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