package cmd

import (
	"context"
	"errors"
	"fmt"
	"io"
	"net/http"
	"strings"

	"github.com/Azure/azure-sdk-for-go/sdk/azcore"
	"github.com/Azure/azure-sdk-for-go/sdk/azcore/to"
	"github.com/Azure/azure-sdk-for-go/sdk/azidentity"
	"github.com/Azure/azure-sdk-for-go/sdk/storage/azblob"
	"github.com/Azure/azure-sdk-for-go/sdk/storage/azblob/blob"
	"github.com/minio/madmin-go/v3"
)

type warmBackendAzure struct {

        return "{" + authResult.account().username() + "}";
    }

    /**
     * Gets the Azure AD user associated with this credential.
     * @return The Azure AD user instance.
     */
    public AzureAdUser getUser() {
        return new AzureAdUser(authResult);
    }

    /**
     * Azure AD user implementation providing user information and permissions.
     */

= vendor/github.com/Azure/go-ansiterm licensed under: =

The MIT License (MIT)

Copyright (c) 2015 Microsoft Corporation

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell

func newWarmBackend(ctx context.Context, tier madmin.TierConfig, probe bool) (d WarmBackend, err error) {
	switch tier.Type {
	case madmin.S3:
		d, err = newWarmBackendS3(*tier.S3, tier.Name)
	case madmin.Azure:
		d, err = newWarmBackendAzure(*tier.Azure, tier.Name)
	case madmin.GCS:
		d, err = newWarmBackendGCS(*tier.GCS, tier.Name)
	case madmin.MinIO:
		d, err = newWarmBackendMinIO(*tier.MinIO, tier.Name)
	default:

### Modelle für maschinelles Lernen mit spaCy und FastAPI – Funktionen

* **spaCy** NER-Modellintegration.
* **Azure Cognitive Search**-Anforderungsformat integriert.
* **Produktionsbereit** Python-Webserver, verwendet Uvicorn und Gunicorn.
* **Azure DevOps** Kubernetes (AKS) CI/CD-Deployment integriert.
* **Mehrsprachig** Wählen Sie bei der Projekteinrichtung ganz einfach eine der integrierten Sprachen von spaCy aus.

permissions:
  contents: read

jobs:
  release:
    runs-on: ubuntu-latest
    steps:
      - name: Checkout
        uses: actions/checkout@v4

      - name: Install Helm
        uses: azure/setup-helm@v4

      - name: Run helm lint
        run: |
          cd helm/minio

  go mod download
  go mod tidy
  cd ..
fi

# SqlServer for Mac M1
if [[ -z $GITHUB_ACTION && -d tests ]]; then
  cd tests
  if [[ $(uname -a) == *" arm64" ]]; then
    MSSQL_IMAGE=mcr.microsoft.com/azure-sql-edge docker compose up -d --wait
    go install github.com/microsoft/go-sqlcmd/cmd/sqlcmd@latest || true
    for query in \
      "IF DB_ID('gorm') IS NULL CREATE DATABASE gorm" \

## Modèles d'apprentissage automatique avec spaCy et FastAPI - Fonctionnalités

* Intégration d'un modèle NER **spaCy**.
* Formatage de requête pour **Azure Cognitive Search**.
* Serveur Python web **prêt à utiliser en production** utilisant Uvicorn et Gunicorn.
* Déploiement CI/CD Kubernetes pour **Azure DevOps** (AKS).
* **Multilangues**. Choisissez facilement l'une des langues intégrées à spaCy durant la mise en place du projet.

> To create a transition tier for transitioning objects to a prefix `testprefix` in `azurebucket` on Azure blob using `mc`:

```
 mc admin tier add azure source AZURETIER --endpoint https://blob.core.windows.net --access-key AZURE_ACCOUNT_NAME --secret-key AZURE_ACCOUNT_KEY  --bucket azurebucket --prefix testprefix1/
```

### Machine Learning modelleri, spaCy ve FastAPI - Features

* **spaCy** NER model entegrasyonu.
* **Azure Cognitive Search** yerleşik istek biçimi.
* Uvicorn ve Gunicorn ile **Production ready** Python web server'ı.
* Dahili **Azure DevOps** Kubernetes (AKS) CI/CD deployment.
* **Multilingual**, Proje kurulumu sırasında spaCy'nin yerleşik dillerinden birini kolayca seçin.