File size: 7,595 Bytes
3b87861 0c63622 68322e2 676f81f 1e14657 676f81f 3b87861 c451602 1e14657 676f81f 4cad25d 630c584 4cad25d 630c584 8a8ce66 157537f 0c3cdf9 157537f 9b1c0bb dfcaf77 676f81f b24edfb 98cf4b9 b24edfb fb273d7 445ff53 71955cc 1e14657 180eaf9 da43c80 28e1c18 1926a35 322a014 f9be81d 04edcd6 bab8483 676f81f 5103506 12e6a54 e5cd431 676f81f f018e3b 4cad25d fb872a3 4cad25d 676f81f f018e3b 4cad25d fb872a3 4cad25d 157537f fb872a3 157537f 9b1c0bb dfcaf77 9b1c0bb 28e1c18 676f81f 98cf4b9 b24edfb 98cf4b9 da43c80 180eaf9 da43c80 c35bc0c 28e1c18 1926a35 676f81f cb2df2d 37b967a fb6299c 7c82acb 816011b 83c2bf6 29fbf64 cb2df2d 816011b 83c2bf6 22e9a27 7740f60 d9217c2 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 |
import gradio as gr
import pandas as pd
from datatable import (dt, f,fread, by, ifelse, update, sort,count, min, max, mean, sum, rowsum,rowmean,rowcount,shift,rbind,cbind,union)
import requests
'''
import hashlib
import tempfile
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(code:str):
namespace = {}
fun = compile(code,'<string>','exec')
exec(fun,namespace)
return namespace['py_exe']
'''
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()
def fx_dt(dc,x,y):
DT=fread(dc)
gr.JSON(DT.names)
D_table=DT[:,sum(f[int(y-1)]),by(f[int(x-1)])]
return D_table.to_pandas()
'''
demo=gr.Blocks(css="#jsc:hover{background-color: red;}")
with demo:
with gr.Tabs(selected=5):
'''
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")
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",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",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(最终输出使用变量名py_exe)",lines=18)
d_output=gr.DataFrame(label="输出>")
d_button=gr.Button("开始编译>>")
d_button.click(fx_datatable, inputs=d_input, outputs=d_output,api_name='pyexe')
'''
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')
with gr.TabItem("datatable"):
gr.Markdown("# datatable测试")
dt_input=[gr.File(label="选择需要读取的文档",type='bytes'),gr.Number(label='请输入分组列序号'),gr.Number(label='请输入聚合列序号')]
dt_output=gr.DataFrame(label="输出",max_rows=10,wrap=True)
dt_button=gr.Button("分类汇总")
dt_button.click(fx_dt, inputs=dt_input, outputs=dt_output,api_name='datatable')
'''
with gr.TabItem("js"):
gr.Markdown("# js处理测试")
a=gr.Textbox(label='请输入需要js处理的字符串')
js_output=gr.Textbox(label="JS输出")
js_button1=gr.Button("js_test")
js_button2=gr.Button("js_test2")
js_button=gr.Button("js逆序字符串处理")
js_button3=gr.Button("调用js引用",elem_id="jsc")
js_button1.click(None,a,js_output,_js="x=>'你好:'+x")
js_button2.click(None,a,js_output,_js="x=>`你好:${x},欢迎吹水!`")
js_button.click(None,a,js_output,_js="(x) => [...x].reverse().join('')",api_name='js')
js_button3.click(None,a,js_output,_js='(x)=>md5(x);<script src="https://huggingface.co/spaces/changxin/test/raw/main/statics/md5.js"></script>')
demo.launch()
|