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Generate tagged ElevenLabs v3 TTS audio and upload to Google Drive and FTP

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Created by: Davide || n3witalia

Davide

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This workflow is an AI-powered text-to-speech production pipeline designed to generate highly expressive audio using ElevenLabs v3.
It automates the entire process from raw text input to final audio distribution and upload the mp3 file to Google Drive and an FTP space.

Key Advantages

1. ✅ Cinematic-quality audio output

By combining AI-driven emotional tagging with ElevenLabs v3, the workflow produces audio that feels acted, not simply read.

2. ✅ Fully automated pipeline

From raw text to hosted audio file, everything is handled automatically:

  • No manual tagging
  • No manual uploads
  • No post-processing

3. ✅ Multi-input flexibility

The workflow supports:

  • Manual testing
  • Chat-based usage
  • API/Webhook integrations
    This makes it ideal for apps, CMSs, games, and content platforms.

4. ✅ Language-agnostic

The agent preserves the original language of the input text and applies tags accordingly, making it suitable for international projects.

5.✅ Consistent and correct tagging

The use of Context7 ensures that all audio tags follow the official ElevenLabs v3 specifications, reducing errors and incompatibilities.

6. ✅ Scalable and production-ready

Automatic uploads to Drive and FTP make this workflow ready for:

  • Large content volumes
  • CDN delivery
  • Team collaboration

7.✅ Perfect for storytelling and media

The workflow is especially effective for:

  • Horror and cinematic storytelling
  • Audiobooks and podcasts
  • Games and immersive narratives
  • Voiceovers with emotional depth

How it Works

  1. Text Input & Processing: The workflow accepts text input through multiple triggers - manual execution via "Set text" node, webhook POST requests, or chat message inputs. This text is passed to the Audio Tagger Agent.

  2. AI-Powered Audio Tagging: The Audio Tagger Agent uses Claude Sonnet 4.5 to analyze the input text and intelligently insert ElevenLabs v3 audio tags. The agent follows strict rules: maintaining original meaning, adding tags for pauses, rhythm, emphasis, emotional tones, breathing, laughter, and delivery variations while keeping the output in the original language.

  3. Reference Validation: During tagging, the agent consults the Context7 MCP tool, which provides access to the official ElevenLabs v3 audio tags guide to ensure correct and consistent tag usage.

  4. Text-to-Speech Conversion: The tagged text is sent to ElevenLabs' v3 (alpha) model, which converts it into speech using a specific voice with customized voice settings including stability, similarity boost, style, speaker boost, and speed controls.

  5. Dual Output Distribution: The generated audio file is simultaneously uploaded to two destinations: Google Drive (in a specified "Elevenlabs" folder) and an FTP server (BunnyCDN), ensuring the file is stored in both cloud storage platforms.

Set Up Steps

  1. Prerequisite Configuration:

    • Configure Anthropic API credentials for Claude Sonnet access
    • Set up ElevenLabs API credentials with access to v3 (alpha) models
    • Configure Google Drive OAuth2 credentials with access to the target folder
    • Set up FTP credentials for BunnyCDN or alternative storage
    • Configure Context7 MCP tool with appropriate authentication headers

  2. Workflow-Specific Setup:

    • In the "Set text" node, replace "YOUR TEXT" with the default text you want to process (for manual execution)
    • In the "Upload to FTP" node, update the path from "/YOUR_PATH/" to your actual FTP directory structure
    • Verify the Google Drive folder ID points to your intended destination folder
    • Ensure the webhook path is correctly configured for external integrations
    • Adjust voice parameters in the ElevenLabs node if different voice characteristics are desired

  3. Execution Options:

    • For one-time processing: Use the manual trigger and set text in the "Set text" node
    • For API integration: Use the webhook endpoint to receive text via POST requests
    • For chat-based interaction: Use the chat trigger for conversational text input

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