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Azure OpenAI requires three credentials: API key, API base URL (also called base_url or endpoint), and API version. Make sure you have all three from your Azure Portal before proceeding.

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Prerequisites

Before integrating Azure OpenAI with Respan, ensure you have:
  1. An active Azure OpenAI subscription
  2. At least one deployed model in your Azure OpenAI resource
  3. Your deployment name matches those listed on our Models page

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How to get your Azure OpenAI credentials

1

Access Azure Portal

Visit your Azure Portal OpenAI Service.You will see your deployments. Choose the deployment you want to use.
Azure Portal deployments
2

Get your API Base URL (endpoint)

Click on the “Endpoints” link to view your API base URL.
The API base URL is also called endpoint or base_url. For OpenAI, this would be https://api.openai.com, but for Azure it’s unique to your resource (e.g., https://your-resource.openai.azure.com/).
Azure endpoint and keys
3

Get your API Key

Click on the “Manage Keys” link to view your API keys. You can use either Key 1 or Key 2.
4

Choose API Version

Pick an API version from the available Azure OpenAI versions.
  • 2024-10-21 (recommended)
  • 2024-08-01-preview
  • 2024-06-01
  • 2024-02-01

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Azure OpenAI models compatibility

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Add Azure OpenAI credentials

There are 2 ways to add your Azure OpenAI credentials to your requests:
1

Navigate to Providers page

Go to Providers page and select Azure OpenAI.
Providers Page
2

Add your credentials

Fill in the three required Azure OpenAI credentials:
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api_key
string
required
Your Azure OpenAI API key from the Azure Portal.
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api_base
string
required
Your Azure OpenAI endpoint URL (also called base_url or endpoint).
The api_base (synonyms: base_url, endpoint) is the base URL for your Azure OpenAI resource.Examples:
  • Azure OpenAI: https://your-resource.openai.azure.com/
  • OpenAI (for reference): https://api.openai.com
You can find this in your Azure Portal under “Endpoints”.
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api_version
string
required
Your Azure OpenAI API version (e.g., 2024-10-21). See available versions.
Add Azure credentials
3

Map your deployment name

Azure allows custom deployment names. You need to map your deployment name so Respan knows which Azure deployment to call.Important: When testing the model, use the format azure/{your-deployment-name} in the model test input.For example:
  • If your Azure deployment name is gpt-4o, use: azure/gpt-4o
  • If your Azure deployment name is my-gpt4-deployment, use: azure/my-gpt4-deployment
Azure deployment name mapping
4

(Optional) Specify models to use these credentials

You can limit which models use these credentials. Leave empty to apply your credentials for all Azure OpenAI models.To specify models:
  1. Go to the Models page
  2. Copy the model ID (e.g., azure/gpt-4o)
  3. Paste it in the input field
  4. Press Enter to add the model
Select models

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Option 2: Via Code

1

Install OpenAI SDK

pip install openai
2

Initialize client with Azure credentials

from openai import OpenAI

client = OpenAI(
    base_url="https://api.respan.ai/api/",
    api_key="YOUR_RESPAN_API_KEY",
)

response = client.chat.completions.create(
    model="azure/gpt-4o",  # Use azure/ prefix with your deployment name
    messages=[{"role": "user", "content": "Hello, how are you?"}],
    extra_body={
        "customer_credentials": {
            "azure_openai": {
                "api_key": "YOUR_AZURE_OPENAI_API_KEY",
                "api_base": "https://your-resource.openai.azure.com/",
                "api_version": "2024-10-21",
            }
        }
    }
)
print(response)
3

(Optional) Map custom deployment names

If your Azure deployment name differs from the standard model name, use model_name_map to specify the mapping.Example: If you deployed gpt-4o with a custom name like my-gpt4-prod, map it like this:
response = client.chat.completions.create(
    model="azure/gpt-4o",
    messages=[{"role": "user", "content": "Hello"}],
    extra_body={
        "customer_credentials": {
            "azure_openai": {
                "api_key": "YOUR_AZURE_OPENAI_API_KEY",
                "api_base": "https://your-resource.openai.azure.com/",
                "api_version": "2024-10-21",
            }
        },
        "model_name_map": {
            "azure/gpt-4o": "azure/my-gpt4-prod"  # Map to your custom deployment name
        }
    }
)
model_name_map only works when your credentials are valid.
4

(Optional) Override credentials for specific models

You can override credentials for individual models without changing the default credentials.
response = client.chat.completions.create(
    model="azure/gpt-4o",
    messages=[{"role": "user", "content": "Hello"}],
    extra_body={
        "customer_credentials": {
            "azure_openai": {
                "api_key": "DEFAULT_AZURE_API_KEY",
                "api_base": "https://resource1.openai.azure.com/",
                "api_version": "2024-10-21",
            }
        },
        "credential_override": {
            "azure/gpt-4o": {  # Override for this specific model only
                "api_key": "ANOTHER_AZURE_API_KEY",
                "api_base": "https://resource2.openai.azure.com/",
                "api_version": "2024-10-21",
            }
        }
    }
)
5

(Optional) Load balance between multiple deployments

You can add multiple Azure deployments and load balance between them for better availability and cost optimization.Learn more: Load Balancing Guide

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Testing your integration

Important: When testing in the model playground:
  • The “Model test call” input field should contain the model identifier: azure/your-deployment-name (e.g., azure/gpt-4o)
  • This is NOT for the message content
  • The message content goes in the separate chat input field below
  • The placeholder should show azure/gpt-4o as an example for Azure models

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Requirements and troubleshooting

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Requirements

  1. Deployment name format: Use azure/{deployment-name} format (e.g., azure/gpt-4o)
  2. Credentials match: Ensure your deployment name is correctly mapped if using custom names
  3. Regional availability: Confirm your models are available in the region specified by your credentials
  4. API version: Use a supported Azure OpenAI API version

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Common issues

Cause: Your deployment name doesn’t match what’s configured in Azure.Solution:
  • Check your Azure deployment name in the Azure Portal
  • Use model_name_map to map the standard model name to your custom deployment name
  • Ensure you’re using the azure/ prefix (e.g., azure/gpt-4o)
Cause: One or more of your Azure credentials are incorrect.Solution:
  • Verify api_key in Azure Portal → Manage Keys
  • Verify api_base matches your resource endpoint exactly (including trailing slash)
  • Verify api_version is a valid version
Issue: The “Model test call” input field is for specifying which model to test, not the message.Correct usage:
  • Model test call input: azure/gpt-4o (the model identifier with azure/ prefix)
  • Message/chat input: Your actual message like “Hello, how are you?”
The placeholder should be dynamic and show azure/gpt-4o for Azure providers, not just gpt-4o.
Credential validation is not currently supported. Make sure your credentials are correct before making requests to avoid errors.

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Supported models

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DeepSeek models

  • azure_deepseek/deepseek-v3
  • azure_deepseek/deepseek-chat
  • azure_deepseek/deepseek-reasoner
  • azure_deepseek/deepseek-r1

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O-series models

  • azure/o1
  • azure/o3
  • azure/o3-mini
  • azure/o4-mini

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GPT-4 series

  • azure/gpt-4
  • azure/gpt-4-32k
  • azure/gpt-4-1106-preview
  • azure/gpt-4-vision-preview
  • azure/gpt-4o
  • azure/gpt-4o-mini
  • azure/gpt-4o-2024-08-06
  • azure/gpt-4.1
  • azure/gpt-4.1-mini
  • azure/gpt-4.1-nano

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GPT-5 series

  • azure/gpt-5
  • azure/gpt-5-mini

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GPT-3.5 series

  • azure/gpt-35-turbo
You can find the complete and up-to-date list here.