Containerized RAG Infrastructure

A public technical demonstration of document ingestion, embeddings, semantic search and RAG-style knowledge workflows in a containerized architecture.

A useful retrieval application needs more than a notebook: it needs a clear service layout, ingestion and retrieval interfaces, internal data services and a usable front end.

A personal engineering project focused on deployment architecture, document ingestion and retrieval workflows.

I designed and implemented the application, including the API, data services, ingestion and retrieval flow, Next.js interface and Docker-oriented deployment layout.

The project packages FastAPI, PostgreSQL and Qdrant behind Docker Compose and Traefik. Documents are ingested, chunked, embedded and retrieved through API endpoints, while data services remain internal to the application network.

• Docker Compose deployment layout
• FastAPI application layer
• PostgreSQL and Qdrant data services
• Document ingestion and chunking
• Semantic retrieval and RAG-style endpoints
• Next.js user interface
• Traefik HTTPS and reverse-proxy configuration

• FastAPI
• PostgreSQL
• Qdrant
• OpenAI embeddings
• Docker Compose
• Next.js
• Traefik

• Embeddings for ingested documents
• Semantic search
• RAG-style retrieval and chat endpoints

• Treat networking, internal data services and TLS as part of the technical demonstration.
• Keep application, retrieval and data-service responsibilities separated.
• Expose retrieval through application endpoints rather than a notebook-only interface.

• Document ingestion and chunking
• Semantic retrieval and RAG-style endpoints
• FastAPI, PostgreSQL and Qdrant services
• Docker Compose networking
• Next.js interface
• Traefik HTTPS configuration

None listed.

Working technical demo

A working technical demonstration of containerized ingestion, semantic retrieval and RAG application architecture.