#!/usr/bin/env python3
"""Regression tests for MCP career event adjudication."""

from __future__ import annotations

from mcp_server import _collect_strict_evidence


def _base_career_result() -> dict:
    return {
        "modules": {
            "varga_full": {"D10_Dasamsa": {"summary": "career varga present"}},
            "special_lagnas": {"A10_Karma_Pada": {"sign": "Capricorn", "lord": "Saturn"}},
            "jaimini": {
                "karakas": {
                    "Amatyakaraka": {"planet": "Mercury"},
                    "Atmakaraka": {"planet": "Sun"},
                },
                "karakamsha": {"karakamsha_sign": "Leo", "karakamsha_lord": "Sun"},
            },
            "dasha": {"current_dasha": {"mahadasha": "Mercury", "antardasha": "Sun"}},
            "narayana_dasha": {"current_dasha": {"sign": "Capricorn", "lord": "Saturn"}},
            "dasa_convergence": {
                "domain_activations": {
                    "career_status": {"convergence_level": "L2", "probability": "35-50%"}
                }
            },
            "argala": {
                "houses": {
                    "house_10": {
                        "net_result": "supported",
                        "argala_count": 2,
                        "virodhargala_count": 0,
                    }
                }
            },
        }
    }


def test_career_collects_a10_amk_karakamsha_as_strict_evidence() -> None:
    strict = _collect_strict_evidence("career", _base_career_result())

    assert strict["question_type"] == "career"
    assert strict["present_evidence"]["d10_dasamsa"] == {"summary": "career varga present"}
    assert strict["present_evidence"]["a10_karma_pada"] == {"sign": "Capricorn", "lord": "Saturn"}
    assert strict["present_evidence"]["amatyakaraka"] == {"planet": "Mercury"}
    assert strict["present_evidence"]["karakamsha"] == {
        "karakamsha_sign": "Leo",
        "karakamsha_lord": "Sun",
    }
    assert strict["event_judgement"]["event_family"] == "career"
    assert strict["event_judgement"]["dominant_label"] == "career_status"
    assert strict["event_judgement"]["secondary_context"] == [
        "a10_active",
        "amk_active",
        "karakamsha_context",
        "argala_support",
    ]


def test_career_blocks_label_when_d10_is_missing_but_preserves_jaimini_context() -> None:
    result = _base_career_result()
    del result["modules"]["varga_full"]["D10_Dasamsa"]

    strict = _collect_strict_evidence("career", result)

    assert "d10_dasamsa" in strict["missing_evidence"]
    assert strict["blocked"] is True
    assert strict["event_judgement"]["dominant_label"] is None
    assert strict["event_judgement"]["secondary_context"] == [
        "a10_active",
        "amk_active",
        "karakamsha_context",
        "argala_support",
    ]


def test_career_argala_bridge_uses_tenth_house_as_modifier_only() -> None:
    result = _base_career_result()

    strict = _collect_strict_evidence("career", result)

    assert strict["present_evidence"]["argala_support"] == {
        "level": "supportive",
        "target_house": 10,
        "source": "argala_house_bridge_v1",
        "signals": ["argala_support"],
        "raw": {
            "net_result": "supported",
            "argala_count": 2,
            "virodhargala_count": 0,
        },
    }
    assert strict["event_judgement"]["dominant_label"] == "career_status"
    assert "argala_support" in strict["event_judgement"]["secondary_context"]


def test_career_kakshya_support_adds_small_score_bump_without_label_override() -> None:
    base_result = _base_career_result()
    base_result["modules"]["dasa_convergence"]["domain_activations"]["career_status"] = {
        "convergence_level": "L1",
        "probability": "+15-20%",
    }
    base = _collect_strict_evidence("career", base_result)
    result = _base_career_result()
    result["modules"]["dasa_convergence"]["domain_activations"]["career_status"] = {
        "convergence_level": "L1",
        "probability": "+15-20%",
    }
    result["modules"]["kakshya"] = {
        "summary": {"average_strength": 6.7},
        "planets": {"Sun": {"kakshya_strength": 7.0}},
    }

    strict = _collect_strict_evidence("career", result)

    assert strict["present_evidence"]["kakshya_career_support"] == {
        "level": "supportive",
        "source": "kakshya_career_bridge_v1",
        "signals": ["kakshya_career_support"],
        "average_strength": 6.7,
    }
    assert strict["event_judgement"]["dominant_label"] == "career_status"
    assert strict["event_judgement"]["score"] >= base["event_judgement"]["score"]
    assert "kakshya_career_support" in strict["event_judgement"]["secondary_context"]


def test_career_caps_confidence_when_provided_shadbala_components_are_incomplete() -> None:
    result = _base_career_result()
    result["modules"]["dasa_convergence"]["domain_activations"]["career_status"] = {
        "convergence_level": "L4",
        "probability": "70-85%",
    }
    result["modules"]["shadbala"] = {"planets": {"Mercury": {"total_rupa": 7.5}}}

    strict = _collect_strict_evidence("career", result)

    assert strict["present_evidence"]["shadbala_component_audit"] == {
        "status": "incomplete",
        "source": "shadbala.planets",
        "required_components": ["sthana", "dig", "kala", "chesta", "naisargika", "drik"],
        "missing": {"Mercury": ["sthana", "dig", "kala", "chesta", "naisargika", "drik"]},
    }
    assert strict["confidence_cap"] == "low"
    assert "shadbala_component_gap" in strict["event_judgement"]["secondary_context"]


def test_career_accepts_complete_shadbala_components_without_cap_penalty() -> None:
    result = _base_career_result()
    result["modules"]["dasa_convergence"]["domain_activations"]["career_status"] = {
        "convergence_level": "L4",
        "probability": "70-85%",
    }
    result["modules"]["shadbala"] = {
        "planets": {
            "Mercury": {
                "components": {
                    "sthana": 1.0,
                    "dig": 0.8,
                    "kala": 1.2,
                    "chesta": 0.7,
                    "naisargika": 0.5,
                    "drik": 0.3,
                },
                "total_rupa": 4.5,
            }
        }
    }

    strict = _collect_strict_evidence("career", result)

    assert strict["present_evidence"]["shadbala_component_audit"]["status"] == "complete"
    assert strict["confidence_cap"] == "medium-high"
    assert "shadbala_component_gap" not in strict["event_judgement"]["secondary_context"]