chore: model.query change to db.session.query (#19551)

Co-authored-by: QuantumGhost <obelisk.reg+git@gmail.com>

api/services/vector_service.py

@@ -1,3 +1,4 @@
+import logging
 from typing import Optional
 
 from core.model_manager import ModelInstance, ModelManager
@@ -12,6 +13,8 @@ from models.dataset import ChildChunk, Dataset, DatasetProcessRule, DocumentSegm
 from models.dataset import Document as DatasetDocument
 from services.entities.knowledge_entities.knowledge_entities import ParentMode
 
+_logger = logging.getLogger(__name__)
+
 
 class VectorService:
     @classmethod
@@ -22,7 +25,14 @@ class VectorService:
 
         for segment in segments:
             if doc_form == IndexType.PARENT_CHILD_INDEX:
-                document = DatasetDocument.query.filter_by(id=segment.document_id).first()
+                document = db.session.query(DatasetDocument).filter_by(id=segment.document_id).first()
+                if not document:
+                    _logger.warning(
+                        "Expected DatasetDocument record to exist, but none was found, document_id=%s, segment_id=%s",
+                        segment.document_id,
+                        segment.id,
+                    )
+                    continue
                 # get the process rule
                 processing_rule = (
                     db.session.query(DatasetProcessRule)
@@ -52,7 +62,7 @@ class VectorService:
                     raise ValueError("The knowledge base index technique is not high quality!")
                 cls.generate_child_chunks(segment, document, dataset, embedding_model_instance, processing_rule, False)
             else:
-                document = Document(
+                document = Document(  # type: ignore
                     page_content=segment.content,
                     metadata={
                         "doc_id": segment.index_node_id,
@@ -64,7 +74,7 @@ class VectorService:
                 documents.append(document)
         if len(documents) > 0:
             index_processor = IndexProcessorFactory(doc_form).init_index_processor()
-            index_processor.load(dataset, documents, with_keywords=True, keywords_list=keywords_list)
+            index_processor.load(dataset, documents, with_keywords=True, keywords_list=keywords_list)  # type: ignore
 
     @classmethod
     def update_segment_vector(cls, keywords: Optional[list[str]], segment: DocumentSegment, dataset: Dataset):