System One Calibrated Decisions — POST /v1/systemone

System One is a typed decision API designed for fast, calibrated inference. Instead of generating free-form text, Jev models take a state — the context to reason about — and a map of structured questions, then return a precise answer for each one: a probability for yes/no questions, a ranked choice with confidence for classification tasks, and a continuous score with a legend for rubric-based evaluation. Responses arrive in 70–500 ms, making System One suitable for real-time routing, triage, scoring, and moderation pipelines. An existing TypeSafe client only needs its base URL changed to https://api.piramyd.cloud/v1 — the request and response shapes are identical.

System One models can only be called via /v1/systemone. Sending a Jev model ID to /v1/chat/completions, /v1/responses, or /v1/messages returns 400. Conversely, sending a chat model to /v1/systemone also returns 400.

Endpoints

Method	Path	Purpose
`POST`	`/v1/systemone`	Submit a state and questions; receive typed answers
`GET`	`/v1/systemone/models`	List available System One model IDs

POST /v1/systemone

POST https://api.piramyd.cloud/v1/systemone

Headers

Header	Value
`Authorization`	`Bearer sk-<your-api-key>`
`Content-Type`	`application/json`

Request Parameters

string

required

The Jev model ID to use. Retrieve valid IDs from GET /v1/systemone/models — these do not appear in GET /v1/models. Examples: jev-latest, jev-1.13.0.Pin a specific version (e.g. jev-1.13.0) if you are calibrating decision thresholds on confidence scores. Using an alias like jev-latest may silently shift your thresholds when the model is updated.

string | object | array

required

The context the model should analyse when answering the questions. This may be a plain string, a structured object, or an array. Maximum 64k tokens total across the entire request; 32k for the state plus the longest single question.

object

required

A map of question_key → question definition. Each key becomes the corresponding key in the answers response. You may include any mix of question types in a single request.

Show noul question

A yes/no (boolean probability) question.

string

required

Must be "noul".

string

required

Natural-language description of what to evaluate. Example: "Does this message convey urgency?".

object

Optional rubric with keys "true" and "false", each containing a string description of what qualifies as that answer. Omit to let the model interpret the instructions directly.

Show choice question

A classification question with 1–255 named options.

string

required

Must be "choice".

string

required

Natural-language description of the classification task.

object

required

Map of option_name → rubric_string | null. Provide a rubric string to describe when that option applies, or null to let the model infer from the option name. Must contain between 1 and 255 keys.

Show score question

A rubric-based scoring question with 2–10 ordered levels.

string

required

Must be "score".

string

required

Natural-language description of what to score.

array

required

Ordered array of level descriptions, from lowest to highest. Must contain between 2 and 10 elements. The model returns a continuous score that can land between levels (e.g. 1.4 on a 3-level scale of 0–2).

Full Request Example

The following example shows a real-world customer support routing scenario using all three question types in a single request.

{
  "model": "jev-latest",
  "state": "Help! My payouts have been failing for 3 days.",
  "questions": {
    "is_urgent": {
      "type": "noul",
      "instructions": "Does this message convey urgency?"
    },
    "department": {
      "type": "choice",
      "instructions": "Which team should handle this?",
      "criteria": {
        "billing": "Payments, refunds, invoicing issues",
        "technical": "Bugs, outages, API errors",
        "sales": null
      }
    },
    "frustration": {
      "type": "score",
      "instructions": "How frustrated is the customer?",
      "criteria": ["Calm", "Frustrated", "Very angry"]
    }
  }
}

Python example

import httpx

headers = {"Authorization": "Bearer sk-YOUR_KEY"}

response = httpx.post(
    "https://api.piramyd.cloud/v1/systemone",
    headers=headers,
    json={
        "model": "jev-latest",
        "state": "Help! My payouts have been failing for 3 days.",
        "questions": {
            "is_urgent": {
                "type": "noul",
                "instructions": "Does this message convey urgency?",
            },
            "department": {
                "type": "choice",
                "instructions": "Which team should handle this?",
                "criteria": {
                    "billing": "Payments, refunds, invoicing issues",
                    "technical": "Bugs, outages, API errors",
                    "sales": None,
                },
            },
            "frustration": {
                "type": "score",
                "instructions": "How frustrated is the customer?",
                "criteria": ["Calm", "Frustrated", "Very angry"],
            },
        },
    },
    timeout=10.0,
)

data = response.json()
print(data["answers"]["is_urgent"]["noul"])        # e.g. 0.95
print(data["answers"]["department"]["choice"])     # e.g. "billing"
print(data["answers"]["frustration"]["score"])     # e.g. 1.6

Response Shape

string

The exact version of the model that answered (e.g. jev-1.13.0), even when you requested an alias like jev-latest. Use this value if you need to reproduce a result or audit a decision.

object

Map of question_key → answer. One entry per question submitted.

Show noul answer

string

"noul"

float

Calibrated probability of the answer being true, from 0.0 to 1.0. A value of 0.95 means the model is 95% confident the answer is yes.

Show choice answer

string

"choice"

string

The selected option key (the most probable option).

object

Map of every option key to its probability. Values sum to 1.0.

float

Calibrated confidence in the selected choice, from 0.0 to 1.0.

Show score answer

string

"score"

float

Continuous score that can land between level indices (e.g. 1.4 on a 3-level scale indexed 0–2).

string

Human-readable label for the score, derived from the criteria array.

object

Map of each level label to its probability.

float

Calibrated confidence in the score, from 0.0 to 1.0.

object

Token counts for this request.

Show usage fields

integer

Total input tokens (state + all questions). This is what you are billed for.

integer

Output tokens generated. Output tokens are free for System One requests.

Example response

{
  "model": "jev-1.13.0",
  "answers": {
    "is_urgent": {
      "type": "noul",
      "noul": 0.95
    },
    "department": {
      "type": "choice",
      "choice": "billing",
      "probabilities": {
        "billing": 0.88,
        "technical": 0.12,
        "sales": 0.0
      },
      "confidence": 0.81
    },
    "frustration": {
      "type": "score",
      "score": 1.6,
      "legend": "Frustrated",
      "probabilities": {
        "Calm": 0.05,
        "Frustrated": 0.65,
        "Very angry": 0.30
      },
      "confidence": 0.72
    }
  },
  "usage": {
    "input_tokens": 304,
    "output_tokens": 18
  }
}

GET /v1/systemone/models

GET https://api.piramyd.cloud/v1/systemone/models

Returns the list of available System One model IDs that can be used in POST /v1/systemone.

System One model IDs do not appear in GET /v1/models. Always use GET /v1/systemone/models to discover valid Jev model IDs.

Example response

{
  "object": "list",
  "data": [
    { "id": "jev-latest",   "type": "systemone" },
    { "id": "jev-1.13.0",  "type": "systemone" },
    { "id": "jev-1.12.0",  "type": "systemone" }
  ]
}

Limits and Errors

Token Limits

Constraint	Limit
Total request (state + all questions)	64k tokens
State + longest single question	32k tokens

If your request exceeds either limit, the API returns 413 context_too_large. There is no automatic compaction for System One — shrink your state to fit within the limits.

Error Reference

Status	Code	Meaning	Action
`413`	`context_too_large`	Request exceeds token limits	Shrink `state`
`422`	—	Invalid question definition	Fix the malformed question
`404`	`model_not_found`	Model ID not found or not accessible on your tier	Use `GET /v1/systemone/models`; see note below
`403`	—	Tier restriction	Upgrade your plan
`429`	—	Rate limit exceeded	Retry with exponential backoff; respect `Retry-After`
`503`	—	Provider unavailable	Retry after a delay

When a System One model ID is not found, the API returns 404 model_not_found and never silently substitutes a different model. Substituting would shift your calibrated probability distributions and break any decision thresholds you have tuned. Always verify the model ID with GET /v1/systemone/models before deploying a pipeline.

Feature Restrictions

System One has a deliberately constrained interface. The following features are not available:

Streaming (stream parameter is not accepted)
Tool/function calling
System prompt field
Automatic context compaction / thread_id

Billing

You are billed for input tokens only. Output tokens for System One requests are always free.

Pin the model version (e.g. jev-1.13.0) if you are calibrating decision thresholds based on confidence scores. Using an alias like jev-latest will silently shift thresholds whenever the model is updated to a new version — a different model may return different probability distributions for identical inputs.

Inference

Models

Web Intelligence

Account

System One Calibrated Decisions — POST /v1/systemone

Endpoints

POST /v1/systemone

Request Parameters

Full Request Example

Response Shape

GET /v1/systemone/models

Limits and Errors

Token Limits

Error Reference

Feature Restrictions

Billing

​Endpoints

​POST /v1/systemone

​Request Parameters

​Full Request Example

​Response Shape

​GET /v1/systemone/models

​Limits and Errors

​Token Limits

​Error Reference

​Feature Restrictions

​Billing

Endpoints

POST /v1/systemone

Request Parameters

Full Request Example

Response Shape

GET /v1/systemone/models

Limits and Errors

Token Limits

Error Reference

Feature Restrictions

Billing