Purpose
TypeLLM adds JSON Schema-constrained outputs to existing autoregressive models without changing their weights or architecture.
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Jev’s role
Inspired by Jev, it retains free text and optional reasoning and supports dependencies between output fields.
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How to use it
Serve a compatible model with SGLang, then submit context and typed questions through TypeLLMClient.
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Limits to consider
Schema constraints govern allowed values; text, numeric outputs and optional reasoning still generate multiple tokens.
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Evidence checked:
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.
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