diff --git a/rag/src/util/text_seg.py b/rag/src/util/text_seg.py
new file mode 100644
index 0000000..1d54f91
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+++ b/rag/src/util/text_seg.py
@@ -0,0 +1,62 @@
+# 对文本类的（非QA对）数据做切分 --- 使用qwen的api对书籍进行语义分割
+import json
+import random
+import argparse
+import yaml
+import re
+import copy
+
+from tqdm import tqdm
+
+# config.yml文件由自己定义
+with open('config.yml', 'r', encoding='utf-8') as f:
+    configs = yaml.load(f.read(), Loader=yaml.FullLoader)
+
+def qwen_api(content):
+    import dashscope
+    from http import HTTPStatus
+
+    Input = '''我们的分割要求是每一个划分占一行，请你帮我将下列txt文本按照书本的内容（比如：事件的背景，心理学名词的定义，特点，阶段划分，实验内容等）进行划分，要求文本内容不能缩减，也可以按照语义分割，比如某几句话都是讲的一回事就划分一行，要求划分之后的文本内容详细，主题明确，要求每一个划分仅用一行表示。以下为要求分割的txt文本：{}
+        '''.format(content)
+
+    dashscope.api_key = configs['dashscope_api_key']
+    response = dashscope.Generation.call(
+        model='qwen-max',
+        prompt=Input,
+        history=[],
+    )
+
+    if response.status_code == HTTPStatus.OK:
+        result = response.output.text
+        print(result)
+    else:
+        result = 'ERROR'
+    return result
+
+
+def save_jsonl(data_lis, file_path):
+    import json
+
+    # 将字典列表写入文件，每一行一个字典
+    with open(file_path, 'at', encoding='utf-8') as file:
+        for item in data_lis:
+            json_string = json.dumps(item, ensure_ascii=False) + '\n'
+            file.write(json_string)
+
+
+if __name__ == '__main__':
+    file_name = 'a0.jsonl'
+    conversations = []
+    path = configs['txt_path']
+    f = open(path, 'r', encoding='utf-8')
+    str = f.read()
+    f.close()
+    for i in tqdm(range(0, len(str), 2500)):
+        # 保证所有文本都能按照完整的语义进行分割
+        content = str[i:i+3500]
+        print(content)
+        answer = qwen_api(content)
+
+        f2 = open('seg1.txt', 'a', encoding='utf-8')
+        f2.write(answer)
+        f2.close()
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