Open-source AI Trading OS, agent trading, and vibe trading, with Jev System One integration. Research, build Python strategies, backtest, and paper/live trade across crypto, stocks, and forex. Launch your own multi-tenant trading SaaS with built-in user management, billing, payments, and settlement.
OpenDecision is an open-source semantic decision engine like typesafe's jev.
1207 public resources for Jev, TypeSafe AI's System One decision model, indexed by decision pattern. Source citations, dated link checks and scheduled call-site text checks; runtime and performance are not independently tested here. EN/δΈζ, JSON schema and platform compatibility.
Curated Jev resources and runnable examples for typed AI decisions.
π₯π₯ Awesome Jev: open-source models, projects, benchmarks, and independent evaluations for Jev and System One models.
Drop-in TypeSafeClient replacement backed by LLM APIs
Build calibrated AI Functions from human feedback using Jev and GEPA.
The official Python library for the TypeSafe API
Calibrated 151M Non-Autoregressive Decision Engine beating TypeSafe Jev & Laya on LocalLLaMA/typed-decisions (77.10% acc, 0.0636 Brier, 0.0144 ECE)
Jev demos, projects, SDKs and skills, with source links and a curated X gallery.
Eyes are All JEV Needs - real time visual devisions from RGB, video and RGB-D cameras.
Unofficial skill that teaches coding agents to build with TypeSafe AI's Jev: typed decisions, calibrated confidence, and prior art from 150+ community projects.
Non-autoregressive decision engine on ModernBERT (151M) with calibrated uncertainty (RLCD), TypeSafe AI Jev benchmark audit, and in-browser WebGPU playground
A database-agnostic Agentic GraphRAG framework using swappable System One models (local Laya / cloud Jev). A plug-and-play intelligence layer featuring a complete 4-phase pipeline, continuous evaluation and custom A* traversal for any graph database.
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.
GTM workflows with Jev: datasets, prompts, and benchmark results.
离线ε―η¨ηζ¬ε°η±»εεε³ηοΌ4 ζ Έ CPU ει’ 15.6msγLocal & offline Jev / System One inference on CPU β ONNX + INT8, no torch at runtime. ζ―ζ laya / kev / PlayJev