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import numpy as np
import gradio as gr

def flip_text(x):
    return x[::-1]

def extract_qa(question):
    """
        抽取式qa
    """
    return question

def flip_image(x):
    return np.fliplr(x)

with gr.Blocks() as demo:
    gr.Markdown("""
        # 自研大语言模型DEMO
        - 抽取式QA
        - 小区测评
    """)
    with gr.Tab("抽取式QA"):
        text_input = gr.Textbox(label="输入",placeholder="默认值")
        gr.Examples(["出租出去的房屋家电坏了,应该谁负责出维修费用?", "退租房东不还押金怎么办?"], inputs=text_input)
        text_button = gr.Button("提交")
        text_output = gr.Textbox(label="输出")

    with gr.Tab("小区测评"):
        #text_input = gr.Textbox()
        text_input = gr.Textbox(label="输入",placeholder="默认值")
        gr.Examples(["出租出去的房屋家电坏了,应该谁负责出维修费用?", "退租房东不还押金怎么办?"], inputs=text_input)
        #text_output = gr.Textbox()
        text_button = gr.Button("提交")
        text_output = gr.Textbox(label="输出")

    with gr.Tab("图像测试"):
        with gr.Row():
            image_input = gr.Image()
            image_output = gr.Image()
        image_button = gr.Button("翻转")

    with gr.Accordion("备注"):
        gr.Markdown("DEMO基于幸福里策略算法组自研大语言模型")

    text_button.click(extract_qa, inputs=text_input, outputs=text_output)
    #text_button.click(flip_text, inputs=text_input, outputs=text_output)
    image_button.click(flip_image, inputs=image_input, outputs=image_output)

demo.launch(share=True)