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>

common/settings.py

@@ -85,6 +85,7 @@ OAUTH_CONFIG = None
 DOC_ENGINE = os.getenv("DOC_ENGINE", "elasticsearch")
 DOC_ENGINE_INFINITY = DOC_ENGINE.lower() == "infinity"
 DOC_ENGINE_OCEANBASE = DOC_ENGINE.lower() == "oceanbase"
+DOC_ENGINE_SERENEDB = DOC_ENGINE.lower() == "serenedb"
 
 
 docStoreConn = None
@@ -123,6 +124,7 @@ OB = {}
 OSS = {}
 OS = {}
 GCS = {}
+SERENEDB = {}
 
 DOC_MAXIMUM_SIZE: int = 128 * 1024 * 1024
 DOC_BULK_SIZE: int = 32
@@ -301,10 +303,11 @@ def init_settings():
     FEISHU_OAUTH = get_base_config("oauth", {}).get("feishu")
     OAUTH_CONFIG = get_base_config("oauth", {})
 
-    global DOC_ENGINE, DOC_ENGINE_INFINITY, DOC_ENGINE_OCEANBASE, docStoreConn, ES, OB, OS, INFINITY
+    global DOC_ENGINE, DOC_ENGINE_INFINITY, DOC_ENGINE_OCEANBASE, DOC_ENGINE_SERENEDB, docStoreConn, ES, OB, OS, INFINITY, SERENEDB
     DOC_ENGINE = os.environ.get("DOC_ENGINE", "elasticsearch").strip()
     DOC_ENGINE_INFINITY = DOC_ENGINE.lower() == "infinity"
     DOC_ENGINE_OCEANBASE = DOC_ENGINE.lower() == "oceanbase"
+    DOC_ENGINE_SERENEDB = DOC_ENGINE.lower() == "serenedb"
     lower_case_doc_engine = DOC_ENGINE.lower()
     if lower_case_doc_engine == "elasticsearch":
         ES = get_base_config("es", {})
@@ -321,6 +324,12 @@ def init_settings():
     elif lower_case_doc_engine == "seekdb":
         OB = get_base_config("seekdb", {})
         docStoreConn = rag.utils.ob_conn.OBConnection()
+    elif lower_case_doc_engine == "serenedb":
+        SERENEDB = get_base_config("serenedb", {})
+        # Imported lazily so psycopg2/SereneDB is only touched when selected.
+        from rag.utils import serenedb_conn
+
+        docStoreConn = serenedb_conn.SereneDBConnection()
     else:
         raise Exception(f"Not supported doc engine: {DOC_ENGINE}")