Leftovers for AI

keep-ui/app/ai/ai.tsx

@@ -9,22 +9,32 @@ export default function Ai() {
   const { data: aistats, isLoading, refetch: refetchAIStats } = useAIStats();
   const { updateAISettings } = UseAIActions();
 
+  useEffect(() => {
+    const interval = setInterval(() => {
+      refetchAIStats();
+    }, 5000);
+
+    return () => clearInterval(interval);
+  }, [refetchAIStats]);
+
   return (
     <main className="p-4 md:p-10 mx-auto max-w-full">
       <div className="flex justify-between items-center">
         <div>
-          <Title>AI Correlation</Title>
+          <Title>Pluggable AI</Title>
           <Subtitle>
-            Correlating alerts to incidents based on past alerts, incidents, and
-            the other data.
+            External AI engines can be plugged in and configured here.
           </Subtitle>
         </div>
       </div>
       <Card className="mt-10 p-4 md:p-10 mx-auto">
         <div>
           <div>
-            <div className="grid grid-cols-1 gap-4 mt-6">
-              {isLoading ? <p>Loading algorithms and settings...</p> : null}
+            <div className="grid grid-cols-1 gap-4">
+              {isLoading ? <p>Loading algorithms and their settings...</p> : null}
+              {aistats?.algorithm_configs?.length === 0 && (
+                <p>No AI plugged in yet. Please reach out to us!</p>
+              )}
               {aistats?.algorithm_configs?.map((algorithm_config, index) => (
                 <Card
                   key={index}

keep-ui/components/navbar/AILink.tsx

@@ -9,7 +9,7 @@ import { usePollAILogs } from "utils/hooks/useAI";
 
 export const AILink = () => {
   const [text, setText] = useState("");
-  const [newText, setNewText] = useState("AI correlation");
+  const [newText, setNewText] = useState("Pluggable AI");
 
   const mutateAILogs = (logs: any) => {
     setNewText("AI iterated 🎉")

keep/api/bl/incidents_bl.py

@@ -80,7 +80,7 @@ def create_incident(self, incident_dto: IncidentDtoIn) -> IncidentDto:
         return new_incident_dto
 
     async def add_alerts_to_incident(
-        self, incident_id: UUID, alert_ids: List[UUID]
+        self, incident_id: UUID, alert_ids: List[UUID], is_created_by_ai: bool = False
     ) -> None:
         self.logger.info(
             "Adding alerts to incident",
@@ -90,7 +90,7 @@ async def add_alerts_to_incident(
         if not incident:
             raise HTTPException(status_code=404, detail="Incident not found")
 
-        add_alerts_to_incident_by_incident_id(self.tenant_id, incident_id, alert_ids)
+        add_alerts_to_incident_by_incident_id(self.tenant_id, incident_id, alert_ids, is_created_by_ai)
         self.logger.info(
             "Alerts added to incident",
             extra={"incident_id": incident_id, "alert_ids": alert_ids},

keep/api/models/db/ai_external.py

@@ -51,9 +51,10 @@ def unique_id(self):
     api_url=os.environ.get("AI_TRANSFORMERS_API_HOST", None),
     config_default=json.dumps(
         [
-            {"min": 0.3, "max": 0.99, "value": 0.8, "type": "float", "name": "Correlation Threshold", "description": "The minimum correlation value to consider two alerts belonging to an ancident."},
-            {"min": 0.3, "max": 0.99, "value": 0.8, "type": "float", "name": "Model Accuracy Threshold", "description": "The trained model accuracy will be evaluated using cross-validation. If the accuracy is below this threshold, the model will be retrained."},
-            {"min": 2, "max": 20, "value": 10, "type": "int", "name": "Train Epochs", "description": "The amount of epochs to train the model for. The less the better to avoid over-fitting."},
+            {"min": 0.3, "max": 0.99, "value": 0.9, "type": "float", "name": "Model Accuracy Threshold", "description": "The trained model accuracy will be evaluated using 30 percent of alerts-to-incident correlations as a validation dataset. If the accuracy is below this threshold, the correlation won't be launched."},
+            {"min": 0.3, "max": 0.99, "value": 0.9, "type": "float", "name": "Correlation Threshold", "description": "The minimum correlation value to consider two alerts belonging to an ancident."},
+            {"min": 1, "max": 20, "value": 1, "type": "int", "name": "Train Epochs", "description": "The amount of epochs to train the model for. The less the better to avoid over-fitting."},
+            {"value": True, "type": "bool", "name": "Create New Incidents", "description": "Do you want AI to issue new incident if correlation is detected and the icnident alerts are related to is resolved?"},
             {"value": True, "type": "bool", "name": "Enabled", "description": "Enable or disable the algorithm."},
         ]
     )

keep/api/routes/incidents.py

@@ -446,7 +446,7 @@ async def add_alerts_to_incident(
 ):
     tenant_id = authenticated_entity.tenant_id
     incident_bl = IncidentBl(tenant_id, session, pusher_client)
-    await incident_bl.add_alerts_to_incident(incident_id, alert_ids)
+    await incident_bl.add_alerts_to_incident(incident_id, alert_ids, is_created_by_ai)
     return Response(status_code=202)