serapeum-azure-openai 0.1.0

serapeum azure openai integration

Serapeum Azure OpenAI Provider

Azure OpenAI integration for the Serapeum LLM framework

The serapeum-azure-openai package extends serapeum-openai to work with Azure OpenAI Service deployments. It provides:

• Azure Authentication: API key and Microsoft Entra ID (Azure AD) support
• Deployment Management: Routes requests to your named Azure deployments
• Full Feature Parity: Uses the same chat, streaming, tool calling, and structured output capabilities as the OpenAI provider via shared base classes

The public classes are Completions and Responses, which are built from an AzureClient mixin combined with the corresponding serapeum.openai base classes (OpenAICompletions and OpenAIResponses), so all OpenAI provider features work transparently with Azure deployments.

Installation

From Source

cd libs/providers/azure-openai
uv sync --active

From PyPI (when published)

pip install serapeum-azure-openai

Prerequisites

1. An Azure OpenAI resource with at least one model deployment
2. Either an API key or Microsoft Entra ID credentials

Set the required environment variables:

export AZURE_OPENAI_API_KEY="your-azure-api-key"
export AZURE_OPENAI_ENDPOINT="https://YOUR_RESOURCE.openai.azure.com/"
export OPENAI_API_VERSION="2024-02-01"

Quick Start

API Key Authentication

from serapeum.azure_openai import Completions
from serapeum.core.llms import Message, MessageRole

llm = Completions(
    engine="my-gpt4o-deployment",
    model="gpt-4o",
    api_key="your-azure-api-key",
    azure_endpoint="https://YOUR_RESOURCE.openai.azure.com/",
    api_version="2024-02-01",
)

messages = [
    Message(role=MessageRole.USER, content="Explain quantum computing in one sentence.")
]
response = llm.chat(messages)
print(response.message.content)

Using the Responses API

from serapeum.azure_openai import Responses

llm = Responses(
    engine="my-gpt4o-deployment",
    model="gpt-4o",
    api_key="your-azure-api-key",
    azure_endpoint="https://YOUR_RESOURCE.openai.azure.com/",
    api_version="2024-02-01",
)

Microsoft Entra ID (Azure AD) Authentication

from azure.identity import DefaultAzureCredential, get_bearer_token_provider
from serapeum.azure_openai import Completions

credential = DefaultAzureCredential()
token_provider = get_bearer_token_provider(
    credential, "https://cognitiveservices.azure.com/.default"
)

llm = Completions(
    engine="my-gpt4o-deployment",
    model="gpt-4o",
    azure_ad_token_provider=token_provider,
    use_azure_ad=True,
    azure_endpoint="https://YOUR_RESOURCE.openai.azure.com/",
    api_version="2024-02-01",
)

Features

Since Completions and Responses share the same base classes as the OpenAI provider, all features from serapeum-openai are available. See the OpenAI provider README for full usage examples of:

• Streaming (sync and async)
• Tool calling
• Structured outputs with Pydantic models
• Completion-style usage with prompt templates

The only difference is initialization: use Completions or Responses with your deployment name and Azure endpoint instead of the OpenAI equivalents with an API key.

Configuration

from serapeum.azure_openai import Completions

llm = Completions(
    engine="my-deployment",                # Required: Azure deployment name
    model="gpt-4o",                        # Required: model name
    azure_endpoint="https://...",          # Azure resource endpoint
    api_key="...",                         # Azure API key (or env var)
    api_version="2024-02-01",             # Required: API version
    use_azure_ad=False,                    # Use Entra ID authentication
    azure_ad_token_provider=None,          # Custom token provider callable
    temperature=0.7,                       # Sampling temperature
    max_tokens=1024,                       # Max tokens to generate
    timeout=60.0,                          # Request timeout
    additional_kwargs={},                  # Extra API parameters
)

The engine parameter accepts several aliases: deployment_name, deployment_id, deployment, or azure_deployment.

Class Hierarchy

AzureClient (mixin)
├── Completions(AzureClient, OpenAICompletions)  ─── Chat Completions API
└── Responses(AzureClient, OpenAIResponses)      ─── Responses API

AzureClient handles Azure-specific fields (engine, azure_endpoint, use_azure_ad, azure_ad_token_provider) and overrides SDK client construction to target Azure OpenAI endpoints.

Package Layout

src/serapeum/azure_openai/
├── __init__.py    # Lazy imports (AzureClient, Completions, Responses, SyncAzureOpenAI, AsyncAzureOpenAI)
├── llm.py         # AzureClient mixin, Completions, and Responses classes
└── utils.py       # Azure AD token refresh, alias resolution

Testing

# All tests (from repo root)
python -m pytest libs/providers/azure-openai/tests

# Skip end-to-end tests
python -m pytest libs/providers/azure-openai/tests -m "not e2e"

Links

• Homepage: github.com/Serapieum-of-alex/serapeum
• Documentation: serapieum-of-alex.github.io/serapeum
• Azure OpenAI Service: learn.microsoft.com/azure/ai-services/openai