[全量] 初始化项目代码、配置、文档及Agent协同harness

langchain-chat/text_splitter/ali_text_splitter.py

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+from langchain.text_splitter import CharacterTextSplitter
+import re
+from typing import List
+
+
+class AliTextSplitter(CharacterTextSplitter):
+    def __init__(self, pdf: bool = False, **kwargs):
+        super().__init__(**kwargs)
+        self.pdf = pdf
+
+    def split_text(self, text: str) -> List[str]:
+        # use_document_segmentation参数指定是否用语义切分文档，此处采取的文档语义分割模型为达摩院开源的nlp_bert_document-segmentation_chinese-base，论文见https://arxiv.org/abs/2107.09278
+        # 如果使用模型进行文档语义切分，那么需要安装modelscope[nlp]：pip install "modelscope[nlp]" -f https://modelscope.oss-cn-beijing.aliyuncs.com/releases/repo.html
+        # 考虑到使用了三个模型，可能对于低配置gpu不太友好，因此这里将模型load进cpu计算，有需要的话可以替换device为自己的显卡id
+        if self.pdf:
+            text = re.sub(r"\n{3,}", r"\n", text)
+            text = re.sub('\s', " ", text)
+            text = re.sub("\n\n", "", text)
+        try:
+            from modelscope.pipelines import pipeline
+        except ImportError:
+            raise ImportError(
+                "Could not import modelscope python package. "
+                "Please install modelscope with `pip install modelscope`. "
+            )
+
+
+        p = pipeline(
+            task="document-segmentation",
+            model='damo/nlp_bert_document-segmentation_chinese-base',
+            device="cpu")
+        result = p(documents=text)
+        sent_list = [i for i in result["text"].split("\n\t") if i]
+        return sent_list