portfolio-optimiser/tests/test_verdicts.py

"""Step 3 tests — non-tautological top-K retrieval + REAL-SessionContext two-arg injection.

The true match shares the *structured* similarity fields with the query but uses different
description text; the decoys share surface text but differ structurally. The injection test
uses a REAL ``agent_framework.SessionContext`` (not a single-arg fake), exercising the
genuine two-arg ``extend_instructions(source_id, instructions)`` GA signature — retiring the
Critical Fase 1 risk. Pattern: tests/spikes/test_d_verdictstore.py + real SessionContext.
"""

import json
import logging
from pathlib import Path

import pytest
from agent_framework import SessionContext

from portfolio_optimiser.verdicts import (
    ExpeLContextProvider,
    ProposalFeatures,
    Verdict,
    VerdictStore,
    bundle_candidate_features,
    capture_verdict,
    load_verdicts_from_dir,
    seed_store_from_bundle,
    write_verdict,
)

_BUNDLE_DIR = Path(__file__).resolve().parents[1] / "shared" / "examples" / "bygg-energi-mikro"

_QUERY = ProposalFeatures(
    affected_codes=frozenset({"05.2", "03.1"}),
    measure_type="scope_reduction",
    claimed_saving_nok=220_000,  # bucket [100k, 500k)
    description="asphalt base course reduction near school",
)


def _store_with_true_match_and_decoys() -> tuple[VerdictStore, str]:
    true_match = Verdict(
        id="TRUE",
        proposal_features=ProposalFeatures(
            affected_codes=frozenset({"05.2", "03.1"}),  # same codes
            measure_type="scope_reduction",  # same measure type
            claimed_saving_nok=200_000,  # same magnitude bucket
            description="zzz totally unrelated wording alpha beta",  # DIFFERENT text
        ),
        decision="approved",
        rationale="prior scope reduction on the same codes was approved",
    )
    decoy_low = Verdict(
        id="DECOY-LOW",
        proposal_features=ProposalFeatures(
            affected_codes=frozenset({"09.1"}),
            measure_type="rate_renegotiation",
            claimed_saving_nok=50_000,
            description="asphalt base course reduction near school",  # same words as query
        ),
        decision="rejected",
        rationale="surface-text decoy",
    )
    decoy_high = Verdict(
        id="DECOY-HIGH",
        proposal_features=ProposalFeatures(
            affected_codes=frozenset({"21.2"}),
            measure_type="material_substitution",
            claimed_saving_nok=700_000,
            description="asphalt base course reduction extra words",
        ),
        decision="rejected",
        rationale="surface-text decoy",
    )
    return VerdictStore(verdicts=[decoy_low, true_match, decoy_high]), "TRUE"


def test_retrieve_finds_structural_match_over_text_decoys() -> None:
    store, true_id = _store_with_true_match_and_decoys()
    hits = store.retrieve(_QUERY, k=3)
    assert hits[0].id == true_id  # structural match ranks #1 despite different wording


def test_retrieve_is_deterministic() -> None:
    store, _ = _store_with_true_match_and_decoys()
    assert [h.id for h in store.retrieve(_QUERY, k=3)] == [
        h.id for h in store.retrieve(_QUERY, k=3)
    ]


def test_retrieve_rejects_non_positive_k() -> None:
    store, _ = _store_with_true_match_and_decoys()
    with pytest.raises(ValueError):
        store.retrieve(_QUERY, k=0)


def test_capture_verdict_mints_stable_id() -> None:
    a = capture_verdict(_QUERY, "approved", "ok")
    b = capture_verdict(
        ProposalFeatures(
            affected_codes=frozenset({"03.1", "05.2"}),  # same set, different order
            measure_type="scope_reduction",
            claimed_saving_nok=220_000,
            description="DIFFERENT surface wording entirely",  # text excluded from the id
        ),
        "approved",
        "ok",
    )
    assert a.id == b.id  # structurally identical -> stable id
    assert len(a.id) == 16


async def test_before_run_populates_real_sessioncontext_two_arg() -> None:
    store, true_id = _store_with_true_match_and_decoys()
    provider = ExpeLContextProvider(store, _QUERY, k=2)
    # A REAL SessionContext (not a single-arg fake) — exercises the genuine GA two-arg
    # extend_instructions(source_id, instructions) signature.
    ctx = SessionContext(input_messages=[], instructions=[])
    await provider.before_run(agent=None, session=None, context=ctx, state={})
    assert any(true_id in instr for instr in ctx.instructions)


# --- OKF-bundle seeding (Fase 2a): the pre-hypothesis ExpeL query key + the seed store ---


def test_bundle_candidate_features_keys_on_the_ir_projection() -> None:
    """The pre-hypothesis ExpeL query is the candidate measure's cost-IR features (from the
    bundle's ``validator-input.json``) — available BEFORE any proposal is generated."""
    features = bundle_candidate_features(str(_BUNDLE_DIR))
    assert features.affected_codes == frozenset({"ENERGI-TOTAL-EL"})
    assert "LED-retrofit" in features.measure_type
    assert features.claimed_saving_nok == 30000


def test_seed_store_from_bundle_carries_the_realization_signal() -> None:
    """Each ``type: verdict`` file becomes a structurally-keyed ``Verdict`` whose rationale carries
    the learning signal the validator cannot compute (the realization rate 0.82)."""
    store = seed_store_from_bundle(str(_BUNDLE_DIR))
    assert len(store.verdicts) == 1
    seed = store.verdicts[0]
    assert seed.proposal_features.affected_codes == frozenset({"ENERGI-TOTAL-EL"})
    assert "approved" in seed.decision
    assert "0.82" in seed.rationale


def test_seed_store_retrieval_matches_the_candidate() -> None:
    """A3: seed and query derive from the SAME IR -> similarity 1.0 -> the lone seed is retrieved
    for the candidate (the structural match the Step-1 wiring relies on)."""
    store = seed_store_from_bundle(str(_BUNDLE_DIR))
    query = bundle_candidate_features(str(_BUNDLE_DIR))
    hits = store.retrieve(query, k=3)
    assert len(hits) == 1
    assert "0.82" in hits[0].rationale


# --- S2.5 (Step 7): inbox herding — vocabulary SKIP + rationale-cap (skip) + file-count (fail-fast) ---


def _feats(code: str, magnitude: float = 1.0) -> ProposalFeatures:
    return ProposalFeatures(
        affected_codes=frozenset({code}), measure_type="m", claimed_saving_nok=magnitude
    )


def test_load_skips_unknown_decision_vocabulary(tmp_path) -> None:
    """T-2.5a: an inbox verdict whose decision is outside the binary run-path vocabulary
    {approved, rejected} is SKIPPED (never enters the store) — tolerant load, never raises. Detach
    the vocabulary check → the ``banana`` verdict enters the store → RED."""
    write_verdict(str(tmp_path), capture_verdict(_feats("X"), "banana", "weird decision"))
    write_verdict(str(tmp_path), capture_verdict(_feats("Y", 2.0), "approved", "fine"))

    decisions = [v.decision for v in load_verdicts_from_dir(str(tmp_path))]
    assert "banana" not in decisions
    assert "approved" in decisions


def test_load_skips_oversized_rationale_with_log(tmp_path, caplog) -> None:
    """T-2.5b: a rationale over ``max_rationale_len`` is SKIPPED and logged (caplog-observable) — a
    per-file tolerant skip, NOT a raise (contrast the file-count cap)."""
    write_verdict(str(tmp_path), capture_verdict(_feats("X"), "approved", "x" * 500))

    with caplog.at_level(logging.WARNING):
        loaded = load_verdicts_from_dir(str(tmp_path), max_rationale_len=100)

    assert loaded == []
    assert any("rationale" in r.message.lower() for r in caplog.records)


def test_load_fails_fast_over_max_files(tmp_path) -> None:
    """T-2.5c: a file count over ``max_files`` per merge is a fail-fast RAISE (aggregate guard,
    contrast the per-file tolerant skips)."""
    for i in range(3):
        write_verdict(
            str(tmp_path), capture_verdict(_feats(f"C{i}", float(i + 1)), "approved", "r")
        )

    with pytest.raises(ValueError):
        load_verdicts_from_dir(str(tmp_path), max_files=2)


def test_load_within_caps_is_unchanged(tmp_path) -> None:
    """Control: with vocabulary-valid decisions and no cap breach, the loader behaves exactly as
    before — the tolerant contract (which the Step-7 loop relies on) is intact."""
    write_verdict(str(tmp_path), capture_verdict(_feats("X"), "approved", "ok"))
    write_verdict(str(tmp_path), capture_verdict(_feats("Y", 2.0), "rejected", "no"))

    loaded = load_verdicts_from_dir(str(tmp_path), max_rationale_len=100, max_files=10)
    assert {v.decision for v in loaded} == {"approved", "rejected"}


def test_load_skips_non_utf8_file(tmp_path) -> None:
    """T-2.5d: a hand-authored inbox verdict saved in Latin-1 (Norwegian ``æ/ø/å``) is valid JSON bytes
    but INVALID UTF-8; it matches the ``*.json`` glob yet must be SKIPPED, never raise — the loader's
    per-file tolerant contract (the Step-7 loop relies on it). Detach the ``UnicodeDecodeError`` catch
    → ``read_text(encoding='utf-8')`` raises → RED. The valid verdict alongside still loads."""
    (tmp_path / "latin1.json").write_bytes(
        json.dumps(
            {
                "id": "X",
                "decision": "approved",
                "rationale": "godkjent på møtet",
                "proposal_features": {
                    "affected_codes": ["05.2"],
                    "measure_type": "m",
                    "claimed_saving_nok": 200.0,
                },
            },
            ensure_ascii=False,
        ).encode("latin-1")
    )
    write_verdict(str(tmp_path), capture_verdict(_feats("Y"), "approved", "fine"))

    loaded = load_verdicts_from_dir(str(tmp_path))
    assert [v.decision for v in loaded] == ["approved"]  # latin1 file skipped, the valid one loads


def test_load_skips_non_iterable_affected_codes(tmp_path) -> None:
    """Parity ground-truth: ``verdict_from_dict``'s ``frozenset(affected_codes)`` raises ``TypeError``
    on a non-iterable (``null``), and ``load_verdicts_from_dir`` SKIPS it. This pins the reference the
    hitl inbox predicate mirrors (``test_hitl_loadbearing.test_inbox_idset_skips_non_iterable_affected_codes``)
    so the parity contract cannot silently rot on the loader side."""
    (tmp_path / "bad.json").write_text(
        json.dumps(
            {
                "id": "X",
                "decision": "approved",
                "rationale": "r",
                "proposal_features": {
                    "affected_codes": None,
                    "measure_type": "m",
                    "claimed_saving_nok": 1.0,
                },
            }
        ),
        encoding="utf-8",
    )
    write_verdict(str(tmp_path), capture_verdict(_feats("Y"), "approved", "fine"))

    loaded = load_verdicts_from_dir(str(tmp_path))
    assert [v.decision for v in loaded] == ["approved"]  # non-iterable affected_codes skipped


def test_no_inbox_json_uses_approved_with_adjustment() -> None:
    """Assumption 3 (TDD guard): no shipped/test ``.json`` uses the promotion-only decision
    ``approved_with_adjustment`` — the vocabulary SKIP would now silently drop it. It lives only in
    bundle-seed frontmatter + the promotion gate ``_APPROVED_DECISIONS``, never a binary run-path
    inbox file."""
    root = Path(__file__).resolve().parents[1]
    offenders = [
        p
        for p in root.rglob("*.json")
        if ".venv" not in p.parts
        and ".git" not in p.parts
        and "approved_with_adjustment" in p.read_text(encoding="utf-8", errors="ignore")
    ]
    assert offenders == [], f"inbox JSON with promotion-only decision: {offenders}"