🆒Deployment Steps

A Step-by-Step Guide to Deploying Open AI on Microsoft Azure

1. Login into Azure Portal: Go to portal.azure.com and sign in with your credentials.

2. Locate Azure OpenAI: Use the search bar at the top of the page to search for “Azure OpenAI” and select the Azure services only option and you will get the azure OpenAI.

3. “Create Azure OpenAI”.

4. Create an Azure OpenAI Resource: Azure will direct you to the Azure AI Services | Azure OpenAI page. To create a new one, click on “+Create” or the “Create Azure OpenAI” button.

On the next page, fill out the required fields:
Subscription: Ensure your subscription is selected (choose the correct one if you have multiple).
Resource Group: Select an existing resource group or create a new one to manage related resources collectively.
Region: Choose the appropriate region based on model availability and the location of your users (closer regions reduce latency).
Resource Name: Give your resource a unique name.
Pricing Tier: Select the “Standard S0” tier (you can learn more about pricing here).

5. Network Configuration: Azure AI services offer a layered security model. Choose one of the following options based on your needs:

All networks have access: Use this for public-facing applications that need global access, such as a chatbot on a website.
Selected networks have access: Choose this for internal applications restricted to specific IP addresses or virtual networks for company use.
Disabled, no networks can access: Use this for highly sensitive data, ensuring access is limited to secure, private endpoints (e.g., financial applications processing confidential transactions).

6. Tags: Adding tags to your Azure resources provides several benefits, including:

Organization: Tags help categorize and identify resources across different projects.
Cost Management: Tags enable better cost management by allowing you to generate reports based on tags.
Automation: Tags can be used in automation scripts for applying policies or performing actions on specific resources.
Compliance and Governance: Tags help enforce compliance and governance by identifying resources that meet certain criteria.
Resource Management: Tags make it easier to manage and filter resources within the Azure portal.

7.Review and Create:

After completing the form, review your inputs and click “Create.” Once the resource is created, you’ll be directed to the resource page. Click “Go to resource” to continue.

`Deploying a model`

7.Open Azure OpenAI Studio: Click on “Go to Azure OpenAI Studio” or go directly to oai.azure.com.

8.Select “Deployments” from the left-hand menu.

9.Deploy Your Model: If this is your first deployment, the page will be empty. Click “Deploy model” and choose one of the following options:

Deploy base model: Select from the available OpenAI models in your region.
Deploy fine-tuned model: If you need to fine-tune a model.

10.A page will pop-up with all OpenAI models available in the region, if you select one you will see a description of the model in the right panel. Select the one you want to deploy and click “confirm”.

11.Configure Deployment:

Deployment Name: Use the model name by default, or create a custom name.
Model Version: Choose the version of the model you want to deploy.
Deployment Type: Choose the configuration (e.g., Global Standard for general use, Global Batch for batch processing, Standard for typical deployments, or Provisioned Managed for managed infrastructure).
Tokens per Minute Rate Limit: Define the maximum number of tokens your model can process per minute.
Content Filter: Set the content filter to control the type of content your model can generate or process.

After filling the fields, click “deploy”.

12.Finalize and Deploy: After completing the configuration, click “Deploy.” The model will appear on the “Deployments” page. To test the model, click “Open in Playground,” which will redirect you to the “Chat session” for testing.