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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>
35 lines
1.6 KiB
Go
35 lines
1.6 KiB
Go
//
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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 serenedb implements the doc-store DocEngine backed by SereneDB, a
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// PostgreSQL-wire engine whose single inverted index carries both a scored
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// text column (@@, BM25) and an IVF vector column (<#>, inner product), so
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// hybrid search is one SQL statement. It connects with database/sql + lib/pq
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// and emits SQL directly; the query shapes mirror the Python
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// SereneDBConnection (rag/utils/serenedb_conn.py) that reached Elasticsearch
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// retrieval parity.
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//
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// Table layout follows the Elasticsearch/OceanBase model: one chunk table per
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// tenant (the index name) with kb_id as a filter column, so BM25 statistics are
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// computed over the whole tenant corpus. Metadata is one table per tenant
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// (ragflow_doc_meta_{tenantID}).
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//
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// Minimum engine version: SereneDB 26.07.4. The vector-branch and fusion
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// queries use the natural forms that rely on the 26.07.4 fixes for the
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// vector-op predicate in an ANN scan's WHERE and the multi-reference index
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// CTE; on earlier builds both silently returned empty.
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package serenedb
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