feat: 第四轮功能增强 - LLM 思维记忆优化、DevTools 记忆UI、9个新工具、5分钟自我思考
- 优化 LLM 思维方式和记忆方法（类别/重要性/关键词/相似度合并/衰减） - DevTools 记忆查询 UI 重新设计（类别筛选/排序/星标/搜索） - 新增 9 个 LLM 工具：calculator, datetime, file_ops, http_request, json_ops, text, random, crypto, markdown - 管理员主对话 5 分钟自我思考增强（工具调用/记忆提取/记忆维护）
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@@ -1,15 +1,18 @@
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package model
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import "time"
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import (
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"encoding/json"
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"time"
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)
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// MemoryPriority 记忆优先级
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type MemoryPriority int
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const (
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MemoryTemp MemoryPriority = 0 // 临时记忆 (会话内)
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MemoryNormal MemoryPriority = 1 // 普通记忆
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MemoryTemp MemoryPriority = 0 // 临时记忆 (会话内)
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MemoryNormal MemoryPriority = 1 // 普通记忆
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MemoryImportant MemoryPriority = 2 // 重要记忆
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MemoryCore MemoryPriority = 3 // 核心记忆 (永远保留)
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MemoryCore MemoryPriority = 3 // 核心记忆 (永远保留)
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)
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// String 返回优先级的中文描述
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@@ -32,37 +35,167 @@ func (p MemoryPriority) String() string {
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type MemoryCategory string
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const (
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CategoryPreference MemoryCategory = "preference" // 喜好/偏好
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CategoryFact MemoryCategory = "fact" // 事实信息
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CategoryEvent MemoryCategory = "event" // 事件/经历
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CategoryRelationship MemoryCategory = "relationship" // 关系/情感
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CategoryHabit MemoryCategory = "habit" // 习惯
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CategoryOther MemoryCategory = "other" // 其他
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CategoryUserPreference MemoryCategory = "user_preference" // 用户偏好 (食物、颜色、习惯)
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CategoryPersonalInfo MemoryCategory = "personal_info" // 个人信息 (姓名、年龄、职业)
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CategoryConversation MemoryCategory = "conversation" // 对话摘要
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CategoryKnowledge MemoryCategory = "knowledge" // 知识性信息
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CategoryEvent MemoryCategory = "event" // 事件记录
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CategoryTask MemoryCategory = "task" // 任务/计划
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CategoryRelationship MemoryCategory = "relationship" // 关系信息
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// 向后兼容的旧分类别名
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CategoryPreference = CategoryUserPreference
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CategoryFact = CategoryPersonalInfo
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CategoryHabit = CategoryUserPreference
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CategoryOther = CategoryKnowledge
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)
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// CategoryDisplayName 返回分类的中文显示名
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func (c MemoryCategory) DisplayName() string {
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switch c {
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case CategoryUserPreference:
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return "用户偏好"
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case CategoryPersonalInfo:
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return "个人信息"
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case CategoryConversation:
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return "对话摘要"
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case CategoryKnowledge:
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return "知识信息"
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case CategoryEvent:
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return "事件记录"
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case CategoryTask:
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return "任务计划"
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case CategoryRelationship:
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return "关系情感"
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default:
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return "其他"
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}
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}
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// MemoryEntry 记忆条目
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type MemoryEntry struct {
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ID string `json:"id" db:"id"`
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UserID string `json:"user_id" db:"user_id"`
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Content string `json:"content" db:"content"`
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Summary string `json:"summary" db:"summary"` // 简短摘要
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Category MemoryCategory `json:"category" db:"category"`
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Priority MemoryPriority `json:"priority" db:"priority"`
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SessionID string `json:"session_id" db:"session_id"` // 来源会话
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Source string `json:"source" db:"source"` // 来源文本片断
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Embedding []float32 `json:"-" db:"embedding"` // 向量 (pgvector)
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AccessCount int `json:"access_count" db:"access_count"`
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LastAccess time.Time `json:"last_access" db:"last_access"`
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CreatedAt time.Time `json:"created_at" db:"created_at"`
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ExpiresAt *time.Time `json:"expires_at,omitempty" db:"expires_at"` // 临时记忆过期时间
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ID string `json:"id" db:"id"`
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UserID string `json:"user_id" db:"user_id"`
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Content string `json:"content" db:"content"`
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Summary string `json:"summary" db:"summary"` // 简短摘要
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Category MemoryCategory `json:"category" db:"category"`
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Priority MemoryPriority `json:"priority" db:"priority"`
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Importance int `json:"importance" db:"importance"` // 重要程度 1-10
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Keywords []string `json:"keywords" db:"keywords"` // 关键词标签
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SessionID string `json:"session_id" db:"session_id"` // 来源会话
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Source string `json:"source" db:"source"` // 来源 (conversation/thinking)
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Embedding []float32 `json:"-" db:"embedding"` // 向量 (pgvector)
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AccessCount int `json:"access_count" db:"access_count"`
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LastAccess time.Time `json:"last_access" db:"last_access"`
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CreatedAt time.Time `json:"created_at" db:"created_at"`
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UpdatedAt time.Time `json:"updated_at" db:"updated_at"` // 最后更新时间
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ExpiresAt *time.Time `json:"expires_at,omitempty" db:"expires_at"` // 临时记忆过期时间
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}
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// KeywordsJSON 将关键词序列化为 JSON 字符串（用于数据库存储）
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func (e *MemoryEntry) KeywordsJSON() string {
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if len(e.Keywords) == 0 {
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return "[]"
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}
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data, _ := json.Marshal(e.Keywords)
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return string(data)
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}
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// ParseKeywords 从 JSON 字符串解析关键词
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func ParseKeywords(raw string) []string {
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if raw == "" || raw == "[]" {
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return nil
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}
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var keywords []string
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if err := json.Unmarshal([]byte(raw), &keywords); err != nil {
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return nil
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}
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return keywords
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}
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// SimilarityScore 计算两个记忆条目的简单文本相似度（基于词汇重叠）
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// 返回值 0.0 - 1.0
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func (e *MemoryEntry) SimilarityScore(other *MemoryEntry) float64 {
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if e.Content == other.Content {
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return 1.0
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}
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// 基于关键词的重叠度
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if len(e.Keywords) > 0 && len(other.Keywords) > 0 {
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keywordSet := make(map[string]bool, len(e.Keywords))
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for _, k := range e.Keywords {
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keywordSet[k] = true
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}
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overlap := 0
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for _, k := range other.Keywords {
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if keywordSet[k] {
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overlap++
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}
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}
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keywordScore := float64(overlap) / float64(max(len(e.Keywords), len(other.Keywords)))
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if keywordScore > 0.6 {
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return keywordScore
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}
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}
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// 基于内容的字符级 Jaccard 相似度
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return jaccardSimilarity(e.Content, other.Content)
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}
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// jaccardSimilarity 计算两个字符串的 Jaccard 相似度
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func jaccardSimilarity(a, b string) float64 {
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if a == b {
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return 1.0
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}
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if len(a) == 0 || len(b) == 0 {
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return 0.0
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}
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// 使用 bigram 分词
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bigramsA := make(map[string]int)
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runesA := []rune(a)
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for i := 0; i < len(runesA)-1; i++ {
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bigramsA[string(runesA[i:i+2])]++
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}
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bigramsB := make(map[string]int)
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runesB := []rune(b)
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for i := 0; i < len(runesB)-1; i++ {
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bigramsB[string(runesB[i:i+2])]++
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}
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intersection := 0
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for bg, countA := range bigramsA {
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if countB, ok := bigramsB[bg]; ok {
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intersection += min(countA, countB)
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}
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}
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union := 0
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allBigrams := make(map[string]bool)
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for bg := range bigramsA {
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allBigrams[bg] = true
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}
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for bg := range bigramsB {
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allBigrams[bg] = true
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}
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for bg := range allBigrams {
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union += max(bigramsA[bg], bigramsB[bg])
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}
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if union == 0 {
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return 0.0
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}
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return float64(intersection) / float64(union)
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}
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// MemoryQuery 记忆查询参数
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type MemoryQuery struct {
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UserID string
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Query string // 查询文本
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Category MemoryCategory
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Priority MemoryPriority
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Limit int
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Offset int
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UserID string
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Query string // 查询文本
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Category MemoryCategory
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Priority MemoryPriority
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MinImportance int // 最低重要程度筛选
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Limit int
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Offset int
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}
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