3f3f3; border-top: 4px solid #3498db; border-radius: 50%; animation: spin 1s linear infinite; margin: 0 auto;"></div>
+                            <p style="margin-top: 20px; color: #666;">Loading financial data for {company_name}...</p>
+                            <style>
+                                @keyframes spin {{
+                                    0% {{ transform: rotate(0deg); }}
+                                    100% {{ transform: rotate(360deg); }}
+                                }}
+                            </style>
+                        </div>
+                    </div>
+                    '''
+                    yield loading_html, loading_html, loading_html
+                    
+                    # 获取更新后的数据
+                    try:
+                        stock_card_html, financial_metrics_html, income_table_html = update_metrics_dashboard(company_name)
+                        yield stock_card_html, financial_metrics_html, income_table_html
+                    except Exception as e:
+                        error_html = f'''
+                        <div style="padding: 20px; text-align: center; color: #666;">
+                            <p>Error loading financial data: {str(e)}</p>
+                            <p>Please try again later.</p>
+                        </div>
+                        '''
+                        yield error_html, error_html, error_html
+                else:
+                    # 如果没有选择公司，返回空内容
+                    empty_html = "<div style=\"padding: 20px; text-align: center; color: #666;\">Please select a company</div>"
+                    yield empty_html, empty_html, empty_html
+            
+            selected_company_state.change(
+                fn=update_metrics_dashboard_wrapper,
+                inputs=[selected_company_state],
+                outputs=list(metrics_dashboard_components),
+                concurrency_limit=None
+            )
+    
+    return demo
+
+if __name__ == "__main__":
+    demo = main()
+    demo.launch(share=True)

app.py

@@ -4,20 +4,24 @@ import datetime
 import re
 import pandas as pd
 from sqlalchemy import true
+# from EasyFinancialAgent.chat import query_company
 from chatbot.chat_main import respond
 import globals as g
 from service.mysql_service import get_companys, insert_company, get_company_by_name
 from service.chat_service import get_analysis_report, get_stock_price_from_bailian, search_company, search_news, get_invest_suggest, chat_bot
 from service.company import check_company_exists
 from service.hf_upload import get_hf_files_with_links
-from service.news_quote_mcp import get_company_news, get_quote
-from service.report_mcp import query_financial_data
+from MarketandStockMCP.news_quote_mcp import get_company_news, get_quote
+from EasyReportDataMCP.report_mcp import query_financial_data
+from service.report_service import get_report_data, query_company_advanced
 from service.report_tools import build_financial_metrics_three_year_data, calculate_yoy_comparison, extract_financial_table, extract_last_three_with_fallback, get_yearly_data
 from service.three_year_table_tool import build_table_format
 from service.three_year_tool import  process_financial_data_with_metadata
 from service.tool_processor import get_stock_price
 
+
 get_companys_state = True
+my_companies = []
 # JavaScript代码用于读取和存储数据
 js_code = """
 function handleStorage(operation, key, value) {
@@ -139,7 +143,8 @@ def get_company_list_choices():
     if not get_companys_state:
         return gr.update(choices=choices)
     try:
-        companies_data = get_companys()
+        # companies_data = get_companys()
+        companies_data = my_companies
         print(f"Getting init add company list choices...companies_data: {companies_data}")
         if isinstance(companies_data, pd.DataFrame) and not companies_data.empty:
             choices = [str(row.get('company_name', 'Unknown')) for _, row in companies_data.iterrows()]
@@ -158,27 +163,22 @@ def handle_company_click(company_name):
     print(f"Handling click for company: {company_name}")
     
     # 1. 判断是否已经入库
-    if not check_company_exists(company_name):
+    if not check_company_exists(my_companies, company_name):
         # 2. 如果没有入库，则进行入库操作
         # 获取股票代码（如果有的话）
         stock_code = companies_map.get(company_name, {}).get("CODE", "Unknown")
         print(f"Inserting company {company_name} with code {stock_code}")
         
         # 插入公司到数据库
-        success = insert_company(company_name, stock_code)
-        if success:
-            print(f"Successfully inserted company: {company_name}")
-            # 直接更新companies_map，而不是重新加载整个映射
-            companies_map[company_name] = {"NAME": company_name, "CODE": stock_code}
-            # 使用Gradio的成功提示
-            gr.Info(f"Successfully added company: {company_name}")
-            # 返回True表示添加成功，需要刷新列表
-            return True
-        else:
-            print(f"Failed to insert company: {company_name}")
-            # 使用Gradio的错误提示
-            gr.Error(f"Failed to insert company: {company_name}")
-            return False
+        # success = insert_company(company_name, stock_code)
+        my_companies.append({"company_name": company_name, "stock_code": stock_code})
+        print(f"Successfully inserted company: {company_name}")  # 直接更新companies_map，而不是重新加载整个映射
+        # 直接更新companies_map，而不是重新加载整个映射
+        companies_map[company_name] = {"NAME": company_name, "CODE": stock_code}
+        # 使用Gradio的成功提示
+        gr.Info(f"Successfully added company: {company_name}")
+        # 返回True表示添加成功，需要刷新列表
+        return True
     else:
         print(f"Company {company_name} already exists in database")
         # 使用Gradio的警告提示
@@ -190,7 +190,8 @@ def handle_company_click(company_name):
 def get_company_list_html(selected_company=""):
     try:
         # 从数据库获取所有公司
-        companies_data = get_companys()
+        # companies_data = get_companys()
+        companies_data = my_companies
         # 检查是否为错误信息
         if isinstance(companies_data, str):
             if "查询执行失败" in companies_data:
@@ -247,8 +248,12 @@ def select_company(company_name):
     g.SELECT_COMPANY = company_name if company_name else ""
     # 对于Radio组件，我们只需要返回更新后的选项列表
     try:
-        companies_data = get_companys()
-        if isinstance(companies_data, pd.DataFrame) and not companies_data.empty:
+        # companies_data = get_companys()
+        companies_data = my_companies
+        if isinstance(companies_data, list) and len(companies_data) > 0:
+            # my_companies 是对象列表 [{company_name: '', stock_code: ''}, ...]
+            choices = [str(item.get('company_name', 'Unknown')) for item in companies_data]
+        elif isinstance(companies_data, pd.DataFrame) and not companies_data.empty:
             choices = [str(row.get('company_name', 'Unknown')) for _, row in companies_data.iterrows()]
         else:
             choices = []
@@ -287,7 +292,8 @@ def initialize_companies_map():
         print(f"Predefined companies added: {len(predefined_companies)}")
         
         # 从数据库获取公司数据
-        companies_data = get_companys()
+        # companies_data = get_companys()
+        companies_data = my_companies
         # companies_data = window.cachedCompanies or []
 
 
@@ -408,31 +414,32 @@ def add_company(selected, current_list):
         # print(f"Company name: {company_name}, Stock code: {stock_code}")
         # print(f"Company exists: {check_company_exists(company_name)}")
         
-        if not check_company_exists(company_name):
+        if not check_company_exists(my_companies, company_name):
             # 入库
-            success = insert_company(company_name, stock_code)
-            if success:
-                # 从数据库获取更新后的公司列表
-                try:
-                    companies_data = get_companys()
-                    if isinstance(companies_data, pd.DataFrame) and not companies_data.empty:
-                        updated_list = [str(row.get('company_name', 'Unknown')) for _, row in companies_data.iterrows()]
-                    else:
-                        updated_list = []
-                except:
+            # success = insert_company(company_name, stock_code)
+            my_companies.append({"company_name": company_name, "stock_code": stock_code})
+            # 从数据库获取更新后的公司列表
+            try:
+                # companies_data = get_companys()
+                companies_data = my_companies
+                if isinstance(companies_data, list) and len(companies_data) > 0:
+                    # my_companies 是对象列表 [{company_name: '', stock_code: ''}, ...]
+                    updated_list = [str(item.get('company_name', 'Unknown')) for item in companies_data]
+                elif isinstance(companies_data, pd.DataFrame) and not companies_data.empty:
+                    updated_list = [str(row.get('company_name', 'Unknown')) for _, row in companies_data.iterrows()]
+                else:
+                    updated_list = []
+            except:
                     updated_list = []
                 
-                # 添加默认公司选项
-                if not updated_list:
-                    updated_list = ['Alibaba', '腾讯控股', 'Tencent', '阿里巴巴-W', 'Apple']
+            # 添加默认公司选项
+            if not updated_list:
+                updated_list = ['Alibaba', '腾讯控股', 'Tencent', '阿里巴巴-W', 'Apple']
                 
-                # 成功插入后清除状态消息，并更新Radio组件的选项，同时默认选中刚添加的公司
-                # 通过设置value参数，会自动触发change事件来加载数据
-                return gr.update(visible=False), gr.update(choices=updated_list, value=company_name), gr.update(visible=False, value="")
-            else:
-                # 插入失败显示错误消息，使用Gradio内置的错误提示
-                gr.Error("插入公司失败")
-                return gr.update(visible=False), current_list, gr.update(visible=False, value="")
+            # 成功插入后清除状态消息，并更新Radio组件的选项，同时默认选中刚添加的公司
+            # 通过设置value参数，会自动触发change事件来加载数据
+            return gr.update(visible=False), gr.update(choices=updated_list, value=company_name), gr.update(visible=False, value="")
+            
         else:
             # 公司已存在，使用Gradio内置的警告消息
             gr.Warning(f"公司 '{company_name}' 已存在")
@@ -498,35 +505,48 @@ def update_report_section(selected_company, report_data, stock_code):
         return gr.update(value=html_content, visible=True)
     else:
         # 有选中的公司，显示相关报告
-        # try:
-        #     # 尝试从Hugging Face获取文件列表
-        #     report_data = get_hf_files_with_links("JC321/files-world")
-        # except Exception as e:
-        #     # 如果获取失败，使用模拟数据并显示错误消息
-        #     print(f"获取Hugging Face文件列表失败: {str(e)}")
-        #     report_data = []
-        stock_code = get_stock_code_by_company_name(selected_company)
-        report_data = query_financial_data(stock_code, "5-Year")
-        # report_data = process_financial_data_with_metadata(financial_metrics_pre)
-        
-        html_content = '<div class="report-list-box bg-white">'
-        html_content += '<div class="report-list-title bg-white card-title  left-card-title" style="border-bottom: 1px solid #e3e3e6 !important;"><h3>Financial Reports</h3></div>'
-        for report in report_data:
-            html_content += f'''
-            <div class="report-item bg-white hover:bg-blue-50 cursor-pointer" onclick="window.open('{report['source_url']}', '_blank')">
+        try:
+            # prmpt = f"""
+            
+            # """
+            stock_code = get_stock_code_by_company_name(selected_company)
+            result = get_report_data(stock_code)
+            print(f"get_report_data=====================: {result}")
+            report_data = query_financial_data(stock_code, "5-Year")
+            # report_data = process_financial_data_with_metadata(financial_metrics_pre)
+            
+            # 检查 report_data 是否是列表且第一个元素是字典
+            if not isinstance(report_data, list) or len(report_data) == 0:
+                return gr.update(value="<div>暂无报告数据</div>", visible=True)
+            
+            # 检查第一个元素是否是字典
+            if not isinstance(report_data[0], dict):
+                return gr.update(value="<div>数据格式不正常</div>", visible=True)
+            
+            html_content = '<div class="report-list-box bg-white">'
+            html_content += '<div class="report-list-title bg-white card-title  left-card-title" style="border-bottom: 1px solid #e3e3e6 !important;"><h3>Financial Reports</h3></div>'
+            for report in report_data:
+                source_url = report.get('source_url', '#')
+                period = report.get('period', 'N/A')
+                source_form = report.get('source_form', 'N/A')
+                html_content += f'''
+            <div class="report-item bg-white hover:bg-blue-50 cursor-pointer" onclick="window.open('{source_url}', '_blank')">
                 <div class="report-item-content">
-                    <span class="text-gray-800">{report['period']}-{stock_code}-{report['source_form']}</span>
+                    <span class="text-gray-800">{period}-{stock_code}-{source_form}</span>
                     <svg xmlns="http://www.w3.org/2000/svg" width="12" height="12" class="text-blue-500" viewBox="0 0 20 20" fill="currentColor">
                         <path fill-rule="evenodd" d="M12.586 4.586a2 2 0 112.828 2.828l-3 3a2 2 0 01-2.828 0 1 1 0 10-1.414 1.414 4 4 0 005.656 0l3-3a4 4 0 00-5.656-5.656l-1.5 1.5a1 1 0 101.414 1.414l-1.5-1.5zm-5 5a2 2 0 012.828 0 1 1 0 101.414-1.414 4 4 0 00-5.656 0l-3 3a4 4 0 105.656 5.656l1.5-1.5a1 1 0 10-1.414-1.414l-1.5 1.5a2 2 0 11-2.828-2.828l3-3z" clip-rule="evenodd" />
                     </svg>
                 </div>
             </div>
             '''
-        
-        html_content += f'<div class="pdf-footer mt-3"><span class="text-xs text-gray-500">共{len(report_data)}份报告</span></div>'
-        html_content += '</div>'
-        
-        return gr.update(value=html_content, visible=True)
+            
+            html_content += f'<div class="pdf-footer mt-3"><span class="text-xs text-gray-500">共{len(report_data)}份报告</span></div>'
+            html_content += '</div>'
+            
+            return gr.update(value=html_content, visible=True)
+        except Exception as e:
+            print(f"Error in update_report_section: {str(e)}")
+            return gr.update(value=f"<div>报告载入失败: {str(e)}</div>", visible=True)
 def update_news_section(selected_company):
     """根据选中的公司更新报告部分"""
     html_content = ""
@@ -599,44 +619,38 @@ def create_header():
             gr.Markdown(current_time, elem_classes=["text-sm-top-time"])
 
 def create_company_list(get_companys_state):
+    """创建公司列表组件"""
+    try:
+        # 获取公司列表数据
+        # companies_data = get_companys()
+        companies_data = my_companies
+        print(f"创建公司列表组件 - Companies data: {companies_data}")
+        if isinstance(companies_data, list) and len(companies_data) > 0:
+            # my_companies 是对象列表 [{company_name: '', stock_code: ''}, ...]
+            choices = [str(item.get('company_name', 'Unknown')) for item in companies_data]
+        elif isinstance(companies_data, pd.DataFrame) and not companies_data.empty:
+            choices = [str(row.get('company_name', 'Unknown')) for _, row in companies_data.iterrows()]
+        else:
+            choices = []
+    except Exception as e:
+        print(f"Error creating company list: {str(e)}")
+        choices = []
+    
+    # 添加默认公司选项
+    if not choices:
+        choices = []
+    
+    # 使用Radio组件显示公司列表，不显示标签
     company_list = gr.Radio(
-        choices=[],
+        choices=choices,
         label="",
         interactive=True,
         elem_classes=["company-list-container"],
         container=False,  # 不显示外部容器边框
         visible=True
-      ) 
-    if (get_companys_state == False):
-        return company_list
-    else:
-        """创建公司列表组件"""
-        # 获取公司列表数据
-        try:
-            companies_data = get_companys()
-            print(f"创建公司列表组件 - Companies data: {companies_data}")
-            if isinstance(companies_data, pd.DataFrame) and not companies_data.empty:
-                choices = [str(row.get('company_name', 'Unknown')) for _, row in companies_data.iterrows()]
-            else:
-                choices = []
-        except:
-            choices = []
-        
-        # 添加默认公司选项
-        if not choices:
-            choices = []
-        
-        # 使用Radio组件显示公司列表，不显示标签
-        company_list = gr.Radio(
-            choices=choices,
-            label="",
-            interactive=True,
-            elem_classes=["company-list-container"],
-            container=False,  # 不显示外部容器边框
-            visible=True
-        )
-    
-        return company_list
+    )
+
+    return company_list
 
 def create_company_selector():
     """创建公司选择器组件"""
@@ -830,8 +844,12 @@ def create_sidebar():
                         if result is True:
                             # 正确地刷新通过create_company_list()创建的Radio组件
                             try:
-                                companies_data = get_companys()
-                                if isinstance(companies_data, pd.DataFrame) and not companies_data.empty:
+                                # companies_data = get_companys()
+                                companies_data = my_companies
+                                if isinstance(companies_data, list) and len(companies_data) > 0:
+                                    # my_companies 是对象列表 [{company_name: '', stock_code: ''}, ...]
+                                    updated_choices = [str(item.get('company_name', 'Unknown')) for item in companies_data]
+                                elif isinstance(companies_data, pd.DataFrame) and not companies_data.empty:
                                     updated_choices = [str(row.get('company_name', 'Unknown')) for _, row in companies_data.iterrows()]
                                 else:
                                     updated_choices = []
@@ -1786,6 +1804,9 @@ def main():
                                                 # 这里应该调用获取详细分析报告的函数
                                                 # 暂时使用占位内容，您需要替换为实际的函数调用
                                                 # content = f"# Analysis Report for {company}\n\nDetailed financial analysis for {company} will be displayed here."
+                                                stock_code = get_stock_code_by_company_name(company)
+                                                result = query_company_advanced(stock_code)
+                                                print(f"Result=====================: {result}")
                                                 yield get_analysis_report(company)
                                             except Exception as e:
                                                 error_html = f'''
@@ -1805,55 +1826,20 @@ def main():
                                     )
                                 # with gr.TabItem("Comparison", elem_classes=["tab-item"]):
                                 #     create_tab_content("comparison")
-                        with gr.Column(scale=2, min_width=400):
+                        # with gr.Column(scale=2, min_width=400):
                             # 聊天面板
+                          
+                            # chatbot.render()
+                            # gr.LoginButton()
                             # gr.ChatInterface(
                             #     respond,
                             #     title="Easy Financial Report",
-                            #     # label="Easy Financial Report",
                             #     additional_inputs=[
-                            #         # gr.Textbox(value="You are a financial analysis assistant. Provide concise investment insights from company financial reports.", label="System message"),
-                            #         # gr.Slider(minimum=1, maximum=4096, value=1024, step=1, label="Max new tokens"),
-                            #         # gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-                            #         # gr.Slider(
-                            #         #     minimum=0.1,
-                            #         #     maximum=1.0,
-                            #         #     value=0.95,
-                            #         #     step=0.05,
-                            #         #     label="Top-p (nucleus sampling)",
-                            #         # ),
-                            #         gr.State(value="")  # CRITICAL: Add State to store session URL across turns
+                            #         gr.State(value=""),  # CRITICAL: Store session URL across turns (hidden from UI)
+                            #         gr.State(value={})   # CRITICAL: Store agent context across turns (hidden from UI)
                             #     ],
+                            #     additional_inputs_accordion=gr.Accordion(label="Settings", open=False, visible=False),  # Hide the accordion completely
                             # )
-                            # chatbot.render()
-                            # gr.LoginButton()
-                            gr.ChatInterface(
-                                respond,
-                                title="Easy Financial Report",
-                                additional_inputs=[
-                                    gr.State(value=""),  # CRITICAL: Store session URL across turns (hidden from UI)
-                                    gr.State(value={})   # CRITICAL: Store agent context across turns (hidden from UI)
-                                ],
-                                additional_inputs_accordion=gr.Accordion(label="Settings", open=False, visible=False),  # Hide the accordion completely
-                            )
-                            # chatbot.render()
-
-                            # with gr.Blocks() as demo:
-                            #     # Add custom CSS for Agent Plan styling
-                            #     gr.Markdown("""
-                            #     <style>
-                            #     .agent-plan {
-                            #         background-color: #f8f9fa;
-                            #         border-left: 4px solid #6c757d;
-                            #         padding: 10px;
-                            #         margin: 10px 0;
-                            #         border-radius: 4px;
-                            #         font-family: monospace;
-                            #         color: #495057;
-                            #     }
-                            #     </style>
-                            #     """)                                
-                                # chatbot.render()
             
             # 在页面加载时自动刷新公司列表，确保显示最新的数据
             # demo.load(

requirements.txt

@@ -14,4 +14,9 @@ httpx>=0.23.0
 pymysql
 sse-starlette>=1.6.5
 starlette>=0.27.0
-mcp>=1.0.0
+mcp>=1.0.0
+uvicorn[standard]==0.27.0
+pydantic==2.5.3
+
+# SEC EDGAR API
+sec-edgar-api==1.1.0

service/news_quote_mcp_server.py

@@ -1,321 +0,0 @@
-#!/usr/bin/env python3
-"""
-Finnhub MCP Server - Standard MCP Protocol (JSON-RPC over SSE)
-
-This is a standalone MCP server that implements the standard Model Context Protocol.
-It provides three tools for accessing Finnhub financial data:
-- get_quote: Real-time stock quotes
-- get_market_news: Latest market news by category
-- get_company_news: Company-specific news
-
-Usage:
-    python mcp_server.py
-
-Environment Variables:
-    FINNHUB_API_KEY: Your Finnhub API key (required)
-"""
-
-import os
-import requests
-from typing import Optional, Dict, Any
-from datetime import datetime, timedelta
-from mcp.server.fastmcp import FastMCP
-
-# Initialize FastMCP server with standard MCP protocol
-mcp = FastMCP("finnhub-market-info")
-
-
-def get_api_key() -> Optional[str]:
-    """Get the Finnhub API key from environment"""
-    return os.getenv("FINNHUB_API_KEY")
-
-
-def make_finnhub_request(endpoint: str, params: Dict[str, Any]) -> Dict[str, Any]:
-    """
-    Make a request to Finnhub API
-    
-    Args:
-        endpoint: API endpoint path
-        params: Query parameters
-    
-    Returns:
-        API response as dictionary
-    """
-    api_key = get_api_key()
-    if not api_key:
-        return {"error": "API key not configured. Please set FINNHUB_API_KEY environment variable."}
-    
-    params["token"] = api_key
-    base_url = "https://finnhub.io/api/v1"
-    url = f"{base_url}/{endpoint}"
-    
-    try:
-        response = requests.get(url, params=params, timeout=10)
-        response.raise_for_status()
-        return response.json()
-    except requests.exceptions.RequestException as e:
-        return {"error": f"API request failed: {str(e)}"}
-
-
-@mcp.tool()
-def get_quote(symbol: str) -> dict:
-    """
-    Get real-time quote data for US stocks. Use this tool when you need current stock price 
-    information and market performance metrics for any US-listed stock.
-    
-    When to use:
-    - User asks "What's the current price of [stock]?"
-    - Need real-time stock quote data
-    - User mentions "stock price", "current value", "how is [stock] trading?"
-    - Want to check latest market price and daily changes
-    
-    Examples:
-    - "What's Apple's stock price?" → get_quote(symbol="AAPL")
-    - "How is Tesla trading today?" → get_quote(symbol="TSLA")
-    - "Show me Microsoft's current quote" → get_quote(symbol="MSFT")
-    
-    Args:
-        symbol: Stock ticker symbol (e.g., 'AAPL', 'MSFT', 'TSLA', 'GOOGL')
-    
-    Returns:
-        dict: Real-time quote data containing:
-              - symbol: Stock ticker symbol
-              - current_price: Current trading price (c)
-              - change: Price change in dollars (d)
-              - percent_change: Price change in percentage (dp)
-              - high: Today's high price (h)
-              - low: Today's low price (l)
-              - open: Opening price (o)
-              - previous_close: Previous trading day's closing price (pc)
-              - timestamp: Quote timestamp
-    """
-    result = make_finnhub_request("quote", {"symbol": symbol.upper()})
-    
-    if "error" in result:
-        return {
-            "error": result["error"],
-            "symbol": symbol.upper()
-        }
-    
-    # Return structured data
-    return {
-        "symbol": symbol.upper(),
-        "current_price": result.get('c'),
-        "change": result.get('d'),
-        "percent_change": result.get('dp'),
-        "high": result.get('h'),
-        "low": result.get('l'),
-        "open": result.get('o'),
-        "previous_close": result.get('pc'),
-        "timestamp": datetime.fromtimestamp(result.get('t', 0)).strftime('%Y-%m-%d %H:%M:%S') if result.get('t') else None
-    }
-
-
-@mcp.tool()
-def get_market_news(category: str = "general", min_id: int = 0) -> dict:
-    """
-    Get latest market news across different categories. Use this tool when you need current market 
-    news, trends, and developments in general markets, forex, cryptocurrency, or mergers.
-    
-    When to use:
-    - User asks "What's the latest market news?"
-    - Need current financial news and market updates
-    - User mentions "news", "market trends", "what's happening in the market?"
-    - Want to get news for specific categories (forex, crypto, M&A)
-    
-    Categories explained:
-    - general: General market news, stocks, economy, major companies
-    - forex: Foreign exchange and currency market news
-    - crypto: Cryptocurrency and blockchain news
-    - merger: Mergers & acquisitions, corporate deals
-    
-    Examples:
-    - "What's the latest market news?" → get_market_news(category="general")
-    - "Show me crypto news" → get_market_news(category="crypto")
-    - "Any forex updates?" → get_market_news(category="forex")
-    - "Recent merger news" → get_market_news(category="merger")
-    
-    Args:
-        category: News category - "general", "forex", "crypto", or "merger" (default: "general")
-        min_id: Minimum news ID for pagination (default: 0, use 0 to get latest news)
-    
-    Returns:
-        dict: Market news data containing:
-              - category: News category requested
-              - total_articles: Total number of articles returned
-              - articles: List of news articles (max 10), each with:
-                * id: Article ID
-                * headline: News headline
-                * summary: Brief summary of the article
-                * source: News source
-                * url: Link to full article
-                * published: Publication timestamp
-                * image: Article image URL (if available)
-    """
-    params = {"category": category}
-    if min_id > 0:
-        params["minId"] = str(min_id)
-    
-    result = make_finnhub_request("news", params)
-    
-    if isinstance(result, dict) and "error" in result:
-        return {
-            "error": result["error"],
-            "category": category
-        }
-    
-    if not result or len(result) == 0:
-        return {
-            "category": category,
-            "total_articles": 0,
-            "articles": [],
-            "message": "No news articles found for this category"
-        }
-    
-    # Format the news articles
-    articles = []
-    for article in result[:10]:  # Limit to 10 articles  # pyright: ignore[reportArgumentType]
-        articles.append({
-            "id": article.get('id'),
-            "headline": article.get('headline', 'No headline'),
-            "summary": article.get('summary', ''),
-            "source": article.get('source', 'Unknown'),
-            "url": article.get('url'),
-            "published": datetime.fromtimestamp(article.get('datetime', 0)).strftime('%Y-%m-%d %H:%M:%S') if article.get('datetime') else None,
-            "image": article.get('image')
-        })
-    
-    return {
-        "category": category,
-        "total_articles": len(articles),
-        "articles": articles
-    }
-
-
-@mcp.tool()
-def get_company_news(symbol: str, from_date: Optional[str] = None, to_date: Optional[str] = None) -> dict:
-    """
-    Get latest news for a specific company by stock symbol. This endpoint provides company-specific 
-    news, press releases, and announcements. Only available for North American companies.
-    
-    When to use:
-    - User asks about a specific company's news (e.g., "Apple news", "Tesla updates")
-    - Need company-specific announcements or press releases
-    - User mentions "[company name] news", "recent [company] developments"
-    - Want to filter news by date range
-    
-    Date range tips:
-    - Default: Last 7 days if no dates specified
-    - Can go back up to several years
-    - Use YYYY-MM-DD format (e.g., "2024-01-01")
-    
-    Examples:
-    - "What's the latest Apple news?" → get_company_news(symbol="AAPL")
-    - "Tesla news from last month" → get_company_news(symbol="TSLA", from_date="2024-10-01", to_date="2024-10-31")
-    - "Microsoft announcements this week" → get_company_news(symbol="MSFT")
-    - "Show me Amazon news from January 2024" → get_company_news(symbol="AMZN", from_date="2024-01-01", to_date="2024-01-31")
-    
-    Args:
-        symbol: Company stock ticker symbol (e.g., 'AAPL', 'MSFT', 'TSLA', 'GOOGL')
-                Must be a North American (US/Canada) listed company
-        from_date: Start date in YYYY-MM-DD format (default: 7 days ago)
-        to_date: End date in YYYY-MM-DD format (default: today)
-    
-    Returns:
-        dict: Company news data containing:
-              - symbol: Company stock symbol
-              - from_date: Start date of news range
-              - to_date: End date of news range
-              - total_articles: Total number of articles returned
-              - articles: List of news articles (max 10), each with:
-                * headline: News headline
-                * summary: Brief summary
-                * source: News source
-                * url: Link to full article
-                * published: Publication timestamp
-                * related: Related stock symbols (if any)
-    """
-    # Set default date range if not provided
-    if not to_date:
-        to_date = datetime.now().strftime('%Y-%m-%d')
-    
-    if not from_date:
-        from_date = (datetime.now() - timedelta(days=7)).strftime('%Y-%m-%d')
-    
-    params = {
-        "symbol": symbol.upper(),
-        "from": from_date,
-        "to": to_date
-    }
-    
-    result = make_finnhub_request("company-news", params)
-    
-    if isinstance(result, dict) and "error" in result:
-        return {
-            "error": result["error"],
-            "symbol": symbol.upper(),
-            "from_date": from_date,
-            "to_date": to_date
-        }
-    
-    if not result or len(result) == 0:
-        # Provide helpful suggestions based on the symbol
-        suggestion = "Try expanding the date range or check if the symbol is correct."
-        if symbol.upper() in ["BABA", "BIDU", "JD", "PDD", "NIO"]:
-            suggestion = "Note: Chinese ADRs may have limited news coverage. Try US companies like AAPL, MSFT, TSLA, or GOOGL for better results."
-        
-        return {
-            "symbol": symbol.upper(),
-            "from_date": from_date,
-            "to_date": to_date,
-            "total_articles": 0,
-            "articles": [],
-            "message": f"No news found for {symbol.upper()} between {from_date} and {to_date}.",
-            "suggestion": suggestion,
-            "note": "Company news is only available for North American companies. Some companies may have limited news coverage during certain periods."
-        }
-    
-    # Format the news articles
-    articles = []
-    for article in result[:10]:  # Limit to 10 articles  # pyright: ignore[reportArgumentType]
-        articles.append({
-            "headline": article.get('headline', 'No headline'),
-            "summary": article.get('summary', ''),
-            "source": article.get('source', 'Unknown'),
-            "url": article.get('url'),
-            "published": datetime.fromtimestamp(article.get('datetime', 0)).strftime('%Y-%m-%d %H:%M:%S') if article.get('datetime') else None,
-            "related": article.get('related', '')
-        })
-    
-    return {
-        "symbol": symbol.upper(),
-        "from_date": from_date,
-        "to_date": to_date,
-        "total_articles": len(articles),
-        "articles": articles
-    }
-
-
-if __name__ == "__main__":
-    # Check for API key
-    api_key = get_api_key()
-    if not api_key:
-        print("❌ Error: FINNHUB_API_KEY environment variable is not set")
-        print("Please set your Finnhub API key:")
-        print("  export FINNHUB_API_KEY='your_api_key_here'")
-        exit(1)
-    
-    print("✅ API Key loaded from environment variable")
-    print("▶️  Starting Finnhub MCP Server (JSON-RPC over SSE)...")
-    print("📡 Server name: finnhub-market-info")
-    print("🔧 Protocol: Model Context Protocol (MCP)")
-    print("🌐 Transport: SSE (Server-Sent Events)")
-    print("")
-    print("Available tools:")
-    print("  • get_quote(symbol)")
-    print("  • get_market_news(category, min_id)")
-    print("  • get_company_news(symbol, from_date, to_date)")
-    print("")
-    
-    # Run the MCP server with SSE transport
-    mcp.run(transport="sse")

service/report_service.py

@@ -0,0 +1,311 @@
+"""
+Report Service - 财务报告数据服务
+集成 EasyFinancialAgent 的 MCP 工具，提供完整的数据查询方法
+"""
+
+from EasyFinancialAgent.chat_direct import (
+    search_company_direct,
+    get_company_info_direct,
+    extract_financial_metrics_direct,
+    get_company_filings_direct,
+    get_latest_financial_data_direct,
+    query_company_direct
+)
+from datetime import datetime
+from typing import Optional
+
+
+def get_report_data(symbol_or_name: str, years: int = 5):
+    """
+    获取公司完整财务报告数据
+    
+    Args:
+        symbol_or_name: 公司代码或名称 (e.g., "Apple", "AAPL", "0000320193")
+        years: 财务年限 (默认 5 年)
+    
+    Returns:
+        完整的报告数据字典，包含公司信息、财务指标、最新数据等
+    
+    Example:
+        report = get_report_data("Apple", years=5)
+    """
+    result = {
+        "timestamp": datetime.now().isoformat(),
+        "query_input": symbol_or_name,
+        "status": "success",
+        "data": {
+            "company_search": None,
+            "company_info": None,
+            "latest_financial": None,
+            "financial_metrics": None,
+            "filings": None
+        },
+        "errors": []
+    }
+    
+    try:
+        # 1. 搜索公司
+        print(f"[Report Service] 搜索公司: {symbol_or_name}")
+        search_result = search_company_direct(symbol_or_name)
+        print(f"[Report Service] 搜索结果: {search_result}")
+        if "error" in search_result:
+            result["errors"].append(f"Search failed: {search_result['error']}")
+            result["status"] = "error"
+            return result
+        
+        result["data"]["company_search"] = search_result
+        
+        # 从搜索结果提取 CIK
+        cik = None
+        if isinstance(search_result, dict):
+            cik = search_result.get("cik")
+        elif isinstance(search_result, (list, tuple)) and len(search_result) > 0:
+            try:
+                first = search_result[0] if isinstance(search_result, (list, tuple)) else None
+                if isinstance(first, dict):
+                    cik = first.get("cik")
+            except (IndexError, TypeError):
+                pass
+        
+        if not cik:
+            result["errors"].append("Could not extract CIK from search result")
+            result["status"] = "error"
+            return result
+        
+        print(f"[Report Service] 找到公司 CIK: {cik}")
+        
+        # 2. 获取公司详细信息
+        # print(f"[Report Service] 获取公司详细信息")
+        # company_info = get_company_info_direct(cik)
+        # if "error" not in company_info:
+        #     result["data"]["company_info"] = company_info
+        # else:
+        #     result["errors"].append(f"Failed to get company info: {company_info.get('error')}")
+        
+        # 3. 获取最新财务数据
+        # print(f"[Report Service] 获取最新财务数据")
+        # latest_data = get_latest_financial_data_direct(cik)
+        # if "error" not in latest_data:
+        #     result["data"]["latest_financial"] = latest_data
+        # else:
+        #     result["errors"].append(f"Failed to get latest financial data: {latest_data.get('error')}")
+        
+        # 4. 获取多年财务指标
+        print(f"[Report Service] 获取 {years} 年财务指标")
+        metrics = extract_financial_metrics_direct(cik, years=years)
+        if "error" not in metrics:
+            result["data"]["financial_metrics"] = metrics
+        else:
+            result["errors"].append(f"Failed to get financial metrics: {metrics.get('error')}")
+        
+        # 5. 获取公司文件列表
+        # print(f"[Report Service] 获取公司 SEC 文件列表")
+        # filings = get_company_filings_direct(cik)
+        # if "error" not in filings:
+        #     result["data"]["filings"] = filings
+        # else:
+        #     result["errors"].append(f"Failed to get filings: {filings.get('error')}")
+        
+        print(f"[Report Service] 报告数据获取完成")
+        
+    except Exception as e:
+        result["status"] = "error"
+        result["errors"].append(f"Exception: {str(e)}")
+        import traceback
+        result["errors"].append(traceback.format_exc())
+    
+    return result
+
+
+def get_company_summary(symbol_or_name: str):
+    """
+    获取公司摘要信息（轻量级查询）
+    
+    Args:
+        symbol_or_name: 公司代码或名称
+    
+    Returns:
+        公司摘要数据字典
+    
+    Example:
+        summary = get_company_summary("Tesla")
+    """
+    result = {
+        "timestamp": datetime.now().isoformat(),
+        "query_input": symbol_or_name,
+        "status": "success",
+        "data": {
+            "company_search": None,
+            "company_info": None,
+            "latest_financial": None
+        },
+        "errors": []
+    }
+    
+    try:
+        # 搜索公司
+        search_result = search_company_direct(symbol_or_name)
+        if "error" in search_result:
+            result["errors"].append(f"Search failed: {search_result['error']}")
+            result["status"] = "error"
+            return result
+        
+        result["data"]["company_search"] = search_result
+        
+        # 提取 CIK
+        cik = None
+        if isinstance(search_result, dict):
+            cik = search_result.get("cik")
+        elif isinstance(search_result, (list, tuple)) and len(search_result) > 0:
+            try:
+                first = search_result[0] if isinstance(search_result, (list, tuple)) else None
+                if isinstance(first, dict):
+                    cik = first.get("cik")
+            except (IndexError, TypeError):
+                pass
+        
+        if not cik:
+            result["errors"].append("Could not extract CIK")
+            result["status"] = "error"
+            return result
+        
+        # 获取公司信息
+        company_info = get_company_info_direct(cik)
+        if "error" not in company_info:
+            result["data"]["company_info"] = company_info
+        
+        # 获取最新财务数据
+        latest_data = get_latest_financial_data_direct(cik)
+        if "error" not in latest_data:
+            result["data"]["latest_financial"] = latest_data
+        
+    except Exception as e:
+        result["status"] = "error"
+        result["errors"].append(str(e))
+    
+    return result
+
+
+def get_financial_metrics(symbol_or_name: str, years: int = 5):
+    """
+    获取财务指标趋势数据
+    
+    Args:
+        symbol_or_name: 公司代码或名称
+        years: 年数（默认 5 年）
+    
+    Returns:
+        财务指标数据字典
+    
+    Example:
+        metrics = get_financial_metrics("Microsoft", years=10)
+    """
+    result = {
+        "timestamp": datetime.now().isoformat(),
+        "query_input": symbol_or_name,
+        "years": years,
+        "status": "success",
+        "data": None,
+        "errors": []
+    }
+    
+    try:
+        # 搜索公司
+        search_result = search_company_direct(symbol_or_name)
+        if "error" in search_result:
+            result["errors"].append(f"Search failed: {search_result['error']}")
+            result["status"] = "error"
+            return result
+        
+        # 提取 CIK
+        cik = None
+        if isinstance(search_result, dict):
+            cik = search_result.get("cik")
+        elif isinstance(search_result, (list, tuple)) and len(search_result) > 0:
+            try:
+                first = search_result[0] if isinstance(search_result, (list, tuple)) else None
+                if isinstance(first, dict):
+                    cik = first.get("cik")
+            except (IndexError, TypeError):
+                pass
+        
+        if not cik:
+            result["errors"].append("Could not extract CIK")
+            result["status"] = "error"
+            return result
+        
+        # 获取财务指标
+        metrics = extract_financial_metrics_direct(cik, years=years)
+        if "error" in metrics:
+            result["errors"].append(f"Failed to get metrics: {metrics['error']}")
+            result["status"] = "error"
+        else:
+            result["data"] = metrics
+        
+    except Exception as e:
+        result["status"] = "error"
+        result["errors"].append(str(e))
+    
+    return result
+
+
+def get_service_health():
+    """
+    检查财务数据服务健康状态
+    
+    Returns:
+        服务状态字典
+    
+    Example:
+        health = get_service_health()
+    """
+    return {
+        "status": "ok",
+        "message": "Using direct MCP functions (no HTTP service required)"
+    }
+
+
+def query_company_advanced(company_input: str, get_filings: bool = True, get_metrics: bool = True):
+    """
+    综合查询公司信息 (直接调用 chat_direct 的高级方法)
+    包括搜索、基本信息、文件列表和财务指标
+    
+    Args:
+        company_input: 公司名称或代码
+        get_filings: 是否获取文件列表
+        get_metrics: 是否获取财务指标
+    
+    Returns:
+        综合结果字典，包含 company_search, company_info, filings, metrics
+    
+    Example:
+        result = query_company_advanced("Apple", get_filings=True, get_metrics=True)
+    """
+    prompt = f"""
+        Role:
+
+        You are an expert investment advisor who provides data-driven recommendations based on a company’s financials, news, and market data.
+
+        Task:
+
+        Analyze the following for {company_input}:
+
+        Financial metrics – revenue, profit, debt, cash flow, etc.
+        Recent news – assess risks and opportunities.
+        Stock data – price trend, volume, etc.
+        Then provide clear, objective investment guidance in this format:
+
+        Investment Recommendation:
+
+        Recommendation: [Buy / Hold / Avoid]
+        Entry & Exit Price: [Specify]
+        Stop-Loss & Take-Profit Levels: [Specify]
+        Holding Horizon: Short-term (<1 month) or Long-term (>1 month)
+        Rules:
+        Base all advice strictly on factual data—no speculation.
+        Be concise, professional, and actionable.
+        Always include a risk disclaimer acknowledging market uncertainty.
+        Output must be in English only.
+    
+    """
+    return query_company_direct(prompt, get_filings=get_filings, get_metrics=get_metrics)