jev-ultralightspeed

BRRRRRRRRRRRRRRRRRRRRRR

How it uses Jev

You have a pile of text and one question about each. Fifty thousand support tickets to triage. A quarter of reviews to sort by sentiment. A month of logs to flag. A column to backfill on a table you already have. This answers the question for all of them, with TypeSafe's Jev, in the time it takes to get a coffee.

Highlights

  • It does not change your question. The only difference between a packed question and a single
  • It does not defend against what is inside your items. Packing puts thirty-two items in one
  • It does not cache across processes unless you ask it to. The cache lives in the client, in
  • The cache key holds the pack you asked for, not the one an answer came back from. A call of
  • It does not hide failures. Retries cover 429, 500, 502, 503, 504 and 529, with jitter and the
  • It is not an eval harness. It makes a judge fast, and it will tell you which of its verdicts

Source: community catalog. Details and metrics reflect the published community snapshot and are not a performance endorsement. Documentation details extracted from GitHub · the README · the project website.

Keep exploring

Similar to jev-ultralightspeed

Browse all
stuntd project preview
Demos & playgrounds
Local proxy that learns your app's typed LLM decisions and answers them with a Laya head. Jev and OpenAI compatible.
jevframe project preview
Demos & playgrounds
Semantic AI for pandas and Polars: classify text, analyze sentiment, and score DataFrame rows with natural-language questions and full probabilities using TypeSafe Jev.
jev-me project preview
Demos & playgrounds
A grill-me style interrogation of your idea, with Jev doing the grilling.
Browser & computer use
A browser agent that turns a single goal into a sequence of lightning-fast actions.
SemIf project preview
Jev alternatives & open source
Semantic ifs from open models, on a 3090 at home. Independent; not affiliated with Jev or TypeSafe.
NanoJev project preview
Benchmarks & research
A nano replica of Jev: parallel decisions, dynamic candidates, and an end-to-end training pipeline.
jevlike project preview
Benchmarks & research
Train a small model that chooses among a changing list of text options, one probability per option in a single pass. Includes Doom, chess, and Wikispeedia demos.
typesafe-computer-use project preview
Browser & computer use
Computer use for about $0.0002 a step: OCR the screen, classify the next action with TypeSafe, click. macOS.
hermes-jev-skills project preview
Browser & computer use
Jev-powered model routing, memory, compaction, skill selection, computer and browser use for Hermes agents (also Claude Code and Codex)