Documentation Index

Fetch the complete documentation index at: https://docs.typesafe.ai/llms.txt Use this file to discover all available pages before exploring further.

API reference

Full HTTP API reference for the TypeSafe evaluation endpoint.

Evaluate a state against a map of typed questions and get back structured answers, one per question. For a guided introduction, start with the primitives.

Evaluation endpoint

POST https://api.typesafe.ai/v1/systemone
Authorization: Bearer <API_KEY>
Content-Type: application/json

Request body

The top-level shape of every request. Each entry in the questions map is a typed question you name.

<ParamField body="state" type="string | object | array" required> The content to evaluate. A plain string for text, or structured data (object/array) for things like chat logs, records, or the current state of your application. See [State](/concepts/state) for formats and best practices. </ParamField>

<ParamField body="model" type="string" required> The model that handles the request. Use `"jev-latest"`, TypeSafe's flagship model. See [Models](/models) for the available models and aliases. </ParamField>

<ParamField body="questions" type="map<string, Question>" required> A map of typed [Question](#question-types) objects. You choose each key; answers come back under the same keys.

<Expandable title="map entries"> <ParamField body="‹question id›" type="Question"> A key you choose. The matching [Answer](#answer-types) is returned under this same id. The key is not sent to the underlying model and is not used in inference. </ParamField> </Expandable> </ParamField>

{
  "state": "Help! My payouts have been failing for 3 days.",
  "model": "jev-latest",
  "questions": {
    "is_urgent": {
      "type": "noul",
      "instructions": "Does this convey urgency?"
    }
  }
}

Question types

A Question is one of three types, set by its type field. All three share type and instructions; each adds its own criteria.

The instructions property can be a string, an object, or an array. You can break up a long question that has extra context, or data it needs to reference, into a structured object. Put the question in one field and the data in the others, and refer to the data fields by name in backticks, the same way you point a question at a nested state value:

"instructions": {
  "potential_duplicate": {
    "name": "John Smith",
    "location": "Oakland, California",
    "last_employer": "Google"
  },
  "question": "Is the resume for the same person as `potential_duplicate`?"
}

See Use structure in the questions to learn more.

Noul

A yes/no question. Returns the probability the answer is yes.

<ParamField body="instructions" type="string | object | array" required> The yes/no question to evaluate. An object can hold the question in one field and data it refers to in others; see [Use structure in the questions](/concepts/how-to-build-with-system-one#use-structure-in-the-questions). </ParamField>

<ParamField body="criteria" type="object"> Optional descriptions of what a yes and a no mean.

<Expandable title="properties"> <ParamField body="true" type="string | object | array"> What a yes (value near 1) means. </ParamField>

<ParamField body="false" type="string | object | array"> What a no (value near 0) means. </ParamField> </Expandable> </ParamField>

{
  "state": "Help! My payouts have been failing for 3 days.",
  "model": "jev-latest",
  "questions": {
    "is_urgent": {
      "type": "noul",
      "instructions": "Does this convey urgency?",
      "criteria": {
        "true": "Explicitly time-sensitive",
        "false": "No urgency expressed"
      }
    }
  }
}

Choice

Picks one option from a set you define. Returns the chosen option and the full probability distribution.

<ParamField body="instructions" type="string | object | array" required> What the model should decide. An object can hold the question in one field and data it refers to in others; see [Structured instructions and criteria](/primitives/choice#structured-instructions-and-criteria). </ParamField>

<ParamField body="criteria" type="map<string, string | object | array | null>" required> A map of option to rubric description; use null when an option needs no extra detail. You can have a maximum of 255 options per Choice.

<Expandable title="map entries"> <ParamField body="‹option›" type="string | object | array | null"> A key you choose. A description of this option. </ParamField> </Expandable> </ParamField>

{
  "state": "Help! My payouts have been failing for 3 days.",
  "model": "jev-latest",
  "questions": {
    "department": {
      "type": "choice",
      "instructions": "Which team should handle this?",
      "criteria": {
        "billing": "Payments, invoicing, refunds",
        "technical": "Bugs, outages, integrations",
        "sales": "Pricing, upgrades, new accounts"
      }
    }
  }
}

Score

Rates the state along a rubric you define. Returns a probability-weighted value across your levels.

<ParamField body="instructions" type="string | object | array" required> What the model should rate. An object can hold the question in one field and data it refers to in others; see [Use structure in the questions](/concepts/how-to-build-with-system-one#use-structure-in-the-questions). </ParamField>

<ParamField body="criteria" type="array<string | object | array>" required> An ordered array of level descriptions. A Score should have at least two levels; the API accepts up to 10. </ParamField>

{
  "state": "Help! My payouts have been failing for 3 days.",
  "model": "jev-latest",
  "questions": {
    "frustration": {
      "type": "score",
      "instructions": "How frustrated is the customer?",
      "criteria": ["Calm", "Frustrated", "Very angry"]
    }
  }
}

Response body

One answer per question, returned under the same ids you provided.

<ResponseField name="model" type="string" required> The model that performed the evaluation. </ResponseField>

<ResponseField name="answers" type="map<string, Answer>" required> One [Answer](#answer-types) per question, keyed by the same ids you used in questions.

<Expandable title="map entries"> <ResponseField name="‹question id›" type="Answer"> The same id you chose in questions. </ResponseField> </Expandable> </ResponseField>

<ResponseField name="usage" type="object" required> Token usage for the request.

{
  "model": "jev-1.13.0",
  "answers": {
    "is_urgent": {
      "type": "noul",
      "noul": 0.95
    }
  },
  "usage": { "input_tokens": 296, "output_tokens": 20 }
}

Answer types

Every answer carries a type matching its question. Choice and Score answers also carry a confidence between 0 to 1, derived from the answer's probability distribution. See Confidence.

Noul answer

<ResponseField name="noul" type="number" required> The yes/no answer on a scale from 0 (no) to 1 (yes). </ResponseField>

{
  "model": "jev-1.13.0",
  "answers": {
    "is_urgent": {
      "type": "noul",
      "noul": 0.95
    }
  },
  "usage": { "input_tokens": 307, "output_tokens": 20 }
}

Choice answer

<ResponseField name="choice" type="string" required> The highest-probability option. </ResponseField>

<ResponseField name="probabilities" type="map<string, number>" required> Every option mapped to its probability (floats that sum to 1).

<Expandable title="map entries"> <ResponseField name="‹option›" type="number"> An option you defined in criteria. </ResponseField> </Expandable> </ResponseField>

<ResponseField name="confidence" type="number" required> How certain the model is, derived from probabilities. </ResponseField>

{
  "model": "jev-1.13.0",
  "answers": {
    "department": {
      "type": "choice",
      "choice": "billing",
      "probabilities": { "billing": 0.88, "technical": 0.12, "sales": 0.0 },
      "confidence": 0.81
    }
  },
  "usage": { "input_tokens": 318, "output_tokens": 34 }
}

Score answer

<ResponseField name="score" type="number" required> The probability-weighted answer across the levels; can land between levels. </ResponseField>

<ResponseField name="legend" type="map<string, string>" required> Each level number mapped back to its description. </ResponseField>

<ResponseField name="probabilities" type="map<string, number>" required> Each level (string key) mapped to its probability (floats that sum to 1).

<Expandable title="map entries"> <ResponseField name="‹level›" type="number"> A level index, as a string key matching legend. </ResponseField> </Expandable> </ResponseField>

<ResponseField name="confidence" type="number" required> How certain the model is, derived from probabilities. </ResponseField>

{
  "model": "jev-1.13.0",
  "answers": {
    "frustration": {
      "type": "score",
      "score": 1.05,
      "legend": { "0": "Calm", "1": "Frustrated", "2": "Very angry" },
      "probabilities": { "0": 0.0, "1": 0.95, "2": 0.05 },
      "confidence": 0.92
    }
  },
  "usage": { "input_tokens": 304, "output_tokens": 18 }
}

Errors

Errors use standard HTTP status codes with a JSON body describing what went wrong.

Status	Meaning
`401 Unauthorized`	Missing or invalid API key. Check the `Authorization` header.
`422 Unprocessable Entity`	The request body failed validation — for example a missing required field or a malformed question. The body details the offending field.
`429 Too Many Requests`	You have exceeded your rate limit. Back off and retry after a short delay.
`529 Overloaded`	TypeSafe is temporarily overloaded. Retry after a short delay.

Handling rate limits

When you receive a 429 Too Many Requests or 529 Overloaded response, retry the request with exponential backoff instead of retrying immediately. Our client SDKs handle this automatically, so no extra handling is needed if you use one of our SDKs with its default retry policy.

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