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README.md

@@ -1,13 +1,39 @@
----
-title: EastReportDataMCP Test
-emoji: 🏆
-colorFrom: pink
-colorTo: red
-sdk: gradio
-sdk_version: 6.0.1
-app_file: app.py
-pinned: false
-license: mit
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+---
+title: SEC Financial Data Query Assistant
+emoji: 📊
+colorFrom: blue
+colorTo: green
+sdk: gradio
+sdk_version: 4.0.0
+app_file: app.py
+pinned: false
+license: mit
+---
+
+# SEC Financial Data Query Assistant
+
+A Gradio-based web application for querying SEC financial data through MCP Server.
+
+## Features
+
+- 🔍 Search companies by name or ticker symbol
+- 📈 View latest financial data
+- 📊 Analyze 3-year and 5-year financial trends
+- 💰 Display revenue, net income, EPS, operating expenses, and cash flow metrics
+
+## Usage
+
+Simply enter a company name or ticker symbol (e.g., NVIDIA, AAPL, Microsoft) and select the query type:
+- **Latest Financial Data**: Shows the most recent fiscal year data
+- **3-Year Trend**: Displays financial trends over 3 years
+- **5-Year Trend**: Displays financial trends over 5 years
+
+## Data Source
+
+SEC EDGAR data via MCP Server: https://jc321-easyreportdatemcp.hf.space
+
+## Technology Stack
+
+- **Frontend**: Gradio 4.0+
+- **Backend**: Python with requests
+- **Data Source**: SEC EDGAR via MCP Server

app.py

@@ -68,6 +68,8 @@ def query_financial_data(company_name, query_type):
             result += f"- **总收入**: ${data.get('total_revenue', 0):,.0f} (${data.get('total_revenue', 0)/1e9:.2f}B)\n"
             result += f"- **净利润**: ${data.get('net_income', 0):,.0f} (${data.get('net_income', 0)/1e9:.2f}B)\n"
             result += f"- **每股收益**: ${data.get('earnings_per_share', 0):.2f}\n"
+            result += f"- **运营花费**: ${data.get('operating_expenses', 0):,.0f} (${data.get('operating_expenses', 0)/1e9:.2f}B)\n"
+            result += f"- **运营现金流**: ${data.get('operating_cash_flow', 0):,.0f} (${data.get('operating_cash_flow', 0)/1e9:.2f}B)\n"
             result += f"- **来源**: {data.get('source_form', 'N/A')}\n"
         
         elif query_type == "3年趋势":
@@ -89,20 +91,22 @@ def query_financial_data(company_name, query_type):
             if isinstance(metrics, dict) and metrics.get("error"):
                 return result + f"❌ {metrics['error']}"
             
-            result += f"## 财务趋势 (共 {metrics.get('count', 0)} 个期间)\n\n"
+            result += f"## Financial Trends ({metrics.get('count', 0)} periods)\n\n"
             
             # 只显示年度数据
             annual_data = [m for m in metrics.get('metrics', []) if 'Q' not in m.get('period', '')][:3]
             
-            result += "| 期间 | 收入(十亿) | 净利润(十亿) | EPS |\n"
-            result += "|------|-----------|------------|-----|\n"
+            result += "| Period | Revenue (B) | Net Income (B) | EPS | Operating Expenses (B) | Operating Cash Flow (B) |\n"
+            result += "|--------|-------------|----------------|-----|------------------------|-------------------------|\n"
             
             for m in annual_data:
-                period = m['period']
+                period = m.get('period', 'N/A')
                 rev = m.get('total_revenue', 0) / 1e9
                 inc = m.get('net_income', 0) / 1e9
                 eps = m.get('earnings_per_share', 0)
-                result += f"| FY{period} | ${rev:.2f}B | ${inc:.2f}B | ${eps:.2f} |\n"
+                opex = m.get('operating_expenses', 0) / 1e9
+                ocf = m.get('operating_cash_flow', 0) / 1e9
+                result += f"| FY{period} | ${rev:.2f}B | ${inc:.2f}B | ${eps:.2f} | ${opex:.2f}B | ${ocf:.2f}B |\n"
         
         elif query_type == "5年趋势":
             metrics_resp = requests.post(
@@ -125,15 +129,18 @@ def query_financial_data(company_name, query_type):
             
             annual_data = [m for m in metrics.get('metrics', []) if 'Q' not in m.get('period', '')][:5]
             
-            result += f"## 5年财务趋势\n\n"
-            result += "| 期间 | 收入 | 净利润 | EPS |\n"
-            result += "|------|------|--------|-----|\n"
+            result += f"## 5-Year Financial Trends\n\n"
+            result += "| Period | Revenue (B) | Net Income (B) | EPS | Operating Expenses (B) | Operating Cash Flow (B) |\n"
+            result += "|--------|-------------|----------------|-----|------------------------|-------------------------|\n"
             
             for m in annual_data:
+                period = m.get('period', 'N/A')
                 rev = m.get('total_revenue', 0) / 1e9
                 inc = m.get('net_income', 0) / 1e9
                 eps = m.get('earnings_per_share', 0)
-                result += f"| FY{m['period']} | ${rev:.2f}B | ${inc:.2f}B | ${eps:.2f} |\n"
+                opex = m.get('operating_expenses', 0) / 1e9
+                ocf = m.get('operating_cash_flow', 0) / 1e9
+                result += f"| FY{period} | ${rev:.2f}B | ${inc:.2f}B | ${eps:.2f} | ${opex:.2f}B | ${ocf:.2f}B |\n"
         
         return result