refactor(logs): replace score-based usage trace matching with path-and-model filtering

This commit is contained in:
Supra4E8C
2026-02-23 21:10:18 +08:00
Unverified
parent 95798f6b4d
commit bdda9be187
6 changed files with 57 additions and 109 deletions
+1
View File
@@ -1023,6 +1023,7 @@
"trace_confidence_low": "Low",
"trace_score": "Score {{score}}",
"trace_delta_seconds": "Δt {{seconds}}s",
"trace_model_matched": "Model Matched",
"trace_request_id": "Request ID",
"trace_method": "Method",
"trace_path": "Path",
+1
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@@ -1026,6 +1026,7 @@
"trace_confidence_low": "Низкая",
"trace_score": "Оценка {{score}}",
"trace_delta_seconds": "Δt {{seconds}}с",
"trace_model_matched": "Модель совпала",
"trace_request_id": "Request ID",
"trace_method": "Метод",
"trace_path": "Путь",
+1
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@@ -1023,6 +1023,7 @@
"trace_confidence_low": "低",
"trace_score": "分数 {{score}}",
"trace_delta_seconds": "时间差 {{seconds}} 秒",
"trace_model_matched": "模型匹配",
"trace_request_id": "请求 ID",
"trace_method": "请求方法",
"trace_path": "路径",
+2 -18
View File
@@ -693,34 +693,18 @@
flex-wrap: wrap;
}
.traceConfidenceBadge {
.traceModelBadge {
display: inline-flex;
align-items: center;
padding: 2px 8px;
border-radius: $radius-full;
border: 1px solid var(--border-color);
border: 1px solid var(--success-badge-border, #6ee7b7);
font-size: 11px;
font-weight: 700;
}
.traceConfidenceHigh {
color: var(--success-badge-text, #065f46);
background: var(--success-badge-bg, #d1fae5);
border-color: var(--success-badge-border, #6ee7b7);
}
.traceConfidenceMedium {
color: var(--warning-text);
background: var(--warning-bg);
border-color: var(--warning-border);
}
.traceConfidenceLow {
color: var(--text-secondary);
background: var(--bg-primary);
}
.traceScore,
.traceDelta {
font-size: 11px;
color: var(--text-secondary);
+5 -12
View File
@@ -970,12 +970,6 @@ export function LogsPage() {
) : (
<div className={styles.traceCandidates}>
{trace.traceCandidates.map((candidate) => {
const confidenceClass =
candidate.confidence === 'high'
? styles.traceConfidenceHigh
: candidate.confidence === 'medium'
? styles.traceConfidenceMedium
: styles.traceConfidenceLow;
const sourceInfo = trace.resolveTraceSourceInfo(
String(candidate.detail.source ?? ''),
candidate.detail.auth_index
@@ -986,12 +980,11 @@ export function LogsPage() {
className={styles.traceCandidate}
>
<div className={styles.traceCandidateHeader}>
<span className={`${styles.traceConfidenceBadge} ${confidenceClass}`}>
{t(`logs.trace_confidence_${candidate.confidence}`)}
</span>
<span className={styles.traceScore}>
{t('logs.trace_score', { score: candidate.score })}
</span>
{candidate.modelMatched && (
<span className={styles.traceModelBadge}>
{t('logs.trace_model_matched')}
</span>
)}
{candidate.timeDeltaMs !== null && (
<span className={styles.traceDelta}>
{t('logs.trace_delta_seconds', {
+47 -79
View File
@@ -12,19 +12,14 @@ import {
} from '@/utils/usage';
import type { ParsedLogLine } from './logTypes';
type TraceConfidence = 'high' | 'medium' | 'low';
export type TraceCandidate = {
detail: UsageDetailWithEndpoint;
score: number;
confidence: TraceConfidence;
modelMatched: boolean;
timeDeltaMs: number | null;
};
const TRACE_AUTH_CACHE_MS = 60 * 1000;
const TRACE_MATCH_STRONG_WINDOW_MS = 3 * 1000;
const TRACE_MATCH_WINDOW_MS = 10 * 1000;
const TRACE_MATCH_MAX_WINDOW_MS = 30 * 1000;
const TRACE_MAX_CANDIDATES = 5;
const TRACEABLE_EXACT_PATHS = new Set(['/v1/chat/completions', '/v1/messages', '/v1/responses']);
const TRACEABLE_PREFIX_PATHS = ['/v1beta/models'];
@@ -48,70 +43,17 @@ export const isTraceableRequestPath = (value?: string): boolean => {
return TRACEABLE_PREFIX_PATHS.some((prefix) => normalizedPath.startsWith(prefix));
};
const scoreTraceCandidate = (
line: ParsedLogLine,
detail: UsageDetailWithEndpoint
): TraceCandidate | null => {
let score = 0;
let timeDeltaMs: number | null = null;
const MODEL_EXTRACT_REGEX = /\bmodel[=:]\s*"?([a-zA-Z0-9._\-/]+)"?/i;
const logTimestampMs = line.timestamp ? Date.parse(line.timestamp) : Number.NaN;
const detailTimestampMs = detail.__timestampMs;
if (!Number.isNaN(logTimestampMs) && detailTimestampMs > 0) {
timeDeltaMs = Math.abs(logTimestampMs - detailTimestampMs);
if (timeDeltaMs <= TRACE_MATCH_STRONG_WINDOW_MS) {
score += 42;
} else if (timeDeltaMs <= TRACE_MATCH_WINDOW_MS) {
score += 30;
} else if (timeDeltaMs <= TRACE_MATCH_MAX_WINDOW_MS) {
score += 12;
} else {
score -= 12;
}
}
const extractModelFromMessage = (message?: string): string | undefined => {
if (!message) return undefined;
const match = message.match(MODEL_EXTRACT_REGEX);
return match?.[1] || undefined;
};
let methodMatched = false;
if (line.method && detail.__endpointMethod) {
if (line.method.toUpperCase() === detail.__endpointMethod.toUpperCase()) {
score += 18;
methodMatched = true;
} else {
score -= 8;
}
}
const logPath = normalizeTracePath(line.path);
const detailPath = normalizeTracePath(detail.__endpointPath);
let pathMatched = false;
if (logPath && detailPath) {
if (logPath === detailPath) {
score += 24;
pathMatched = true;
} else if (logPath.startsWith(detailPath) || detailPath.startsWith(logPath)) {
score += 12;
pathMatched = true;
} else {
score -= 8;
}
}
if (typeof line.statusCode === 'number') {
const logFailed = line.statusCode >= 400;
score += logFailed === detail.failed ? 10 : -6;
}
if (
timeDeltaMs !== null &&
timeDeltaMs > TRACE_MATCH_MAX_WINDOW_MS &&
!methodMatched &&
!pathMatched
) {
return null;
}
if (score <= 0) return null;
const confidence: TraceConfidence = score >= 70 ? 'high' : score >= 45 ? 'medium' : 'low';
return { detail, score, confidence, timeDeltaMs };
const isPathMatch = (logPath: string, detailPath: string): boolean => {
if (!logPath || !detailPath) return false;
return logPath === detailPath || logPath.startsWith(detailPath) || detailPath.startsWith(logPath);
};
const getErrorMessage = (err: unknown): string => {
@@ -236,16 +178,42 @@ export function useTraceResolver(options: UseTraceResolverOptions): UseTraceReso
const traceCandidates = useMemo(() => {
if (!traceLogLine) return [];
const scored = traceUsageDetails
.map((detail) => scoreTraceCandidate(traceLogLine, detail))
.filter((item): item is TraceCandidate => item !== null)
.sort((a, b) => {
if (b.score !== a.score) return b.score - a.score;
const aDelta = a.timeDeltaMs ?? Number.MAX_SAFE_INTEGER;
const bDelta = b.timeDeltaMs ?? Number.MAX_SAFE_INTEGER;
return aDelta - bDelta;
});
return scored.slice(0, 8);
const logPath = normalizeTracePath(traceLogLine.path);
if (!logPath) return [];
const logTimestampMs = traceLogLine.timestamp
? Date.parse(traceLogLine.timestamp)
: Number.NaN;
// Step 1: filter by path match
const pathMatched = traceUsageDetails.filter((detail) =>
isPathMatch(logPath, normalizeTracePath(detail.__endpointPath))
);
if (pathMatched.length === 0) return [];
// Step 2: try to extract model from log message, then filter by model
const logModel = extractModelFromMessage(traceLogLine.message);
const modelMatched = logModel
? pathMatched.filter(
(d) => d.__modelName?.toLowerCase() === logModel.toLowerCase()
)
: [];
// Step 3: prefer model-matched set; fall back to path-matched
const useModelSet = modelMatched.length > 0;
const source = useModelSet ? modelMatched : pathMatched;
return source
.map((detail) => {
const timeDeltaMs =
!Number.isNaN(logTimestampMs) && detail.__timestampMs > 0
? Math.abs(logTimestampMs - detail.__timestampMs)
: null;
return { detail, modelMatched: useModelSet, timeDeltaMs } satisfies TraceCandidate;
})
.sort((a, b) => (b.detail.__timestampMs || 0) - (a.detail.__timestampMs || 0))
.slice(0, TRACE_MAX_CANDIDATES);
}, [traceLogLine, traceUsageDetails]);
const resolveTraceSourceInfo = useCallback(