livekit-plugins-azure
Agent Framework plugin for services from Azure
Decision gist · record as of 2026-08-14
Yes, if you're building LiveKit agents that need Azure Speech or other Azure AI services. The package is actively maintained, has low install friction, uses a permissive license, and integrates cleanly into the LiveKit ecosystem. Verify that Azure Speech is the service you need (Azure OpenAI requires a separate plugin) and that you can provide the required environment variables for authentication.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later.
- Azure Speech Key and Deployment Region must be set as environment variables (AZURE_SPEECH_KEY and AZURE_SPEECH_REGION).
- Low friction install with a pure-Python wheel.
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 permissive license allows commercial and private use with minimal restrictions, making it suitable for most production deployments.
last release 2026-08-13 (1 days) · last repo commit 2026-08-14 · 13,003 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 311,194 downloads/mo, #7,738 on PyPI
Alternatives
Verify before relying
pip install livekit-plugins-azure
import livekit_plugins_azure
# Configure with AZURE_SPEECH_KEY and AZURE_SPEECH_REGION environment variables- Specific Azure AI services supported beyond Azure Speech (e.g., language, translation, vision capabilities)
- Whether this plugin works with Azure OpenAI or if the separate OpenAI plugin is required
- Performance characteristics and latency for real-time speech processing
- Cost implications of using Azure Speech through this integration
What it is and what it does
This package is a plugin for the LiveKit Agents framework that adds support for Azure AI services, with a focus on Azure Speech for voice processing. It acts as a bridge between LiveKit's real-time communication infrastructure and Azure's cognitive services, allowing developers to build voice-enabled agents that can process audio in real time using Azure's speech recognition and synthesis capabilities.
The plugin is designed to work within the LiveKit Agents ecosystem and requires configuration through environment variables for Azure credentials. It's part of a broader plugin architecture where other Azure services (like Azure OpenAI) are handled by separate plugins. The package is actively maintained and targets modern Python versions (3.10+), indicating it's built for current development practices.
Use it for
- Build voice-enabled chatbots using LiveKit's agent framework with Azure Speech for transcription and synthesis
- Create real-time voice assistants that process audio streams through Azure cognitive services
- Integrate Azure Speech capabilities into existing LiveKit video/voice applications for AI-driven interactions
- Develop multi-modal agents that combine video, audio, and Azure AI services for interactive applications
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you're building LiveKit agents that need Azure Speech or other Azure AI services.
The package is actively maintained, has low install friction, uses a permissive license, and integrates cleanly into the LiveKit ecosystem. Verify that Azure Speech is the service you need (Azure OpenAI requires a separate plugin) and that you can provide the required environment variables for authentication.
Install
livekit-plugins-azure on PyPI
Before you install
Low friction install with a pure-Python wheel. Actively maintained with a release one day old and a well-established parent project (13003 stars). Requires only two runtime dependencies: azure-cognitiveservices-speech and livekit-agents.
Requires Python 3.10 or later. Azure Speech Key and Deployment Region must be set as environment variables (AZURE_SPEECH_KEY and AZURE_SPEECH_REGION).
License in practice
Apache-2.0 permissive license allows commercial and private use with minimal restrictions, making it suitable for most production deployments.
Quickstart
pip install livekit-plugins-azure
import livekit_plugins_azure
# Configure with AZURE_SPEECH_KEY and AZURE_SPEECH_REGION environment variables
Verify before relying
- Specific Azure AI services supported beyond Azure Speech (e.g., language, translation, vision capabilities)
- Whether this plugin works with Azure OpenAI or if the separate OpenAI plugin is required
- Performance characteristics and latency for real-time speech processing
- Cost implications of using Azure Speech through this integration
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release >=3.10.0 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 2 packagesazure-cognitiveservices-speechlivekit-agents |
| Maintenance | Actively maintained 1 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 311,194 / month, #7,738 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Intended Audience :: DevelopersLicense :: OSI Approved :: Apache Software LicenseProgramming Language :: Python :: 3Programming Language :: Python :: 3 :: OnlyProgramming Language :: Python :: 3.10Topic :: Multimedia :: Sound/AudioTopic :: Multimedia :: VideoTopic :: Scientific/Engineering :: Artificial Intelligence |
Evidence: livekit_plugins_azure-1.6.10-py3-none-any.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “azure speech integration”
- livekit-plugins-azureIntegrates Azure AI services, particularly Azure Speech, into LiveKit…
- azure-cognitiveservices-speechProvides Python bindings to Microsoft's Speech Service SDK for…
- livekit-plugins-openaiIntegrates OpenAI's Realtime, Responses, LLM, TTS, and STT APIs into…
Give your agent the search over MCP, or paste the wish link into any chat.
More Artificial Intelligence packages
LiteLLM provides a unified Python interface to call 100+ LLM providers (OpenAI, Anthropic, Gemini, Bedrock, Azure, and others) using OpenAI-compatible API format, available as both a Python SDK and a self-hosted AI Gateway proxy server.
Install it if you need to work with multiple LLM providers or want to centralize LLM routing in your organization.
Client library and CLI tool for downloading, uploading, and managing models, datasets, and repositories on the Hugging Face Hub platform.
Install it if you work with Hugging Face Hub models or datasets.
LangChain provides a framework for building agents and LLM-powered applications by composing language models, tools, and memory through a unified API that abstracts over multiple model providers.
hf-xet provides chunk-based deduplication and efficient file transfer for the Hugging Face Hub, enabling faster uploads and downloads of large files with local disk caching.
Tokenizers converts raw text into token sequences for NLP models, with support for training custom vocabularies and using pre-built tokenizers (BPE, WordPiece) optimized for speed via Rust.
Transformers provides a unified framework for loading, fine-tuning, and running state-of-the-art pretrained models across text, vision, audio, video, and multimodal tasks using PyTorch, JAX, or TensorFlow.
Install it if you need to run or train any transformer-based model for NLP, vision, audio, or multimodal tasks.
See also livekit-plugins-openai · livekit-plugins-cartesia · livekit-plugins-google · livekit-plugins-deepgram · livekit-plugins-ai-coustics · livekit-plugins-aws · azure-cognitiveservices-speech · livekit-plugins-assemblyai · livekit-plugins-gladia · livekit-plugins-anam