Structured Evaluation (System One) ​

POST https://openqiao.com/api/v1/systemone

The System One endpoint evaluates a piece of state (the content to evaluate) against a set of typed questions that you define, and returns one structured answer per question. Answers map back to questions by the keys you choose.

Each question is one of three types:

• noul: a yes/no judgment; returns the probability that the answer is yes.
• choice: picks one option from a set you define; returns the chosen option and the full probability distribution.
• score: rates along a rubric you define; returns a probability-weighted value across the levels.

Request Headers ​

Authorization string * ​

Bearer Token authentication.

Content-Type string * ​

Request content type, defaults to application/json.

Request Parameters ​

model string * ​

The model ID to use, in the format <provider>/<model-name>, for example typesafe/jev-latest.

state string, object, or array * ​

The content to evaluate. It can be plain text (string) or structured data (object / array), such as a chat log, a business record, or the current state of your application.

questions object * ​

A map of typed questions. You choose each key, and the returned answers come back under the same keys. The keys are not sent to the underlying model and are not used in inference.

questions.<question-id> object * ​

A typed question object. All types share type and instructions; each type adds its own criteria.

type string * ​

The question type, one of noul, choice, or score.

instructions string, object, or array * ​

What the model should decide for this question.

criteria object or array depends on type ​

The evaluation criteria, whose shape depends on type:

• noul (optional): an object describing what a yes and a no mean via true / false.
• choice (required): an object mapping each option to its rubric description; use null when an option needs no extra detail.
• score (required): an ordered array describing the levels in order; include at least two levels.

Response ​

Returns a JSON object containing the structured answers.

model string ​

The model that performed the evaluation.

answers object ​

A map of answers, keyed by the same keys used in the request questions, with one answer per question.

answers.<question-id> object ​

The answer object whose type matches its question. choice and score answers also carry a confidence (0 to 1), derived from the answer's probability distribution.

• noul answer
  • type string — always noul.
  • noul number — the yes/no answer on a scale from 0 (no) to 1 (yes).
• choice answer
  • type string — always choice.
  • choice string — the highest-probability option.
  • probabilities object — every option mapped to its probability (floats that sum to 1).
  • confidence number — how certain the model is, derived from the probabilities.
• score answer
  • type string — always score.
  • score number — the probability-weighted value across the levels; can land between levels.
  • legend object — each level number mapped back to its description.
  • probabilities object — each level (string key) mapped to its probability (floats that sum to 1).
  • confidence number — how certain the model is, derived from the probabilities.

usage object ​

Token usage for this request.

• input_tokens integer — the number of tokens consumed by the input.
• output_tokens integer — the number of tokens consumed by the output.

curl https://openqiao.com/api/v1/systemone \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $OPENQIAO_API_KEY" \
  -d '{
    "model": "typesafe/jev-latest",
    "state": "Help! My payouts have been failing for 3 days.",
    "questions": {
      "is_urgent": {
        "type": "noul",
        "instructions": "Does this convey urgency?"
      },
      "department": {
        "type": "choice",
        "instructions": "Which team should handle this?",
        "criteria": {
          "billing": "Payments, invoicing, refunds",
          "technical": "Bugs, outages, integrations",
          "sales": "Pricing, upgrades, new accounts"
        }
      },
      "frustration": {
        "type": "score",
        "instructions": "How frustrated is the customer?",
        "criteria": ["Calm", "Frustrated", "Very angry"]
      }
    }
  }'

import requests

resp = requests.post(
    "https://openqiao.com/api/v1/systemone",
    headers={
        "Authorization": "Bearer <your_OPENQIAO_API_KEY>",
        "Content-Type": "application/json",
    },
    json={
        "model": "typesafe/jev-latest",
        "state": "Help! My payouts have been failing for 3 days.",
        "questions": {
            "is_urgent": {
                "type": "noul",
                "instructions": "Does this convey urgency?",
            },
            "department": {
                "type": "choice",
                "instructions": "Which team should handle this?",
                "criteria": {
                    "billing": "Payments, invoicing, refunds",
                    "technical": "Bugs, outages, integrations",
                    "sales": "Pricing, upgrades, new accounts",
                },
            },
            "frustration": {
                "type": "score",
                "instructions": "How frustrated is the customer?",
                "criteria": ["Calm", "Frustrated", "Very angry"],
            },
        },
    },
)

print(resp.json())

const resp = await fetch("https://openqiao.com/api/v1/systemone", {
  method: "POST",
  headers: {
    Authorization: "Bearer <OPENQIAO_API_KEY>",
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    model: "typesafe/jev-latest",
    state: "Help! My payouts have been failing for 3 days.",
    questions: {
      is_urgent: {
        type: "noul",
        instructions: "Does this convey urgency?",
      },
      department: {
        type: "choice",
        instructions: "Which team should handle this?",
        criteria: {
          billing: "Payments, invoicing, refunds",
          technical: "Bugs, outages, integrations",
          sales: "Pricing, upgrades, new accounts",
        },
      },
      frustration: {
        type: "score",
        instructions: "How frustrated is the customer?",
        criteria: ["Calm", "Frustrated", "Very angry"],
      },
    },
  }),
});

console.log(await resp.json());

{
  "model": "typesafe/jev-latest",
  "answers": {
    "is_urgent": {
      "type": "noul",
      "noul": 0.92
    },
    "department": {
      "type": "choice",
      "choice": "technical",
      "probabilities": { "billing": 0.08, "technical": 0.85, "sales": 0.07 },
      "confidence": 0.82
    },
    "frustration": {
      "type": "score",
      "score": 1.6,
      "legend": { "0": "Calm", "1": "Frustrated", "2": "Very angry" },
      "probabilities": { "0": 0.05, "1": 0.3, "2": 0.65 },
      "confidence": 0.78
    }
  },
  "usage": { "input_tokens": 312, "output_tokens": 48 }
}