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TypeSafe AI’s Jev 1.14.0 adds image understanding to its typed decision API, including a new box question that locates an object with normalized coordinates. The release also introduces an opt-in context budget of approximately 262,000 tokens. It is available through the moving jev-preview alias, while applications that need a fixed target should pin jev-1.14.0.
What Jev 1.14 changes
Jev is a decision API rather than a general prose chatbot. An application sends state and typed questions, then receives structured values, probabilities and confidence. Jev 1.14 keeps the existing text decision types and adds three capabilities aimed at multimodal and large-document workflows:
- A fourth question type,
box, for locating a described target in an image. - PNG and JPEG still-image references through a top-level
assetsmap. - An opt-in long-context mode with a ceiling of about 262k tokens.
TypeSafe AI documents the vision and long-context features as preview functionality. Existing text-only integrations do not need to change unless they require image analysis or the larger context budget.
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Jev 1.13 versus Jev 1.14
| Capability | Jev 1.13 | Jev 1.14.0 |
|---|---|---|
| Availability | Earlier model line | Preview release; available as jev-1.14.0 or the moving jev-preview alias |
| Question types | choice, score and noul |
Those types plus box |
| Image handling | Not provided in this release comparison | PNG/JPEG assets referenced from state, instructions or criteria |
| Context budget | Earlier limits | About 262k tokens per request and question when the long-context header is enabled; reported defaults are 64k per request and 32k per question |
| Required opt-in headers | Not applicable to the new features | TypeSafe-Danger-Zone-Images: true for images and TypeSafe-Danger-Zone-Long-Context: true for long context |
| Request size | Earlier limits | Official multimodal documentation reports a whole-request body cap near 32 MiB |
| Operational reliability | Text-only behavior | Vision is preview and may be less reliable than pure-text calls; validate outputs |
How the Box question works
A box question asks Jev to find a described object in an attached image. The response supplies four normalized edges—top, bottom, left and right—as fractions from 0 to 1, plus confidence. A value of 0.25 for left, for example, represents a left edge one quarter of the image width from the left side; the coordinates are not pixel values.
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Because a box response inherently contains coordinates, pair it with a presence check when the target might be absent. That lets an application distinguish “the object is not present” from a low-confidence or meaningless rectangle.
Typical decision flow
- Upload or include the PNG or JPEG once in the request’s top-level
assetsmap. - Reference that asset from the state, instructions or criteria used by the question.
- Send the image opt-in header:
TypeSafe-Danger-Zone-Images: true. - Ask a concise
boxquestion describing the target. - Check the presence result, confidence and coordinate ranges before using the rectangle downstream.
Keep descriptions specific—such as “the red warning label on the front panel”—rather than combining several unrelated objects in one question. TypeSafe AI cautions that multimodal behavior is less reliable than pure-text calls, so simple questions and application-side validation are important.
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Sending images through the assets map
Images are not repeatedly embedded in every question. Jev 1.14 expects a top-level assets map, with questions or criteria referring to the asset by its key. This allows one uploaded image to support multiple typed decisions in the same request.
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The documented image formats are PNG and JPEG still images. Independent coverage reports a limit of up to 16 MiB per file and a supported side range of 256 to 1,568 pixels; the official multimodal documentation separately reports a whole-request body cap near 32 MiB. Treat both as operational limits, and account for all assets and request fields when sizing a call.
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How the 262k-token context mode is enabled
Jev 1.14 does not automatically grant the larger window. Send TypeSafe-Danger-Zone-Long-Context: true to raise both the per-request and per-question budgets to approximately 262k tokens. MarkTechPost reports the default budgets as 64k tokens per request and 32k per question when the header is absent.
The larger budget is useful for long records, collections of documents or image-plus-text decisions, but it does not remove the request-body limit. Token capacity and byte size are separate constraints: a request can fit the token budget and still exceed the near-32 MiB body cap.
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Versioning and rollout guidance
Pin while testing
Use jev-1.14.0 for reproducible tests. The jev-preview alias can move as TypeSafe AI updates preview behavior, which makes it unsuitable for a controlled production experiment unless your deployment process explicitly accepts model changes.
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- Reject boxes with edges outside the 0–1 range or with
leftgreater thanrightortopgreater thanbottom. - Set an application confidence threshold appropriate to the cost of a false detection.
- Log the pinned model identifier, headers and asset dimensions so a changed result can be investigated.
- Keep a text-only fallback for workflows where an incorrect visual decision has serious consequences.
Check preview readiness
Jev 1.14 is not presented as a generally stable vision release. The vision and long-context options are preview features, and TypeSafe AI warns that multimodal calls can be less reliable than pure-text decisions. Production use should therefore begin with a limited rollout, representative images and explicit output checks rather than an unconditional replacement of a text-only model.
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Who should upgrade
Teams that only use choice, score or noul questions can continue on their current Jev integration. Upgrade testing is justified when an application needs object localization, image-based criteria or documents beyond the earlier context budgets. In each case, enable the relevant danger-zone header deliberately; neither images nor the 262k-token mode is implied by selecting the 1.14 model identifier alone.
The Bottom Line
Jev 1.14.0 is a preview typed-decision model line that adds normalized image boxes and optional approximately 262k-token context. Pin the version, send the required opt-in headers, respect image and body limits, and validate every visual result before treating it as production-grade.
Quick Recap
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