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 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])