LangWatch allows you to trace your Azure OpenAI API calls using the same otelopenai middleware you use for OpenAI. The setup requires pointing the client to your specific Azure resource endpoint and using your Azure API key.

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Setup

You will need three key pieces of information from your Azure OpenAI service deployment:
  1. Your Azure Endpoint: The URL for your Azure OpenAI resource (e.g., https://my-langwatch-demo.openai.azure.com).
  2. Your Deployment Name: The name you gave your model deployment (e.g., gpt-4o-mini-deployment).
  3. Your Azure API Key: The API key for your Azure resource.
Set your API key as an environment variable: 
export AZURE_OPENAI_API_KEY="your-azure-api-key"

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Example

To configure the openai.Client, you must construct the correct base URL by combining your Azure endpoint and deployment name. You should also set the gen_ai.system attribute to "azure" for proper categorization in LangWatch.
The following example assumes you have already configured the LangWatch SDK. See the Go setup guide for details.
package main

import (
	"context"
	"fmt"
	"log"
	"os"

	"github.com/langwatch/langwatch/sdk-go"
	otelopenai "github.com/langwatch/langwatch/sdk-go/instrumentation/openai"
	"github.com/openai/openai-go"
	oaioption "github.com/openai/openai-go/option"
)

func main() {
	ctx := context.Background()
	// Assumes LangWatch is already set up.

	// Your Azure OpenAI details
	apiKey := os.Getenv("AZURE_OPENAI_API_KEY")

	// Your Azure-specific details
	azureEndpoint := "https://<your-resource-name>.openai.azure.com"
	deploymentName := "<your-deployment-name>"

	// Construct the full base URL
	baseURL := fmt.Sprintf("%s/openai/deployments/%s", azureEndpoint, deploymentName)

	client := openai.NewClient(
		// Set the specific URL for your Azure deployment
		oaioption.WithBaseURL(baseURL),

		// Use your Azure API key
		oaioption.WithAPIKey(apiKey),

		// Add the middleware, identifying the system as "azure"
		oaioption.WithMiddleware(otelopenai.Middleware("my-azure-app",
			otelopenai.WithGenAISystem("azure"),
			otelopenai.WithCaptureInput(),
			otelopenai.WithCaptureOutput(),
		)),
	)

	// When making the call, the model name is your deployment name
	response, err := client.Chat.Completions.New(ctx, openai.ChatCompletionNewParams{
		Model: openai.ChatModel(deploymentName),
		Messages: []openai.ChatCompletionMessageParamUnion{
			openai.UserMessage("Hello, Azure OpenAI!"),
		},
	})

	if err != nil {
		log.Fatalf("Azure OpenAI API call failed: %v", err)
	}

	log.Printf("Response from Azure: %s", response.Choices[0].Message.Content)
}
Model vs. Deployment Name: When using the Azure OpenAI endpoint, the Model parameter in your Chat.Completions.New call should typically be your deployment name, not the underlying model name (e.g., gpt-4o-mini).