Upload 2 files

app.py

@@ -25,7 +25,7 @@ MCP_TOOLS = [
 
 # ========== MCP 服务配置 ==========
 MCP_SERVICES = {
-    "financial": {"url": "https://jc321-easyreportdatemcp.hf.space/mcp", "type": "fastmcp"},
+    "financial": {"url": "https://huggingface.co/spaces/JC321/EasyReportDataMCP", "type": "fastmcp"},
     "market": {"url": "https://jc321-marketandstockmcp.hf.space", "type": "gradio"}
 }
 

app_simplified.py

@@ -0,0 +1,236 @@
+import gradio as gr
+import requests
+import json
+import os
+from huggingface_hub import InferenceClient
+
+# ========== 配置两个 MCP 服务 ==========
+MCP_SERVICES = {
+    "financial": {
+        "name": "SEC Financial Reports",
+        "url": "https://huggingface.co/spaces/JC321/EasyReportDataMCP",
+        "tools": [
+            {
+                "type": "function",
+                "function": {
+                    "name": "advanced_search_company",
+                    "description": "Search for US listed companies by name or ticker to get CIK and basic info",
+                    "parameters": {
+                        "type": "object",
+                        "properties": {
+                            "company_input": {"type": "string", "description": "Company name or ticker (e.g., 'Apple', 'AAPL')"}
+                        },
+                        "required": ["company_input"]
+                    }
+                }
+            },
+            {
+                "type": "function",
+                "function": {
+                    "name": "get_latest_financial_data",
+                    "description": "Get latest financial data (revenue, net income, EPS, etc.) for a company",
+                    "parameters": {
+                        "type": "object",
+                        "properties": {
+                            "cik": {"type": "string", "description": "10-digit CIK number"}
+                        },
+                        "required": ["cik"]
+                    }
+                }
+            },
+            {
+                "type": "function",
+                "function": {
+                    "name": "extract_financial_metrics",
+                    "description": "Get multi-year financial trends (3 or 5 years)",
+                    "parameters": {
+                        "type": "object",
+                        "properties": {
+                            "cik": {"type": "string", "description": "10-digit CIK number"},
+                            "years": {"type": "integer", "enum": [3, 5]}
+                        },
+                        "required": ["cik", "years"]
+                    }
+                }
+            }
+        ]
+    },
+    "market": {
+        "name": "Market & Stock Data",
+        "url": "https://jc321-marketandstockmcp.hf.space/mcp",
+        "tools": []  # 需要获取实际工具列表
+    }
+}
+
+# 合并所有工具
+ALL_TOOLS = []
+TOOL_ROUTING = {}  # tool_name -> mcp_url 的映射
+
+for service_key, service in MCP_SERVICES.items():
+    for tool in service["tools"]:
+        tool_name = tool["function"]["name"]
+        ALL_TOOLS.append(tool)
+        TOOL_ROUTING[tool_name] = service["url"]
+
+# ========== 初始化 LLM 客户端 ==========
+hf_token = os.environ.get("HF_TOKEN") or os.environ.get("HUGGING_FACE_HUB_TOKEN")
+client = InferenceClient(api_key=hf_token) if hf_token else InferenceClient()
+print(f"✅ LLM client initialized (Qwen/Qwen2.5-72B-Instruct:novita)")
+
+# ========== 系统提示词 ==========
+SYSTEM_PROMPT = """You are an intelligent financial and market analysis assistant with access to real-time data.
+
+You have access to two powerful data sources:
+1. **SEC Financial Reports** - Get official financial data for US-listed companies (revenue, earnings, cash flow, etc.)
+2. **Market & Stock Data** - Get real-time market data, stock prices, and market analysis
+
+When users ask about:
+- Company financials, earnings, revenue → Use SEC Financial Reports tools
+- Stock prices, market trends, trading data → Use Market & Stock Data tools
+
+Be conversational, insightful, and provide data-driven analysis. Automatically fetch data when needed."""
+
+# ========== 核心函数：调用 MCP 工具 ==========
+def call_mcp_tool(tool_name, arguments):
+    """调用 MCP 工具"""
+    mcp_url = TOOL_ROUTING.get(tool_name)
+    if not mcp_url:
+        return {"error": f"Unknown tool: {tool_name}"}
+    
+    try:
+        response = requests.post(
+            mcp_url,
+            json={
+                "jsonrpc": "2.0",
+                "method": "tools/call",
+                "params": {"name": tool_name, "arguments": arguments},
+                "id": 1
+            },
+            headers={"Content-Type": "application/json"},
+            timeout=60
+        )
+        
+        if response.status_code == 200:
+            return response.json()
+        else:
+            return {"error": f"HTTP {response.status_code}", "detail": response.text[:200]}
+    except Exception as e:
+        return {"error": str(e)}
+
+# ========== 核心函数：AI 助手 ==========
+def chatbot_response(message, history):
+    """AI 助手主函数"""
+    try:
+        # 构建消息历史
+        messages = [{"role": "system", "content": SYSTEM_PROMPT}]
+        
+        # 添加对话历史（最近5轮）
+        if history:
+            for item in history[-5:]:
+                if isinstance(item, dict):
+                    messages.append(item)
+                elif isinstance(item, (list, tuple)) and len(item) == 2:
+                    user_msg, assistant_msg = item
+                    messages.append({"role": "user", "content": user_msg})
+                    messages.append({"role": "assistant", "content": assistant_msg})
+        
+        messages.append({"role": "user", "content": message})
+        
+        # LLM 调用循环（支持多轮工具调用）
+        tool_calls_log = []
+        max_iterations = 5
+        
+        for iteration in range(max_iterations):
+            # 调用 LLM
+            response = client.chat_completion(
+                messages=messages,
+                model="Qwen/Qwen2.5-72B-Instruct:novita",
+                tools=ALL_TOOLS,
+                max_tokens=3000,
+                temperature=0.7,
+                tool_choice="auto"
+            )
+            
+            choice = response.choices[0]
+            
+            # 检查是否有工具调用
+            if choice.message.tool_calls:
+                messages.append(choice.message)
+                
+                for tool_call in choice.message.tool_calls:
+                    tool_name = tool_call.function.name
+                    tool_args = json.loads(tool_call.function.arguments)
+                    
+                    # 记录工具调用
+                    tool_calls_log.append({"name": tool_name, "arguments": tool_args})
+                    
+                    # 调用 MCP 工具
+                    tool_result = call_mcp_tool(tool_name, tool_args)
+                    
+                    # 添加工具结果到消息
+                    messages.append({
+                        "role": "tool",
+                        "name": tool_name,
+                        "content": json.dumps(tool_result),
+                        "tool_call_id": tool_call.id
+                    })
+                
+                continue  # 继续下一轮
+            else:
+                # 无工具调用，返回最终答案
+                response_text = choice.message.content
+                break
+        
+        # 构建最终响应
+        final_response = ""
+        
+        # 显示模型信息
+        final_response += f"<div style='padding: 8px; background: #e3f2fd; border-left: 3px solid #2196f3; margin-bottom: 10px; font-size: 0.9em;'>🤖 <strong>Model:</strong> Qwen/Qwen2.5-72B-Instruct:novita</div>\n\n"
+        
+        # 显示工具调用日志
+        if tool_calls_log:
+            final_response += "**🛠️ MCP Tools Used:**\n\n"
+            for i, tool_call in enumerate(tool_calls_log, 1):
+                final_response += f"{i}. `{tool_call['name']}` - {json.dumps(tool_call['arguments'])}\n"
+            final_response += "\n---\n\n"
+        
+        final_response += response_text
+        
+        return final_response
+        
+    except Exception as e:
+        return f"❌ Error: {str(e)}"
+
+# ========== Gradio 界面 ==========
+with gr.Blocks(title="Financial & Market AI Assistant") as demo:
+    gr.Markdown("# 🤖 Financial & Market AI Assistant")
+    
+    gr.Markdown("""
+    <div style='padding: 15px; background: #d4edda; border-left: 4px solid #28a745; margin: 10px 0; border-radius: 4px;'>
+        <strong>✅ AI Powered by:</strong> Qwen/Qwen2.5-72B-Instruct:novita
+        <br>
+        <strong>📊 Data Sources:</strong> SEC Financial Reports + Market & Stock Data
+    </div>
+    """)
+    
+    chat = gr.ChatInterface(
+        fn=chatbot_response,
+        examples=[
+            "What's Apple's latest revenue and profit?",
+            "Show me NVIDIA's 3-year financial trends",
+            "How is Tesla's stock performing today?",
+            "Compare Microsoft's earnings with its stock price",
+            "Analyze Amazon's cash flow and market cap",
+        ],
+        title="💬 AI Assistant",
+        description="Ask me about company financials, stock prices, or market trends. I'll automatically fetch the data you need!"
+    )
+
+# 启动应用
+if __name__ == "__main__":
+    demo.launch(
+        server_name="0.0.0.0",
+        server_port=7860,
+        show_error=True,
+        ssr_mode=False
+    )