package com.sherpaonnxofflinestt

import org.junit.Test
import org.junit.Assert.*

/**
 * Unit tests for STTConstants configuration values
 */
class STTConstantsTest {

    @Test
    fun `audio processing constants have valid values`() {
        assertEquals(16000, STTConstants.DEFAULT_SAMPLE_RATE)
        assertEquals(160, STTConstants.VAD_HOP_SIZE)
        assertEquals(5 * 16000, STTConstants.MAX_DENOISER_CHUNK_SAMPLES)
        assertEquals(80, STTConstants.AUDIO_CHUNK_SIZE_MS)
    }

    @Test
    fun `VAD threshold constants are within valid range`() {
        assertTrue(STTConstants.DEFAULT_VAD_THRESHOLD in 0f..1f)
        assertTrue(STTConstants.VAD_THRESHOLD_MIN in 0f..1f)
        assertTrue(STTConstants.VAD_THRESHOLD_MAX in 0f..1f)
        assertTrue(STTConstants.VAD_THRESHOLD_MIN < STTConstants.VAD_THRESHOLD_MAX)
    }

    @Test
    fun `VAD timing constants are positive`() {
        assertTrue(STTConstants.DEFAULT_MIN_SPEECH_MS > 0)
        assertTrue(STTConstants.DEFAULT_MIN_SILENCE_MS > 0)
        assertTrue(STTConstants.DEFAULT_MAX_SPEECH_MS > 0)
        assertTrue(STTConstants.DEFAULT_SPEECH_PADDING_MS >= 0)
    }

    @Test
    fun `diarization constants have valid ranges`() {
        assertTrue(STTConstants.DEFAULT_SPEAKER_THRESHOLD in 0f..1f)
        assertTrue(STTConstants.DEFAULT_EMBEDDING_THRESHOLD in 0f..1f)
        assertTrue(STTConstants.DEFAULT_MAX_SPEAKERS > 0)
        assertTrue(STTConstants.DEFAULT_EMBEDDING_AVERAGE_WEIGHT in 0f..1f)
    }

    @Test
    fun `diarization window constants are properly ordered`() {
        assertTrue(STTConstants.DIARIZATION_WINDOW_SIZE_MS > 0)
        assertTrue(STTConstants.DIARIZATION_WINDOW_STEP_MS > 0)
        // Step should be <= size for proper overlap
        assertTrue(STTConstants.DIARIZATION_WINDOW_STEP_MS <= STTConstants.DIARIZATION_WINDOW_SIZE_MS)
    }

    @Test
    fun `streaming state constants are valid`() {
        assertTrue(STTConstants.DEFAULT_CONFIRMATION_THRESHOLD in 0f..1f)
        assertTrue(STTConstants.DEFAULT_MIN_CONTEXT_MS > 0)
    }

    @Test
    fun `embedding validation constants are valid`() {
        assertTrue(STTConstants.MIN_EMBEDDING_NORM > 0)
        assertTrue(STTConstants.EMBEDDING_QUALITY_FACTOR > 0)
    }

    @Test
    fun `pyannote defaults are valid`() {
        assertTrue(STTConstants.DEFAULT_CLUSTERING_THRESHOLD in 0f..1f)
        assertTrue(STTConstants.DEFAULT_MIN_DURATION_ON > 0)
        assertTrue(STTConstants.DEFAULT_MIN_DURATION_OFF > 0)
    }

    @Test
    fun `model inference constants are valid`() {
        assertTrue(STTConstants.DEFAULT_STT_NUM_THREADS > 0)
        assertTrue(STTConstants.DEFAULT_AUXILIARY_NUM_THREADS > 0)
        assertNotNull(STTConstants.DEFAULT_PROVIDER)
        assertTrue(STTConstants.DEFAULT_PROVIDER.isNotEmpty())
    }

    @Test
    fun `speaker threshold is more lenient than embedding threshold`() {
        // Speaker matching should use a lower threshold than profile updates
        assertTrue(STTConstants.DEFAULT_SPEAKER_THRESHOLD < STTConstants.DEFAULT_EMBEDDING_THRESHOLD)
    }

    @Test
    fun `min speech for new speaker is greater than min speech duration`() {
        // New speaker creation requires more accumulated speech
        assertTrue(STTConstants.DEFAULT_MIN_SPEECH_FOR_NEW_SPEAKER >= STTConstants.DEFAULT_MIN_SPEECH_DURATION_MS)
    }
}