sessions-tutorial-prerequisites.md

author	anthonychu
ms.service	azure-container-apps
ms.topic	include
ms.date	05/08/2024
ms.author	antchu

Prerequisites

• An Azure account with an active subscription.
  • If you don't have one, you can create one for free.
• Install the Azure CLI.
• Git.
• Python 3.10 or later.

Create Azure resources

The sample app in this quickstart uses an LLM from Azure OpenAI. It also uses Azure Container Apps sessions to run code generated by the LLM.

1. Update the Azure CLI to the latest version.

    az upgrade

2. Remove the Azure Container Apps extension if it's already installed and install a preview version the Azure Container Apps extension containing commands for sessions:

   az extension remove --name containerapp
   az extension add \
       --name containerapp \
       --allow-preview true -y

3. Sign in to Azure:

   az login

4. Set the variables used in this quickstart:

   RESOURCE_GROUP_NAME=aca-sessions-tutorial
   AZURE_OPENAI_LOCATION=swedencentral
   AZURE_OPENAI_NAME=<UNIQUE_OPEN_AI_NAME>
   SESSION_POOL_LOCATION=eastasia
   SESSION_POOL_NAME=code-interpreter-pool

   Replace <UNIQUE_OPEN_AI_NAME> with a unique name to create your Azure OpenAI account.

5. Create a resource group:

   az group create --name $RESOURCE_GROUP_NAME --location $SESSION_POOL_LOCATION

6. Create an Azure OpenAI account:

   az cognitiveservices account create \
       --name $AZURE_OPENAI_NAME \
       --resource-group $RESOURCE_GROUP_NAME \
       --location $AZURE_OPENAI_LOCATION \
       --kind OpenAI \
       --sku s0 \
       --custom-domain $AZURE_OPENAI_NAME

7. Create a GPT 3.5 Turbo model deployment named gpt-35-turbo in the Azure OpenAI account:

   az cognitiveservices account deployment create \
       --resource-group $RESOURCE_GROUP_NAME \
       --name $AZURE_OPENAI_NAME \
       --deployment-name gpt-35-turbo \
       --model-name gpt-35-turbo \
       --model-version "1106" \
       --model-format OpenAI \
       --sku-capacity "100" \
       --sku-name "Standard"

8. Create a code interpreter session pool:

   az containerapp sessionpool create \
       --name $SESSION_POOL_NAME \
       --resource-group $RESOURCE_GROUP_NAME \
       --location $SESSION_POOL_LOCATION \
       --max-sessions 100 \
       --container-type PythonLTS \
       --cooldown-period 300