import numpy as np
import pytest
from datetime import datetime, timezone
from unittest.mock import patch, MagicMock


def _make_chunk(samples: int = 4000, amplitude: float = 0.0) -> bytes:
    """Create a fake PCM int16 chunk."""
    audio = (np.ones(samples) * amplitude * 32767).astype(np.int16)
    return audio.tobytes()


@pytest.fixture
def buf(mocker):
    """RoomVADBuffer with mocked VAD model."""
    mocker.patch(
        "app.pipeline.ingestion.vad_prob",
        side_effect=lambda chunk: 0.9 if np.frombuffer(chunk, np.int16).max() > 100 else 0.1,
    )
    from app.pipeline.ingestion import RoomVADBuffer
    return RoomVADBuffer(silence_threshold_ms=600, min_speech_ms=500, chunk_ms=250)


def test_silence_produces_no_segment(buf):
    ts = datetime(2026, 1, 1, tzinfo=timezone.utc)
    for _ in range(10):
        result = buf.process_chunk(_make_chunk(amplitude=0.0), ts)
        assert result is None


def test_speech_then_silence_produces_segment(buf):
    ts = datetime(2026, 1, 1, tzinfo=timezone.utc)
    # 4 speech chunks = 1 second of speech
    for _ in range(4):
        result = buf.process_chunk(_make_chunk(amplitude=0.5), ts)
        assert result is None  # still accumulating
    # 3 silence chunks = 750ms silence (> 600ms threshold)
    segment = None
    for _ in range(3):
        segment = buf.process_chunk(_make_chunk(amplitude=0.0), ts)
    assert segment is not None
    assert isinstance(segment, tuple)
    audio_bytes, start_time = segment
    assert len(audio_bytes) > 0


def test_short_speech_discarded(buf):
    ts = datetime(2026, 1, 1, tzinfo=timezone.utc)
    # 1 speech chunk = 250ms (below 500ms min)
    buf.process_chunk(_make_chunk(amplitude=0.5), ts)
    # Now silence to trigger emission
    result = None
    for _ in range(3):
        result = buf.process_chunk(_make_chunk(amplitude=0.0), ts)
    assert result is None  # discarded as too short