update pay function

mcp_database.py

@@ -781,3 +781,246 @@ async def remove_favorite_event(user_id: str, event_id: int) -> Dict[str, Any]:
                 return {"success": True, "message": "删除自选事件成功"}
             else:
                 return {"success": False, "message": "未找到该自选事件"}
+
+
+# ==================== ClickHouse 分钟频数据查询 ====================
+
+from clickhouse_driver import Client as ClickHouseClient
+
+# ClickHouse 连接配置
+CLICKHOUSE_CONFIG = {
+    'host': '222.128.1.157',
+    'port': 18000,
+    'user': 'default',
+    'password': 'Zzl33818!',
+    'database': 'stock'
+}
+
+# ClickHouse 客户端（懒加载）
+_clickhouse_client = None
+
+
+def get_clickhouse_client():
+    """获取 ClickHouse 客户端（单例模式）"""
+    global _clickhouse_client
+    if _clickhouse_client is None:
+        _clickhouse_client = ClickHouseClient(
+            host=CLICKHOUSE_CONFIG['host'],
+            port=CLICKHOUSE_CONFIG['port'],
+            user=CLICKHOUSE_CONFIG['user'],
+            password=CLICKHOUSE_CONFIG['password'],
+            database=CLICKHOUSE_CONFIG['database']
+        )
+        logger.info("ClickHouse client created")
+    return _clickhouse_client
+
+
+async def get_stock_minute_data(
+    code: str,
+    start_time: Optional[str] = None,
+    end_time: Optional[str] = None,
+    limit: int = 240
+) -> List[Dict[str, Any]]:
+    """
+    获取股票分钟频数据
+
+    Args:
+        code: 股票代码（例如：'600519' 或 '600519.SH'）
+        start_time: 开始时间，格式：YYYY-MM-DD HH:MM:SS 或 YYYY-MM-DD
+        end_time: 结束时间，格式：YYYY-MM-DD HH:MM:SS 或 YYYY-MM-DD
+        limit: 返回条数，默认240（一个交易日的分钟数据）
+
+    Returns:
+        分钟频数据列表
+    """
+    try:
+        client = get_clickhouse_client()
+
+        # 标准化股票代码（去除后缀）
+        stock_code = code.split('.')[0] if '.' in code else code
+
+        # 构建查询
+        query = """
+            SELECT
+                code,
+                timestamp,
+                open,
+                high,
+                low,
+                close,
+                volume,
+                amt
+            FROM stock_minute
+            WHERE code = %(code)s
+        """
+
+        params = {'code': stock_code}
+
+        if start_time:
+            query += " AND timestamp >= %(start_time)s"
+            params['start_time'] = start_time
+
+        if end_time:
+            query += " AND timestamp <= %(end_time)s"
+            params['end_time'] = end_time
+
+        query += " ORDER BY timestamp DESC LIMIT %(limit)s"
+        params['limit'] = limit
+
+        # 执行查询
+        result = client.execute(query, params, with_column_types=True)
+
+        rows = result[0]
+        columns = [col[0] for col in result[1]]
+
+        # 转换为字典列表
+        data = []
+        for row in rows:
+            record = {}
+            for i, col in enumerate(columns):
+                value = row[i]
+                # 处理 datetime 类型
+                if hasattr(value, 'isoformat'):
+                    record[col] = value.isoformat()
+                else:
+                    record[col] = value
+            data.append(record)
+
+        logger.info(f"[ClickHouse] 查询分钟数据: code={stock_code}, 返回 {len(data)} 条记录")
+        return data
+
+    except Exception as e:
+        logger.error(f"[ClickHouse] 查询分钟数据失败: {e}", exc_info=True)
+        return []
+
+
+async def get_stock_minute_aggregation(
+    code: str,
+    date: str,
+    interval: int = 5
+) -> List[Dict[str, Any]]:
+    """
+    获取股票分钟频数据的聚合（按指定分钟间隔）
+
+    Args:
+        code: 股票代码
+        date: 日期，格式：YYYY-MM-DD
+        interval: 聚合间隔（分钟），默认5分钟
+
+    Returns:
+        聚合后的K线数据
+    """
+    try:
+        client = get_clickhouse_client()
+
+        # 标准化股票代码
+        stock_code = code.split('.')[0] if '.' in code else code
+
+        # 使用 ClickHouse 的时间函数进行聚合
+        query = f"""
+            SELECT
+                code,
+                toStartOfInterval(timestamp, INTERVAL {interval} MINUTE) as interval_start,
+                argMin(open, timestamp) as open,
+                max(high) as high,
+                min(low) as low,
+                argMax(close, timestamp) as close,
+                sum(volume) as volume,
+                sum(amt) as amt
+            FROM stock_minute
+            WHERE code = %(code)s
+              AND toDate(timestamp) = %(date)s
+            GROUP BY code, interval_start
+            ORDER BY interval_start
+        """
+
+        params = {'code': stock_code, 'date': date}
+
+        result = client.execute(query, params, with_column_types=True)
+
+        rows = result[0]
+        columns = [col[0] for col in result[1]]
+
+        data = []
+        for row in rows:
+            record = {}
+            for i, col in enumerate(columns):
+                value = row[i]
+                if hasattr(value, 'isoformat'):
+                    record[col] = value.isoformat()
+                else:
+                    record[col] = value
+            data.append(record)
+
+        logger.info(f"[ClickHouse] 聚合分钟数据: code={stock_code}, date={date}, interval={interval}min, 返回 {len(data)} 条记录")
+        return data
+
+    except Exception as e:
+        logger.error(f"[ClickHouse] 聚合分钟数据失败: {e}", exc_info=True)
+        return []
+
+
+async def get_stock_intraday_statistics(
+    code: str,
+    date: str
+) -> Dict[str, Any]:
+    """
+    获取股票日内统计数据
+
+    Args:
+        code: 股票代码
+        date: 日期，格式：YYYY-MM-DD
+
+    Returns:
+        日内统计数据（开盘价、最高价、最低价、收盘价、成交量、成交额、波动率等）
+    """
+    try:
+        client = get_clickhouse_client()
+
+        stock_code = code.split('.')[0] if '.' in code else code
+
+        query = """
+            SELECT
+                code,
+                toDate(timestamp) as trade_date,
+                argMin(open, timestamp) as open,
+                max(high) as high,
+                min(low) as low,
+                argMax(close, timestamp) as close,
+                sum(volume) as total_volume,
+                sum(amt) as total_amount,
+                count(*) as data_points,
+                min(timestamp) as first_time,
+                max(timestamp) as last_time,
+                (max(high) - min(low)) / min(low) * 100 as intraday_range_pct,
+                stddevPop(close) as price_volatility
+            FROM stock_minute
+            WHERE code = %(code)s
+              AND toDate(timestamp) = %(date)s
+            GROUP BY code, trade_date
+        """
+
+        params = {'code': stock_code, 'date': date}
+
+        result = client.execute(query, params, with_column_types=True)
+
+        if not result[0]:
+            return {"success": False, "error": f"未找到 {stock_code} 在 {date} 的分钟数据"}
+
+        row = result[0][0]
+        columns = [col[0] for col in result[1]]
+
+        data = {}
+        for i, col in enumerate(columns):
+            value = row[i]
+            if hasattr(value, 'isoformat'):
+                data[col] = value.isoformat()
+            else:
+                data[col] = float(value) if isinstance(value, (int, float)) else value
+
+        logger.info(f"[ClickHouse] 日内统计: code={stock_code}, date={date}")
+        return {"success": True, "data": data}
+
+    except Exception as e:
+        logger.error(f"[ClickHouse] 日内统计失败: {e}", exc_info=True)
+        return {"success": False, "error": str(e)}

mcp_server.py

@@ -701,6 +701,75 @@ TOOLS: List[ToolDefinition] = [
             "required": []
         }
     ),
+    # ==================== 分钟频数据工具 ====================
+    ToolDefinition(
+        name="get_stock_minute_data",
+        description="获取股票分钟频K线数据。适用于分析日内走势、寻找交易时机、技术分析等场景。",
+        parameters={
+            "type": "object",
+            "properties": {
+                "code": {
+                    "type": "string",
+                    "description": "股票代码，例如：'600519' 或 '600519.SH'"
+                },
+                "start_time": {
+                    "type": "string",
+                    "description": "开始时间，格式：YYYY-MM-DD HH:MM:SS 或 YYYY-MM-DD"
+                },
+                "end_time": {
+                    "type": "string",
+                    "description": "结束时间，格式：YYYY-MM-DD HH:MM:SS 或 YYYY-MM-DD"
+                },
+                "limit": {
+                    "type": "integer",
+                    "description": "返回条数，默认240（约一个交易日）",
+                    "default": 240
+                }
+            },
+            "required": ["code"]
+        }
+    ),
+    ToolDefinition(
+        name="get_stock_minute_aggregation",
+        description="获取股票分钟频数据的聚合K线（5分钟、15分钟、30分钟等周期）。适用于中短期技术分析。",
+        parameters={
+            "type": "object",
+            "properties": {
+                "code": {
+                    "type": "string",
+                    "description": "股票代码"
+                },
+                "date": {
+                    "type": "string",
+                    "description": "交易日期，格式：YYYY-MM-DD"
+                },
+                "interval": {
+                    "type": "integer",
+                    "description": "聚合间隔（分钟），可选：5、15、30、60",
+                    "default": 5
+                }
+            },
+            "required": ["code", "date"]
+        }
+    ),
+    ToolDefinition(
+        name="get_stock_intraday_statistics",
+        description="获取股票日内统计数据，包括开高低收、成交量、成交额、日内波动率等汇总指标。",
+        parameters={
+            "type": "object",
+            "properties": {
+                "code": {
+                    "type": "string",
+                    "description": "股票代码"
+                },
+                "date": {
+                    "type": "string",
+                    "description": "交易日期，格式：YYYY-MM-DD"
+                }
+            },
+            "required": ["code", "date"]
+        }
+    ),
 ]
 
 # ==================== MCP协议端点 ====================
@@ -1114,6 +1183,48 @@ async def handle_get_user_following_events(args: Dict[str, Any]) -> Any:
             "data": []
         }
 
+
+# ==================== 分钟频数据处理函数 ====================
+
+async def handle_get_stock_minute_data(args: Dict[str, Any]) -> Any:
+    """处理股票分钟频数据查询"""
+    code = args["code"]
+    start_time = args.get("start_time")
+    end_time = args.get("end_time")
+    limit = args.get("limit", 240)
+
+    result = await db.get_stock_minute_data(code, start_time, end_time, limit)
+    return {
+        "success": True,
+        "data": result,
+        "count": len(result)
+    }
+
+
+async def handle_get_stock_minute_aggregation(args: Dict[str, Any]) -> Any:
+    """处理股票分钟频数据聚合查询"""
+    code = args["code"]
+    date = args["date"]
+    interval = args.get("interval", 5)
+
+    result = await db.get_stock_minute_aggregation(code, date, interval)
+    return {
+        "success": True,
+        "data": result,
+        "count": len(result),
+        "interval": f"{interval}分钟"
+    }
+
+
+async def handle_get_stock_intraday_statistics(args: Dict[str, Any]) -> Any:
+    """处理股票日内统计数据查询"""
+    code = args["code"]
+    date = args["date"]
+
+    result = await db.get_stock_intraday_statistics(code, date)
+    return result
+
+
 # 工具处理函数映射
 TOOL_HANDLERS = {
     "search_news": handle_search_news,
@@ -1136,6 +1247,10 @@ TOOL_HANDLERS = {
     "get_stock_comparison": handle_get_stock_comparison,
     "get_user_watchlist": handle_get_user_watchlist,
     "get_user_following_events": handle_get_user_following_events,
+    # 分钟频数据工具
+    "get_stock_minute_data": handle_get_stock_minute_data,
+    "get_stock_minute_aggregation": handle_get_stock_minute_aggregation,
+    "get_stock_intraday_statistics": handle_get_stock_intraday_statistics,
 }
 
 # ==================== Agent系统实现 ====================

package.json

@@ -70,6 +70,7 @@
     "react-to-print": "^3.0.3",
     "react-tsparticles": "^2.12.2",
     "recharts": "^3.1.2",
+    "remark-gfm": "^4.0.1",
     "sass": "^1.49.9",
     "socket.io-client": "^4.7.4",
     "styled-components": "^5.3.11",

src/components/ChatBot/MarkdownWithCharts.js

@@ -2,8 +2,9 @@
 // 支持 ECharts 图表的 Markdown 渲染组件
 
 import React from 'react';
-import { Box, Alert, AlertIcon, Text, VStack, Code, useColorModeValue } from '@chakra-ui/react';
+import { Box, Alert, AlertIcon, Text, VStack, Code, useColorModeValue, Table, Thead, Tbody, Tr, Th, Td, TableContainer } from '@chakra-ui/react';
 import ReactMarkdown from 'react-markdown';
+import remarkGfm from 'remark-gfm';
 import { EChartsRenderer } from './EChartsRenderer';
 import { logger } from '@utils/logger';
 
@@ -83,6 +84,7 @@ export const MarkdownWithCharts = ({ content, variant = 'auto' }) => {
           return (
             <Box key={index}>
               <ReactMarkdown
+                remarkPlugins={[remarkGfm]}
                 components={{
                   // 自定义渲染样式
                   p: ({ children }) => (
@@ -142,6 +144,55 @@ export const MarkdownWithCharts = ({ content, variant = 'auto' }) => {
                       {children}
                     </Box>
                   ),
+                  // 表格渲染
+                  table: ({ children }) => (
+                    <TableContainer
+                      mb={4}
+                      borderRadius="md"
+                      border="1px solid"
+                      borderColor={isDark ? 'rgba(255, 255, 255, 0.1)' : 'gray.200'}
+                      overflowX="auto"
+                    >
+                      <Table size="sm" variant="simple">
+                        {children}
+                      </Table>
+                    </TableContainer>
+                  ),
+                  thead: ({ children }) => (
+                    <Thead bg={isDark ? 'rgba(255, 255, 255, 0.05)' : 'gray.50'}>
+                      {children}
+                    </Thead>
+                  ),
+                  tbody: ({ children }) => <Tbody>{children}</Tbody>,
+                  tr: ({ children }) => (
+                    <Tr
+                      _hover={{
+                        bg: isDark ? 'rgba(255, 255, 255, 0.03)' : 'gray.50'
+                      }}
+                    >
+                      {children}
+                    </Tr>
+                  ),
+                  th: ({ children }) => (
+                    <Th
+                      fontSize="xs"
+                      color={headingColor}
+                      borderColor={isDark ? 'rgba(255, 255, 255, 0.1)' : 'gray.200'}
+                      py={2}
+                    >
+                      {children}
+                    </Th>
+                  ),
+                  td: ({ children }) => (
+                    <Td
+                      fontSize="sm"
+                      color={textColor}
+                      borderColor={isDark ? 'rgba(255, 255, 255, 0.1)' : 'gray.200'}
+                      py={2}
+                    >
+                      {children}
+                    </Td>
+                  ),
                 }}
               >
                 {part.content}

src/views/AgentChat/hooks/useAgentChat.ts

@@ -190,6 +190,9 @@ export const useAgentChat = ({
           setCurrentSessionId(data.session_id);
         }
 
+        // 获取执行步骤（后端返回 step_results 字段）
+        const stepResults = data.step_results || data.steps || [];
+
         // 显示执行计划（如果有）
         if (data.plan) {
           addMessage({
@@ -200,24 +203,24 @@ export const useAgentChat = ({
         }
 
         // 显示执行步骤（如果有）
-        if (data.steps && data.steps.length > 0) {
+        if (stepResults.length > 0) {
           addMessage({
             type: MessageTypes.AGENT_EXECUTING,
             content: '正在执行步骤...',
             plan: data.plan,
-            stepResults: data.steps,
+            stepResults: stepResults,
           });
         }
 
         // 移除 "执行中" 消息
         setMessages((prev) => prev.filter((m) => m.type !== MessageTypes.AGENT_EXECUTING));
 
-        // 显示最终回复
+        // 显示最终回复（使用 final_summary 或 final_answer 或 message）
         addMessage({
           type: MessageTypes.AGENT_RESPONSE,
-          content: data.final_answer || data.message || '处理完成',
+          content: data.final_summary || data.final_answer || data.message || '处理完成',
           plan: data.plan,
-          stepResults: data.steps,
+          stepResults: stepResults,
           metadata: data.metadata,
         });