Weights & Biases (W&B) Weave integrates with Microsoft Azure OpenAI services, helping teams to optimize their Azure AI applications. Using W&B, you can
For the latest tutorials, visit Weights & Biases on Microsoft Azure.

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Getting started

To get started using Azure with Weave, simply decorate the function(s) you want to track with weave.op. 
@weave.op()
def call_azure_chat(model_id: str, messages: list, max_tokens: int = 1000, temperature: float = 0.5):
    response = client.chat.completions.create(
        model=model_id,
        messages=messages,
        max_tokens=max_tokens,
        temperature=temperature
    )
    return {"status": "success", "response": response.choices[0].message.content}

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Learn more

Learn more about advanced Azure with Weave topics using the resources below.

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Use the Azure AI Model Inference API with Weave

Learn how to use the [Azure AI Model Inference API] with Weave to gain insights into Azure models in this guide.

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Trace Azure OpenAI models with Weave

Learn how to trace Azure OpenAI models using Weave in this guide.