OpenAI Decisions API

import json
import os
import requests

payload = json.loads(r'''{
  "model": "gpt-6-luna",
  "input": "CSV export fails on every attempt. The customer needs the file today and asks for a human agent.",
  "questions": [
    {
      "type": "choice",
      "name": "team",
      "instructions": "Which team should handle this ticket?",
      "choices": [
        {
          "value": "engineering",
          "description": "Software defects"
        },
        {
          "value": "billing",
          "description": "Payments and refunds"
        }
      ]
    },
    {
      "type": "score",
      "name": "urgency",
      "instructions": "How soon does the customer need help?",
      "levels": [
        {
          "label": "No deadline",
          "description": "No deadline is specified."
        },
        {
          "label": "This week",
          "description": "Help is needed within a week."
        },
        {
          "label": "Today",
          "description": "Help is explicitly required today."
        }
      ]
    },
    {
      "type": "predicate",
      "name": "needs_human",
      "instructions": "Does the customer request a human agent?"
    }
  ]
}''')
response = requests.post(
    "https://api.mixroute.ai/v1/decisions",
    headers={"Authorization": "Bearer " + os.environ["MIXROUTE_API_KEY"]},
    json=payload,
    timeout=60,
    allow_redirects=False,
)
response.raise_for_status()
result = response.json()
if not isinstance(result.get("answers"), list):
    raise ValueError("Expected an answers array")
for answer in result["answers"]:
    kind = answer["type"]
    if kind == "refusal":
        print(answer.get("name"), "refused")
        continue
    field = {"predicate": "probability", "choice": "choice", "score": "score"}.get(kind)
    if field is None:
        raise ValueError("Unexpected answer type: " + kind)
    print(answer.get("name"), answer[field])

const apiKey = process.env.MIXROUTE_API_KEY;
if (!apiKey) throw new Error("Set MIXROUTE_API_KEY");
const payload = {
  "model": "gpt-6-luna",
  "input": "CSV export fails on every attempt. The customer needs the file today and asks for a human agent.",
  "questions": [
    {
      "type": "choice",
      "name": "team",
      "instructions": "Which team should handle this ticket?",
      "choices": [
        {
          "value": "engineering",
          "description": "Software defects"
        },
        {
          "value": "billing",
          "description": "Payments and refunds"
        }
      ]
    },
    {
      "type": "score",
      "name": "urgency",
      "instructions": "How soon does the customer need help?",
      "levels": [
        {
          "label": "No deadline",
          "description": "No deadline is specified."
        },
        {
          "label": "This week",
          "description": "Help is needed within a week."
        },
        {
          "label": "Today",
          "description": "Help is explicitly required today."
        }
      ]
    },
    {
      "type": "predicate",
      "name": "needs_human",
      "instructions": "Does the customer request a human agent?"
    }
  ]
};
const response = await fetch("https://api.mixroute.ai/v1/decisions", {
  method: "POST",
  headers: {
    Authorization: "Bearer " + apiKey,
    "Content-Type": "application/json",
  },
  body: JSON.stringify(payload),
  signal: AbortSignal.timeout(60000),
  redirect: "error",
});
const result = await response.json();
if (!response.ok) {
  throw new Error(result.error?.message ?? "HTTP " + response.status);
}
if (!Array.isArray(result.answers)) throw new Error("Expected an answers array");
for (const answer of result.answers) {
  if (answer.type === "refusal") {
    console.log(answer.name, "refused");
    continue;
  }
  const field = { predicate: "probability", choice: "choice", score: "score" }[answer.type];
  if (!field) throw new Error("Unexpected answer type: " + answer.type);
  console.log(answer.name, answer[field]);
}