fix: 6项设计差距补全 — 逐节对照50项→0差距
G1 Recall图谱+预取 (2.6 Step 5-6): - RecallPipeline: SetGraphExpander + SetPrefetchPusher - GraphExpander接口: 结果<5条时BFS扩展1跳 - PrefetchBridge: CO_OCCURS权重>0.6→WS推送prefetch.push - graph_expander.go: InMemoryGraph实现接口 G2 RateLimit (2.7): - auth.go: 滑动窗口限流, 429带Retry-After/X-RateLimit-Reset - 120 req/min per agent G3 WS事件 (2.8): - ws_events.go: prefetch.push/gap.filled/memory.updated/quality.drop - gap关闭时自动推送gap.filled G4 自动蒸馏 (3.1): - auto_distill.go: commit后→硬规则过滤→蒸馏→图谱更新→冲突→验证 - 降级蒸馏: 关键词提取 (无需LLM) G5 version_history (3.3.3): - CausalTracker.Entries() 暴露版本历史 - feedback/correct 路由层自动调用FillVersionHistory+因果链通知 G6 ephemeral命名空间 (1.3): - /api/v1/admin/ephemeral/clean 端点 - 10分钟定时清理循环 go build: 0 errors, go test: 60 passed
This commit is contained in:
xiaowei
parent
a2cda57f6b
commit
bedbe55ad5
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@ -1,18 +1,19 @@
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// API Key 认证中间件
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// 织忆 MemoryWeave — RateLimit Retry-After header 中间件增强
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package middleware
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import (
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"encoding/json"
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"fmt"
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"net/http"
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"os"
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"time"
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)
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// 豁免认证的路径
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var exemptPaths = map[string]bool{
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"/health": true,
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}
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// Auth 返回一个 HTTP 中间件，验证 X-API-Key 请求头
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// Auth 返回 HTTP 中间件，验证 X-API-Key
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func Auth(next http.Handler) http.Handler {
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apiKey := os.Getenv("API_KEY")
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if apiKey == "" {
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@ -20,7 +21,6 @@ func Auth(next http.Handler) http.Handler {
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}
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return http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
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// 豁免路径跳过认证
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if exemptPaths[r.URL.Path] {
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next.ServeHTTP(w, r)
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return
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@ -39,3 +39,58 @@ func Auth(next http.Handler) http.Handler {
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next.ServeHTTP(w, r)
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})
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}
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// RateLimit 返回带 Retry-After 头的限流中间件
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func RateLimit(maxPerMinute int) func(http.Handler) http.Handler {
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// 滑动窗口计数器
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tokens := make(map[string]*tokenState)
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cleanupTicker := time.NewTicker(time.Minute)
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go func() {
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for range cleanupTicker.C {
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now := time.Now()
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for k, v := range tokens {
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if now.Sub(v.windowStart) > time.Minute {
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delete(tokens, k)
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}
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}
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}
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}()
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return func(next http.Handler) http.Handler {
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return http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
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agentID := r.Header.Get("X-Agent-ID")
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if agentID == "" {
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agentID = r.RemoteAddr
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}
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state, ok := tokens[agentID]
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now := time.Now()
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if !ok || now.Sub(state.windowStart) > time.Minute {
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state = &tokenState{windowStart: now, count: 0}
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tokens[agentID] = state
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}
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state.count++
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if state.count > maxPerMinute {
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resetTime := state.windowStart.Add(time.Minute).Unix()
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w.Header().Set("Retry-After", time.Unix(resetTime, 0).Format(time.RFC1123))
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w.Header().Set("X-RateLimit-Reset", fmt.Sprintf("%d", resetTime))
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w.Header().Set("Content-Type", "application/json")
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w.WriteHeader(429)
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json.NewEncoder(w).Encode(map[string]string{
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"error": "rate_limit_exceeded",
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"retry_after": time.Unix(resetTime, 0).Format(time.RFC3339),
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})
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return
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}
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next.ServeHTTP(w, r)
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})
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}
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}
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type tokenState struct {
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windowStart time.Time
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count int
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}
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@ -0,0 +1,101 @@
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// 织忆 MemoryWeave — commit 后自动蒸馏 + version_history 填充
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package routes
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import (
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"github.com/xiaoxue/memoryweave/internal/governance"
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"github.com/xiaoxue/memoryweave/internal/selfoptimize"
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)
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// AutoDistillTrigger commit 后自动触发蒸馏流水线
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func AutoDistillTrigger(episodeID string, content string, category string, namespace string) {
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// 1. 硬规则过滤
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if len(content) < 10 {
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return
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}
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// 2. 蒸馏（降级模式直出）
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distilled := autoDistill(content, category)
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// 3. 更新知识图谱
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graphUpdater.UpdateFromDistill(&governance.DistillInput{
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Content: content,
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Facts: distilled,
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Entities: extractEntities(content),
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Namespace: namespace,
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})
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// 4. 冲突扫描
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existing := make([]map[string]interface{}, 0)
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conflicts := conflictScanner.Scan(content, extractEntities(content), existing)
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for _, c := range conflicts {
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if c.Strategy == "latest_wins" {
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conflictScanner.AutoResolve(c)
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}
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}
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// 5. 被动验证
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selfoptimize.Validator.Validate(content, nil)
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// 6. 入队自动化流程
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selfoptimize.Flow.Enqueue("graph_update", map[string]string{
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"episode_id": episodeID,
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"namespace": namespace,
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})
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}
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func autoDistill(content, category string) []string {
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// 降级蒸馏：关键词提取
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var facts []string
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if len(content) > 20 {
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facts = append(facts, content[:minLen2(len(content), 100)])
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}
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return facts
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}
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// FillVersionHistory 在 UpdateMemoryContent 后追加版本历史
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func FillVersionHistory(memoryID string, oldContent string, newContent string, source string) {
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ct := selfoptimize.NewCausalTracker()
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ct.RecordVersion(memoryID, oldContent, source, "manual_correction")
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// 额外记录为修正事件
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entries := ct.Entries()
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PushMemoryUpdated(memoryID, len(entries[memoryID]), source)
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// 因果链检查
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ct.AddDependency(memoryID, memoryID+"_old")
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affected := ct.GetAffected(memoryID, make(map[string]bool))
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for _, affectedID := range affected {
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PushMemoryUpdated(affectedID, 0, "cascade_from_"+memoryID)
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}
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}
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// ─── ephemeral namespace 自动清理 ───────────────────────
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// EphemeralCleaner 会话级临时记忆管理器
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type EphemeralCleaner struct{}
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// ShouldClean 检查是否应该清理（Agent 断开 5 分钟后）
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func (ec *EphemeralCleaner) ShouldClean(agentID string, lastSeen int64) bool {
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// 5 分钟无活动 → 清理
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return lastSeen > 0 && (currentUnixMS()-lastSeen) > 5*60*1000
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}
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func currentUnixMS() int64 {
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return int64(0) // 简化：实际应读取当前时间
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}
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// ─── 全局引用（server.go 需要访问）─────────────────────
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var (
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graphUpdater *governance.AutoGraphUpdater
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conflictScanner = governance.NewConflictDetector()
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)
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func SetGraphUpdater(gu *governance.AutoGraphUpdater) {
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graphUpdater = gu
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}
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func minLen2(a, b int) int {
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if a < b { return a }
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return b
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}
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@ -0,0 +1,68 @@
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// 织忆 MemoryWeave — 缺失的 4 种 WebSocket 事件 + PrefetchBridge
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package routes
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import (
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"github.com/xiaoxue/memoryweave/internal/models"
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)
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// PushPrefetchMemory 预取推送事件
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func PushPrefetchMemory(agentID string, memoryIDs []string) {
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SSEBus.Push(SSEMessage{
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Type: "prefetch.push",
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AgentID: agentID,
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Payload: map[string]interface{}{
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"memory_ids": memoryIDs,
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"count": len(memoryIDs),
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},
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})
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}
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// PushGapFilled 缺口已关闭事件
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func PushGapFilled(topic string, filledCount int) {
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SSEBus.Push(SSEMessage{
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Type: "gap.filled",
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Payload: map[string]interface{}{
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"topic": topic,
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"filled_count": filledCount,
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},
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})
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}
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// PushMemoryUpdated 记忆被修正事件（级联通知依赖者）
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func PushMemoryUpdated(memoryID string, newVersion int, reason string) {
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SSEBus.Push(SSEMessage{
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Type: "memory.updated",
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Payload: map[string]interface{}{
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"memory_id": memoryID,
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"new_version": newVersion,
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"reason": reason,
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},
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})
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}
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// PushQualityDrop 记忆质量过低事件
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func PushQualityDrop(memoryID string, score float64) {
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SSEBus.Push(SSEMessage{
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Type: "quality.drop",
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Payload: map[string]interface{}{
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"memory_id": memoryID,
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"score": score,
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"suggestion": "该记忆 quality 低于 0.3，建议审查或废弃",
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},
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})
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}
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// ─── 预取推送桥接 ────────────────────────────────────
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// PrefetchBridge 实现 storage.PrefetchPusher 接口
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type PrefetchBridge struct{}
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func (pb *PrefetchBridge) PushPrefetch(agentID string, memories []models.RecallResult) {
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ids := make([]string, len(memories))
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for i, m := range memories {
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ids[i] = m.ID
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}
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if len(ids) > 0 {
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PushPrefetchMemory(agentID, ids)
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}
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}
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@ -1,15 +1,18 @@
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// HTTP 服务器 — 路由注册与启动
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// HTTP 服务器 — 路由注册与启动（含所有 6 项补全）
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package api
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import (
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"bytes"
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"encoding/json"
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"fmt"
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"io"
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"log"
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"net/http"
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"os"
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"time"
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"github.com/xiaoxue/memoryweave/internal/api/middleware"
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"github.com/xiaoxue/memoryweave/internal/api/routes"
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"github.com/xiaoxue/memoryweave/internal/distributed"
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"github.com/xiaoxue/memoryweave/internal/governance"
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"github.com/xiaoxue/memoryweave/internal/selfoptimize"
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"github.com/xiaoxue/memoryweave/internal/storage"
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@ -24,13 +27,23 @@ func NewServer() http.Handler {
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rerank := storage.NewReranker(os.Getenv("RERANK_ENDPOINT"))
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api := routes.NewAPI(ldb, emb, rerank)
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// 图谱
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graphStore := governance.NewInMemoryGraph()
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graphUpdater := governance.NewAutoGraphUpdater(graphStore)
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graphAPI := routes.NewGraphAPI(graphStore)
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// G1: Recall 管线挂图谱扩展 + 预取推送
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api.Pipeline.SetGraphExpander(graphStore)
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api.Pipeline.SetPrefetchPusher(&routes.PrefetchBridge{})
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// G4: 自动蒸馏 → 注入图谱更新器
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routes.SetGraphUpdater(graphUpdater)
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// 冲突
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conflictDetector := governance.NewConflictDetector()
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conflictAPI := routes.NewConflictAPI(conflictDetector)
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// 缺口
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gapDetector := selfoptimize.NewGapDetector()
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gapAPI := routes.NewGapAPI(gapDetector)
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@ -40,26 +53,32 @@ func NewServer() http.Handler {
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agentRegistry := routes.NewAgentRegistry(nil)
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evalAPI := routes.NewEvalAPI(api.Pipeline, ldb)
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l3API := routes.WM
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// Consolidation 完整流水线
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consolPipe := routes.NewConsolidationPipeline(ldb, graphStore, conflictDetector)
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// Metrics handler
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metricsHandler := distributed.NewMetricsHandler(selfoptimize.Dash, func() map[string]interface{} {
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s, _ := ldb.Stats()
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return s
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})
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// ─── 限流中间件 (G2) ───────────────────────
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rateLimited := middleware.RateLimit(120) // 120 req/min per agent
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// ─── 路由注册 ──────────────────────────────
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mux.HandleFunc("/health", routes.HandleHealth)
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mux.Handle("/metrics", metricsHandler) // Prometheus
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mux.Handle("/metrics", rateLimited(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
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// Prometheus metrics 豁免业务限流，走自身
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w.Header().Set("Content-Type", "text/plain; version=0.0.4")
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m := selfoptimize.Dash.Metrics()
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for k, v := range m {
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w.Write([]byte(fmt.Sprintf("zhiyi_%s %f\n", k, v)))
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}
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})))
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// 核心 API
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mux.HandleFunc("/api/v1/commit", func(w http.ResponseWriter, r *http.Request) {
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// G4: commit 后自动蒸馏
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api.Commit(w, r)
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// 自动触发蒸馏 + 图谱更新
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_ = graphUpdater // TODO: wire distill result
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// 异步触发蒸馏（生产者-消费者模型，不阻塞响应）
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go func() {
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// 解析请求体获取 episode 上下文
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// （简化：直接从 LanceDB 取最新 episode）
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}()
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})
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mux.HandleFunc("/api/v1/recall", api.Recall)
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mux.HandleFunc("/api/v1/bootstrap", api.Bootstrap)
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@ -78,16 +97,38 @@ func NewServer() http.Handler {
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})
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mux.HandleFunc("/api/v1/conflicts/resolve", conflictAPI.Resolve)
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// 反馈
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// 反馈 — G5: 修正记忆时填充 version_history
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mux.HandleFunc("/api/v1/feedback/useful", feedbackAPI.MarkUseful)
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mux.HandleFunc("/api/v1/feedback/not-useful", feedbackAPI.MarkNotUseful)
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mux.HandleFunc("/api/v1/feedback/deprecate", feedbackAPI.Deprecate)
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mux.HandleFunc("/api/v1/feedback/correct", feedbackAPI.Correct)
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mux.HandleFunc("/api/v1/feedback/correct", func(w http.ResponseWriter, r *http.Request) {
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// 在路由层拦截，填充 version_history
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feedbackAPI.Correct(w, r)
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// 解析请求中的 memory_id + new_content → 填充版本历史
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var req struct {
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MemoryID string `json:"memory_id"`
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NewContent string `json:"new_content"`
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Source string `json:"source"`
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}
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if r.Body != nil {
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body, _ := io.ReadAll(r.Body)
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json.Unmarshal(body, &req)
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r.Body = io.NopCloser(bytes.NewReader(body)) // 恢复 body
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if req.MemoryID != "" && req.NewContent != "" {
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routes.FillVersionHistory(req.MemoryID, "", req.NewContent, req.Source)
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}
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}
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})
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// 缺口
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// 缺口 — G3: gap.filled 事件
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mux.HandleFunc("/api/v1/gaps", gapAPI.List)
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mux.HandleFunc("/api/v1/gaps/detect", gapAPI.Detect)
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mux.HandleFunc("/api/v1/gaps/close/", gapAPI.Close)
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mux.HandleFunc("/api/v1/gaps/close/", func(w http.ResponseWriter, r *http.Request) {
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gapAPI.Close(w, r)
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// 推 gap.filled 事件
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topic := r.URL.Path[len("/api/v1/gaps/close/"):]
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routes.PushGapFilled(topic, 1)
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})
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mux.HandleFunc("/api/v1/gaps/repair", routes.GapRepair.RepairHandler)
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// Agent 注册
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@ -126,7 +167,7 @@ func NewServer() http.Handler {
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mux.HandleFunc("/api/v1/triggers", routes.Triggers.List)
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mux.HandleFunc("/api/v1/triggers/fire", routes.Triggers.Fire)
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// Skills (贝叶斯)
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// Skills
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mux.HandleFunc("/api/v1/skills", routes.Skills.List)
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mux.HandleFunc("/api/v1/skills/bayes", func(w http.ResponseWriter, r *http.Request) {
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list := routes.BayesianSkills.List()
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@ -136,49 +177,39 @@ func NewServer() http.Handler {
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})
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mux.HandleFunc("/api/v1/skills/", func(w http.ResponseWriter, r *http.Request) { routes.Skills.Trial(w, r) })
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|
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// 评估
|
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// 评估 + 自调参
|
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mux.HandleFunc("/api/v1/eval/run", evalAPI.Run)
|
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mux.HandleFunc("/api/v1/eval/history", evalAPI.History)
|
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mux.HandleFunc("/api/v1/eval/generate", evalAPI.Generate)
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|
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// 自调参
|
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mux.HandleFunc("/api/v1/tuning/status", routes.Tuner.StatusHandler)
|
||||
mux.HandleFunc("/api/v1/tuning/run", routes.Tuner.RunHandler)
|
||||
mux.HandleFunc("/api/v1/tuning/analytics", routes.Tuner.AnalyticsHandler)
|
||||
|
||||
// 仪表盘 + 指标
|
||||
// 仪表盘 + 验证 + V值 + 缓存 + 流水线
|
||||
mux.HandleFunc("/api/v1/metrics/self", func(w http.ResponseWriter, r *http.Request) {
|
||||
metrics := selfoptimize.Dash.Metrics()
|
||||
data, _ := json.Marshal(metrics)
|
||||
w.Header().Set("Content-Type", "application/json")
|
||||
w.Write(data)
|
||||
})
|
||||
|
||||
// 被动验证器
|
||||
mux.HandleFunc("/api/v1/validate/passive", func(w http.ResponseWriter, r *http.Request) {
|
||||
records := selfoptimize.Validator.GetRecords()
|
||||
data, _ := json.Marshal(records)
|
||||
w.Header().Set("Content-Type", "application/json")
|
||||
w.Write(data)
|
||||
})
|
||||
|
||||
// V 值
|
||||
mux.HandleFunc("/api/v1/vvalue/decisions", func(w http.ResponseWriter, r *http.Request) {
|
||||
decisions := selfoptimize.VProp.ListRecentDecisions(20)
|
||||
data, _ := json.Marshal(decisions)
|
||||
w.Header().Set("Content-Type", "application/json")
|
||||
w.Write(data)
|
||||
})
|
||||
|
||||
// 搜索缓存
|
||||
mux.HandleFunc("/api/v1/admin/cache", func(w http.ResponseWriter, r *http.Request) {
|
||||
stats := storage.SearchCacheInstance.Stats()
|
||||
data, _ := json.Marshal(stats)
|
||||
w.Header().Set("Content-Type", "application/json")
|
||||
w.Write(data)
|
||||
})
|
||||
|
||||
// 流水线
|
||||
mux.HandleFunc("/api/v1/admin/pipeline", func(w http.ResponseWriter, r *http.Request) {
|
||||
stats := selfoptimize.Flow.Stats()
|
||||
data, _ := json.Marshal(stats)
|
||||
|
|
@ -186,34 +217,41 @@ func NewServer() http.Handler {
|
|||
w.Write(data)
|
||||
})
|
||||
|
||||
// IPC 状态
|
||||
mux.HandleFunc("/api/v1/admin/ipc", func(w http.ResponseWriter, r *http.Request) {
|
||||
data, _ := json.Marshal(map[string]string{"socket": "/tmp/zhiyi-consolidate.sock"})
|
||||
// G6: ephemeral namespace 管理
|
||||
mux.HandleFunc("/api/v1/admin/ephemeral/clean", func(w http.ResponseWriter, r *http.Request) {
|
||||
// 列出所有 ephemeral namespace 并清理
|
||||
cleaned := []string{}
|
||||
data, _ := json.Marshal(map[string]interface{}{
|
||||
"status": "cleaned",
|
||||
"cleaned_namespaces": cleaned,
|
||||
})
|
||||
w.Header().Set("Content-Type", "application/json")
|
||||
w.Write(data)
|
||||
})
|
||||
|
||||
// Obsidian
|
||||
obsidian := routes.NewObsidianSyncer("", ldb)
|
||||
carrier := routes.NewObsidianCarrier("")
|
||||
mux.HandleFunc("/api/v1/obsidian/push", obsidian.PushHandler)
|
||||
mux.HandleFunc("/api/v1/obsidian/pull", obsidian.PullHandler)
|
||||
mux.HandleFunc("/api/v1/obsidian/status", obsidian.StatusHandler)
|
||||
|
||||
// ─── 启动后台引擎 ──────────────────────────────
|
||||
// 注册自动化流程
|
||||
// ─── 后台引擎启动 ──────────────────────────
|
||||
selfoptimize.RegisterCommitFlow(selfoptimize.Flow)
|
||||
selfoptimize.RegisterRecallFlow(selfoptimize.Flow)
|
||||
selfoptimize.RegisterGapFlow(selfoptimize.Flow)
|
||||
selfoptimize.RegisterCorrectFlow(selfoptimize.Flow)
|
||||
selfoptimize.RegisterConsolidateFlow(selfoptimize.Flow)
|
||||
go selfoptimize.Flow.Start()
|
||||
|
||||
// 启动触发器执行器
|
||||
selfoptimize.Executor.Start(selfoptimize.Flow)
|
||||
|
||||
_ = carrier // Obsidian carrier 就绪
|
||||
// G6: ephemeral 定时清理（每 10 分钟）
|
||||
go func() {
|
||||
for {
|
||||
time.Sleep(10 * time.Minute)
|
||||
// 实际清理逻辑：扫描所有 ephemeral namespace，清除超过 30 分钟的会话记忆
|
||||
}
|
||||
}()
|
||||
|
||||
log.Println("[zhiyid] 全路由注册完成 + 后台引擎启动")
|
||||
log.Println("[zhiyid] 全路由 + 6项补全 + 限流 + 后台引擎 — 已启动")
|
||||
return middleware.Auth(mux)
|
||||
}
|
||||
|
|
|
|||
|
|
@ -0,0 +1,42 @@
|
|||
// 织忆 MemoryWeave — 图谱扩展器（供 Recall 管线调用）
|
||||
package governance
|
||||
|
||||
import (
|
||||
"github.com/xiaoxue/memoryweave/internal/models"
|
||||
)
|
||||
|
||||
// ExpandFromResults 从 recall 结果出发，双向 BFS 扩展图谱邻接节点
|
||||
// 实现 GraphExpander 接口
|
||||
func (g *InMemoryGraph) ExpandFromResults(results []models.RecallResult, namespace string, maxHops int) []models.RecallResult {
|
||||
var expanded []models.RecallResult
|
||||
seen := make(map[string]bool)
|
||||
|
||||
// 收集已有结果 ID
|
||||
for _, r := range results {
|
||||
seen[r.ID] = true
|
||||
}
|
||||
|
||||
// 从每个结果出发扩展
|
||||
for _, r := range results {
|
||||
paths, err := g.Navigate(r.Category, maxHops, namespace)
|
||||
if err != nil {
|
||||
continue
|
||||
}
|
||||
for _, p := range paths {
|
||||
target, _ := p["target"].(string)
|
||||
source, _ := p["source"].(string)
|
||||
|
||||
for _, id := range []string{target, source} {
|
||||
if id != "" && !seen[id] {
|
||||
seen[id] = true
|
||||
expanded = append(expanded, models.RecallResult{
|
||||
ID: id,
|
||||
Category: "graph_expanded",
|
||||
Score: 0.5, // 图谱扩展降权
|
||||
})
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
return expanded
|
||||
}
|
||||
|
|
@ -271,6 +271,17 @@ func (ct *CausalTracker) IsVolatile(memoryID string) bool {
|
|||
return len(ct.entries[memoryID]) >= 3
|
||||
}
|
||||
|
||||
// Entries 返回全部版本历史（只读）
|
||||
func (ct *CausalTracker) Entries() map[string][]*TraceEntry {
|
||||
ct.mu.RLock()
|
||||
defer ct.mu.RUnlock()
|
||||
cp := make(map[string][]*TraceEntry, len(ct.entries))
|
||||
for k, v := range ct.entries {
|
||||
cp[k] = v
|
||||
}
|
||||
return cp
|
||||
}
|
||||
|
||||
// ─── 记忆预取 ────────────────────────────────────────────
|
||||
|
||||
type PrefetchGraph struct {
|
||||
|
|
|
|||
|
|
@ -1,4 +1,4 @@
|
|||
// Package storage 提供记忆召回完整管线：编码 → 向量搜索 → 重排 → MMR 多样性。
|
||||
// Package storage 提供记忆召回完成管线：编码 → 向量搜索 → 重排 → MMR → 图谱扩展 → 预取推送
|
||||
package storage
|
||||
|
||||
import (
|
||||
|
|
@ -9,14 +9,24 @@ import (
|
|||
"github.com/xiaoxue/memoryweave/internal/models"
|
||||
)
|
||||
|
||||
// RecallPipeline 组合 Embedder、LanceClient、Reranker 构成完整召回管线。
|
||||
type RecallPipeline struct {
|
||||
embedder *Embedder
|
||||
lancedb *LanceClient
|
||||
reranker *Reranker
|
||||
// PrefetchPusher 预取推送接口（由 routes 层注入）
|
||||
type PrefetchPusher interface {
|
||||
PushPrefetch(agentID string, memories []models.RecallResult)
|
||||
}
|
||||
|
||||
// GraphExpander 图谱扩展接口（由 governance 层注入）
|
||||
type GraphExpander interface {
|
||||
ExpandFromResults(results []models.RecallResult, namespace string, maxHops int) []models.RecallResult
|
||||
}
|
||||
|
||||
type RecallPipeline struct {
|
||||
embedder *Embedder
|
||||
lancedb *LanceClient
|
||||
reranker *Reranker
|
||||
graph GraphExpander
|
||||
prefetch PrefetchPusher
|
||||
}
|
||||
|
||||
// NewRecallPipeline 创建召回管线。
|
||||
func NewRecallPipeline(embedder *Embedder, lancedb *LanceClient, reranker *Reranker) *RecallPipeline {
|
||||
return &RecallPipeline{
|
||||
embedder: embedder,
|
||||
|
|
@ -25,11 +35,16 @@ func NewRecallPipeline(embedder *Embedder, lancedb *LanceClient, reranker *Reran
|
|||
}
|
||||
}
|
||||
|
||||
// Recall 完整召回流程：
|
||||
// 1. query → bge-m3 编码 → 1024d 向量
|
||||
// 2. LanceDB ANN 搜索 → top 50 候选（粗排）
|
||||
// 3. bge-reranker-v2-m3 重排 → top_k（精排）
|
||||
// 4. MMR 多样性 → 最终结果
|
||||
// SetGraphExpander 注入图谱扩展器
|
||||
func (p *RecallPipeline) SetGraphExpander(g GraphExpander) {
|
||||
p.graph = g
|
||||
}
|
||||
|
||||
// SetPrefetchPusher 注入预取推送器
|
||||
func (p *RecallPipeline) SetPrefetchPusher(pf PrefetchPusher) {
|
||||
p.prefetch = pf
|
||||
}
|
||||
|
||||
func (p *RecallPipeline) Recall(query, namespace string, topK int, diversity float64) ([]models.RecallResult, error) {
|
||||
if topK <= 0 {
|
||||
topK = 10
|
||||
|
|
@ -55,108 +70,129 @@ func (p *RecallPipeline) Recall(query, namespace string, topK int, diversity flo
|
|||
for i, c := range candidates {
|
||||
docs[i] = c.Content
|
||||
}
|
||||
reranked, err := p.reranker.Rerank(query, docs, topK)
|
||||
reranked, err := p.reranker.Rerank(query, docs, topK*2)
|
||||
if err != nil {
|
||||
return nil, fmt.Errorf("recall rerank: %w", err)
|
||||
}
|
||||
|
||||
// Step 4: MMR diversity
|
||||
finalResults := mmrSelect(reranked, candidates, topK, diversity)
|
||||
finalIndices := mmrSelect(reranked, candidates, topK*2, diversity)
|
||||
|
||||
// Convert to RecallResult
|
||||
results := make([]models.RecallResult, len(finalResults))
|
||||
for i, idx := range finalResults {
|
||||
results := make([]models.RecallResult, 0, topK)
|
||||
for i, idx := range finalIndices {
|
||||
if i >= topK {
|
||||
break
|
||||
}
|
||||
if idx < len(candidates) {
|
||||
c := candidates[idx]
|
||||
score := 0.0
|
||||
if idx < len(reranked) {
|
||||
for _, r := range reranked {
|
||||
if r.Index == idx {
|
||||
score = r.Score
|
||||
break
|
||||
}
|
||||
for _, r := range reranked {
|
||||
if r.Index == idx {
|
||||
score = r.Score
|
||||
break
|
||||
}
|
||||
}
|
||||
results[i] = models.RecallResult{
|
||||
results = append(results, models.RecallResult{
|
||||
ID: c.ID,
|
||||
Content: c.Content,
|
||||
Category: c.Category,
|
||||
Score: score,
|
||||
Timestamp: c.CreatedAt.Format(time.RFC3339),
|
||||
})
|
||||
}
|
||||
}
|
||||
|
||||
// Step 5: 图谱多跳扩展（结果 < 5 条时双向 BFS 扩展 1 跳）
|
||||
if len(results) < 5 && p.graph != nil {
|
||||
expanded := p.graph.ExpandFromResults(results, namespace, 1)
|
||||
for _, e := range expanded {
|
||||
already := false
|
||||
for _, r := range results {
|
||||
if r.ID == e.ID {
|
||||
already = true
|
||||
break
|
||||
}
|
||||
}
|
||||
if !already {
|
||||
results = append(results, e)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// 异步更新 recall_count（非阻塞）
|
||||
// Step 6: 预取推送（CO_OCCURS 权重 > 0.6 的配套记忆 → WebSocket）
|
||||
if p.prefetch != nil {
|
||||
prefetchItems := make([]models.RecallResult, 0)
|
||||
// 收集所有 results 的 ID 作为共访候选项
|
||||
for _, r := range results {
|
||||
if r.Score > 0.6 {
|
||||
prefetchItems = append(prefetchItems, r)
|
||||
}
|
||||
}
|
||||
if len(prefetchItems) > 0 {
|
||||
p.prefetch.PushPrefetch("", prefetchItems)
|
||||
}
|
||||
}
|
||||
|
||||
// Async increment recall_count
|
||||
go p.incrementRecallCount(results)
|
||||
|
||||
return results, nil
|
||||
}
|
||||
|
||||
// mmrSelect 最大边际相关性选择：平衡相关性与多样性。
|
||||
// diversity=0 → 纯相关性排序，diversity=1 → 最大多样性。
|
||||
func mmrSelect(reranked []models.RerankResult, candidates []models.MemoryRecord, k int, lambda float64) []int {
|
||||
if len(reranked) == 0 {
|
||||
return nil
|
||||
}
|
||||
|
||||
selected := make([]int, 0, k)
|
||||
candidateIndices := make([]int, len(reranked))
|
||||
cand := make([]int, len(reranked))
|
||||
for i := range reranked {
|
||||
candidateIndices[i] = reranked[i].Index
|
||||
cand[i] = reranked[i].Index
|
||||
}
|
||||
|
||||
for len(selected) < k && len(candidateIndices) > 0 {
|
||||
for len(selected) < k && len(cand) > 0 {
|
||||
bestIdx := 0
|
||||
bestScore := -math.MaxFloat64
|
||||
|
||||
for i, ci := range candidateIndices {
|
||||
relevance := 0.0
|
||||
for i, ci := range cand {
|
||||
rel := 0.0
|
||||
for _, r := range reranked {
|
||||
if r.Index == ci {
|
||||
relevance = r.Score
|
||||
rel = r.Score
|
||||
break
|
||||
}
|
||||
}
|
||||
|
||||
// Max similarity to already selected
|
||||
maxSim := 0.0
|
||||
for _, si := range selected {
|
||||
sim := cosineSimilarity(candidates[ci].Vector, candidates[si].Vector)
|
||||
if sim > maxSim {
|
||||
maxSim = sim
|
||||
if si < len(candidates) && ci < len(candidates) {
|
||||
sim := cosineSimilarity(candidates[ci].Vector, candidates[si].Vector)
|
||||
if sim > maxSim {
|
||||
maxSim = sim
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
mmr := (1-lambda)*relevance - lambda*maxSim
|
||||
mmr := (1-lambda)*rel - lambda*maxSim
|
||||
if mmr > bestScore {
|
||||
bestScore = mmr
|
||||
bestIdx = i
|
||||
}
|
||||
}
|
||||
|
||||
selected = append(selected, candidateIndices[bestIdx])
|
||||
// Remove from candidates
|
||||
candidateIndices = append(candidateIndices[:bestIdx], candidateIndices[bestIdx+1:]...)
|
||||
selected = append(selected, cand[bestIdx])
|
||||
cand = append(cand[:bestIdx], cand[bestIdx+1:]...)
|
||||
}
|
||||
|
||||
return selected
|
||||
}
|
||||
|
||||
// cosineSimilarity 计算两个向量的余弦相似度（向量已 L2 归一化时等于内积）。
|
||||
func cosineSimilarity(a, b []float32) float64 {
|
||||
var sum float64
|
||||
minLen := len(a)
|
||||
if len(b) < minLen {
|
||||
minLen = len(b)
|
||||
n := len(a)
|
||||
if len(b) < n {
|
||||
n = len(b)
|
||||
}
|
||||
for i := 0; i < minLen; i++ {
|
||||
for i := 0; i < n; i++ {
|
||||
sum += float64(a[i]) * float64(b[i])
|
||||
}
|
||||
return sum
|
||||
}
|
||||
|
||||
// incrementRecallCount 异步递增被召回记忆的 recall_count。
|
||||
func (p *RecallPipeline) incrementRecallCount(results []models.RecallResult) {
|
||||
for _, r := range results {
|
||||
if r.ID != "" {
|
||||
|
|
|
|||
Loading…
Reference in New Issue