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25b46a7b9e
* Add files via upload * Update local_doc_qa.py * Update model_config.py * Update zh_title_enhance.py * Add files via upload * Update README.md * fix bugs in MyFAISS.delete_doc * fix:前端知识库获取失败. * update zh_title_enhance.py * update zh_title_enhance.py * Update zh_title_enhance.py * add test/textsplitter * add test_zh_title_enhance.py --------- Co-authored-by: imClumsyPanda <littlepanda0716@gmail.com> Co-authored-by: JZF <jiangzhifeng_jzf@163.com> Co-authored-by: fxjhello <127916299+fxjhello@users.noreply.github.com>
22 lines
871 B
Python
22 lines
871 B
Python
from configs.model_config import *
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from langchain.embeddings.huggingface import HuggingFaceEmbeddings
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import nltk
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from vectorstores import MyFAISS
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from chains.local_doc_qa import load_file
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nltk.data.path = [NLTK_DATA_PATH] + nltk.data.path
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if __name__ == "__main__":
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filepath = os.path.join(os.path.dirname(os.path.dirname(os.path.dirname(__file__))),
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"knowledge_base", "samples", "content", "test.txt")
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embeddings = HuggingFaceEmbeddings(model_name=embedding_model_dict[EMBEDDING_MODEL],
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model_kwargs={'device': EMBEDDING_DEVICE})
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docs = load_file(filepath, using_zh_title_enhance=True)
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vector_store = MyFAISS.from_documents(docs, embeddings)
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query = "指令提示技术有什么示例"
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search_result = vector_store.similarity_search(query)
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print(search_result)
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pass
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