Jev vs OpenAI Decision API (Luna): Typed Decisions Compared

import os
import requests

# Public beta since 2026-10-06: question types are predicate /
# choice / score (predicate = Jev's Noul), $0.10 per 1M input
# tokens, output free. Field shapes below are the announced shape -
# verify against the current guide before shipping; beta APIs move.
resp = requests.post(
    "https://api.openai.com/v1/decisions",
    headers={"Authorization": f"Bearer {os.environ['OPENAI_API_KEY']}"},
    json={
        "model": "gpt-6-luna",
        "context": "Ticket: my invoice shows the same charge twice...",
        "question": "Which queue should this ticket go to?",
        "answers": ["billing", "technical", "sales", "abuse"],
    },
    timeout=5,
)
resp.raise_for_status()
decision = resp.json()  # -> {"answer": "billing", "confidence": 0.91}

# Images (when you need them): inline base64 data URLs only -
# hosted image URLs and file IDs are not supported in the beta.

import requests

JEV_ENDPOINT = "https://api.typesafe.ai/v1/systemone"
AUTO_ROUTE_CONFIDENCE = 0.85

QUESTIONS = {
    "routing": {
        "type": "choice",
        "instructions": "Which queue should this ticket go to?",
        "criteria": {
            "billing": "Payment, invoice or refund issue",
            "technical": "Product malfunction or bug",
            "sales": "Buying or upgrade question",
            "abuse": "Safety or abuse report",
        },
    },
    "needs_safety_escalation": {
        "type": "noul",
        "instructions": "Does this ticket require a safety escalation regardless of queue?",
    },
    "urgency": {
        "type": "score",
        "instructions": "Rate how urgent a human reply is, 1 (routine) to 5 (business-stopping)",
    },
}

resp = requests.post(
    JEV_ENDPOINT,
    json={"state": {"ticket": "..."}, "questions": QUESTIONS},
    timeout=5,
)
resp.raise_for_status()
data = resp.json()

route = data["answers"]["routing"]  # criteria-checked answer + calibrated confidence
if (
    route["confidence"] >= AUTO_ROUTE_CONFIDENCE
    and not data["answers"]["needs_safety_escalation"]["noul"]
):
    lane = f"auto:{route['answer']}"  # ~70-100ms, input tokens only
else:
    lane = "review"  # 0.60-0.85 band or safety flag

const resp = await fetch("https://api.openai.com/v1/decisions", {
  method: "POST",
  headers: {
    Authorization: `Bearer ${process.env.OPENAI_API_KEY}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    model: "gpt-6-luna",
    context: "Ticket: my invoice shows the same charge twice...",
    question: "Which queue should this ticket go to?",
    answers: ["billing", "technical", "sales", "abuse"],
  }),
});
// Public beta since 2026-10-06 (predicate / choice / score; $0.10 per
// 1M input, output free) - verify field names against the current
// guide before shipping; beta APIs move.
const decision = (await resp.json()) as {
  answer: string;
  confidence: number;
};

const JEV_ENDPOINT = "https://api.typesafe.ai/v1/systemone";
const AUTO_ROUTE_CONFIDENCE = 0.85;

const QUESTIONS = {
  routing: {
    type: "choice",
    instructions: "Which queue should this ticket go to?",
    criteria: {
      billing: "Payment, invoice or refund issue",
      technical: "Product malfunction or bug",
      sales: "Buying or upgrade question",
      abuse: "Safety or abuse report",
    },
  },
  needs_safety_escalation: {
    type: "noul",
    instructions:
      "Does this ticket require a safety escalation regardless of queue?",
  },
  urgency: {
    type: "score",
    instructions:
      "Rate how urgent a human reply is, 1 (routine) to 5 (business-stopping)",
  },
} as const;

const resp = await fetch(JEV_ENDPOINT, {
  method: "POST",
  headers: { "Content-Type": "application/json" },
  body: JSON.stringify({ state: { ticket: "..." }, questions: QUESTIONS }),
});
const data = await resp.json();

const lane =
  data.answers.routing.confidence >= AUTO_ROUTE_CONFIDENCE &&
  !data.answers.needs_safety_escalation.noul
    ? `auto:${data.answers.routing.choice}`
    : "review";