"""D14b wiring: status=auto, search_formulas, and evidence loader skips formula files.

Completes the formula layer beyond the store: the `auto` status the spec requires
(§4.7.2), the concept-substring retrieval that `tht search find --kind formula` uses,
and the guarantee that load_evidence_dir does NOT choke on *.sql.md formula files when
they live under the evidence root.
"""
import json
from types import SimpleNamespace

from typer.testing import CliRunner

from tht.cli import app, search_cmd
from tht.evidence import formula_store
from tht.evidence.formula_store import ConceptFormula, save_formula, search_formulas
from tht.evidence.model import EvidenceDoc, load_evidence_dir
from tht.evidence.search import EvidenceSearchOutcome


def test_status_auto_is_valid():
    f = ConceptFormula(concept="x", sql="SELECT 1", status="auto")
    assert f.status == "auto"
    # round-trips through parse/dump
    assert ConceptFormula.parse(f.dump()).status == "auto"


def test_search_formulas_substring_case_insensitive(tmp_path):
    save_formula(tmp_path, ConceptFormula(concept="fascia pediatrica", sql="SELECT 1"))
    save_formula(tmp_path, ConceptFormula(concept="indice di Charlson", sql="SELECT 2"))
    hits = search_formulas(tmp_path, "PEDIATRICA")
    assert len(hits) == 1
    assert hits[0].concept == "fascia pediatrica"
    assert search_formulas(tmp_path, "charlson")[0].concept == "indice di Charlson"


def test_load_evidence_dir_skips_formula_files(tmp_path):
    # a real evidence doc + a formula file under the same root
    (tmp_path / "ev1.md").write_text(
        "---\nid: ev1\ntitle: T\n---\nbody text\n"
    )
    save_formula(tmp_path, ConceptFormula(concept="ablazione", sql="SELECT 1"))
    docs = load_evidence_dir(tmp_path)
    ids = [d.id for d in docs]
    assert ids == ["ev1"]  # the .sql.md formula file is skipped, no crash
    assert all(isinstance(d, EvidenceDoc) for d in docs)


def test_unreviewed_legacy_formulas_cannot_become_curated_evidence():
    for status in ("auto", "draft"):
        formula = ConceptFormula(
            concept="fascia pediatrica",
            columns=["clinical.patient.birth_date"],
            sql="CASE WHEN age < 18 THEN 'pediatrica' ELSE 'adulta' END",
            status=status,
        )
        assert formula_store.legacy_formula_to_curated(
            formula, legacy_path="formulas/pediatric-1.sql.md",
        ) is None


def test_formula_search_uses_typed_evidence_with_a_formula_constraint():
    class Searcher:
        vector_generation = "gen:" + "a" * 32

        def __init__(self):
            self.calls = []

        def search(self, embedding, **kwargs):
            self.calls.append((embedding, kwargs))
            return [SimpleNamespace(
                id="fragment:formula", similarity=0.9, content="formula excerpt",
                title="Fascia pediatrica", metadata={
                    "evidence_id": "evidence:fascia-pediatrica",
                    "evidence_kind": "formula",
                    "document_id": "doc:formula",
                    "ordinal": 0,
                    "source_uri": "file:///curated/formula/fascia-pediatrica.md",
                    "provenance": {},
                },
            )]

    class Embedder:
        def embed_query(self, query):
            return [0.25]

    searcher = Searcher()
    outcome = search_cmd.search_formula_evidence(
        "fascia pediatrica", searcher=searcher, embedder=Embedder(), top=3,
    )

    assert outcome.status == "available"
    assert [result.evidence_id for result in outcome.results] == ["evidence:fascia-pediatrica"]
    assert searcher.calls[0][1]["metadata_filter"]["required_kinds"] == ["formula"]


def test_formula_search_json_is_pristine_while_human_output_warns_about_legacy_store(monkeypatch):
    monkeypatch.setattr(search_cmd, "_load_config_or_exit", lambda _path: SimpleNamespace(embeddings=object()))
    monkeypatch.setattr(search_cmd, "workspace_id_for_config", lambda _cfg, _path: "workspace-a")
    monkeypatch.setattr(search_cmd, "search_formula_evidence", lambda *args, **kwargs: EvidenceSearchOutcome(
        "available", "gen:" + "a" * 32,
    ))
    monkeypatch.setattr("tht.cli.vector_cmd.require_vector_cfg", lambda _cfg: None)
    monkeypatch.setattr("tht.cli.vector_cmd.open_searcher", lambda _cfg: object())
    monkeypatch.setattr("tht.cli.vector_cmd.make_embedder", lambda _cfg: object())
    monkeypatch.setattr("tht.evidence.active_searcher", lambda *args, **kwargs: object())
    monkeypatch.setattr("tht.evidence.validate_corpus_workspace", lambda _cfg, _workspace: None)

    json_result = CliRunner().invoke(
        app, ["search", "find", "fascia pediatrica", "--kind", "formula", "--top", "1", "--json"],
    )
    human_result = CliRunner().invoke(
        app, ["search", "find", "fascia pediatrica", "--kind", "formula", "--top", "1"],
    )

    assert json_result.exit_code == 0
    assert json.loads(json_result.stdout) == []
    assert "ATTENZIONE" not in json_result.stdout
    assert human_result.exit_code == 0
    assert "ATTENZIONE" in human_result.output