add app

app.py

@@ -44,10 +44,10 @@ def predict(model_name, text):
     return_all_scores=True,
     function_to_apply='sigmoid'
     )
-
-    for result in pipe(text):
-        print(result)
-    return result
+    output = []
+    for result in pipe(text)[0]:
+        output.append(result+'\n')
+    return output
 
 if __name__ == '__main__':
     exam1 = '경기도 성남시 수정구 태평3동은 우리 동네야!'
@@ -70,8 +70,6 @@ if __name__ == '__main__':
             [MODEL_BUF["name"], exam3]
             ],
         title="한국어 혐오표현, 개인정보 판별기 (Korean Hate Speech and Privacy Detection)",
-        description="Korean Hate Speech and Privacy Detection.\n \
-        15개 label Detection: 여성/가족, 남성, 성소수자, 인종/국적, 연령, 지역, 종교, 기타 혐오, 악플/욕설, clean, name, number, address, bank, person\n \
-        Current Supported Model:\n1. momo/KcELECTRA-base_Hate_speech_Privacy_Detection\n2. momo/KcBERT-base_Hate_speech_Privacy_Detection."
+        description="Korean Hate Speech and Privacy Detection.\n15개 label Detection:\ 여성/가족, 남성, 성소수자, 인종/국적, 연령, 지역, 종교, 기타 혐오, 악플/욕설, clean, name, number, address, bank, person\nCurrent Supported Model:\n1. momo/KcELECTRA-base_Hate_speech_Privacy_Detection\n2. momo/KcBERT-base_Hate_speech_Privacy_Detection."
         )
     app.launch()