feat: GraphRAG — LLM 抽三元组建 Neo4j 图谱 + 混合检索加图谱第三路

混合检索从 2 路(向量+全文)升级为 3 路(+图谱)。入库时 LLM 抽实体/关系建 Neo4j 图，检索时图谱路(实体关联三元组)融进 RRF；UI 可视化图谱。 - mcp-go rag: chat.go(OpenAI 兼容非流式 chat 客户端,抽取用) + graph.go(neo4j-go-driver 连接 + LLM 抽三元组 + MERGE 实体/关系 + 图谱召回/全量三元组) + rag.go(Config 结构; graph+chat 路;Ingest 加抽实体/写Neo4j 阶段;Search 三路 RRF 融合;SetChat 热更新) - mcp-go: Neo4j env(默认 neo4j://localhost:7687, neo4j/sundynix);订阅 chat 控制面配置 (复用 DeepSeek 做抽取);新工具 kb_graph(返回三元组) - gateway: GET /api/v1/kb/graph;frontend KbView 知识图谱面板(实体—关系→实体) - 验证: 全模块 build✓ + e2e PASS; live——入库'sundynix用Milvus...'→DeepSeek 抽 4 三元组 →Neo4j(8 实体);检索三路融合向量=4 全文=2 图谱=1;浏览器图谱面板渲染 4 三元组 - 边界: 实体链接用 CONTAINS 朴素匹配(可升级 LLM 查询实体抽取);全文/图谱重启随入库重建 Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-11 11:10:22 +08:00
parent 2d5fd2fca5
commit d623b8590e
11 changed files with 399 additions and 22 deletions
@@ -0,0 +1,158 @@
+package rag
+
+import (
+	"context"
+	"encoding/json"
+	"fmt"
+	"log"
+	"strings"
+
+	"github.com/neo4j/neo4j-go-driver/v5/neo4j"
+	"github.com/neo4j/neo4j-go-driver/v5/neo4j/auth"
+)
+
+// Triple 是一条知识三元组（主体-关系-客体）。
+type Triple struct {
+	S string `json:"s"`
+	P string `json:"p"`
+	O string `json:"o"`
+}
+
+// graphStore 是 GraphRAG 的图路：实体/关系存 Neo4j。
+type graphStore struct {
+	driver neo4j.DriverWithContext
+}
+
+func openGraph(ctx context.Context, uri, user, pass string) *graphStore {
+	if uri == "" {
+		return &graphStore{}
+	}
+	drv, err := neo4j.NewDriverWithContext(uri,
+		auth.BasicTokenManager(func(context.Context) (neo4j.AuthToken, error) {
+			return neo4j.BasicAuth(user, pass, ""), nil
+		}))
+	if err != nil {
+		log.Printf("[rag] Neo4j 连接失败，图谱路降级: %v", err)
+		return &graphStore{}
+	}
+	if err := drv.VerifyConnectivity(ctx); err != nil {
+		log.Printf("[rag] Neo4j 不可用，图谱路降级: %v", err)
+		return &graphStore{}
+	}
+	// 实体唯一约束（kb+name）。
+	_, _ = neo4j.ExecuteQuery(ctx, drv,
+		"CREATE CONSTRAINT entity_key IF NOT EXISTS FOR (e:Entity) REQUIRE (e.kb, e.name) IS UNIQUE",
+		nil, neo4j.EagerResultTransformer)
+	log.Printf("[rag] Neo4j connected %s", uri)
+	return &graphStore{driver: drv}
+}
+
+func (g *graphStore) ready() bool { return g != nil && g.driver != nil }
+
+func (g *graphStore) close(ctx context.Context) {
+	if g.ready() {
+		_ = g.driver.Close(ctx)
+	}
+}
+
+// store 把三元组 MERGE 进 Neo4j（实体 + 关系，按 kb 隔离）。
+func (g *graphStore) store(ctx context.Context, kb string, triples []Triple) (int, error) {
+	if !g.ready() {
+		return 0, nil
+	}
+	n := 0
+	for _, t := range triples {
+		if t.S == "" || t.O == "" || t.P == "" {
+			continue
+		}
+		_, err := neo4j.ExecuteQuery(ctx, g.driver,
+			`MERGE (a:Entity {kb:$kb, name:$s})
+			 MERGE (b:Entity {kb:$kb, name:$o})
+			 MERGE (a)-[r:REL {type:$p}]->(b)`,
+			map[string]any{"kb": kb, "s": t.S, "o": t.O, "p": t.P},
+			neo4j.EagerResultTransformer, neo4j.ExecuteQueryWithDatabase("neo4j"))
+		if err != nil {
+			return n, err
+		}
+		n++
+	}
+	return n, nil
+}
+
+// search 图谱召回：找查询里提到的实体，返回其相连三元组（文本化）。
+func (g *graphStore) search(ctx context.Context, kb, query string, limit int) []Hit {
+	if !g.ready() || query == "" {
+		return nil
+	}
+	res, err := neo4j.ExecuteQuery(ctx, g.driver,
+		`MATCH (a:Entity {kb:$kb})-[r:REL]->(b:Entity {kb:$kb})
+		 WHERE $q CONTAINS a.name OR $q CONTAINS b.name
+		 RETURN a.name AS s, r.type AS p, b.name AS o LIMIT $k`,
+		map[string]any{"kb": kb, "q": query, "k": limit},
+		neo4j.EagerResultTransformer, neo4j.ExecuteQueryWithDatabase("neo4j"))
+	if err != nil {
+		return nil
+	}
+	var hits []Hit
+	for _, rec := range res.Records {
+		s, _ := rec.Get("s")
+		p, _ := rec.Get("p")
+		o, _ := rec.Get("o")
+		hits = append(hits, Hit{Text: fmt.Sprintf("%v —%v→ %v", s, p, o), Score: 1})
+	}
+	return hits
+}
+
+// triples 返回某 kb 的全部三元组（供 UI 图谱可视化）。
+func (g *graphStore) triples(ctx context.Context, kb string, limit int) []Triple {
+	if !g.ready() {
+		return nil
+	}
+	res, err := neo4j.ExecuteQuery(ctx, g.driver,
+		`MATCH (a:Entity {kb:$kb})-[r:REL]->(b:Entity {kb:$kb})
+		 RETURN a.name AS s, r.type AS p, b.name AS o LIMIT $k`,
+		map[string]any{"kb": kb, "k": limit},
+		neo4j.EagerResultTransformer, neo4j.ExecuteQueryWithDatabase("neo4j"))
+	if err != nil {
+		return nil
+	}
+	var out []Triple
+	for _, rec := range res.Records {
+		s, _ := rec.Get("s")
+		p, _ := rec.Get("p")
+		o, _ := rec.Get("o")
+		out = append(out, Triple{S: fmt.Sprint(s), P: fmt.Sprint(p), O: fmt.Sprint(o)})
+	}
+	return out
+}
+
+// extractTriples 用 LLM 从文本抽取知识三元组。
+func extractTriples(ctx context.Context, chat *chatClient, text string) ([]Triple, error) {
+	if !chat.ready() {
+		return nil, nil
+	}
+	const sys = "你是知识图谱抽取器。从用户文本中抽取知识三元组，输出 JSON 数组，每项形如 {\"s\":\"主体\",\"p\":\"关系\",\"o\":\"客体\"}。实体用简洁名词，关系用简短动词短语。只输出 JSON，不要任何解释或代码块标记。"
+	out, err := chat.complete(ctx, sys, text)
+	if err != nil {
+		return nil, err
+	}
+	return parseTriples(out), nil
+}
+
+// parseTriples 容忍代码块/前后噪声地解析三元组 JSON。
+func parseTriples(s string) []Triple {
+	s = strings.TrimSpace(s)
+	s = strings.TrimPrefix(s, "```json")
+	s = strings.TrimPrefix(s, "```")
+	s = strings.TrimSuffix(s, "```")
+	if i := strings.Index(s, "["); i >= 0 {
+		if j := strings.LastIndex(s, "]"); j > i {
+			s = s[i : j+1]
+		}
+	}
+	var triples []Triple
+	if json.Unmarshal([]byte(s), &triples) != nil {
+		return nil
+	}
+	return triples
+}