feat: 完整实现 NLP 三元组提取系统 + token budget 上下文分配

- 重写 extractor.go: 分句、17条 POS 模板、依存模板 + COO 链、ATT合并
- parser.go: 分句循环 + TransE 向量验证(h+r≈t)
- fallback.go: jieba POS 降级解析器
- bridge.go: nlp.Triple ↔ memory.Triple 转换
- pipeline.go: extractKeyTriples 改用 NLP 提取器, 删除5条旧前缀规则
- distill.go: docToTriples 改用 NLP 提取器
- reorgGraph: 语义相似度增强检测, 保持纯 LLM 决断
- Provider 接口加 MaxContextTokens() + 模型窗口映射表
- tokenbudget.go: 中文 token 估算器 + budget 分配(80%利用率)
- process.go/buildSystemPrompt: 按 token 预算截断 memory+timeline
This commit is contained in:
root
2026-07-27 15:26:23 +08:00
parent d19b7bd13e
commit 1cb3e87dde
30 changed files with 1508 additions and 773 deletions

View File

@ -14,6 +14,7 @@ import (
"time"
"gitcode.com/JianFeeeee/HomeAgent/internal/memory"
"gitcode.com/JianFeeeee/HomeAgent/internal/nlp"
)
type RawRecord struct {
@ -265,182 +266,24 @@ func (d *Distiller) cleanupRawFiles() {
func extractKeyTriples(userContent, assistantContent string) []memory.Triple {
var triples []memory.Triple
// 提取对话中的关键信息,而不是直接 dump 原文
// 规则1: "我的名字是X" / "我叫X" → (用户, 姓名, X)
if name := extractName(userContent); name != "" {
triples = append(triples, memory.Triple{Subject: "用户", Relation: "姓名", Object: name})
e := nlp.NewExtractor(nil)
text := userContent
if assistantContent != "" {
text += assistantContent
}
// 规则2: "我住在X" / "我家在X" → (用户, 居住地, X)
if loc := extractLocation(userContent); loc != "" {
triples = append(triples, memory.Triple{Subject: "用户", Relation: "居住地", Object: loc})
}
// 规则3: "我喜欢X" / "我爱X" → (用户, 喜好, X)
if like := extractLike(userContent); like != "" {
triples = append(triples, memory.Triple{Subject: "用户", Relation: "喜好", Object: like})
}
// 规则4: "我X岁" / "我的年龄是X" → (用户, 年龄, X)
if age := extractAge(userContent); age != "" {
triples = append(triples, memory.Triple{Subject: "用户", Relation: "年龄", Object: age})
}
// 规则5: "我的工作是X" / "我在X工作" → (用户, 职业, X)
if job := extractJob(userContent); job != "" {
triples = append(triples, memory.Triple{Subject: "用户", Relation: "职业", Object: job})
result := e.Extract(text)
if result != nil {
for _, nt := range result.Triples {
mt := nlp.ToMemoryTriple(nt)
if mt.Subject != "" && mt.Relation != "" && mt.Object != "" {
triples = append(triples, mt)
}
}
}
return triples
}
func extractName(s string) string {
patterns := []struct {
prefix string
suffix string
}{
{"我叫", ""},
{"我的名字是", ""},
{"名字是", ""},
{"我是", ""},
}
s = strings.TrimSpace(s)
for _, p := range patterns {
if strings.HasPrefix(s, p.prefix) {
candidate := strings.TrimPrefix(s, p.prefix)
if p.suffix != "" && strings.Contains(candidate, p.suffix) {
candidate = candidate[:strings.Index(candidate, p.suffix)]
}
candidate = strings.TrimSpace(candidate)
// 取第一个空格/逗号/句号前的内容
for _, sep := range []string{",", "。", " ", ","} {
if idx := strings.Index(candidate, sep); idx > 0 {
candidate = candidate[:idx]
}
}
// "我是张三"(姓名) vs "我是一个程序员"(职业):名字通常 ≤4 字符
if p.prefix == "我是" && len([]rune(candidate)) > 4 {
continue
}
if len(candidate) > 0 && len(candidate) < 20 {
return candidate
}
}
}
return ""
}
func extractLocation(s string) string {
s = strings.TrimSpace(s)
after := ""
switch {
case strings.HasPrefix(s, "我住在"):
after = strings.TrimPrefix(s, "我住在")
case strings.HasPrefix(s, "我家在"):
after = strings.TrimPrefix(s, "我家在")
case strings.HasPrefix(s, "我居住在"):
after = strings.TrimPrefix(s, "我居住在")
case strings.HasPrefix(s, "住在"):
after = strings.TrimPrefix(s, "住在")
default:
return ""
}
for _, sep := range []string{"。", ",", " ", ","} {
if idx := strings.Index(after, sep); idx > 0 {
after = after[:idx]
}
}
if len(after) > 0 && len(after) < 50 {
return strings.TrimSpace(after)
}
return ""
}
func extractLike(s string) string {
s = strings.TrimSpace(s)
after := ""
switch {
case strings.HasPrefix(s, "我喜欢"):
after = strings.TrimPrefix(s, "我喜欢")
case strings.HasPrefix(s, "我爱"):
after = strings.TrimPrefix(s, "我爱")
case strings.HasPrefix(s, "我最喜欢"):
after = strings.TrimPrefix(s, "我最喜欢")
default:
return ""
}
for _, sep := range []string{"。", ",", " ", ","} {
if idx := strings.Index(after, sep); idx > 0 {
after = after[:idx]
}
}
if len(after) > 0 && len(after) < 50 {
return strings.TrimSpace(after)
}
return ""
}
func extractAge(s string) string {
s = strings.TrimSpace(s)
after := ""
switch {
case strings.HasPrefix(s, "我"):
rest := strings.TrimPrefix(s, "我")
if strings.Contains(rest, "岁") {
after = rest[:strings.Index(rest, "岁")]
} else if strings.HasPrefix(rest, "的年龄是") {
after = strings.TrimPrefix(rest, "的年龄是")
} else {
return ""
}
default:
return ""
}
for _, sep := range []string{"。", ",", " ", ","} {
if idx := strings.Index(after, sep); idx > 0 {
after = after[:idx]
}
}
if len(after) > 0 && len(after) < 5 {
return strings.TrimSpace(after)
}
return ""
}
func extractJob(s string) string {
s = strings.TrimSpace(s)
after := ""
switch {
case strings.HasPrefix(s, "我的工作是"):
after = strings.TrimPrefix(s, "我的工作是")
case strings.HasPrefix(s, "我在"):
rest := strings.TrimPrefix(s, "我在")
if strings.Contains(rest, "工作") {
after = rest[:strings.Index(rest, "工作")]
} else {
return ""
}
case strings.HasPrefix(s, "我是"):
rest := strings.TrimPrefix(s, "我是")
// "我是一个程序员" / "我是老师"
for _, keyword := range []string{"一个", "一名", "一位"} {
if strings.HasPrefix(rest, keyword) {
rest = strings.TrimPrefix(rest, keyword)
break
}
}
// 职业通常较短,先看看
after = rest
default:
return ""
}
for _, sep := range []string{"。", ",", " ", ",", "。"} {
if idx := strings.Index(after, sep); idx > 0 {
after = after[:idx]
}
}
if len(after) > 0 && len(after) < 20 {
return strings.TrimSpace(after)
}
return ""
}
func truncate(s string, max int) string {
if len(s) > max {
return s[:max] + "..."