Peluncuran pada 16 September 2026

Agen mengubah kontrol yang terlihat menjadi ruang tindakan berindeks untuk menjalankan tujuan berbahasa alami. Jev memilih operasi dan elemen yang cocok dalam satu permintaan; LLM terpisah hanya menghasilkan teks untuk TYPE_TEXT.

Proyek ini menangani keputusan semantik kecil seperti perutean, percobaan ulang, dan pemeriksaan bukti tanpa menghasilkan kalimat jawaban. Yang ditiru adalah pola antarmuka Jev, bukan model atau pelatihannya yang tidak dipublikasikan; proyek tidak berafiliasi dengan TypeSafe.

Bot mengganti order limit post-only pada blok Monad dan mengalirkan peristiwa buku order, order, serta eksekusi ke dasbor. Dengan MODEL=jev dan TYPESAFE_AI_API_KEY, Jev memilih beli atau jual; model mock bawaan memakai heuristik momentum.

typesafe-computer-use mengubah tujuan tertulis menjadi tindakan di Mac, dengan membaca layar melalui OCR dan kontrol aksesibilitas. TypeSafe Jev memilih tindakan, sasaran, dan situs; kode menghitung fakta, sedangkan model penulis terpisah menangani teks bebas. Diperlukan kunci TypeSafe serta izin perekaman layar dan aksesibilitas. CLI menyediakan simulasi sebelum mengendalikan mouse dan keyboard sungguhan.

decider menghasilkan probabilitas Choice, Score, dan Noul dari status dan pertanyaan bertipe dalam satu lintasan maju. Keluarga model independen bergaya Jev ini berbasis Qwen; data pelatihannya tidak didistilasi dari Jev. Gunakan antarmuka Python Decider atau arahkan SDK TypeSafe ke endpoint HTTP lokal yang kompatibel.

Jev Review memeriksa diff Git atau seluruh kode untuk kebenaran, keamanan, keandalan, kompatibilitas, dan cakupan tes. Jev memilih bukti, mengklasifikasikan mekanisme, dan menilai keparahan; ketika syaratnya terpenuhi, Choice memilih peninjau. Kode menerapkan ambang dan kebijakan alur. Gunakan Node.js 24+, Git, dan kunci TypeSafe untuk membuat JSON atau melihat ulasan tersimpan secara lokal.

jev-router menjalankan CLI asli melalui proxy lokal dan memilih tingkat model pada setiap giliran pengguna baru. Pasang melalui npm, atur JEV_API_KEY, lalu jalankan jev-claude atau jev-codex dengan CLI asli yang terpasang dan terautentikasi.

TypeSafe Mario adalah pengontrol NES eksperimental yang memakai telemetri emulator dan pengamatan dari RAM. Siapkan Python 3.13, kunci TypeSafe, dan gim lokal; periksa state-demo sebelum menjalankan play.

Tentukan harapan semantik dalam perch.yaml untuk berkas atau metode, lalu periksa temuan kodenya. Klien System One mengirim pertanyaan bertipe tentang status ke TypeSafe dengan jev-latest sebagai bawaan.

Camera-only autonomous drone in MuJoCo with a small judgment model (TypeSafe Jev) in the loop at 2.5Hz

Guardrails for Pi that steer instead of interrupt: enforces your project rules on every write, holds only hard-to-undo actions (3 per 1,000 calls, measured on real sessions), catches unverified "done" claims and stuck loops, and trims tool output. Built on pi-typesafe.

Typesafe.ai System One Model Jev navigating a Neo4j graph by using a classifier over neighbouring relationships

TypeSafe Jev as a decision layer for the Pi coding agent: a measured tool-call gate plus jev_ask for typed, calibrated answers

A calibrated context sieve for Claude Code: every tool result is judged by a System One model before it enters context.

A small, type-safe client for asking AI questions about your data, powered by TypeSafe Jev.

Browser automation where an LLM plans and Jev (Typesafe System One) decides. Library, CLI and MCP server.

Codebase search powered by Jev from @typesafe-ai

Typed semantic decisions for Unix pipelines and CI, powered by TypeSafe AI Jev.

JEV-inspired parallel decisions for CUDA LLMs. One context, many decisions. vLLM API, game-agent examples, and reproducible benchmarks.

TypeSafe decisions for Pi: batched evaluation tool, terminal playground, and typed API for extension authors

Typed JSON inference with DiffusionGemma, with Every and Jev benchmark results

This is a LLM Gateway that mimics typesafe ai structured output. Like an imposter Jev.

Local bilingual probability decisions from context, questions, and candidate answers. Independent research preview inspired by TypeSafe Jev.

TypeSafe Jev controls original StarCraft shareware through keyboard and mouse with recorded action probabilities.

Agent-ergonomic CLI for TypeSafe's Jev: fast calibrated judgments (pick, rate, check, rank, triage, guard) from the shell

Unofficial study: Jev-style parallel typed decisions on stock 1.5B-8B models on an Apple Silicon laptop. Benchmarks, research notes, and a Hugging Face Space demo.

MCP server for TypeSafe Jev: typed classify, score, check, match and screen for any agent, with confidence on every answer

Typed, confidence-aware agent skill routing with TypeSafe Jev.

Community TypeSafe AI playground: 110 use cases, games, dilemmas and model challenges, with editable prompts, A/B comparisons and a mobile-friendly UI.

TypeSafe structured-output provider for RubyLLM 2

BrighTO LLM Router: free open-source, ultra-fast self-hosted Rust LLM gateway for OpenAI/Anthropic APIs, SystemOne/JEV/DJEV decisions, Ollaya/Laya, load balancing, fallback routing, team keys and token budgets.

TypeSafe (Jev) skill routing for Hermes Agent: names the one skill worth loading, before the model call. Opt-in, stdlib only, ~$0.001 per routed turn.

Async LangGraph workflow that gets a typed Jev Choice (invoice or general) and routes each inbound email to the matching handler.

Community .NET SDK for the TypeSafe AI System One API — typed noul, choice, and score questions with structured, confidence-scored answers. Not affiliated with TypeSafe AI.

Can a decision model beat dedicated rerankers? TypeSafe Jev vs Cohere Rerank 4 vs ZeroEntropy zerank-2 vs a chat-model baseline: 14 datasets, every raw API response, bootstrap ranges on every gap.

Hybrid coding harness: System 2 writes, System 1 (Jev) runs reflexes.

Ruby client for typesafe.ai

macOS computer use driven by Jev (TypeSafe System One) as the decision maker

Benchmarks and a playground for TypeSafe's Jev (System One) model: chess, and who-is-the-player-talking-to for speech-to-text game NPCs

A word-level language model whose output layer is Jev: n-gram drafter, Noul chunk verification, bits-per-token eval

Jev (TypeSafe) vs Claude Haiku 4.5 on 2 000 phishing emails: accuracy, calibration, latency, cost. Reproducible benchmark.

Discriminative Monte Carlo Tree Search using System One and Harnesses

Go client for TypeSafe's System One API and its model Jev: typed judgments and calibrated probabilities instead of generated text

Experimental multi-horizon BTC signal generator using TypeSafe Jev probabilities and Binance market data.

DeepSeek Harness (dsh) 插件:论文伴读工作台 —— PDF 转录 / 检索 / 流式问答 + 内置阅读器页面。

Eight minimal working examples of TypeSafe's Jev (a System One model) applied to mechanical and electrical engineering: CAD/CAE/CAM routing, FEM result triage, DFM screening, BOM alignment, hallucination-proof extraction. Zero dependencies.

Jev-style calibrated decision model (Choice/Score/Noul) on Qwen3.5-0.8B

Ask Jev typed questions from the shell: noul, choice, and score answers as numbers, not prose

Independent Jev 1.13.0 behavior study: report, controlled prompt experiments, raw results, and offline verification.

Drives a real browser with Jev making every decision and Vercel's agent-browser performing every action, with a benchmark.