"""L1: arricchimento metadata memory — subject/detail/rationale nel jsonb (decisione spec 6).

Una volta che il registry e' droppato (decisione spec 5), il vectordb e' l'unica
fonte delle memory. L'hit di search_similar deve bastare per ricostruire la decisione
completa. Per questo memory_vector_records mette subject/detail/rationale nel metadata
del VectorRecord (pack_metadata li serializza nel jsonb via **record.metadata).
"""
from datetime import datetime

from tht.memory import MemoryRecord, memory_vector_records


def _record(**kw) -> MemoryRecord:
    base = dict(
        id="mem-x", ts=datetime(2025, 1, 1), session_id="s", decision_seq=1,
        type="concept_clarified", subject="paziente attivo", detail="flag_attivo = TRUE",
        rationale="perche' serve", question_context="dammi pazienti",
        tables=[], concepts=["paziente attivo"],
    )
    base.update(kw)
    return MemoryRecord(**base)


def test_memory_vector_record_has_subject_detail_rationale_in_metadata():
    vr = memory_vector_records([_record()])[0]
    assert vr.metadata["subject"] == "paziente attivo"
    assert vr.metadata["detail"] == "flag_attivo = TRUE"
    assert vr.metadata["rationale"] == "perche' serve"


def test_memory_vector_record_metadata_keeps_existing_fields():
    vr = memory_vector_records([_record()])[0]
    # i campi che gia' c'erano restano (backward compat)
    assert vr.metadata["type"] == "concept_clarified"
    assert vr.metadata["tables"] == []
    assert vr.metadata["concepts"] == ["paziente attivo"]
    assert vr.metadata["session_id"] == "s"


def test_each_record_carries_its_own_subject():
    # piu' record, ciascuno con il proprio subject (no cross-contamination)
    recs = [
        _record(id="m1", subject="t_a", detail="d_a", rationale="r_a"),
        _record(id="m2", subject="t_b", detail="d_b", rationale="r_b"),
    ]
    out = memory_vector_records(recs)
    assert {v.metadata["subject"] for v in out} == {"t_a", "t_b"}
    assert {v.metadata["detail"] for v in out} == {"d_a", "d_b"}


def test_save_one_memory_preserves_subject_through_upsert_row():
    # end-to-end: save_one_memory costruisce la riga upsert; il metadata deve arrivare
    # con subject/detail/rationale (pack_metadata lo prende da record.metadata).
    from unittest.mock import MagicMock

    from tht.memory import save_one_memory

    writer = MagicMock()
    writer.upsert.return_value = 1
    embedder = MagicMock()
    embedder.embed_documents.return_value = [[0.0] * 8]
    save_one_memory([_record(decision_seq=1)], decision_seq=1, store=writer, embedder=embedder)
    row = writer.upsert.call_args[0][1][0]
    md = row.record.metadata
    assert md["subject"] == "paziente attivo"
    assert md["detail"] == "flag_attivo = TRUE"
    assert md["rationale"] == "perche' serve"