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40 lines
1.3 KiB
Python
40 lines
1.3 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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from typing import List
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from langchain.schema import Document
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from pilot.configs.model_config import KNOWLEDGE_CHUNK_SPLIT_SIZE
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from pilot.source_embedding import SourceEmbedding, register
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from pilot.source_embedding.chn_document_splitter import CHNDocumentSplitter
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from pilot.source_embedding.pdf_loader import UnstructuredPaddlePDFLoader
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class PDFEmbedding(SourceEmbedding):
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"""yuque embedding for read yuque document."""
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def __init__(self, file_path, model_name, vector_store_config):
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"""Initialize with pdf path."""
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super().__init__(file_path, model_name, vector_store_config)
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self.file_path = file_path
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self.model_name = model_name
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self.vector_store_config = vector_store_config
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@register
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def read(self):
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"""Load from pdf path."""
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loader = UnstructuredPaddlePDFLoader(self.file_path)
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textsplitter = CHNDocumentSplitter(pdf=True, sentence_size=KNOWLEDGE_CHUNK_SPLIT_SIZE)
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return loader.load_and_split(textsplitter)
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@register
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def data_process(self, documents: List[Document]):
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i = 0
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for d in documents:
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documents[i].page_content = d.page_content.replace("\n", "")
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i += 1
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return documents
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