"""Tests for FDA alternatives tool (mocked HTTP)."""

from __future__ import annotations

from unittest.mock import patch

from app.tools.medication_alternatives import build_alternatives_response


def test_build_alternatives_empty_input() -> None:
    out = build_alternatives_response(None, [], max_suggestions=5)
    assert "errors" in out
    assert out["source"] in {"none", "external"}


def test_multi_regimen_without_query_drug_returns_error() -> None:
    """Do not silently use regimen[0] when several drugs are listed."""
    out = build_alternatives_response(None, ["benzodiazepine_like", "warfarin_like"], max_suggestions=5)
    assert out["suggestions"] == []
    assert out["errors"]
    assert "first" in out["errors"][0].lower() or "pick" in out["errors"][0].lower()


@patch("app.tools.medication_alternatives._external_suggestions", return_value=None)
@patch("app.tools.medication_alternatives._fda_get")
def test_build_alternatives_simulator_token_class_probe(mock_fda, _mock_ext) -> None:
    """benzodiazepine_like normalizes and hits direct pharm_class_epc search."""

    def side_effect(search: str, limit: int) -> dict | None:
        if "pharm_class_epc" in search and "enzodiazepine" in search.lower():
            return {
                "results": [
                    {
                        "openfda": {
                            "brand_name": ["VALIUM"],
                            "generic_name": ["DIAZEPAM"],
                            "pharm_class_epc": ["Benzodiazepine"],
                            "route": ["ORAL"],
                        },
                        "adverse_reactions": ["Drowsiness."],
                    }
                ]
            }
        return None

    mock_fda.side_effect = side_effect
    out = build_alternatives_response("benzodiazepine_like", [], max_suggestions=5)
    assert out["therapeutic_class"] == "Benzodiazepine"
    assert len(out["suggestions"]) >= 1


@patch("app.tools.medication_alternatives._external_suggestions", return_value=None)
@patch("app.tools.medication_alternatives._fda_get")
def test_build_alternatives_openfda_path(mock_fda, _mock_ext) -> None:
    """Resolve class from first label, then class search returns neighbors."""
    nsaid = "Nonsteroidal Anti-inflammatory Drug"

    def side_effect(search: str, limit: int) -> dict | None:
        if "openfda.generic_name" in search and "ibuprofen" in search.lower():
            return {
                "results": [
                    {
                        "openfda": {
                            "generic_name": ["IBUPROFEN"],
                            "pharm_class_epc": [nsaid],
                        },
                    }
                ]
            }
        if "pharm_class_epc" in search and nsaid in search:
            return {
                "results": [
                    {
                        "openfda": {
                            "brand_name": ["OTHER NSAID"],
                            "generic_name": ["KETOPROFEN"],
                            "pharm_class_epc": [nsaid],
                            "route": ["ORAL"],
                        },
                        "adverse_reactions": ["GI bleeding risk in some patients."],
                    }
                ]
            }
        return None

    mock_fda.side_effect = side_effect
    out = build_alternatives_response("ibuprofen", [], max_suggestions=5)
    assert out["focus_drug"] == "ibuprofen"
    assert out["therapeutic_class"] == nsaid
    assert len(out["suggestions"]) >= 1
    assert out["suggestions"][0]["display_name"]