add log error level count

api/core/tools/builtin_tool/providers/apo_select/tools/log_error_level_count.py

@@ -0,0 +1,48 @@
+import json
+from collections.abc import Generator
+from typing import Any, Optional
+
+import requests
+
+from configs import dify_config
+from core.tools.builtin_tool.tool import BuiltinTool
+from core.tools.entities.tool_entities import ToolInvokeMessage
+from libs.apo_utils import APOUtils
+
+
+class LogErrorLevelCountTool(BuiltinTool):
+    def _invoke(
+        self,
+        user_id: str,
+        tool_parameters: dict[str, Any],
+        conversation_id: Optional[str] = None,
+        app_id: Optional[str] = None,
+        message_id: Optional[str] = None,
+    ) -> Generator[ToolInvokeMessage, None, None]:
+        pod_name = tool_parameters.get('pod_name', '.*')
+        namespace = tool_parameters.get('namespace', '.*')
+        pid = tool_parameters.get('pid', '.*')
+        start_time = tool_parameters.get("startTime")
+        end_time = tool_parameters.get("endTime")
+        params = {
+            'metricName': '宿主机监控指标 - 日志解析错误计数总览 - log error level count',
+            'params': {
+                'pod_name': pod_name,
+                'namespace': namespace,
+                'pid': pid
+            },
+            'startTime': start_time,
+            'endTime': end_time,
+            'step': APOUtils.get_step(start_time, end_time),
+        }
+        resp = requests.post(dify_config.APO_BACKEND_URL + '/api/metric/query', json=params)
+        list = resp.json()['result']
+        list = json.dumps({
+            'type': 'metric',
+            'display': True,
+            'unit': list['unit'],
+            'data': {
+                'timeseries': list['timeseries']
+            }
+        })
+        yield self.create_text_message(list)

api/core/tools/builtin_tool/providers/apo_select/tools/log_error_level_count.yaml

@@ -0,0 +1,75 @@
+identity:
+  name: 记录了日志解析系统中按错误级别统计的总次数
+  author: APO
+  label:
+    en_US: Records the total count of log parsing system errors categorized by error level
+    zh_Hans: 记录了日志解析系统中按错误级别统计的总次数
+description:
+  human:
+    en_US: Records the total count of log parsing system errors categorized by error level
+    zh_Hans: 记录了日志解析系统中按错误级别统计的总次数
+  llm: Records the total count of log parsing system errors categorized by error level
+display:
+  type: metric
+  title: 宿主机监控指标 - 日志解析错误计数总览 - log error level count
+  unit: "short"
+parameters:
+  - name: pod_name
+    type: string
+    required: False
+    label:
+      en_US: Pod name
+      zh_Hans: Pod名称
+    human_description:
+      en_US: Pod name
+      zh_Hans: Pod名称
+    llm_description: Pod name
+    form: llm
+  - name: namespace
+    type: string
+    required: False
+    label:
+      en_US: Namespace
+      zh_Hans: 命名空间
+    human_description:
+      en_US: Namespace
+      zh_Hans: 命名空间
+    llm_description: Namespace
+    form: llm
+  - name: pid
+    type: string
+    required: False
+    label:
+      en_US: Process ID
+      zh_Hans: 进程ID
+    human_description:
+      en_US: Process ID
+      zh_Hans: 进程ID
+    llm_description: Process ID
+    form: llm
+  - name: startTime
+    type: number
+    required: true
+    label:
+      en_US: startTime
+      zh_Hans: startTime
+      pt_BR: startTime
+    human_description:
+      en_US: Data query start time(Microsecond)
+      zh_Hans: 开始时间 (微秒)
+      pt_BR: Data query start time
+    llm_description: Data query start time(Microsecond)
+    form: llm
+  - name: endTime
+    type: number
+    required: true
+    label:
+      en_US: endTime
+      zh_Hans: endTime
+      pt_BR: endTime
+    human_description:
+      en_US: Data query end time(Microsecond)
+      zh_Hans: 结束时间 (微秒)
+      pt_BR: Data query end time(Microsecond)
+    llm_description: Data query end time(Microsecond)
+    form: llm

api/core/tools/builtin_tool/providers/apo_select/tools/thread_polaris_p90.py

@@ -41,15 +41,13 @@ class ThreadPolarisP90(BuiltinTool):
             values = [float(value[1]) for value in entry["values"]]
     
             stats[tid] = {
-                "max": max(values),
+                "avg": sum(values) / len(values),
-                "min": min(values)
             }
 
         return json.dumps(stats)
 
     def get_metrics(self, type: str, pod: str, start: int, end: int) -> dict:
-        pre_query = '''histogram_quantile(0.9, sum(rate(originx_thread_polaris_nanoseconds_bucket{pod="'''
+        query = 'increase(originx_thread_polaris_nanoseconds_sum{pod="' + pod + '", type="cpu"}[1m])'
-        query = pre_query + pod + '''", type="''' + type + '''"}[1m]))  by (tid, vmrange))'''
         step = '10m'
         hour = 3600 * 1000
 

api/initializer/__init__.py

@@ -11,6 +11,8 @@ import os
 def run_initializers(app: Flask):
     if os.environ.get("MODE") != "api":
         return
+    if os.environ.get("APO_INIT") == "false":
+        return
     with app.app_context():
         for func, _ in sorted(_initializers, key=lambda x: x[1]):
             func()