tooluse1/grade.py

"""Grading: canonical argument comparison and per-case verdicts."""

from __future__ import annotations

import math
import re
from dataclasses import dataclass
from typing import Any, Mapping, Sequence

from .parse import answer_text, parse_output
from .schema import Case, CaseResult, ExpectCall, ExpectNoCall, Protocol
from .tools import REGISTRY, canonical_name


@dataclass(frozen=True)
class ArgMatch:
    ok: bool
    missing: tuple[str, ...] = ()
    mismatched: tuple[str, ...] = ()
    extra: tuple[str, ...] = ()

    def describe(self) -> str:
        parts = []
        if self.missing:
            parts.append("missing=" + ",".join(self.missing))
        if self.mismatched:
            parts.append("mismatched=" + ",".join(self.mismatched))
        if self.extra:
            parts.append("extra=" + ",".join(self.extra))
        return "; ".join(parts)


def _normalize(tool: str, key: str, value: Any) -> Any:
    spec = REGISTRY.get(canonical_name(tool))
    if spec is None:
        return re.sub(r"\s+", " ", str(value)).strip().lower()
    normalizer = spec.normalizers.get(key)
    if normalizer is None:
        return re.sub(r"\s+", " ", str(value)).strip().lower()
    return normalizer(value)


def _equal(left: Any, right: Any) -> bool:
    if isinstance(left, float) and isinstance(right, float):
        return math.isclose(left, right, rel_tol=1e-6, abs_tol=1e-6)
    if isinstance(left, (int, float)) and isinstance(right, (int, float)):
        return math.isclose(float(left), float(right), rel_tol=1e-6, abs_tol=1e-6)
    if isinstance(left, list) and isinstance(right, list):
        return len(left) == len(right) and all(_equal(a, b) for a, b in zip(left, right))
    if isinstance(left, Mapping) and isinstance(right, Mapping):
        return set(left) == set(right) and all(_equal(left[k], right[k]) for k in left)
    return left == right


def match_args(tool: str, expected: Mapping[str, Any], predicted: Mapping[str, Any]) -> ArgMatch:
    missing: list[str] = []
    mismatched: list[str] = []
    for key, value in expected.items():
        if key not in predicted:
            missing.append(key)
            continue
        try:
            left = _normalize(tool, key, value)
            right = _normalize(tool, key, predicted[key])
        except Exception:
            left, right = value, predicted[key]
        if not _equal(left, right):
            mismatched.append(key)
    spec = REGISTRY.get(canonical_name(tool))
    allowed = set(spec.parameters) if spec else set(expected)
    extra = tuple(sorted(key for key in predicted if key not in expected and key not in allowed))
    optional_extra = tuple(sorted(key for key in predicted if key not in expected and key in allowed))
    return ArgMatch(
        ok=not missing and not mismatched,
        missing=tuple(missing),
        mismatched=tuple(mismatched),
        extra=extra + optional_extra,
    )


def _answer_matches(expect: ExpectNoCall, text: str) -> bool | None:
    if not expect.answer_contains_any and not expect.answer_contains_all:
        return None
    haystack = text.lower()
    if expect.answer_contains_all and not all(needle.lower() in haystack for needle in expect.answer_contains_all):
        return False
    if expect.answer_contains_any:
        return any(any(needle.lower() in haystack for needle in group) for group in expect.answer_contains_any)
    return True


def grade_case(case: Case, protocol: Protocol, raw_output: str) -> CaseResult:
    parsed = parse_output(raw_output)
    calls = parsed.calls
    called = bool(calls)
    text = answer_text(raw_output)

    base = dict(
        case_id=case.id,
        protocol=protocol,
        lang=case.lang,
        category=case.category,
        difficulty=case.difficulty,
        malformed=parsed.malformed,
        output=raw_output,
    )

    if isinstance(case.expect, ExpectCall):
        if len(calls) != 1:
            detail = "no call emitted" if not calls else f"{len(calls)} calls emitted (expected 1)"
            return CaseResult(passed=False, called=called, expected_call=True, name_correct=False, args_exact=False, answer_ok=None, detail=detail, **base)
        call = calls[0]
        name_correct = call.name == canonical_name(case.expect.name)
        args = match_args(case.expect.name, case.expect.args, call.args) if name_correct else ArgMatch(ok=False, mismatched=("name",))
        detail = "" if (name_correct and args.ok) else f"predicted={call.canonical()}" + (f" ({args.describe()})" if args.describe() else "")
        return CaseResult(
            passed=bool(name_correct and args.ok),
            called=True,
            expected_call=True,
            name_correct=name_correct,
            args_exact=args.ok,
            answer_ok=None,
            detail=detail,
            **base,
        )

    answer_ok = _answer_matches(case.expect, text)
    passed = not calls and answer_ok is not False
    detail = ""
    if calls:
        detail = "spurious call: " + "; ".join(c.canonical() for c in calls)
    elif answer_ok is False:
        detail = "answer failed constraint: " + text[:160]
    return CaseResult(
        passed=passed,
        called=called,
        expected_call=False,
        name_correct=not calls,
        args_exact=not calls,
        answer_ok=answer_ok,
        detail=detail,
        **base,
    )


def wilson_interval(successes: int, total: int, z: float = 1.96) -> tuple[float, float]:
    if total == 0:
        return (0.0, 0.0)
    phat = successes / total
    denominator = 1 + z * z / total
    center = (phat + z * z / (2 * total)) / denominator
    spread = z * math.sqrt(phat * (1 - phat) / total + z * z / (4 * total * total)) / denominator
    return (max(0.0, center - spread), min(1.0, center + spread))


def rate(numerator: int, denominator: int) -> float:
    return round(numerator / denominator, 4) if denominator else 0.0


def _group_summary(results: Sequence[CaseResult]) -> dict[str, Any]:
    positives = [r for r in results if r.expected_call]
    negatives = [r for r in results if not r.expected_call]
    answered = [r for r in negatives if r.answer_ok is not None]
    lo, hi = wilson_interval(sum(1 for r in results if r.passed), len(results))
    return {
        "cases": len(results),
        "score": rate(sum(1 for r in results if r.passed), len(results)),
        "score_ci95": [round(lo, 4), round(hi, 4)],
        "correct_call_when_expected": rate(sum(1 for r in positives if r.passed), len(positives)),
        "correct_abstention": rate(sum(1 for r in negatives if r.passed), len(negatives)),
        "spurious_call_rate": rate(sum(1 for r in negatives if r.called), len(negatives)),
        "name_accuracy": rate(sum(1 for r in positives if r.name_correct), len(positives)),
        "args_accuracy": rate(sum(1 for r in positives if r.args_exact), len(positives)),
        "answer_constraint_accuracy": rate(sum(1 for r in answered if r.answer_ok), len(answered)),
        "malformed_rate": rate(sum(1 for r in results if r.malformed), len(results)),
    }


def summarize(results: Sequence[CaseResult], model_id: str = "", protocol: Protocol | None = None) -> dict[str, Any]:
    def slice_by(key: str) -> dict[str, Any]:
        values: dict[str, list[CaseResult]] = {}
        for result in results:
            values.setdefault(getattr(result, key), []).append(result)
        return {name: _group_summary(group) for name, group in sorted(values.items())}

    return {
        "benchmark": "ToolUse.1",
        "model": model_id,
        "protocol": protocol or "all",
        "n_cases": len(results),
        "overall": _group_summary(results),
        "by_protocol": slice_by("protocol"),
        "by_language": slice_by("lang"),
        "by_category": slice_by("category"),
        "by_difficulty": slice_by("difficulty"),
    }