Imported from jeremylongshore/tons-of-skills-marketplace (plugins/saas-packs/elevenlabs-pack/skills/elevenlabs-deploy-integration/SKILL.md). Install upstream with npx skills add jeremylongshore/tons-of-skills-marketplace --skill elevenlabs-deploy-integration. Copyright stays with the author (MIT).

ElevenLabs Deploy Integration

Overview

Deploy ElevenLabs TTS/voice applications to Vercel (serverless), Fly.io (containers), or Google Cloud Run with proper secrets management, timeout configuration, and streaming support. Pick the platform that matches your traffic shape, write the platform config + server code, store the API key as a platform secret, then deploy and smoke-test the live endpoint.

Prerequisites

• ElevenLabs API key for production
• Platform CLI installed (vercel, fly, or gcloud)
• Application code tested locally

Instructions

Follow these steps. The lean skeleton is below; the full config files and server code for each platform are in references/implementation.md.

1. Inspect the repo and pick a platform. Read the existing app code and any current deploy config, then choose from the comparison table below — Vercel for a simple stateless TTS API, Fly.io for streaming/WebSocket, Cloud Run for bursty variable load.

2. Write the platform config + server code. Use Write/Edit to create the platform files in the repo — vercel.json + the API route for Vercel, fly.toml + Express server for Fly.io, Dockerfile for Cloud Run. Full versions are in references/implementation.md.

3. Set the API key as a platform secret (never commit it):

   vercel env add ELEVENLABS_API_KEY production   # Vercel
   fly secrets set ELEVENLABS_API_KEY=sk_...       # Fly.io
   echo -n "sk_..." | gcloud secrets create elevenlabs-api-key --data-file=-  # Cloud Run

4. Mind the timeout. Vercel Hobby caps functions at 10s (30s on Pro) — use the eleven_flash_v2_5 model to stay under it. Fly.io and Cloud Run have no such short cap.

5. Deploy, then smoke-test the live endpoint (see references/examples.md):

   vercel --prod        # Vercel
   fly deploy           # Fly.io
   gcloud run deploy tts-service --source .   # Cloud Run (see full flags in implementation.md)

Platform Comparison for ElevenLabs

Output

A working deployment of a validated TTS build produces:

• A live TTS endpoint returning audio/mpeg (Vercel/Fly.io/Cloud Run URL)
• ELEVENLABS_API_KEY (and any webhook secret) stored as a platform secret, never in the repo
• Platform config committed to the repo — vercel.json, fly.toml, or Dockerfile — matching the chosen platform's timeout/concurrency limits
• A /health endpoint (Fly.io/Cloud Run) reporting live quota via the SDK

Error Handling

Examples

Deploy a simple TTS API to Vercel (Flash model, under the Pro timeout):

vercel env add ELEVENLABS_API_KEY production
vercel --prod

Deploy a streaming service to Fly.io and confirm quota via the health check:

fly secrets set ELEVENLABS_API_KEY=sk_your_prod_key
fly deploy
curl -s https://my-tts-service.fly.dev/health | jq

Full end-to-end flows for all three platforms — secret setup, deploy, and live smoke-test — are in references/examples.md.

Resources

• references/implementation.md — complete config files + server code per platform
• references/examples.md — end-to-end deploy + smoke-test flows for Vercel, Fly.io, Cloud Run
• Vercel Functions
• Fly.io Node.js
• Cloud Run Docs
• ElevenLabs API Quickstart

Next Steps

For webhook handling on a deployed service, see the elevenlabs-webhooks-events skill, which covers verifying signatures and handling ElevenLabs event callbacks against the endpoints you just shipped.