Gemini Live API Development Skill

[!NOTE] The Live API currently only supports WebSockets. For WebRTC support or simplified integration, use a partner integration.

Models

• gemini-2.5-flash-native-audio-preview-12-2025 — Native audio output, affective dialog, proactive audio, thinking. 128k context window. This is the recommended model for all Live API use cases.

[!WARNING] The following Live API models are deprecated and will be shut down. Migrate to gemini-2.5-flash-native-audio-preview-12-2025.

• gemini-live-2.5-flash-preview — Released June 17, 2025. Shutdown: December 9, 2025.
• gemini-2.0-flash-live-001 — Released April 9, 2025. Shutdown: December 9, 2025.

SDKs

• Python: google-genai — pip install google-genai
• JavaScript/TypeScript: @google/genai — npm install @google/genai

[!WARNING] Legacy SDKs google-generativeai (Python) and @google/generative-ai (JS) are deprecated. Use the new SDKs above.

Partner Integrations

To streamline real-time audio/video app development, use a third-party integration supporting 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.
• Firebase AI SDK — Get started with the Gemini Live API using Firebase AI Logic.

Audio Formats

• Input: Raw PCM, little-endian, 16-bit, mono. 16kHz native (will resample others). MIME type: audio/pcm;rate=16000
• Output: Raw PCM, little-endian, 16-bit, mono. 24kHz sample rate.

[!IMPORTANT] Use send_realtime_input / sendRealtimeInput for all real-time user input (audio, video, and text). Use send_client_content / sendClientContent only for incremental conversation history updates (appending prior turns to context), not for sending new user messages.

[!WARNING] Do not use media in sendRealtimeInput. Use the specific keys: audio for audio data, video for images/video frames, and text for text input.

Quick Start

Authentication

Python

from google import genai

client = genai.Client(api_key="YOUR_API_KEY")

JavaScript

import { GoogleGenAI } from '@google/genai';

const ai = new GoogleGenAI({ apiKey: 'YOUR_API_KEY' });

Connecting to the Live API

Python

from google.genai import types

config = types.LiveConnectConfig(
    response_modalities=[types.Modality.AUDIO],
    system_instruction=types.Content(
        parts=[types.Part(text="You are a helpful assistant.")]
    )
)

async with client.aio.live.connect(model="gemini-2.5-flash-native-audio-preview-12-2025", config=config) as session:
    pass  # Session is now active

JavaScript

const session = await ai.live.connect({
  model: 'gemini-2.5-flash-native-audio-preview-12-2025',
  config: {
    responseModalities: ['audio'],
    systemInstruction: { parts: [{ text: 'You are a helpful assistant.' }] }
  },
  callbacks: {
    onopen: () => console.log('Connected'),
    onmessage: (response) => console.log('Message:', response),
    onerror: (error) => console.error('Error:', error),
    onclose: () => console.log('Closed')
  }
});

Sending Text

Python

await session.send_realtime_input(text="Hello, how are you?")

JavaScript

session.sendRealtimeInput({ text: 'Hello, how are you?' });

Sending Audio

Python

await session.send_realtime_input(
    audio=types.Blob(data=chunk, mime_type="audio/pcm;rate=16000")
)

JavaScript

session.sendRealtimeInput({
  audio: { data: chunk.toString('base64'), mimeType: 'audio/pcm;rate=16000' }
});

Sending Video

Python

# frame: raw JPEG-encoded bytes
await session.send_realtime_input(
    video=types.Blob(data=frame, mime_type="image/jpeg")
)

JavaScript

session.sendRealtimeInput({
  video: { data: frame.toString('base64'), mimeType: 'image/jpeg' }
});

Receiving Audio and Text

Python

async for response in session.receive():
    content = response.server_content
    if content:
        # Audio
        if content.model_turn:
            for part in content.model_turn.parts:
                if part.inline_data:
                    audio_data = part.inline_data.data
        # Transcription
        if content.input_transcription:
            print(f"User: {content.input_transcription.text}")
        if content.output_transcription:
            print(f"Gemini: {content.output_transcription.text}")
        # Interruption
        if content.interrupted is True:
            pass  # Stop playback, clear audio queue

JavaScript

// Inside the onmessage callback
const content = response.serverContent;
if (content?.modelTurn?.parts) {
  for (const part of content.modelTurn.parts) {
    if (part.inlineData) {
      const audioData = part.inlineData.data; // Base64 encoded
    }
  }
}
if (content?.inputTranscription) console.log('User:', content.inputTranscription.text);
if (content?.outputTranscription) console.log('Gemini:', content.outputTranscription.text);
if (content?.interrupted) { /* Stop playback, clear audio queue */ }

Limitations

• Response modality — Only TEXT or AUDIO per session, not both
• Audio-only session — 15 min without compression
• Audio+video session — 2 min without compression
• Connection lifetime — ~10 min (use session resumption)
• Context window — 128k tokens (native audio) / 32k tokens (standard)
• Code execution — Not supported
• URL context — Not supported

Best Practices

1. Use headphones when testing mic audio to prevent echo/self-interruption
2. Enable context window compression for sessions longer than 15 minutes
3. Implement session resumption to handle connection resets gracefully
4. Use ephemeral tokens for client-side deployments — never expose API keys in browsers
5. Use send_realtime_input for all real-time user input (audio, video, text). Reserve send_client_content only for injecting conversation history
6. Send audioStreamEnd when the mic is paused to flush cached audio
7. Clear audio playback queues on interruption signals

How to use the Gemini API

For detailed API documentation, fetch from the official docs index:

llms.txt URL: https://ai.google.dev/gemini-api/docs/llms.txt

This index contains links to all documentation pages in .md.txt format. Use web fetch tools to:

1. Fetch llms.txt to discover available documentation pages
2. Fetch specific pages (e.g., https://ai.google.dev/gemini-api/docs/live-session.md.txt)

Key Documentation Pages

[!IMPORTANT] Those are not all the documentation pages. Use the llms.txt index to discover available documentation pages

• Live API Overview — getting started, raw WebSocket usage
• Live API Capabilities Guide — voice config, transcription config, native audio (affective dialog, proactive audio, thinking), VAD configuration, media resolution
• Live API Tool Use — function calling (sync and async), Google Search grounding
• Session Management — context window compression, session resumption, GoAway signals
• Ephemeral Tokens — secure client-side authentication for browser/mobile
• WebSockets API Reference — raw WebSocket protocol details

Supported Languages

The Live API supports 70 languages including: English, Spanish, French, German, Italian, Portuguese, Chinese, Japanese, Korean, Hindi, Arabic, Russian, and many more. Native audio models automatically detect and switch languages.3e:["$","$L45",null,{"content":"$46","frontMatter":{"name":"gemini-live-api-dev","description":"Use this skill when building real-time, bidirectional streaming applications with the Gemini Live API. Covers WebSocket-based audio/video/text streaming, voice activity detection (VAD), native audio features, function calling, session management, ephemeral tokens for client-side auth, and all Live API configuration options. SDKs covered - google-genai (Python), @google/genai (JavaScript/TypeScript)."}}]