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41 lines
1.4 KiB
Markdown
41 lines
1.4 KiB
Markdown
PPTEmbedding
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==================================
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ppt embedding can import ppt text into a vector knowledge base. The entire embedding process includes the read (loading data), data_process (data processing), and index_to_store (embedding to the vector database) methods.
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inheriting the SourceEmbedding
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```
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class PPTEmbedding(SourceEmbedding):
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"""ppt embedding for read ppt document."""
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def __init__(self, file_path, vector_store_config):
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"""Initialize with pdf path."""
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super().__init__(file_path, vector_store_config)
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self.file_path = file_path
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self.vector_store_config = vector_store_config
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```
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implement read() and data_process()
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read() method allows you to read data and split data into chunk
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```
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@register
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def read(self):
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"""Load from ppt path."""
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loader = UnstructuredPowerPointLoader(self.file_path)
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textsplitter = SpacyTextSplitter(
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pipeline="zh_core_web_sm",
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chunk_size=CFG.KNOWLEDGE_CHUNK_SIZE,
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chunk_overlap=200,
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)
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return loader.load_and_split(textsplitter)
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```
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data_process() method allows you to pre processing your ways
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```
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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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```
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