Deploy Your Complete AI Stack

Powered by Prayog.io - Your Ultimate AI Development Platform

Get your complete AI development environment running in minutes! This guide focuses on the fastest way to deploy your AI stack with OpenWebUI, N8N workflow automation, Qdrant vector database, PostgreSQL, and comprehensive monitoring.

What You Get Instantly

Your complete AI development environment includes:

App	URL	Intent
Open WebUI	http://localhost:3000	AI Chat Interface
Grafana Monitoring	http://localhost:4000	Infrastructure & System Monitoring
Langfuse	http://localhost:3001	LLM Observability & Analytics
OpenWebUI Pipelines	http://localhost:9099	AI Pipeline Processing
N8N with OpenTelemetry	http://localhost:5678	Workflow Automation + Observability
Qdrant	http://localhost:6333	Vector Database
PostgreSQL	localhost:5433	Relational Database

Prerequisites

Before you begin, ensure you have:

1. Docker and Docker Compose installed - Download from docker.com
2. Git installed - For cloning the repository Prayog.io/prayog-ai-stack
3. 8GB+ RAM recommended - For optimal performance
4. Available ports - Ensure ports 3000, 3001, 4000, 5433, 5678, 6333, and 9099 are free

Super Quick Start (One Command!)

The fastest way to get your entire AI stack running:

git clone https://github.com/prayog-io/prayog-ai-stack.git
cd prayog-ai-stack
./quick-start.sh

That’s it! This single command sets up everything and gets you running in minutes.

Quick Access

Once the stack is running, access your services:

Service	URL	Login
OpenWebUI	http://localhost:3000	Sign up on first visit
Grafana	http://localhost:4000	admin / admin123
Langfuse	http://localhost:3001	Create account
N8N	http://localhost:5678	Setup on first visit

Management Commands

Command	Description
./quick-start.sh	Start everything
./status.sh	Check service health
./logs.sh	View service logs
./stop.sh	Stop all services

Consumption Steps

Once your AI stack is running:

1. Open OpenWebUI at http://localhost:3000 and create your account
2. Start chatting with AI models immediately
3. Monitor everything through Grafana at http://localhost:4000
4. Track AI interactions with Langfuse at http://localhost:3001
5. Create workflows using N8N at http://localhost:5678

Your AI development environment is now ready for immediate use!

Need More Control?

For advanced configuration, custom deployment options, troubleshooting, and production setup, see our comprehensive Custom Deployment Guide.

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Ready for production? Check out our Custom Deployment Guide for advanced configuration, security settings, and scaling options.