Provider: Azure OpenAI

Call Azure OpenAI models through Respan Gateway with unified logs, cost, and latency.
This page is for Respan LLM Gateway users.

Use Respan Gateway to call Azure OpenAI deployments (gpt-5.5, gpt-5, gpt-5-mini, o3, and the rest) while keeping unified observability (logs, cost, latency, reliability) in Respan.

Quick setup

1

Get a Respan API key

Sign up and create a key on the API keys page.

Send your first request

Pick the integration that matches your stack. The base URL is https://api.respan.ai/api and the only key needed is your RESPAN_API_KEY. Use the azure/ prefix plus your deployment name (or any Azure-compatible model ID) as the model.

Point the standard OpenAI SDK at the Respan gateway. No Azure-specific client needed, Respan translates to your Azure deployment based on the model ID.

1from openai import OpenAI
2
3client = OpenAI(
4 api_key="YOUR_RESPAN_API_KEY",
5 base_url="https://api.respan.ai/api",
6)
7
8response = client.chat.completions.create(
9 model="azure/gpt-5.5",
10 messages=[{"role": "user", "content": "Hello, Azure OpenAI!"}],
11)
12print(response.choices[0].message.content)

More integrations

Azure OpenAI models work with every Respan gateway integration:

Switch models

Change the model parameter to call any supported model through the same client. Use the azure/ prefix plus your Azure deployment name (or model ID) to disambiguate when routing across providers. Browse the full list on the Models page.

1client.chat.completions.create(model="azure/gpt-5.5", messages=messages)
2client.chat.completions.create(model="azure/gpt-5-mini", messages=messages)
3client.chat.completions.create(model="azure/o3", messages=messages)
4client.chat.completions.create(model="openai/gpt-5.5", messages=messages)
5client.chat.completions.create(model="anthropic/claude-sonnet-4-5-20250929", messages=messages)

Use your own Azure OpenAI key (BYOK)

Credits are the default path. If you’d rather bill Azure directly, attach your own Azure OpenAI credentials.

1

Open Providers

Go to the Providers page.

2

Add Azure OpenAI

Select Azure OpenAI and fill in the required credential fields:

  • api_key (your Azure OpenAI API key)
  • api_base (your Azure OpenAI resource endpoint, also called base URL)
  • api_version (the Azure OpenAI API version to use)

Azure allows custom deployment names. Use the azure/{deployment-name} model ID format in gateway requests.

3

Load balancing (Optional)

Add multiple credential sets and use Load balancing weight to distribute traffic across them.

Override credentials per model (Optional)

Use credential_override when one model on a request should use a different Azure resource than the default.

1{
2 "customer_credentials": {
3 "azure_openai": {
4 "api_key": "YOUR_AZURE_OPENAI_API_KEY",
5 "api_base": "https://your-resource.openai.azure.com/",
6 "api_version": "2024-10-21"
7 }
8 },
9 "credential_override": {
10 "azure/gpt-5.5": {
11 "api_key": "ANOTHER_API_KEY",
12 "api_base": "https://another-resource.openai.azure.com/",
13 "api_version": "2024-10-21"
14 }
15 }
16}

Log without proxying (Optional)

Already calling Azure OpenAI directly? Send logs to Respan asynchronously to track cost, latency, and performance for those external calls.

1import requests
2
3requests.post(
4 "https://api.respan.ai/api/request-logs/create/",
5 headers={
6 "Authorization": "Bearer YOUR_RESPAN_API_KEY",
7 "Content-Type": "application/json",
8 },
9 json={
10 "model": "azure/gpt-5.5",
11 "prompt_messages": [{"role": "user", "content": "Hello, how are you?"}],
12 "completion_message": {"role": "assistant", "content": "Hello from Azure OpenAI through Respan."},
13 "cost": 0.001,
14 "generation_time": 1.2,
15 "customer_params": {"customer_identifier": "user_123"},
16 },
17)

See the logging guide for the full setup.