mirror of
https://github.com/fawney19/Aether.git
synced 2026-01-03 00:02:28 +08:00
- Remove stream_smoothing configuration from SystemConfigService (moved to handler default) - Remove stream smoothing UI controls from admin settings page - Add AdminClearSingleAffinityAdapter for targeted cache invalidation - Add clearSingleAffinity API endpoint to clear specific affinity cache entries - Include global_model_id in affinity list response for UI deletion support - Improve CI/CD workflow with hash-based base image change detection - Add hash label to base image for reliable cache invalidation detection - Use remote image inspection to determine if base image rebuild is needed - Include Dockerfile.base in hash calculation for proper dependency tracking
377 lines
10 KiB
TypeScript
377 lines
10 KiB
TypeScript
/**
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* 缓存监控 API 客户端
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*/
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import api from './client'
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export interface CacheStats {
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scheduler: string
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cache_reservation_ratio: number
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affinity_stats: {
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storage_type: string
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total_affinities: number
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active_affinities: number | string
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cache_hits: number
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cache_misses: number
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cache_hit_rate: number
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cache_invalidations: number
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provider_switches: number
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key_switches: number
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config: {
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default_ttl: number
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}
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}
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}
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export interface DynamicReservationConfig {
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probe_phase_requests: number
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probe_reservation: number
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stable_min_reservation: number
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stable_max_reservation: number
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low_load_threshold: number
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high_load_threshold: number
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success_count_for_full_confidence: number
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cooldown_hours_for_full_confidence: number
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}
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export interface CacheConfig {
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cache_ttl_seconds: number
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cache_reservation_ratio: number
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dynamic_reservation?: {
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enabled: boolean
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config: DynamicReservationConfig
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description: Record<string, string>
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}
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description: {
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cache_ttl: string
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cache_reservation_ratio: string
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dynamic_reservation?: string
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}
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}
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export interface UserAffinity {
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affinity_key: string
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user_api_key_name: string | null
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user_api_key_prefix: string | null // 用户 API Key 脱敏显示(前4...后4)
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is_standalone: boolean
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user_id: string | null
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username: string | null
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email: string | null
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provider_id: string
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provider_name: string | null
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endpoint_id: string
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endpoint_api_format: string | null
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endpoint_url: string | null
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key_id: string
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key_name: string | null
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key_prefix: string | null // Provider Key 脱敏显示(前4...后4)
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rate_multiplier: number
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global_model_id: string | null // 原始的 global_model_id(用于删除)
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model_name: string | null // 模型名称(如 claude-haiku-4-5-20250514)
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model_display_name: string | null // 模型显示名称(如 Claude Haiku 4.5)
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api_format: string | null // API 格式 (claude/openai)
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created_at: number
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expire_at: number
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request_count: number
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}
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export interface AffinityListResponse {
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items: UserAffinity[]
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total: number
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matched_user_id?: string | null
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}
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export const cacheApi = {
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/**
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* 获取缓存统计信息
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*/
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async getStats(): Promise<CacheStats> {
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const response = await api.get('/api/admin/monitoring/cache/stats')
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return response.data.data
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},
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/**
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* 获取缓存配置
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*/
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async getConfig(): Promise<CacheConfig> {
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const response = await api.get('/api/admin/monitoring/cache/config')
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return response.data.data
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},
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/**
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* 查询用户缓存亲和性(现在返回该用户所有端点的亲和性列表)
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*
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* @param userIdentifier 用户标识符,支持:用户名、邮箱、User UUID、API Key ID
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*/
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async getUserAffinity(userIdentifier: string): Promise<UserAffinity[] | null> {
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const response = await api.get(`/api/admin/monitoring/cache/affinity/${userIdentifier}`)
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if (response.data.status === 'not_found') {
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return null
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}
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return response.data.affinities
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},
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/**
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* 清除用户缓存
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*
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* @param userIdentifier 用户标识符,支持:用户名、邮箱、User UUID、API Key ID
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*/
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async clearUserCache(userIdentifier: string): Promise<void> {
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await api.delete(`/api/admin/monitoring/cache/users/${userIdentifier}`)
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},
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/**
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* 清除单条缓存亲和性
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*
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* @param affinityKey API Key ID
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* @param endpointId Endpoint ID
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* @param modelId GlobalModel ID
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* @param apiFormat API 格式 (claude/openai)
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*/
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async clearSingleAffinity(affinityKey: string, endpointId: string, modelId: string, apiFormat: string): Promise<void> {
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await api.delete(`/api/admin/monitoring/cache/affinity/${affinityKey}/${endpointId}/${modelId}/${apiFormat}`)
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},
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/**
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* 清除所有缓存
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*/
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async clearAllCache(): Promise<{ count: number }> {
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const response = await api.delete('/api/admin/monitoring/cache')
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return response.data
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},
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/**
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* 清除指定Provider的所有缓存
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*/
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async clearProviderCache(providerId: string): Promise<{ count: number; provider_id: string }> {
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const response = await api.delete(`/api/admin/monitoring/cache/providers/${providerId}`)
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return response.data
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},
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/**
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* 获取缓存亲和性列表
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*/
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async listAffinities(keyword?: string): Promise<AffinityListResponse> {
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const response = await api.get('/api/admin/monitoring/cache/affinities', {
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params: keyword ? { keyword } : undefined
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})
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return response.data.data
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}
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}
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// 导出便捷函数
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export const {
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getStats,
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getConfig,
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getUserAffinity,
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clearUserCache,
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clearAllCache,
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clearProviderCache,
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listAffinities
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} = cacheApi
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// ==================== 缓存亲和性分析 API ====================
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export interface TTLAnalysisUser {
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group_id: string
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username: string | null
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email: string | null
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request_count: number
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interval_distribution: {
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within_5min: number
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within_15min: number
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within_30min: number
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within_60min: number
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over_60min: number
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}
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interval_percentages: {
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within_5min: number
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within_15min: number
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within_30min: number
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within_60min: number
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over_60min: number
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}
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percentiles: {
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p50: number | null
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p75: number | null
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p90: number | null
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}
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avg_interval_minutes: number | null
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min_interval_minutes: number | null
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max_interval_minutes: number | null
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recommended_ttl_minutes: number
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recommendation_reason: string
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}
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export interface TTLAnalysisResponse {
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analysis_period_hours: number
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total_users_analyzed: number
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ttl_distribution: {
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'5min': number
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'15min': number
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'30min': number
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'60min': number
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}
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users: TTLAnalysisUser[]
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}
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export interface CacheHitAnalysisResponse {
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analysis_period_hours: number
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total_requests: number
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requests_with_cache_hit: number
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request_cache_hit_rate: number
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total_input_tokens: number
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total_cache_read_tokens: number
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total_cache_creation_tokens: number
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token_cache_hit_rate: number
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total_cache_read_cost_usd: number
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total_cache_creation_cost_usd: number
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estimated_savings_usd: number
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}
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export interface IntervalTimelinePoint {
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x: string // ISO 时间字符串
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y: number // 间隔分钟数
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user_id?: string // 用户 ID(仅 include_user_info=true 时存在)
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model?: string // 模型名称
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}
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export interface IntervalTimelineResponse {
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analysis_period_hours: number
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total_points: number
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points: IntervalTimelinePoint[]
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users?: Record<string, string> // user_id -> username 映射(仅 include_user_info=true 时存在)
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models?: string[] // 出现的模型列表
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}
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export const cacheAnalysisApi = {
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/**
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* 分析缓存亲和性 TTL 推荐
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*/
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async analyzeTTL(params?: {
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user_id?: string
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api_key_id?: string
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hours?: number
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}): Promise<TTLAnalysisResponse> {
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const response = await api.get('/api/admin/usage/cache-affinity/ttl-analysis', { params })
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return response.data
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},
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/**
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* 分析缓存命中情况
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*/
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async analyzeHit(params?: {
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user_id?: string
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api_key_id?: string
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hours?: number
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}): Promise<CacheHitAnalysisResponse> {
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const response = await api.get('/api/admin/usage/cache-affinity/hit-analysis', { params })
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return response.data
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},
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/**
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* 获取请求间隔时间线数据
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*
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* @param params.include_user_info 是否包含用户信息(用于管理员多用户视图)
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*/
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async getIntervalTimeline(params?: {
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hours?: number
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limit?: number
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user_id?: string
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include_user_info?: boolean
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}): Promise<IntervalTimelineResponse> {
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const response = await api.get('/api/admin/usage/cache-affinity/interval-timeline', { params })
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return response.data
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}
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}
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// ==================== 模型映射缓存管理 API ====================
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// 映射条目
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export interface ModelMappingItem {
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mapping_name: string
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global_model_name: string | null
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global_model_display_name: string | null
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providers: string[]
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ttl: number | null
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}
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// 未映射的条目(NOT_FOUND、invalid、error)
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export interface UnmappedEntry {
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mapping_name: string
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status: 'not_found' | 'invalid' | 'error'
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ttl: number | null
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}
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// Provider 模型映射缓存(Redis 缓存)
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export interface ProviderModelMapping {
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provider_id: string
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provider_name: string
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global_model_id: string
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global_model_name: string
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global_model_display_name: string | null
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provider_model_name: string
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aliases: string[] | null
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ttl: number | null
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hit_count: number
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}
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export interface ModelMappingCacheStats {
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available: boolean
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message?: string
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ttl_seconds?: number
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total_keys?: number
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breakdown?: {
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model_by_id: number
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model_by_provider_global: number
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global_model_by_id: number
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global_model_by_name: number
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global_model_resolve: number
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}
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mappings?: ModelMappingItem[]
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provider_model_mappings?: ProviderModelMapping[] | null
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unmapped?: UnmappedEntry[] | null
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}
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export interface ClearModelMappingCacheResponse {
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status: string
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message: string
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deleted_count?: number
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model_name?: string
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deleted_keys?: string[]
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}
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export const modelMappingCacheApi = {
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/**
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* 获取模型映射缓存统计
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*/
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async getStats(): Promise<ModelMappingCacheStats> {
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const response = await api.get('/api/admin/monitoring/cache/model-mapping/stats')
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return response.data.data
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},
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/**
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* 清除所有模型映射缓存
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*/
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async clearAll(): Promise<ClearModelMappingCacheResponse> {
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const response = await api.delete('/api/admin/monitoring/cache/model-mapping')
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return response.data
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},
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/**
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* 清除指定模型名称的映射缓存
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*/
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async clearByName(modelName: string): Promise<ClearModelMappingCacheResponse> {
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const response = await api.delete(`/api/admin/monitoring/cache/model-mapping/${encodeURIComponent(modelName)}`)
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return response.data
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},
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/**
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* 清除指定 Provider 和 GlobalModel 的映射缓存
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*/
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async clearProviderModel(providerId: string, globalModelId: string): Promise<ClearModelMappingCacheResponse> {
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const response = await api.delete(`/api/admin/monitoring/cache/model-mapping/provider/${providerId}/${globalModelId}`)
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return response.data
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}
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}
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