Files
sundynix-agentix/sundynix-mcp-go/internal/rag/graph.go
T
Blizzard d623b8590e 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

159 lines
4.6 KiB
Go

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
}