retellai-deploy-integrationClaude Skill

Retell AI Deploy Integration

Overview

Deploy Retell AI-powered applications to popular platforms with proper secrets management.

Prerequisites

• Retell AI API keys for production environment
• Platform CLI installed (vercel, fly, or gcloud)
• Application code ready for deployment
• Environment variables documented

Vercel Deployment

Environment Setup

# Add Retell AI secrets to Vercel
vercel secrets add retellai_api_key sk_live_***
vercel secrets add retellai_webhook_secret whsec_***

# Link to project
vercel link

# Deploy preview
vercel

# Deploy production
vercel --prod

vercel.json Configuration

{
  "env": {
    "RETELLAI_API_KEY": "@retellai_api_key"
  },
  "functions": {
    "api/**/*.ts": {
      "maxDuration": 30
    }
  }
}

Fly.io Deployment

fly.toml

app = "my-retellai-app"
primary_region = "iad"

[env]
  NODE_ENV = "production"

[http_service]
  internal_port = 3000
  force_https = true
  auto_stop_machines = true
  auto_start_machines = true

Secrets

# Set Retell AI secrets
fly secrets set RETELLAI_API_KEY=sk_live_***
fly secrets set RETELLAI_WEBHOOK_SECRET=whsec_***

# Deploy
fly deploy

Google Cloud Run

Dockerfile

FROM node:20-slim
WORKDIR /app
COPY package*.json ./
RUN npm ci --only=production
COPY . .
CMD ["npm", "start"]

Deploy Script

#!/bin/bash
# deploy-cloud-run.sh

PROJECT_ID="${GOOGLE_CLOUD_PROJECT}"
SERVICE_NAME="retellai-service"
REGION="us-central1"

# Build and push image
gcloud builds submit --tag gcr.io/$PROJECT_ID/$SERVICE_NAME

# Deploy to Cloud Run
gcloud run deploy $SERVICE_NAME \
  --image gcr.io/$PROJECT_ID/$SERVICE_NAME \
  --region $REGION \
  --platform managed \
  --allow-unauthenticated \
  --set-secrets=RETELLAI_API_KEY=retellai-api-key:latest

Environment Configuration Pattern

// config/retellai.ts
interface Retell AIConfig {
  apiKey: string;
  environment: 'development' | 'staging' | 'production';
  webhookSecret?: string;
}

export function getRetell AIConfig(): Retell AIConfig {
  const env = process.env.NODE_ENV || 'development';

  return {
    apiKey: process.env.RETELLAI_API_KEY!,
    environment: env as Retell AIConfig['environment'],
    webhookSecret: process.env.RETELLAI_WEBHOOK_SECRET,
  };
}

Health Check Endpoint

// api/health.ts
export async function GET() {
  const retellaiStatus = await checkRetell AIConnection();

  return Response.json({
    status: retellaiStatus ? 'healthy' : 'degraded',
    services: {
      retellai: retellaiStatus,
    },
    timestamp: new Date().toISOString(),
  });
}

Instructions

Step 1: Choose Deployment Platform

Select the platform that best fits your infrastructure needs and follow the platform-specific guide below.

Step 2: Configure Secrets

Store Retell AI API keys securely using the platform's secrets management.

Step 3: Deploy Application

Use the platform CLI to deploy your application with Retell AI integration.

Step 4: Verify Health

Test the health check endpoint to confirm Retell AI connectivity.

Output

• Application deployed to production
• Retell AI secrets securely configured
• Health check endpoint functional
• Environment-specific configuration in place

Error Handling

Issue	Cause	Solution
Secret not found	Missing configuration	Add secret via platform CLI
Deploy timeout	Large build	Increase build timeout
Health check fails	Wrong API key	Verify environment variable
Cold start issues	No warm-up	Configure minimum instances

Examples

Quick Deploy Script

#!/bin/bash
# Platform-agnostic deploy helper
case "$1" in
  vercel)
    vercel secrets add retellai_api_key "$RETELLAI_API_KEY"
    vercel --prod
    ;;
  fly)
    fly secrets set RETELLAI_API_KEY="$RETELLAI_API_KEY"
    fly deploy
    ;;
esac

Resources

• Vercel Documentation
• Fly.io Documentation
• Cloud Run Documentation
• Retell AI Deploy Guide

Next Steps

For webhook handling, see retellai-webhooks-events.