Photo Essay Rights Desk
Paste an essay's image list, contributor records, and publication plan, and Jev routes each frame to a rights-check path while scoring documentation completeness and flagging whether contributor permission is missing.
The kernel.
Photographers paste in what arrives for Documentary publishing and Jev picks exactly one option from a fixed list, with the odds for every option shown — unclear cases get a "needs review" badge.
Why this primitiveA structured rights route and completeness score reveal publication blockers without creating ambiguous legal prose.
Required key.
Add this in your Lovable project under Settings → Secrets before pasting the prompt below.
The build prompt.
Paste into a fresh Lovable project. Make sure the key above is set first. read the build strategy →
Build "Photo Essay Rights Desk" as a ONE-SHOT Lovable build (~5 credits, no follow-ups).
Single-page TanStack Start app, one route, cut scope ruthlessly.
THIS PROMPT IS SELF-CONTAINED
Do not assume the participant knows Jev or has read any other page. TypeSafe Jev is a decision model,
not a text generator. It receives `state` plus a map of typed `questions` and returns JSON that code can
use directly. Use Choice to select exactly one defined option, Noul for a yes/no probability from 0 to 1,
and Score for a probability-weighted position across ordered levels. Keep rules, thresholds, arithmetic,
and actions in code. Use a generative model only if the product separately needs prose.
CONCEPT
Paste an essay's image list, contributor records, and publication plan, and Jev routes each frame to a rights-check path while scoring documentation completeness and flagging whether contributor permission is missing.
Discipline: Photography (Documentary publishing).
Jev pattern: Choice Router (pick one of a set) — a Jev `choice` question that routes each incoming item to one handler/category from a fixed option map, plus branch-specific questions asked in the same request.
Why typed decisions: A structured rights route and completeness score reveal publication blockers without creating ambiguous legal prose.
ENGINE: TypeSafe Jev (typed decisions, not text)
- Before writing code, ask the participant for `TYPESAFE_API_KEY` with Lovable's secure secret form. Never
ask them to paste it into chat, never prefix it with `VITE_`, and never expose it to browser code.
- Put the callable server function in `src/lib/jev.functions.ts`; do not import a server-only module from UI code.
- Validate the user's input before the handler and read `process.env['TYPESAFE_API_KEY']` inside the handler.
- From the server, call:
POST https://api.typesafe.ai/v1/systemone
Authorization: Bearer <TYPESAFE_API_KEY>, Content-Type: application/json
body: { "model": "jev-latest", "state": <Image list, contributor records, publication plan, and permissions policy>, "questions": QUESTIONS }
- Ask all questions in ONE request (they run in parallel and cannot see each other).
- Read Choice from `answers[id].choice`, `.probabilities`, and `.confidence`; Score from `.score`,
`.probabilities`, `.legend`, and `.confidence`; Noul from `.noul` only (it has no separate confidence).
SERVER IMPLEMENTATION (adapt the input name and result mapping to this concept)
```ts
import { createServerFn } from "@tanstack/react-start";
import { z } from "zod";
const Input = z.object({ text: z.string().trim().min(1).max(20000) });
export const decide = createServerFn({ method: "POST" })
.inputValidator((input: unknown) => Input.parse(input))
.handler(async ({ data }) => {
const apiKey = process.env['TYPESAFE_API_KEY'];
if (!apiKey) return { ok: false as const, status: 500, message: "TYPESAFE_API_KEY is not configured." };
const requestBody = {
model: "jev-latest",
state: { text: data.text },
questions: QUESTIONS,
};
let response: Response | undefined;
for (let attempt = 0; attempt < 3; attempt += 1) {
response = await fetch("https://api.typesafe.ai/v1/systemone", {
method: "POST",
headers: { Authorization: `Bearer ${apiKey}`, "Content-Type": "application/json" },
body: JSON.stringify(requestBody),
});
if (response.ok || (response.status !== 429 && response.status < 500)) break;
if (attempt < 2) await new Promise((resolve) => setTimeout(resolve, 750 * 2 ** attempt));
}
if (!response) return { ok: false as const, status: 503, message: "Jev did not respond." };
if (!response.ok) {
const message = (await response.text()).slice(0, 500) || `Jev request failed (${response.status}).`;
return { ok: false as const, status: response.status, message };
}
const result = await response.json();
return { ok: true as const, answers: result.answers };
});
```
In the page component, call `decide` with `useServerFn`, preserve the participant's input while loading or
on error, disable duplicate submissions, and render the returned typed values rather than parsing prose.
QUESTIONS (start here, refine wording if needed)
{
"rights_route": {
"type": "choice",
"instructions": "Which rights-check path best fits this image and publication plan?",
"criteria": {
"photographer": "Photographer ownership or license needs confirmation",
"subject": "Subject consent or release needs confirmation",
"archive": "Agency, archive, or third-party license needs confirmation",
"editorial_exception": "A documented editorial-use basis needs review"
}
},
"records_completeness": {
"type": "score",
"instructions": "How complete are the records relevant to this rights path?",
"criteria": [
"1: Missing essential records",
"2: Several material details are unclear",
"3: Mostly complete with a minor gap",
"4: Complete and consistent for the planned use"
]
},
"permission_missing": {
"type": "noul",
"instructions": "For this route, is required written permission missing from the supplied records?",
"criteria": {
"true": "A required permission is absent or cannot be confirmed",
"false": "The supplied records show required permission"
}
}
}
DECISION RULES (in code, not in the model)
- choice/score: if confidence < 0.6 show a "needs review" badge instead of acting.
- noul: >= 0.75 = yes, <= 0.25 = no, otherwise "review".
- score: normalise with score / (levels - 1) before combining with weights.
- Missing or malformed answers go to review. Show safe HTTP status and message in the UI. Retry only 429/5xx,
at most twice with increasing delay; never retry 400/401/402/403/404 and never invent results.
- If the product needs prose (a summary, a message), use Lovable AI for that text only; Jev makes the decisions.
UI
a paste box that shows the chosen option, the full probability bar chart, and a 'needs review' badge when confidence is low. Include 2 sample inputs as one-click chips so the demo works instantly.
Tailwind + shadcn, editorial look, footer: "Built during the Creative AI & Quantum Hackathon organised by StreetKode Fam during Indian Krump Festival 14".
NO database, NO auth, NO extra pages, NO tests.
BEFORE YOU FINISH
- Run the app and test both sample inputs through the real server function.
- Confirm the browser receives no API key and no fabricated fallback result.
- Confirm Choice/Score confidence and Noul probability drive the stated review rules.
- Confirm loading, success, review, empty-input, and service-error states are readable on mobile.
Reference only if needed: https://docs.typesafe.ai/api and https://docs.typesafe.ai/primitives
Market sizing.
Indicative figures for hackathon pitches — refine with your own research before raising.