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import gradio as gr
import json
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':
result = extract_named_entities(txt, types)
if need_trans:
result = f'{txt}\n{result}'
return result
input1 = gr.Textbox(lines=3, label="输入原句", value="Hello world!")
input2 = gr.Textbox(lines=3, label="输入类别", value="友好、不友好")
output = gr.Textbox(label="输出结果")
radio = gr.Radio(["文本分类", "实体抽取"], label="算法类型", value="文本分类")
checkbox = gr.Checkbox(label="翻译成中文")
if __name__ == '__main__':
demo = gr.Interface(
fn=auto_anno,
description='自动标注,使用了openai免费接口,1分钟内只能请求3次,如遇报错请稍后再试,或clone项目到本地后用自己的key替换。如有疑问欢迎联系微信 maqijun123456',
inputs=[input1, input2, radio, checkbox],
examples=[
['前四个月我国外贸进出口同比增长 5.8%', '政治;经济;科技;文化;娱乐;民生;军事;教育;环保;其它', '文本分类', False],
['There is a cat trapped on the Avenue of Happiness', '地点', '实体抽取', True],
['联系方式:18812345678,联系地址:幸福大街20号', '手机号、地址', '实体抽取', False],
],
outputs=[output]
)
demo.launch(share=False)
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