Purpose

TypeLLM adds JSON Schema-constrained outputs to existing autoregressive models without changing their weights or architecture.

Evidence 1 ↗

Jev’s role

Inspired by Jev, it retains free text and optional reasoning and supports dependencies between output fields.

Evidence 1 ↗ · Evidence 2 ↗

How to use it

Serve a compatible model with SGLang, then submit context and typed questions through TypeLLMClient.

Evidence 1 ↗ · Evidence 2 ↗

Limits to consider

Schema constraints govern allowed values; text, numeric outputs and optional reasoning still generate multiple tokens.

Evidence 1 ↗ · Evidence 2 ↗

Repository description

TypeLLM: LLMs with type-safe generation

Project facts

Relationship to Jev
Local alternative
Evidence
Documented
Language
Python
License
Apache-2.0
Origin
Original repository
Repository status
Not archived
Created
2026-09-17
Last code update
2026-09-28
GitHub stars
835
Evidence checked
Sep 30, 2026
Metadata checked
Sep 28, 2026
Check status
Up to date

Stars measure the whole repository, including work unrelated to Jev.

Evidence and scope

Documented records the linked documentation or source. JevHunt has not independently run or benchmarked this project.

Evidence commit: f009f6acb6108f7944ae8d84f0032109860fa812

Discovered through: awesome-jev, github-search.

How we review →

Suggest a correction · Claim this listing · Submit a project