据 AlphaMoat 统计,截至 2026-09,Voice Assistant 累计下载 3,020 次、获 4 个星标,在全部 5,078 个 AI 技能中排名第 3,718 位,在「AI 智能体」分类(969 个)中排名第 751 位。
| 平台 | 累计安装 | 累计下载 | 星标 | 评论 |
|---|---|---|---|---|
| ClawHub ↗ | 90 | 2,901 | 4 | - |
| SkillHub ↗ | 160 | 3,020 | 4 | — |
各平台的计数口径不同,统计时间不一致。
浏览器语音界面连接 OpenClaw 网关,可配置语音识别和合成。音频、转写和生成文本可能发送至第三方并写入日志;使用可信网络、限制网关权限,避免传输未获批准的敏感内容。 需要Python/uv、已配置运行的OpenClaw网关、麦克风权限及所选STT/TTS分支的Deepgram或ElevenLabs凭据。服务无认证,绑定localhost,对外暴露前加认证和Origin检查;审查日志,不发送未获准敏感语音。
资料发布于 2026-10-27
以下是根据技能文档生成的示例,不代表实际运行结果。
2026-09 起统计方法调整:同名技能按作者分别统计,并覆盖全部技能。图中虚线为调整前的月份,与之后的数据不直接比较,也不计算跨越调整的增长。
| 月份 | 累计下载 | 环比 | 星标 |
|---|---|---|---|
| 2026-09 | 3,020 | — | 4 |
| 2026-08 | 2,797 | +4.5% | 4 |
| 2026-07 | 2,677 | — | 4 |
| 2026-05 | 2,280 | — | 4 |
| 2026-03 | 1,815 | — | 4 |
以下是作者发布的原始文件,按纯文本显示,本站未做修改或审核;其中的链接不可点击,命令请核实后再运行。抓取于 2026-10-23。
---
name: voice-assistant
description: Real-time voice assistant for OpenClaw. Streams mic audio through configurable STT (Deepgram or ElevenLabs) into your OpenClaw agent, then speaks the response via configurable TTS (Deepgram Aura or ElevenLabs). Sub-2s time-to-first-audio with full streaming at every stage.
metadata:
openclaw:
emoji: "🎙️"
requires:
bins: ["uv"]
env: []
primaryEnv: "VOICE_STT_PROVIDER" install:
- id: "uv"
kind: "brew"
formula: "uv"
bins: ["uv"]
label: "Install uv (brew)"
---
# Voice Assistant
Real-time voice interface for your OpenClaw agent. Talk to your agent and hear it respond — with configurable STT and TTS providers, full streaming at every stage, and sub-2 second time-to-first-audio.
## Architecture
```
Browser Mic → WebSocket → STT (Deepgram / ElevenLabs) → Text
→ OpenClaw Gateway (/v1/chat/completions, streaming) → Response Text
→ TTS (Deepgram Aura / ElevenLabs) → Audio chunks → Browser Speaker
```
The voice interface connects to your running OpenClaw gateway's OpenAI-compatible endpoint. It's the same agent with all its context, tools, and memory — just with a voice.
## Quick Start
```bash
cd {baseDir}
cp .env.example .env
# Fill in your API keys and gateway URL
uv run scripts/server.py
# Open http://localhost:7860 and click the mic
```
## Supported Providers
### STT (Speech-to-Text)
| Provider | Model | Latency | Notes |
|-----------|------------------|----------|------------------------------|
| Deepgram | nova-2 (streaming) | ~200-300ms | WebSocket streaming, best accuracy/speed |
| ElevenLabs | Scribe v1 | ~300-500ms | REST-based, good multilingual |
### TTS (Text-to-Speech)
| Provider | Model | Latency | Notes |
|------------|--------------|----------|--------------------------------|
| Deepgram | aura-2 | ~200ms | WebSocket streaming, low cost |
| ElevenLabs | Turbo v2.5 | ~300ms | Best voice quality, streaming |
## Configuration
All configuration is via environment variables in `.env`:
```bash
# === Required ===
OPENCLAW_GATEWAY_URL=http://localhost:4141/v1 # Your OpenClaw gateway
OPENCLAW_MODEL=claude-sonnet-4-5-20250929 # Model your gateway routes to
# === STT Provider (pick one) ===
VOICE_STT_PROVIDER=deepgram # "deepgram" or "elevenlabs"
DEEPGRAM_API_KEY=your-key-here # Required if STT=deepgram
ELEVENLABS_API_KEY=your-key-here # Required if STT=elevenlabs
# === TTS Provider (pick one) ===
VOICE_TTS_PROVIDER=elevenlabs # "deepgram" or "elevenlabs"
# Uses the same API keys as above
# === Optional Tuning ===
VOICE_TTS_VOICE=rachel # ElevenLabs voice name/ID
VOICE_TTS_VOICE_DG=aura-2-theia-en # Deepgram Aura voice
VOICE_VAD_SILENCE_MS=400 # Silence before end-of-turn (ms)
VOICE_SAMPLE_RATE=16000 # Audio sample rate
VOICE_SERVER_PORT=7860 # Server port
VOICE_SYSTEM_PROMPT="" # Optional system prompt override
```
## Provider Combinations
| Setup | Best For |
|------------------------------------|---------------------------------|
| Deepgram STT + ElevenLabs TTS | Best quality voice output |
| Deepgram STT + Deepgram TTS | Lowest latency, single vendor |
| ElevenLabs STT + ElevenLabs TTS | Best multilingual support |
## How It Works
1. **Browser captures mic audio** via Web Audio API and streams raw PCM over a WebSocket
2. **Server receives audio** and pipes it to the configured STT provider's streaming endpoint
3. **STT returns partial transcripts** in real-time; on end-of-utterance the full text is sent to the OpenClaw gateway
4. **OpenClaw gateway streams** the LLM response token-by-token via SSE (Server-Sent Events)
5. **Tokens are accumulated** into sentence-sized chunks and streamed to the TTS provider
6. **TTS returns audio chunks** that are immediately forwarded to the browser over the same WebSocket
7. **Browser plays audio** using the Web Audio API with a jitter buffer for smooth playback
## Interruption Handling (Barge-In)
When the user starts speaking while the agent is still talking:
- Current TTS audio is immediately cancelled
- The agent stops its current response
- New STT session begins capturing the user's interruption
## Usage Examples
```
User: "Hey, set up my voice assistant"
→ OpenClaw runs: cd {baseDir} && cp .env.example .env
→ Opens .env for the user to fill in API keys
→ Runs: uv run scripts/server.py
User: "Start a voice chat"
→ Opens http://localhost:7860 in the browser
User: "Switch TTS to Deepgram"
→ Updates VOICE_TTS_PROVIDER=deepgram in .env
→ Restarts the server
```
## Troubleshooting
- **No audio output?** Check that your TTS API key is valid and the provider is set correctly
- **High latency?** Use Deepgram for both STT and TTS; ensure your gateway is on the same network
- **Cuts off speech?** Increase `VOICE_VAD_SILENCE_MS` to 600-800ms
- **Echo/feedback?** Use headphones, or enable the built-in echo cancellation in the browser UI
## Latency Budget
| Stage | Target | Actual (typical) |
|-------------------------|-----------|------------------|
| Audio capture + VAD | <200ms | ~100-150ms |
| STT transcription | <400ms | ~200-400ms |
| OpenClaw LLM first token| <1500ms | ~500-1500ms |
| TTS first audio chunk | <400ms | ~200-400ms |
| **Total first audio** | **<2.5s** | **~1.0-2.5s** |
把开发过程中的经验、错误与纠正记录为 Markdown 文件,供后续复用并晋升为工作区记忆。
用自然语言描述需求,在本地与远程技能市场里找技能并给出推荐的技能。
给 AI agent 用的浏览器自动化命令行技能。
把用户纠正与自我复盘沉淀成分层记忆、并按使用情况升降级的技能。
在安装第三方技能之前,按清单审查来源、权限与危险模式的技能。
把 agent 的记忆与跨技能状态存成带类型和约束的知识图谱的技能。
一份为 AI 代理规划主动跟进、工作记忆与复盘流程的工作区配置指南。
指导如何创建与更新有效 Claude 技能的写作指南。
数据月份:2026-09 · 下载/星标/安装数聚合自公开技能注册库(ClawHub、SkillHub),按月更新。口径说明见数据方法。