audio-reply
Generate audio replies using TTS. Trigger with "read it to me [URL]" to fetch and read content aloud, or "talk to me [topic]" to generate a spoken response. Also responds to "speak", "say it", "voice reply".
- License 许可
- MIT
- 最近更新
- 2026-04-05
- Stars
- ★ 7
- Forks
- 1
01 前言 Front Matter
- name
- audio-reply
- homepage
- https://github.com/anthropics/claude-code
- metadata
- { "clawdbot": { "emoji": "?", "requires": { "bins": [ "uv" ] } } }
- description
- Generate audio replies using TTS. Trigger with "read it to me [URL]" to fetch and read content aloud, or "talk to me [topic]" to generate a spoken response. Also responds to "speak", "say it", "voice reply".
02 资源文件 1
- 参考文档_meta.json281 B
03 SKILL.md 正文
Audio Reply Skill
Generate spoken audio responses using MLX Audio TTS (chatterbox-turbo model).
Trigger Phrases
- "read it to me [URL]" - Fetch content from URL and read it aloud
- "talk to me [topic/question]" - Generate a conversational response as audio
- "speak", "say it", "voice reply" - Convert your response to audio
How to Use
Mode 1: Read URL Content
User: read it to me https://example.com/article
- Fetch the URL content using WebFetch
- Extract readable text (strip HTML, focus on main content)
- Generate audio using TTS
- Play the audio and delete the file afterward
Mode 2: Conversational Audio Response
User: talk to me about the weather today
- Generate a natural, conversational response
- Keep it concise (TTS works best with shorter segments)
- Convert to audio, play it, then delete the file
Implementation
TTS Command
uv run mlx_audio.tts.generate \
--model mlx-community/chatterbox-turbo-fp16 \
--text "Your text here" \
--play \
--file_prefix /tmp/audio_reply
Key Parameters
--model mlx-community/chatterbox-turbo-fp16- Fast, natural voice--play- Auto-play the generated audio--file_prefix- Save to temp location for cleanup--exaggeration 0.3- Optional: add expressiveness (0.0-1.0)--speed 1.0- Adjust speech rate if needed
Text Preparation Guidelines
For "read it to me" mode:
- Fetch URL with WebFetch tool
- Extract main content, strip navigation/ads/boilerplate
- Summarize if very long (>500 words) - keep key points
- Add natural pauses with periods and commas
For "talk to me" mode:
- Write conversationally, as if speaking
- Use contractions (I'm, you're, it's)
- Add filler words sparingly for naturalness ([chuckle], um, anyway)
- Keep responses under 200 words for best quality
- Avoid technical jargon unless explaining it
Audio Generation & Cleanup (IMPORTANT)
Always delete the audio file after playing - it's already in the chat history.
# Generate with unique filename and play
OUTPUT_FILE="/tmp/audio_reply_$(date +%s)"
uv run mlx_audio.tts.generate \
--model mlx-community/chatterbox-turbo-fp16 \
--text "Your response text" \
--play \
--file_prefix "$OUTPUT_FILE"
# ALWAYS clean up after playing
rm -f "${OUTPUT_FILE}"*.wav 2>/dev/null
Error Handling
If TTS fails:
- Check if model is downloaded (first run downloads ~500MB)
- Ensure
uvis installed and in PATH - Fall back to text response with apology
Example Workflows
Example 1: Read URL
User: read it to me https://blog.example.com/new-feature
Assistant actions:
1. WebFetch the URL
2. Extract article content
3. Generate TTS:
uv run mlx_audio.tts.generate \
--model mlx-community/chatterbox-turbo-fp16 \
--text "Here's what I found... [article summary]" \
--play --file_prefix /tmp/audio_reply_1706123456
4. Delete: rm -f /tmp/audio_reply_1706123456*.wav
5. Confirm: "Done reading the article to you."
Example 2: Talk to Me
User: talk to me about what you can help with
Assistant actions:
1. Generate conversational response text
2. Generate TTS:
uv run mlx_audio.tts.generate \
--model mlx-community/chatterbox-turbo-fp16 \
--text "Hey! So I can help you with all kinds of things..." \
--play --file_prefix /tmp/audio_reply_1706123789
3. Delete: rm -f /tmp/audio_reply_1706123789*.wav
4. (No text output needed - audio IS the response)
Notes
- First run may take longer as the model downloads (~500MB)
- Audio quality is best for English; other languages may vary
- For long content, consider chunking into multiple audio segments
- The
--playflag uses system audio - ensure volume is up
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