tmp

Lib/montior.py

@@ -32,7 +32,7 @@ class MainMonitor(object):
         logger.info("启动后台服务")
 
         # add api user
-        logger.info("写入ASF_TOKEN到缓存")
+        logger.info("写入ASP_TOKEN到缓存")
         api_usr = User()
         api_usr.username = "api_token"
         api_usr.is_active = True

PLAYBOOKS/Alert_Analysis_Agent.py

@@ -119,7 +119,7 @@ class Playbook(LanggraphPlaybook):
 
 
 if __name__ == "__main__":
-    params_debug = {'rowid': '113d3844-792d-47f9-b4f5-29e6f9b3c776', 'worksheet': 'alert'}
+    params_debug = {'rowid': '13782e0a-2423-4fc3-9b16-7f2eb15ae83f', 'worksheet': 'alert'}
     module = Playbook()
     module._params = params_debug
     module.run()

PLUGINS/SIRP/message_test.py

@@ -1,147 +0,0 @@
-import json
-from typing import List, Dict, Any
-
-from PLUGINS.SIRP.sirpapi import PlaybookMessage
-
-# 尝试导入 langchain_core，如果未安装则报错提示
-try:
-    from langchain_core.messages import (
-        BaseMessage,
-        SystemMessage,
-        HumanMessage,
-        AIMessage,
-        ToolMessage
-    )
-except ImportError:
-    raise ImportError("请先安装 langchain-core: pip install langchain-core")
-
-
-def parse_langchain_messages(msg: BaseMessage, playbook_rowid=None, node=None) -> List[Dict[str, Any]]:
-    """
-    将 LangChain 的消息对象列表解析为纯字典列表 (List[Dict])。
-    涵盖 System, Human, AI (含 tool_calls), ToolMessage。
-    """
-
-    # 1. 处理 SystemMessage
-    if isinstance(msg, SystemMessage):
-
-        fields = [
-            {"id": "type", "value": "SystemMessage"},
-            {"id": "node", "value": node},
-            {"id": "playbook_rowid", "value": playbook_rowid},
-            {"id": "content", "value": msg.content},
-            {"id": "json", "value": None},
-        ]
-
-
-    # 2. 处理 HumanMessage
-    elif isinstance(msg, HumanMessage):
-
-        fields = [
-            {"id": "type", "value": "HumanMessage"},
-            {"id": "node", "value": node},
-            {"id": "playbook_rowid", "value": playbook_rowid},
-            {"id": "content", "value": msg.content},
-            {"id": "json", "value": None},
-        ]
-
-
-    # 3. 处理 AIMessage (包含普通回复和工具调用)
-    elif isinstance(msg, AIMessage):
-        # 检查是否有 tool_calls
-        if hasattr(msg, 'tool_calls') and msg.tool_calls:
-            fields = [
-                {"id": "type", "value": "AIMessage"},
-                {"id": "node", "value": node},
-                {"id": "playbook_rowid", "value": playbook_rowid},
-                {"id": "content", "value": msg.content},
-                {"id": "json", "value": json.dumps(msg.tool_calls)},
-            ]
-        else:
-            fields = [
-                {"id": "type", "value": "AIMessage"},
-                {"id": "node", "value": node},
-                {"id": "playbook_rowid", "value": playbook_rowid},
-                {"id": "content", "value": msg.content},
-                {"id": "json", "value": None},
-            ]
-    # 4. 处理 ToolMessage (工具执行的结果)
-    elif isinstance(msg, ToolMessage):
-
-        try:
-            json_data = {"name": msg.name, "tool_call_id": msg.tool_call_id, "result": json.loads(msg.content)}
-        except json.decoder.JSONDecodeError:
-            json_data = {"name": msg.name, "tool_call_id": msg.tool_call_id, "result": msg.content}
-
-        fields = [
-            {"id": "type", "value": "ToolMessage"},
-            {"id": "node", "value": node},
-            {"id": "playbook_rowid", "value": playbook_rowid},
-            {"id": "json", "value": json.dumps(json_data)},
-        ]
-    # 5. 处理其他未知类型 (兜底)
-    else:
-        message_dict = {
-            "role": "unknown",
-            "content": msg.content,
-            "type": msg.type
-        }
-        fields = [
-            {"id": "role", "value": msg.type},
-            {"id": "node", "value": node},
-            {"id": "playbook_rowid", "value": playbook_rowid},
-            {"id": "content", "value": msg.content},
-            {"id": "json", "value": None},
-        ]
-    row_id = PlaybookMessage.create(fields)
-    return row_id
-
-
-# ==========================================
-# 测试代码部分
-# ==========================================
-if __name__ == "__main__":
-    print("-" * 30)
-    print("开始测试 LangChain Message 解析")
-    print("-" * 30)
-
-    # 1. 模拟构建 LangChain 的消息列表
-    # 场景：用户问天气 -> AI 决定调用工具 -> 工具返回结果 -> AI 总结
-
-    # 模拟 tool_call 数据
-    dummy_tool_call_id = "call_12345xyz"
-
-    test_messages = [
-        # System Message
-        SystemMessage(content="你是一个有用的AI助手。"),
-
-        # Human Message
-        HumanMessage(content="东京现在的天气怎么样？"),
-
-        # AI Message (决定调用工具)
-        AIMessage(
-            content="",  # 思维链内容可能为空
-            tool_calls=[{
-                "name": "get_current_weather",
-                "args": {"location": "Tokyo", "unit": "celsius"},
-                "id": dummy_tool_call_id
-            }]
-        ),
-
-        # Tool Message (工具返回的结果)
-        ToolMessage(
-            content=json.dumps({"temperature": 22, "description": "Sunny"}),
-            tool_call_id=dummy_tool_call_id,
-            name="get_current_weather"
-        ),
-
-        # AI Message (最终回复)
-        AIMessage(content="东京现在天气晴朗，气温约为 22 摄氏度。")
-    ]
-
-    # 2. 执行解析
-    try:
-        for msg in test_messages:
-            results = parse_langchain_messages(msg)
-    except Exception as e:
-        print(f"\n❌ 测试失败: {e}")