Azure OpenAI LLM

Overview

AzureLLMService provides access to Azure OpenAI’s language models through an OpenAI-compatible interface. It inherits from OpenAILLMService and supports streaming responses, function calling, and context management with enterprise-grade security and compliance.

Azure LLM API Reference

Pipecat’s API methods for Azure OpenAI integration

Example Implementation

Complete example with function calling

Azure OpenAI Documentation

Official Azure OpenAI documentation and setup

Azure Portal

Create OpenAI resources and get credentials

Installation

To use Azure OpenAI services, install the required dependency:

uv add "pipecat-ai[azure]"

Prerequisites

Azure OpenAI Setup

Before using Azure OpenAI LLM services, you need:

Azure Account: Sign up at Azure Portal
OpenAI Resource: Create an Azure OpenAI resource in your subscription
Model Deployment: Deploy your chosen model (GPT-4, GPT-4o, etc.)
Credentials: Get your endpoint and deployment name, plus either:
- An API key for key-based authentication, or
- Microsoft Entra ID credentials for token-based authentication

Environment Variables

AZURE_CHATGPT_ENDPOINT: Your Azure OpenAI endpoint URL
AZURE_CHATGPT_MODEL: Your model deployment name
AZURE_CHATGPT_API_KEY: Your Azure OpenAI API key (required unless using token_provider)

Configuration

str

required

Azure OpenAI endpoint URL. Ending it in /openai/v1 selects the v1 API surface (recommended), where api_version does not apply. Example: "https://my-resource.openai.azure.com/openai/v1".

str | None

default:"None"

Azure OpenAI API key for key-based authentication. Required unless token_provider is given. Raises ValueError when neither is given.

AzureTokenProvider | None

default:"None"

Async callable supplying a Microsoft Entra ID bearer token, used instead of api_key when given. Build one with azure.identity.aio.get_bearer_token_provider() and the https://ai.azure.com/.default scope.

str

default:"None"

deprecated

Deprecated since 0.0.105, removed in 2.0.0. Use settings=AzureLLMService.Settings(model=...) instead.

str | None

default:"None"

deprecated

Deprecated since 1.8.0, removed in 2.0.0. Use an endpoint ending in /openai/v1 instead. Azure API version applied to endpoints outside the v1 API surface. Defaults to 2025-04-01-preview.

AzureLLMService.Settings

default:"None"

Runtime-configurable settings. See Settings below.

Since AzureLLMService inherits from OpenAILLMService, it also accepts the following parameters (its base_url, organization, project, and default_headers arguments are accepted but have no effect):

InputParams

default:"None"

deprecated

Deprecated since 0.0.105, removed in 2.0.0. Use settings=AzureLLMService.Settings(...) instead.

float

default:"5.0"

Request timeout in seconds. Used when retry_on_timeout is enabled to determine when to retry.

bool

default:"False"

Whether to retry the request once if it times out. The retry attempt has no timeout limit.

Settings

Runtime-configurable settings passed via the settings constructor argument using AzureLLMService.Settings(...). These can be updated mid-conversation with LLMUpdateSettingsFrame. See Service Settings for details. AzureLLMService uses the same settings as OpenAILLMService. See the OpenAI LLM Settings section for the full parameter reference.

Usage

Basic Setup

import os

from pipecat.services.azure.llm import AzureLLMService

llm = AzureLLMService(
    api_key=os.getenv("AZURE_CHATGPT_API_KEY"),
    endpoint="https://my-resource.openai.azure.com/openai/v1",
    settings=AzureLLMService.Settings(
        model=os.getenv("AZURE_CHATGPT_MODEL"),
    ),
)

With Microsoft Entra ID Authentication

This requires the azure-identity package (uv add azure-identity), which pipecat-ai[azure] doesn’t install:

from azure.identity.aio import DefaultAzureCredential, get_bearer_token_provider
from pipecat.services.azure.llm import AzureLLMService

llm = AzureLLMService(
    token_provider=get_bearer_token_provider(
        DefaultAzureCredential(), "https://ai.azure.com/.default"
    ),
    endpoint="https://my-resource.openai.azure.com/openai/v1",
    settings=AzureLLMService.Settings(
        model="my-deployment",
    ),
)

With Custom Settings

from pipecat.services.azure.llm import AzureLLMService

llm = AzureLLMService(
    api_key=os.getenv("AZURE_CHATGPT_API_KEY"),
    endpoint="https://my-resource.openai.azure.com/openai/v1",
    settings=AzureLLMService.Settings(
        model=os.getenv("AZURE_CHATGPT_MODEL"),
        temperature=0.7,
        max_completion_tokens=1000,
        frequency_penalty=0.5,
    ),
)

Updating Settings at Runtime

Model settings can be changed mid-conversation using LLMUpdateSettingsFrame:

from pipecat.frames.frames import LLMUpdateSettingsFrame
from pipecat.services.openai.base_llm import OpenAILLMSettings

await worker.queue_frame(
    LLMUpdateSettingsFrame(
        delta=OpenAILLMSettings(
            temperature=0.3,
            max_completion_tokens=500,
        )
    )
)

Notes

Deployment name vs model name: The model parameter should be your Azure deployment name, not the underlying model name (e.g., use "my-gpt4-deployment" instead of "gpt-4").
v1 API surface: Endpoints ending in /openai/v1 use Azure’s v1 API, which tracks new features without requiring a dated api_version. This is the recommended surface. Endpoints without this suffix route through the dated API version 2025-04-01-preview (the last version Azure issued).
Full OpenAI compatibility: Since AzureLLMService inherits from OpenAILLMService, it supports all the same features including function calling, vision input, and streaming responses.

Event Handlers

AzureLLMService supports the same event handlers as OpenAILLMService, inherited from LLMService:

Event	Description
`on_completion_timeout`	Called when an LLM completion request times out
`on_function_calls_started`	Called when function calls are received and execution is about to start
`on_function_calls_cancelled`	Called after one or more in-progress function calls are cancelled

@llm.event_handler("on_completion_timeout")
async def on_completion_timeout(service):
    print("LLM completion timed out")

Get Started

Pipecat Server

Client SDKs

Pipecat Flows

Pipecat Cloud

CLI

Pipecat Context Hub

Azure OpenAI LLM

Overview

Azure LLM API Reference

Example Implementation

Azure OpenAI Documentation

Azure Portal

Installation

Prerequisites

Azure OpenAI Setup

Environment Variables

Configuration

Settings

Usage

Basic Setup

With Microsoft Entra ID Authentication

With Custom Settings

Updating Settings at Runtime

Notes

Event Handlers

​Overview

Azure LLM API Reference

Example Implementation

Azure OpenAI Documentation

Azure Portal

​Installation

​Prerequisites

​Azure OpenAI Setup

​Environment Variables

​Configuration

​Settings

​Usage

​Basic Setup

​With Microsoft Entra ID Authentication

​With Custom Settings

​Updating Settings at Runtime

​Notes

​Event Handlers

Overview

Installation

Prerequisites

Azure OpenAI Setup

Environment Variables

Configuration

Settings

Usage

Basic Setup

With Microsoft Entra ID Authentication

With Custom Settings

Updating Settings at Runtime

Notes

Event Handlers