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Gemini Live API Dev

Google (Gemini)OfficialPublished by Google (Gemini)

  • Skill
  • Tool integration
  • Data and AI
  • Apache-2.0
  • Low risk

From the author

Use this skill when building real-time, bidirectional streaming applications with the Gemini Live API, or migrating legacy Live models (2.0/2.5/3.1) to Gemini 3.8 Live. Covers WebSocket-based audio/video/text streaming, voice activity detection (VAD), background reasoning (extended thinking), asynchronous function calling, session management, ephemeral tokens, live transcription, and live translation. SDKs covered - google-genai (Python), @google/genai (JavaScript/TypeScript).
— the description by Google (Gemini)

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

The Gemini Live API development skill provides the necessary framework for integrating low-latency, real-time voice and video interactions into applications. It covers WebSocket-based communication for audio, video, and text, supporting advanced features like background reasoning, voice activity detection (VAD), and asynchronous function calling. The skill includes guidance for using the latest Gemini 3.8 models, managing session lifecycles, and implementing secure authentication via ephemeral tokens.

What it does

  • Enables bidirectional audio and video streaming over WebSockets.
  • Supports background reasoning with conversational fillers for complex tasks.
  • Provides real-time speech-to-text transcription and speech-to-speech translation.
  • Facilitates asynchronous function calling for non-blocking tool execution.
  • Manages session state, including context compression and resumption.
  • Offers secure client-side authentication using ephemeral tokens.

When to use it

  • When building low-latency, real-time voice or video AI agents.
  • When migrating legacy Gemini Live models to the 3.8 series.
  • When implementing real-time streaming transcription or translation services.
  • When requiring background reasoning capabilities during live voice interactions.

Advantages

  • Low-latency performance optimized for human-like conversational flow.
  • Supports complex reasoning tasks without interrupting the user experience.
  • Flexible integration with major SDKs for Python and JavaScript/TypeScript.
  • Robust session management features for long-running interactions.

Usage examples

“How do I connect to the Gemini 3.8 Live model using Python?”
The skill provides a code snippet using the google-genai SDK to establish an asynchronous connection with LiveConnectConfig.
“How can I enable background reasoning in my voice agent?”
The skill instructs to use the gemini-3.8-live-extended-thinking model and configure non-blocking tools.
“What is the correct way to send audio data to the API?”
The skill specifies using the send_realtime_input method with raw PCM 16kHz audio data.

Install

  1. Download the skill as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/google-gemini/gemini-live-api-dev/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip gemini-live-api-dev.zip -d .agents/skills

Documentation by Google (Gemini)

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:

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

[!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
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
// 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:

    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:

    {
      "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
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
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
{
  "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://aistudio.google.com/llms.txt

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

  1. Fetch llms.txt to discover available documentation pages

  2. Fetch specific pages (e.g., https://aistudio.google.com/docs/live-api/session-management.md)

Key Documentation Pages

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

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.

Files

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Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs an MCP server, Needs an API key, Needs Python, Needs Node.js

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Attribution and licence

Published by
Google (Gemini)
Publisher
Google (Gemini) (Official)
Source
google-gemini/gemini-skills · skills/gemini-live-api-dev · commit 7cfc690
Licence
Apache License 2.0 (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
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