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Gemini Live API overview

Gemini Live API overview

AI cloud Google
Google’s Gemini Live API is now generally available, providing low-latency, bidirectional streaming for voice and vision agents.
What: The Live API uses stateful WebSockets to handle real-time input/output (audio/video/text). Google recommends using ephemeral tokens for client-to-server connections to mitigate security risks in production environments.
Why it matters: Providing direct client-to-server access for real-time streaming bypasses backend bottlenecks, though it forces developers to handle security and token management on the frontend.
Takeaway: If building a real-time agent, implement ephemeral tokens rather than using static API keys on your frontend to protect your project.
Deep dive
  • Modalities: Supports raw 16-bit PCM audio (16kHz in, 24kHz out), JPEG images, and text.
  • Latency: Designed for conversational speed using persistent WebSocket connections.
  • Implementation: Supports server-to-server proxies or direct client-to-server connections for better performance.
  • Integration: Compatible with frameworks like LiveKit, Pipecat, and Agora.
Decoder
  • WebSocket (WSS): A communication protocol providing full-duplex, real-time communication channels over a single TCP connection.
  • Barge-in: A feature allowing a user to interrupt a speaking AI mid-response, causing the model to stop and listen.
Original article

Gemini Live API overview

The Live API enables low-latency, real-time voice and vision interactions with Gemini. It processes continuous streams of audio, images, and text to deliver immediate, human-like spoken responses, creating a natural conversational experience for your users.

Use cases

Live API can be used to build real-time voice agents for a variety of industries, including:

  • E-commerce and retail: Shopping assistants that offer personalized recommendations and support agents that resolve customer issues.
  • Gaming: Interactive non-player characters (NPCs), in-game help assistants, and real-time translation of in-game content.
  • Next-gen interfaces: Voice- and video-enabled experiences in robotics, smart glasses, and vehicles.
  • Healthcare: Health companions for patient support and education.
  • Financial services: AI advisors for wealth management and investment guidance.
  • Education: AI mentors and learner companions that provide personalized instruction and feedback.
  • Translation and localization: Real-time, low-latency translation of spoken conversations, enabling seamless multilingual communication.

Key features

Live API offers a comprehensive set of features for building robust voice agents:

  • Multilingual support: Converse in 70 supported languages.
  • Barge-in: Users can interrupt the model at any time for responsive interactions.
  • Tool use: Integrates tools like function calling and Google Search for dynamic interactions.
  • Audio transcriptions: Provides text transcripts of both user input and model output.
  • Proactive audio: Lets you control when the model responds and in what contexts.
  • Affective dialog: Adapts response style and tone to match the user's input expression.
  • Live Translation: Real-time voice-to-voice translation in 70+ languages.

Technical specifications

The following table outlines the technical specifications for the Live API:

Category Details
Input modalities Audio (raw 16-bit PCM audio, 16kHz, little-endian), images (JPEG <= 1FPS), text
Output modalities Audio (raw 16-bit PCM audio, 24kHz, little-endian)
Protocol Stateful WebSocket connection (WSS)

Choose an implementation approach

When integrating with Live API, you'll need to choose one of the following implementation approaches:

  • Server-to-server: Your backend connects to the Live API using WebSockets. Typically, your client sends stream data (audio, video, text) to your server, which then forwards it to the Live API.
  • Client-to-server: Your frontend code connects directly to the Live API using WebSockets to stream data, bypassing your backend.

Get started

Select the guide that matches your development environment:

GenAI SDK tutorial

Connect to the Gemini Live API using the GenAI SDK to build a real-time multimodal application with a Python backend.

WebSocket tutorial

Connect to the Gemini Live API using WebSockets to build a real-time multimodal application with a JavaScript frontend and ephemeral tokens.

ADK tutorial

Create an agent and use the Agent Development Kit (ADK) Streaming to enable voice and video communication.

Partner integrations

To streamline the development of real-time audio and video apps, you can use a third-party integration that supports the Gemini Live API over WebRTC or WebSockets.

  • LiveKit: Use the Gemini Live API with LiveKit Agents.
  • Pipecat by Daily: Create a real-time AI chatbot using Gemini Live and Pipecat.
  • Fishjam by Software Mansion: Create live video and audio streaming applications with Fishjam.
  • Vision Agents by Stream: Build real-time voice and video AI applications with Vision Agents.
  • Voximplant: Connect inbound and outbound calls to Live API with Voximplant.
  • Agora: Build real-time conversational AI applications with Agora.
  • Firebase AI SDK: Get started with the Gemini Live API using Firebase AI Logic.
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