Upload 2 files

app.py

@@ -11,11 +11,21 @@ HEADERS = {
 }
 
 # 初始化 Gradio Client
-try:
-    client = Client(MCP_URL)
-except Exception as e:
-    client = None
-    print(f"Warning: Failed to initialize Gradio Client: {e}")
+client = None
+client_error = None
+
+def get_client():
+    """获取或初始化 Gradio Client"""
+    global client, client_error
+    if client is not None:
+        return client
+    
+    try:
+        client = Client(MCP_URL, verbose=False)
+        return client
+    except Exception as e:
+        client_error = str(e)
+        return None
 
 def query_financial_data(company_name, query_type):
     """查询财务数据的主函数"""
@@ -23,13 +33,23 @@ def query_financial_data(company_name, query_type):
     if not company_name:
         return "请输入公司名称或股票代码"
     
-    if client is None:
-        return "❌ Gradio Client 未初始化，无法连接到 MCP 服务"
+    # 获取 client
+    current_client = get_client()
+    if current_client is None:
+        error_msg = f"❌ Gradio Client 初始化失败\n\n"
+        error_msg += f"**MCP Server**: {MCP_URL}\n"
+        if client_error:
+            error_msg += f"**错误信息**: {client_error}\n\n"
+        error_msg += "**可能原因**:\n"
+        error_msg += "- MCP 服务可能正在启动中，请稍后重试\n"
+        error_msg += "- MCP 服务可能不可用或已暂停\n"
+        error_msg += "- 网络连接问题\n"
+        return error_msg
     
     try:
         # 使用 Gradio Client 调用 MCP 服务
         # 先搜索公司
-        company = client.predict(
+        company = current_client.predict(
             company_input=company_name,
             api_name="/advanced_search"
         )
@@ -45,7 +65,7 @@ def query_financial_data(company_name, query_type):
         
         # 根据查询类型获取数据
         if query_type == "最新财务数据":
-            data = client.predict(
+            data = current_client.predict(
                 cik=cik,
                 api_name="/get_latest_financial_data"
             )
@@ -60,7 +80,7 @@ def query_financial_data(company_name, query_type):
             result += f"- **来源**: {data.get('source_form', 'N/A')}\n"
         
         elif query_type == "3年趋势":
-            metrics = client.predict(
+            metrics = current_client.predict(
                 cik=cik,
                 years=3,
                 api_name="/extract_financial_metrics"
@@ -85,7 +105,7 @@ def query_financial_data(company_name, query_type):
                 result += f"| FY{period} | ${rev:.2f}B | ${inc:.2f}B | ${eps:.2f} |\n"
         
         elif query_type == "5年趋势":
-            metrics = client.predict(
+            metrics = current_client.predict(
                 cik=cik,
                 years=5,
                 api_name="/extract_financial_metrics"