fix: OceanBase metadata not returned in document list API (#13209)

### What problem does this PR solve?

Fix #13144.

### Type of change

- [x] Bug Fix (non-breaking change which fixes an issue)

api/db/services/doc_metadata_service.py

@@ -102,13 +102,13 @@ class DocMetadataService:
     @classmethod
     def _iter_search_results(cls, results):
         """
-        Iterate over search results in various formats (DataFrame, ES, list).
+        Iterate over search results in various formats (DataFrame, ES, OceanBase, list).
 
         Yields:
             Tuple of (doc_id, doc_dict) for each document
 
         Args:
-            results: Search results from ES/Infinity in any format
+            results: Search results from ES/Infinity/OceanBase in any format
         """
         # Handle tuple return from Infinity: (DataFrame, int)
         # Check this FIRST because pandas DataFrames also have __getitem__
@@ -148,6 +148,14 @@ class DocMetadataService:
                     if doc_id:
                         yield doc_id, doc
 
+        # Check if OceanBase SearchResult format
+        elif hasattr(results, 'chunks') and hasattr(results, 'total'):
+            # OceanBase format: SearchResult(total=int, chunks=[{...}, {...}])
+            for doc in results.chunks:
+                doc_id = cls._extract_doc_id(doc)
+                if doc_id:
+                    yield doc_id, doc
+
     @classmethod
     def _search_metadata(cls, kb_id: str, condition: Dict = None, limit: int = 10000):
         """
@@ -367,7 +375,7 @@ class DocMetadataService:
             logging.debug(f"[update_document_metadata] Updating doc_id: {doc_id}, kb_id: {kb_id}, meta_fields: {processed_meta}")
 
             # For Elasticsearch, use efficient partial update
-            if not settings.DOC_ENGINE_INFINITY:
+            if not settings.DOC_ENGINE_INFINITY and not settings.DOC_ENGINE_OCEANBASE:
                 try:
                     # Use ES partial update API - much more efficient than delete+insert
                     settings.docStoreConn.es.update(

common/doc_store/ob_conn_base.py

@@ -24,7 +24,8 @@ from typing import Any
 
 from pymysql.converters import escape_string
 from pyobvector import ObVecClient, FtsIndexParam, FtsParser, VECTOR
-from sqlalchemy import Column, Table
+from sqlalchemy import Column, JSON, Table
+from sqlalchemy.dialects.mysql import VARCHAR
 
 from common.doc_store.doc_store_base import DocStoreConnection, MatchExpr, OrderByExpr
 
@@ -37,6 +38,15 @@ fulltext_search_template = "MATCH (%s) AGAINST ('%s' IN NATURAL LANGUAGE MODE)"
 vector_search_template = "cosine_distance(%s, '%s')"
 vector_column_pattern = re.compile(r"q_(?P<vector_size>\d+)_vec")
 
+# Document metadata table columns
+doc_meta_columns = [
+    Column("id", VARCHAR(256), primary_key=True, comment="document id"),
+    Column("kb_id", VARCHAR(256), nullable=False, comment="knowledge base id"),
+    Column("meta_fields", JSON, nullable=True, comment="document metadata fields"),
+]
+doc_meta_column_names = [col.name for col in doc_meta_columns]
+doc_meta_column_types = {col.name: col.type for col in doc_meta_columns}
+
 
 def get_value_str(value: Any) -> str:
     """Convert value to SQL string representation."""
@@ -266,19 +276,9 @@ class OBConnectionBase(DocStoreConnection):
         Table name pattern: ragflow_doc_meta_{tenant_id}
         - Per-tenant metadata table for storing document metadata fields
         """
-        from sqlalchemy import JSON
-        from sqlalchemy.dialects.mysql import VARCHAR
-
         table_name = index_name
         lock_prefix = self.get_lock_prefix()
 
-        # Define columns for document metadata table
-        doc_meta_columns = [
-            Column("id", VARCHAR(256), primary_key=True, comment="document id"),
-            Column("kb_id", VARCHAR(256), nullable=False, comment="knowledge base id"),
-            Column("meta_fields", JSON, nullable=True, comment="document metadata fields"),
-        ]
-
         try:
             # Create table with distributed lock
             _try_with_lock(
@@ -319,11 +319,17 @@ class OBConnectionBase(DocStoreConnection):
 
     def index_exist(self, index_name: str, dataset_id: str = None) -> bool:
         """Check if index/table exists."""
-        # For doc_meta tables, use index_name directly as table name
+        # For doc_meta tables, use index_name directly and only check table existence
+        # (metadata tables don't have fulltext/vector indexes that chunk tables have)
         if index_name.startswith("ragflow_doc_meta_"):
-            table_name = index_name
+            if index_name in self._table_exists_cache:
-        else:
+                return True
-            table_name = self.get_table_name(index_name, dataset_id) if dataset_id else index_name
+            if not self.client.check_table_exists(index_name):
+                return False
+            with self._table_exists_cache_lock:
+                self._table_exists_cache.add(index_name)
+            return True
+        table_name = self.get_table_name(index_name, dataset_id) if dataset_id else index_name
         return self._check_table_exists_cached(table_name)
 
     """

rag/utils/ob_conn.py

@@ -34,7 +34,8 @@ from common.doc_store.doc_store_base import MatchExpr, OrderByExpr, FusionExpr,
 from common.doc_store.ob_conn_base import (
     OBConnectionBase, get_value_str,
     vector_search_template, vector_column_pattern,
-    fulltext_index_name_template,
+    fulltext_index_name_template, doc_meta_column_names,
+    doc_meta_column_types,
 )
 from common.float_utils import get_float
 from rag.nlp import rag_tokenizer
@@ -135,8 +136,9 @@ class SearchResult(BaseModel):
 
 
 def get_column_value(column_name: str, value: Any) -> Any:
-    if column_name in column_types:
+    # Check chunk table columns first, then doc_meta table columns
-        column_type = column_types[column_name]
+    column_type = column_types.get(column_name) or doc_meta_column_types.get(column_name)
+    if column_type:
         if isinstance(column_type, String):
             return str(value)
         elif isinstance(column_type, Integer):
@@ -658,6 +660,12 @@ class OBConnection(OBConnectionBase):
             return result
 
         output_fields = select_fields.copy()
+        if "*" in output_fields:
+            if index_names[0].startswith("ragflow_doc_meta_"):
+                output_fields = doc_meta_column_names.copy()
+            else:
+                output_fields = column_names.copy()
+
         if "id" not in output_fields:
             output_fields = ["id"] + output_fields
         if "_score" in output_fields: