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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:

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Santiago

451,925 subscribers

34,632 次观看 • 10 个月前 •via X (Twitter)

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Here is the fastest way to turn text into a voice. Less than 100ms to start streaming. This is an absolute must for anyone who wants to build a voice agent that doesn't sound robotic (latency kills the perception of reality). Here is how easy this is:
3:38

Here is the fastest way to turn text into a voice. Less than 100ms to start streaming. This is an absolute must for anyone who wants to build a voice agent that doesn't sound robotic (latency kills the perception of reality). Here is how easy this is:

Santiago

38,164 次观看 • 1 个月前

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.
4:52

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

11,908 次观看 • 1 个月前

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:
2:41

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:

Andrew Ng

87,377 次观看 • 1 年前

I really enjoyed doing these voice impressions, and honestly, I'd love to one day turn the dream of becoming a voice actor into reality!
0:34

I really enjoyed doing these voice impressions, and honestly, I'd love to one day turn the dream of becoming a voice actor into reality!

Ndukauba

71,108 次观看 • 6 个月前

I built a service desk agent using ElevenLabs’ new Conversational AI Agents feature. Watch the video to see how responsive it is! Previously, I used ElevenLabs for cloning my voice and used my generated voice for narrations in some of my youtube videos. This feature takes elevenlabs' voice AI to a whole new level! It simplifies systems that used to require separate TTS (text-to-speech) and STT (speech-to-text) processes for both sides of the conversation. Now, it’s much simpler! Create your own agent here What will you create with this?
3:29

I built a service desk agent using ElevenLabs’ new Conversational AI Agents feature. Watch the video to see how responsive it is! Previously, I used ElevenLabs for cloning my voice and used my generated voice for narrations in some of my youtube videos. This feature takes elevenlabs' voice AI to a whole new level! It simplifies systems that used to require separate TTS (text-to-speech) and STT (speech-to-text) processes for both sides of the conversation. Now, it’s much simpler! Create your own agent here What will you create with this?

Melvin Vivas

27,722 次观看 • 1 年前

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™.
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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™.

LiveKit

20,232 次观看 • 3 个月前

Preview of a Gaia 🌱 device! Turn-by-turn voice conversation with your own knowledge assistant (a Gaia node). 💸 $15 worth of hardware (pre-tariff!) 🌱 Voice-to-text, LLM and text-to-voice AI models on Gaia nodes 📖 Open source all-the-way — hardware, firmware, server, AI models 🦀 Rust all-the-way from firmware to AI server Notice how I switched to another language (Chinese) in the middle of the conversation and it seamlessly switched too. Very smart. PS. we are still optimizing performance before the software release.
1:24

Preview of a Gaia 🌱 device! Turn-by-turn voice conversation with your own knowledge assistant (a Gaia node). 💸 $15 worth of hardware (pre-tariff!) 🌱 Voice-to-text, LLM and text-to-voice AI models on Gaia nodes 📖 Open source all-the-way — hardware, firmware, server, AI models 🦀 Rust all-the-way from firmware to AI server Notice how I switched to another language (Chinese) in the middle of the conversation and it seamlessly switched too. Very smart. PS. we are still optimizing performance before the software release.

Michael Yuan

14,983 次观看 • 1 年前

What if you could talk to your Telegram bot and it actually talked back? Learn how built a voice-enabled Telegram bot with the Gemini Interactions API in ~400 lines of Python. Send a voice note in any language, Gemini understands the audio and replies with text and a spoken voice message. Uses: - Gemini 3.1 Flash Lite for reasoning, 3.1 Flash TTS for speech - Interactions API handles multi-turn memory server-side - Native audio input, no transcription step needed - Deploys to Cloud Run with scale-to-zero Awesome work by Thor 雷神 ⚡️. 🤗
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What if you could talk to your Telegram bot and it actually talked back? Learn how built a voice-enabled Telegram bot with the Gemini Interactions API in ~400 lines of Python. Send a voice note in any language, Gemini understands the audio and replies with text and a spoken voice message. Uses: - Gemini 3.1 Flash Lite for reasoning, 3.1 Flash TTS for speech - Interactions API handles multi-turn memory server-side - Native audio input, no transcription step needed - Deploys to Cloud Run with scale-to-zero Awesome work by Thor 雷神 ⚡️. 🤗

Philipp Schmid

11,156 次观看 • 1 个月前

Introducing Speech Engine. Developers can now turn their existing chat agent into a full voice agent with one prompt. Speech Engine combines our leading speech, transcription, and voice orchestration models into a single pipeline - all custom built to work best together.
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Introducing Speech Engine. Developers can now turn their existing chat agent into a full voice agent with one prompt. Speech Engine combines our leading speech, transcription, and voice orchestration models into a single pipeline - all custom built to work best together.

ElevenLabs

133,211 次观看 • 20 天前

Introducing --agent flag in CodeRabbit CLI 🎉 The new --agent flag turns CodeRabbit into a tool your AI agent can use, providing structured JSON output instead of terminal text. Your agent writes code, CodeRabbit reviews it, reads the JSON, and fixes what's flagged.
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Introducing --agent flag in CodeRabbit CLI 🎉 The new --agent flag turns CodeRabbit into a tool your AI agent can use, providing structured JSON output instead of terminal text. Your agent writes code, CodeRabbit reviews it, reads the JSON, and fixes what's flagged.

CodeRabbit

22,404 次观看 • 2 个月前

BREAKING: ChatGPT GPT-4o was just announce by OpenAI. It improves on vision, audio and text. The ease of use is incredibly enhanced. It makes interaction with the GPT much more natural, especially with voice. GPT-4o reasons across voice, text and vision. GPT-4 wil be available to everyone.
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BREAKING: ChatGPT GPT-4o was just announce by OpenAI. It improves on vision, audio and text. The ease of use is incredibly enhanced. It makes interaction with the GPT much more natural, especially with voice. GPT-4o reasons across voice, text and vision. GPT-4 wil be available to everyone.

Ed Krassenstein

21,605 次观看 • 2 年前

"Free, accurate voice transcription in the browser using Whisper" ⚡️ I'm happy to share a modern voice-to-text app (Say) that uses in-browser AI (Whisper and T5) to offer voice transcription, text summaries and note management. Everything is done locally in a privacy-friendly way. Built with React and Transformers.js by Xenova
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"Free, accurate voice transcription in the browser using Whisper" ⚡️ I'm happy to share a modern voice-to-text app (Say) that uses in-browser AI (Whisper and T5) to offer voice transcription, text summaries and note management. Everything is done locally in a privacy-friendly way. Built with React and Transformers.js by Xenova

Addy Osmani

33,616 次观看 • 1 年前

Hacked today: A realtime voice-to-voice assistant for my Mac that runs in the background and helps me be productive. Stack - RealtimeTTS package (for python) - Groq for fast inference - Mac native text to speech Quite happy with this :)
1:02

Hacked today: A realtime voice-to-voice assistant for my Mac that runs in the background and helps me be productive. Stack - RealtimeTTS package (for python) - Groq for fast inference - Mac native text to speech Quite happy with this :)

Paras Chopra

19,316 次观看 • 1 年前

Introducing Line by Cartesia: the modern voice agent development platform. Line was built to be code-first, because best-in-class products are built in code. ▶️ Watch us build an advanced voice agent with background reasoning in just minutes.
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Introducing Line by Cartesia: the modern voice agent development platform. Line was built to be code-first, because best-in-class products are built in code. ▶️ Watch us build an advanced voice agent with background reasoning in just minutes.

Cartesia

158,584 次观看 • 9 个月前

Some examples: - Text to Speech: Read aloud content or create audiobooks. - Speech to Text: Transcribe audio and video into text. - Voice Designer: Create custom AI voices. - Conversational AI: Build dynamic voice agents and make outbound calls.
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Some examples: - Text to Speech: Read aloud content or create audiobooks. - Speech to Text: Transcribe audio and video into text. - Voice Designer: Create custom AI voices. - Conversational AI: Build dynamic voice agents and make outbound calls.

ElevenLabs

19,318 次观看 • 1 年前

Maven Voice is our enterprise-grade AI voice agent built for the chaotic, noisy and unpredictable situations we encounter everyday. Thank you to OpenAI, Phonic, , and for helping make this possible.
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Maven Voice is our enterprise-grade AI voice agent built for the chaotic, noisy and unpredictable situations we encounter everyday. Thank you to OpenAI, Phonic, , and for helping make this possible.

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Ask Kip: A text activated assistant that runs on #OpenAI #ChatGPT text based version: voice based version:
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Ask Kip: A text activated assistant that runs on #OpenAI #ChatGPT text based version: voice based version:

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We’re finally breaking the silence 🔊 Meet Higgsfield Audio, our all-in-one AI audio generator. Higgsfield is now the ultimate full-cycle AI content production platform. 🧩 Give a voice to any of your text with 21 voice presets 🧩 Change the voice in any of your videos 🧩 Translate and lip-sync any speech in 10 built-in languages An end-to-end AI workflow under one subscription.
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We’re finally breaking the silence 🔊 Meet Higgsfield Audio, our all-in-one AI audio generator. Higgsfield is now the ultimate full-cycle AI content production platform. 🧩 Give a voice to any of your text with 21 voice presets 🧩 Change the voice in any of your videos 🧩 Translate and lip-sync any speech in 10 built-in languages An end-to-end AI workflow under one subscription.

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Voice RAG Agent using OpenAI Agents SDK and Qdrant as the vector database. 100% Opensource Code.
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