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Python SDK question types (Noul, Choice, Score)

[ reference ][ updated 2026-09-17 ][ confidence high ][ jev-1.13.0 ][ python sdk 0.6.0 ]#python · sdk · questions · noul · choice · score

TL;DR Build questions either as objects (Noul, Choice, Score — all keyword-only) or as plain dicts with a "type" key (NoulModel, ChoiceModel, ScoreModel); you may mix both in one questions mapping. Choice.criteria is a Mapping[str, JSONContent | None] of labels; since 0.6.0 Score.criteria is an ordered Sequence[JSONContent], one entry per score starting at 0, not an int-keyed dict. instructions is optional everywhere.

The questions argument

system_one(state, questions, ...) takes questions: Mapping[str, Question], where the keys are names you choose — the same names come back on the answers. The mapping must be nonempty.

Question: TypeAlias = Noul | Choice | Score | QuestionModel
QuestionModel: TypeAlias = NoulModel | ChoiceModel | ScoreModel
Questions: TypeAlias = Mapping[str, Question]

Questions is exported for annotating your own helpers:

from typesafe_sdk import Choice, Questions, Score

QUESTIONS: Questions = {
    "tone": Choice(instructions="What is the tone?", criteria={"calm": None, "angry": None}),
    "urgency": Score(instructions="How urgent?", criteria=["low", "medium", "high"]),
}

state and the JSON content types

state is the text or JSON object the questions are asked about. It cannot be None, but values inside an object may be None.

Alias Definition
JSONValue str | int | float | bool | Sequence["JSONValue | None"] | Mapping[str, "JSONValue | None"]
JSONContent str | Mapping[str, JSONValue | None] | Sequence[JSONValue | None]

JSONContent is what state, instructions, and every criterion description accept: a plain string, a JSON object, or an array. The abstract Mapping/Sequence (rather than dict/list) annotations landed in 0.6.0. See State: what you send Jev for what to put in state.

Question objects

All three are msgspec Struct subclasses of the generated wire structs, declared kw_only=True, omit_defaults=True — so you must use keyword arguments, and fields left at their default are omitted from the JSON body. Each carries the wire type tag automatically (tag_field="type"), so you never set type on an object.

Noul

class Noul(wire.NoulQuestion, kw_only=True, omit_defaults=True)
Field Type Required Default Description
instructions JSONContent | None no None The question to ask, as text, a JSON object, or an array.
criteria NoulCriteria | None no None Optional descriptions of the yes and no outcomes.

NoulCriteria is a TypedDict(total=False, extra_items=JSONValue | None) — both keys optional, extra keys allowed:

Key Type Required Description
true JSONContent | None no Description of the yes outcome; None leaves it undescribed.
false JSONContent | None no Description of the no outcome; None leaves it undescribed.

Naming collision to be aware of: the public typesafe_sdk.NoulCriteria is the TypedDict in _core/question_types.py. A different NoulCriteria msgspec Struct exists in the generated _schemas/models.py; it is private and not exported.

from typesafe_sdk import Noul

Noul(
    instructions="Is this ticket about billing?",
    criteria={
        "true": "The customer mentions a charge, invoice, refund or subscription",
        "false": "Anything else",
    },
)

Choice

class Choice(wire.ChoiceQuestion, kw_only=True, omit_defaults=True)
Field Type Required Default Description
criteria Mapping[str, JSONContent | None] yes Labels mapped to text/object/array descriptions, or None for an undescribed label.
instructions JSONContent | None no None The question to ask.

The mapping keys are the labels the model may return in ChoiceAnswer.choice.

from typesafe_sdk import Choice

Choice(
    instructions="What is the customer's tone?",
    criteria={"calm": None, "frustrated": None, "angry": None},
)

Choice(
    instructions="Route this ticket",
    criteria={
        "billing": "Charges, invoices, refunds, subscriptions",
        "technical": {"includes": ["errors", "outages", "integration bugs"]},
        "other": None,
    },
)

Score

class Score(wire.ScoreQuestion, kw_only=True, omit_defaults=True)
Field Type Required Default Description
criteria Sequence[JSONContent] yes A nonempty, ordered list of descriptions, one per score starting from zero.
instructions JSONContent | None no None The question to ask.

Index i of the sequence describes score i. Entries may not be None (the element type is JSONContent, not JSONContent | None) — unlike Choice.criteria values.

from typesafe_sdk import Score

Score(
    instructions="How urgent is this ticket?",
    criteria=["can wait", "this week", "today"],  # 0, 1, 2
)

Question dictionaries

Any question may be a plain dictionary carrying a "type" key: "noul", "choice", or "score". Dictionaries and objects mix freely in the same questions mapping. Use dictionaries when you need a field a given SDK version does not model yet — all three TypedDicts are declared extra_items=JSONValue | None, so extra keys type-check and are sent through.

Object Dict equivalent Required keys Optional keys
Noul(...) NoulModel type: Literal["noul"] instructions (NotRequired[JSONContent | None]), criteria (NotRequired[NoulCriteria | None])
Choice(...) ChoiceModel type: Literal["choice"], criteria: Mapping[str, JSONContent | None] instructions (NotRequired[JSONContent | None])
Score(...) ScoreModel type: Literal["score"], criteria: Sequence[JSONContent] instructions (NotRequired[JSONContent | None])

Side-by-side:

from typesafe_sdk import Choice, Noul, Score, TypeSafeClient

objects = {
    "billing": Noul(instructions="Is this about billing?"),
    "tone": Choice(instructions="What is the tone?", criteria={"calm": None, "angry": None}),
    "urgency": Score(instructions="How urgent?", criteria=["low", "medium", "high"]),
}

dicts = {
    "billing": {"type": "noul", "instructions": "Is this about billing?"},
    "tone": {
        "type": "choice",
        "instructions": "What is the tone?",
        "criteria": {"calm": None, "angry": None},
    },
    "urgency": {
        "type": "score",
        "instructions": "How urgent?",
        "criteria": ["low", "medium", "high"],
    },
}

with TypeSafeClient() as client:
    a = client.system_one("I was charged twice. Please help.", objects)
    b = client.system_one("I was charged twice. Please help.", dicts)
    assert a.choices["tone"].choice in {"calm", "angry"}
    assert b.choices["tone"].choice in {"calm", "angry"}

Forward-compatible extra field on a dict question:

with TypeSafeClient() as client:
    client.system_one(
        "I was charged twice.",
        {"billing": {"type": "noul", "instructions": "About billing?", "weight": 2}},
    )

Client-side validation

_core/questions.py:normalize_questions runs before encoding and raises TypeSafeError (no HTTP request is made):

Condition Message
questions is empty At least one question is required.
A Score object with empty criteria Score question "<name>" has no criteria; at least one score is required.
A dict question that is not a dict, or whose "type" is missing / not a str / empty Question "<name>" must be a question object or a dictionary with a nonempty string "type".
A dict with type "choice" or "score" and no "criteria" key Question "<name>" requires "criteria".
A dict with type == "score" and empty "criteria" Score question "<name>" has no criteria; at least one score is required.

Gotchas that validation does not catch (verified against normalize_questions):

0.6.0 breaking change: Score.criteria

Release 0.6.0 (2026-09-15) changed Score.criteria to accept an ordered sequence instead of a dictionary keyed by integers.

Version Score.criteria form
≤ 0.5.7 dictionary keyed by integer score
0.6.0 ordered Sequence[JSONContent], index = score, starting at 0
# 0.6.0 and later — correct
Score(instructions="How urgent?", criteria=["can wait", "this week", "today"])

# pre-0.6.0 form — no longer the documented shape
# Score(instructions="How urgent?", criteria={0: "can wait", 1: "this week", 2: "today"})

Note the asymmetry that survives the change: the question criteria is a sequence, but the answer ScoreAnswer.legend and ScoreAnswer.probabilities are still keyed by integer score (dict[int, ...]). See Python SDK responses, answers, usage, models.

A tuple works anywhere a list does, since the annotation is Sequence:

LEVELS = ("can wait", "this week", "today")
Score(instructions="How urgent?", criteria=LEVELS)

Typing and generics

Related

Sources