Gemini Live Api Dev

Gemini Live API Development Skill

Overview

The Live API enables low-latency, real-time voice and video interactions with Gemini over WebSockets. It processes continuous streams of audio, video, or text to deliver immediate, human-like spoken responses and background reasoning.

Key capabilities:

• Bidirectional audio streaming — real-time mic-to-speaker conversations
• Background reasoning (extended thinking) — multi-step background reasoning with spoken conversational fillers
• Live streaming transcription — real-time speech-to-text with interim and finalized streams
• Video streaming — send camera/screen frames alongside audio
• Text input/output — send and receive text within a live session
• Audio transcriptions — get text transcripts of both input and output audio
• Voice Activity Detection (VAD) — automatic server VAD, client-side Hybrid VAD, and manual Push-to-Talk
• Asynchronous function calling — non-blocking tool execution while audio continues streaming
• Full-session client content — inject and update conversation turns mid-stream
• Session management — context compression, session resumption, GoAway signals
• Ephemeral tokens — secure client-side authentication

[!NOTE] The Live API connects directly via WebSockets. For WebRTC support or simplified integration, use a partner integration.

Models

Current Models (Use These)

• gemini-3.8-live — Default option for most low-latency voice agent experiences and real-time dialogue without reasoning delays. Supports interleaved reasoning, asynchronous function calling by default (behavior: NON_BLOCKING), and full-session client content updates.
• gemini-3.8-live-extended-thinking — High-reasoning audio-to-audio model recommended when higher background reasoning is required during live interactions. Processes background reasoning and async tool calls (behavior: NON_BLOCKING required) while streaming continuous spoken conversational fillers; lifecycle managed via interaction_status (IN_PROGRESS vs IDLE).
• gemini-3.5-transcribe-live — Real-time streaming speech-to-text with interim hypotheses, finalized transcripts, smart formatting, and Hybrid VAD.
• gemini-3.5-live-translate-preview — Real-time speech-to-speech streaming translation across 70+ languages.

[!WARNING] Legacy Models (gemini-3.1-flash-live-preview, gemini-2.5-flash-native-audio-*, gemini-live-2.5-flash-preview, gemini-2.0-flash-live-001): Read references/migration.md for breaking protocol changes (behavior: "NON_BLOCKING", thinking_level, interaction_status, send_client_content).

SDKs

• Python: google-genai >= 2.3.0 — pip install -U google-genai
• JavaScript/TypeScript: @google/genai >= 2.3.0 — npm install @google/genai

[!WARNING] Legacy SDKs google-generativeai (Python) and @google/generative-ai (JS) are deprecated. Never use them.

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 streaming user input (audio, video, and text). On Gemini 3.8 models, send_client_content / sendClientContent is supported across the full session lifecycle with explicit roles (user or model) to inject conversation context (turn_complete=true unconditionally interrupts active generation).

[!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

pythonCopy code
from google import genai

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

JavaScript

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

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

Connecting to the Live API

Python

pythonCopy code
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-3.8-live", config=config) as session:
    pass  # Session is active

JavaScript

jsCopy code
const session = await ai.live.connect({
  model: 'gemini-3.8-live',
  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

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

JavaScript

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

Sending Audio

Python

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

JavaScript

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

Sending Video

Python

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

JavaScript

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

Receiving Audio and Text

[!IMPORTANT] A single server event can contain multiple content parts simultaneously (e.g., audio chunks and transcript). Always process all parts in each event to avoid missing content.

Python

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async for response in session.receive():
    content = response.server_content
    if content:
        # Audio — process ALL parts in each event
        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

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// 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 */ }

Background Reasoning (Extended Thinking)

Use gemini-3.8-live-extended-thinking when your voice agent must evaluate complex data, plan multiple steps, or handle long-running tools. The model speaks natural conversational fillers (e.g. "Checking flight options now...") while executing asynchronous tools in the background.

Key requirements:

• Thinking config: Set thinking_config=types.ThinkingConfig(thinking_level="low") ("minimal" | "low" | "medium" | "high").
• Non-blocking tools: All function declarations must set behavior="NON_BLOCKING". Synchronous blocking mode is not supported and returns an error.
• Lifecycle tracking (interaction_status): Do not rely on turn_complete=True alone to detect turn completion. Monitor message.interaction_status (Python) / message.interactionStatus (JS):
  • "IN_PROGRESS": Server is reasoning, speaking conversational fillers, or waiting for async tool responses.
  • "IDLE": Server has completed all background reasoning and tool calls; session is ready for user input.

See references/migration.md and the Thinking in Live API Guide for complete Python and JavaScript implementation examples.

Live Translation (Gemini Live Translate)

The Live API supports real-time, low-latency streaming translation of speech (audio) across 70+ languages. For full details on options and capabilities, see the Live Translate Guide.

Model

• gemini-3.5-live-translate-preview — The recommended translation model for all Live Translate use cases.

Configuration (TranslationConfig)

To enable translation, specify a TranslationConfig object inside your live session setup:

• Python SDK: Configure the connection using translation_config on LiveConnectConfig:

  pythonCopy code
  config = types.LiveConnectConfig(
      response_modalities=[types.Modality.AUDIO],
      translation_config=types.TranslationConfig(
          target_language_code="es",  # Target language code (e.g. es, fr, pl)
          echo_target_language=True,
      ),
      input_audio_transcription=types.AudioTranscriptionConfig(),
      output_audio_transcription=types.AudioTranscriptionConfig(),
  )
  

• Raw WebSockets: Place translationConfig inside generationConfig:

  jsonCopy code
  {
    "setup": {
      "model": "models/gemini-3.5-live-translate-preview",
      "generationConfig": {
        "responseModalities": ["AUDIO"],
        "translationConfig": {
          "targetLanguageCode": "es",
          "echoTargetLanguage": true
        }
      }
    }
  }
  

Live Streaming Transcription (Gemini Live Transcribe)

The Live API supports real-time streaming speech-to-text over WebSockets with low-latency interim hypotheses, finalized transcripts, and Hybrid VAD. For full details, see the Live Transcription Guide and Colab Cookbook.

Model

• gemini-3.5-transcribe-live

Modes

• smart: cleans up filler words, resolves inline self-corrections, and structures formatting.
• verbatim (default): exact word-for-word transcript.

Python

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config = types.LiveConnectConfig(
    response_modalities=["TEXT"],
    input_audio_transcription=types.AudioTranscriptionConfig(),
)

async with client.aio.live.connect(model="gemini-3.5-transcribe-live", config=config) as session:
    # Stream audio
    await session.send_realtime_input(audio=types.Blob(data=chunk, mime_type="audio/pcm;rate=16000"))
    # Hybrid VAD: notify turn end on client-detected silence for zero latency
    await session.send_realtime_input(audio_stream_end=True)

JavaScript

javascriptCopy code
const session = await ai.live.connect({
  model: 'gemini-3.5-transcribe-live',
  config: {
    responseModalities: ['text'],
    inputAudioTranscription: { mode: 'smart' }
  },
  callbacks: {
    onmessage: (msg) => {
      if (msg.serverContent?.interimInputTranscription) {
        console.log('Interim:', msg.serverContent.interimInputTranscription.text);
      }
      if (msg.serverContent?.inputTranscription) {
        console.log('Final:', msg.serverContent.inputTranscription.text);
      }
    }
  }
});

session.sendRealtimeInput({ audio: { data: chunkBase64, mimeType: 'audio/pcm;rate=16000' } });
session.sendRealtimeInput({ audioStreamEnd: true }); // Hybrid VAD

Raw WebSockets

jsonCopy code
{
  "setup": {
    "model": "models/gemini-3.5-transcribe-live",
    "generationConfig": {
      "responseModalities": ["TEXT"],
      "speechConfig": {
        "voiceConfig": {}
      }
    },
    "inputAudioTranscription": {
      "mode": "smart"
    }
  }
}

Limitations

• Response modality — Only TEXT or AUDIO per session, not both. Native audio models output audio (response_modalities=["AUDIO"]); enable output_audio_transcription if you need text transcripts.
• Audio-only session — 15 min without compression
• Audio+video session — 2 min without compression
• Connection lifetime — ~10 min (use session resumption)
• Context window — 128k input tokens / 64k output tokens
• Code execution / URL context — Not supported

Upgrading & Migration

For step-by-step migration checklists and protocol deltas when upgrading from gemini-3.1-flash-live-preview, gemini-2.5-flash-native-audio-*, or gemini-2.0-flash-live-001 to Gemini 3.8 Live or Gemini 3.8 Live Extended Thinking, read references/migration.md.

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 real-time user input (audio, video, text). Use send_client_content with explicit user/model roles to inject context turns mid-stream
6. Send audioStreamEnd / audio_stream_end (Hybrid VAD) when the mic is paused or user finishes speaking
7. Clear audio playback queues on interruption signals (interrupted: true)
8. Process all parts in each server event — events can contain multiple content parts
9. Monitor interaction_status (IN_PROGRESS vs IDLE) when using gemini-3.8-live-extended-thinking rather than relying on turn_complete alone

Documentation Lookup

When MCP is Installed (Preferred)

If the search_docs tool (from the Google MCP server) is available, use it as your only documentation source:

1. Call search_docs with your query
2. Read the returned documentation
3. Trust MCP results as source of truth for API details — they are always up-to-date.

[!IMPORTANT] When MCP tools are present, never fetch URLs manually. MCP provides up-to-date, indexed documentation that is more accurate and token-efficient than URL fetching.

When MCP is NOT Installed (Fallback Only)

If no MCP documentation tools are available, 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
• Thinking in Live API — background reasoning, conversational fillers, interaction_status, non-blocking tools
• Model Card: Gemini 3.8 Live — default low-latency voice agent model & migration guide
• Model Card: Gemini 3.8 Live Extended Thinking — high-reasoning voice model & upgrading guide
• Live Transcription — real-time speech-to-text, interim hypotheses, smart formatting, and Hybrid VAD
• Live Translate — configuration options and capabilities for translation
• Live API Capabilities Guide — voice config, transcription config, 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
• Migration & Upgrading Guide — step-by-step checklists and code examples for Gemini 3.8 Live and Extended Thinking

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.