update test.

.github/workflows/ubuntu.yml

@@ -47,6 +47,7 @@ jobs:
         run: |
           pip install -r requirements.txt
           pip install .
+          pip install pytest
       - name: PKG-TEST
         run: |
-          python -m unittest discover tests/
+          python -m pytest

README.md

@@ -439,7 +439,7 @@ version = {1.0.1}
 项目代码还很粗糙，如果大家对代码有所改进，欢迎提交回本项目，在提交之前，注意以下两点：
 
 - 在`tests`添加相应的单元测试
-- 使用`python setup.py test`来运行所有单元测试，确保所有单测都是通过的
+- 使用`python -m pytest`来运行所有单元测试，确保所有单测都是通过的
 
 之后即可提交PR。
 

requirements.txt

@@ -1,7 +1,7 @@
 text2vec>=1.1.5
 jieba>=0.39
 loguru
-transformers>=4.6.0
+transformers
 Pillow
 hnswlib
 annoy

setup.py

@@ -42,7 +42,7 @@ setup(
     keywords='similarities,Chinese Text Similarity Calculation Tool,similarity,word2vec',
     install_requires=[
         "text2vec>=1.1.5",
-        "transformers>=4.6.0",
+        "transformers",
         "jieba>=0.39",
         "loguru",
         "Pillow",

tests/test_sim_score.py

@@ -36,6 +36,22 @@ class SimScoreTestCase(unittest.TestCase):
         self.assertEqual(len(r), 2)
         self.assertEqual(len(r[0]), 0)
 
+    def test_case(self):
+        cases = [("牙疼有蛀牙怎么办", "手机前十名排行榜"),
+                 ("小游戏,下载", "干洗机什么牌子的好"),
+                 ("如何恢复微信里面的聊天记录", "吸氢气机"),
+                 ("胃病症状的早期表现", "胃溃疡症状"), ]
+        for i in cases:
+            print(i)
+            r = m.similarity(i[0], i[1])
+            print(r)
+        print("-" * 50)
+        new_m = Similarity(model_name_or_path="sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2")
+        for i in cases:
+            print(i)
+            r = new_m.similarity(i[0], i[1])
+            print(r)
+
 
 if __name__ == '__main__':
     unittest.main()