Add visual indicators for the Hybrid ML model version

Update the UI to display badges indicating the use of Hybrid ML v2.0.0 on both the Training and Anomaly Detection cards, and refine descriptive text for clarity.

Replit-Commit-Author: Agent
Replit-Commit-Session-Id: 7a657272-55ba-4a79-9a2e-f1ed9bc7a528
Replit-Commit-Checkpoint-Type: full_checkpoint
Replit-Commit-Event-Id: 7abf54ed-5574-4967-a851-0590e80d6ad1
Replit-Commit-Screenshot-Url: https://storage.googleapis.com/screenshot-production-us-central1/449cf7c4-c97a-45ae-8234-e5c5b8d6a84f/7a657272-55ba-4a79-9a2e-f1ed9bc7a528/jFtLBWL
This commit is contained in:
marco370 2025-11-25 17:24:29 +00:00
parent fa61c820e7
commit 9761ee6036
2 changed files with 21 additions and 11 deletions

View File

@ -19,7 +19,7 @@ localPort = 41303
externalPort = 3002 externalPort = 3002
[[ports]] [[ports]]
localPort = 43081 localPort = 42975
externalPort = 4200 externalPort = 4200
[[ports]] [[ports]]

View File

@ -198,14 +198,19 @@ export default function TrainingPage() {
<div className="grid grid-cols-1 md:grid-cols-2 gap-4"> <div className="grid grid-cols-1 md:grid-cols-2 gap-4">
<Card data-testid="card-train-action"> <Card data-testid="card-train-action">
<CardHeader> <CardHeader>
<div className="flex items-center justify-between">
<CardTitle className="flex items-center gap-2"> <CardTitle className="flex items-center gap-2">
<Brain className="h-5 w-5" /> <Brain className="h-5 w-5" />
Addestramento Modello Addestramento Modello
</CardTitle> </CardTitle>
<Badge variant="secondary" className="bg-blue-50 text-blue-700 dark:bg-blue-950 dark:text-blue-300" data-testid="badge-model-version">
Hybrid ML v2.0.0
</Badge>
</div>
</CardHeader> </CardHeader>
<CardContent className="space-y-4"> <CardContent className="space-y-4">
<p className="text-sm text-muted-foreground"> <p className="text-sm text-muted-foreground">
Addestra il modello Isolation Forest analizzando i log recenti per rilevare pattern di traffico normale. Addestra il modello Hybrid ML (Isolation Forest + Ensemble Classifier) analizzando i log recenti per rilevare pattern di traffico normale.
</p> </p>
<Dialog open={isTrainDialogOpen} onOpenChange={setIsTrainDialogOpen}> <Dialog open={isTrainDialogOpen} onOpenChange={setIsTrainDialogOpen}>
<DialogTrigger asChild> <DialogTrigger asChild>
@ -273,14 +278,19 @@ export default function TrainingPage() {
<Card data-testid="card-detect-action"> <Card data-testid="card-detect-action">
<CardHeader> <CardHeader>
<div className="flex items-center justify-between">
<CardTitle className="flex items-center gap-2"> <CardTitle className="flex items-center gap-2">
<Search className="h-5 w-5" /> <Search className="h-5 w-5" />
Rilevamento Anomalie Rilevamento Anomalie
</CardTitle> </CardTitle>
<Badge variant="secondary" className="bg-green-50 text-green-700 dark:bg-green-950 dark:text-green-300" data-testid="badge-detection-version">
Hybrid ML v2.0.0
</Badge>
</div>
</CardHeader> </CardHeader>
<CardContent className="space-y-4"> <CardContent className="space-y-4">
<p className="text-sm text-muted-foreground"> <p className="text-sm text-muted-foreground">
Analizza i log recenti per rilevare anomalie e IP sospetti. Opzionalmente blocca automaticamente gli IP critici. Analizza i log recenti per rilevare anomalie e IP sospetti con il modello Hybrid ML. Blocca automaticamente gli IP critici (risk_score 80).
</p> </p>
<Dialog open={isDetectDialogOpen} onOpenChange={setIsDetectDialogOpen}> <Dialog open={isDetectDialogOpen} onOpenChange={setIsDetectDialogOpen}>
<DialogTrigger asChild> <DialogTrigger asChild>