refactor: app.py

app.py

@@ -1,9 +1,15 @@
 import gradio as gr
 import json
 
-def auto_anno(txt, types, radio, need_trans=False):
+from utils.anno.cls.text_classification import text_classification
+from utils.anno.ner.entity_extract import extract_named_entities
+from utils.api.google_trans import en2cn
+from utils.format.txt_2_list import txt_2_list
+
+def auto_anno(txt, types_txt, radio, need_trans=False):
   if need_trans:
     txt = en2cn(txt)
+  types = txt_2_list(types_txt)
   if radio == '文本分类':
     result = text_classification(txt, types)
   if radio == '实体抽取':
@@ -18,18 +24,6 @@ output = gr.Textbox(label="输出结果")
 radio = gr.Radio(["文本分类", "实体抽取"], label="算法类型")
 checkbox = gr.Checkbox(label="翻译成中文")
 
-# 读取数据
-from utils.anno.cls.text_classification import text_classification
-from utils.anno.ner.entity_extract import extract_named_entities
-from utils.api.google_trans import en2cn
-
 if __name__ == '__main__':
-  # # 多文本分类
-  # txts = open('data/cls/jd.csv', 'r', encoding='utf-8').read().split('\n')[1:]
-  # txts = [txt.split(',')[0] for txt in txts if txt != '']
-
-  # results = []
-  # for txt in txts:
-  #   results.append(text_classification(txt, ['好评', '差评']))
   demo = gr.Interface(fn=auto_anno, inputs=[input1, input2, radio, checkbox], outputs=[output])
   demo.launch(share=False)