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.
state (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 for formats and best practices.
model (string, required)
The model that handles the request. Use "jev-latest", TypeSafe's flagship model. See Models for the available models and aliases.
questions (map<string, Question>, required)
A map of typed Question objects. You choose each key; answers come back under the same keys.
map entries
‹question id› (Question)
A key you choose. The matching Answer is returned under this same id. The key is not sent to the underlying model and is not used in inference.
{
"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.
type ("noul", required)
instructions (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.
criteria (object)
Optional descriptions of what a yes and a no mean.
properties
true (string | object | array)
What a yes (value near 1) means.
false (string | object | array)
What a no (value near 0) means.
{
"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.
type ("choice", required)
instructions (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.
criteria (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.
map entries
‹option› (string | object | array | null)
A key you choose. A description of this option.
{
"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.
type ("score", required)
instructions (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.
criteria (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.
{
"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.
model (string, required)
The model that performed the evaluation.
answers (map<string, Answer>, required)
One Answer per question, keyed by the same ids you used in questions.
map entries
‹question id› (Answer)
The same id you chose in questions.
usage (object, required)
Token usage for the request.
properties
input_tokens (integer)
output_tokens (integer)
{
"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¶
type ("noul", required)
noul (number, required)
The yes/no answer on a scale from 0 (no) to 1 (yes).
{
"model": "jev-1.13.0",
"answers": {
"is_urgent": {
"type": "noul",
"noul": 0.95
}
},
"usage": { "input_tokens": 307, "output_tokens": 20 }
}
Choice answer¶
type ("choice", required)
choice (string, required)
The highest-probability option.
probabilities (map<string, number>, required)
Every option mapped to its probability (floats that sum to 1).
map entries
‹option› (number)
An option you defined in criteria.
confidence (number, required)
How certain the model is, derived from probabilities.
{
"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¶
type ("score", required)
score (number, required)
The probability-weighted answer across the levels; can land between levels.
legend (map<string, string>, required)
Each level number mapped back to its description.
probabilities (map<string, number>, required)
Each level (string key) mapped to its probability (floats that sum to 1).
map entries
‹level› (number)
A level index, as a string key matching legend.
confidence (number, required)
How certain the model is, derived from probabilities.
{
"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.