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gemini-live-api-dev

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.

Install / Use

npx skills add google-gemini/gemini-skills --skill gemini-live-api-dev

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

95/100

Category

Other

Supported Platforms

Gemini CLI

Our assessment of gemini-live-api-dev

gemini-live-api-dev scores 95/100 on our quality scale, 6th of 115 Other skills we index (top 6%).

Its SKILL.md is 18 KB long, well organised into 45 sections with 15 code examples: a thorough specification that gives an agent plenty to work with.

With 4,205 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
30/30
Structure
20/20
Description
15/15
Adoption
15/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 5 days ago, so gemini-live-api-dev is actively maintained.
  • It is released under the Apache-2.0 license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

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All 4 of these similar skills score higher than gemini-live-api-dev; compare them before choosing.

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Frequently asked questions

How do I install gemini-live-api-dev?
Run npx skills add google-gemini/gemini-skills --skill gemini-live-api-dev. The install tabs above show the steps for each supported agent.
Which AI agents does gemini-live-api-dev work with?
It is written for Gemini CLI, as a SKILL.md file. Other agents that read the same format can often use it too.
Is gemini-live-api-dev safe to use?
It is Apache-2.0-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is gemini-live-api-dev still maintained?
The repository was last updated 5 days ago, so gemini-live-api-dev is actively maintained.

name: gemini-live-api-dev description: 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).

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

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-corr

Truncated for display — read the full file on GitHub.

Related Skills

View on GitHub
GitHub Stars4.2k
CategoryOther
Updated5d ago
Forks443

Languages

Python

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions