立体物をthree.jsで作成し、あらゆる角度から確認できるビューアーに表示します。OBJ + MTLやGLBで保存し、他の3D制作ソフトへ持ち込めます。
- 立体物を作って全方向から確認したいとき
- Blenderで編集するモデルの作成
- シルエットや素材の見え方の確認
Gemini Live APIを使うリアルタイム音声・映像アプリの実装や旧モデルからの移行を支援し、文字起こしや翻訳、セッション管理も扱います。
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).
実行スコア 未検証
インストール方法を見るGemini Live APIを使い、音声・映像・テキストをWebSocketで双方向にやり取りするリアルタイムアプリの実装を支援します。音声応答やストリーミング文字起こし、70以上の言語へのライブ翻訳、カメラ映像の送信を扱います。発話の開始・終了を検出する音声活動検出、応答中の非同期ツール実行、セッションの再開やコンテキスト管理についても説明します。旧LiveモデルからGemini 3.8 Live系へ移行する際の変更点も対象です。Pythonのgoogle-genaiとJavaScript/TypeScriptの@google/genaiを扱います。
音声で会話するエージェント、ライブ文字起こしや翻訳、音声とカメラ映像を組み合わせたアプリを開発するときに向いています。既存のLive API連携を新しいモデルに更新する場合にも使えます。
APIキーと、Pythonではgoogle-genai、JavaScript/TypeScriptでは@google/genaiが必要です。接続はWebSocketを使います。旧SDKのgoogle-generativeaiと@google/generative-aiは非推奨です。
この紹介文は、公開されている SKILL.md をもとに AI(OpenAI Codex)が作成しました。正確な仕様は下の原文を確認してください。
SKILL.md の記述から、注意が要る操作と導入の前提を AI が確認しました。点数は実際に動かした結果(実行検証)だけで付けています。
点数には入れていません。 2026年10月30日 時点で AI(OpenAI Codex)が判定しました。目安なので、入れる前に原文も確認してください。
インストールする前に、エージェントに与えられる指示の中身を確認できます。
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:
[!NOTE]
The Live API connects directly via WebSockets. For WebRTC support or simplified integration, use a partner integration.
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): Readreferences/migration.mdfor breaking protocol changes (behavior: "NON_BLOCKING",thinking_level,interaction_status,send_client_content).
google-genai >= 2.3.0 — pip install -U google-genai@google/genai >= 2.3.0 — npm install @google/genai[!WARNING]
Legacy SDKsgoogle-generativeai(Python) and@google/generative-ai(JS) are deprecated. Never use them.
To streamline real-time audio/video app development, use a third-party integration supporting the Gemini Live API over WebRTC or WebSockets:
audio/pcm;rate=16000[!IMPORTANT]
Usesend_realtime_input/sendRealtimeInputfor all real-time streaming user input (audio, video, and text). On Gemini 3.8 models,send_client_content/sendClientContentis supported across the full session lifecycle with explicit roles (userormodel) to inject conversation context (turn_complete=trueunconditionally interrupts active generation).
[!WARNING]
Do not usemediainsendRealtimeInput. Use the specific keys:audiofor audio data,videofor images/video frames, andtextfor text input.
from google import genai
client = genai.Client(api_key="YOUR_API_KEY")
import { GoogleGenAI } from '@google/genai';
const ai = new GoogleGenAI({ apiKey: 'YOUR_API_KEY' });
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
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')
}
});
await session.send_realtime_input(text="Hello, how are you?")
session.sendRealtimeInput({ text: 'Hello, how are you?' });
await session.send_realtime_input(
audio=types.Blob(data=chunk, mime_type="audio/pcm;rate=16000")
)
session.sendRealtimeInput({
audio: { data: chunk.toString('base64'), mimeType: 'audio/pcm;rate=16000' }
});
# frame: raw JPEG-encoded bytes
await session.send_realtime_input(
video=types.Blob(data=frame, mime_type="image/jpeg")
)
session.sendRealtimeInput({
video: { data: frame.toString('base64'), mimeType: 'image/jpeg' }
});
[!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.
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
// 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 */ }
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=types.ThinkingConfig(thinking_level="low") ("minimal" | "low" | "medium" | "high").behavior="NON_BLOCKING". Synchronous blocking mode is not supported and returns an error.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.
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.
gemini-3.5-live-translate-preview — The recommended translation model for all Live Translate use cases.TranslationConfig)To enable translation, specify a TranslationConfig object inside your live session setup:
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(),
)
translationConfig inside generationConfig:
{
"setup": {
"model": "models/gemini-3.5-live-translate-preview",
"generationConfig": {
"responseModalities": ["AUDIO"],
"translationConfig": {
"targetLanguageCode": "es",
"echoTargetLanguage": true
}
}
}
}
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.
gemini-3.5-transcribe-livesmart: cleans up filler words, resolves inline self-corrections, and structures formatting.verbatim (default): exact word-for-word transcript.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)
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
{
"setup": {
"model": "models/gemini-3.5-transcribe-live",
"generationConfig": {
"responseModalities": ["TEXT"],
"speechConfig": {
"voiceConfig": {}
}
},
"inputAudioTranscription": {
"mode": "smart"
}
}
}
TEXT or AUDIO per session, not both. Native audio models output audio (response_modalities=["AUDIO"]); enable output_audio_transcription if you need text transcripts.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.
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-streamaudioStreamEnd / audio_stream_end (Hybrid VAD) when the mic is paused or user finishes speakinginterrupted: true)interaction_status (IN_PROGRESS vs IDLE) when using gemini-3.8-live-extended-thinking rather than relying on turn_complete aloneIf the gemini_search_docs tool (or search_docs) is available, use it as your only documentation source:
gemini_search_docs with your query (or use gemini_get_doc to retrieve a specific doc path)[!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.
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:
llms.txt to discover available documentation pageshttps://ai.google.dev/gemini-api/docs/live-session.md.txt)[!IMPORTANT]
Those are not all the documentation pages. Use thellms.txtindex to discover available documentation pages
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.
まだレビューはありません。使ってみた感想をお寄せください。
ログインなしで書き込めます。使ってみた感想、質問、動かなかった環境などを気軽にどうぞ。
まだコメントはありません。最初のコメントを書いてみませんか。
立体物をthree.jsで作成し、あらゆる角度から確認できるビューアーに表示します。OBJ + MTLやGLBで保存し、他の3D制作ソフトへ持ち込めます。
Chrome DevTools MCPでWebページのアクセシビリティを監査し、見出し構造、ラベル、キーボード操作、フォーカス、タップ領域、色のコントラストに関する問題を調べます。
個人用のタスク一覧に、やることや期限、返答待ち、作業が止まる理由を記録します。進捗や依存関係を更新し、重複や完了済みの項目も整理するスキルです。
作業の目標と完了条件を整理し、必要に応じて複数のエージェントへ分担します。進捗報告、成果の検証、PRのマージまで、プロジェクトとして進行を管理します。
Antigravityのカスタマイズの種類や読み込み順、検出場所を説明し、スキル、ルール、プラグイン、フック、MCPサーバーの作成方法を案内します。
再生・一時停止や時間位置の指定ができるアニメーションをHTMLページとして制作します。場面の長さや速度を調整し、横長・縦長の動画書き出しに備えます。