Li

Live conversations with ChatGPT using WebRTC

Hacker News

Live conversations with ChatGPT using WebRTC

HN, meet KITT! https://livekit.io/kitt Like many folks here, the LiveKit team is enamored with ChatGPT. Given that we spend most of our time working with real-time media, we thought we'd try connecting GPT to a WebRTC video call. KITT can do some neat things: - Answer questions like Siri, Alexa, or Google Assistant - Summarize what was discussed in a meeting - Speak multiple languages and even act like a third-party translator - Act as a DM in a D&D campaign At first, we weren’t sure if we could get the latency low enough to have a human-like conversation, but after making a handful of tweaks, things feel pretty close to speaking with a person. The key optimization we made was to stream all the things: - We convert streaming audio from participants to text in 20ms frames - We pre-prompt GPT to be concise in its responses and generate short sentences - Each sentence is converted to speech in real-time and streamed out to all participants We also use GPT-3 Turbo instead of GPT-4 which shaves off response time, as well. To make it easy for anyone to plug in their own AI, we built KITT as a server-side Go program that uses [Pion]( https://github.com/pion/webrtc ) to publish audio and video streams like any other WebRTC participant. That means it’s fairly straightforward to plug in your own STT, LLM, custom voice or avatar. For more details on how we built this: https://blog.livekit.io/meet-kitt Would love to hear your thoughts and feedback in the comments!

Share card

Actual performance

6points
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Strong signals: google, chatgpt, using · Missing: mac, agents, macos
93%93% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
68%68% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
57%57% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive
57%57% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: video, google · Missing: mobile apps, ios, personal
48%48% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
20%20% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat, audio · Missing: web3, crypto, cryptocurrency
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

Similar products

YA
YAML to Django Using ChatGPT49%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

YAML to Django Using ChatGPT

Hacker News4
I
I made a game about awkward conversations using Jev38%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

I made a game about awkward conversations using Jev

Hacker News3
An
An extension to navigate conversations with GPTs, built using ChatGPT26%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

An extension to navigate conversations with GPTs, built using ChatGPT

Hacker News1
Us
Using data to figure out where to live58%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Using data to figure out where to live

Hacker News3
I
I built WorkoutTools using ShipFa.st and ChatGPT40%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

I built WorkoutTools using ShipFa.st and ChatGPT

Hacker News2
Op
OpenArena Live – OpenArena in the Browser Using WebRTC59%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

OpenArena Live – OpenArena in the Browser Using WebRTC

Hacker News2
Op
OpenArena Live – OpenArena in the Browser Using WebRTC59%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

OpenArena Live – OpenArena in the Browser Using WebRTC

Hacker News7
Co
ConvoLounge – Live chats and conversations43%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

ConvoLounge – Live chats and conversations

Hacker News1
Co
Conversations with my OCD40%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Conversations with my OCD

Hacker News8
Ha
Hashtag conversations40%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Hashtag conversations

Hacker News1