Guide
Build a Local RAG Stack with Ollama, Open WebUI, and Qdrant
A local RAG stack lets you test private document Q&A while keeping more of the workflow under your control.
Who this is for
Developers building private document search and Q&A prototypes.
Recommended stack
- Ollama
- Open WebUI
- Qdrant
- BGE reranker or E5 embeddings
- Ragas or Phoenix for evaluation
Architecture
Use Ollama for model runtime, Open WebUI for chat, Qdrant for retrieval storage, and an evaluation tool to catch regressions.
Evaluation
Create a small test set with expected source citations before expanding the document collection.
Practical recommendations
- Chunk documents consistently
- Store source URLs and metadata
- Test reranking after initial retrieval
Tradeoffs
Local control increases operational responsibility. Retrieval quality still needs testing.
Related links
FAQ
Can this run fully offline?
Yes if all models, embeddings, and tools are local and no external APIs are configured.
Sources
Next steps
Use the model and tool directories to choose the concrete pieces for your local AI stack. Sponsor and affiliate placements will be added later.