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We shipped Agent Console, a realtime debugging surface for voice agents. Talk to your agent and see the entire pipeline live, from audio and latency to tool calls, transcripts, and participant state. Available now in the LiveKit Cloud dashboard.

LiveKit

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11,915 görüntüleme • 2 ay önce •via X (Twitter)

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Add a face to your voice agent. LiveAvatar by HeyGen is now supported in LiveKit Agents. Add a realtime human avatar to your agent without rebuilding the conversation loop. Your LiveKit agent still owns the room, turn-taking, model orchestration, and voice pipeline. LiveAvatar renders the synchronized face and video stream. Useful for product demos, onboarding, tutoring, and support agents that need a visual layer.

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We shipped LiveKit Turn Detector v1. Instead of reading transcripts, it listens to speech directly, combining semantic and acoustic cues into one end-of-turn prediction. The result: high accuracy, low latency—the best model we tested across 14 languages. Available on LiveKit Cloud.

We shipped LiveKit Turn Detector v1. Instead of reading transcripts, it listens to speech directly, combining semantic and acoustic cues into one end-of-turn prediction. The result: high accuracy, low latency—the best model we tested across 14 languages. Available on LiveKit Cloud.

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We shipped the tutorial for Agents UI. In 5 minutes you'll have a fully wired voice agent frontend with audio visualizers, media controls, and session management built directly into your codebase. Watch it, build it, own it. shadcn inside™.

We shipped the tutorial for Agents UI. In 5 minutes you'll have a fully wired voice agent frontend with audio visualizers, media controls, and session management built directly into your codebase. Watch it, build it, own it. shadcn inside™.

LiveKit

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Introducing Agents UI, an open-source shadcn component library for building polished React frontends for your voice agents. Audio visualizers. Media controls. Session management tools. Chat transcripts. All wired to LiveKit Agents. Install via the shadcn CLI and own the code.

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LiveKit

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You can now deploy AI voice agents to LiveKit Cloud. We handle: • Stateful load balancing • Capacity management • Draining and instant rollbacks • Operational observability

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LiveKit

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xAI STT is live. You can now run a complete cascaded voice agent pipeline on xAI (STT + Grok + TTS) through LiveKit Inference with one API key, giving you more control, full visibility, and easy component swaps.

xAI STT is live. You can now run a complete cascaded voice agent pipeline on xAI (STT + Grok + TTS) through LiveKit Inference with one API key, giving you more control, full visibility, and easy component swaps.

LiveKit

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Learn to build conversational AI voice agents in "Building AI Voice Agents for Production", created in collaboration with LiveKit and RealAvatar, and taught by dsa (Co-founder & CEO of LiveKit), Shayne (Developer Advocate, LiveKit), and Nedelina Teneva (Head of AI at RealAvatar, an AI Fund portfolio company). Voice agents combine speech and reasoning capabilities to enable real-time conversations. They're already being used to support customer service, to improve accessibility in healthcare, for entertainment applications, and for talk therapy. In this course, you’ll learn to build voice agents that listen, reason, and respond naturally. You’ll follow the architecture used to create the "AI Andrew" Avatar, a collaborative project between and RealAvatar that responds to users in what sounds like my voice. You’ll build a voice agent from scratch and deploy it to the cloud, enabling support for many simultaneous users. What you’ll learn: - Understand the fundamentals of voice agents, including key components like speech-to-text (STT), text-to-speech (TTS), and LLMs, and how latency is introduced at each layer. - Explore voice agent architectures and the trade-offs between modular pipelines and speech-to-speech APIs. - Explore how platforms like LiveKit mitigate latency issues with optimized networking infrastructure and low-latency communication protocols. - Learn how to connect client devices to voice agents using WebRTC—and why it outperforms HTTP and WebSocket for low-latency audio streaming. - Incorporate voice activity detection (VAD), end-of-turn detection, and context management to detect turns, handle interruptions, and manage conversational flow. - Understand the trade-offs between latency, quality, and cost in an example in which you build a voice agent and change its voice. - Equip your agent with metrics to measure latency at each stage of the voice pipeline and learn the key levers you can pull to make your agent faster and more responsive. The voice agents built in this course also incorporate voice technology from , a supporting contributor to the project. By the end of this course, you'll have learned the components of an AI voice agent pipeline, combined them into a system with low-latency communication, and deployed them on cloud infrastructure so it scales to many users. I’m looking forward to seeing what voice agents you build from this course! Please sign up here:

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How can a voice agent tell when you’re actually interrupting it? VAD is too sensitive—laughs, “mm-hmm,” or a sneeze shouldn’t stop the agent. We trained an audio model for adaptive interruption handling so agents can distinguish real interruptions from noise.

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LiveKit

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Gemini 3.1 Flash Live just dropped and it's available with LiveKit today. This is the first Gemini 3 native audio model on the Live API. Better instruction following, improved tool calling, reduced speaker drift, and support for 70+ languages. Audio in, audio out. No text conversion in between.

Gemini 3.1 Flash Live just dropped and it's available with LiveKit today. This is the first Gemini 3 native audio model on the Live API. Better instruction following, improved tool calling, reduced speaker drift, and support for 70+ languages. Audio in, audio out. No text conversion in between.

LiveKit

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Introducing LiveKit Inference — a new cloud service that gives you access to the most popular voice AI models with just your LiveKit API key. We manage rate limits for you, report on usage, and consolidate billing. All LiveKit Cloud plans now include free monthly inference credits. A single string update allows you to call models from: AssemblyAI Deepgram Google DeepMind Inworld AI OpenAI Rime

Introducing LiveKit Inference — a new cloud service that gives you access to the most popular voice AI models with just your LiveKit API key. We manage rate limits for you, report on usage, and consolidate billing. All LiveKit Cloud plans now include free monthly inference credits. A single string update allows you to call models from: AssemblyAI Deepgram Google DeepMind Inworld AI OpenAI Rime

LiveKit

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Next, the Traces dashboard now supports Realtime API sessions, letting you visualize voice agent runs, including audio input/output, tool invocations, and interruptions, whether created via the API or the Agents SDK. Here's Alex Gamble to show you how it works:

Next, the Traces dashboard now supports Realtime API sessions, letting you visualize voice agent runs, including audio input/output, tool invocations, and interruptions, whether created via the API or the Agents SDK. Here's Alex Gamble to show you how it works:

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Voice cloning is now available on LiveKit Inference. We’re launching with Inworld AI and Cartesia. Clone a voice once and use it across multiple TTS providers, with automatic fallback to the same voice if a provider fails mid-call. Free to create and available on all paid plans today.

Voice cloning is now available on LiveKit Inference. We’re launching with Inworld AI and Cartesia. Clone a voice once and use it across multiple TTS providers, with automatic fallback to the same voice if a provider fails mid-call. Free to create and available on all paid plans today.

LiveKit

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New course: Add voice to your AI agents and applications, built with Vocal Bridge (disclosure: an AI Fund portfolio company) and taught by its CEO Ashwyn Sharma. Voice applications historically required making a hard tradeoff: using fast voice-to-voice models that sacrifice reliability, or accurate speech-to-text pipelines that add latency. This course teaches you how to build voice agents that are both reliable and fast. You'll build three types of voice-enabled applications: a voice-interactive game where voice commands and mouse clicks work together over a single channel, an agent that gains a voice in about 10 lines of code without touching its prompts or tools, and an agent that places outbound phone calls using a make_phone_call function. Skills you'll gain: - Add a voice layer to an existing agent without rewriting your prompts, RAG pipeline, or tools - Give an agent the ability to place outbound calls and stream transcripts back live - Set up voice evaluation to score calls, catch regressions, and improve quality before deployment Join and add voice to your agents without overhauling your architecture:

New course: Add voice to your AI agents and applications, built with Vocal Bridge (disclosure: an AI Fund portfolio company) and taught by its CEO Ashwyn Sharma. Voice applications historically required making a hard tradeoff: using fast voice-to-voice models that sacrifice reliability, or accurate speech-to-text pipelines that add latency. This course teaches you how to build voice agents that are both reliable and fast. You'll build three types of voice-enabled applications: a voice-interactive game where voice commands and mouse clicks work together over a single channel, an agent that gains a voice in about 10 lines of code without touching its prompts or tools, and an agent that places outbound phone calls using a make_phone_call function. Skills you'll gain: - Add a voice layer to an existing agent without rewriting your prompts, RAG pipeline, or tools - Give an agent the ability to place outbound calls and stream transcripts back live - Set up voice evaluation to score calls, catch regressions, and improve quality before deployment Join and add voice to your agents without overhauling your architecture:

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Grok's Text to Speech API is now available in LiveKit Inference. Natural, expressive voices with low-latency streaming. Multilingual in 20+ languages. Telephony and production-ready out of the box. One API key. No extra setup. →

Grok's Text to Speech API is now available in LiveKit Inference. Natural, expressive voices with low-latency streaming. Multilingual in 20+ languages. Telephony and production-ready out of the box. One API key. No extra setup. →

LiveKit

159,093 görüntüleme • 3 ay önce

I built a simple voice assistant in 70 lines of Python code. It uses: • LiveKit - The voice agent • AssemblyAI - To turn your voice into text • OpenAI - The brain of the agent, and to turn text into audio There's something really cool about this:

I built a simple voice assistant in 70 lines of Python code. It uses: • LiveKit - The voice agent • AssemblyAI - To turn your voice into text • OpenAI - The brain of the agent, and to turn text into audio There's something really cool about this:

Santiago

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Big release here! AG-UI 🤝 Google A2A Embed A2A multi-agent meshes in your frontend, and build fullstack multi-agent apps with A2A and AG-UI. 🔍How it works: Simply drop-in A2A agent endpoints, and an A2A AG-UI orchestrator agent will bi-directionally stream events between your Agents & application. Includes: - UI for A2A Interactions - Generative UI for Agent Tool Calls - Human-in-the Loop Approvals - State Synchronization (agent mesh application state) - Frontend Tool Calls for A2A Agents Watch the demo below > LangGraph & Google ADK agents working together simultaneously inside an app Demo GitHub, docs, and more 👇

Big release here! AG-UI 🤝 Google A2A Embed A2A multi-agent meshes in your frontend, and build fullstack multi-agent apps with A2A and AG-UI. 🔍How it works: Simply drop-in A2A agent endpoints, and an A2A AG-UI orchestrator agent will bi-directionally stream events between your Agents & application. Includes: - UI for A2A Interactions - Generative UI for Agent Tool Calls - Human-in-the Loop Approvals - State Synchronization (agent mesh application state) - Frontend Tool Calls for A2A Agents Watch the demo below > LangGraph & Google ADK agents working together simultaneously inside an app Demo GitHub, docs, and more 👇

CopilotKit🪁

31,845 görüntüleme • 9 ay önce

Voice-controlled UI. This is an agent design pattern I'm calling EPIC, "explicit prompting for implicit coordination." Feel free to suggest a better name. :-) In the video, I'm navigating around a map, conversationally, pulling in information dynamically from tool calls and realtime streamed events. There are two separate agents (inference loops) here: a voice agent and a UI control agent. They know about each other (at the prompt level) but they work independently.

Voice-controlled UI. This is an agent design pattern I'm calling EPIC, "explicit prompting for implicit coordination." Feel free to suggest a better name. :-) In the video, I'm navigating around a map, conversationally, pulling in information dynamically from tool calls and realtime streamed events. There are two separate agents (inference loops) here: a voice agent and a UI control agent. They know about each other (at the prompt level) but they work independently.

kwindla

14,091 görüntüleme • 5 ay önce

Your agent: Call me, maybe? ❤️ Check out how we used the Copilot SDK to give an agent a voice tool, allowing it to initiate a call and talk back in real time. 👀

Your agent: Call me, maybe? ❤️ Check out how we used the Copilot SDK to give an agent a voice tool, allowing it to initiate a call and talk back in real time. 👀

GitHub

24,413 görüntüleme • 4 ay önce

Introducing: Agent Messenger The easiest way to let your agents talk to other agents. Dro a CLI + Skill into your agent and let it discover & talk to agents from your friends, coworkers and even strangers ⚠️ Live on Product Hunt - LINK BELOW - Please consider upvoting ⚠️

Introducing: Agent Messenger The easiest way to let your agents talk to other agents. Dro a CLI + Skill into your agent and let it discover & talk to agents from your friends, coworkers and even strangers ⚠️ Live on Product Hunt - LINK BELOW - Please consider upvoting ⚠️

Patrick Tobler

19,868 görüntüleme • 2 ay önce