# Azure OpenAI (/en/ai/models/llm/azure-openai)

> For AI agents: see the complete documentation index at [llms.txt](/llms.txt).

Azure OpenAI service provides REST API access to OpenAI's powerful language models through Microsoft Azure's secure infrastructure.

### Sample configuration [#sample-configuration]

The following example shows how to configure Azure OpenAI LLM when starting a conversational AI agent.

<Tabs defaultValue="python" groupId="ai-sdk-language">
  <TabsList>
    <TabsTrigger value="python">
      Python SDK
    </TabsTrigger>

    <TabsTrigger value="typescript">
      TypeScript SDK
    </TabsTrigger>

    <TabsTrigger value="go">
      Go SDK
    </TabsTrigger>

    <TabsTrigger value="rest-api">
      REST API
    </TabsTrigger>
  </TabsList>

  <TabsContent value="python">
    ```python
    from agora_agent import Agent, AzureOpenAI

    # client is your configured Agora client
    agent = (
        Agent(client)
        .with_stt(...)  # configure your STT vendor
        .with_llm(AzureOpenAI(
            api_key='your-azure-api-key',
            endpoint='https://your-resource-name.openai.azure.com',
            deployment_name='your-deployment-name', # the name given to your model deployment in Azure OpenAI Studio
            model='gpt-4o-mini',
            system_messages=[{'role': 'system', 'content': 'You are a helpful chatbot.'}],
            greeting_message='Hello, how can I assist you today?',
            failure_message='Please hold on a second.',
            max_history=32,
        ))
        .with_tts(...)  # configure your TTS vendor
    )
    ```
  </TabsContent>

  <TabsContent value="typescript">
    ```typescript
    import { Agent, AzureOpenAI } from 'agora-agents';

    // client is your configured Agora client
    const agent = new Agent({ client })
      .withStt(/* configure your STT vendor */)
      .withLlm(new AzureOpenAI({
        apiKey: 'your-azure-api-key',
        resourceName: 'your-resource-name',
        deploymentName: 'your-deployment-name', // the name given to your model deployment in Azure OpenAI Studio
        model: 'gpt-4o-mini',
        systemMessages: [{ role: 'system', content: 'You are a helpful chatbot.' }],
        greetingMessage: 'Hello, how can I assist you today?',
        failureMessage: 'Please hold on a second.',
        maxHistory: 32,
      }))
      .withTts(/* configure your TTS vendor */);
    ```
  </TabsContent>

  <TabsContent value="go">
    ```go
    import "github.com/AgoraIO/agora-agents-go/v2/agentkit/vendors"

    // client is your configured Agora client
    agent := agentkit.NewAgent(client).WithStt(/* configure your STT vendor */).
      WithLlm(
        vendors.NewAzureOpenAI(vendors.AzureOpenAIOptions{
            APIKey:         "your-azure-api-key",
            Endpoint:       "https://your-resource-name.openai.azure.com",
            DeploymentName: "your-deployment-name", // the name given to your model deployment in Azure OpenAI Studio
            Model:          "gpt-4o-mini",
            SystemMessages: []map[string]interface{}{
                {"role": "system", "content": "You are a helpful chatbot."},
            },
            GreetingMessage: "Hello, how can I assist you today?",
            FailureMessage:  "Please hold on a second.",
            MaxHistory:      agora.Int(32),
        }),
    ).WithTts(/* configure your TTS vendor */)
    ```
  </TabsContent>

  <TabsContent value="rest-api">
    Use the following `llm` configuration in your request:

    ```json
    "llm": {
        "url": "https://YOUR_RESOURCE_NAME.openai.azure.com/openai/deployments/YOUR_DEPLOYMENT_NAME/chat/completions?api-version=AZURE_API_VERSION",
        "api_key": "<api_key>",
        "system_messages": [
            {
                "role": "system",
                "content": "You are a helpful chatbot."
            }
        ],
        "max_history": 32,
        "greeting_message": "Hello, how can I assist you today?",
        "failure_message": "Please hold on a second.",
        "style": "openai",
        "vendor": "azure",
        "params": {
            "model": "gpt-4o-mini"
        }
    }
    ```
  </TabsContent>
</Tabs>

### Key parameters [#key-parameters]

<ParameterList title="llm" required="true">
  <Parameter name="api_key" type="string" required="true">
    Find your API key in the Azure portal under your OpenAI resource.
  </Parameter>

  <Parameter name="url" type="string" required="true">
    Replace `YOUR_RESOURCE_NAME` with your Azure resource name and `YOUR_DEPLOYMENT_NAME` with your model deployment name.
  </Parameter>

  <Parameter name="params" type="object" required="true">
    <Parameter name="model" type="string" required="true">
      Use the deployment name you created in Azure, not the base model name.
    </Parameter>
  </Parameter>
</ParameterList>

For advanced configuration options, deployment setup, and detailed parameter descriptions, see the [Azure OpenAI API documentation](https://learn.microsoft.com/en-us/azure/ai-services/openai/reference).