lmux-azure-foundry

Azure AI Foundry provider for lmux. Uses the openai SDK's AzureOpenAI client.

Supports chat completions, streaming, embeddings, and the Responses API.

Part of the lmux ecosystem: standardized interface, cost tracking on every response, and registry-based routing across providers.

Optional Extras

  • lmux-azure-foundry[identity]: Azure AD token authentication via azure-identity

Auth

Three authentication methods:

API Key (default)

Set AZURE_FOUNDRY_API_KEY in your environment:

from lmux_azure_foundry import AzureFoundryProvider

provider = AzureFoundryProvider(endpoint="https://your-resource.openai.azure.com")

Azure AD Token

from lmux_azure_foundry import AzureFoundryProvider, AzureAdToken

provider = AzureFoundryProvider(
    endpoint="https://your-resource.openai.azure.com",
    auth=my_auth_returning_azure_ad_token,
)

Token Provider

from lmux_azure_foundry import AzureFoundryTokenAuthProvider

provider = AzureFoundryProvider(
    endpoint="https://your-resource.openai.azure.com",
    auth=AzureFoundryTokenAuthProvider(),  # uses azure-identity DefaultAzureCredential
)

Usage

Chat

from lmux import UserMessage

response = provider.chat("gpt-4o", [UserMessage(content="Hello")])
print(response.content)
print(response.cost)

Streaming

for chunk in provider.chat_stream("gpt-4o", [UserMessage(content="Hello")]):
    if chunk.delta:
        print(chunk.delta, end="")

Embeddings

response = provider.embed("text-embedding-3-small", "Hello")
print(response.embeddings)

Responses API

Required for models that are only served through the Responses API:

response = provider.create_response("gpt-5-pro", "Hello")
print(response.output_text)

Async

All methods have async variants: achat, achat_stream, aembed, acreate_response.

Registry

Use with the lmux registry to route across multiple providers:

from lmux import Registry

registry = Registry()
registry.register("azure", provider)
response = registry.chat("azure/gpt-4o", messages)

Provider Params

from lmux_azure_foundry import AzureFoundryParams

response = provider.chat(
    "gpt-4o",
    messages,
    provider_params=AzureFoundryParams(deployment_type="data_zone"),
)
Parameter Type Description
reasoning_effort "low" | "medium" | "high" Reasoning effort for o-series models
seed int Deterministic sampling seed
user str End-user identifier
deployment_type "global" | "data_zone" | "regional" Affects cost calculation only, not sent to API

Constructor Options

AzureFoundryProvider(
    endpoint=...,      # required, Azure resource endpoint
    auth=...,          # AuthProvider, default: AzureFoundryKeyAuthProvider()
    api_version=...,   # API version (default: "2025-04-01-preview")
    timeout=...,       # Request timeout in seconds
    max_retries=...,   # Max retry attempts
)

Project links

Data verified by PyPI on Jul 10, 2026
Data provided by the project maintainers, verified at the time the release was uploaded to PyPI.

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Newer release available (0.10.0)

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for cluebbehusen from gravatar.com cluebbehusen

Credits

PyPI data
Data sourced directly from PyPI's database.

Author: Connor Luebbehusen

GitHub Statistics

Data verified by PyPI on Jul 10, 2026
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License expression

MIT
View SPDX License List

Requires

Python >=3.13

Provides Extra

identity

Tags

llm ai azure openai language-model

Classifiers

Report project as malware

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

lmux_azure_foundry-0.7.0.tar.gz (12.5 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

lmux_azure_foundry-0.7.0-py3-none-any.whl (15.9 kB view details)

Uploaded Python 3

File details

Details for the file lmux_azure_foundry-0.7.0.tar.gz.

File metadata

  • Download URL: lmux_azure_foundry-0.7.0.tar.gz
  • Upload date:
  • Size: 12.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for lmux_azure_foundry-0.7.0.tar.gz
Algorithm Hash digest
SHA256 950899afd991f2f5c10a80db7b6f1ba18019429d563d866346522a6884dad782
MD5 8f22b891b7d37b6defa79a0b6610fe8e
BLAKE2b-256 f812c50da9b85944d108cd45a2aa4614fb089e2deca0d1a785e3ac07fa3a10de

See more details on using hashes here.

Provenance

The following attestation bundles were made for lmux_azure_foundry-0.7.0.tar.gz:

Publisher: publish.yml on cluebbehusen/lmux

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file lmux_azure_foundry-0.7.0-py3-none-any.whl.

File metadata

File hashes

Hashes for lmux_azure_foundry-0.7.0-py3-none-any.whl
Algorithm Hash digest
SHA256 a2e9be7c6e7c1b9b8c30ad927381defe382d345150ac5f5ed870f7dfaac6caf0
MD5 c482555765d3d939ca06ad32ce20472f
BLAKE2b-256 1ac4032d45bbcf48f83f2b778296af681c35618cbdd8f140ff17f470949a5501

See more details on using hashes here.

Provenance

The following attestation bundles were made for lmux_azure_foundry-0.7.0-py3-none-any.whl:

Publisher: publish.yml on cluebbehusen/lmux

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page