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# Helsinki-NLP/opus-mt-zh-en
import gradio as gr
from transformers import pipeline
import os

# def test(text):
#     return text
# inputs=gr.TextArea(lines=10,label='请输入英文字段名',placeholder='以换行\\n为分隔符')
# outputs=gr.TextArea(lines=10,label='转译结果')
# interface = gr.Interface(fn=test, inputs=inputs, outputs=outputs)
# interface.launch()

# translator = pipeline("translation", model=os.path.join(os.getcwd(),"test-ml-trained"), max_time=5)
# # list-list
# def en2zh(EnNames):
#     pres=[]
#     for name in EnNames:
#         pre = translator(name[0].replace('_',' '), )[0]["translation_text"]
#         pres.append([pre])
#         print(name,pre)
#     return pres
# interface = gr.Interface(fn=en2zh, inputs="list", outputs="list")
# interface.launch()

translator = pipeline("translation", model=os.path.join(os.getcwd(),"test-ml-trained+"), max_time=5)
# text-text
def en2zh(text):
    pres=[]
    enNames=text.split('\n')
    for name in enNames:
        pre = translator(name.replace('_',' '), )[0]["translation_text"]
        pres.append(pre)
        print(name,pre)
    return '\n'.join(pres)
inputs=gr.TextArea(lines=10,label='请输入英文字段名',placeholder='以换行\\n为分隔符')
outputs=gr.TextArea(lines=10,label='转译结果')
interface = gr.Interface(fn=en2zh, inputs=inputs, outputs=outputs)
interface.launch()