"""Tests for confidence scoring and low-confidence selection (subtask 7.2)."""

from __future__ import annotations

from typing import List, Dict, Any

from src.services.multi_pass_transcription import MultiPassTranscriptionPipeline


def _build_segments(values: List[tuple[float, float, str]]) -> List[Dict[str, Any]]:
    # values: (avg_logprob, no_speech_prob, label)
    segments: List[Dict[str, Any]] = []
    t = 0.0
    for lp, ns, label in values:
        segments.append(
            {
                "start": t,
                "end": t + 1.0,
                "text": label,
                "avg_logprob": lp,
                "no_speech_prob": ns,
            }
        )
        t += 1.1
    return segments


def test_calculate_confidence_basic_monotonicity():
    pipeline = MultiPassTranscriptionPipeline()

    segments = _build_segments(
        [
            (-5.0, 1.0, "very_low"),   # worst
            (-2.5, 0.5, "medium"),     # medium
            (0.0, 0.0, "high"),        # best
        ]
    )

    scored = pipeline._calculate_confidence(segments)
    scores = {s["text"]: s["confidence"] for s in scored}

    assert 0.0 <= scores["very_low"] <= 0.3
    assert 0.3 <= scores["medium"] <= 0.8
    assert 0.9 <= scores["high"] <= 1.0
    assert scores["high"] > scores["medium"] > scores["very_low"]


def test_identify_low_confidence_segments_thresholding():
    pipeline = MultiPassTranscriptionPipeline()
    pipeline.confidence_threshold = 0.75

    segments = _build_segments(
        [
            (-4.0, 0.8, "low1"),
            (-1.0, 0.2, "mid1"),
            (0.0, 0.0, "high1"),
        ]
    )

    scored = pipeline._calculate_confidence(segments)
    lows = pipeline._identify_low_confidence_segments(scored)
    low_labels = {s["text"] for s in lows}

    assert "low1" in low_labels
    assert "high1" not in low_labels