Creating azure openai instance with model deployment

readme.md

terraform init

terraform plan 

terraform apply --auto-approve 

provide a prefix to keep your resources unique

look for relevant output once the apply is finished

azure_ml_resource_group = "prefixresources"
azure_ml_subscription_id = "your-subscription-id-"
azure_ml_workspace_name = "example-ml-workspace"
openai_api_version = "2023-12-01-preview"
openai_azure_endpoint = "https://southcentralus.api.cognitive.microsoft.com/"
openai_deployment_model = "gpt-35-turbo"
openai_text_embedding_model = "text-curie-001"

and find the api key in the Azure OpenAI > "keys and endpoint"

tear it down

terraform destroy --auto-approve

main.tf

provider "azurerm" {
  features {
    resource_group {
      prevent_deletion_if_contains_resources = false 
    }
  }
}

variable "prefix" {
    description = "Prefix for the resources (rock1)"
}


data "azurerm_client_config" "current" {}

# Resource Group
resource "azurerm_resource_group" "ai_rg" {
  name     = "${var.prefix}ai-resources"
  location = "South Central US"
}

# Azure Machine Learning Workspace
resource "azurerm_machine_learning_workspace" "example" {
  name                    = "example-ml-workspace"
  location                = azurerm_resource_group.ai_rg.location
  resource_group_name     = azurerm_resource_group.ai_rg.name
  application_insights_id = azurerm_application_insights.example.id
  key_vault_id            = azurerm_key_vault.example.id
  storage_account_id      = azurerm_storage_account.example.id

  identity {
    type = "SystemAssigned"
  }
}

# Application Insights for the ML Workspace
resource "azurerm_application_insights" "example" {
  name                = "example-app-insights"
  location            = azurerm_resource_group.ai_rg.location
  resource_group_name = azurerm_resource_group.ai_rg.name
  application_type    = "web"
}

# Key Vault for the ML Workspace
resource "azurerm_key_vault" "example" {
  name                = "${var.prefix}-dev1-kv"
  location            = azurerm_resource_group.ai_rg.location
  resource_group_name = azurerm_resource_group.ai_rg.name
  sku_name            = "standard"
  tenant_id           = data.azurerm_client_config.current.tenant_id

  purge_protection_enabled   = true
}

# Storage Account for the ML Workspace
resource "azurerm_storage_account" "example" {
  name                     = "${var.prefix}mlstudiostorage"
  resource_group_name      = azurerm_resource_group.ai_rg.name
  location                 = azurerm_resource_group.ai_rg.location
  account_tier             = "Standard"
  account_replication_type = "LRS"
}

# Azure Cognitive Services Account for OpenAI
resource "azurerm_cognitive_account" "example" {
  name                = "${var.prefix}-ca-ai"
  location            = azurerm_resource_group.ai_rg.location
  resource_group_name = azurerm_resource_group.ai_rg.name
  kind                = "OpenAI"
  sku_name            = "S0"
}

# # Cognitive Service Deployment for OpenAI
resource "azurerm_cognitive_deployment" "embedding" {
  name                 = "embedding-curie"
  cognitive_account_id = azurerm_cognitive_account.example.id
  model {
    format  = "OpenAI"
    name    = "text-curie-001"
    version = "1"
  }

  scale {
    type = "Standard"
  }
}



# Cognitive Service Deployment for OpenAI
resource "azurerm_cognitive_deployment" "text" {
  name                 = "text-gpt-3"
  cognitive_account_id = azurerm_cognitive_account.example.id
  model {
    format  = "OpenAI"
    name    = "gpt-35-turbo"
    version = "0125"
  }

  scale {
    type = "Standard"
  }
}


# Output Azure ML Subscription ID
output "azure_ml_subscription_id" {
  value = data.azurerm_client_config.current.subscription_id
}

# Output Azure ML Resource Group
output "azure_ml_resource_group" {
  value = azurerm_resource_group.ai_rg.name
}

# Output Azure ML Workspace Name
output "azure_ml_workspace_name" {
  value = azurerm_machine_learning_workspace.example.name
}


output "openai_azure_endpoint" {
  value = azurerm_cognitive_account.example.endpoint
}

# Output OpenAI API Version (example setting, adjust as needed)
output "openai_api_version" {
  value = "2023-12-01-preview"  # Placeholder, replace with actual versioning schema if available
}

# Output OpenAI Deployment Model
output "openai_deployment_model" {
  value = azurerm_cognitive_deployment.text.model[0].name
}

# Output OpenAI Text Embedding Model 
output "openai_text_embedding_model" {
  value = azurerm_cognitive_deployment.embedding.model[0].name 
}