feat:完善长期记忆控制台导入链路与联调测试
summary:\n- 扩展长期记忆控制台导入、调优与删除相关 UI/接口，补充中文化展示与任务细粒度状态管理\n- 强化 memory API 与后端路由能力，补齐导入任务、图谱检索、配置与运行态相关字段\n- 新增与增强前后端测试，覆盖导入多文件类型、检索、调优、删除及图谱查询关键路径 description:\n- dashboard: 重构 knowledge-base 页面与 memory-api，统一任务队列、分块分页、来源删除恢复、调优闭环交互\n- backend: 扩展 webui memory 路由与 A_Memorix 内核检索逻辑，完善服务侧能力与配置 schema\n- tests: 增加 webui 集成测试和 kernel 单测，提升导入/检索/调优/删除全流程回归保障
This commit is contained in:
DawnARC
@@ -53,6 +53,31 @@ export interface MemoryGraphPayload {
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total_edges: number
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}
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export interface MemoryGraphSearchItem {
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type: 'entity' | 'relation'
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title: string
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matched_field: string
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matched_value: string
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entity_name?: string
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entity_hash?: string
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appearance_count?: number
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subject?: string
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predicate?: string
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object?: string
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relation_hash?: string
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confidence?: number
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created_at?: number
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}
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export interface MemoryGraphSearchPayload {
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success: boolean
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query: string
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limit: number
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count: number
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items: MemoryGraphSearchItem[]
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error?: string
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}
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export interface MemoryGraphRelationDetailPayload {
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hash: string
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subject: string
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@@ -185,6 +210,8 @@ export interface MemoryRawConfigPayload {
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success: boolean
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config: string
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path: string
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exists?: boolean
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using_default?: boolean
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}
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export interface MemoryConfigSchemaPayload {
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@@ -198,7 +225,7 @@ export interface MemoryImportGuidePayload {
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content: string
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source?: string
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path?: string
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settings?: Record<string, unknown>
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settings?: MemoryImportSettings
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}
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export interface MemoryTaskPayload {
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@@ -217,6 +244,158 @@ export interface MemoryTaskListPayload {
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settings?: Record<string, unknown>
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}
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export type MemoryImportInputMode = 'text' | 'json'
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export type MemoryImportTaskKind =
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| 'upload'
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| 'paste'
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| 'raw_scan'
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| 'lpmm_openie'
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| 'lpmm_convert'
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| 'temporal_backfill'
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| 'maibot_migration'
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export interface MemoryImportSettings {
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max_queue_size?: number
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max_files_per_task?: number
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max_file_size_mb?: number
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max_paste_chars?: number
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default_file_concurrency?: number
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default_chunk_concurrency?: number
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max_file_concurrency?: number
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max_chunk_concurrency?: number
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poll_interval_ms?: number
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maibot_source_db_default?: string
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maibot_target_data_dir?: string
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path_aliases?: Record<string, string>
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llm_retry?: Record<string, number>
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convert_enable_staging_switch?: boolean
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convert_keep_backup_count?: number
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}
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export interface MemoryImportSettingsPayload {
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success: boolean
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settings: MemoryImportSettings
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}
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export interface MemoryImportPathAliasesPayload {
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success: boolean
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path_aliases: Record<string, string>
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}
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export interface MemoryImportResolvePathPayload {
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success?: boolean
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alias: string
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relative_path: string
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resolved_path: string
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exists: boolean
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is_file: boolean
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is_dir: boolean
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error?: string
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}
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export interface MemoryImportChunkPayload {
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chunk_id: string
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index: number
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chunk_type: string
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status: string
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step: string
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failed_at: string
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retryable: boolean
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error: string
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progress: number
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content_preview: string
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updated_at: number
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}
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export interface MemoryImportFilePayload {
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file_id: string
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name: string
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source_kind: string
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input_mode: MemoryImportInputMode
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status: string
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current_step: string
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detected_strategy_type: string
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total_chunks: number
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done_chunks: number
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failed_chunks: number
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cancelled_chunks: number
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progress: number
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error: string
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created_at: number
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updated_at: number
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source_path?: string
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content_hash?: string
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retry_chunk_indexes?: number[]
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retry_mode?: string
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chunks?: MemoryImportChunkPayload[]
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}
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export interface MemoryImportRetrySummary {
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chunk_retry_files?: number
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chunk_retry_chunks?: number
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file_fallback_files?: number
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skipped_files?: number
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parent_task_id?: string
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skipped_details?: Array<Record<string, string>>
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}
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export interface MemoryImportTaskPayload extends MemoryTaskPayload {
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task_id: string
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source: string
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status: string
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current_step: string
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total_chunks: number
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done_chunks: number
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failed_chunks: number
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cancelled_chunks: number
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progress: number
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error: string
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file_count: number
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created_at: number
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started_at?: number | null
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finished_at?: number | null
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updated_at: number
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task_kind?: MemoryImportTaskKind | string
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schema_detected?: string
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artifact_paths?: Record<string, string>
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rollback_info?: Record<string, unknown>
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retry_parent_task_id?: string
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retry_summary?: MemoryImportRetrySummary
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params?: Record<string, unknown>
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files?: MemoryImportFilePayload[]
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}
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export interface MemoryImportTaskListPayload {
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success: boolean
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items: MemoryImportTaskPayload[]
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count?: number
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settings?: MemoryImportSettings
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}
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export interface MemoryImportTaskDetailPayload {
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success: boolean
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task?: MemoryImportTaskPayload
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error?: string
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}
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export interface MemoryImportChunkListPayload {
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success: boolean
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task_id?: string
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file_id?: string
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offset?: number
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limit?: number
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total?: number
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items?: MemoryImportChunkPayload[]
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error?: string
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}
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export interface MemoryImportActionPayload {
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success: boolean
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task?: MemoryImportTaskPayload
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error?: string
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}
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export interface MemoryTuningProfilePayload {
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success: boolean
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profile?: Record<string, unknown>
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@@ -335,6 +514,17 @@ export async function getMemoryGraph(limit: number = 120): Promise<MemoryGraphPa
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return requestJson<MemoryGraphPayload>(`/graph?limit=${limit}`)
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}
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export async function getMemoryGraphSearch(
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query: string,
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limit: number = 50,
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): Promise<MemoryGraphSearchPayload> {
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const params = new URLSearchParams({
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query,
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limit: String(limit),
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})
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return requestJson<MemoryGraphSearchPayload>(`/graph/search?${params.toString()}`)
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}
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export async function getMemoryGraphNodeDetail(
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nodeId: string,
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options?: {
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@@ -466,16 +656,120 @@ export async function getMemoryImportGuide(): Promise<MemoryImportGuidePayload>
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return requestJson<MemoryImportGuidePayload>('/import/guide')
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}
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export async function getMemoryImportSettings(): Promise<Record<string, unknown>> {
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return requestJson('/import/settings')
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export async function getMemoryImportSettings(): Promise<MemoryImportSettingsPayload> {
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return requestJson<MemoryImportSettingsPayload>('/import/settings')
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}
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export async function getMemoryImportTasks(limit: number = 20): Promise<MemoryTaskListPayload> {
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return requestJson<MemoryTaskListPayload>(`/import/tasks?limit=${limit}`)
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export async function getMemoryImportPathAliases(): Promise<MemoryImportPathAliasesPayload> {
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return requestJson<MemoryImportPathAliasesPayload>('/import/path-aliases')
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}
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export async function createMemoryPasteImport(payload: Record<string, unknown>): Promise<{ success: boolean; task?: MemoryTaskPayload }> {
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return requestJson('/import/paste', {
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export async function resolveMemoryImportPath(payload: {
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alias: string
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relative_path?: string
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must_exist?: boolean
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}): Promise<MemoryImportResolvePathPayload> {
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return requestJson<MemoryImportResolvePathPayload>('/import/resolve-path', {
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method: 'POST',
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headers: { 'Content-Type': 'application/json' },
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body: JSON.stringify(payload),
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})
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}
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export async function getMemoryImportTasks(limit: number = 20): Promise<MemoryImportTaskListPayload> {
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return requestJson<MemoryImportTaskListPayload>(`/import/tasks?limit=${limit}`)
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}
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export async function getMemoryImportTask(taskId: string, includeChunks: boolean = false): Promise<MemoryImportTaskDetailPayload> {
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return requestJson<MemoryImportTaskDetailPayload>(
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`/import/tasks/${encodeURIComponent(taskId)}?include_chunks=${includeChunks ? 'true' : 'false'}`,
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)
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}
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export async function getMemoryImportTaskChunks(
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taskId: string,
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fileId: string,
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offset: number = 0,
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limit: number = 50,
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): Promise<MemoryImportChunkListPayload> {
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return requestJson<MemoryImportChunkListPayload>(
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`/import/tasks/${encodeURIComponent(taskId)}/chunks/${encodeURIComponent(fileId)}?offset=${offset}&limit=${limit}`,
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)
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}
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export async function createMemoryUploadImport(files: File[], payload: Record<string, unknown>): Promise<MemoryImportActionPayload> {
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const formData = new FormData()
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files.forEach((file) => {
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formData.append('files', file)
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})
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formData.append('payload_json', JSON.stringify(payload))
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return requestJson<MemoryImportActionPayload>('/import/upload', {
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method: 'POST',
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body: formData,
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})
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}
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export async function createMemoryPasteImport(payload: Record<string, unknown>): Promise<MemoryImportActionPayload> {
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return requestJson<MemoryImportActionPayload>('/import/paste', {
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method: 'POST',
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headers: { 'Content-Type': 'application/json' },
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body: JSON.stringify(payload),
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})
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}
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export async function createMemoryRawScanImport(payload: Record<string, unknown>): Promise<MemoryImportActionPayload> {
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return requestJson<MemoryImportActionPayload>('/import/raw-scan', {
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method: 'POST',
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headers: { 'Content-Type': 'application/json' },
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body: JSON.stringify(payload),
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})
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}
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export async function createMemoryLpmmOpenieImport(payload: Record<string, unknown>): Promise<MemoryImportActionPayload> {
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return requestJson<MemoryImportActionPayload>('/import/lpmm-openie', {
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method: 'POST',
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headers: { 'Content-Type': 'application/json' },
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body: JSON.stringify(payload),
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})
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}
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export async function createMemoryLpmmConvertImport(payload: Record<string, unknown>): Promise<MemoryImportActionPayload> {
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return requestJson<MemoryImportActionPayload>('/import/lpmm-convert', {
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method: 'POST',
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headers: { 'Content-Type': 'application/json' },
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body: JSON.stringify(payload),
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})
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}
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export async function createMemoryTemporalBackfillImport(payload: Record<string, unknown>): Promise<MemoryImportActionPayload> {
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return requestJson<MemoryImportActionPayload>('/import/temporal-backfill', {
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method: 'POST',
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headers: { 'Content-Type': 'application/json' },
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body: JSON.stringify(payload),
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})
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}
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export async function createMemoryMaibotMigrationImport(payload: Record<string, unknown>): Promise<MemoryImportActionPayload> {
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return requestJson<MemoryImportActionPayload>('/import/maibot-migration', {
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method: 'POST',
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headers: { 'Content-Type': 'application/json' },
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body: JSON.stringify(payload),
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})
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}
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export async function cancelMemoryImportTask(taskId: string): Promise<MemoryImportActionPayload> {
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return requestJson<MemoryImportActionPayload>(`/import/tasks/${encodeURIComponent(taskId)}/cancel`, {
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method: 'POST',
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})
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}
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export async function retryMemoryImportTask(
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taskId: string,
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payload: {
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overrides?: Record<string, unknown>
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} = {},
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): Promise<MemoryImportActionPayload> {
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return requestJson<MemoryImportActionPayload>(`/import/tasks/${encodeURIComponent(taskId)}/retry`, {
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method: 'POST',
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headers: { 'Content-Type': 'application/json' },
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body: JSON.stringify(payload),
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@@ -1,4 +1,4 @@
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import { render, screen } from '@testing-library/react'
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import { act, render, screen, waitFor, within } from '@testing-library/react'
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import userEvent from '@testing-library/user-event'
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import { beforeEach, describe, expect, it, vi } from 'vitest'
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@@ -28,12 +28,25 @@ vi.mock('@/components/memory/MemoryConfigEditor', () => ({
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vi.mock('@/components/memory/MemoryDeleteDialog', () => ({
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MemoryDeleteDialog: ({
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open,
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onExecute,
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onRestore,
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preview,
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result,
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}: {
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open: boolean
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preview?: { mode?: string; item_count?: number } | null
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result?: { operation_id?: string } | null
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onExecute?: () => void
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onRestore?: () => void
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}) => (
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open ? <div data-testid="memory-delete-dialog">{`delete:${preview?.mode ?? 'none'}:${preview?.item_count ?? 0}`}</div> : null
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open ? (
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<div data-testid="memory-delete-dialog">
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<div>{`preview:${preview?.mode ?? 'none'}:${preview?.item_count ?? 0}`}</div>
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<div>{`result:${result?.operation_id ?? 'none'}`}</div>
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<button type="button" onClick={onExecute}>执行删除</button>
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<button type="button" onClick={onRestore}>执行恢复</button>
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</div>
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) : null
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),
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}))
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@@ -41,26 +54,104 @@ vi.mock('@/lib/memory-api', () => ({
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getMemoryConfigSchema: vi.fn(),
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getMemoryConfig: vi.fn(),
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getMemoryConfigRaw: vi.fn(),
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getMemoryDeleteOperation: vi.fn(),
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getMemoryRuntimeConfig: vi.fn(),
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getMemoryImportGuide: vi.fn(),
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getMemoryImportSettings: vi.fn(),
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getMemoryImportPathAliases: vi.fn(),
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getMemoryImportTasks: vi.fn(),
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getMemoryTuningProfile: vi.fn(),
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getMemoryTuningTasks: vi.fn(),
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getMemorySources: vi.fn(),
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getMemoryDeleteOperations: vi.fn(),
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getMemoryImportTask: vi.fn(),
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getMemoryImportTaskChunks: vi.fn(),
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createMemoryUploadImport: vi.fn(),
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createMemoryPasteImport: vi.fn(),
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createMemoryRawScanImport: vi.fn(),
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createMemoryLpmmOpenieImport: vi.fn(),
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createMemoryLpmmConvertImport: vi.fn(),
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createMemoryTemporalBackfillImport: vi.fn(),
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createMemoryMaibotMigrationImport: vi.fn(),
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cancelMemoryImportTask: vi.fn(),
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retryMemoryImportTask: vi.fn(),
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resolveMemoryImportPath: vi.fn(),
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refreshMemoryRuntimeSelfCheck: vi.fn(),
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updateMemoryConfig: vi.fn(),
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updateMemoryConfigRaw: vi.fn(),
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createMemoryPasteImport: vi.fn(),
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getMemoryTuningProfile: vi.fn(),
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getMemoryTuningTasks: vi.fn(),
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createMemoryTuningTask: vi.fn(),
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applyBestMemoryTuningProfile: vi.fn(),
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getMemorySources: vi.fn(),
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getMemoryDeleteOperations: vi.fn(),
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getMemoryDeleteOperation: vi.fn(),
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previewMemoryDelete: vi.fn(),
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executeMemoryDelete: vi.fn(),
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restoreMemoryDelete: vi.fn(),
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}))
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describe('KnowledgeBasePage', () => {
|
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function mockImportTask(taskId: string, status: string = 'running'): memoryApi.MemoryImportTaskPayload {
|
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return {
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task_id: taskId,
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source: 'webui',
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status,
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current_step: status === 'completed' ? 'completed' : 'running',
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total_chunks: 120,
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done_chunks: status === 'completed' ? 120 : 36,
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failed_chunks: status === 'completed' ? 0 : 2,
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cancelled_chunks: 0,
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progress: status === 'completed' ? 100 : 30,
|
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error: '',
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||||
file_count: 2,
|
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created_at: 1_710_000_000,
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||||
started_at: 1_710_000_001,
|
||||
finished_at: status === 'completed' ? 1_710_000_099 : null,
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||||
updated_at: 1_710_000_100,
|
||||
task_kind: 'paste',
|
||||
params: {},
|
||||
files: [],
|
||||
}
|
||||
}
|
||||
|
||||
function mockImportDetail(taskId: string): memoryApi.MemoryImportTaskPayload {
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return {
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||||
...mockImportTask(taskId),
|
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files: [
|
||||
{
|
||||
file_id: 'file-alpha',
|
||||
name: 'alpha.txt',
|
||||
source_kind: 'paste',
|
||||
input_mode: 'text',
|
||||
status: 'running',
|
||||
current_step: 'running',
|
||||
detected_strategy_type: 'auto',
|
||||
total_chunks: 80,
|
||||
done_chunks: 30,
|
||||
failed_chunks: 1,
|
||||
cancelled_chunks: 0,
|
||||
progress: 37.5,
|
||||
error: '',
|
||||
created_at: 1_710_000_000,
|
||||
updated_at: 1_710_000_100,
|
||||
},
|
||||
{
|
||||
file_id: 'file-beta',
|
||||
name: 'beta.txt',
|
||||
source_kind: 'paste',
|
||||
input_mode: 'text',
|
||||
status: 'failed',
|
||||
current_step: 'extracting',
|
||||
detected_strategy_type: 'auto',
|
||||
total_chunks: 40,
|
||||
done_chunks: 6,
|
||||
failed_chunks: 4,
|
||||
cancelled_chunks: 0,
|
||||
progress: 25,
|
||||
error: 'mock error',
|
||||
created_at: 1_710_000_000,
|
||||
updated_at: 1_710_000_100,
|
||||
},
|
||||
],
|
||||
}
|
||||
}
|
||||
|
||||
describe('KnowledgeBasePage import workflow', () => {
|
||||
beforeEach(() => {
|
||||
navigateMock.mockReset()
|
||||
toastMock.mockReset()
|
||||
@@ -119,14 +210,113 @@ describe('KnowledgeBasePage', () => {
|
||||
paragraph_vector_backfill_failed: 1,
|
||||
paragraph_vector_backfill_done: 3,
|
||||
})
|
||||
|
||||
vi.mocked(memoryApi.getMemoryImportGuide).mockResolvedValue({
|
||||
success: true,
|
||||
content: '# 导入指南\n导入说明',
|
||||
})
|
||||
vi.mocked(memoryApi.getMemoryImportSettings).mockResolvedValue({
|
||||
success: true,
|
||||
settings: {
|
||||
max_paste_chars: 200_000,
|
||||
max_file_concurrency: 8,
|
||||
max_chunk_concurrency: 16,
|
||||
default_file_concurrency: 2,
|
||||
default_chunk_concurrency: 4,
|
||||
poll_interval_ms: 60_000,
|
||||
maibot_source_db_default: 'data/maibot.db',
|
||||
},
|
||||
})
|
||||
vi.mocked(memoryApi.getMemoryImportPathAliases).mockResolvedValue({
|
||||
success: true,
|
||||
path_aliases: {
|
||||
lpmm: 'data/lpmm',
|
||||
plugin_data: 'data/plugins/a-dawn.a-memorix',
|
||||
raw: 'data/raw',
|
||||
},
|
||||
})
|
||||
vi.mocked(memoryApi.getMemoryImportTasks).mockResolvedValue({
|
||||
success: true,
|
||||
items: [{ task_id: 'import-1', status: 'done', mode: 'text' }],
|
||||
items: [
|
||||
mockImportTask('import-run-1', 'running'),
|
||||
mockImportTask('import-queued-1', 'queued'),
|
||||
mockImportTask('import-done-1', 'completed'),
|
||||
],
|
||||
})
|
||||
vi.mocked(memoryApi.getMemoryImportTask).mockResolvedValue({
|
||||
success: true,
|
||||
task: mockImportDetail('import-run-1'),
|
||||
})
|
||||
vi.mocked(memoryApi.getMemoryImportTaskChunks).mockImplementation(async (_taskId, fileId, offset = 0) => ({
|
||||
success: true,
|
||||
task_id: 'import-run-1',
|
||||
file_id: fileId,
|
||||
offset,
|
||||
limit: 50,
|
||||
total: 120,
|
||||
items: [
|
||||
{
|
||||
chunk_id: `${fileId}-${offset + 0}`,
|
||||
index: offset + 0,
|
||||
chunk_type: 'text',
|
||||
status: 'running',
|
||||
step: 'extracting',
|
||||
failed_at: '',
|
||||
retryable: true,
|
||||
error: '',
|
||||
progress: 50,
|
||||
content_preview: `chunk-preview-${offset + 0}`,
|
||||
updated_at: 1_710_000_111,
|
||||
},
|
||||
],
|
||||
}))
|
||||
|
||||
vi.mocked(memoryApi.createMemoryUploadImport).mockResolvedValue({
|
||||
success: true,
|
||||
task: mockImportTask('upload-task-1', 'queued'),
|
||||
})
|
||||
vi.mocked(memoryApi.createMemoryPasteImport).mockResolvedValue({
|
||||
success: true,
|
||||
task: mockImportTask('paste-task-1', 'queued'),
|
||||
})
|
||||
vi.mocked(memoryApi.createMemoryRawScanImport).mockResolvedValue({
|
||||
success: true,
|
||||
task: mockImportTask('raw-task-1', 'queued'),
|
||||
})
|
||||
vi.mocked(memoryApi.createMemoryLpmmOpenieImport).mockResolvedValue({
|
||||
success: true,
|
||||
task: mockImportTask('openie-task-1', 'queued'),
|
||||
})
|
||||
vi.mocked(memoryApi.createMemoryLpmmConvertImport).mockResolvedValue({
|
||||
success: true,
|
||||
task: mockImportTask('convert-task-1', 'queued'),
|
||||
})
|
||||
vi.mocked(memoryApi.createMemoryTemporalBackfillImport).mockResolvedValue({
|
||||
success: true,
|
||||
task: mockImportTask('backfill-task-1', 'queued'),
|
||||
})
|
||||
vi.mocked(memoryApi.createMemoryMaibotMigrationImport).mockResolvedValue({
|
||||
success: true,
|
||||
task: mockImportTask('migration-task-1', 'queued'),
|
||||
})
|
||||
vi.mocked(memoryApi.cancelMemoryImportTask).mockResolvedValue({
|
||||
success: true,
|
||||
task: mockImportTask('import-run-1', 'cancel_requested'),
|
||||
})
|
||||
vi.mocked(memoryApi.retryMemoryImportTask).mockResolvedValue({
|
||||
success: true,
|
||||
task: mockImportTask('retry-task-1', 'queued'),
|
||||
})
|
||||
vi.mocked(memoryApi.resolveMemoryImportPath).mockResolvedValue({
|
||||
success: true,
|
||||
alias: 'raw',
|
||||
relative_path: 'exports',
|
||||
resolved_path: 'D:/Dev/rdev/MaiBot/data/raw/exports',
|
||||
exists: true,
|
||||
is_file: false,
|
||||
is_dir: true,
|
||||
})
|
||||
|
||||
vi.mocked(memoryApi.getMemoryTuningProfile).mockResolvedValue({
|
||||
success: true,
|
||||
profile: { retrieval: { top_k: 10 } },
|
||||
@@ -136,13 +326,13 @@ describe('KnowledgeBasePage', () => {
|
||||
success: true,
|
||||
items: [{ task_id: 'tune-1', status: 'done' }],
|
||||
})
|
||||
vi.mocked(memoryApi.createMemoryTuningTask).mockResolvedValue({ success: true } as never)
|
||||
vi.mocked(memoryApi.applyBestMemoryTuningProfile).mockResolvedValue({ success: true } as never)
|
||||
|
||||
vi.mocked(memoryApi.getMemorySources).mockResolvedValue({
|
||||
success: true,
|
||||
items: [
|
||||
{ source: 'demo-1', paragraph_count: 2, relation_count: 1 },
|
||||
{ source: 'demo-2', paragraph_count: 1, relation_count: 0 },
|
||||
],
|
||||
count: 2,
|
||||
items: [{ source: 'demo-1', paragraph_count: 2, relation_count: 1 }],
|
||||
count: 1,
|
||||
})
|
||||
vi.mocked(memoryApi.getMemoryDeleteOperations).mockResolvedValue({
|
||||
success: true,
|
||||
@@ -164,31 +354,9 @@ describe('KnowledgeBasePage', () => {
|
||||
status: 'executed',
|
||||
selector: { sources: ['demo-1'] },
|
||||
summary: { counts: { paragraphs: 2, relations: 1, sources: 1 }, sources: ['demo-1'] },
|
||||
items: [
|
||||
{
|
||||
item_type: 'paragraph',
|
||||
item_hash: 'p-1',
|
||||
item_key: 'paragraph:p-1',
|
||||
payload: { paragraph: { source: 'demo-1', content: '这是用于测试删除详情展示的段落内容。' } },
|
||||
},
|
||||
],
|
||||
items: [],
|
||||
},
|
||||
})
|
||||
vi.mocked(memoryApi.refreshMemoryRuntimeSelfCheck).mockResolvedValue({
|
||||
success: true,
|
||||
report: { ok: true },
|
||||
})
|
||||
vi.mocked(memoryApi.updateMemoryConfig).mockResolvedValue({
|
||||
success: true,
|
||||
config_path: 'config/a_memorix.toml',
|
||||
} as never)
|
||||
vi.mocked(memoryApi.updateMemoryConfigRaw).mockResolvedValue({
|
||||
success: true,
|
||||
config_path: 'config/a_memorix.toml',
|
||||
} as never)
|
||||
vi.mocked(memoryApi.createMemoryPasteImport).mockResolvedValue({ success: true } as never)
|
||||
vi.mocked(memoryApi.createMemoryTuningTask).mockResolvedValue({ success: true } as never)
|
||||
vi.mocked(memoryApi.applyBestMemoryTuningProfile).mockResolvedValue({ success: true } as never)
|
||||
vi.mocked(memoryApi.previewMemoryDelete).mockResolvedValue({
|
||||
success: true,
|
||||
mode: 'source',
|
||||
@@ -212,59 +380,243 @@ describe('KnowledgeBasePage', () => {
|
||||
deleted_source_count: 1,
|
||||
} as never)
|
||||
vi.mocked(memoryApi.restoreMemoryDelete).mockResolvedValue({ success: true } as never)
|
||||
vi.mocked(memoryApi.refreshMemoryRuntimeSelfCheck).mockResolvedValue({
|
||||
success: true,
|
||||
report: { ok: true },
|
||||
})
|
||||
vi.mocked(memoryApi.updateMemoryConfig).mockResolvedValue({ success: true } as never)
|
||||
vi.mocked(memoryApi.updateMemoryConfigRaw).mockResolvedValue({ success: true } as never)
|
||||
})
|
||||
|
||||
it('renders long-term memory console and key tabs', async () => {
|
||||
it('loads import settings/guide/tasks on first render', async () => {
|
||||
const user = userEvent.setup()
|
||||
|
||||
render(<KnowledgeBasePage />)
|
||||
|
||||
expect(await screen.findByText('长期记忆控制台')).toBeInTheDocument()
|
||||
expect(screen.getByText(/config\/a_memorix\.toml/)).toBeInTheDocument()
|
||||
expect(screen.getByText('运行就绪')).toBeInTheDocument()
|
||||
|
||||
await user.click(screen.getByRole('tab', { name: '配置' }))
|
||||
expect(await screen.findByTestId('memory-config-editor')).toBeInTheDocument()
|
||||
|
||||
expect(await screen.findByText('长期记忆控制台', undefined, { timeout: 10_000 })).toBeInTheDocument()
|
||||
await user.click(screen.getByRole('tab', { name: '导入' }))
|
||||
expect(await screen.findByText(/导入说明/)).toBeInTheDocument()
|
||||
expect(screen.getByText('import-1')).toBeInTheDocument()
|
||||
|
||||
expect(await screen.findByRole('button', { name: '创建导入任务' })).toBeInTheDocument()
|
||||
expect((await screen.findAllByText('import-run-1')).length).toBeGreaterThan(0)
|
||||
expect(memoryApi.getMemoryImportSettings).toHaveBeenCalled()
|
||||
expect(memoryApi.getMemoryImportPathAliases).toHaveBeenCalled()
|
||||
expect(memoryApi.getMemoryImportTasks).toHaveBeenCalled()
|
||||
})
|
||||
|
||||
it('creates import tasks for all 7 modes and calls correct endpoints', async () => {
|
||||
const user = userEvent.setup()
|
||||
const { container } = render(<KnowledgeBasePage />)
|
||||
|
||||
const openImportTab = async () => {
|
||||
await user.click(screen.getByRole('tab', { name: '导入' }))
|
||||
await screen.findByRole('button', { name: '创建导入任务' })
|
||||
}
|
||||
|
||||
await screen.findByText('长期记忆控制台', undefined, { timeout: 10_000 })
|
||||
await openImportTab()
|
||||
|
||||
const fileInput = container.querySelector('input[type="file"]') as HTMLInputElement
|
||||
const uploadFiles = [
|
||||
new File(['hello'], 'demo.txt', { type: 'text/plain' }),
|
||||
new File(['{"name":"mai"}'], 'demo.json', { type: 'application/json' }),
|
||||
new File(['a,b\n1,2'], 'demo.csv', { type: 'text/csv' }),
|
||||
new File(['# note'], 'demo.md', { type: 'text/markdown' }),
|
||||
]
|
||||
await user.upload(fileInput, uploadFiles)
|
||||
await user.click(screen.getByRole('button', { name: '创建导入任务' }))
|
||||
await waitFor(() => expect(memoryApi.createMemoryUploadImport).toHaveBeenCalledTimes(1))
|
||||
|
||||
await openImportTab()
|
||||
await user.click(screen.getByRole('tab', { name: '粘贴导入' }))
|
||||
const editableTextarea = Array.from(container.querySelectorAll('textarea')).find((item) => !item.readOnly)
|
||||
if (!editableTextarea) {
|
||||
throw new Error('missing editable textarea')
|
||||
}
|
||||
await user.type(editableTextarea, 'paste content')
|
||||
await user.click(screen.getByRole('button', { name: '创建导入任务' }))
|
||||
await waitFor(() => expect(memoryApi.createMemoryPasteImport).toHaveBeenCalledTimes(1))
|
||||
|
||||
await openImportTab()
|
||||
await user.click(screen.getByRole('tab', { name: '本地扫描' }))
|
||||
await user.click(screen.getByRole('button', { name: '创建导入任务' }))
|
||||
await waitFor(() => expect(memoryApi.createMemoryRawScanImport).toHaveBeenCalledTimes(1))
|
||||
|
||||
await openImportTab()
|
||||
await user.click(screen.getByRole('tab', { name: 'LPMM OpenIE' }))
|
||||
await user.click(screen.getByRole('button', { name: '创建导入任务' }))
|
||||
await waitFor(() => expect(memoryApi.createMemoryLpmmOpenieImport).toHaveBeenCalledTimes(1))
|
||||
|
||||
await openImportTab()
|
||||
await user.click(screen.getByRole('tab', { name: 'LPMM 转换' }))
|
||||
await user.click(screen.getByRole('button', { name: '创建导入任务' }))
|
||||
await waitFor(() => expect(memoryApi.createMemoryLpmmConvertImport).toHaveBeenCalledTimes(1))
|
||||
|
||||
await openImportTab()
|
||||
await user.click(screen.getByRole('tab', { name: '时序回填' }))
|
||||
await user.click(screen.getByRole('button', { name: '创建导入任务' }))
|
||||
await waitFor(() => expect(memoryApi.createMemoryTemporalBackfillImport).toHaveBeenCalledTimes(1))
|
||||
|
||||
await openImportTab()
|
||||
await user.click(screen.getByRole('tab', { name: 'MaiBot 迁移' }))
|
||||
await user.click(screen.getByRole('button', { name: '创建导入任务' }))
|
||||
await waitFor(() => expect(memoryApi.createMemoryMaibotMigrationImport).toHaveBeenCalledTimes(1))
|
||||
|
||||
const [uploadedFiles, uploadPayload] = vi.mocked(memoryApi.createMemoryUploadImport).mock.calls[0]
|
||||
expect(uploadedFiles).toHaveLength(4)
|
||||
expect(uploadedFiles.map((file) => file.name)).toEqual(['demo.txt', 'demo.json', 'demo.csv', 'demo.md'])
|
||||
expect(uploadPayload).toMatchObject({
|
||||
input_mode: 'text',
|
||||
llm_enabled: true,
|
||||
strategy_override: 'auto',
|
||||
dedupe_policy: 'content_hash',
|
||||
})
|
||||
}, 60_000)
|
||||
|
||||
it('loads task detail and supports chunk pagination', async () => {
|
||||
const user = userEvent.setup()
|
||||
render(<KnowledgeBasePage />)
|
||||
|
||||
await screen.findByText('长期记忆控制台', undefined, { timeout: 10_000 })
|
||||
await user.click(screen.getByRole('tab', { name: '导入' }))
|
||||
|
||||
expect(await screen.findByText('alpha.txt')).toBeInTheDocument()
|
||||
expect(await screen.findByText('chunk-preview-0')).toBeInTheDocument()
|
||||
|
||||
const betaButton = screen.getByText('beta.txt').closest('button')
|
||||
if (!betaButton) {
|
||||
throw new Error('missing file beta button')
|
||||
}
|
||||
await user.click(betaButton)
|
||||
await waitFor(() =>
|
||||
expect(memoryApi.getMemoryImportTaskChunks).toHaveBeenCalledWith('import-run-1', 'file-beta', 0, 50),
|
||||
)
|
||||
|
||||
await user.click(screen.getByRole('button', { name: '下一页分块' }))
|
||||
await waitFor(() =>
|
||||
expect(memoryApi.getMemoryImportTaskChunks).toHaveBeenCalledWith('import-run-1', 'file-beta', 50, 50),
|
||||
)
|
||||
}, 20_000)
|
||||
|
||||
it('supports cancel and retry actions for selected task', async () => {
|
||||
const user = userEvent.setup()
|
||||
render(<KnowledgeBasePage />)
|
||||
|
||||
await screen.findByText('长期记忆控制台', undefined, { timeout: 10_000 })
|
||||
await user.click(screen.getByRole('tab', { name: '导入' }))
|
||||
await screen.findByText('任务详情')
|
||||
|
||||
await user.click(screen.getByRole('button', { name: '取消选中导入任务' }))
|
||||
await waitFor(() => expect(memoryApi.cancelMemoryImportTask).toHaveBeenCalledWith('import-run-1'))
|
||||
|
||||
await user.click(screen.getByRole('button', { name: '重试选中导入任务' }))
|
||||
await waitFor(() => expect(memoryApi.retryMemoryImportTask).toHaveBeenCalled())
|
||||
const [taskId, retryPayload] = vi.mocked(memoryApi.retryMemoryImportTask).mock.calls[0]
|
||||
expect(taskId).toBe('import-run-1')
|
||||
expect(retryPayload).toMatchObject({
|
||||
overrides: {
|
||||
llm_enabled: true,
|
||||
strategy_override: 'auto',
|
||||
},
|
||||
})
|
||||
}, 20_000)
|
||||
|
||||
it('auto polling updates queue and keeps page stable when refresh fails once', async () => {
|
||||
vi.mocked(memoryApi.getMemoryImportSettings).mockResolvedValue({
|
||||
success: true,
|
||||
settings: {
|
||||
max_paste_chars: 200_000,
|
||||
max_file_concurrency: 8,
|
||||
max_chunk_concurrency: 16,
|
||||
default_file_concurrency: 2,
|
||||
default_chunk_concurrency: 4,
|
||||
poll_interval_ms: 200,
|
||||
maibot_source_db_default: 'data/maibot.db',
|
||||
},
|
||||
})
|
||||
const user = userEvent.setup()
|
||||
render(<KnowledgeBasePage />)
|
||||
|
||||
await screen.findByText('长期记忆控制台', undefined, { timeout: 10_000 })
|
||||
await user.click(screen.getByRole('tab', { name: '导入' }))
|
||||
await screen.findByText('导入队列')
|
||||
|
||||
const initialCalls = vi.mocked(memoryApi.getMemoryImportTasks).mock.calls.length
|
||||
vi.mocked(memoryApi.getMemoryImportTasks).mockRejectedValueOnce(new Error('poll failure'))
|
||||
await act(async () => {
|
||||
await new Promise((resolve) => setTimeout(resolve, 350))
|
||||
})
|
||||
|
||||
expect(screen.getByText('长期记忆控制台')).toBeInTheDocument()
|
||||
expect(vi.mocked(memoryApi.getMemoryImportTasks).mock.calls.length).toBeGreaterThan(initialCalls)
|
||||
}, 20_000)
|
||||
|
||||
it('creates tuning task and applies best profile (tuning module)', async () => {
|
||||
const user = userEvent.setup()
|
||||
render(<KnowledgeBasePage />)
|
||||
|
||||
await screen.findByText('长期记忆控制台', undefined, { timeout: 10_000 })
|
||||
await user.click(screen.getByRole('tab', { name: '调优' }))
|
||||
expect(await screen.findByText('tune-1')).toBeInTheDocument()
|
||||
expect(screen.getByRole('button', { name: '应用最佳' })).toBeInTheDocument()
|
||||
})
|
||||
await screen.findByText('调优任务')
|
||||
|
||||
it('shows delete tab and opens source delete preview', async () => {
|
||||
await user.click(screen.getByRole('button', { name: '创建调优任务' }))
|
||||
await waitFor(() =>
|
||||
expect(memoryApi.createMemoryTuningTask).toHaveBeenCalledWith({
|
||||
objective: 'precision_priority',
|
||||
intensity: 'standard',
|
||||
sample_size: 24,
|
||||
top_k_eval: 20,
|
||||
}),
|
||||
)
|
||||
|
||||
await user.click(screen.getByRole('button', { name: '应用最佳' }))
|
||||
await waitFor(() => expect(memoryApi.applyBestMemoryTuningProfile).toHaveBeenCalledWith('tune-1'))
|
||||
}, 20_000)
|
||||
|
||||
it('previews executes and restores source delete (delete module)', async () => {
|
||||
const user = userEvent.setup()
|
||||
|
||||
render(<KnowledgeBasePage />)
|
||||
|
||||
expect(await screen.findByText('长期记忆控制台')).toBeInTheDocument()
|
||||
await screen.findByText('长期记忆控制台', undefined, { timeout: 10_000 })
|
||||
await user.click(screen.getByRole('tab', { name: '删除' }))
|
||||
await screen.findByText('来源批量删除')
|
||||
|
||||
expect(await screen.findByText('来源批量删除')).toBeInTheDocument()
|
||||
expect(screen.getAllByText('demo-1').length).toBeGreaterThan(0)
|
||||
expect(screen.getAllByText('del-1').length).toBeGreaterThan(0)
|
||||
expect(screen.getByText('恢复这次删除')).toBeInTheDocument()
|
||||
const sourceCellCandidates = await screen.findAllByText('demo-1')
|
||||
const sourceRow = sourceCellCandidates
|
||||
.map((item) => item.closest('tr'))
|
||||
.find((row): row is HTMLTableRowElement => Boolean(row && within(row).queryByRole('checkbox')))
|
||||
if (!sourceRow) {
|
||||
throw new Error('missing source row')
|
||||
}
|
||||
await user.click(within(sourceRow).getByRole('checkbox'))
|
||||
|
||||
await user.click(screen.getAllByRole('checkbox')[0])
|
||||
await user.click(screen.getByRole('button', { name: '预览删除' }))
|
||||
await waitFor(() =>
|
||||
expect(memoryApi.previewMemoryDelete).toHaveBeenCalledWith({
|
||||
mode: 'source',
|
||||
selector: { sources: ['demo-1'] },
|
||||
reason: 'knowledge_base_source_delete',
|
||||
requested_by: 'knowledge_base',
|
||||
}),
|
||||
)
|
||||
|
||||
expect(await screen.findByTestId('memory-delete-dialog')).toHaveTextContent('delete:source:1')
|
||||
})
|
||||
const dialog = await screen.findByTestId('memory-delete-dialog')
|
||||
expect(dialog).toHaveTextContent('preview:source:1')
|
||||
|
||||
it('loads selected delete operation detail items from detail endpoint', async () => {
|
||||
const user = userEvent.setup()
|
||||
await user.click(screen.getByRole('button', { name: '执行删除' }))
|
||||
await waitFor(() =>
|
||||
expect(memoryApi.executeMemoryDelete).toHaveBeenCalledWith({
|
||||
mode: 'source',
|
||||
selector: { sources: ['demo-1'] },
|
||||
reason: 'knowledge_base_source_delete',
|
||||
requested_by: 'knowledge_base',
|
||||
}),
|
||||
)
|
||||
|
||||
render(<KnowledgeBasePage />)
|
||||
|
||||
expect(await screen.findByText('长期记忆控制台')).toBeInTheDocument()
|
||||
await user.click(screen.getByRole('tab', { name: '删除' }))
|
||||
|
||||
expect(await screen.findByText('删除操作恢复')).toBeInTheDocument()
|
||||
expect(await screen.findByText('paragraph')).toBeInTheDocument()
|
||||
expect(screen.getByText('p-1')).toBeInTheDocument()
|
||||
expect(screen.getByText('这是用于测试删除详情展示的段落内容。')).toBeInTheDocument()
|
||||
})
|
||||
await user.click(screen.getByRole('button', { name: '执行恢复' }))
|
||||
await waitFor(() =>
|
||||
expect(memoryApi.restoreMemoryDelete).toHaveBeenCalledWith({
|
||||
operation_id: 'del-2',
|
||||
requested_by: 'knowledge_base',
|
||||
}),
|
||||
)
|
||||
}, 20_000)
|
||||
})
|
||||
|
||||
@@ -107,6 +107,7 @@ vi.mock('../knowledge-graph/GraphDialogs', () => ({
|
||||
|
||||
vi.mock('@/lib/memory-api', () => ({
|
||||
getMemoryGraph: vi.fn(),
|
||||
getMemoryGraphSearch: vi.fn(),
|
||||
getMemoryGraphNodeDetail: vi.fn(),
|
||||
getMemoryGraphEdgeDetail: vi.fn(),
|
||||
previewMemoryDelete: vi.fn(),
|
||||
@@ -139,6 +140,13 @@ describe('KnowledgeGraphPage', () => {
|
||||
total_nodes: 2,
|
||||
total_edges: 1,
|
||||
})
|
||||
vi.mocked(memoryApi.getMemoryGraphSearch).mockResolvedValue({
|
||||
success: true,
|
||||
query: 'alpha',
|
||||
limit: 50,
|
||||
count: 0,
|
||||
items: [],
|
||||
})
|
||||
vi.mocked(memoryApi.getMemoryGraphNodeDetail).mockResolvedValue({
|
||||
success: true,
|
||||
node: { id: 'alpha', type: 'entity', content: 'Alpha', hash: 'entity-1', appearance_count: 3 },
|
||||
@@ -255,7 +263,7 @@ describe('KnowledgeGraphPage', () => {
|
||||
vi.mocked(memoryApi.restoreMemoryDelete).mockResolvedValue({ success: true } as never)
|
||||
})
|
||||
|
||||
it('renders graph summary and supports empty-result filtering', async () => {
|
||||
it('calls backend graph search and renders no-hit state', async () => {
|
||||
const user = userEvent.setup()
|
||||
|
||||
render(<KnowledgeGraphPage />)
|
||||
@@ -264,11 +272,102 @@ describe('KnowledgeGraphPage', () => {
|
||||
expect(screen.getByText(/总节点 2/)).toBeInTheDocument()
|
||||
expect(screen.getByTestId('graph-visualization')).toHaveTextContent('nodes:2,edges:1')
|
||||
|
||||
await user.type(screen.getByPlaceholderText('筛选实体名称、节点 ID 或边标签'), 'missing')
|
||||
await user.type(screen.getByPlaceholderText('搜索实体、关系、hash（后端全库）'), 'missing')
|
||||
expect(memoryApi.getMemoryGraph).toHaveBeenCalledTimes(1)
|
||||
await user.click(screen.getByRole('button', { name: '筛选' }))
|
||||
await user.click(screen.getByRole('button', { name: '搜索' }))
|
||||
|
||||
await waitFor(() => {
|
||||
expect(memoryApi.getMemoryGraphSearch).toHaveBeenCalledWith('missing', 50)
|
||||
})
|
||||
expect(await screen.findByText('未命中实体或关系。')).toBeInTheDocument()
|
||||
})
|
||||
|
||||
it('supports clicking entity search result to locate evidence', async () => {
|
||||
const user = userEvent.setup()
|
||||
vi.mocked(memoryApi.getMemoryGraphSearch).mockResolvedValue({
|
||||
success: true,
|
||||
query: 'alpha',
|
||||
limit: 50,
|
||||
count: 1,
|
||||
items: [
|
||||
{
|
||||
type: 'entity',
|
||||
title: 'Alpha',
|
||||
matched_field: 'name',
|
||||
matched_value: 'Alpha',
|
||||
entity_name: 'alpha',
|
||||
entity_hash: 'entity-1',
|
||||
appearance_count: 3,
|
||||
},
|
||||
],
|
||||
})
|
||||
|
||||
render(<KnowledgeGraphPage />)
|
||||
|
||||
await screen.findByTestId('graph-visualization')
|
||||
await user.type(screen.getByPlaceholderText('搜索实体、关系、hash（后端全库）'), 'alpha')
|
||||
await user.click(screen.getByRole('button', { name: '搜索' }))
|
||||
|
||||
await screen.findByText('搜索词：alpha')
|
||||
await user.click(screen.getByRole('button', { name: /Alpha/ }))
|
||||
|
||||
await waitFor(() => {
|
||||
expect(memoryApi.getMemoryGraphNodeDetail).toHaveBeenCalledWith('alpha')
|
||||
})
|
||||
expect(screen.getByRole('tab', { name: '证据视图' })).toHaveAttribute('data-state', 'active')
|
||||
})
|
||||
|
||||
it('supports clicking relation search result to locate evidence', async () => {
|
||||
const user = userEvent.setup()
|
||||
vi.mocked(memoryApi.getMemoryGraphSearch).mockResolvedValue({
|
||||
success: true,
|
||||
query: '关联',
|
||||
limit: 50,
|
||||
count: 1,
|
||||
items: [
|
||||
{
|
||||
type: 'relation',
|
||||
title: 'alpha 关联 beta',
|
||||
matched_field: 'predicate',
|
||||
matched_value: '关联',
|
||||
subject: 'alpha',
|
||||
predicate: '关联',
|
||||
object: 'beta',
|
||||
relation_hash: 'rel-1',
|
||||
confidence: 0.9,
|
||||
},
|
||||
],
|
||||
})
|
||||
|
||||
render(<KnowledgeGraphPage />)
|
||||
|
||||
await screen.findByTestId('graph-visualization')
|
||||
await user.type(screen.getByPlaceholderText('搜索实体、关系、hash（后端全库）'), '关联')
|
||||
await user.click(screen.getByRole('button', { name: '搜索' }))
|
||||
await user.click(screen.getByRole('button', { name: /alpha 关联 beta/ }))
|
||||
|
||||
await waitFor(() => {
|
||||
expect(memoryApi.getMemoryGraphEdgeDetail).toHaveBeenCalledWith('alpha', 'beta')
|
||||
})
|
||||
expect(screen.getByRole('tab', { name: '证据视图' })).toHaveAttribute('data-state', 'active')
|
||||
})
|
||||
|
||||
it('falls back to local filtering when backend search fails', async () => {
|
||||
const user = userEvent.setup()
|
||||
vi.mocked(memoryApi.getMemoryGraphSearch).mockRejectedValue(new Error('search unavailable'))
|
||||
|
||||
render(<KnowledgeGraphPage />)
|
||||
|
||||
await screen.findByTestId('graph-visualization')
|
||||
await user.type(screen.getByPlaceholderText('搜索实体、关系、hash（后端全库）'), 'missing')
|
||||
await user.click(screen.getByRole('button', { name: '搜索' }))
|
||||
|
||||
expect(await screen.findByText('还没有可展示的长期记忆图谱')).toBeInTheDocument()
|
||||
expect(toastMock).toHaveBeenCalledWith(
|
||||
expect.objectContaining({
|
||||
title: '后端检索失败，已回退本地筛选',
|
||||
}),
|
||||
)
|
||||
})
|
||||
|
||||
it('shows empty state when switching to evidence view without a selection', async () => {
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
@@ -22,6 +22,7 @@ import {
|
||||
getMemoryGraph,
|
||||
getMemoryGraphEdgeDetail,
|
||||
getMemoryGraphNodeDetail,
|
||||
getMemoryGraphSearch,
|
||||
previewMemoryDelete,
|
||||
restoreMemoryDelete,
|
||||
type MemoryDeleteExecutePayload,
|
||||
@@ -34,6 +35,7 @@ import {
|
||||
type MemoryGraphParagraphDetailPayload,
|
||||
type MemoryGraphPayload,
|
||||
type MemoryGraphRelationDetailPayload,
|
||||
type MemoryGraphSearchItem,
|
||||
} from '@/lib/memory-api'
|
||||
|
||||
import {
|
||||
@@ -211,6 +213,9 @@ export function KnowledgeGraphPage() {
|
||||
const [nodeLimit, setNodeLimit] = useState('120')
|
||||
const [searchInput, setSearchInput] = useState('')
|
||||
const [appliedSearchQuery, setAppliedSearchQuery] = useState('')
|
||||
const [searchLoading, setSearchLoading] = useState(false)
|
||||
const [searchResults, setSearchResults] = useState<MemoryGraphSearchItem[]>([])
|
||||
const [searchFallbackMode, setSearchFallbackMode] = useState(false)
|
||||
const [viewMode, setViewMode] = useState<GraphViewMode>('entity')
|
||||
const [fullGraph, setFullGraph] = useState<GraphData>({ nodes: [], edges: [] })
|
||||
const [graphData, setGraphData] = useState<GraphData>({ nodes: [], edges: [] })
|
||||
@@ -258,9 +263,12 @@ export function KnowledgeGraphPage() {
|
||||
setLoading(true)
|
||||
const payload = await getMemoryGraph(Number(nodeLimit))
|
||||
const nextGraph = toEntityGraphData(payload)
|
||||
const visibleGraph = searchFallbackMode && appliedSearchQuery
|
||||
? filterGraphData(nextGraph, appliedSearchQuery)
|
||||
: nextGraph
|
||||
setGraphMeta(payload)
|
||||
setFullGraph(nextGraph)
|
||||
setGraphData(filterGraphData(nextGraph, appliedSearchQuery))
|
||||
setGraphData(visibleGraph)
|
||||
setEvidenceGraph({ nodes: [], edges: [] })
|
||||
resetDetailSelections()
|
||||
if (!options?.silent) {
|
||||
@@ -278,21 +286,54 @@ export function KnowledgeGraphPage() {
|
||||
} finally {
|
||||
setLoading(false)
|
||||
}
|
||||
}, [appliedSearchQuery, nodeLimit, resetDetailSelections, toast])
|
||||
}, [appliedSearchQuery, nodeLimit, resetDetailSelections, searchFallbackMode, toast])
|
||||
|
||||
useEffect(() => {
|
||||
void loadGraph({ silent: true })
|
||||
}, [loadGraph])
|
||||
|
||||
const handleSearch = useCallback(() => {
|
||||
const handleSearch = useCallback(async () => {
|
||||
const nextQuery = searchInput.trim()
|
||||
if (!nextQuery) {
|
||||
setAppliedSearchQuery('')
|
||||
setSearchFallbackMode(false)
|
||||
setSearchResults([])
|
||||
setGraphData(fullGraph)
|
||||
toast({
|
||||
title: '已重置筛选',
|
||||
description: `当前显示 ${fullGraph.nodes.length} 个节点、${fullGraph.edges.length} 条关系`,
|
||||
})
|
||||
return
|
||||
}
|
||||
|
||||
setSearchLoading(true)
|
||||
setAppliedSearchQuery(nextQuery)
|
||||
const filtered = filterGraphData(fullGraph, nextQuery)
|
||||
setGraphData(filtered)
|
||||
toast({
|
||||
title: nextQuery ? '筛选完成' : '已重置筛选',
|
||||
description: `当前显示 ${filtered.nodes.length} 个节点、${filtered.edges.length} 条关系`,
|
||||
})
|
||||
try {
|
||||
const payload = await getMemoryGraphSearch(nextQuery, 50)
|
||||
if (!payload.success) {
|
||||
throw new Error(payload.error || '图谱检索失败')
|
||||
}
|
||||
const items = Array.isArray(payload.items) ? payload.items : []
|
||||
setSearchResults(items)
|
||||
setSearchFallbackMode(false)
|
||||
setGraphData(fullGraph)
|
||||
toast({
|
||||
title: '全库检索完成',
|
||||
description: `命中 ${payload.count ?? items.length} 条结果`,
|
||||
})
|
||||
} catch (error) {
|
||||
const filtered = filterGraphData(fullGraph, nextQuery)
|
||||
setSearchResults([])
|
||||
setSearchFallbackMode(true)
|
||||
setGraphData(filtered)
|
||||
toast({
|
||||
title: '后端检索失败，已回退本地筛选',
|
||||
description: `仅当前已加载范围（${filtered.nodes.length} 个节点、${filtered.edges.length} 条关系）`,
|
||||
variant: 'destructive',
|
||||
})
|
||||
} finally {
|
||||
setSearchLoading(false)
|
||||
}
|
||||
}, [fullGraph, searchInput, toast])
|
||||
|
||||
const stats = useMemo(
|
||||
@@ -397,21 +438,41 @@ export function KnowledgeGraphPage() {
|
||||
}
|
||||
}, [closeDeleteDialog, deleteResult?.operation_id, loadGraph, toast])
|
||||
|
||||
const handleNodeClick = useCallback(async (_: React.MouseEvent, node: Node) => {
|
||||
const selected = graphData.nodes.find((item) => item.id === node.id)
|
||||
setSelectedNodeData(selected ?? null)
|
||||
const openNodeDetail = useCallback(async (
|
||||
nodeId: string,
|
||||
options?: { locateInEvidence?: boolean },
|
||||
) => {
|
||||
const nodeToken = String(nodeId || '').trim()
|
||||
if (!nodeToken) {
|
||||
return
|
||||
}
|
||||
const selected = graphData.nodes.find((item) => item.id === nodeToken)
|
||||
if (options?.locateInEvidence) {
|
||||
setSelectedNodeData(null)
|
||||
} else {
|
||||
setSelectedNodeData(
|
||||
selected ?? {
|
||||
id: nodeToken,
|
||||
type: 'entity',
|
||||
content: nodeToken,
|
||||
metadata: {},
|
||||
},
|
||||
)
|
||||
}
|
||||
setSelectedEdgeData(null)
|
||||
setEdgeDetail(null)
|
||||
setSelectedRelationDetail(null)
|
||||
setSelectedRelationMetadata(null)
|
||||
setSelectedParagraphDetail(null)
|
||||
if (!selected) {
|
||||
return
|
||||
}
|
||||
setSelectedParagraphMetadata(null)
|
||||
try {
|
||||
setDetailLoading(true)
|
||||
const detail = await getMemoryGraphNodeDetail(selected.id)
|
||||
const detail = await getMemoryGraphNodeDetail(nodeToken)
|
||||
setNodeDetail(detail)
|
||||
setEvidenceGraph(toEvidenceGraphData(detail.evidence_graph))
|
||||
if (options?.locateInEvidence) {
|
||||
setViewMode('evidence')
|
||||
}
|
||||
} catch (error) {
|
||||
toast({
|
||||
title: '加载节点详情失败',
|
||||
@@ -423,27 +484,62 @@ export function KnowledgeGraphPage() {
|
||||
}
|
||||
}, [graphData.nodes, toast])
|
||||
|
||||
const handleEdgeClick = useCallback(async (_: React.MouseEvent, edge: Edge) => {
|
||||
const sourceNode = graphData.nodes.find((nodeItem) => nodeItem.id === edge.source)
|
||||
const targetNode = graphData.nodes.find((nodeItem) => nodeItem.id === edge.target)
|
||||
const edgeData = graphData.edges.find((item) => item.source === edge.source && item.target === edge.target)
|
||||
if (!sourceNode || !targetNode || !edgeData) {
|
||||
const openEdgeDetail = useCallback(async (
|
||||
source: string,
|
||||
target: string,
|
||||
options?: { locateInEvidence?: boolean },
|
||||
) => {
|
||||
const sourceToken = String(source || '').trim()
|
||||
const targetToken = String(target || '').trim()
|
||||
if (!sourceToken || !targetToken) {
|
||||
return
|
||||
}
|
||||
setSelectedNodeData(null)
|
||||
setNodeDetail(null)
|
||||
setSelectedRelationDetail(null)
|
||||
setSelectedRelationMetadata(null)
|
||||
setSelectedParagraphDetail(null)
|
||||
setSelectedEdgeData({
|
||||
source: sourceNode,
|
||||
target: targetNode,
|
||||
edge: edgeData,
|
||||
})
|
||||
setSelectedParagraphMetadata(null)
|
||||
if (options?.locateInEvidence) {
|
||||
setSelectedEdgeData(null)
|
||||
} else {
|
||||
const sourceNode = graphData.nodes.find((nodeItem) => nodeItem.id === sourceToken) ?? {
|
||||
id: sourceToken,
|
||||
type: 'entity' as const,
|
||||
content: sourceToken,
|
||||
metadata: {},
|
||||
}
|
||||
const targetNode = graphData.nodes.find((nodeItem) => nodeItem.id === targetToken) ?? {
|
||||
id: targetToken,
|
||||
type: 'entity' as const,
|
||||
content: targetToken,
|
||||
metadata: {},
|
||||
}
|
||||
const edgeData = graphData.edges.find((item) => item.source === sourceToken && item.target === targetToken) ?? {
|
||||
source: sourceToken,
|
||||
target: targetToken,
|
||||
weight: 1,
|
||||
kind: 'relation' as const,
|
||||
label: '',
|
||||
relationHashes: [],
|
||||
predicates: [],
|
||||
relationCount: 0,
|
||||
evidenceCount: 0,
|
||||
}
|
||||
setSelectedEdgeData({
|
||||
source: sourceNode,
|
||||
target: targetNode,
|
||||
edge: edgeData,
|
||||
})
|
||||
}
|
||||
try {
|
||||
setDetailLoading(true)
|
||||
const detail = await getMemoryGraphEdgeDetail(edge.source, edge.target)
|
||||
const detail = await getMemoryGraphEdgeDetail(sourceToken, targetToken)
|
||||
setEdgeDetail(detail)
|
||||
setEvidenceGraph(toEvidenceGraphData(detail.evidence_graph))
|
||||
if (options?.locateInEvidence) {
|
||||
setViewMode('evidence')
|
||||
}
|
||||
} catch (error) {
|
||||
toast({
|
||||
title: '加载关系详情失败',
|
||||
@@ -455,6 +551,36 @@ export function KnowledgeGraphPage() {
|
||||
}
|
||||
}, [graphData.edges, graphData.nodes, toast])
|
||||
|
||||
const handleNodeClick = useCallback((_: React.MouseEvent, node: Node) => {
|
||||
void openNodeDetail(node.id)
|
||||
}, [openNodeDetail])
|
||||
|
||||
const handleEdgeClick = useCallback((_: React.MouseEvent, edge: Edge) => {
|
||||
void openEdgeDetail(edge.source, edge.target)
|
||||
}, [openEdgeDetail])
|
||||
|
||||
const handleSearchResultClick = useCallback((item: MemoryGraphSearchItem) => {
|
||||
if (item.type === 'entity') {
|
||||
const entityName = String(item.entity_name ?? item.title ?? '').trim()
|
||||
if (!entityName) {
|
||||
return
|
||||
}
|
||||
void openNodeDetail(entityName, { locateInEvidence: true })
|
||||
return
|
||||
}
|
||||
const source = String(item.subject ?? '').trim()
|
||||
const target = String(item.object ?? '').trim()
|
||||
if (!source || !target) {
|
||||
toast({
|
||||
title: '结果缺少定位信息',
|
||||
description: '该关系记录没有可用的 subject/object，无法定位。',
|
||||
variant: 'destructive',
|
||||
})
|
||||
return
|
||||
}
|
||||
void openEdgeDetail(source, target, { locateInEvidence: true })
|
||||
}, [openEdgeDetail, openNodeDetail, toast])
|
||||
|
||||
const handleEvidenceNodeClick = useCallback(async (_: React.MouseEvent, node: Node) => {
|
||||
const selected = evidenceGraph.nodes.find((item) => item.id === node.id)
|
||||
if (!selected) {
|
||||
@@ -640,12 +766,12 @@ export function KnowledgeGraphPage() {
|
||||
<Input
|
||||
value={searchInput}
|
||||
onChange={(event) => setSearchInput(event.target.value)}
|
||||
onKeyDown={(event) => event.key === 'Enter' && handleSearch()}
|
||||
placeholder="筛选实体名称、节点 ID 或边标签"
|
||||
onKeyDown={(event) => event.key === 'Enter' && void handleSearch()}
|
||||
placeholder="搜索实体、关系、hash（后端全库）"
|
||||
/>
|
||||
<Button onClick={handleSearch} variant="secondary">
|
||||
<Button onClick={() => void handleSearch()} variant="secondary" disabled={searchLoading}>
|
||||
<Search className="mr-2 h-4 w-4" />
|
||||
筛选
|
||||
{searchLoading ? '检索中' : '搜索'}
|
||||
</Button>
|
||||
</div>
|
||||
|
||||
@@ -678,6 +804,48 @@ export function KnowledgeGraphPage() {
|
||||
<TabsTrigger value="evidence">证据视图</TabsTrigger>
|
||||
</TabsList>
|
||||
</Tabs>
|
||||
|
||||
{appliedSearchQuery ? (
|
||||
<div className="rounded-lg border bg-background/80 p-3">
|
||||
<div className="flex flex-wrap items-center justify-between gap-2">
|
||||
<div className="text-sm font-medium">
|
||||
搜索词：{appliedSearchQuery}
|
||||
</div>
|
||||
<Badge variant={searchFallbackMode ? 'destructive' : 'secondary'}>
|
||||
{searchFallbackMode ? '仅当前已加载范围' : `全库命中 ${searchResults.length} 条`}
|
||||
</Badge>
|
||||
</div>
|
||||
{searchFallbackMode ? (
|
||||
<p className="mt-2 text-sm text-muted-foreground">
|
||||
后端检索不可用，当前结果来自已加载图谱范围。请先刷新图谱或稍后重试。
|
||||
</p>
|
||||
) : searchResults.length <= 0 ? (
|
||||
<p className="mt-2 text-sm text-muted-foreground">未命中实体或关系。</p>
|
||||
) : (
|
||||
<div className="mt-3 max-h-56 space-y-2 overflow-auto pr-1">
|
||||
{searchResults.map((item, index) => (
|
||||
<button
|
||||
key={`${item.type}-${item.entity_hash ?? item.relation_hash ?? `${item.title}-${index}`}`}
|
||||
type="button"
|
||||
className="w-full rounded-md border bg-card px-3 py-2 text-left transition hover:bg-accent/40"
|
||||
onClick={() => handleSearchResultClick(item)}
|
||||
>
|
||||
<div className="flex items-center gap-2">
|
||||
<Badge variant="outline">{item.type === 'entity' ? '实体' : '关系'}</Badge>
|
||||
<span className="truncate text-sm font-medium">{item.title || '(无标题结果)'}</span>
|
||||
</div>
|
||||
<p className="mt-1 text-xs text-muted-foreground">
|
||||
命中字段：{item.matched_field} = {item.matched_value}
|
||||
{item.type === 'entity'
|
||||
? ` · appearance=${item.appearance_count ?? 0}`
|
||||
: ` · confidence=${Number(item.confidence ?? 0).toFixed(2)}`}
|
||||
</p>
|
||||
</button>
|
||||
))}
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
) : null}
|
||||
</div>
|
||||
</div>
|
||||
|
||||
|
||||
113
pytests/A_memorix_test/test_memory_graph_search_kernel.py
Normal file
113
pytests/A_memorix_test/test_memory_graph_search_kernel.py
Normal file
@@ -0,0 +1,113 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from pathlib import Path
|
||||
from typing import Any
|
||||
|
||||
import pytest
|
||||
|
||||
from src.A_memorix.core.runtime.sdk_memory_kernel import SDKMemoryKernel
|
||||
|
||||
|
||||
class _DummyMetadataStore:
|
||||
def __init__(self, *, entities: list[dict[str, Any]], relations: list[dict[str, Any]]) -> None:
|
||||
self._entities = entities
|
||||
self._relations = relations
|
||||
|
||||
def query(self, sql: str, params: tuple[Any, ...] = ()) -> list[dict[str, Any]]:
|
||||
sql_token = " ".join(str(sql or "").lower().split())
|
||||
keyword = str(params[0] or "").strip("%").lower() if params else ""
|
||||
if "from entities" in sql_token:
|
||||
rows = [dict(item) for item in self._entities if not bool(item.get("is_deleted", 0))]
|
||||
if not keyword:
|
||||
return rows
|
||||
return [
|
||||
row
|
||||
for row in rows
|
||||
if keyword in str(row.get("name", "") or "").lower()
|
||||
or keyword in str(row.get("hash", "") or "").lower()
|
||||
]
|
||||
if "from relations" in sql_token:
|
||||
rows = [dict(item) for item in self._relations if not bool(item.get("is_inactive", 0))]
|
||||
if not keyword:
|
||||
return rows
|
||||
return [
|
||||
row
|
||||
for row in rows
|
||||
if keyword in str(row.get("subject", "") or "").lower()
|
||||
or keyword in str(row.get("object", "") or "").lower()
|
||||
or keyword in str(row.get("predicate", "") or "").lower()
|
||||
or keyword in str(row.get("hash", "") or "").lower()
|
||||
]
|
||||
raise AssertionError(f"unexpected query: {sql_token}")
|
||||
|
||||
|
||||
def _build_kernel(*, entities: list[dict[str, Any]], relations: list[dict[str, Any]]) -> SDKMemoryKernel:
|
||||
kernel = SDKMemoryKernel(plugin_root=Path.cwd(), config={})
|
||||
|
||||
async def _fake_initialize() -> None:
|
||||
return None
|
||||
|
||||
kernel.initialize = _fake_initialize # type: ignore[method-assign]
|
||||
kernel.metadata_store = _DummyMetadataStore(entities=entities, relations=relations)
|
||||
kernel.graph_store = object() # type: ignore[assignment]
|
||||
return kernel
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_memory_graph_admin_search_orders_and_dedupes_results() -> None:
|
||||
kernel = _build_kernel(
|
||||
entities=[
|
||||
{"hash": "e1", "name": "Alice", "appearance_count": 5, "is_deleted": 0},
|
||||
{"hash": "e1", "name": "Alice Duplicate", "appearance_count": 99, "is_deleted": 0},
|
||||
{"hash": "e2", "name": "Alice Cooper", "appearance_count": 7, "is_deleted": 0},
|
||||
{"hash": "e3", "name": "my alice note", "appearance_count": 11, "is_deleted": 0},
|
||||
{"hash": "e4", "name": "alice deleted", "appearance_count": 100, "is_deleted": 1},
|
||||
],
|
||||
relations=[
|
||||
{"hash": "r1", "subject": "Alice", "predicate": "knows", "object": "Bob", "confidence": 0.6, "created_at": 100, "is_inactive": 0},
|
||||
{"hash": "r3", "subject": "Alice", "predicate": "supports", "object": "Carol", "confidence": 0.9, "created_at": 90, "is_inactive": 0},
|
||||
{"hash": "r1", "subject": "Alice", "predicate": "knows duplicate", "object": "Bob", "confidence": 0.99, "created_at": 200, "is_inactive": 0},
|
||||
{"hash": "r2", "subject": "Alice Cooper", "predicate": "likes", "object": "Tea", "confidence": 0.2, "created_at": 50, "is_inactive": 0},
|
||||
{"hash": "", "subject": "Carol", "predicate": "mentions alice", "object": "Topic", "confidence": 0.8, "created_at": 70, "is_inactive": 0},
|
||||
{"hash": "", "subject": "Carol", "predicate": "mentions alice", "object": "Topic", "confidence": 0.3, "created_at": 10, "is_inactive": 0},
|
||||
{"hash": "r4", "subject": "alice inactive", "predicate": "old", "object": "Data", "confidence": 1.0, "created_at": 300, "is_inactive": 1},
|
||||
],
|
||||
)
|
||||
|
||||
payload = await kernel.memory_graph_admin(action="search", query="alice", limit=20)
|
||||
|
||||
assert payload["success"] is True
|
||||
assert payload["count"] == len(payload["items"])
|
||||
entity_items = [item for item in payload["items"] if item["type"] == "entity"]
|
||||
relation_items = [item for item in payload["items"] if item["type"] == "relation"]
|
||||
|
||||
assert [item["entity_hash"] for item in entity_items] == ["e1", "e2", "e3"]
|
||||
assert [item["relation_hash"] for item in relation_items] == ["r3", "r1", "r2", ""]
|
||||
assert relation_items[0]["confidence"] == pytest.approx(0.9)
|
||||
assert relation_items[1]["confidence"] == pytest.approx(0.6)
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_memory_graph_admin_search_filters_deleted_and_inactive_records() -> None:
|
||||
kernel = _build_kernel(
|
||||
entities=[
|
||||
{"hash": "e-deleted", "name": "Ghost Alice", "appearance_count": 10, "is_deleted": 1},
|
||||
],
|
||||
relations=[
|
||||
{
|
||||
"hash": "r-inactive",
|
||||
"subject": "Ghost Alice",
|
||||
"predicate": "linked",
|
||||
"object": "Ghost Bob",
|
||||
"confidence": 0.9,
|
||||
"created_at": 10,
|
||||
"is_inactive": 1,
|
||||
},
|
||||
],
|
||||
)
|
||||
|
||||
payload = await kernel.memory_graph_admin(action="search", query="ghost", limit=50)
|
||||
|
||||
assert payload["success"] is True
|
||||
assert payload["items"] == []
|
||||
assert payload["count"] == 0
|
||||
@@ -52,6 +52,54 @@ def test_webui_memory_graph_route(client: TestClient, monkeypatch):
|
||||
assert response.json()["edges"][0]["evidence_count"] == 2
|
||||
|
||||
|
||||
def test_webui_memory_graph_search_route(client: TestClient, monkeypatch):
|
||||
async def fake_graph_admin(*, action: str, **kwargs):
|
||||
assert action == "search"
|
||||
assert kwargs["query"] == "Alice"
|
||||
assert kwargs["limit"] == 33
|
||||
return {
|
||||
"success": True,
|
||||
"query": kwargs["query"],
|
||||
"limit": kwargs["limit"],
|
||||
"count": 1,
|
||||
"items": [
|
||||
{
|
||||
"type": "entity",
|
||||
"title": "Alice",
|
||||
"matched_field": "name",
|
||||
"matched_value": "Alice",
|
||||
"entity_name": "Alice",
|
||||
"entity_hash": "entity-1",
|
||||
"appearance_count": 3,
|
||||
}
|
||||
],
|
||||
}
|
||||
|
||||
monkeypatch.setattr(memory_router_module.memory_service, "graph_admin", fake_graph_admin)
|
||||
|
||||
response = client.get("/api/webui/memory/graph/search", params={"query": "Alice", "limit": 33})
|
||||
|
||||
assert response.status_code == 200
|
||||
assert response.json()["success"] is True
|
||||
assert response.json()["query"] == "Alice"
|
||||
assert response.json()["limit"] == 33
|
||||
assert response.json()["items"][0]["type"] == "entity"
|
||||
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
"params",
|
||||
[
|
||||
{"query": "", "limit": 50},
|
||||
{"query": "Alice", "limit": 0},
|
||||
{"query": "Alice", "limit": 201},
|
||||
],
|
||||
)
|
||||
def test_webui_memory_graph_search_route_validation(client: TestClient, params):
|
||||
response = client.get("/api/webui/memory/graph/search", params=params)
|
||||
|
||||
assert response.status_code == 422
|
||||
|
||||
|
||||
def test_webui_memory_graph_node_detail_route(client: TestClient, monkeypatch):
|
||||
async def fake_graph_admin(*, action: str, **kwargs):
|
||||
assert action == "node_detail"
|
||||
@@ -200,28 +248,59 @@ def test_memory_config_routes(client: TestClient, monkeypatch):
|
||||
"get_raw_config",
|
||||
lambda: "[plugin]\nenabled = true\n",
|
||||
)
|
||||
monkeypatch.setattr(
|
||||
memory_router_module.a_memorix_host_service,
|
||||
"get_raw_config_with_meta",
|
||||
lambda: {
|
||||
"config": "[plugin]\nenabled = true\n",
|
||||
"exists": True,
|
||||
"using_default": False,
|
||||
},
|
||||
)
|
||||
|
||||
schema_response = client.get("/api/webui/memory/config/schema")
|
||||
config_response = client.get("/api/webui/memory/config")
|
||||
raw_response = client.get("/api/webui/memory/config/raw")
|
||||
expected_path = memory_router_module.Path("/tmp/config/a_memorix.toml").as_posix()
|
||||
|
||||
assert schema_response.status_code == 200
|
||||
assert schema_response.json()["path"] == "/tmp/config/a_memorix.toml"
|
||||
assert memory_router_module.Path(schema_response.json()["path"]).as_posix() == expected_path
|
||||
assert schema_response.json()["schema"]["layout"]["type"] == "tabs"
|
||||
|
||||
assert config_response.status_code == 200
|
||||
assert config_response.json() == {
|
||||
"success": True,
|
||||
"config": {"plugin": {"enabled": True}},
|
||||
"path": "/tmp/config/a_memorix.toml",
|
||||
}
|
||||
assert config_response.json()["success"] is True
|
||||
assert config_response.json()["config"] == {"plugin": {"enabled": True}}
|
||||
assert memory_router_module.Path(config_response.json()["path"]).as_posix() == expected_path
|
||||
|
||||
assert raw_response.status_code == 200
|
||||
assert raw_response.json() == {
|
||||
"success": True,
|
||||
"config": "[plugin]\nenabled = true\n",
|
||||
"path": "/tmp/config/a_memorix.toml",
|
||||
}
|
||||
assert raw_response.json()["success"] is True
|
||||
assert raw_response.json()["config"] == "[plugin]\nenabled = true\n"
|
||||
assert memory_router_module.Path(raw_response.json()["path"]).as_posix() == expected_path
|
||||
|
||||
|
||||
def test_memory_config_raw_returns_default_template_when_file_missing(client: TestClient, monkeypatch):
|
||||
monkeypatch.setattr(
|
||||
memory_router_module.a_memorix_host_service,
|
||||
"get_config_path",
|
||||
lambda: memory_router_module.Path("/tmp/config/a_memorix.toml"),
|
||||
)
|
||||
monkeypatch.setattr(
|
||||
memory_router_module.a_memorix_host_service,
|
||||
"get_raw_config_with_meta",
|
||||
lambda: {
|
||||
"config": "[plugin]\nenabled = true\n",
|
||||
"exists": False,
|
||||
"using_default": True,
|
||||
},
|
||||
)
|
||||
|
||||
response = client.get("/api/webui/memory/config/raw")
|
||||
|
||||
assert response.status_code == 200
|
||||
assert response.json()["success"] is True
|
||||
assert response.json()["config"] == "[plugin]\nenabled = true\n"
|
||||
assert response.json()["exists"] is False
|
||||
assert response.json()["using_default"] is True
|
||||
|
||||
|
||||
def test_memory_config_update_routes(client: TestClient, monkeypatch):
|
||||
|
||||
499
pytests/webui/test_memory_routes_integration.py
Normal file
499
pytests/webui/test_memory_routes_integration.py
Normal file
@@ -0,0 +1,499 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from pathlib import Path
|
||||
from time import monotonic, sleep
|
||||
from typing import Any, Dict, Generator
|
||||
from uuid import uuid4
|
||||
|
||||
import asyncio
|
||||
import json
|
||||
|
||||
from fastapi import FastAPI
|
||||
from fastapi.testclient import TestClient
|
||||
import pytest
|
||||
import tomlkit
|
||||
|
||||
from src.A_memorix import host_service as host_service_module
|
||||
from src.A_memorix.core.utils import retrieval_tuning_manager as tuning_manager_module
|
||||
from src.webui.dependencies import require_auth
|
||||
from src.webui.routers import memory as memory_router_module
|
||||
|
||||
|
||||
REQUEST_TIMEOUT_SECONDS = 30
|
||||
IMPORT_TIMEOUT_SECONDS = 120
|
||||
TUNING_TIMEOUT_SECONDS = 420
|
||||
|
||||
IMPORT_TERMINAL_STATUSES = {"completed", "completed_with_errors", "failed", "cancelled"}
|
||||
TUNING_TERMINAL_STATUSES = {"completed", "failed", "cancelled"}
|
||||
|
||||
|
||||
def _build_test_config(data_dir: Path) -> Dict[str, Any]:
|
||||
return {
|
||||
"storage": {
|
||||
"data_dir": str(data_dir),
|
||||
},
|
||||
"advanced": {
|
||||
"enable_auto_save": False,
|
||||
},
|
||||
"embedding": {
|
||||
"dimension": 64,
|
||||
"batch_size": 4,
|
||||
"max_concurrent": 1,
|
||||
"retry": {
|
||||
"max_attempts": 1,
|
||||
"min_wait_seconds": 0.1,
|
||||
"max_wait_seconds": 0.2,
|
||||
"backoff_multiplier": 1.0,
|
||||
},
|
||||
"fallback": {
|
||||
"enabled": True,
|
||||
"allow_metadata_only_write": True,
|
||||
"probe_interval_seconds": 30,
|
||||
},
|
||||
"paragraph_vector_backfill": {
|
||||
"enabled": False,
|
||||
"interval_seconds": 60,
|
||||
"batch_size": 32,
|
||||
"max_retry": 2,
|
||||
},
|
||||
},
|
||||
"retrieval": {
|
||||
"enable_parallel": False,
|
||||
"enable_ppr": False,
|
||||
"top_k_paragraphs": 20,
|
||||
"top_k_relations": 10,
|
||||
"top_k_final": 10,
|
||||
"alpha": 0.5,
|
||||
"search": {
|
||||
"smart_fallback": {
|
||||
"enabled": True,
|
||||
},
|
||||
},
|
||||
"sparse": {
|
||||
"enabled": True,
|
||||
"mode": "auto",
|
||||
"candidate_k": 80,
|
||||
"relation_candidate_k": 60,
|
||||
},
|
||||
"fusion": {
|
||||
"method": "weighted_rrf",
|
||||
"rrf_k": 60,
|
||||
"vector_weight": 0.7,
|
||||
"bm25_weight": 0.3,
|
||||
},
|
||||
},
|
||||
"threshold": {
|
||||
"percentile": 70.0,
|
||||
"min_results": 1,
|
||||
},
|
||||
"web": {
|
||||
"tuning": {
|
||||
"enabled": True,
|
||||
"poll_interval_ms": 300,
|
||||
"max_queue_size": 4,
|
||||
"default_objective": "balanced",
|
||||
"default_intensity": "quick",
|
||||
"default_sample_size": 4,
|
||||
"default_top_k_eval": 5,
|
||||
"eval_query_timeout_seconds": 1.0,
|
||||
"llm_retry": {
|
||||
"max_attempts": 1,
|
||||
"min_wait_seconds": 0.1,
|
||||
"max_wait_seconds": 0.2,
|
||||
"backoff_multiplier": 1.0,
|
||||
},
|
||||
},
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
def _assert_response_ok(response: Any) -> Dict[str, Any]:
|
||||
assert response.status_code == 200, response.text
|
||||
payload = response.json()
|
||||
assert payload.get("success", True) is True, payload
|
||||
return payload
|
||||
|
||||
|
||||
def _wait_for_import_task_terminal(client: TestClient, task_id: str, *, timeout_seconds: float = IMPORT_TIMEOUT_SECONDS) -> Dict[str, Any]:
|
||||
deadline = monotonic() + timeout_seconds
|
||||
last_payload: Dict[str, Any] = {}
|
||||
while monotonic() < deadline:
|
||||
response = client.get(
|
||||
f"/api/webui/memory/import/tasks/{task_id}",
|
||||
params={"include_chunks": True},
|
||||
)
|
||||
payload = _assert_response_ok(response)
|
||||
last_payload = payload
|
||||
task = payload.get("task") or {}
|
||||
status = str(task.get("status", "") or "")
|
||||
if status in IMPORT_TERMINAL_STATUSES:
|
||||
return task
|
||||
sleep(0.2)
|
||||
raise AssertionError(f"导入任务超时: task_id={task_id}, last_payload={last_payload}")
|
||||
|
||||
|
||||
def _wait_for_tuning_task_terminal(client: TestClient, task_id: str, *, timeout_seconds: float = TUNING_TIMEOUT_SECONDS) -> Dict[str, Any]:
|
||||
deadline = monotonic() + timeout_seconds
|
||||
last_payload: Dict[str, Any] = {}
|
||||
while monotonic() < deadline:
|
||||
response = client.get(
|
||||
f"/api/webui/memory/retrieval_tuning/tasks/{task_id}",
|
||||
params={"include_rounds": False},
|
||||
)
|
||||
payload = _assert_response_ok(response)
|
||||
last_payload = payload
|
||||
task = payload.get("task") or {}
|
||||
status = str(task.get("status", "") or "")
|
||||
if status in TUNING_TERMINAL_STATUSES:
|
||||
return task
|
||||
sleep(0.3)
|
||||
raise AssertionError(f"调优任务超时: task_id={task_id}, last_payload={last_payload}")
|
||||
|
||||
|
||||
def _wait_for_query_hit(client: TestClient, query: str, *, timeout_seconds: float = 30.0) -> Dict[str, Any]:
|
||||
deadline = monotonic() + timeout_seconds
|
||||
last_payload: Dict[str, Any] = {}
|
||||
while monotonic() < deadline:
|
||||
payload = _assert_response_ok(
|
||||
client.get(
|
||||
"/api/webui/memory/query/aggregate",
|
||||
params={"query": query, "limit": 20},
|
||||
)
|
||||
)
|
||||
last_payload = payload
|
||||
hits = payload.get("hits") or []
|
||||
if isinstance(hits, list) and len(hits) > 0:
|
||||
return payload
|
||||
sleep(0.2)
|
||||
raise AssertionError(f"检索命中超时: query={query}, last_payload={last_payload}")
|
||||
|
||||
|
||||
def _get_source_item(client: TestClient, source_name: str) -> Dict[str, Any] | None:
|
||||
payload = _assert_response_ok(client.get("/api/webui/memory/sources"))
|
||||
items = payload.get("items") or []
|
||||
for item in items:
|
||||
if not isinstance(item, dict):
|
||||
continue
|
||||
if str(item.get("source", "") or "") == source_name:
|
||||
return item
|
||||
return None
|
||||
|
||||
|
||||
def _source_paragraph_count(item: Dict[str, Any] | None) -> int:
|
||||
payload = item or {}
|
||||
if "paragraph_count" in payload:
|
||||
return int(payload.get("paragraph_count", 0) or 0)
|
||||
return int(payload.get("count", 0) or 0)
|
||||
|
||||
|
||||
def _wait_for_source_paragraph_count(
|
||||
client: TestClient,
|
||||
source_name: str,
|
||||
*,
|
||||
min_count: int,
|
||||
timeout_seconds: float = 30.0,
|
||||
) -> Dict[str, Any]:
|
||||
deadline = monotonic() + timeout_seconds
|
||||
last_item: Dict[str, Any] = {}
|
||||
while monotonic() < deadline:
|
||||
item = _get_source_item(client, source_name)
|
||||
count = _source_paragraph_count(item)
|
||||
if count >= int(min_count):
|
||||
return item or {}
|
||||
if item:
|
||||
last_item = dict(item)
|
||||
sleep(0.2)
|
||||
raise AssertionError(
|
||||
f"等待来源段落计数超时: source={source_name}, min_count={min_count}, last_item={last_item}"
|
||||
)
|
||||
|
||||
|
||||
def _create_multitype_upload_task(client: TestClient) -> str:
|
||||
structured_json = {
|
||||
"paragraphs": [
|
||||
{
|
||||
"content": "Alice 携带地图前往火星港。",
|
||||
"source": "integration-upload-json",
|
||||
"entities": ["Alice", "地图", "火星港"],
|
||||
"relations": [
|
||||
{"subject": "Alice", "predicate": "携带", "object": "地图"},
|
||||
{"subject": "Alice", "predicate": "前往", "object": "火星港"},
|
||||
],
|
||||
}
|
||||
]
|
||||
}
|
||||
extra_json = {
|
||||
"paragraphs": [
|
||||
{
|
||||
"content": "Carol 记录了一条补充说明。",
|
||||
"source": "integration-upload-json-extra",
|
||||
"entities": ["Carol"],
|
||||
"relations": [],
|
||||
}
|
||||
]
|
||||
}
|
||||
payload_json = json.dumps(
|
||||
{
|
||||
"input_mode": "text",
|
||||
"llm_enabled": False,
|
||||
"file_concurrency": 2,
|
||||
"chunk_concurrency": 2,
|
||||
"dedupe_policy": "none",
|
||||
},
|
||||
ensure_ascii=False,
|
||||
)
|
||||
files = [
|
||||
("files", ("integration-notes.txt", "Alice 在测试环境记录了一条长期记忆。".encode("utf-8"), "text/plain")),
|
||||
("files", ("integration-diary.md", "# 日志\nBob 与 Alice 讨论了导图。".encode("utf-8"), "text/markdown")),
|
||||
("files", ("integration-structured.json", json.dumps(structured_json, ensure_ascii=False).encode("utf-8"), "application/json")),
|
||||
("files", ("integration-extra.json", json.dumps(extra_json, ensure_ascii=False).encode("utf-8"), "application/json")),
|
||||
]
|
||||
|
||||
response = client.post(
|
||||
"/api/webui/memory/import/upload",
|
||||
data={"payload_json": payload_json},
|
||||
files=files,
|
||||
)
|
||||
payload = _assert_response_ok(response)
|
||||
task_id = str((payload.get("task") or {}).get("task_id") or "").strip()
|
||||
assert task_id, payload
|
||||
return task_id
|
||||
|
||||
|
||||
def _create_seed_paste_task(client: TestClient, *, source: str, unique_token: str) -> str:
|
||||
seed_payload = {
|
||||
"paragraphs": [
|
||||
{
|
||||
"content": f"Alice 在火星港携带地图并记录了口令 {unique_token}。",
|
||||
"source": source,
|
||||
"entities": ["Alice", "火星港", "地图"],
|
||||
"relations": [
|
||||
{"subject": "Alice", "predicate": "前往", "object": "火星港"},
|
||||
{"subject": "Alice", "predicate": "携带", "object": "地图"},
|
||||
],
|
||||
},
|
||||
{
|
||||
"content": f"Bob 在火星港遇见 Alice，并重复口令 {unique_token}。",
|
||||
"source": source,
|
||||
"entities": ["Bob", "Alice", "火星港"],
|
||||
"relations": [
|
||||
{"subject": "Bob", "predicate": "遇见", "object": "Alice"},
|
||||
{"subject": "Bob", "predicate": "位于", "object": "火星港"},
|
||||
],
|
||||
},
|
||||
]
|
||||
}
|
||||
response = client.post(
|
||||
"/api/webui/memory/import/paste",
|
||||
json={
|
||||
"name": "integration-seed.json",
|
||||
"input_mode": "json",
|
||||
"llm_enabled": False,
|
||||
"content": json.dumps(seed_payload, ensure_ascii=False),
|
||||
"dedupe_policy": "none",
|
||||
},
|
||||
)
|
||||
payload = _assert_response_ok(response)
|
||||
task_id = str((payload.get("task") or {}).get("task_id") or "").strip()
|
||||
assert task_id, payload
|
||||
return task_id
|
||||
|
||||
|
||||
@pytest.fixture(scope="module")
|
||||
def integration_state(tmp_path_factory: pytest.TempPathFactory) -> Generator[Dict[str, Any], None, None]:
|
||||
tmp_root = tmp_path_factory.mktemp("memory_routes_integration")
|
||||
data_dir = (tmp_root / "data").resolve()
|
||||
staging_dir = (tmp_root / "upload_staging").resolve()
|
||||
artifacts_dir = (tmp_root / "artifacts").resolve()
|
||||
config_file = (tmp_root / "config" / "a_memorix.toml").resolve()
|
||||
|
||||
config_file.parent.mkdir(parents=True, exist_ok=True)
|
||||
config_file.write_text(tomlkit.dumps(_build_test_config(data_dir)), encoding="utf-8")
|
||||
|
||||
patches = pytest.MonkeyPatch()
|
||||
patches.setattr(host_service_module, "config_path", lambda: config_file)
|
||||
patches.setattr(memory_router_module, "STAGING_ROOT", staging_dir)
|
||||
patches.setattr(tuning_manager_module, "artifacts_root", lambda: artifacts_dir)
|
||||
|
||||
asyncio.run(host_service_module.a_memorix_host_service.stop())
|
||||
host_service_module.a_memorix_host_service._config_cache = None # type: ignore[attr-defined]
|
||||
|
||||
app = FastAPI()
|
||||
app.dependency_overrides[require_auth] = lambda: "ok"
|
||||
app.include_router(memory_router_module.router, prefix="/api/webui")
|
||||
app.include_router(memory_router_module.compat_router)
|
||||
|
||||
unique_token = f"INTEG_TOKEN_{uuid4().hex[:12]}"
|
||||
source_name = f"integration-source-{uuid4().hex[:8]}"
|
||||
|
||||
with TestClient(app) as client:
|
||||
upload_task_id = _create_multitype_upload_task(client)
|
||||
upload_task = _wait_for_import_task_terminal(client, upload_task_id)
|
||||
|
||||
seed_task_id = _create_seed_paste_task(client, source=source_name, unique_token=unique_token)
|
||||
seed_task = _wait_for_import_task_terminal(client, seed_task_id)
|
||||
assert str(seed_task.get("status", "") or "") in {"completed", "completed_with_errors"}, seed_task
|
||||
|
||||
_wait_for_query_hit(client, unique_token, timeout_seconds=45.0)
|
||||
|
||||
yield {
|
||||
"client": client,
|
||||
"upload_task": upload_task,
|
||||
"seed_task": seed_task,
|
||||
"source_name": source_name,
|
||||
"unique_token": unique_token,
|
||||
}
|
||||
|
||||
asyncio.run(host_service_module.a_memorix_host_service.stop())
|
||||
host_service_module.a_memorix_host_service._config_cache = None # type: ignore[attr-defined]
|
||||
patches.undo()
|
||||
|
||||
|
||||
def test_import_module_end_to_end_supports_multitype_upload(integration_state: Dict[str, Any]) -> None:
|
||||
upload_task = integration_state["upload_task"]
|
||||
|
||||
assert str(upload_task.get("status", "") or "") in {"completed", "completed_with_errors"}, upload_task
|
||||
files = upload_task.get("files") or []
|
||||
assert isinstance(files, list)
|
||||
assert len(files) >= 4
|
||||
|
||||
file_names = {str(item.get("name", "") or "") for item in files if isinstance(item, dict)}
|
||||
assert "integration-notes.txt" in file_names
|
||||
assert "integration-diary.md" in file_names
|
||||
assert "integration-structured.json" in file_names
|
||||
assert "integration-extra.json" in file_names
|
||||
|
||||
|
||||
def test_retrieval_module_end_to_end_queries_seeded_data(integration_state: Dict[str, Any]) -> None:
|
||||
client = integration_state["client"]
|
||||
unique_token = integration_state["unique_token"]
|
||||
|
||||
aggregate_payload = _wait_for_query_hit(client, unique_token, timeout_seconds=45.0)
|
||||
hits = aggregate_payload.get("hits") or []
|
||||
joined_content = "\n".join(str(item.get("content", "") or "") for item in hits if isinstance(item, dict))
|
||||
assert unique_token in joined_content
|
||||
|
||||
graph_payload = _assert_response_ok(
|
||||
client.get(
|
||||
"/api/webui/memory/graph/search",
|
||||
params={"query": "Alice", "limit": 20},
|
||||
)
|
||||
)
|
||||
graph_items = graph_payload.get("items") or []
|
||||
assert isinstance(graph_items, list)
|
||||
assert any(str(item.get("type", "") or "") == "entity" for item in graph_items if isinstance(item, dict)), graph_items
|
||||
|
||||
|
||||
def test_tuning_module_end_to_end_create_and_apply_best(integration_state: Dict[str, Any]) -> None:
|
||||
client = integration_state["client"]
|
||||
|
||||
create_payload = _assert_response_ok(
|
||||
client.post(
|
||||
"/api/webui/memory/retrieval_tuning/tasks",
|
||||
json={
|
||||
"objective": "balanced",
|
||||
"intensity": "quick",
|
||||
"rounds": 2,
|
||||
"sample_size": 4,
|
||||
"top_k_eval": 5,
|
||||
"llm_enabled": False,
|
||||
"eval_query_timeout_seconds": 1.0,
|
||||
"seed": 20260403,
|
||||
},
|
||||
)
|
||||
)
|
||||
task_id = str((create_payload.get("task") or {}).get("task_id") or "").strip()
|
||||
assert task_id, create_payload
|
||||
|
||||
task = _wait_for_tuning_task_terminal(client, task_id)
|
||||
assert str(task.get("status", "") or "") == "completed", task
|
||||
|
||||
apply_payload = _assert_response_ok(
|
||||
client.post(
|
||||
f"/api/webui/memory/retrieval_tuning/tasks/{task_id}/apply-best",
|
||||
)
|
||||
)
|
||||
assert "applied" in apply_payload
|
||||
|
||||
|
||||
def test_delete_module_end_to_end_preview_execute_restore(integration_state: Dict[str, Any]) -> None:
|
||||
client = integration_state["client"]
|
||||
unique_token = integration_state["unique_token"]
|
||||
source_name = integration_state["source_name"]
|
||||
|
||||
before_source_item = _wait_for_source_paragraph_count(client, source_name, min_count=1, timeout_seconds=45.0)
|
||||
assert _source_paragraph_count(before_source_item) >= 1
|
||||
|
||||
preview_payload = _assert_response_ok(
|
||||
client.post(
|
||||
"/api/webui/memory/delete/preview",
|
||||
json={
|
||||
"mode": "source",
|
||||
"selector": {"sources": [source_name]},
|
||||
"reason": "integration_delete_preview",
|
||||
"requested_by": "pytest_integration",
|
||||
},
|
||||
)
|
||||
)
|
||||
preview_counts = preview_payload.get("counts") or {}
|
||||
assert int(preview_counts.get("paragraphs", 0) or 0) >= 1, preview_payload
|
||||
|
||||
execute_payload = _assert_response_ok(
|
||||
client.post(
|
||||
"/api/webui/memory/delete/execute",
|
||||
json={
|
||||
"mode": "source",
|
||||
"selector": {"sources": [source_name]},
|
||||
"reason": "integration_delete_execute",
|
||||
"requested_by": "pytest_integration",
|
||||
},
|
||||
)
|
||||
)
|
||||
operation_id = str(execute_payload.get("operation_id", "") or "").strip()
|
||||
assert operation_id, execute_payload
|
||||
|
||||
after_delete_payload = _assert_response_ok(
|
||||
client.get(
|
||||
"/api/webui/memory/query/aggregate",
|
||||
params={"query": unique_token, "limit": 20},
|
||||
)
|
||||
)
|
||||
after_delete_hits = after_delete_payload.get("hits") or []
|
||||
after_delete_text = "\n".join(
|
||||
str(item.get("content", "") or "")
|
||||
for item in after_delete_hits
|
||||
if isinstance(item, dict)
|
||||
)
|
||||
assert unique_token not in after_delete_text
|
||||
assert int(execute_payload.get("deleted_paragraph_count", 0) or 0) >= 1, execute_payload
|
||||
|
||||
_assert_response_ok(
|
||||
client.post(
|
||||
"/api/webui/memory/delete/restore",
|
||||
json={
|
||||
"operation_id": operation_id,
|
||||
"requested_by": "pytest_integration",
|
||||
},
|
||||
)
|
||||
)
|
||||
|
||||
restored_source_item = _wait_for_source_paragraph_count(client, source_name, min_count=1, timeout_seconds=45.0)
|
||||
assert _source_paragraph_count(restored_source_item) >= 1
|
||||
|
||||
operations_payload = _assert_response_ok(
|
||||
client.get(
|
||||
"/api/webui/memory/delete/operations",
|
||||
params={"limit": 20, "mode": "source"},
|
||||
)
|
||||
)
|
||||
operation_items = operations_payload.get("items") or []
|
||||
operation_ids = {
|
||||
str(item.get("operation_id", "") or "")
|
||||
for item in operation_items
|
||||
if isinstance(item, dict)
|
||||
}
|
||||
assert operation_id in operation_ids
|
||||
|
||||
operation_detail_payload = _assert_response_ok(client.get(f"/api/webui/memory/delete/operations/{operation_id}"))
|
||||
detail_operation = operation_detail_payload.get("operation") or {}
|
||||
assert str(detail_operation.get("status", "") or "") == "restored"
|
||||
@@ -98,7 +98,7 @@
|
||||
"data_dir": {
|
||||
"name": "data_dir",
|
||||
"type": "string",
|
||||
"default": "data/plugins/a-dawn.a-memorix",
|
||||
"default": "data/a-memorix",
|
||||
"description": "数据目录",
|
||||
"label": "数据目录",
|
||||
"ui_type": "text",
|
||||
@@ -107,7 +107,7 @@
|
||||
"disabled": false,
|
||||
"order": 1,
|
||||
"hint": "相对路径按 MaiBot 仓库根目录解析，建议保持默认外置目录。",
|
||||
"placeholder": "data/plugins/a-dawn.a-memorix",
|
||||
"placeholder": "data/a-memorix",
|
||||
"choices": null
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1317,6 +1317,11 @@ class SDKMemoryKernel:
|
||||
act = str(action or "").strip().lower()
|
||||
if act == "get_graph":
|
||||
return {"success": True, **self._serialize_graph(limit=max(1, int(kwargs.get("limit", 200) or 200)))}
|
||||
if act == "search":
|
||||
return self._search_graph(
|
||||
query=str(kwargs.get("query", "") or "").strip(),
|
||||
limit=max(1, min(200, int(kwargs.get("limit", 50) or 50))),
|
||||
)
|
||||
if act == "node_detail":
|
||||
detail = self._build_graph_node_detail(
|
||||
node_id=str(kwargs.get("node_id", "") or kwargs.get("node", "") or "").strip(),
|
||||
@@ -2275,6 +2280,179 @@ class SDKMemoryKernel:
|
||||
"total_edges": int(self.graph_store.num_edges),
|
||||
}
|
||||
|
||||
@staticmethod
|
||||
def _graph_search_match_rank(value: str, keyword: str) -> Optional[int]:
|
||||
token = str(value or "").strip().lower()
|
||||
if not token or not keyword:
|
||||
return None
|
||||
if token == keyword:
|
||||
return 0
|
||||
if token.startswith(keyword):
|
||||
return 1
|
||||
if keyword in token:
|
||||
return 2
|
||||
return None
|
||||
|
||||
@classmethod
|
||||
def _pick_graph_search_match(
|
||||
cls,
|
||||
fields: Sequence[tuple[str, str]],
|
||||
keyword: str,
|
||||
) -> Optional[tuple[str, str, int]]:
|
||||
best_match: Optional[tuple[str, str, int]] = None
|
||||
for field, raw_value in fields:
|
||||
value = str(raw_value or "").strip()
|
||||
if not value:
|
||||
continue
|
||||
rank = cls._graph_search_match_rank(value, keyword)
|
||||
if rank is None:
|
||||
continue
|
||||
if best_match is None or rank < best_match[2]:
|
||||
best_match = (field, value, rank)
|
||||
return best_match
|
||||
|
||||
def _search_graph(self, *, query: str, limit: int) -> Dict[str, Any]:
|
||||
assert self.metadata_store is not None
|
||||
token = str(query or "").strip()
|
||||
normalized_query = token.lower()
|
||||
safe_limit = max(1, int(limit or 50))
|
||||
if not token:
|
||||
return {
|
||||
"success": False,
|
||||
"query": token,
|
||||
"limit": safe_limit,
|
||||
"count": 0,
|
||||
"items": [],
|
||||
"error": "query 不能为空",
|
||||
}
|
||||
|
||||
like_keyword = f"%{normalized_query}%"
|
||||
entity_rows = self.metadata_store.query(
|
||||
"""
|
||||
SELECT hash, name, appearance_count, created_at
|
||||
FROM entities
|
||||
WHERE (is_deleted IS NULL OR is_deleted = 0)
|
||||
AND (
|
||||
LOWER(COALESCE(name, '')) LIKE ?
|
||||
OR LOWER(COALESCE(hash, '')) LIKE ?
|
||||
)
|
||||
""",
|
||||
(like_keyword, like_keyword),
|
||||
)
|
||||
|
||||
relation_rows = self.metadata_store.query(
|
||||
"""
|
||||
SELECT hash, subject, predicate, object, confidence, created_at
|
||||
FROM relations
|
||||
WHERE (is_inactive IS NULL OR is_inactive = 0)
|
||||
AND (
|
||||
LOWER(COALESCE(subject, '')) LIKE ?
|
||||
OR LOWER(COALESCE(object, '')) LIKE ?
|
||||
OR LOWER(COALESCE(predicate, '')) LIKE ?
|
||||
OR LOWER(COALESCE(hash, '')) LIKE ?
|
||||
)
|
||||
""",
|
||||
(like_keyword, like_keyword, like_keyword, like_keyword),
|
||||
)
|
||||
|
||||
entity_items: List[Dict[str, Any]] = []
|
||||
seen_entity_keys: set[str] = set()
|
||||
for row in entity_rows:
|
||||
name = str(row.get("name", "") or "").strip()
|
||||
hash_value = str(row.get("hash", "") or "").strip()
|
||||
match = self._pick_graph_search_match(
|
||||
[("name", name), ("hash", hash_value)],
|
||||
normalized_query,
|
||||
)
|
||||
if match is None:
|
||||
continue
|
||||
dedupe_key = hash_value or f"name:{name.lower()}"
|
||||
if dedupe_key in seen_entity_keys:
|
||||
continue
|
||||
seen_entity_keys.add(dedupe_key)
|
||||
matched_field, matched_value, rank = match
|
||||
entity_items.append(
|
||||
{
|
||||
"type": "entity",
|
||||
"title": name or hash_value,
|
||||
"matched_field": matched_field,
|
||||
"matched_value": matched_value,
|
||||
"entity_name": name or hash_value,
|
||||
"entity_hash": hash_value,
|
||||
"appearance_count": int(row.get("appearance_count", 0) or 0),
|
||||
"_rank": rank,
|
||||
}
|
||||
)
|
||||
|
||||
relation_items: List[Dict[str, Any]] = []
|
||||
seen_relation_keys: set[str] = set()
|
||||
for row in relation_rows:
|
||||
subject = str(row.get("subject", "") or "").strip()
|
||||
predicate = str(row.get("predicate", "") or "").strip()
|
||||
obj = str(row.get("object", "") or "").strip()
|
||||
relation_hash = str(row.get("hash", "") or "").strip()
|
||||
match = self._pick_graph_search_match(
|
||||
[
|
||||
("subject", subject),
|
||||
("object", obj),
|
||||
("predicate", predicate),
|
||||
("hash", relation_hash),
|
||||
],
|
||||
normalized_query,
|
||||
)
|
||||
if match is None:
|
||||
continue
|
||||
dedupe_key = relation_hash or f"{subject.lower()}|{predicate.lower()}|{obj.lower()}"
|
||||
if dedupe_key in seen_relation_keys:
|
||||
continue
|
||||
seen_relation_keys.add(dedupe_key)
|
||||
matched_field, matched_value, rank = match
|
||||
relation_items.append(
|
||||
{
|
||||
"type": "relation",
|
||||
"title": self._format_relation_text(subject, predicate, obj),
|
||||
"matched_field": matched_field,
|
||||
"matched_value": matched_value,
|
||||
"subject": subject,
|
||||
"predicate": predicate,
|
||||
"object": obj,
|
||||
"relation_hash": relation_hash,
|
||||
"confidence": float(row.get("confidence", 0.0) or 0.0),
|
||||
"created_at": float(row.get("created_at", 0.0) or 0.0),
|
||||
"_rank": rank,
|
||||
}
|
||||
)
|
||||
|
||||
items = entity_items + relation_items
|
||||
items.sort(
|
||||
key=lambda item: (
|
||||
int(item["_rank"]) if item.get("_rank") is not None else 99,
|
||||
0 if str(item.get("type", "") or "") == "entity" else 1,
|
||||
-int(item.get("appearance_count", 0) or 0)
|
||||
if str(item.get("type", "") or "") == "entity"
|
||||
else -float(item.get("confidence", 0.0) or 0.0),
|
||||
0.0 if str(item.get("type", "") or "") == "entity" else -float(item.get("created_at", 0.0) or 0.0),
|
||||
str(item.get("entity_name", item.get("subject", "")) or "").lower(),
|
||||
str(item.get("predicate", "") or "").lower(),
|
||||
str(item.get("object", "") or "").lower(),
|
||||
str(item.get("entity_hash", item.get("relation_hash", "")) or "").lower(),
|
||||
)
|
||||
)
|
||||
|
||||
normalized_items: List[Dict[str, Any]] = []
|
||||
for item in items[:safe_limit]:
|
||||
normalized = dict(item)
|
||||
normalized.pop("_rank", None)
|
||||
normalized_items.append(normalized)
|
||||
|
||||
return {
|
||||
"success": True,
|
||||
"query": token,
|
||||
"limit": safe_limit,
|
||||
"count": len(normalized_items),
|
||||
"items": normalized_items,
|
||||
}
|
||||
|
||||
@staticmethod
|
||||
def _dedupe_strings(values: Iterable[Any]) -> List[str]:
|
||||
deduped: List[str] = []
|
||||
|
||||
@@ -277,6 +277,7 @@ class EpisodeSegmentationService:
|
||||
model_config, model_label = self._resolve_model_config()
|
||||
if model_config is None:
|
||||
raise RuntimeError("episode segmentation model unavailable")
|
||||
task_name = llm_api.resolve_task_name_from_model_config(model_config, preferred_task_name=model_label)
|
||||
|
||||
prompt = self._build_prompt(
|
||||
source=source,
|
||||
@@ -284,11 +285,17 @@ class EpisodeSegmentationService:
|
||||
window_end=window_end,
|
||||
paragraphs=paragraphs,
|
||||
)
|
||||
success, response, _, _ = await llm_api.generate_with_model(
|
||||
prompt=prompt,
|
||||
model_config=model_config,
|
||||
request_type="A_Memorix.EpisodeSegmentation",
|
||||
result = await llm_api.generate(
|
||||
llm_api.LLMServiceRequest(
|
||||
task_name=task_name,
|
||||
request_type="A_Memorix.EpisodeSegmentation",
|
||||
prompt=prompt,
|
||||
temperature=getattr(model_config, "temperature", None),
|
||||
max_tokens=getattr(model_config, "max_tokens", None),
|
||||
)
|
||||
)
|
||||
success = bool(result.success)
|
||||
response = str(result.completion.response or "")
|
||||
if not success or not response:
|
||||
raise RuntimeError("llm_generate_failed")
|
||||
|
||||
|
||||
@@ -1306,6 +1306,7 @@ class RetrievalTuningManager:
|
||||
model_cfg = await self._select_llm_model()
|
||||
if model_cfg is None:
|
||||
raise RuntimeError("no_llm_model")
|
||||
task_name = llm_api.resolve_task_name_from_model_config(model_cfg)
|
||||
|
||||
retry = self._llm_retry_cfg()
|
||||
max_attempts = int(retry["max_attempts"])
|
||||
@@ -1316,11 +1317,17 @@ class RetrievalTuningManager:
|
||||
last_error: Optional[Exception] = None
|
||||
for idx in range(max_attempts):
|
||||
try:
|
||||
success, response, _, _ = await llm_api.generate_with_model(
|
||||
prompt=prompt,
|
||||
model_config=model_cfg,
|
||||
request_type=request_type,
|
||||
result = await llm_api.generate(
|
||||
llm_api.LLMServiceRequest(
|
||||
task_name=task_name,
|
||||
request_type=request_type,
|
||||
prompt=prompt,
|
||||
temperature=getattr(model_cfg, "temperature", None),
|
||||
max_tokens=getattr(model_cfg, "max_tokens", None),
|
||||
)
|
||||
)
|
||||
success = bool(result.success)
|
||||
response = str(result.completion.response or "")
|
||||
if not success:
|
||||
raise RuntimeError("llm_generation_failed")
|
||||
text = str(response or "").strip()
|
||||
|
||||
@@ -280,15 +280,22 @@ class SummaryImporter:
|
||||
model_config_to_use = self._resolve_summary_model_config()
|
||||
if model_config_to_use is None:
|
||||
return False, "未找到可用的总结模型配置"
|
||||
task_name_to_use = llm_api.resolve_task_name_from_model_config(model_config_to_use)
|
||||
|
||||
logger.info(f"正在为流 {stream_id} 执行总结，消息条数: {len(messages)}")
|
||||
logger.info(f"总结模型候选列表: {model_config_to_use.model_list}")
|
||||
|
||||
success, response, _, _ = await llm_api.generate_with_model(
|
||||
prompt=prompt,
|
||||
model_config=model_config_to_use,
|
||||
request_type="A_Memorix.ChatSummarization"
|
||||
result = await llm_api.generate(
|
||||
llm_api.LLMServiceRequest(
|
||||
task_name=task_name_to_use,
|
||||
request_type="A_Memorix.ChatSummarization",
|
||||
prompt=prompt,
|
||||
temperature=getattr(model_config_to_use, "temperature", None),
|
||||
max_tokens=getattr(model_config_to_use, "max_tokens", None),
|
||||
)
|
||||
)
|
||||
success = bool(result.success)
|
||||
response = str(result.completion.response or "")
|
||||
|
||||
if not success or not response:
|
||||
return False, "LLM 生成总结失败"
|
||||
|
||||
@@ -3165,14 +3165,21 @@ class ImportTaskManager:
|
||||
async def _llm_call(self, prompt: str, model_config: Any) -> Dict[str, Any]:
|
||||
cfg = self._llm_retry_config()
|
||||
retries = int(cfg["retries"])
|
||||
task_name = llm_api.resolve_task_name_from_model_config(model_config)
|
||||
last_error: Optional[Exception] = None
|
||||
for attempt in range(retries + 1):
|
||||
try:
|
||||
success, response, _, _ = await llm_api.generate_with_model(
|
||||
prompt=prompt,
|
||||
model_config=model_config,
|
||||
request_type="A_Memorix.WebImport",
|
||||
result = await llm_api.generate(
|
||||
llm_api.LLMServiceRequest(
|
||||
task_name=task_name,
|
||||
request_type="A_Memorix.WebImport",
|
||||
prompt=prompt,
|
||||
temperature=getattr(model_config, "temperature", None),
|
||||
max_tokens=getattr(model_config, "max_tokens", None),
|
||||
)
|
||||
)
|
||||
success = bool(result.success)
|
||||
response = str(result.completion.response or "")
|
||||
if not success or not response:
|
||||
raise RuntimeError("LLM 生成失败")
|
||||
|
||||
|
||||
@@ -88,11 +88,59 @@ class AMemorixHostService:
|
||||
def get_config(self) -> Dict[str, Any]:
|
||||
return dict(self._read_config())
|
||||
|
||||
def get_raw_config(self) -> str:
|
||||
def _build_default_config(self) -> Dict[str, Any]:
|
||||
schema = self.get_config_schema()
|
||||
sections = schema.get("sections") if isinstance(schema, dict) else None
|
||||
if not isinstance(sections, dict):
|
||||
return {}
|
||||
|
||||
defaults: Dict[str, Any] = {}
|
||||
for section_name, section_payload in sections.items():
|
||||
if not isinstance(section_payload, dict):
|
||||
continue
|
||||
fields = section_payload.get("fields")
|
||||
if not isinstance(fields, dict):
|
||||
continue
|
||||
|
||||
section_parts = [part for part in str(section_name or "").split(".") if part]
|
||||
if not section_parts:
|
||||
continue
|
||||
|
||||
section_target: Dict[str, Any] = defaults
|
||||
for part in section_parts:
|
||||
nested = section_target.get(part)
|
||||
if not isinstance(nested, dict):
|
||||
nested = {}
|
||||
section_target[part] = nested
|
||||
section_target = nested
|
||||
|
||||
for field_name, field_payload in fields.items():
|
||||
if not isinstance(field_payload, dict) or "default" not in field_payload:
|
||||
continue
|
||||
section_target[str(field_name)] = _to_builtin_data(field_payload.get("default"))
|
||||
|
||||
return defaults
|
||||
|
||||
def get_raw_config_with_meta(self) -> Dict[str, Any]:
|
||||
path = self.get_config_path()
|
||||
if not path.exists():
|
||||
return ""
|
||||
return path.read_text(encoding="utf-8")
|
||||
if path.exists():
|
||||
return {
|
||||
"config": path.read_text(encoding="utf-8"),
|
||||
"exists": True,
|
||||
"using_default": False,
|
||||
}
|
||||
|
||||
default_config = self._build_default_config()
|
||||
default_raw = tomlkit.dumps(default_config) if default_config else ""
|
||||
return {
|
||||
"config": default_raw,
|
||||
"exists": False,
|
||||
"using_default": True,
|
||||
}
|
||||
|
||||
def get_raw_config(self) -> str:
|
||||
payload = self.get_raw_config_with_meta()
|
||||
return str(payload.get("config", "") or "")
|
||||
|
||||
async def update_raw_config(self, raw_config: str) -> Dict[str, Any]:
|
||||
tomlkit.loads(raw_config)
|
||||
@@ -231,16 +279,18 @@ class AMemorixHostService:
|
||||
|
||||
path = self.get_config_path()
|
||||
if not path.exists():
|
||||
self._config_cache = {}
|
||||
return {}
|
||||
defaults = self._build_default_config()
|
||||
self._config_cache = defaults
|
||||
return dict(defaults)
|
||||
|
||||
try:
|
||||
with path.open("r", encoding="utf-8") as handle:
|
||||
loaded = tomlkit.load(handle)
|
||||
except Exception as exc:
|
||||
logger.warning("读取 A_Memorix 配置失败 %s: %s", path, exc)
|
||||
self._config_cache = {}
|
||||
return {}
|
||||
defaults = self._build_default_config()
|
||||
self._config_cache = defaults
|
||||
return dict(defaults)
|
||||
|
||||
self._config_cache = _to_builtin_data(loaded) if isinstance(loaded, dict) else {}
|
||||
return dict(self._config_cache)
|
||||
|
||||
@@ -560,11 +560,18 @@ Chat paragraph:
|
||||
)
|
||||
async def _llm_call(self, prompt: str, model_config: Any) -> Dict:
|
||||
"""Generic LLM Caller"""
|
||||
success, response, _, _ = await llm_api.generate_with_model(
|
||||
prompt=prompt,
|
||||
model_config=model_config,
|
||||
request_type="Script.ProcessKnowledge"
|
||||
task_name = llm_api.resolve_task_name_from_model_config(model_config)
|
||||
result = await llm_api.generate(
|
||||
llm_api.LLMServiceRequest(
|
||||
task_name=task_name,
|
||||
request_type="Script.ProcessKnowledge",
|
||||
prompt=prompt,
|
||||
temperature=getattr(model_config, "temperature", None),
|
||||
max_tokens=getattr(model_config, "max_tokens", None),
|
||||
)
|
||||
)
|
||||
success = bool(result.success)
|
||||
response = str(result.completion.response or "")
|
||||
if success:
|
||||
txt = response.strip()
|
||||
if "```" in txt:
|
||||
|
||||
@@ -230,6 +230,61 @@ def resolve_task_name(task_name: str = "") -> str:
|
||||
return normalized_task_name
|
||||
|
||||
|
||||
def resolve_task_name_from_model_config(model_config: Any, preferred_task_name: str = "") -> str:
|
||||
"""根据旧版 `TaskConfig` 风格参数解析可用任务名。
|
||||
|
||||
该方法用于兼容仍以 `model_config` 传参的调用方：
|
||||
1. 优先使用显式给出的 `preferred_task_name`；
|
||||
2. 其次匹配对象同一性；
|
||||
3. 再尝试按 `model_list` 精确匹配；
|
||||
4. 最后按 `model_list` 中首个命中的模型进行近似映射。
|
||||
|
||||
Args:
|
||||
model_config: 旧调用方持有的任务配置对象。
|
||||
preferred_task_name: 候选任务名（可选）。
|
||||
|
||||
Returns:
|
||||
str: 可用于 `LLMServiceRequest.task_name` 的任务名。
|
||||
|
||||
Raises:
|
||||
RuntimeError: 当前没有可用模型配置。
|
||||
ValueError: 无法解析任何可用任务名时抛出。
|
||||
"""
|
||||
models = get_available_models()
|
||||
if not models:
|
||||
raise RuntimeError("没有可用的模型配置")
|
||||
|
||||
normalized_preferred = str(preferred_task_name or "").strip()
|
||||
if normalized_preferred and normalized_preferred in models:
|
||||
return normalized_preferred
|
||||
|
||||
for task_name, task_cfg in models.items():
|
||||
if task_cfg is model_config:
|
||||
return task_name
|
||||
|
||||
requested_model_list_raw = getattr(model_config, "model_list", [])
|
||||
requested_model_list = [str(item).strip() for item in (requested_model_list_raw or []) if str(item).strip()]
|
||||
if requested_model_list:
|
||||
for task_name, task_cfg in models.items():
|
||||
candidate_list = [str(item).strip() for item in getattr(task_cfg, "model_list", []) if str(item).strip()]
|
||||
if candidate_list == requested_model_list:
|
||||
return task_name
|
||||
|
||||
for requested_model in requested_model_list:
|
||||
for task_name, task_cfg in models.items():
|
||||
candidate_list = [str(item).strip() for item in getattr(task_cfg, "model_list", []) if str(item).strip()]
|
||||
if requested_model in candidate_list:
|
||||
logger.info(
|
||||
"[LLMService] 旧版 model_config 未命中任务配置，"
|
||||
f"按模型 `{requested_model}` 近似映射到任务 `{task_name}`"
|
||||
)
|
||||
return task_name
|
||||
|
||||
if normalized_preferred:
|
||||
logger.warning(f"[LLMService] 无法映射旧版 model_config，回退默认任务: preferred={normalized_preferred}")
|
||||
return resolve_task_name("")
|
||||
|
||||
|
||||
def _normalize_role(role_name: str) -> RoleType:
|
||||
"""将原始角色字符串转换为内部角色枚举。
|
||||
|
||||
|
||||
@@ -168,6 +168,10 @@ async def _graph_get(limit: int) -> dict:
|
||||
return await memory_service.graph_admin(action="get_graph", limit=limit)
|
||||
|
||||
|
||||
async def _graph_search(query: str, limit: int) -> dict:
|
||||
return await memory_service.graph_admin(action="search", query=query, limit=limit)
|
||||
|
||||
|
||||
async def _graph_get_node_detail(
|
||||
node_id: str,
|
||||
*,
|
||||
@@ -390,9 +394,20 @@ async def _memory_config_get() -> dict:
|
||||
|
||||
|
||||
async def _memory_config_get_raw() -> dict:
|
||||
raw_payload_getter = getattr(a_memorix_host_service, "get_raw_config_with_meta", None)
|
||||
if callable(raw_payload_getter):
|
||||
raw_payload = raw_payload_getter()
|
||||
else:
|
||||
raw_payload = {
|
||||
"config": a_memorix_host_service.get_raw_config(),
|
||||
"exists": bool(a_memorix_host_service.get_config_path().exists()),
|
||||
"using_default": False,
|
||||
}
|
||||
return {
|
||||
"success": True,
|
||||
"config": a_memorix_host_service.get_raw_config(),
|
||||
"config": str(raw_payload.get("config", "") or ""),
|
||||
"exists": bool(raw_payload.get("exists", False)),
|
||||
"using_default": bool(raw_payload.get("using_default", False)),
|
||||
"path": str(a_memorix_host_service.get_config_path()),
|
||||
}
|
||||
|
||||
@@ -649,6 +664,14 @@ async def get_memory_graph(limit: int = Query(200, ge=1, le=5000)):
|
||||
return await _graph_get(limit)
|
||||
|
||||
|
||||
@router.get("/graph/search")
|
||||
async def search_memory_graph(
|
||||
query: str = Query(..., min_length=1),
|
||||
limit: int = Query(50, ge=1, le=200),
|
||||
):
|
||||
return await _graph_search(query, limit)
|
||||
|
||||
|
||||
@router.get("/graph/node-detail")
|
||||
async def get_memory_graph_node_detail(
|
||||
node_id: str = Query(..., min_length=1),
|
||||
|
||||
Reference in New Issue
Block a user