csiebler

import requests
import io
import logging
import threading
import time
import concurrent.futures

import Levenshtein as lev
from datetime import datetime

csiebler

import azure.cognitiveservices.speech as speechsdk
import requests

# Access key to Speech API from Azure (this needs to be stored in the backend and show not get to the client)
access_key = 'xxxxxxxxxxxx'
region = "westeurope"

# This method should run in the backend, so that access_key is not needed in the client
def get_auth_token(access_key):
    fetch_token_url = f"https://{region}.api.cognitive.microsoft.com/sts/v1.0/issueToken"

csiebler

<?xml version="1.0" encoding="utf-8"?>
<lexicon xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.w3.org/2005/01/pronunciation-lexicon http://www.w3.org/TR/2007/CR-pronunciation-lexicon-20071212/pls.xsd" version="1.0" alphabet="ipa" xml:lang="de-DE" xmlns="http://www.w3.org/2005/01/pronunciation-lexicon">
  <lexeme>
    <grapheme>passieren</grapheme>
    <phoneme>paˈsiːʁən</phoneme>
  </lexeme>
  <lexeme>
    <grapheme>Reserve</grapheme>
    <phoneme>ʁeˈzɛʁvə</phoneme>
  </lexeme>

csiebler

        {
            "@odata.type": "#Microsoft.Skills.Text.V3.SentimentSkill",
            "name": "#4",
            "description": null,
            "context": "/document/transcript/*",
            "defaultLanguageCode": "en",
            "modelVersion": null,
            "includeOpinionMining": false,
            "inputs": [
                {

csiebler

import requests
import io
import time

n = 50

# Enter your resource details here
url = "https://xxxxxxx.cognitiveservices.azure.com/vision/v3.2/read/analyze?language=en&pages=1&readingOrder=natural"
key = "xxxxxxx"

csiebler

import requests, json

key = "xxxxx" # Paste your API key here
url = "https://api.bing.microsoft.com/v7.0/search"

search_term = "Azure Cognitive Services"

headers = {"Ocp-Apim-Subscription-Key" : key}
params = {"q": search_term, "textDecorations": True, "textFormat": "HTML"}

csiebler

{
    "mode": "All",
    "policyRule": {
        "if": {
            "allOf": [
                {
                    "field": "type",
                    "equals": "Microsoft.MachineLearningServices/workspaces/computes"
                },
                {

csiebler

from azureml.core import Workspace, Model
from azureml.core.model import InferenceConfig
from azureml.core.environment import Environment
from azureml.core.conda_dependencies import CondaDependencies

ws = Workspace.from_config()

env = Environment("inference-env")
env.docker.enabled = True
# Replace with your conda enviroment file

csiebler

name: conda-env

dependencies:
  - pip
  - pip:
    - --index-url https://xxxxx
    - --extra-index-url https://xxxxxx
    - xxxxxx==x.x.x
    - -e git+https://github.com/xxxxxxxxxxx
    - -e ./xxxxxxx

csiebler

Steps:

• Create private Feed in Azure DevOps
• Create Personal Access Token (PAT) in Azure DevOps with Feed Read permission (details)
• Navigate to the Azure DevOps Artifacts Feed page where you can see the details for the next steps (you'll need feed name, project name, organization name and later also package name):
• Create Build pipeline in Azure DevOps to create package and push to private feed:

trigger: