2 posts tagged with "tutorial"

Retrieval-Augmented Generation (RAG) is how you make an LLM answer questions about your data without paying to fine-tune it. You take a question, find the most relevant chunks of your documents, and stuff them into the prompt as context.

This post walks through building a production-grade RAG pipeline in C# — from a flat file on disk to a working Ask my docs system with hybrid retrieval that beats simple semantic search on real-world queries.

If you want to run an LLM from a C# application without sending data to OpenAI or Anthropic, Ollama is the easiest path. It runs llama3, mistral, qwen, deepseek, and dozens of other models on your laptop or server, and exposes a simple HTTP API.

This guide walks through using Ollama from C# end-to-end — installation, basic chat, streaming, embeddings, tool calling, and the production gotchas you only learn after you ship.