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google-gemini/gemini-live-api-dev

google-gemini

gemini-live-api-dev

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).

global
0installs0uses~3.1k
v1.0Saved May 2, 2026

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.

Key capabilities:

  • Bidirectional audio streaming — real-time mic-to-speaker conversations
  • 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 interruption handling
  • Native audio — thinking (with configurable thinkingLevel)
  • Function calling — synchronous tool use
  • Google Search grounding — ground responses in real-time search results
  • Session management — context compression, session resumption, GoAway signals
  • Ephemeral tokens — secure client-side authentication

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

Models

  • gemini-3.1-flash-live-preview — Optimized for low-latency, real-time dialogue. Native audio output, thinking (via thinkingLevel). 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-3.1-flash-live-preview.

  • gemini-2.5-flash-native-audio-preview-12-2025 — Migrate to gemini-3.1-flash-live-preview.
  • 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-genaipip install google-genai
  • JavaScript/TypeScript: @google/genainpm 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). send_client_content / sendClientContent is only supported for seeding initial context history (requires setting initial_history_in_client_content in history_config). Do not use it to send new user messages during the conversation.

[!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-3.1-flash-live-preview", config=config) as session:
    pass  # Session is active

JavaScript

const session = await ai.live.connect({
  model: 'gemini-3.1-flash-live-preview',
  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 */ }

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)
  • Async function calling — Not yet supported; function calling is synchronous only. The model will not start responding until you've sent the tool response.
  • Proactive audio — Not yet supported in Gemini 3.1 Flash Live. Remove any configuration for this feature.
  • Affective dialogue — Not yet supported in Gemini 3.1 Flash Live. Remove any configuration for this feature.
  • Code execution — Not supported
  • URL context — Not supported

Migrating from Gemini 2.5 Flash Live

When migrating from gemini-2.5-flash-native-audio-preview-12-2025 to gemini-3.1-flash-live-preview:

  1. Model string — Update from gemini-2.5-flash-native-audio-preview-12-2025 to gemini-3.1-flash-live-preview.
  2. Thinking configuration — Use thinkingLevel (minimal, low, medium, high) instead of thinkingBudget. Default is minimal for lowest latency.
  3. Server events — A single event can contain multiple content parts simultaneously (audio + transcript). Process all parts in each event.
  4. Client contentsend_client_content is only for seeding initial context history (set initial_history_in_client_content in history_config). Use send_realtime_input for text during conversation.
  5. Turn coverage — Defaults to TURN_INCLUDES_AUDIO_ACTIVITY_AND_ALL_VIDEO instead of TURN_INCLUDES_ONLY_ACTIVITY. If sending constant video frames, consider sending only during audio activity to reduce costs.
  6. Async function calling — Not yet supported. Function calling is synchronous only.
  7. Proactive audio & affective dialogue — Not yet supported. Remove any configuration for these features.

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 seeding initial context history
  6. Send audioStreamEnd when the mic is paused to flush cached audio
  7. Clear audio playback queues on interruption signals
  8. Process all parts in each server event — events can contain multiple content parts

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

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.

Files1
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Grade adjusted by static analysis guardrails

AI scored this skill as grade A, but static analysis findings capped it to C:

  • Hardcoded credentials or secrets detected in content (max: C)

Overall Score

87/100

Grade

C

Adequate

Safety

92

Quality

88

Clarity

85

Completeness

82

Summary

This skill teaches developers how to build real-time, bidirectional streaming applications using Google's Gemini Live API. It covers WebSocket-based audio/video/text streaming, session management, function calling, voice activity detection, and authentication patterns. The skill provides code examples in Python and JavaScript/TypeScript using the new `google-genai` and `@google/genai` SDKs.

Static Analysis Findings

1 finding

Patterns detected by deterministic static analysis before AI scoring. Hover over any finding code for detailed information and remediation guidance.

Credential Exposure
SEC-021Hardcoded API Key or Token2x in 1 fileMax: C

Hardcoded API key or token pattern

SKILL.mdapi_key="YOUR_API_KEYapiKey: 'YOUR_API_KEY2x

Detected Capabilities

WebSocket streaming setup and connection managementReal-time audio input/output handling (PCM format)Video frame streaming and processingText input and transcription outputVoice activity detection (VAD) configurationSession resumption and context compressionEphemeral token generation for client-side authenticationFunction calling and Google Search groundingMulti-language support (70+ languages)

Trigger Keywords

Phrases that MCP clients use to match this skill to user intent.

real-time voice aigemini live apiwebsocket audio streamingvoice assistant developmentlive video chatbotephemeral authenticationsession management

Risk Signals

INFO

Placeholder API key in code examples: api_key="YOUR_API_KEY"

SKILL.md | Quick Start > Authentication > Python section
INFO

Placeholder API key in code examples: apiKey: 'YOUR_API_KEY'

SKILL.md | Quick Start > Authentication > JavaScript section

Referenced Domains

External domains referenced in skill content, detected by static analysis.

ai.google.devdocs.fishjam.iodocs.livekit.iodocs.pipecat.aifirebase.google.comvisionagents.aivoximplant.comwww.apache.org

Use Cases

  • Build real-time voice assistant applications with Gemini
  • Create live video streaming chatbots with audio/text interaction
  • Implement low-latency audio conferencing with AI participation
  • Develop browser-based AI voice interfaces using ephemeral tokens
  • Integrate Gemini Live API into existing LiveKit, Pipecat, or Fishjam applications

Quality Notes

  • ✓ Comprehensive coverage of Live API capabilities with clear sections for authentication, streaming, and session management
  • ✓ Code examples provided in both Python and JavaScript/TypeScript with consistent syntax
  • ✓ Clear warnings about deprecated models and migration paths from Gemini 2.5 to 3.1
  • ✓ Important callouts (via blockquotes) highlight critical usage patterns like processing all parts in each server event
  • ✓ Audio format specifications clearly documented (16-bit PCM, 16kHz input, 24kHz output)
  • ✓ Comprehensive limitations section documents what is NOT supported (async function calling, code execution, URL context)
  • ✓ Best practices section provides actionable guidance (use headphones, enable compression, implement session resumption)
  • ✓ Documentation lookup strategy explains MCP preference and fallback to official docs
  • ✓ Partner integrations clearly referenced with links (LiveKit, Pipecat, Fishjam, Vision Agents, Voximplant, Firebase)
  • ✓ Placeholder API keys use clear 'YOUR_API_KEY' format, making it obvious these are templates
  • ✓ Clear distinction between send_realtime_input (for all real-time input) and send_client_content (seeding only) prevents misuse
  • - Could benefit from more error handling guidance (what to do if connection drops, WebSocket errors)
  • - No explicit rate limiting or quota guidance for API calls
  • - Could include example of ephemeral token generation (mentioned but not shown)
Model: claude-haiku-4-5-20251001Analyzed: May 2, 2026

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