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v0.7.2: 根目录清理 + Agent 心跳重构 + 内嵌 ONNX 模型

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- 根目录清理: branding/docs/knowledge -> assets/, package/tools/deploy -> deploy/
- meta.go: Version 0.7.2, SDKCompatibleVersion 语义改为最高兼容
- Makefile: 版本回退 0.7.2
- registry.go: 系统提示词改用 meta.Version 格式化
- Agent 心跳: reorgGraph 拆分为三个独立循环(archive/merge/review)，各自可配间隔
- GraphDB: 新增 sentences 表 + 关系句子溯源 + ClearSentenceID + CleanupOrphanedSentences
- Knowledge: 支持词嵌入向量化器
- NLP 四阶段流水线: Parse -> Extract -> Verify -> Fuse + SentenceRef
- 移除远程 HTTP 解析器(remote_parser.go)
- 新增内嵌 ONNX 模型(vocab + dep_parser.onnx):
  +build onnxruntime: 全量 ONNX Runtime 推理
  !build onnxruntime: 内嵌词表规则式降级解析器
- config: core.agent.onnx_model_path 替代 dep_parser_url
This commit is contained in:
JianFeeeee
2026-07-28 09:56:26 +08:00
parent 61fbc55274
commit 5006712c8f
47 changed files with 26141 additions and 242 deletions
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141
internal/nlp/extractor.go
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@ -36,19 +36,32 @@ var depTemplates = []depTemplate{
{subjRel: "SBV", objRel: "IOB", score: 0.85},
{subjRel: "SBV", objRel: "FOB", score: 0.8},
{subjRel: "SBV", objRel: "POB", score: 0.75},
{subjRel: "ATT", objRel: "VOB", score: 0.7},
{subjRel: "ATT", objRel: "IOB", score: 0.65},
{subjRel: "ATT", objRel: "FOB", score: 0.6},
{subjRel: "ATT", objRel: "POB", score: 0.55},
}
// extractFromDep 基于依存句法树提取三元组
func extractFromDep(result *ParseResult) []Triple {
// extractFromDep 基于依存句法树提取三元组 (Phase 2: 结构初筛)
// 输入：Token 序列（含依存关系）
// 处理：标记名词性节点 → 遍历谓词中心 → 收集 SBV/ATT 主语、VOB/IOB/POB 宾语 → 笛卡尔积 → 赋句法置信度 → ATT 链合并
// 输出：候选三元组列表（带 syntax_conf）
func extractFromDep(result *ParseResult, sentence string) []Triple {
if len(result.Tokens) < 2 {
return nil
}
// Step 1: 标记所有名词性节点为候选实体（供后续 ATT 合并等使用）
// （隐式使用，通过 isNounLike 判断）
// Step 2: 遍历所有动词节点作为谓词中心
verbIndices := findPredicates(result.POS, result.Tokens)
var triples []Triple
verbIndices := findPredicates(result.POS, result.Tokens)
for _, vi := range verbIndices {
var subj, obj string
var objIdx int
// Step 3: 沿依存弧收集主语（SBV/ATT）和宾语（VOB/IOB/FOB/POB）
var subjIndices, objIndices []int
var subjRels, objRels []string
for i, head := range result.Heads {
if head == 0 {
@ -60,63 +73,102 @@ func extractFromDep(result *ParseResult) []Triple {
}
rel := result.DepRels[i]
if isSubjRel(rel) && subj == "" {
subj = result.Tokens[i]
} else if isObjRel(rel) && obj == "" {
obj = result.Tokens[i]
objIdx = i
if isSubjRel(rel) {
subjIndices = append(subjIndices, i)
subjRels = append(subjRels, rel)
} else if isObjRel(rel) {
objIndices = append(objIndices, i)
objRels = append(objRels, rel)
}
}
if subj == "" {
// 主语降级：无 SBV/ATT 主语时向左查找最近的名词性节点
if len(subjIndices) == 0 {
for j := vi - 1; j >= 0; j-- {
if isNounLike(result.POS[j]) {
subj = result.Tokens[j]
subjIndices = append(subjIndices, j)
subjRels = append(subjRels, "SBV_IMPLICIT")
break
}
}
}
if subj != "" && obj != "" {
relLabel := result.Tokens[vi]
score := 0.8
if objIdx < len(result.Heads) && result.Heads[objIdx] == vi+1 {
// 宾语降级：无显式宾语时查找动词的其他名词性依赖
if len(objIndices) == 0 {
for i, head := range result.Heads {
if head == 0 {
continue
}
if head-1 == vi && isNounLike(result.POS[i]) && !isSubjRel(result.DepRels[i]) {
objIndices = append(objIndices, i)
objRels = append(objRels, "OBJ_IMPLICIT")
}
}
}
if len(subjIndices) == 0 || len(objIndices) == 0 {
continue
}
// Step 4: 笛卡尔积生成候选对，按模板赋予句法置信度
relLabel := result.Tokens[vi]
for _, si := range subjIndices {
for _, oi := range objIndices {
if si == oi {
continue
}
subj := result.Tokens[si]
obj := result.Tokens[oi]
score := 0.8 // 默认句法置信度
// 匹配模板查询精确置信度
for _, t := range depTemplates {
if t.objRel == result.DepRels[objIdx] {
if si < len(result.Heads) && result.Heads[si] == vi+1 &&
oi < len(result.Heads) && result.Heads[oi] == vi+1 &&
t.subjRel == result.DepRels[si] && t.objRel == result.DepRels[oi] {
score = t.score
break
}
}
triples = append(triples, Triple{
Subject: subj,
Relation: relLabel,
Object: obj,
Score: score,
Src: "dep",
SentenceRef: sentence,
})
}
triples = append(triples, Triple{
Subject: subj,
Relation: relLabel,
Object: obj,
Score: score,
Src: "dep",
})
}
// COO 链扩展：如果宾语有并列结构，为每个并列项生成三元组
if obj != "" {
cooExpanded := expandCOO(result, objIdx, vi)
// COO 链扩展：为每个宾语所在的并列结构生成额外三元组
for _, oi := range objIndices {
cooExpanded := expandCOO(result, oi, vi)
for _, cooObj := range cooExpanded {
if cooObj == obj {
if cooObj == result.Tokens[oi] {
continue
}
relLabel := result.Tokens[vi]
triples = append(triples, Triple{
Subject: subj,
Relation: relLabel,
Object: cooObj,
Score: 0.7,
Src: "dep_coo",
})
for _, si := range subjIndices {
subj := result.Tokens[si]
triples = append(triples, Triple{
Subject: subj,
Relation: relLabel,
Object: cooObj,
Score: 0.7,
Src: "dep_coo",
SentenceRef: sentence,
})
}
}
}
}
// Step 5: ATT 链合并多词实体
triples = mergeAttTriples(result, triples)
// 去重
triples = dedupTriples(triples)
return triples
}
@ -213,8 +265,8 @@ var posTemplates = []posTemplate{
{pattern: []string{"n", "v", "v", "n"}, subj: 0, verb: 1, obj: 3, score: 0.55},
}
// extractFromPOS 基于 POS 序列匹配模板提取三元组
func extractFromPOS(result *ParseResult) []Triple {
// extractFromPOS 基于 POS 序列匹配模板提取三元组 (Phase 2 降级路径)
func extractFromPOS(result *ParseResult, sentence string) []Triple {
if len(result.Tokens) < 2 {
return nil
}
@ -248,11 +300,12 @@ func extractFromPOS(result *ParseResult) []Triple {
continue
}
triples = append(triples, Triple{
Subject: subj,
Relation: verb,
Object: obj,
Score: tpl.score,
Src: "pos",
Subject: subj,
Relation: verb,
Object: obj,
Score: tpl.score,
Src: "pos",
SentenceRef: sentence,
})
}
}
@ -375,7 +428,7 @@ func isAdj(p string) bool {
}
func isSubjRel(rel string) bool {
return rel == "SBV"
return rel == "SBV" || rel == "ATT"
}
func isObjRel(rel string) bool {