livekit-plugins-inworld
Agent Framework plugin for voice synthesis and speech-to-text with Inworld's API.
Decision gist · record as of 2026-08-14
Yes, if you are building a LiveKit voice agent and want to use Inworld's TTS and STT APIs. The package is actively maintained, has no known vulnerabilities, installs cleanly with minimal dependencies, and the Apache-2.0 license is permissive. The main prerequisite is an Inworld API key and willingness to use their services; evaluate Inworld's pricing and model quality for your use case before committing.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires INWORLD_API_KEY environment variable set in .env file; obtain from https://platform.inworld.ai/login.
- Requires Python >=3.10.0.
- Low friction: pure Python wheel with a single runtime dependency (livekit-agents).
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 permissive license allows commercial and private use with minimal restrictions—suitable for most production deployments.
last release 2026-08-13 (1 days) · last repo commit 2026-08-14 · 13,004 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 81,604 downloads/mo, #14,213 on PyPI
Alternatives
Verify before relying
pip install livekit-plugins-inworld
from livekit.plugins import inworld
tts = inworld.TTS(voice="Hades")
stt = inworld.STT(model="inworld/inworld-stt-1")- Whether Inworld API pricing or rate limits affect typical agent workloads.
- Supported voice IDs and whether custom cloned voices are available in all Inworld plans.
- Latency characteristics of WebSocket streaming mode under typical network conditions.
What it is and what it does
This package is a LiveKit Agents plugin that wraps Inworld's text-to-speech and speech-to-text APIs, allowing you to build voice agents that synthesize speech and transcribe user input using Inworld's models. It handles the integration plumbing so you can drop Inworld TTS and STT components into a LiveKit AgentSession alongside an LLM and other agent logic.
The TTS side supports multiple voice IDs, encoding formats (LINEAR16, MP3, OGG_OPUS, ALAW, MULAW, FLAC), sample rates, and real-time streaming via WebSocket with buffering controls for lower-latency synthesis. The STT side provides streaming speech-to-text with optional voice profile detection. Both are designed to work within LiveKit's real-time agent framework, so you configure them as session components and let the framework handle audio routing.
Use it for
- Build a voice agent that listens to user speech, transcribes it with Inworld STT, processes it through an LLM, and speaks back using Inworld TTS.
- Stream text incrementally to Inworld TTS as it's generated by an LLM, reducing latency in conversational interactions.
- Integrate Inworld's voice synthesis into an existing LiveKit agent to replace or supplement other TTS providers.
- Deploy a multi-modal agent that combines LiveKit's video/audio infrastructure with Inworld's speech models for real-time conversations.
- Use voice profile detection with Inworld STT to identify speaker characteristics during transcription in multi-participant sessions.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are building a LiveKit voice agent and want to use Inworld's TTS and STT APIs.
The package is actively maintained, has no known vulnerabilities, installs cleanly with minimal dependencies, and the Apache-2.0 license is permissive. The main prerequisite is an Inworld API key and willingness to use their services; evaluate Inworld's pricing and model quality for your use case before committing.
Install
livekit-plugins-inworld on PyPI
Before you install
Low friction: pure Python wheel with a single runtime dependency (livekit-agents). Released 1 day ago with active maintenance; the parent repository has 13004 stars and current commit history.
Requires INWORLD_API_KEY environment variable set in .env file; obtain from https://platform.inworld.ai/login. Requires Python >=3.10.0.
License in practice
Apache-2.0 permissive license allows commercial and private use with minimal restrictions—suitable for most production deployments.
Quickstart
pip install livekit-plugins-inworld
from livekit.plugins import inworld
tts = inworld.TTS(voice="Hades")
stt = inworld.STT(model="inworld/inworld-stt-1")
Verify before relying
- Whether Inworld API pricing or rate limits affect typical agent workloads.
- Supported voice IDs and whether custom cloned voices are available in all Inworld plans.
- Latency characteristics of WebSocket streaming mode under typical network conditions.
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 | 1 packagelivekit-agents |
| Maintenance | Actively maintained 1 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 81,604 / month, #14,213 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_inworld-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 › “inworld tts stt livekit”
- livekit-plugins-inworldIntegrates Inworld's text-to-speech and speech-to-text APIs into…
- livekit-plugins-sonioxIntegrates Soniox speech-to-text and text-to-speech APIs into LiveKit…
- livekit-plugins-sarvamIntegrates Sarvam.ai's Indian-language voice AI services…
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-soniox · livekit-plugins-speechmatics · livekit-plugins-deepgram · livekit-plugins-cartesia · livekit-plugins-sarvam · livekit-plugins-gladia · livekit-plugins-google · livekit-plugins-assemblyai · livekit-plugins-elevenlabs · kugelaudio