1. 1

    此套件透過 ONNX Runtime 執行 Convai Innovations 的 Laya 模型,為 Node.js 和 TypeScript 提供具型別的分類與評分。 以 Node.js 20 或更新版本安裝 @receptron/laya,載入 Laya 後將狀態和具型別的問題交給 systemOne,用完關閉實例。

    本地替代模型TypeScriptREADME.md:13-16 @6478649
    589
  2. 2

    DocJev 可分類 PDF、DOCX 和 PPTX,或將合併文件拆成帶類別的頁碼範圍,並可匯出 PDF。 以 uv 安裝 Python 套件,匯出 TYPESAFE_API_KEY,再提供分類規則執行 docjev classify 或 split。Office 格式需要 LibreOffice。

    Jev 應用PythonREADME.md:7-15 @c7abe27
    473
  3. 3

    LLM2Jev 使用本地語言及視覺模型的預填充 logits 為候選評分,不逐 token 產生答案。 它提供獨立的 Jev 風格實作,以及相容的 System One HTTP 端點。 可透過 Python 或 HTTP 使用 SGLang、Transformers、MLX,並傳入支援的文字與影像。

    本地替代模型PythonREADME.md:21 @a4aafa8
    367
  4. 4

    此實驗性 CLI 透過反覆評估、標註及定義提案,建立二元、多類別、多標籤和評分函式。 Jev 經 TypeSafe、Vercel 或 Cloudflare 評估資料;GEPA 的反思模型另外設定。

    300
  5. 5

    儲存庫提供 Jev 風格 Choice、Score 和 Noul 流程的開放模型,區分 Verdict 與 Verdict 2.0。 以 Python HTTP 伺服器提供 webgpu-demo,再開啟文件中的瀏覽器展示;模型產物與評估紀錄另附連結。

    本地替代模型PythonREADME.md:17-18 @bff2856
    292
  6. 6

    jeff 使用 GLiFormer 權重提供 Jev 相容 System One API,支援 Choice、Score 和 Noul 決策。 準備 Python 3.12 和 uv,下載檢查點,設定 JEFF_API_KEYS 並將用戶端指向 localhost:8000。

    本地替代模型PythonREADME.md:3-7 @34b32f9
    260
  7. 7

    The System One harness for System One models. Run Jev and other System One models locally or directly on HarnessRouter.ai.

    Jev 應用PythonREADME.md:44 @ab8e8f0
    185
  8. 8

    JevBench v1 - a benchmark for Jev-class typed decision models: smart, cheap, fast, reliable, open.

    研究評測PythonREADME.md:14 @9ec6f15
    165
  9. 9

    grep by meaning, across languages. TypeSafe Jev scores every line against a meaning; combine meanings with AND/OR/NOT. 意味で探す grep。日本語で英語を、英語で日本語を検索できる

    Jev 應用JavaScriptREADME.md:212 @e116fdc
    145
  10. 10

    A small extension that demos the combination of Jev x WebMCP

    Jev 整合JavaScriptREADME.md:68 @1ec3afb
    120
  11. 11

    Say it, and your Mac does it. A computer-use harness on Jev that reads the screen through Accessibility. Fast, no vision model

    Jev 應用SwiftREADME.md:49 @b22e568
    111
  12. 12

    lint text in code by jev scorerer

    Jev 應用TypeScriptREADME.md:31 @1123887
    103
  13. 13

    Connect TypeSafe Jev to Grok Bot as a cheap decision layer - usage gates, skill template, examples

    Jev 應用PythonREADME.md:34 @d015279
    87
  14. 14

    Open-source AI email triage for Gmail. Sorts your inbox into Needs reply, Updates, Promos, Sales and Spam with Jev, TypeSafe AI's decision model, via Vercel AI Gateway. Read-only, runs locally, 1,000 emails in about a minute for 3 cents.

    Jev 整合TypeScriptREADME.md:59 @f6f20af
    86
  15. 15

    TypeSafe Jev action selection inside Codex Computer Use

    Jev 應用JavaScriptREADME.md:7 @9b02783
    75
  16. 16

    Fine-grained robot control with Jev, physics previews, and configurable LIBERO tasks.

    Jev 應用PythonREADME.md:94 @3bdad98
    73
  17. 17

    An open training and inference stack for Jev-style decision models. Train models to score dynamic candidate branches from a shared prefix, with support for high-cardinality choice, calibration, and fast batched inference.

    本地替代模型PythonREADME.md:36 @6cf0dfe
    72
  18. 18

    grep for what code does, not what it's called. Semantic code search powered by TypeSafe Jev.

    Jev 應用TypeScriptREADME.md:57 @c56119f
    57
  19. 19

    Everything you need to run TypeSafe's Jev with Claude Code: a tool-call guard, tier guard, file search, browser agent, review, belay, compaction and installers.

    Jev 應用PythonREADME.md:69 @dccd374
    51
  20. 20

    Supersimple way to serve LLMs as a Jev-like endpoint

    本地替代模型PythonREADME.md:17 @13a6e41
    48
  21. 21

    Open reproduction of TypeSafe Jev: a 150M typed decision engine (noul/choice/score in one non-autoregressive pass, calibrated confidence). 0.697 vs Jev's 0.727, 2.5x better calibrated, 4x faster, free. Trains on a Colab T4 in 30 min.

    本地替代模型PythonREADME.md:5 @5977431
    45
  22. 22

    Retrieve by relevance, not resemblance: filter an AI assistant's memories with TypeSafe's Jev

    Jev 應用TypeScriptREADME.md:44 @d3e4acf
    38
  23. 23

    Practical, tested recipes for TypeSafe's Jev decision model on OpenRouter: support triage, database indexing, file organizing, tagging, taxonomies, dedupe, PII detection, extraction, search re-ranking and a browser agent.

    Jev 應用JavaScriptREADME.md:27 @3e0207d
    35
  24. 24

    Jev-powered relevance filtering and reranking for RAG in Python.

    Jev 應用PythonREADME.md:50 @d58594b
    34
  25. 25

    用 TypeSafe Jev 推荐已安装 Skill / Bounded installed-skill recommendations with TypeSafe Jev. Python CLI, Codex skill, bilingual docs and live examples.

    Jev 應用PythonREADME.md:11 @05fbd7c
    33
  26. 26

    24/7 market-making system around Jev (TypeSafe System One) decisions: deterministic state, calibrated judgments, hard risk vetoes.

    Jev 應用PythonREADME.md:49 @15d089e
    32
  27. 27

    📡 全网最全 · The world's most comprehensive tracker of the Jev (TypeSafe AI System One) ecosystem — 220+ documented cases · 108 confidence-graded entries · verified & rescanned every 3 hours · API access guide included

    31
  28. 28

    Claude Code / Codex / pi plugin that hands agent steps needing no text output to Jev (TypeSafe's judgment model) — measured p50 ~230 ms and ~$0.02 per 1,000 judgments, with typed escalation back to the LLM

    Jev 整合JavaScriptREADME.md:43 @541c86c
    31
  29. 29

    Command-line tool for TypeSafe AI's Jev model. Ask yes/no, multiple-choice and rubric questions about any text and get calibrated probabilities back. Answers become exit codes for shells and CI, JSON for scripts, and MCP tools for AI agents.

    Jev 應用RustREADME.md:61 @299a2c2
    30
  30. 30

    TypeSafe SDK in Swift

    SDK / 用戶端SwiftREADME.md:3 @4195213
    28
  31. 31

    Jev, TypeSafe's System One classifier, as a tool inside Claude Code, Codex, Pi, and OpenCode: typed classify, check, score, rank, and ask, plus one-command setup.

    Jev 應用TypeScriptREADME.md:67 @9a96edc
    27
  32. 32

    Jev-powered decision layer for DeepSeek Harness

    Jev 應用TypeScriptREADME.md:49 @87e29e2
    25
  33. 33

    sort by meaning: order lines along a plain-English dimension, from pairwise comparisons judged by TypeSafe's Jev model

    Jev 應用PythonREADME.md:61 @14926e0
    25
  34. 34

    Jolt implementation of Laya non-autoregressive System 1 decision engine

    Jev 應用ClojureREADME.md:577 @15213f5
    25
  35. 35

    JevMail - Self-hosted AI email classifier for Gmail powered by Jev. Create custom labels, organize your inbox, and filter spam with confidence and cost controls.

    Jev 應用JavaScriptREADME.md:11 @ade42bf
    22
  36. 36

    Rebuild a site's internal link map in seconds with Jev, race Claude Opus 5 on the same queue, and let a deep model rewrite the rubric from the disagreements.

    Jev 應用HTMLREADME.md:15 @58f636e
    22
  37. 37

    .feels() on anything — the AI if statement as a real, typed method. Jev + BAML.

    Jev 應用BAMLREADME.md:29 @e0f07b4
    21
  38. 38

    The invalidation layer for AI memory. Every fact gets a lease; new evidence ends it. Built on TypeSafe Jev.

    Jev 應用PythonREADME.md:85 @d6ed0ea
    21
  39. 39

    Run SemIf (Jev-style semantic-if decisions) on a CPU — no GPU. Reads typed option probabilities straight from an open model in one forward pass, plus a web UI.

    Jev 應用PythonREADME.md:47 @b49b5bf
    19
  40. 40

    Classify your inbox with Jev (TypeSafe's System One model) — tag, move, flag, and notify, all config-driven.

    Jev 應用PythonREADME.md:211 @db96194
    19
  41. 41

    Hand a whole browser task off in one call: a decision model drives the page server-side, so a flow costs one call, not a turn per click. Ref-based element tables, code-checked assertions, zero-model macro replay, over the Chrome DevTools Protocol.

    Jev 應用PythonREADME.md:611 @6b2e275
    19
  42. 42

    if you're experimenting with jev it will be easier from here

    研究評測PythonREADME.md:47 @25baa49
    17
  43. 43

    A Swift client for TypeSafe AI's Jev — typed judgements, not text

    SDK / 用戶端SwiftREADME.md:78 @d5d2280
    17
  44. 44

    Reproducible benchmark for measuring Jev reranking quality, latency, and cost in RAG

    研究評測PythonREADME.md:13 @7c7fd8a
    16
  45. 45

    Chrome extension that cleans up your LinkedIn feed: hides engagement bait, self-promo and off-topic posts using Jev, TypeSafe AI's typed classification model — and explains every decision.

    Jev 整合TypeScriptREADME.md:46 @85b2882
    16
  46. 46

    One local endpoint. The right model for every turn — enforced in code, not prompts.

    Jev 應用TypeScriptREADME.md:84 @6c37c12
    14
  47. 47

    Jev for PHP, TypeSafe AI PHP SDK

    SDK / 用戶端PHPREADME.md:140 @d71bb9e
    14
  48. 48

    Fast, bounded browser agents powered by Jev and agent-browser — typed actions, research, classification, and safe orchestration.

    Jev 應用JavaScriptREADME.md:20 @b4d4e02
    13
  49. 49

    Jev + TypeScript SDK demo

    SDK / 用戶端TypeScriptREADME.md:3 @02633c4
    13
  50. 50

    Chrome extension that labels every post on X (Substance · Humor · Chit-chat · Promo · Junk · AI-written) with TypeSafe Jev, and hides the ones you don't want.

    Jev 整合JavaScriptREADME.md:5 @24f36bc
    13