Jev FAQ: official access, downloads and integrations

Jev is developed by TypeSafe AI. Use the official documentation and TypeSafe's console for model access. JevHunt is an independent project directory, not the provider or its sign-in page.

Use the official console. The quick start links to the playground and API-key page. Creating a JevHunt account is for submissions and does not create a TypeSafe account or model credential.

First distinguish an API client, a community application and model weights. The official quick start documents hosted API access and installation of typesafe-sdk or @typesafe-ai/sdk. Installing those packages does not download the hosted model. For a particular app, use its original repository's release instructions; for independent local models, see local alternatives.

A local TypeSafe SDK client calls the hosted API; its CPU does not run the hosted inference. Independent models and adapters have their own CPU, GPU, MPS or MLX support. Check the exact checkpoint and runtime in the hardware comparison.

TypeSafe documents the official Python and JavaScript/TypeScript clients. Other language clients and CLI tools need individual ownership and compatibility checks. The SDK guide explains what to verify.

JevHunt's status page reports directory discovery and catalog updates. It does not certify a provider's API availability. For an inference issue, check the selected provider's console, documented error response and request logs.

Jev is TypeSafe AI's model. A Google-related integration or search query does not establish a native Vertex deployment. Verify the provider's model catalog, endpoint and authentication. An adapter backed by another model remains a different backend. See provider distinctions.

OpenRouter's official cookbook sends typed questions to its Decisions API. That is distinct from generic chat completion and from typesafe/jev-router, which routes requests to models. Use the documented endpoint and current model ID in the API guide.

It judges supplied state through typed questions and returns choices, scores or probabilities for software to use. Jev's output is different from generated prose. Read the model explanation for the answer types and limits.

State is the material supplied for a request: text, a JSON object or an array of text values. It is not automatically persistent conversation memory. Your application decides what history and supporting facts to include.

The documented Jev model returns typed decisions rather than generated text. A chat or coding application can use it alongside a generative model, but the surrounding app supplies that additional capability. See TypeSafe's coding-agent explanation.

Start with official recipes. Community cookbooks and demos cover different providers and workflows. The cookbook guide maps classification, retrieval, routing and scoring tasks to appropriate examples.

The official playground is the documented starting point. Jev Showcase is an independent interactive example. A project called playground or showcase is not automatically the provider's official console.

Kill My Idea composes judgments about a startup idea into a rubric-driven verdict. It illustrates a decision application; the verdict is not a validated prediction of business success.

No individual answer is guaranteed by confidence or calibration. Evaluate errors and review coverage on your workload. Choice and Score include confidence in the documented interface; Noul supplies a yes probability. See the official confidence reference.

Choose an agent skill for writing TypeSafe integrations, a decision tool for bounded questions, a router for model/skill selection, or a hook for permissions and context. The integration guide distinguishes these jobs.

It can provide API guidance through a skill or judgments through a community tool or hook. It does not become Codex's text-generating model. Check the selected project's supported host and version in the Codex section.

A decision plugin can check or route work while the generative model keeps producing code. Use the documented plugin or permission-hook interface for the relevant release. See OpenCode integrations.

Community components document model routing, skill selection, context decisions and other helpers. Those capabilities belong to the particular component and configuration. The Hermes section links to the relevant source.

No. A router chooses models or agents; an approval gate judges tool calls. Extensions also differ in what happens without credentials or during an outage. Compare their documented behavior in the Pi and Oh My Pi section.

Retained text can remain verbatim, but pruning can still remove facts needed later. Define what must survive and measure task completion as well as token reduction. See context compaction and evidence retention.

A framework integration places a decision at an application boundary, such as graph routing or issue triage. It does not automatically configure a coding CLI. Check the supported purpose and host in the agent project directory.

Extract text first with a parser or OCR component, then ask typed category or tag questions. Keep unreadable inputs separate from ambiguous categories and preserve originals. The document guide includes a Python example and review workflow.

Community integrations expose typed judgments as database functions, with distinct installation, permissions and network requirements. Start with the SQL guide and the exact extension's README.

Neo4Jev describes graph traversal; JevGraph describes proposing document-backed relationships with schema checks. Entity alignment is another distinct task. See the graph comparison.

It can judge candidates, filter passages or check answerability; another component retrieves the candidates and another may generate the answer. The RAG guide explains those boundaries and provenance checks.

Several owners use that name for different search tools. Match the package, owner, source scope and backend to your task. The Jevgrep section gives a verified code-search starting point.

Permissions and required approvals belong in deterministic application policy. A model can assist with judgments inside those boundaries, with response validation and an explicit failure path. See permission-hook design.

No. Detection, logging, masking and blocking are different behaviors. One documented UiPath project only records detection and fails open; it never masks or blocks. Inspect the PII example before treating a detector as a boundary.

They are independent decision implementations or models. A compatible interface does not establish shared weights, training or calibration. The alternatives guide identifies owners and comparison criteria.

They adapt other model backends to bounded decision questions or a compatible evaluation interface. Check probability support and response semantics before changing a base URL. See adapter distinctions.

They provide community evaluation or comparison tools. Results depend on the task set, model version and conditions; they are not official certifications. Use the evaluation scorecard to compare results fairly.

The documented TypeSafe API is text-only. External components can prepare text from media; independent visual models have their own architectures. See computer use, visual and voice workflows.

An engine/controller supplies observations and legal actions, Jev judges a bounded choice, and the controller acts. Check whether a demonstration uses a real model, mock, replay or simulator. See game-agent examples.

They document simulated observation, decision and control workflows. The perception model, physics environment and controller remain separate components. Read the robotics section for evaluation boundaries.

A client can run locally while calling remote models. Check its platform, provider, retained history and final action behavior. The desktop and mobile guide separates the client from inference.

They are distinct community components: a UI workspace, a call visualizer/proxy and a browser extension. Their names do not establish official ownership. See UI and observability tools.

A dashboard may use a mock policy, replay or simulated fills. Check model identity and actual execution records before interpreting outcomes. The trading-project guide explains those distinctions without making return claims.

A project can combine world-model planning with a decision judge. That does not identify the judge's architecture or establish broad general intelligence. See research scope and evidence.

Match the full owner/repository identifier, the package or release source, and the actual backend. Search the project directory and read its evidence link. If no reliable matching entity exists, do not install a similarly named package or assume a relationship to Jev.