Deploy can be even Faster
AI-powered deployment automation that makes web deployment as simple as a conversation. Chat with our AI, provide your project path, and watch the magic happen.
Why Choose Dipole?
AI-Powered Intelligence
Smart project analysis and deployment strategy selection. Our AI understands your project structure and chooses the optimal deployment method automatically.
Real-Time Progress
Visual progress tracking with live log streaming. Watch your deployment happen in real-time with detailed progress indicators and instant feedback.
Multi-Platform Support
Deploy to Netlify or Vercel with CLI or API methods. Support for React, Next.js, Vue, static sites, and many more frameworks.
Mobile-Friendly Sharing
QR codes and instant URL sharing make it easy to test your deployments on any device. Perfect for client presentations and team collaboration.
Advanced Diagnostics
Built-in log analysis and troubleshooting tools. Copy, download, and analyze deployment logs with intelligent error detection.
Conversational Interface
Natural language deployment commands. Simply chat with the AI using plain English - no complex configuration files needed.
Setup Required for Lovable AI Integration
โ ๏ธ Important: Complete Setup Before Using Public App
To use Dipole in a public Lovable AI environment, you must first complete all setup steps on your local machine. This ensures proper authentication and API access.
Install Prerequisites
Node.js (v18+), Python (v3.9+)
python --version
Get OpenAI API Key
Required for AI functionality
# platform.openai.com/api-keys
Setup Netlify CLI
For Netlify deployments
netlify login
Setup Vercel CLI
For Vercel deployments
vercel login
Clone & Install
Get the Dipole repository
cd fast_deploy
pip install -r demo/requirements.txt
Configure Environment
Set your API keys
# Edit .env with your keys
Enter Secrets in App
Use the left โSecretsโ panel to input tokens
NETLIFY_TOKEN, VERCEL_TOKEN
Optionally enable โRemember on this deviceโ to cache to state/user_secrets.json. These values are injected to CLI and AI agent via environment variables.