Upload 2 files

app.py

@@ -1,7 +1,8 @@
 import gradio as gr
 import requests
-from gradio_client import Client
+import json
 
+MCP_SPACE = "JC321/EasyReportDateMCP"
 MCP_URL = "https://jc321-easyreportdatemcp.hf.space"
 
 # 设置请求头
@@ -10,50 +11,38 @@ HEADERS = {
     "User-Agent": "SEC-Query-Assistant/1.0 (jtyxabc@gmail.com)"
 }
 
-# 初始化 Gradio Client
-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"""
     
     if not company_name:
         return "请输入公司名称或股票代码"
     
-    # 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
+        # 直接使用 HTTP POST 调用 Gradio API
         # 先搜索公司
-        company = current_client.predict(
-            company_input=company_name,
-            api_name="/advanced_search"
+        search_resp = requests.post(
+            f"{MCP_URL}/api/predict",
+            json={
+                "data": [company_name],
+                "fn_index": 0  # advanced_search 函数索引
+            },
+            headers=HEADERS,
+            timeout=30
         )
         
+        if search_resp.status_code != 200:
+            return f"❌ Server Error: HTTP {search_resp.status_code}\n\nResponse: {search_resp.text[:500]}"
+        
+        try:
+            result_data = search_resp.json()
+            # Gradio API 返回格式: {"data": [result]}
+            if "data" in result_data and result_data["data"]:
+                company = result_data["data"][0]
+            else:
+                return f"❌ 无法解析响应: {result_data}"
+        except (ValueError, KeyError) as e:
+            return f"❌ JSON Parse Error: {str(e)}\n\nResponse: {search_resp.text[:500]}"
+        
         if isinstance(company, dict) and company.get("error"):
             return f"❌ 错误: {company['error']}"
         
@@ -65,11 +54,25 @@ 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 = current_client.predict(
-                cik=cik,
-                api_name="/get_latest_financial_data"
+            data_resp = requests.post(
+                f"{MCP_URL}/api/predict",
+                json={
+                    "data": [cik],
+                    "fn_index": 1  # get_latest_financial_data 函数索引
+                },
+                headers=HEADERS,
+                timeout=30
             )
             
+            if data_resp.status_code != 200:
+                return result + f"❌ Server Error: HTTP {data_resp.status_code}\n\n{data_resp.text[:500]}"
+            
+            try:
+                data_result = data_resp.json()
+                data = data_result["data"][0] if "data" in data_result else data_result
+            except (ValueError, KeyError) as e:
+                return result + f"❌ JSON Parse Error: {str(e)}\n\n{data_resp.text[:500]}"
+            
             if isinstance(data, dict) and data.get("error"):
                 return result + f"❌ {data['error']}"
             
@@ -80,12 +83,25 @@ 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 = current_client.predict(
-                cik=cik,
-                years=3,
-                api_name="/extract_financial_metrics"
+            metrics_resp = requests.post(
+                f"{MCP_URL}/api/predict",
+                json={
+                    "data": [cik, 3],
+                    "fn_index": 2  # extract_financial_metrics 函数索引
+                },
+                headers=HEADERS,
+                timeout=60
             )
             
+            if metrics_resp.status_code != 200:
+                return result + f"❌ Server Error: HTTP {metrics_resp.status_code}\n\n{metrics_resp.text[:500]}"
+            
+            try:
+                metrics_result = metrics_resp.json()
+                metrics = metrics_result["data"][0] if "data" in metrics_result else metrics_result
+            except (ValueError, KeyError) as e:
+                return result + f"❌ JSON Parse Error: {str(e)}\n\n{metrics_resp.text[:500]}"
+            
             if isinstance(metrics, dict) and metrics.get("error"):
                 return result + f"❌ {metrics['error']}"
             
@@ -105,12 +121,25 @@ 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 = current_client.predict(
-                cik=cik,
-                years=5,
-                api_name="/extract_financial_metrics"
+            metrics_resp = requests.post(
+                f"{MCP_URL}/api/predict",
+                json={
+                    "data": [cik, 5],
+                    "fn_index": 2  # extract_financial_metrics 函数索引
+                },
+                headers=HEADERS,
+                timeout=60
             )
             
+            if metrics_resp.status_code != 200:
+                return result + f"❌ Server Error: HTTP {metrics_resp.status_code}\n\n{metrics_resp.text[:500]}"
+            
+            try:
+                metrics_result = metrics_resp.json()
+                metrics = metrics_result["data"][0] if "data" in metrics_result else metrics_result
+            except (ValueError, KeyError) as e:
+                return result + f"❌ JSON Parse Error: {str(e)}\n\n{metrics_resp.text[:500]}"
+            
             if isinstance(metrics, dict) and metrics.get("error"):
                 return result + f"❌ {metrics['error']}"
             

requirements.txt

@@ -1,3 +1,2 @@
 gradio>=4.0.0
-requests
-gradio_client
+requests