Deploying a Complete RAG Ecosystem with a Single Command: My Ultimate Docker Stack

A developer created a Docker stack that launches a complete RAG (Retrieval-Augmented Generation) system with a single command, eliminating the headache of setting up multiple AI services separately. The stack includes eight integrated services: Ollama for running local language models, Qdrant vector database for semantic search, MongoDB for document storage, Redis for caching, Neo4j graph database for mapping relationships, Keycloak for security, and n8n for workflow automation, all deployable in under 5 minutes with just 8GB RAM.