Most AI chatbot tutorials reach for Python. FastAPI, LangChain, a quick requests.post — done in 20 minutes. And that's fine for prototyping. But when I wanted to build something I'd actually put behind a real API — something with proper async concurrency, typed errors, and zero GC pauses — I reached for Rust instead.
This is a writeup of chatbot, a production-oriented Rust backend that unifies Claude, OpenAI, and Ollama behind a single interface — with a Web UI, CLI mode, and Docker support baked in.
Why Rust for an AI Backend?
It's a fair question. LLM API calls are network-bound, so why does the backend language even matter?
A few reasons:
