"""Emotion-tag parsing for expressive TTS. A ``[감정]`` tag must steer the
delivery of the text that follows without being spoken; a bracket that is NOT a
known emotion word must be kept as ordinary spoken content.

Delivery is now driven by a base (공통) control dict plus optional per-emotion
overrides. By default there are no overrides, so every emotion delivers with the
base controls (모든 감정 = 기본값)."""

from wsai.backends.emotion import (
    EMOTION_LABELS,
    _SYNONYMS,
    match_emotion,
    parse_segments,
)
from wsai.dashboard import _speech_text

BASE = {"speed": 1.35, "word_gap": -0.07, "sentence_gap": -0.30, "pitch": 0.0}


def test_emotion_tag_is_not_spoken_and_tags_segment():
    segs = parse_segments("[기쁨] 오늘 날씨 좋다", BASE)
    assert len(segs) == 1
    assert "기쁨" not in segs[0].text        # the tag word is dropped
    assert segs[0].text == "오늘 날씨 좋다"
    assert segs[0].emotion == "happy"


def test_default_all_emotions_use_base():
    # No overrides -> a tagged emotion delivers with exactly the base controls.
    segs = parse_segments("[기쁨] 좋아", BASE)
    s = segs[0]
    assert (s.speed, s.word_gap, s.sentence_gap, s.pitch) == (1.35, -0.07, -0.30, 0.0)


def test_per_emotion_override_applies_and_inherits_missing_keys():
    segs = parse_segments("[기쁨] 좋아", BASE, {"happy": {"speed": 1.6, "pitch": 3.0}})
    s = segs[0]
    assert s.speed == 1.6 and s.pitch == 3.0        # overridden
    assert s.word_gap == -0.07 and s.sentence_gap == -0.30  # inherited from base


def test_override_only_affects_its_own_emotion():
    segs = parse_segments("[기쁨] 가. [슬픔] 나.", BASE, {"sad": {"speed": 0.8}})
    assert segs[0].emotion == "happy" and segs[0].speed == 1.35   # untouched
    assert segs[1].emotion == "sad" and segs[1].speed == 0.8      # overridden


def test_midreply_emotion_change_splits_segments():
    segs = parse_segments("[속상함] 정말 힘들었겠다. [힘차게] 하지만 넌 할 수 있어!", BASE)
    assert len(segs) == 2
    assert segs[0].text == "정말 힘들었겠다." and segs[0].emotion == "sad"
    assert segs[1].text == "하지만 넌 할 수 있어!" and segs[1].emotion == "hopeful"


def test_non_emotion_bracket_is_spoken_without_brackets():
    segs = parse_segments("[기쁨] 첫째는 [1번] 항목이야", BASE)
    assert len(segs) == 1
    assert "1번" in segs[0].text
    assert "[" not in segs[0].text and "]" not in segs[0].text
    assert segs[0].emotion == "happy"


def test_text_before_first_tag_is_neutral():
    segs = parse_segments("잠깐만. [신남] 찾았다!", BASE)
    assert segs[0].text == "잠깐만." and segs[0].emotion is None
    assert segs[0].speed == 1.35 and segs[0].pitch == 0.0
    assert segs[1].emotion == "excited"


def test_plain_text_is_one_neutral_segment():
    segs = parse_segments("그냥 평범한 문장이야", BASE)
    assert len(segs) == 1
    assert segs[0].emotion is None and segs[0].speed == 1.35


def test_backward_compat_float_base():
    # A bare float base still works (speed only; other controls neutral).
    segs = parse_segments("그냥 문장", 1.2)
    assert segs[0].speed == 1.2 and segs[0].word_gap == 0.0


def test_empty_input_yields_no_segments():
    assert parse_segments("", BASE) == []
    assert parse_segments("   ", BASE) == []


def test_only_emotion_tags_yield_no_segments():
    # A reply that is nothing but tags has nothing to say.
    assert parse_segments("[기쁨][신남]", BASE) == []


def test_match_emotion_is_synonym_and_space_tolerant():
    assert match_emotion("속상함") == "sad"
    assert match_emotion(" 힘 차게 ") == "hopeful"   # squeezed + trimmed
    assert match_emotion("행복하게") == "happy"
    assert match_emotion("메모") is None            # not an emotion


def test_persona_examples_are_all_recognised():
    # Every emotion the brain persona advertises must resolve, or it would be
    # read aloud instead of shaping the voice.
    for word in ["힘차게", "궁금", "반가움", "차분하게", "웃으며", "속상함"]:
        assert match_emotion(word) is not None, word


def test_every_canonical_emotion_has_a_ui_label():
    # The dashboard dropdown lists EMOTION_LABELS; every emotion a tag can
    # resolve to must appear there or it would be untunable.
    for canon in set(_SYNONYMS.values()):
        assert canon in EMOTION_LABELS, canon


def test_voice_turn_keeps_leading_emotion_tag_for_tts_parser():
    text = "[속상함] 정말 힘들었겠다. [힘차게] 하지만 넌 할 수 있어!"

    spoken = _speech_text(text)
    segs = parse_segments(spoken, BASE)

    assert spoken == text
    assert segs[0].text == "정말 힘들었겠다." and segs[0].emotion == "sad"
    assert segs[1].text == "하지만 넌 할 수 있어!" and segs[1].emotion == "hopeful"