File size: 2,268 Bytes
2d8be88 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 | """Pivot-Alpha / Jev-aligned typed decision schema (English).
Jev: unstructured state in → typed probabilistic decisions out.
We are NOT a free-text generator. Each call returns structured decisions
the host program can wire into a workflow.
"""
from __future__ import annotations
from typing import Any, Literal, Optional
Primitive = Literal["choice", "noul", "score"]
def build_typed_decision(
*,
decision_id: str,
primitive: Primitive,
options: list[str],
index: int,
probs: list[float],
description: Optional[str] = None,
) -> dict[str, Any]:
if len(options) != len(probs):
raise ValueError("options/probs length mismatch")
if not (0 <= index < len(options)):
raise ValueError("index out of range")
# named map for program consumption
prob_map = {str(opt): float(p) for opt, p in zip(options, probs)}
value = options[index]
out: dict[str, Any] = {
"id": decision_id,
"primitive": primitive,
"description": description,
"options": list(options),
"index": int(index),
"value": value,
"probs": prob_map,
"prob_vector": [float(p) for p in probs],
"confidence": float(max(probs) if probs else 0.0),
}
if primitive == "noul":
# binary probabilistic decision (yes-mass = prob of first true-like option if present)
true_aliases = {"true", "yes", "y", "1"}
true_idx = next((i for i, o in enumerate(options) if str(o).lower() in true_aliases), index)
out["p_true"] = float(probs[true_idx])
if primitive == "score":
# expected score if options are ordered numeric levels; else keep categorical
try:
levels = [float(o) for o in options]
out["expected"] = float(sum(l * p for l, p in zip(levels, probs)))
except ValueError:
out["expected"] = None
return out
def build_response(
*,
state: str,
decisions: list[dict[str, Any]],
model_id: str = "Pivot-Alpha",
) -> dict[str, Any]:
return {
"model": model_id,
"contract": "unstructured_state_in__typed_probabilistic_decisions_out",
"state": state,
"decisions": decisions,
"schema_version": "pivot-alpha-v1",
}
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