by katipally
Opensource, on-device voice + vision layer for AI agents. Bring any model or coding agent; the whole speech loop (VAD, STT, TTS, barge-in) runs locally. An open alternative to ElevenLabs Agents, Gemini Live, and OpenAI Realtime.
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# Add to your Claude Code skills
git clone https://github.com/katipally/openliveGuides for using ai agents skills like openlive.
Your AI can think. OpenLive gives it ears, a mouth, and eyes. Bring your own model, or talk to the coding agents you already use, with the whole voice loop running on your own machine. An open alternative to ElevenLabs Agents, Gemini Live, and OpenAI Realtime.
https://github.com/user-attachments/assets/065775b0-0a4a-4adf-8fa7-bcf065e6337f
Wiring an AI into a real conversation is harder than it looks: voice activity detection, knowing when someone actually stopped talking, streaming speech-to-text, the model turn, streaming text-to-speech, and barge-in so you can interrupt. Then camera and screen on top. Hosted platforms rent you that pipeline by the minute and run it on their cloud.
OpenLive is that pipeline, open and local. The listening, the speaking, and the watching all run on-device (WebGPU). You bring the brain, and any brain works:
Whichever brain you pick, OpenLive is the same thing it has always been: the ears, mouth, and eyes around it. Nothing you say leaves the machine. The only thing that goes out is the final transcript (plus camera or screen frames if you turn them on), to whatever brain you picked.
An honest note on architecture: OpenLive is a cascaded pipeline (speech to text to model to speech), not a full-duplex speech-to-speech model like GPT-Live. That's a real trade. A speech-native model can overlap talk and listen in ways a cascade can't, but the cascade is exactly what makes "any brain, all local, no audio fees" possible.
The core, the ears / mouth / eyes:
look tool grabs
a crisp hi-res frame on demand. A text-only model can borrow a separate vision
model's eyes.The integrations that serve it:
~/.claude/projects/… where claude --resume finds it, and the agent's existing
CLI sessions show up in OpenLive's History. Resume from either side.| Home | In a live call |
|---|---|
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| Pre-call setup | Settings — agents |
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| Clone your voice | Mini mode |
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The listening and speaking never leave your computer. The only thing that goes out is the text turn to the brain you picked, the same call you would make from any app. No audio uploads, no per-minute meter, no lock-in.
That also skips the separate speech-to-text, text-to-speech, and real-time-audio fees hosted platforms charge on top. You still pay your normal model and vision API costs, nothing more. With a coding agent as the brain there's nothing extra to pay at all; it runs under the login you already have.
mic ─▶ VAD ─▶ streaming STT ─▶ end-of-turn ─▶ your AI ──────────▶ streaming TTS ─▶ speaker
(Silero) (Whisper) (Smart-Turn) (BYO model, or a (Kokoro / Supertonic /
▲ coding agent over your cloned voice)
camera / screen ────┘ ACP on local stdio)
frames (vision)
Everything outside "your AI" runs locally in the renderer. The turn goes over a warm local WebSocket to a small agent server, which either streams a provider reply or drives your coding agent's ACP adapter as a child process. The app starts speaking sentence by sentence while the reply is still being written.
Just use it: grab the installer from the latest release, open the app, paste a model key (or pick the coding agent you already use — install/sign in from Settings → Agents if needed), and start a call. The voice models download from Hugging Face the first time you talk — roughly 200 MB with Kokoro, more with Supertonic or a bigger Whisper — and are cached after that.
Build it from source:
pnpm install
pnpm desktop:dev # runs the web + agent servers and opens the app window
You can also run it in a browser during development with pnpm dev, then open
localhost:3000. Run the tests with pnpm test.
apps/desktop Electron shell: spawns the local servers, media perms, window,
mini mode, tray + notifications
apps/web Next.js UI + the on-device voice engine (src/lib/live/*) + /api routes
(agents install/auth, history discovery, settings)
services/agent Hono + ws: the /live WebSocket, the ACP agent driver (acp-agent.ts,
supervisor.ts), voice cloning (voice/*), the built-in provider turn loop
packages/shared the agent registry (single source of agent identity), wire protocol,
shared types
packages/harness provider-neutral model adapters, live model listing, cost/effort
packages/db JSON-file store: encrypted keys, settings, conversations
For how the pieces fit together — the ACP driver, the voice loop, resume, and the delegate/worker tool flow — see docs/ARCHITECTURE.md.
OpenLive is open to contributions. Start with CONTRIBUTING.md for how to set up, where things live, and how to send a change. Good first issues are labeled in the tracker.
MIT. Use it, change it, ship it.
openlive is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by katipally. Opensource, on-device voice + vision layer for AI agents. Bring any model or coding agent; the whole speech loop (VAD, STT, TTS, barge-in) runs locally. An open alternative to ElevenLabs Agents, Gemini Live, and OpenAI Realtime. It has 156 GitHub stars.
openlive's catalog security scan is still queued. You can run an instant dependency and prompt-injection check now with the "Scan for vulnerabilities" button above.
Clone the repository with "git clone https://github.com/katipally/openlive" and add it to your Claude Code skills directory (see the Installation section above).
openlive is primarily written in TypeScript. It is open-source under katipally on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh openlive against similar tools.
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