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ai-talk-callback/JSON_LOG_EXAMPLES.md
mark.tian addd75fbf9 增加接口日志输出
2025-12-02 19:57:54 +08:00

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JSON格式日志输出示例

优化后的 log_callback_request 方法 - JSON格式日志

1. site_id 日志输出

📝 site_id: "test-site-123"

2. 请求头日志输出（JSON格式）

📋 请求头: {
  "content-type": "application/json",
  "authorization": "***REDACTED***",
  "x-api-key": "***REDACTED***",
  "user-agent": "python-httpx/0.25.2",
  "accept": "application/json",
  "content-length": "1024",
  "host": "localhost:8000"
}

3. 请求体日志输出（JSON格式）

📄 请求体: {
  "count": 2,
  "data": [
    {
      "bill": 100,
      "duration": 60,
      "callid": "test-call-123",
      "calldate": "2024-01-01 12:00:00",
      "number": "13800138000",
      "numberid": "number-123",
      "customer_id": "customer-123",
      "status": 0,
      "status_str": "失败",
      "user_id": "user-123",
      "type": 1,
      "number_data": {
        "number": "13800138000",
        "province": "广东",
        "city": "深圳",
        "operator": "移动"
      },
      "group": {
        "id": 1,
        "name": "测试组"
      },
      "task": {
        "id": "task-123",
        "name": "测试任务"
      },
      "user": {
        "id": "user-123",
        "name": "测试用户"
      },
      "customer_data": {
        "name": "测试客户",
        "email": "test@example.com",
        "company": "测试公司",
        "extra": "额外信息"
      }
    }
  ]
}

4. server_ip 日志输出（JSON格式）

🏠 server_ip: {
  "ip": "0.0.0.0",
  "port": 8000
}

5. client_ip 日志输出（JSON格式）

🖥️ client_ip: {
  "ip": "127.0.0.1",
  "port": 52345
}

6. callback_data 日志输出（JSON格式）

📦 callback_data: {
  "count": 2,
  "data_count": 1,
  "data_sample": {
    "bill": 100,
    "duration": 60,
    "callid": "test-call-123",
    "calldate": "2024-01-01 12:00:00",
    "number": "13800138000",
    "numberid": "number-123",
    "customer_id": "customer-123",
    "status": 0,
    "status_str": "失败",
    "user_id": "user-123",
    "type": 1,
    "number_data": {
      "number": "13800138000",
      "province": "广东",
      "city": "深圳",
      "operator": "移动"
    },
    "group": {
      "id": 1,
      "name": "测试组"
    },
    "task": {
      "id": "task-123",
      "name": "测试任务"
    },
    "user": {
      "id": "user-123",
      "name": "测试用户"
    },
    "customer_data": {
      "name": "测试客户",
      "email": "test@example.com",
      "company": "测试公司",
      "extra": "额外信息"
    }
  }
}

完整的请求处理日志流程

单次请求的完整日志输出

2024-12-02 16:30:15 - routes - INFO - 🔥 收到AI Talk回调请求: siteId=test-site-123, count=2, data_count=1
2024-12-02 16:30:15 - routes - INFO - 📝 site_id: "test-site-123"
2024-12-02 16:30:15 - routes - INFO - 📋 请求头: {
  "content-type": "application/json",
  "authorization": "***REDACTED***",
  "user-agent": "python-httpx/0.25.2",
  "accept": "application/json",
  "content-length": "1024",
  "host": "localhost:8000"
}
2024-12-02 16:30:15 - routes - INFO - 📄 请求体: {
  "count": 2,
  "data": [
    {
      "bill": 100,
      "duration": 60,
      "callid": "test-call-123",
      "calldate": "2024-01-01 12:00:00",
      "number": "13800138000",
      "numberid": "number-123",
      "customer_id": "customer-123",
      "status": 0,
      "status_str": "失败",
      "user_id": "user-123",
      "type": 1,
      "number_data": {
        "number": "13800138000",
        "province": "广东",
        "city": "深圳",
        "operator": "移动"
      },
      "group": {
        "id": 1,
        "name": "测试组"
      },
      "task": {
        "id": "task-123",
        "name": "测试任务"
      },
      "user": {
        "id": "user-123",
        "name": "测试用户"
      },
      "customer_data": {
        "name": "测试客户",
        "email": "test@example.com",
        "company": "测试公司",
        "extra": "额外信息"
      }
    }
  ]
}
2024-12-02 16:30:15 - routes - INFO - 🏠 server_ip: {
  "ip": "0.0.0.0",
  "port": 8000
}
2024-12-02 16:30:15 - routes - INFO - 🖥️ client_ip: {
  "ip": "127.0.0.1",
  "port": 52345
}
2024-12-02 16:30:15 - routes - INFO - 📦 callback_data: {
  "count": 2,
  "data_count": 1,
  "data_sample": {
    "bill": 100,
    "duration": 60,
    "callid": "test-call-123",
    "calldate": "2024-01-01 12:00:00",
    "number": "13800138000",
    "numberid": "number-123",
    "customer_id": "customer-123",
    "status": 0,
    "status_str": "失败",
    "user_id": "user-123",
    "type": 1,
    "number_data": {
      "number": "13800138000",
      "province": "广东",
      "city": "深圳",
      "operator": "移动"
    },
    "group": {
      "id": 1,
      "name": "测试组"
    },
    "task": {
      "id": "task-123",
      "name": "测试任务"
    },
    "user": {
      "id": "user-123",
      "name": "测试用户"
    },
    "customer_data": {
      "name": "测试客户",
      "email": "test@example.com",
      "company": "测试公司",
      "extra": "额外信息"
    }
  }
}
2024-12-02 16:30:15 - routes - INFO - ✅ 回调请求记录成功保存到数据库，ID: 123
2024-12-02 16:30:15 - routes - INFO - 📞 count=2 < 3，调用外部API
2024-12-02 16:30:15 - routes - DEBUG - 🔒 获取Redis锁成功: external_api_call_test-site-123_2

JSON格式日志的优势

1. 结构化数据

  • 每个字段都以标准JSON格式输出
  • 便于程序解析和处理
  • 支持复杂的嵌套数据结构

2. 可读性强

  • JSON格式具有良好的层次结构
  • 缩进格式便于人工阅读
  • 支持中文字符（ensure_ascii=False）

3. 便于分析

  • 可以直接使用JSON工具解析
  • 支持日志分析工具（如ELK、Fluentd等）
  • 便于数据提取和统计

4. 安全性

  • 敏感信息自动过滤为 ***REDACTED***
  • 保持数据结构完整性
  • 避免敏感信息泄露

日志分析示例

使用jq工具分析JSON日志

# 提取所有site_id
grep "📝 site_id:" logs/app.log | jq -r '.📝 site_id'

# 提取所有client_ip信息
grep "🖥️ client_ip:" logs/app.log | jq -r '.🖥️ client_ip.ip'

# 统计不同count值的请求
grep "📦 callback_data:" logs/app.log | jq -r '.📦 callback_data.count' | sort | uniq -c

# 提取包含特定号码的请求
grep "📄 请求体:" logs/app.log | jq 'select(.📄 请求_body.data[].number == "13800138000")'

使用Python分析JSON日志

import json
import re

# 解析日志中的JSON数据
def parse_json_logs(log_file):
    site_ids = []
    client_ips = []
    
    with open(log_file, 'r', encoding='utf-8') as f:
        for line in f:
            if '📝 site_id:' in line:
                # 提取JSON部分
                json_str = line.split('📝 site_id: ')[1].strip()
                site_id = json.loads(json_str)
                site_ids.append(site_id)
            
            elif '🖥️ client_ip:' in line:
                json_str = line.split('🖥️ client_ip: ')[1].strip()
                client_info = json.loads(json_str)
                client_ips.append(client_info['ip'])
    
    return site_ids, client_ips

性能考虑

1. JSON序列化开销

  • 使用标准库json.dumps()
  • ensure_ascii=False 支持中文但略慢
  • 对于高频调用，可考虑关闭详细日志

2. 日志文件大小

  • JSON格式比纯文本占用更多空间
  • 建议合理设置日志轮转大小
  • 生产环境可考虑使用压缩存储

3. 内存使用

  • 大型请求体会占用较多内存
  • callback_data 只记录摘要信息，避免完整数据

配置建议

开发环境

LOG_LEVEL=INFO  # 显示所有JSON日志

生产环境

LOG_LEVEL=WARNING  # 只显示重要信息，减少JSON日志量

调试特定问题

# 临时开启详细日志
LOG_LEVEL=DEBUG
# 问题解决后恢复
LOG_LEVEL=INFO

现在 log_callback_request 方法以JSON格式输出所有关键信息，便于日志分析和系统监控！

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