2026-03-04 19:17:16 +08:00
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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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package engine
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import (
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"fmt"
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2026-05-06 10:41:58 +08:00
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"ragflow/internal/common"
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2026-06-12 14:56:44 +08:00
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"ragflow/internal/engine/nats"
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2026-03-04 19:17:16 +08:00
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"ragflow/internal/server"
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"sync"
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"ragflow/internal/engine/elasticsearch"
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"ragflow/internal/engine/infinity"
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feat(serenedb): add SereneDB doc-store engine (Go + Python connectors) (#17375)
## 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>
2026-08-04 08:16:39 +02:00
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"ragflow/internal/engine/serenedb"
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2026-06-12 14:56:44 +08:00
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2026-06-18 18:07:27 +08:00
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"ragflow/internal/tokenizer"
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2026-07-02 21:21:10 +08:00
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"go.uber.org/zap"
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2026-03-04 19:17:16 +08:00
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)
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var (
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globalEngine DocEngine
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2026-07-31 17:18:45 +08:00
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engineType string
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messageQueueEngine MessageQueue
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once sync.Once
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2026-03-04 19:17:16 +08:00
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)
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2026-08-02 20:55:19 +08:00
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// InitDocEngine initializes document engine
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func InitDocEngine() error {
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var initErr error
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once.Do(func() {
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2026-07-31 17:18:45 +08:00
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globalConfig := server.GetConfig()
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engineType = globalConfig.DocEngineType()
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tokenizer.SetEngineType(engineType)
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2026-03-04 19:17:16 +08:00
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var err error
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2026-04-24 15:30:14 +08:00
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switch engineType {
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2026-07-31 17:18:45 +08:00
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case "elasticsearch":
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globalEngine, err = elasticsearch.NewEngine(globalConfig.GetElasticsearchConfig())
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case "infinity":
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globalEngine, err = infinity.NewEngine(globalConfig.GetInfinityConfig())
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feat(serenedb): add SereneDB doc-store engine (Go + Python connectors) (#17375)
## 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>
2026-08-04 08:16:39 +02:00
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case "serenedb":
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globalEngine, err = serenedb.NewEngine(globalConfig.GetSereneDBConfig())
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2026-03-04 19:17:16 +08:00
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default:
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err = fmt.Errorf("unsupported doc engine type: %s", engineType)
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}
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if err != nil {
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initErr = fmt.Errorf("failed to create doc engine: %w", err)
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return
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}
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2026-07-31 17:18:45 +08:00
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common.Info("Doc engine initialized", zap.String("type", engineType))
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2026-03-04 19:17:16 +08:00
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})
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return initErr
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}
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2026-04-24 15:30:14 +08:00
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// GetEngineType returns the document engine type
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func GetEngineType() string {
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return engineType
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}
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2026-03-04 19:17:16 +08:00
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// Get gets global document engine instance
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func Get() DocEngine {
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return globalEngine
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}
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// Close closes document engine
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func Close() error {
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if globalEngine != nil {
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return globalEngine.Close()
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}
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return nil
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}
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2026-06-12 14:56:44 +08:00
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func GetMessageQueueEngine() MessageQueue {
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return messageQueueEngine
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}
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2026-07-31 11:25:26 +08:00
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// SetMessageQueueEngine installs the global message-queue engine. It exists
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// primarily as a test seam so callers can drive Start() without a real server
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2026-08-02 20:55:19 +08:00
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// config; production code uses InitMessageQueue.
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2026-07-31 11:25:26 +08:00
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func SetMessageQueueEngine(mq MessageQueue) {
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messageQueueEngine = mq
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}
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2026-08-02 20:55:19 +08:00
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func InitMessageQueue() error {
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globalConfig := server.GetConfig()
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messageQueueType := globalConfig.QueueEngineType()
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2026-06-12 14:56:44 +08:00
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switch messageQueueType {
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case "nats":
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2026-07-31 17:18:45 +08:00
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natsConfig := globalConfig.GetNATSConfig()
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messageQueueEngine = nats.NewNatsEngine(natsConfig.Host, natsConfig.Port)
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2026-06-12 14:56:44 +08:00
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err := messageQueueEngine.Init()
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if err != nil {
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return err
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}
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2026-07-02 21:21:10 +08:00
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case "":
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return fmt.Errorf("message queue type is empty")
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2026-06-12 14:56:44 +08:00
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default:
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return fmt.Errorf("unsupported message queue type: %s", messageQueueType)
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}
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return nil
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}
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