Fireflies Deploy Integration

Fireflies.ai Deploy Integration

Overview

Deploy Fireflies.ai-powered applications to popular platforms with proper secrets management.

Prerequisites

• Fireflies.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 Fireflies.ai secrets to Vercel
vercel secrets add fireflies_api_key sk_live_***
vercel secrets add fireflies_webhook_secret whsec_***

# Link to project
vercel link

# Deploy preview
vercel

# Deploy production
vercel --prod

vercel.json Configuration

{
  "env": {
    "FIREFLIES_API_KEY": "@fireflies_api_key"
  },
  "functions": {
    "api/**/*.ts": {
      "maxDuration": 30
    }
  }
}

Fly.io Deployment

fly.toml

app = "my-fireflies-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 Fireflies.ai secrets
fly secrets set FIREFLIES_API_KEY=sk_live_***
fly secrets set FIREFLIES_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="fireflies-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=FIREFLIES_API_KEY=fireflies-api-key:latest

Environment Configuration Pattern

// config/fireflies.ts
interface Fireflies.aiConfig {
  apiKey: string;
  environment: 'development' | 'staging' | 'production';
  webhookSecret?: string;
}

export function getFireflies.aiConfig(): Fireflies.aiConfig {
  const env = process.env.NODE_ENV || 'development';

  return {
    apiKey: process.env.FIREFLIES_API_KEY!,
    environment: env as Fireflies.aiConfig['environment'],
    webhookSecret: process.env.FIREFLIES_WEBHOOK_SECRET,
  };
}

Health Check Endpoint

// api/health.ts
export async function GET() {
  const firefliesStatus = await checkFireflies.aiConnection();

  return Response.json({
    status: firefliesStatus ? 'healthy' : 'degraded',
    services: {
      fireflies: firefliesStatus,
    },
    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 Fireflies.ai API keys securely using the platform's secrets management.

Step 3: Deploy Application

Use the platform CLI to deploy your application with Fireflies.ai integration.

Step 4: Verify Health

Test the health check endpoint to confirm Fireflies.ai connectivity.

Output

• Application deployed to production
• Fireflies.ai secrets securely configured
• Health check endpoint functional
• Environment-specific configuration in place

Error Handling

Examples

Quick Deploy Script

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

Resources

• Vercel Documentation
• Fly.io Documentation
• Cloud Run Documentation
• Fireflies.ai Deploy Guide

Next Steps

For webhook handling, see fireflies-webhooks-events.