Refactor Training and Whitelist pages to use react-hook-form and Zod for validation, and enhance ML backend API routes with timeouts, input validation, and better error reporting. Replit-Commit-Author: Agent Replit-Commit-Session-Id: 7a657272-55ba-4a79-9a2e-f1ed9bc7a528 Replit-Commit-Checkpoint-Type: intermediate_checkpoint Replit-Commit-Event-Id: 95d9d0e3-3da7-43ff-b8d3-d9d5d8fd6f6f Replit-Commit-Screenshot-Url: https://storage.googleapis.com/screenshot-production-us-central1/449cf7c4-c97a-45ae-8234-e5c5b8d6a84f/7a657272-55ba-4a79-9a2e-f1ed9bc7a528/Aqah4U9
464 lines
19 KiB
TypeScript
464 lines
19 KiB
TypeScript
import { useQuery, useMutation } from "@tanstack/react-query";
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import { queryClient, apiRequest } from "@/lib/queryClient";
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import { Card, CardContent, CardHeader, CardTitle } from "@/components/ui/card";
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import { Button } from "@/components/ui/button";
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import { Badge } from "@/components/ui/badge";
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import { Brain, Play, Search, CheckCircle2, XCircle, Clock, TrendingUp } from "lucide-react";
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import { format } from "date-fns";
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import type { TrainingHistory } from "@shared/schema";
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import { useToast } from "@/hooks/use-toast";
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import { useState } from "react";
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import { useForm } from "react-hook-form";
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import { zodResolver } from "@hookform/resolvers/zod";
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import { z } from "zod";
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import {
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Dialog,
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DialogContent,
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DialogDescription,
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DialogHeader,
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DialogTitle,
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DialogTrigger,
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DialogFooter,
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} from "@/components/ui/dialog";
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import {
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Form,
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FormControl,
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FormField,
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FormItem,
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FormLabel,
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FormMessage,
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FormDescription,
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} from "@/components/ui/form";
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import { Input } from "@/components/ui/input";
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import { Checkbox } from "@/components/ui/checkbox";
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interface MLStatsResponse {
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logs?: { total: number; last_hour: number };
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detections?: { total: number; blocked: number };
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routers?: { active: number };
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latest_training?: any;
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}
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const trainFormSchema = z.object({
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max_records: z.coerce.number().min(1, "Minimo 1 record").max(1000000, "Massimo 1M record"),
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hours_back: z.coerce.number().min(1, "Minimo 1 ora").max(720, "Massimo 720 ore (30 giorni)"),
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});
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const detectFormSchema = z.object({
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max_records: z.coerce.number().min(1, "Minimo 1 record").max(1000000, "Massimo 1M record"),
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hours_back: z.coerce.number().min(1, "Minimo 1 ora").max(720, "Massimo 720 ore"),
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risk_threshold: z.coerce.number().min(0, "Minimo 0").max(100, "Massimo 100"),
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auto_block: z.boolean().default(true),
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});
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export default function TrainingPage() {
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const { toast } = useToast();
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const [isTrainDialogOpen, setIsTrainDialogOpen] = useState(false);
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const [isDetectDialogOpen, setIsDetectDialogOpen] = useState(false);
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const trainForm = useForm<z.infer<typeof trainFormSchema>>({
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resolver: zodResolver(trainFormSchema),
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defaultValues: {
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max_records: 100000,
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hours_back: 24,
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},
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});
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const detectForm = useForm<z.infer<typeof detectFormSchema>>({
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resolver: zodResolver(detectFormSchema),
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defaultValues: {
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max_records: 50000,
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hours_back: 1,
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risk_threshold: 75,
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auto_block: true,
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},
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});
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const { data: history, isLoading } = useQuery<TrainingHistory[]>({
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queryKey: ["/api/training-history"],
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refetchInterval: 10000,
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});
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const { data: mlStats } = useQuery<MLStatsResponse>({
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queryKey: ["/api/ml/stats"],
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refetchInterval: 10000,
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});
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const trainMutation = useMutation({
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mutationFn: async (params: z.infer<typeof trainFormSchema>) => {
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return await apiRequest("POST", "/api/ml/train", params);
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},
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onSuccess: () => {
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queryClient.invalidateQueries({ queryKey: ["/api/training-history"] });
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queryClient.invalidateQueries({ queryKey: ["/api/ml/stats"] });
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toast({
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title: "Training avviato",
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description: "Il modello ML è in addestramento. Controlla lo storico tra qualche minuto.",
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});
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setIsTrainDialogOpen(false);
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trainForm.reset();
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},
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onError: (error: any) => {
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toast({
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title: "Errore",
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description: error.message || "Impossibile avviare il training",
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variant: "destructive",
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});
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},
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});
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const detectMutation = useMutation({
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mutationFn: async (params: z.infer<typeof detectFormSchema>) => {
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return await apiRequest("POST", "/api/ml/detect", params);
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},
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onSuccess: () => {
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queryClient.invalidateQueries({ queryKey: ["/api/detections"] });
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queryClient.invalidateQueries({ queryKey: ["/api/stats"] });
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toast({
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title: "Detection avviata",
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description: "Analisi anomalie in corso. Controlla i rilevamenti tra qualche secondo.",
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});
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setIsDetectDialogOpen(false);
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detectForm.reset();
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},
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onError: (error: any) => {
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toast({
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title: "Errore",
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description: error.message || "Impossibile avviare la detection",
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variant: "destructive",
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});
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},
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});
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const onTrainSubmit = (data: z.infer<typeof trainFormSchema>) => {
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trainMutation.mutate(data);
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};
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const onDetectSubmit = (data: z.infer<typeof detectFormSchema>) => {
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detectMutation.mutate(data);
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};
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return (
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<div className="flex flex-col gap-6 p-6" data-testid="page-training">
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<div>
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<h1 className="text-3xl font-semibold" data-testid="text-page-title">Machine Learning</h1>
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<p className="text-muted-foreground" data-testid="text-page-subtitle">
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Training e detection del modello Isolation Forest
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</p>
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</div>
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{/* ML Stats */}
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{mlStats && (
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<div className="grid grid-cols-1 md:grid-cols-3 gap-4">
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<Card data-testid="card-ml-logs">
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<CardHeader className="flex flex-row items-center justify-between gap-2 space-y-0 pb-2">
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<CardTitle className="text-sm font-medium">Log Totali</CardTitle>
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<Brain className="h-4 w-4 text-muted-foreground" />
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</CardHeader>
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<CardContent>
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<div className="text-2xl font-semibold" data-testid="text-ml-logs-total">
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{mlStats.logs?.total?.toLocaleString() || 0}
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</div>
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<p className="text-xs text-muted-foreground mt-1">
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Ultima ora: {mlStats.logs?.last_hour?.toLocaleString() || 0}
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</p>
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</CardContent>
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</Card>
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<Card data-testid="card-ml-detections">
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<CardHeader className="flex flex-row items-center justify-between gap-2 space-y-0 pb-2">
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<CardTitle className="text-sm font-medium">Detection Totali</CardTitle>
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<Search className="h-4 w-4 text-muted-foreground" />
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</CardHeader>
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<CardContent>
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<div className="text-2xl font-semibold" data-testid="text-ml-detections-total">
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{mlStats.detections?.total || 0}
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</div>
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<p className="text-xs text-muted-foreground mt-1">
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Bloccati: {mlStats.detections?.blocked || 0}
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</p>
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</CardContent>
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</Card>
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<Card data-testid="card-ml-routers">
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<CardHeader className="flex flex-row items-center justify-between gap-2 space-y-0 pb-2">
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<CardTitle className="text-sm font-medium">Router Attivi</CardTitle>
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<TrendingUp className="h-4 w-4 text-muted-foreground" />
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</CardHeader>
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<CardContent>
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<div className="text-2xl font-semibold" data-testid="text-ml-routers-active">
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{mlStats.routers?.active || 0}
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</div>
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</CardContent>
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</Card>
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</div>
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)}
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{/* Actions */}
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<div className="grid grid-cols-1 md:grid-cols-2 gap-4">
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<Card data-testid="card-train-action">
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<CardHeader>
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<CardTitle className="flex items-center gap-2">
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<Brain className="h-5 w-5" />
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Addestramento Modello
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</CardTitle>
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</CardHeader>
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<CardContent className="space-y-4">
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<p className="text-sm text-muted-foreground">
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Addestra il modello Isolation Forest analizzando i log recenti per rilevare pattern di traffico normale.
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</p>
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<Dialog open={isTrainDialogOpen} onOpenChange={setIsTrainDialogOpen}>
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<DialogTrigger asChild>
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<Button className="w-full" data-testid="button-start-training">
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<Play className="h-4 w-4 mr-2" />
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Avvia Training
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</Button>
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</DialogTrigger>
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<DialogContent data-testid="dialog-training">
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<DialogHeader>
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<DialogTitle>Avvia Training ML</DialogTitle>
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<DialogDescription>
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Configura i parametri per l'addestramento del modello
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</DialogDescription>
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</DialogHeader>
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<Form {...trainForm}>
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<form onSubmit={trainForm.handleSubmit(onTrainSubmit)} className="space-y-4 py-4">
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<FormField
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control={trainForm.control}
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name="max_records"
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render={({ field }) => (
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<FormItem>
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<FormLabel>Numero Record</FormLabel>
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<FormControl>
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<Input type="number" {...field} data-testid="input-train-records" />
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</FormControl>
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<FormDescription>Consigliato: 100000</FormDescription>
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<FormMessage />
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</FormItem>
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)}
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/>
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<FormField
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control={trainForm.control}
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name="hours_back"
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render={({ field }) => (
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<FormItem>
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<FormLabel>Ore Precedenti</FormLabel>
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<FormControl>
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<Input type="number" {...field} data-testid="input-train-hours" />
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</FormControl>
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<FormDescription>Consigliato: 24</FormDescription>
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<FormMessage />
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</FormItem>
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)}
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/>
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<DialogFooter>
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<Button
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type="button"
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variant="outline"
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onClick={() => setIsTrainDialogOpen(false)}
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data-testid="button-cancel-training"
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>
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Annulla
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</Button>
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<Button type="submit" disabled={trainMutation.isPending} data-testid="button-confirm-training">
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{trainMutation.isPending ? "Avvio..." : "Avvia Training"}
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</Button>
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</DialogFooter>
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</form>
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</Form>
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</DialogContent>
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</Dialog>
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</CardContent>
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</Card>
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<Card data-testid="card-detect-action">
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<CardHeader>
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<CardTitle className="flex items-center gap-2">
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<Search className="h-5 w-5" />
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Rilevamento Anomalie
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</CardTitle>
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</CardHeader>
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<CardContent className="space-y-4">
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<p className="text-sm text-muted-foreground">
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Analizza i log recenti per rilevare anomalie e IP sospetti. Opzionalmente blocca automaticamente gli IP critici.
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</p>
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<Dialog open={isDetectDialogOpen} onOpenChange={setIsDetectDialogOpen}>
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<DialogTrigger asChild>
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<Button variant="secondary" className="w-full" data-testid="button-start-detection">
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<Search className="h-4 w-4 mr-2" />
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Avvia Detection
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</Button>
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</DialogTrigger>
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<DialogContent data-testid="dialog-detection">
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<DialogHeader>
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<DialogTitle>Avvia Detection Anomalie</DialogTitle>
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<DialogDescription>
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Configura i parametri per il rilevamento anomalie
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</DialogDescription>
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</DialogHeader>
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<Form {...detectForm}>
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<form onSubmit={detectForm.handleSubmit(onDetectSubmit)} className="space-y-4 py-4">
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<FormField
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control={detectForm.control}
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name="max_records"
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render={({ field }) => (
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<FormItem>
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<FormLabel>Numero Record</FormLabel>
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<FormControl>
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<Input type="number" {...field} data-testid="input-detect-records" />
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</FormControl>
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<FormDescription>Consigliato: 50000</FormDescription>
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<FormMessage />
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</FormItem>
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)}
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/>
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<FormField
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control={detectForm.control}
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name="hours_back"
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render={({ field }) => (
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<FormItem>
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<FormLabel>Ore Precedenti</FormLabel>
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<FormControl>
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<Input type="number" {...field} data-testid="input-detect-hours" />
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</FormControl>
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<FormDescription>Consigliato: 1</FormDescription>
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<FormMessage />
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</FormItem>
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)}
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/>
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<FormField
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control={detectForm.control}
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name="risk_threshold"
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render={({ field }) => (
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<FormItem>
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<FormLabel>Soglia Rischio (%)</FormLabel>
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<FormControl>
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<Input type="number" min="0" max="100" {...field} data-testid="input-detect-threshold" />
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</FormControl>
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<FormDescription>Consigliato: 75</FormDescription>
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<FormMessage />
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</FormItem>
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)}
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/>
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<FormField
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control={detectForm.control}
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name="auto_block"
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render={({ field }) => (
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<FormItem className="flex flex-row items-start space-x-3 space-y-0">
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<FormControl>
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<Checkbox
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checked={field.value}
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onCheckedChange={field.onChange}
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data-testid="checkbox-auto-block"
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/>
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</FormControl>
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<div className="space-y-1 leading-none">
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<FormLabel>Blocco automatico IP critici (≥80)</FormLabel>
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</div>
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</FormItem>
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)}
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/>
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<DialogFooter>
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<Button
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type="button"
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variant="outline"
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onClick={() => setIsDetectDialogOpen(false)}
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data-testid="button-cancel-detection"
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>
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Annulla
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</Button>
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<Button type="submit" disabled={detectMutation.isPending} data-testid="button-confirm-detection">
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{detectMutation.isPending ? "Avvio..." : "Avvia Detection"}
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</Button>
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</DialogFooter>
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</form>
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</Form>
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</DialogContent>
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</Dialog>
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</CardContent>
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</Card>
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</div>
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{/* Training History */}
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<Card data-testid="card-training-history">
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<CardHeader>
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<CardTitle className="flex items-center gap-2">
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<Clock className="h-5 w-5" />
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Storico Training ({history?.length || 0})
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</CardTitle>
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</CardHeader>
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<CardContent>
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{isLoading ? (
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<div className="text-center py-8 text-muted-foreground" data-testid="text-loading">
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Caricamento...
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</div>
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) : history && history.length > 0 ? (
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<div className="space-y-3">
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{history.map((item) => (
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<div
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key={item.id}
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className="p-4 rounded-lg border hover-elevate"
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data-testid={`training-item-${item.id}`}
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>
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<div className="flex items-start justify-between gap-4">
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<div className="flex-1 space-y-1">
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<div className="flex items-center gap-2">
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<p className="font-medium" data-testid={`text-version-${item.id}`}>
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Versione {item.modelVersion}
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</p>
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{item.status === "success" ? (
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<Badge variant="outline" className="bg-green-50" data-testid={`badge-status-${item.id}`}>
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<CheckCircle2 className="h-3 w-3 mr-1" />
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Successo
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</Badge>
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) : (
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<Badge variant="destructive" data-testid={`badge-status-${item.id}`}>
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<XCircle className="h-3 w-3 mr-1" />
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Fallito
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</Badge>
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)}
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</div>
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<div className="grid grid-cols-2 md:grid-cols-4 gap-2 text-sm text-muted-foreground">
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<div>
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<span className="font-medium">Record:</span> {item.recordsProcessed.toLocaleString()}
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</div>
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<div>
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<span className="font-medium">Feature:</span> {item.featuresCount}
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</div>
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{item.accuracy && (
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<div>
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<span className="font-medium">Accuracy:</span> {item.accuracy}%
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</div>
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)}
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{item.trainingDuration && (
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<div>
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<span className="font-medium">Durata:</span> {item.trainingDuration}s
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</div>
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)}
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</div>
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<p className="text-xs text-muted-foreground" data-testid={`text-date-${item.id}`}>
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{format(new Date(item.trainedAt), "dd/MM/yyyy HH:mm:ss")}
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</p>
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{item.notes && (
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<p className="text-sm text-muted-foreground" data-testid={`text-notes-${item.id}`}>
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{item.notes}
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</p>
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)}
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</div>
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</div>
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</div>
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))}
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</div>
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) : (
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<div className="text-center py-12 text-muted-foreground" data-testid="text-empty">
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<Brain className="h-12 w-12 mx-auto mb-4 opacity-50" />
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<p className="font-medium">Nessun training eseguito</p>
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<p className="text-sm mt-2">Avvia il primo training per addestrare il modello ML</p>
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</div>
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)}
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</CardContent>
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</Card>
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</div>
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);
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}
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