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Gtts

OrganizationPopular
benchflow-ai
gtts

Google Text-to-Speech (gTTS) for converting text to audio. Use when creating audiobooks, podcasts, or speech synthesis from text. Handles long text by chunking at sentence boundaries and concatenating audio segments with pydub.

Overview

Publisherbenchflow-ai
Repositoryskillsbench
Skill namegtts
Stars
1.8K
Forks
367
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by benchflow-ai on GitHub. Read the source before you install it.

Installation

Install the Gtts AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/benchflow-ai/skillsbench.git /tmp/skillsbench
mkdir -p .claude/skills
cp -r /tmp/skillsbench/tasks-extra/pg-essay-to-audiobook/environment/skills/gtts .claude/skills/gtts
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Gtts in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Gtts on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Gtts is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Google Text-to-Speech (gTTS)

gTTS is a Python library that converts text to speech using Google's Text-to-Speech API. It's free to use and doesn't require an API key.

Installation

bash
pip install gtts pydub

pydub is useful for manipulating and concatenating audio files.

Basic Usage

python
from gtts import gTTS

# Create speech
tts = gTTS(text="Hello, world!", lang='en')

# Save to file
tts.save("output.mp3")

Language Options

python
# US English (default)
tts = gTTS(text="Hello", lang='en')

# British English
tts = gTTS(text="Hello", lang='en', tld='co.uk')

# Slow speech
tts = gTTS(text="Hello", lang='en', slow=True)

Python Example for Long Text

python
from gtts import gTTS
from pydub import AudioSegment
import tempfile
import os
import re

def chunk_text(text, max_chars=4500):
    """Split text into chunks at sentence boundaries."""
    sentences = re.split(r'(?<=[.!?])\s+', text)
    chunks = []
    current_chunk = ""

    for sentence in sentences:
        if len(current_chunk) + len(sentence) < max_chars:
            current_chunk += sentence + " "
        else:
            if current_chunk:
                chunks.append(current_chunk.strip())
            current_chunk = sentence + " "

    if current_chunk:
        chunks.append(current_chunk.strip())

    return chunks


def text_to_audiobook(text, output_path):
    """Convert long text to a single audio file."""
    chunks = chunk_text(text)
    audio_segments = []

    for i, chunk in enumerate(chunks):
        # Create temp file for this chunk
        with tempfile.NamedTemporaryFile(suffix='.mp3', delete=False) as tmp:
            tmp_path = tmp.name

        # Generate speech
        tts = gTTS(text=chunk, lang='en', slow=False)
        tts.save(tmp_path)

        # Load and append
        segment = AudioSegment.from_mp3(tmp_path)
        audio_segments.append(segment)

        # Cleanup
        os.unlink(tmp_path)

    # Concatenate all segments
    combined = audio_segments[0]
    for segment in audio_segments[1:]:
        combined += segment

    # Export
    combined.export(output_path, format="mp3")

Handling Large Documents

gTTS has a character limit per request (~5000 chars). For long documents:

  1. Split text into chunks at sentence boundaries
  2. Generate audio for each chunk using gTTS
  3. Use pydub to concatenate the chunks

Alternative: Using ffmpeg for Concatenation

If you prefer ffmpeg over pydub:

bash
# Create file list
echo "file 'chunk1.mp3'" > files.txt
echo "file 'chunk2.mp3'" >> files.txt

# Concatenate
ffmpeg -f concat -safe 0 -i files.txt -c copy output.mp3

Best Practices

  • Split at sentence boundaries to avoid cutting words mid-sentence
  • Use slow=False for natural speech speed
  • Handle network errors gracefully (gTTS requires internet)
  • Consider adding brief pauses between chapters/sections

Limitations

  • Requires internet connection (uses Google's servers)
  • Voice quality is good but not as natural as paid services
  • Limited voice customization options
  • May have rate limits for very heavy usage

Frequently asked questions

What does the Gtts AI skill do?

Google Text-to-Speech (gTTS) for converting text to audio. Use when creating audiobooks, podcasts, or speech synthesis from text. Handles long text by chunking at sentence boundaries and concatenating audio segments with pydub.

Why use Gtts on TypingMind?

Because you install it once and use it with any model. Gtts is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Gtts in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/benchflow-ai/skillsbench/tree/main/tasks-extra/pg-essay-to-audiobook/environment/skills/gtts. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Gtts?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Gtts?

As many as you like. As long as a model supports skills, you can use Gtts with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Gtts AI skill free?

Yes. It is published on GitHub by benchflow-ai under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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