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                        - 
 - from typing import Optional, List
 - 
 - from langchain.schema import Document
 - 
 - from core.index.index import IndexBuilder
 - 
 - from models.dataset import Dataset, DocumentSegment
 - 
 - 
 - class VectorService:
 - 
 -     @classmethod
 -     def create_segment_vector(cls, keywords: Optional[List[str]], segment: DocumentSegment, dataset: Dataset):
 -         document = Document(
 -             page_content=segment.content,
 -             metadata={
 -                 "doc_id": segment.index_node_id,
 -                 "doc_hash": segment.index_node_hash,
 -                 "document_id": segment.document_id,
 -                 "dataset_id": segment.dataset_id,
 -             }
 -         )
 - 
 -         # save vector index
 -         index = IndexBuilder.get_index(dataset, 'high_quality')
 -         if index:
 -             index.add_texts([document], duplicate_check=True)
 - 
 -         # save keyword index
 -         index = IndexBuilder.get_index(dataset, 'economy')
 -         if index:
 -             if keywords and len(keywords) > 0:
 -                 index.create_segment_keywords(segment.index_node_id, keywords)
 -             else:
 -                 index.add_texts([document])
 - 
 -     @classmethod
 -     def multi_create_segment_vector(cls, pre_segment_data_list: list, dataset: Dataset):
 -         documents = []
 -         for pre_segment_data in pre_segment_data_list:
 -             segment = pre_segment_data['segment']
 -             document = Document(
 -                 page_content=segment.content,
 -                 metadata={
 -                     "doc_id": segment.index_node_id,
 -                     "doc_hash": segment.index_node_hash,
 -                     "document_id": segment.document_id,
 -                     "dataset_id": segment.dataset_id,
 -                 }
 -             )
 -             documents.append(document)
 - 
 -         # save vector index
 -         index = IndexBuilder.get_index(dataset, 'high_quality')
 -         if index:
 -             index.add_texts(documents, duplicate_check=True)
 - 
 -         # save keyword index
 -         keyword_index = IndexBuilder.get_index(dataset, 'economy')
 -         if keyword_index:
 -             keyword_index.multi_create_segment_keywords(pre_segment_data_list)
 - 
 -     @classmethod
 -     def update_segment_vector(cls, keywords: Optional[List[str]], segment: DocumentSegment, dataset: Dataset):
 -         # update segment index task
 -         vector_index = IndexBuilder.get_index(dataset, 'high_quality')
 -         kw_index = IndexBuilder.get_index(dataset, 'economy')
 -         # delete from vector index
 -         if vector_index:
 -             vector_index.delete_by_ids([segment.index_node_id])
 - 
 -         # delete from keyword index
 -         kw_index.delete_by_ids([segment.index_node_id])
 - 
 -         # add new index
 -         document = Document(
 -             page_content=segment.content,
 -             metadata={
 -                 "doc_id": segment.index_node_id,
 -                 "doc_hash": segment.index_node_hash,
 -                 "document_id": segment.document_id,
 -                 "dataset_id": segment.dataset_id,
 -             }
 -         )
 - 
 -         # save vector index
 -         if vector_index:
 -             vector_index.add_texts([document], duplicate_check=True)
 - 
 -         # save keyword index
 -         if keywords and len(keywords) > 0:
 -             kw_index.create_segment_keywords(segment.index_node_id, keywords)
 -         else:
 -             kw_index.add_texts([document])
 
 
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