A specialized notification utility to track F5-TTS model training status and results via Telegram alerts.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install f5-telegram-notify
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install f5-telegram-notify using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is F5-Telegram-Notify?
The F5-Telegram-Notify skill is a dedicated utility designed to provide real-time feedback for long-running F5-TTS training processes. By integrating directly with Telegram bots, it allows developers to monitor the lifecycle of their speech models without constantly checking terminal outputs.
This tool is particularly valuable for those building complex audio pipelines within Openclaw Skills environments, ensuring you are immediately notified of successes, errors, or training initiations. It is optimized for Docker environments, making it a robust choice for remote server monitoring.
F5-Telegram-Notify Use Cases
- Monitoring long-running F5-TTS training sessions in headless Docker environments.
- Receiving instant alerts for CUDA Out of Memory or other critical training failures.
- Capturing model checkpoint paths automatically upon successful training completion.
- Integrating automated status updates into multi-stage AI speech synthesis workflows within Openclaw Skills.
How F5-Telegram-Notify Works
- The user initiates a training process within an Openclaw Skills compatible workspace.
- The training script or manual CLI command triggers the notify.mjs script at specific lifecycle stages.
- The script retrieves the required Telegram bot token and chat ID from the local environment configuration.
- A structured message containing the status, model name, and optional checkpoint path is dispatched via the Telegram API.
- The developer receives a notification on their device, providing immediate visibility into the training state.
F5-Telegram-Notify Setup
To get started with this skill, ensure you have your Telegram Bot credentials ready. Create a .env file in the skill root with the following configuration:
TELEGRAM_BOT_TOKEN=your_bot_token
TELEGRAM_CHAT_ID=your_chat_id
You can then trigger notifications manually or via scripts using the following command structure:
node scripts/notify.mjs success "Training Complete" "my_model" "/path/to/checkpoint"
F5-Telegram-Notify Data Schema & Taxonomy
The skill utilizes a CLI-driven data input structure and environment-based configuration. The notification engine handles the following parameters:
| Parameter | Type | Required | Description |
|---|---|---|---|
| status | String | Yes | The event type: success, error, or start |
| message | String | Yes | Custom text describing the event |
| model_name | String | No | The identifier for the F5-TTS model being trained |
| checkpoint_path | String | No | The file system path to the saved model checkpoint |
F5-Telegram-Notify Advanced Features
- Seamless integration with containerized AI training stacks and Openclaw Skills workflows.
- Support for custom error reporting to debug remote training failures without SSH access.
- Flexible CLI parameters that allow for dynamic messaging based on specific training epochs.
- Lightweight ESM-based implementation for minimal overhead during high-load training sessions.
SKILL.md
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