ba8e8e2a82
后端： 1. 记忆系统移除 todo_hint 类型——随口记已由 Task 系统承接，todo_hint 语义重叠且无完成追踪 - 全链路清理：常量、校验、默认重要度、30 天 TTL、读取预算、LLM 抽取提示词枚举 - 总预算从四类收缩为三类（preference / constraint / fact） 2. 记忆抽取触发点从 chat-persist 移至 graph-completion——避免随口记消息被误提取为 constraint/preference - chat-persist consumer 不再自动入队 memory.extract.requested，仅负责聊天历史落库 - graph 完成后新增条件发布：检测 UsedQuickNote 标记，调用过 quick_note_create 则跳过记忆抽取 - ResetForNextRun 重置 UsedQuickNote，防止跨轮残留导致后续正常消息记忆抽取被误跳过 3. 任务类查询接口返回 items 补充数据库主键 ID（前端拖拽编排依赖此字段） 前端： 4. 排程视图新增手动编排模式——侧边栏任务块拖拽入周课表 + 悬浮删除热区 + 建议块虚线标识 - TaskClassSidebar 拖拽发起 + 预览态嵌入时间格式化（含周次/星期） - WeekPlanningBoard 外部拖入 / 内部移动 / 悬浮删除区交互 - ScheduleView 手动编排状态机（进入/退出/取消/覆盖确认）+ apply 时同步处理新增与删除
134 lines
3.2 KiB
Go
134 lines
3.2 KiB
Go
package utils
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import (
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"crypto/sha256"
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"encoding/hex"
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"fmt"
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"strings"
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memorymodel "github.com/LoveLosita/smartflow/backend/memory/model"
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)
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const (
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maxTitleLength = 64
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maxContentLength = 1000
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)
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// NormalizeFacts 对候选事实做标准化与过滤。
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//
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// 步骤：
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// 1. 标准化 memory_type 与文本字段，丢弃空值和非法类型；
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// 2. 对超长内容截断，避免脏数据污染后续链路；
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// 3. 基于“类型+标准化内容”做去重，避免同一轮重复写入。
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func NormalizeFacts(candidates []memorymodel.FactCandidate) []memorymodel.NormalizedFact {
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if len(candidates) == 0 {
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return nil
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}
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result := make([]memorymodel.NormalizedFact, 0, len(candidates))
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seen := make(map[string]struct{}, len(candidates))
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for _, candidate := range candidates {
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memoryType := memorymodel.NormalizeMemoryType(candidate.MemoryType)
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if memoryType == "" {
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continue
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}
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content := normalizeWhitespace(candidate.Content)
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if content == "" {
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continue
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}
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content = truncateByRune(content, maxContentLength)
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title := normalizeWhitespace(candidate.Title)
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if title == "" {
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title = truncateByRune(content, maxTitleLength)
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}
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title = truncateByRune(title, maxTitleLength)
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confidence := clamp01(candidate.Confidence)
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if confidence == 0 {
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confidence = 0.6
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}
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importance := clamp01(candidate.Importance)
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if importance == 0 {
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importance = defaultImportanceByType(memoryType)
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}
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sensitivityLevel := clampInt(candidate.SensitivityLevel, 0, 2)
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normalizedContent := strings.ToLower(content)
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contentHash := HashContent(memoryType, normalizedContent)
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dedupKey := fmt.Sprintf("%s:%s", memoryType, contentHash)
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if _, exists := seen[dedupKey]; exists {
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continue
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}
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seen[dedupKey] = struct{}{}
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result = append(result, memorymodel.NormalizedFact{
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MemoryType: memoryType,
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Title: title,
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Content: content,
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NormalizedContent: normalizedContent,
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ContentHash: contentHash,
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Confidence: confidence,
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Importance: importance,
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SensitivityLevel: sensitivityLevel,
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IsExplicit: candidate.IsExplicit,
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})
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}
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return result
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}
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func normalizeWhitespace(raw string) string {
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return strings.Join(strings.Fields(strings.TrimSpace(raw)), " ")
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}
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func truncateByRune(raw string, max int) string {
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if max <= 0 {
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return ""
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}
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runes := []rune(raw)
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if len(runes) <= max {
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return raw
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}
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return string(runes[:max])
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}
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func clamp01(v float64) float64 {
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if v < 0 {
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return 0
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}
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if v > 1 {
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return 1
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}
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return v
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}
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func clampInt(v, minValue, maxValue int) int {
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if v < minValue {
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return minValue
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}
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if v > maxValue {
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return maxValue
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}
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return v
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}
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func defaultImportanceByType(memoryType string) float64 {
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switch memoryType {
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case memorymodel.MemoryTypePreference:
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return 0.85
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case memorymodel.MemoryTypeConstraint:
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return 0.95
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default:
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return 0.6
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}
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}
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// HashContent 计算记忆内容的去重哈希。
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// 算法：sha256(memoryType + "::" + normalizedContent)
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// 说明：导出此函数是为了让决策层 apply_actions 也能复用同一算法，避免哈希不一致导致去重失效。
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func HashContent(memoryType, normalizedContent string) string {
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sum := sha256.Sum256([]byte(memoryType + "::" + normalizedContent))
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return hex.EncodeToString(sum[:])
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}
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