app.py

import gradio as gr
import hashlib
import tempfile
import requests
import pandas as pd
from TTS.utils.manage import ModelManager
from TTS.utils.synthesizer import Synthesizer
def fx(x:str):
    hash=hashlib.md5()
    hash.update(x.encode(encoding='utf-8'))
    return hash.hexdigest()
    
manager = ModelManager()
model_path, config_path, model_item = manager.download_model("tts_models/zh-CN/baker/tacotron2-DDC-GST")
synthesizer = Synthesizer(
    model_path, config_path, None, None, None,
)


def inference(text: str):
    wavs = synthesizer.tts(text)
    with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as fp:
        synthesizer.save_wav(wavs, fp)
        return fp.name

def fx_m(s:str):
    headers= {"Content-Type": "application/json"}
    url="https://m-formatter.azurewebsites.net/api/v2"
    data={'code':s,'resultType':'text'}
    respose=requests.post(url,json=data,headers=headers)
    ms=respose.json()
    return ms['result']

def fx_dax(s:str):
    url="https://www.daxformatter.com/"
    data = {"embed":"1","l":"short","fx":s}
    ct=requests.post(url = url,data = data)
    html=ct.text
    s1=html.split('<div class="result">')[1]
    s2='<div class="result">'+s1.split('<a href')[0]+'<a href="https://pbihub.cn/users/44" target="_top"><img src="https://pbihub.cn/uploads/avatars/44_1536391253.jpg?imageView2/1/w/380/h/380" alt="万剑归宗" class="badge" width="380" height="380"></a>'
    return s2
    
def fx_datatable(s:str):
    a=exec(s)
    return {k: v for k, v in locals().items() if isinstance(v,pd.DataFrame)}
    
def fx_dd(tk:str,s:str):
    headers= {"Content-Type": "application/json"}
    url="https://oapi.dingtalk.com/robot/send?access_token="+tk
    data={'msgtype':'text','text':{'title': '吹牛逼',"content": s}, 'at': {'atMobiles': [], 'isAtAll': True}}
    response=requests.post(url,json=data,headers=headers)
    return response.text    
        
def dd_ocr(tk,sl,dt):
    headers= {"Content-Type": "application/json"}
    url="https://oapi.dingtalk.com/topapi/ocr/structured/recognize?access_token="+tk
    dc={"身份证":"idcard","增值税发票":"invoice","营业执照":"blicense","银行卡":"bank_card","车牌":"car_no","机动车发票":"car_invoice","驾驶证":"driving_license","行驶证":"vehicle_license","火车票":"train_ticket","定额发票":"quota_invoice","出租车发票":"taxi_ticket","机票行程单":"air_itinerary","审批表单":"approval_table","花名册":"roster"}
    data={"image_url":sl,"type":dc[dt]}
    response=requests.post(url,json=data,headers=headers)
    return response.json()
            
demo=gr.Blocks()
with demo:
    with gr.Tabs():
        with gr.TabItem("测试1"):
            with gr.Column():
                text_input=gr.Textbox(placeholder='请输入测试字符串',label="请输入需要MD5加密的测试内容")
                text_output=gr.Textbox(label="输出",visible=False)
                text_input.change(fn=lambda visible: gr.update(visible=True), inputs=text_input, outputs=text_output)
                bb_button=gr.Button("运行")
                bb_button.click(fx, inputs=text_input, outputs=text_output,api_name='md5')
            with gr.Column():
                gr.Markdown("# TTS文本字符串转语音合成训练")
                TTS_input=gr.Textbox(label="输入文本",default="你好吗？我很好。") 
                TTS_button=gr.Button("合成")
                TTS_button.click(inference, inputs=TTS_input, outputs=gr.Audio(label="输出合成结果"),api_name='tts')
        with gr.TabItem("M-Formatter"):
            gr.Markdown("# PowerQuery M语言脚本格式化测试")
            M_input=gr.Textbox(label="请填写需要格式化的M脚本",default="let a=1,b=2 in a+b",lines=18)
            M_output=gr.Textbox(label="格式化结果",lines=50) 
            M_button=gr.Button("开始格式化>>")
            M_button.click(fx_m, inputs=M_input, outputs=M_output,api_name='M')
            
        with gr.TabItem("DAX-Formatter"):
            gr.Markdown("# DAX表达式格式化测试")
            with gr.Row():
                DAX_input=gr.Textbox(label="请填写需要格式化的DAX表达式",default="扯淡=CALCULATE(VALUES('价格表'[单价]),FILTER('价格表','价格表'[产品]='销售表'[产品]))",lines=28)
                DAX_button=gr.Button("格式化>>")
                DAX_output=gr.HTML(label="DAX表达式格式化结果") 
                DAX_button.click(fx_dax, inputs=DAX_input, outputs=DAX_output,api_name='DAX')

        with gr.TabItem("Python-Execute"):
            gr.Markdown("# Python脚本测试")
            d_input=gr.Textbox(label="请填写需要datatable库处理的脚本",lines=18)
            d_output=gr.JSON(label="输出>") 
            d_button=gr.Button("开始编译>>")
            d_button.click(fx_datatable, inputs=d_input, outputs=d_output,api_name='datatable')
            
        with gr.TabItem("钉钉群消息推送"):
            gr.Markdown("# 推送测试")
            dd_input=[gr.Textbox(label="请填写机器人token"),gr.Textbox(label="请填写需要推送的信息",lines=10)]
            dd_output=gr.Textbox(label="推送提示") 
            dd_button=gr.Button("提交")
            dd_button.click(fx_dd, inputs=dd_input, outputs=dd_output,api_name='dingding_robot')
            
        with gr.TabItem("钉钉ocr"):
            gr.Markdown("# 网络图片OCR识别")
            ocr_input=[gr.Textbox(label="请填写ocr_token"),gr.Textbox(label="请填写图片网址"),gr.Radio(["身份证","增值税发票","营业执照","银行卡","车牌","机动车发票","驾驶证","行驶证","火车票","定额发票","出租车发票","机票行程单","审批表单","花名册"],value="营业执照增值税发票",label="请选择识别类型：")]
            ocr_button=gr.Button("开始识别>>")
            ocr_output=gr.JSON(label="识别结果") 
            ocr_button.click(dd_ocr, inputs=ocr_input, outputs=ocr_output,api_name='dingding_ocr')
demo.launch()