LLGTRT: TensorRT-LLM+Rust server w/ OpenAI-compat and Structured Output
I wanted to share a project I've been working on for the past few weeks: llgtrt. It's a Rust implementation of a HTTP REST server for hosting Large Language Models using llguidance library for constrained output with NVIDIA TensorRT-LLM. The server is compatible with the OpenAI REST API and supports structured JSON schema enforcement as well as full context-free grammars (via Guidance). It's similar in spirit to the Python-based TensorRT-LLM OpenAI server example but written entirely in Rust and built with constraints in mind. No Triton Inference Server involved. This also serves as a demo…
LLGTRT: TensorRT-LLM+Rust server w/ OpenAI-compat and Structured Output launched on October 30, 2024 with 6 votes, #1,611 of 5,185 launches that month and more than 50% of that year's launches. The site was still online in September 2026, 1 year on.
What it does
TensorRT-LLM server with Structured Outputs (JSON) built with Rust - guidance-ai/llgtrt
This project implements a REST HTTP server with OpenAI-compatible API , based on NVIDIA TensorRT-LLM and llguidance library for constrained output. The server supports regular completions and chat endpoints with JSON schema enforcement ("Structured Output"), as well as full context-free grammars using the Guidance library . This server is similar in spirit to the TensorRT-LLM OpenAI server example , but it is Python-free (implemented in Rust) and includes support for constrained output. Like the example above, it does not use the NVIDIA Triton Inferencefrom github.com
In the maker’s words, at launch
I wanted to share a project I've been working on for the past few weeks: llgtrt. It's a Rust implementation of a HTTP REST server for hosting Large Language Models using llguidance library for constrained output with NVIDIA TensorRT-LLM. The server is compatible with the OpenAI REST API and supports structured JSON…
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