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## What Adds [**SereneDB**](https://serenedb.com) as a selectable doc-store engine on **both** RAGFlow paths: - the **Go** `DocEngine` (`internal/engine/serenedb`), alongside Elasticsearch and Infinity; - the **Python** `DocStoreConnection` (`rag/utils/serenedb_conn.py`) + `DOC_ENGINE=serenedb` registration. SereneDB is a PostgreSQL-wire engine (DuckDB execution) whose single inverted index carries **both** a scored text column (`@@`, BM25) and an IVF vector column (`<#>`, inner product), so hybrid search is one SQL statement. The Go engine connects with `database/sql` + `lib/pq` (already a dependency, no new module); the Python connector uses psycopg2 (already a dependency). ## Storage model One table per tenant with `kb_id` as a filter column - the **Elasticsearch / OceanBase** model, not Infinity's per-dataset tables. This keeps BM25 statistics (IDF, avgdl) computed over the whole tenant corpus (global IDF). Both connectors use this identical layout, so they are storage- and retrieval-compatible: `hybrid` proxy routing and Python↔Go switching are safe. On the Python side the connector is wired as OceanBase's plain-SQL sibling (chunk_data JSON metadata, inline chunk vectors, verbatim ES field names); the ES tokenizer path is unchanged. Metadata stays one table per tenant (`ragflow_doc_meta_<tenant>`). The query shapes mirror the Python connector, including the five empirically-found landmines: the scored dictionary needs `frequency + norm` (else `BM25()` silently returns 0.0), the `@@` query is the tokenized query, the scored lexical branch matches one column, vectors use an L2-normalized shadow column with `ip`/`sq8`, and the similarity threshold goes directly in the ANN scan's `WHERE`. **Minimum engine version: SereneDB 26.07.4.** --------- Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>
270 lines
8.9 KiB
Go
270 lines
8.9 KiB
Go
//go:build integration
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//
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// Copyright 2026 The InfiniFlow Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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//
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// This end-to-end test drives the engine against a real SereneDB. It is
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// skipped unless SERENEDB_TEST_DSN points at a live instance (>= 26.07.4), so
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// the default test run stays pure and CI-safe. To run it:
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//
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// docker run -d --name serenedb-gotest -p 127.0.0.1:7899:7890 \
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// -e POSTGRES_PASSWORD=gotest serenedb/serenedb:26.07.4
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// SERENEDB_TEST_DSN='host=127.0.0.1 port=7899 user=postgres password=gotest dbname=postgres sslmode=disable' \
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// go test -run Integration -v ./internal/engine/serenedb/
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package serenedb
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import (
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"context"
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"os"
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"path/filepath"
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"sync"
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"testing"
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"time"
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"ragflow/internal/common"
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"ragflow/internal/engine/types"
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"ragflow/internal/server/config"
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)
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// logOnce initializes the shared logger the engine's Search path expects. In
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// production the server does this at startup; a bare `go test` does not.
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var logOnce sync.Once
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func liveEngine(t *testing.T) *serenedbEngine {
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t.Helper()
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dsn := os.Getenv("SERENEDB_TEST_DSN")
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if dsn == "" {
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t.Skip("SERENEDB_TEST_DSN not set; skipping live SereneDB integration test")
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}
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logOnce.Do(func() {
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_ = common.InitLogger("info", common.FileOutput{Path: filepath.Join(t.TempDir(), "serenedb-it.log")}, "serenedb-it")
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})
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t.Setenv("SERENEDB_DSN", dsn)
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e, err := NewEngine(config.SereneDBConfig{})
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if err != nil {
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t.Fatalf("NewEngine: %v", err)
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}
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return e
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}
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// waitForFulltext polls until the async inverted index has caught up with the
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// last write (SereneDB refreshes the index ~1s after insert, like ES).
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func waitForFulltext(t *testing.T, e *serenedbEngine, req *types.SearchRequest) *types.SearchResult {
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t.Helper()
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ctx := context.Background()
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deadline := time.Now().Add(15 * time.Second)
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for {
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res, err := e.Search(ctx, req)
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if err != nil {
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t.Fatalf("Search: %v", err)
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}
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if len(res.Chunks) > 0 || time.Now().After(deadline) {
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return res
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}
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time.Sleep(500 * time.Millisecond)
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}
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}
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func chunkIDs(res *types.SearchResult) []string {
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ids := make([]string, 0, len(res.Chunks))
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for _, c := range res.Chunks {
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if id, ok := c["id"].(string); ok {
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ids = append(ids, id)
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}
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}
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return ids
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}
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func contains(ids []string, want string) bool {
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for _, id := range ids {
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if id == want {
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return true
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}
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}
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return false
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}
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func TestIntegrationChunkLifecycle(t *testing.T) {
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e := liveEngine(t)
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defer e.Close()
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ctx := context.Background()
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const base = "ragflow_gotest"
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const kb = "kb1"
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// Start clean and always tear down the throwaway table.
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_ = e.DropChunkStore(ctx, base, kb)
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defer func() { _ = e.DropChunkStore(ctx, base, kb) }()
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if err := e.CreateChunkStore(ctx, base, kb, 4, ""); err != nil {
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t.Fatalf("CreateChunkStore: %v", err)
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}
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if ok, _ := e.ChunkStoreExists(ctx, base, kb); !ok {
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t.Fatal("ChunkStoreExists = false after create")
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}
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chunks := []map[string]interface{}{
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{"id": "a", "doc_id": "d1", "kb_id": kb, "content_ltks": "alpha beta", "content_with_weight": "alpha beta", "q_4_vec": []float64{1, 0, 0, 0}, "important_kwd": []interface{}{"alpha"}},
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{"id": "b", "doc_id": "d1", "kb_id": kb, "content_ltks": "gamma delta", "content_with_weight": "gamma delta", "q_4_vec": []float64{0, 1, 0, 0}, "important_kwd": []interface{}{"gamma"}},
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{"id": "c", "doc_id": "d2", "kb_id": kb, "content_ltks": "alpha gamma", "content_with_weight": "alpha gamma", "q_4_vec": []float64{0.9, 0.1, 0, 0}, "important_kwd": []interface{}{"alpha", "gamma"}},
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}
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if _, err := e.InsertChunks(ctx, chunks, base, kb); err != nil {
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t.Fatalf("InsertChunks: %v", err)
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}
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req := func(exprs []interface{}, filter map[string]interface{}) *types.SearchRequest {
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return &types.SearchRequest{
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IndexNames: []string{base}, KbIDs: []string{kb},
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Limit: 10, MatchExprs: exprs, Filter: filter,
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}
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}
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t.Run("fulltext", func(t *testing.T) {
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res := waitForFulltext(t, e, req([]interface{}{
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&types.MatchTextExpr{MatchingText: "alpha", TopN: 10},
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}, nil))
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ids := chunkIDs(res)
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if !contains(ids, "a") || !contains(ids, "c") {
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t.Fatalf("fulltext 'alpha' should match a and c, got %v", ids)
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}
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if contains(ids, "b") {
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t.Fatalf("fulltext 'alpha' should not match b, got %v", ids)
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}
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for _, ch := range res.Chunks {
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if _, ok := ch["_score"].(float64); !ok {
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t.Errorf("chunk %v missing float _score", ch["id"])
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}
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}
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})
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t.Run("vector", func(t *testing.T) {
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res := waitForFulltext(t, e, req([]interface{}{
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&types.MatchDenseExpr{VectorColumnName: "q_4_vec", EmbeddingData: []float64{1, 0, 0, 0}, TopN: 10},
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}, nil))
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ids := chunkIDs(res)
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if len(ids) == 0 || ids[0] != "a" {
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t.Fatalf("vector query [1,0,0,0] should rank 'a' first, got %v", ids)
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}
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})
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t.Run("fusion", func(t *testing.T) {
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res := waitForFulltext(t, e, req([]interface{}{
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&types.MatchTextExpr{MatchingText: "alpha", TopN: 10},
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&types.MatchDenseExpr{VectorColumnName: "q_4_vec", EmbeddingData: []float64{1, 0, 0, 0}, TopN: 10},
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&types.FusionExpr{Method: "weighted_sum", FusionParams: map[string]interface{}{"weights": "0.3,0.7"}},
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}, nil))
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ids := chunkIDs(res)
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if len(ids) == 0 || ids[0] != "a" {
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t.Fatalf("fusion(alpha, [1,0,0,0]) should rank 'a' first, got %v", ids)
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}
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})
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t.Run("filter_only", func(t *testing.T) {
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res, err := e.Search(ctx, req(nil, map[string]interface{}{"doc_id": "d2"}))
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if err != nil {
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t.Fatalf("filter search: %v", err)
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}
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ids := chunkIDs(res)
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if len(ids) != 1 || ids[0] != "c" {
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t.Fatalf("filter doc_id=d2 should return only c, got %v", ids)
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}
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})
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t.Run("get_and_scores", func(t *testing.T) {
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got, err := e.GetChunk(ctx, base, "a", []string{kb})
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if err != nil || got == nil {
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t.Fatalf("GetChunk(a) = %v, %v", got, err)
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}
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m := got.(map[string]interface{})
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if m["content_ltks"] != "alpha beta" {
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t.Errorf("GetChunk content = %v", m["content_ltks"])
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}
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// important_kwd is a native array column.
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if arr, ok := m["important_kwd"].([]string); !ok || len(arr) == 0 || arr[0] != "alpha" {
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t.Errorf("important_kwd not decoded as array: %v", m["important_kwd"])
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}
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res := waitForFulltext(t, e, req([]interface{}{
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&types.MatchTextExpr{MatchingText: "alpha", TopN: 10},
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}, nil))
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knn, _ := e.KNNScores(ctx, res.Chunks, nil, 10)
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scores := e.GetScores(knn)
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if _, ok := scores["a"]; !ok {
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t.Errorf("GetScores missing 'a': %v", scores)
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}
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})
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t.Run("update_and_delete", func(t *testing.T) {
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if err := e.UpdateChunks(ctx,
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map[string]interface{}{"id": "b"},
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map[string]interface{}{"add": map[string]interface{}{"tag_kwd": "x"}},
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base, kb); err != nil {
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t.Fatalf("UpdateChunks add: %v", err)
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}
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n, err := e.DeleteChunks(ctx, map[string]interface{}{"id": "b"}, base, kb)
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if err != nil || n != 1 {
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t.Fatalf("DeleteChunks(b) = %d, %v (want 1)", n, err)
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}
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})
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}
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func TestIntegrationMetadata(t *testing.T) {
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e := liveEngine(t)
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defer e.Close()
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ctx := context.Background()
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const tenant = "gotest_tenant"
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_ = e.DropMetadataStore(ctx, tenant)
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defer func() { _ = e.DropMetadataStore(ctx, tenant) }()
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if err := e.CreateMetadataStore(ctx, tenant); err != nil {
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t.Fatalf("CreateMetadataStore: %v", err)
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}
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if _, err := e.InsertMetadata(ctx, []map[string]interface{}{
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{"id": "doc1", "kb_id": "kb1", "meta_fields": map[string]interface{}{"author": "ann", "year": float64(2026)}},
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}, tenant); err != nil {
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t.Fatalf("InsertMetadata: %v", err)
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}
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// Merge update preserves untouched keys.
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if err := e.UpdateMetadata(ctx, "doc1", "kb1", map[string]interface{}{"author": "bob"}, tenant); err != nil {
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t.Fatalf("UpdateMetadata: %v", err)
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}
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res, err := e.SearchMetadata(ctx, &types.SearchMetadataRequest{TenantID: tenant, Limit: 10})
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if err != nil {
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t.Fatalf("SearchMetadata: %v", err)
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}
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if res.Total != 1 || len(res.MetadataRecords) != 1 {
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t.Fatalf("SearchMetadata total=%d records=%d", res.Total, len(res.MetadataRecords))
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}
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mf, ok := res.MetadataRecords[0]["meta_fields"].(map[string]interface{})
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if !ok {
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t.Fatalf("meta_fields not decoded to map: %v", res.MetadataRecords[0]["meta_fields"])
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}
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if mf["author"] != "bob" {
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t.Errorf("merge should set author=bob, got %v", mf["author"])
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}
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if _, ok := mf["year"]; !ok {
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t.Errorf("merge should preserve year, got %v", mf)
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}
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if err := e.DeleteMetadataKeys(ctx, "doc1", "kb1", []string{"year"}, tenant); err != nil {
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t.Fatalf("DeleteMetadataKeys: %v", err)
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}
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after, _ := e.loadMetaFields(ctx, buildMetadataTableName(tenant), "doc1", "kb1")
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if _, ok := after["year"]; ok {
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t.Errorf("year should be removed, got %v", after)
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}
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}
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