A candidate-scoring head returns distributions for gates, routes and scores without decoding prose or JSON answers. The README compares a benchmark-trained AgentJev specialist with Jev 1.13.0 evaluated zero-shot; these use different training conditions.
jev-dspy-lab: Reproducible calibration and selective-risk
jmanhype/jev-dspy-lab
VerifiedResearchDocumented
jev-dspy-lab: Reproducible calibration and selective-risk benchmarks for Jev/TypeSafe decisions in DSPy workflows. Explore the Jev references, Python source code and similar projects.
Repository description: Reproducible calibration and selective-risk benchmarks for Jev/TypeSafe decisions in DSPy workflows
Get started
Clone the repository and follow its README for install and usage. JevHunt has not run this project.
git clone https://github.com/jmanhype/jev-dspy-lab.gitProject facts
- Relationship to Jev
- Research
- Evidence
- Documented
- Language
- Python
- License
- MIT
- Origin
- Original repository
- Repository status
- Not archived
- Created
- 2026-09-17
- Last code update
- 2026-09-20
- GitHub stars
- 10
- Evidence checked
- Sep 29, 2026
- Metadata checked
- Sep 29, 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.
- requires both `OPENAI_API_KEY` and `TYPESAFE_API_KEY`,
Evidence commit: b65a738c9da2e192197eb65c5af4405ac81b38df
Discovered through: github-search.
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