NanoJev: local decision-model research through games

Laya uses a non-autoregressive model to answer choice, score and noul questions, with a router selecting checkpoints. Its self-hosted server exposes POST /v1/systemone for existing Jev clients; the underlying model is Laya rather than hosted Jev.

Kev provides pretrained decision models and fine-tuning for yes/no, multiple-choice and rating questions over shared text. Its API follows TypeSafe System One, allowing the TypeSafe Python SDK to target a local Kev server.

SemIf handles small semantic decisions such as routing, retries and evidence checks by reading option probabilities without generating an answer sentence. It reproduces Jev's interface pattern with open models, not Jev's undisclosed model or training, and has no TypeSafe affiliation.

Give jevos text or structured state and a yes/no question; it returns the probability of yes. The local server uses Jev's wire format for Noul requests, allowing existing clients to address a separate self-hosted model.

decider returns Choice, Score and Noul probabilities from a state and typed questions in one forward pass. This independent Jev-style model family uses Qwen bases; its training data was not distilled from Jev. Call the Python Decider interface or point TypeSafe SDKs at its compatible local HTTP endpoint.

AnyJev reads probabilities from open models to answer choice, yes/no and scoring questions without generating prose. It is an independent Jev-style approach; its L2 heads leave the base model’s weights unchanged. Use label-free L0 readouts or fit an L2 head for a particular question, with transformers or vLLM.

Instructions, tools, skills, channels and schedules live in conventional directories, making an agent project inspectable and extensible. The evaluate helper sends typed questions about supplied state through eve's model authentication, defaulting to Jev.

The native CLI supports an interactive shell, scripted requests and embedding, with skills, MCP servers and subagents. Jev receives review policy, context and the pending action, returning a clear or caution decision for the permission pipeline.

The platform supports developing and evaluating SRE agents against live system environments containing operational failure scenarios. Jev support is disabled by default; when enabled for Codex, it reviews diagnostic tests and submissions from evidence sent to TypeSafe.

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