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Agent Skill · 研究检索

gemini-live-api-dev(Gemini live API DEV 搜索)

用于辅助 API 设计、接口文档、请求响应结构和服务集成说明。它适合让 Agent 梳理 endpoint、生成 OpenAPI 草稿、检查字段命名、整理错误码或辅助前后端联调。使用时需要确认真实业务语义、鉴权方式、分页和错误处理规则;涉及生成接口文档时,应避免凭空补字段,最好从现有代码、schema 或接口样例中提取事实。

gemini-live-api-dev 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,674 个 Skill 里排第 2,550。

总安装 58,921周安装 2,533GitHub Stars 3,424下载 20,535核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:gemini-live-api-dev(Gemini live API DEV 搜索)
来源仓库:https://github.com/google-gemini/gemini-skills
仓库路径:skills/gemini-live-api-dev
安装命令:
npx skills add https://github.com/google-gemini/gemini-skills --skill gemini-live-api-dev
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/google-gemini/gemini-skills --skill gemini-live-api-dev

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

通过 WebSockets 使用 Gemini 进行实时双向流传输,用于音频、视频和文本对话。

支持音频输入/输出 (16 kHz PCM)、视频帧、文本和自动转录,并具有用于中断处理的语音活动检测 包含原生音频功能:情感对话、主动音频、思维模式;同步和异步工具使用的函数调用;和 Google 搜索接地 提供具有上下文压缩、恢复和临时令牌的会话管理,以实现安全的客户端身份验证 可在 Python 中使用(google-genai )和 JavaScript/TypeScript(@google/genai ) SDK;通过 WebRTC 适配器与 LiveKit、Pipecat、Fishjam 和其他平台集成

来源仓库内路径:skills/gemini-live-api-dev

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/google-gemini/gemini-skills --skill gemini-liv…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

gemini-live-api-dev 怎么安装?

在终端执行 npx skills add https://github.com/google-gemini/gemini-skills --skill gemini-live-api-dev。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

gemini-live-api-dev 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

gemini-live-api-dev 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

gemini-live-api-dev 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

gemini-live-api-dev 用的人多吗?

公开数据是累计安装 58,921 次,近一周安装 2,533 次,下载 20,535 次,GitHub 3,424 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

gemini-live-api-dev 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 来源仓库有 3,424 星,维护活跃度相对可查。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
gemini-live-api-dev

Gemini live API DEV 搜索 · 本页

58,9213,424需要联网未明确有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

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-genai — pip install google-genai
  • JavaScript/TypeScript: @google/genai — npm 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:

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 content — send_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.

平台分布

Codex

36.23%
按下载量换算7,440

Claude

30.72%
按下载量换算6,308

Cursor

18.67%
按下载量换算3,834

Gemini CLI

8.7%
按下载量换算1,787

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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