Observabilité et ops

Cette plateforme autohébergée couvre stratégies Python, backtests, simulation, exécution réelle et suivi. Jev évalue ordre, stratégie, exposition, positions et budget, puis renvoie des choix typés et leurs probabilités pour filtrer les entrées.

Il fournit conventions et instrumentation pour tracer les applications IA, dont appels de modèles, recherche et outils externes. L'intégration TypeSafe enregistre systemOne en spans avec entrées et sorties JSON, modèle et tokens ; les exemples couvrent Choice, Noul et Score.

DSCODE est un agent de développement macOS dont l’interface, la CLI et les scripts partagent une session persistante. Il inclut un client Jev distinct pour Decisions alpha d’OpenRouter, avec Choice, Score et Noul. Les sessions servent à modifier, tester et transmettre des tâches entre agents ; le client Jev nécessite une clé API.

TypeSafe Mario est une boucle NES expérimentale utilisant la télémétrie de l’émulateur et des observations issues de la RAM. Avec Python 3.13, une clé TypeSafe et le jeu local, inspectez state-demo avant de lancer play.

Local Context Compiler (lcc): clean, dedupe and compact prompt context before it reaches the model, then report every block dropped, the cache tokens a pass invalidates and when pruning pays off. Runs offline with a local 1K decision model. MIT, no API key, zero telemetry.

Confidence-gated incident routing with TypeSafe Jev

A unified, async Python framework for LLM applications—chat, autonomous agents, RAG, and sandboxed code execution. Supports OpenAI, Anthropic, Gemini, Ollama, and more through a single API. Features an 8-phase cognitive reasoning cycle, Docker-based isolation, human-in-the-loop approvals, session management, and comprehensive observability.

Deterministic-first cognitive orchestration with bounded TypeSafe JEV supervision, evidence-aware escalation, and privacy-minimizing telemetry.

An autonomous risk-monitoring MCP server. Define a risk profile — a topic, the geographic locations to watch, and the policy triggers that matter — and the server runs an agentic sweep: live web search scoped by a judgment model (Jev), source scoring, and a Markdown briefing you can read from any MCP client.

A universal, sub-100ms FOSS gaming bot framework powered by OpenCV for lightning-fast visual telemetry and Jev System 1 AI for non-autoregressive decision loops.

Single-agent Pi coding coprocessor with Jev semantic gates, baseline-to-current diff review, and append-only observability telemetry.

Autonomous PlayStation 2 AI Agent with real-time visual telemetry HUD powered by TypeSafe Jev System One

Three composable judgment pipelines on TypeSafe's Jev: support-ticket triage, observability alert triage, and a deploy-risk gate.

ForgeOS Browser - a private, local-first browser built for humans and prepared for trusted AI agents. Educational prototype. Zero telemetry.

一个用TypeSafe Jev打简化掼蛋的demo；TypeSafe Jev plays simplified Guandan — LLM decision-making over dynamic legal card actions with partial observability.

Jev Guard is a real-time Windows process monitoring application powered by TypeSafe's Jev AI model. It tracks newly launched processes, logs event metadata (paths, command lines, and parent processes) to a local SQLite database, and classifies risk levels—labeling events as benign, suspicious, or malicious on a live interactive dashboard.

Trace DeFi incident exposure through sourced portfolio dependencies with optional Jev classification.

Cheap fail-open semantic edge layer for Jev (TypeSafe System One): decision service + confidence policy + decision logging + blind eval harness + skill router over 1,000+ skills. Stdlib-only Python.

Experiments with Jev (TypeSafe classifier via OpenRouter): an incident-triage agent with Jev as tool and gate, and a smart model router compared against an LLM router

Local observability proxy and playground for TypeSafe Jev

Jev-powered operations decision support for Backstage: readiness checks, incident triage, change review, template and team recommendations, and catalog reranking.

Live-stream encoder settings from telemetry and history: TypeSafe's Jev decision model inside a deterministic safety envelope. Deno, Node, edge runtimes.

Conversational agent workspace with guided onboarding, voice, evaluations and monitoring.

AI Eval Platform — an evaluation and quality-engineering layer for LLM, RAG and agentic systems, with production observability integrations.