About This Architecture

Minimal RAG system architecture integrating a web/mobile frontend with a containerized backend that orchestrates PostgreSQL, vector storage, and Mistral LLM for semantic search and generation. User requests flow from the frontend through the backend Docker container, which queries both the relational database and vector store, then sends context to the Mistral LLM server for augmented responses. This three-tier pattern isolates presentation, application logic, and data/AI layers, enabling independent scaling and technology swaps. Fork this diagram on Diagrams.so to customize your LLM provider, vector database, or containerization strategy. The bidirectional connection between Mistral and vector storage highlights the retrieval-in-the-loop pattern central to production RAG systems.

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How do I architect a minimal retrieval-augmented generation system with an LLM backend?

This diagram shows a three-tier RAG architecture where user requests flow from a web/mobile frontend through a Docker-containerized backend that queries both PostgreSQL and vector storage, then sends context to a Mistral LLM server for augmented responses. The bidirectional connection between Mistral and vector storage enables semantic retrieval-in-the-loop, a core RAG pattern for grounding LLM ou