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Azure OpenAI Service provides access to OpenAI’s powerful language models through Microsoft Azure’s enterprise-grade infrastructure. This integration allows you to use your Azure OpenAI deployments directly in Cargo workflows, ideal for organizations with compliance, data residency, or security requirements.

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How to set up Azure OpenAI

Azure OpenAI requires your own Azure credentials (BYOC). Cargo credits are not available for this integration.

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Prerequisites

Before connecting, ensure you have:
  1. An active Azure subscription
  2. An Azure OpenAI resource created in the Azure Portal
  3. At least one model deployment in your Azure OpenAI resource

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Connection details

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Finding your credentials

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Resource Name

  1. Go to the Azure Portal
  2. Navigate to your Azure OpenAI resource
  3. The resource name is in the overview page and part of your endpoint URL
    • If your endpoint is https://my-company-openai.openai.azure.com/, your resource name is my-company-openai

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API Key

  1. In the Azure Portal, navigate to your Azure OpenAI resource
  2. Click Keys and Endpoint under “Resource Management”
  3. Copy KEY 1 or KEY 2
Find your API key and endpoint in the Azure Portal under your Azure OpenAI resource → Keys and Endpoint.

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Azure OpenAI actions

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Instruct

Send a prompt to an Azure OpenAI deployment and receive a text response. Use cases
  • Content generation – Generate personalized emails, messages, or content
  • Classification – Categorize text into predefined categories
  • Summarization – Summarize long text into concise summaries
  • Data extraction – Extract structured data from unstructured text
  • Translation – Translate text between languages
  • Analysis – Analyze sentiment, intent, or other text properties
Configuration
Azure OpenAI uses deployment names instead of model names. You define these names when deploying models in the Azure Portal.

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Understanding deployments

Unlike standard OpenAI where you select models like gpt-4o, Azure OpenAI requires you to:
  1. Deploy a model in the Azure Portal
  2. Give it a custom deployment name (e.g., my-gpt4o-deployment)
  3. Use that deployment name in Cargo
To find your deployment names:
  1. Go to your Azure OpenAI resource in the Azure Portal
  2. Click Model deployments in the left sidebar
  3. Note the Deployment name for each model

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Response formats

Control how the model returns its response:
Use JSON schema when you need structured output with specific fields. Define your schema to ensure consistent, parseable responses.

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Example JSON schema

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Advanced settings

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System prompt

Set instructions that guide the model’s behavior across all prompts:
  • Define the model’s role or persona
  • Set output format guidelines
  • Provide context about your use case
  • Establish constraints or rules

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Temperature

Control the randomness of outputs:
For tasks requiring consistency (classification, extraction), use low temperature (0-0.3). For creative tasks (content generation), use higher temperature (0.7-1).

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API versions

Azure OpenAI requires an API version. Cargo defaults to 2024-08-01-preview. If you need specific features, you can override it:

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Troubleshooting

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”DeploymentNotFound” error

The deployment name you specified doesn’t exist. Verify:
  • The deployment name matches exactly as shown in the Azure Portal
  • The deployment is in the same resource you configured

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”Unauthorized” error

Your credentials may be incorrect. Check that:
  • Your API key is correct and hasn’t been regenerated
  • Your Azure OpenAI resource is active
  • The API key has access to the specified resource