mirror of
https://github.com/router-for-me/Cli-Proxy-API-Management-Center.git
synced 2026-06-16 21:03:58 +08:00
refactor(logs): replace score-based usage trace matching with path-and-model filtering
This commit is contained in:
@@ -1023,6 +1023,7 @@
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"trace_confidence_low": "Low",
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"trace_score": "Score {{score}}",
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"trace_delta_seconds": "Δt {{seconds}}s",
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"trace_model_matched": "Model Matched",
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"trace_request_id": "Request ID",
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"trace_method": "Method",
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"trace_path": "Path",
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@@ -1026,6 +1026,7 @@
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"trace_confidence_low": "Низкая",
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"trace_score": "Оценка {{score}}",
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"trace_delta_seconds": "Δt {{seconds}}с",
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"trace_model_matched": "Модель совпала",
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"trace_request_id": "Request ID",
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"trace_method": "Метод",
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"trace_path": "Путь",
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@@ -1023,6 +1023,7 @@
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"trace_confidence_low": "低",
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"trace_score": "分数 {{score}}",
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"trace_delta_seconds": "时间差 {{seconds}} 秒",
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"trace_model_matched": "模型匹配",
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"trace_request_id": "请求 ID",
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"trace_method": "请求方法",
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"trace_path": "路径",
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@@ -693,34 +693,18 @@
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flex-wrap: wrap;
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}
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.traceConfidenceBadge {
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.traceModelBadge {
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display: inline-flex;
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align-items: center;
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padding: 2px 8px;
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border-radius: $radius-full;
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border: 1px solid var(--border-color);
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border: 1px solid var(--success-badge-border, #6ee7b7);
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font-size: 11px;
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font-weight: 700;
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}
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.traceConfidenceHigh {
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color: var(--success-badge-text, #065f46);
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background: var(--success-badge-bg, #d1fae5);
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border-color: var(--success-badge-border, #6ee7b7);
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}
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.traceConfidenceMedium {
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color: var(--warning-text);
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background: var(--warning-bg);
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border-color: var(--warning-border);
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}
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.traceConfidenceLow {
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color: var(--text-secondary);
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background: var(--bg-primary);
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}
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.traceScore,
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.traceDelta {
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font-size: 11px;
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color: var(--text-secondary);
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+5
-12
@@ -970,12 +970,6 @@ export function LogsPage() {
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) : (
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<div className={styles.traceCandidates}>
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{trace.traceCandidates.map((candidate) => {
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const confidenceClass =
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candidate.confidence === 'high'
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? styles.traceConfidenceHigh
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: candidate.confidence === 'medium'
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? styles.traceConfidenceMedium
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: styles.traceConfidenceLow;
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const sourceInfo = trace.resolveTraceSourceInfo(
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String(candidate.detail.source ?? ''),
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candidate.detail.auth_index
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@@ -986,12 +980,11 @@ export function LogsPage() {
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className={styles.traceCandidate}
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>
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<div className={styles.traceCandidateHeader}>
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<span className={`${styles.traceConfidenceBadge} ${confidenceClass}`}>
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{t(`logs.trace_confidence_${candidate.confidence}`)}
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</span>
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<span className={styles.traceScore}>
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{t('logs.trace_score', { score: candidate.score })}
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</span>
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{candidate.modelMatched && (
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<span className={styles.traceModelBadge}>
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{t('logs.trace_model_matched')}
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</span>
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)}
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{candidate.timeDeltaMs !== null && (
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<span className={styles.traceDelta}>
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{t('logs.trace_delta_seconds', {
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@@ -12,19 +12,14 @@ import {
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} from '@/utils/usage';
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import type { ParsedLogLine } from './logTypes';
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type TraceConfidence = 'high' | 'medium' | 'low';
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export type TraceCandidate = {
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detail: UsageDetailWithEndpoint;
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score: number;
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confidence: TraceConfidence;
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modelMatched: boolean;
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timeDeltaMs: number | null;
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};
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const TRACE_AUTH_CACHE_MS = 60 * 1000;
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const TRACE_MATCH_STRONG_WINDOW_MS = 3 * 1000;
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const TRACE_MATCH_WINDOW_MS = 10 * 1000;
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const TRACE_MATCH_MAX_WINDOW_MS = 30 * 1000;
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const TRACE_MAX_CANDIDATES = 5;
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const TRACEABLE_EXACT_PATHS = new Set(['/v1/chat/completions', '/v1/messages', '/v1/responses']);
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const TRACEABLE_PREFIX_PATHS = ['/v1beta/models'];
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@@ -48,70 +43,17 @@ export const isTraceableRequestPath = (value?: string): boolean => {
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return TRACEABLE_PREFIX_PATHS.some((prefix) => normalizedPath.startsWith(prefix));
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};
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const scoreTraceCandidate = (
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line: ParsedLogLine,
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detail: UsageDetailWithEndpoint
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): TraceCandidate | null => {
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let score = 0;
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let timeDeltaMs: number | null = null;
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const MODEL_EXTRACT_REGEX = /\bmodel[=:]\s*"?([a-zA-Z0-9._\-/]+)"?/i;
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const logTimestampMs = line.timestamp ? Date.parse(line.timestamp) : Number.NaN;
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const detailTimestampMs = detail.__timestampMs;
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if (!Number.isNaN(logTimestampMs) && detailTimestampMs > 0) {
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timeDeltaMs = Math.abs(logTimestampMs - detailTimestampMs);
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if (timeDeltaMs <= TRACE_MATCH_STRONG_WINDOW_MS) {
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score += 42;
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} else if (timeDeltaMs <= TRACE_MATCH_WINDOW_MS) {
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score += 30;
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} else if (timeDeltaMs <= TRACE_MATCH_MAX_WINDOW_MS) {
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score += 12;
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} else {
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score -= 12;
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}
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}
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const extractModelFromMessage = (message?: string): string | undefined => {
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if (!message) return undefined;
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const match = message.match(MODEL_EXTRACT_REGEX);
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return match?.[1] || undefined;
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};
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let methodMatched = false;
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if (line.method && detail.__endpointMethod) {
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if (line.method.toUpperCase() === detail.__endpointMethod.toUpperCase()) {
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score += 18;
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methodMatched = true;
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} else {
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score -= 8;
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}
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}
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const logPath = normalizeTracePath(line.path);
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const detailPath = normalizeTracePath(detail.__endpointPath);
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let pathMatched = false;
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if (logPath && detailPath) {
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if (logPath === detailPath) {
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score += 24;
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pathMatched = true;
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} else if (logPath.startsWith(detailPath) || detailPath.startsWith(logPath)) {
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score += 12;
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pathMatched = true;
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} else {
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score -= 8;
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}
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}
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if (typeof line.statusCode === 'number') {
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const logFailed = line.statusCode >= 400;
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score += logFailed === detail.failed ? 10 : -6;
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}
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if (
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timeDeltaMs !== null &&
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timeDeltaMs > TRACE_MATCH_MAX_WINDOW_MS &&
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!methodMatched &&
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!pathMatched
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) {
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return null;
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}
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if (score <= 0) return null;
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const confidence: TraceConfidence = score >= 70 ? 'high' : score >= 45 ? 'medium' : 'low';
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return { detail, score, confidence, timeDeltaMs };
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const isPathMatch = (logPath: string, detailPath: string): boolean => {
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if (!logPath || !detailPath) return false;
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return logPath === detailPath || logPath.startsWith(detailPath) || detailPath.startsWith(logPath);
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};
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const getErrorMessage = (err: unknown): string => {
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@@ -236,16 +178,42 @@ export function useTraceResolver(options: UseTraceResolverOptions): UseTraceReso
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const traceCandidates = useMemo(() => {
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if (!traceLogLine) return [];
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const scored = traceUsageDetails
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.map((detail) => scoreTraceCandidate(traceLogLine, detail))
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.filter((item): item is TraceCandidate => item !== null)
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.sort((a, b) => {
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if (b.score !== a.score) return b.score - a.score;
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const aDelta = a.timeDeltaMs ?? Number.MAX_SAFE_INTEGER;
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const bDelta = b.timeDeltaMs ?? Number.MAX_SAFE_INTEGER;
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return aDelta - bDelta;
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});
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return scored.slice(0, 8);
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const logPath = normalizeTracePath(traceLogLine.path);
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if (!logPath) return [];
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const logTimestampMs = traceLogLine.timestamp
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? Date.parse(traceLogLine.timestamp)
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: Number.NaN;
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// Step 1: filter by path match
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const pathMatched = traceUsageDetails.filter((detail) =>
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isPathMatch(logPath, normalizeTracePath(detail.__endpointPath))
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);
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if (pathMatched.length === 0) return [];
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// Step 2: try to extract model from log message, then filter by model
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const logModel = extractModelFromMessage(traceLogLine.message);
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const modelMatched = logModel
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? pathMatched.filter(
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(d) => d.__modelName?.toLowerCase() === logModel.toLowerCase()
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)
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: [];
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// Step 3: prefer model-matched set; fall back to path-matched
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const useModelSet = modelMatched.length > 0;
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const source = useModelSet ? modelMatched : pathMatched;
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return source
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.map((detail) => {
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const timeDeltaMs =
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!Number.isNaN(logTimestampMs) && detail.__timestampMs > 0
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? Math.abs(logTimestampMs - detail.__timestampMs)
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: null;
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return { detail, modelMatched: useModelSet, timeDeltaMs } satisfies TraceCandidate;
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})
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.sort((a, b) => (b.detail.__timestampMs || 0) - (a.detail.__timestampMs || 0))
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.slice(0, TRACE_MAX_CANDIDATES);
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}, [traceLogLine, traceUsageDetails]);
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const resolveTraceSourceInfo = useCallback(
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