// From sherpa-onnx v1.13.8 (Apache-2.0, https://github.com/k2-fsa/sherpa-onnx), kotlin-api.
// The JNI names are fixed to this package; the upstream catalog of pretrained models is left out.
package com.k2fsa.sherpa.onnx

import android.content.res.AssetManager

data class EndpointRule(
    var mustContainNonSilence: Boolean,
    var minTrailingSilence: Float,
    var minUtteranceLength: Float,
)

data class EndpointConfig(
    var rule1: EndpointRule = EndpointRule(false, 2.4f, 0.0f),
    var rule2: EndpointRule = EndpointRule(true, 1.4f, 0.0f),
    var rule3: EndpointRule = EndpointRule(false, 0.0f, 20.0f)
)

data class OnlineTransducerModelConfig(
    var encoder: String = "",
    var decoder: String = "",
    var joiner: String = "",
    var qnnConfig: QnnConfig = QnnConfig(),
)

data class OnlineParaformerModelConfig(
    var encoder: String = "",
    var decoder: String = "",
)

data class OnlineZipformer2CtcModelConfig(
    var model: String = "",
)

data class OnlineNeMoCtcModelConfig(
    var model: String = "",
)

data class OnlineToneCtcModelConfig(
    var model: String = "",
)

data class OnlineModelConfig(
    var transducer: OnlineTransducerModelConfig = OnlineTransducerModelConfig(),
    var paraformer: OnlineParaformerModelConfig = OnlineParaformerModelConfig(),
    var zipformer2Ctc: OnlineZipformer2CtcModelConfig = OnlineZipformer2CtcModelConfig(),
    var neMoCtc: OnlineNeMoCtcModelConfig = OnlineNeMoCtcModelConfig(),
    var toneCtc: OnlineToneCtcModelConfig = OnlineToneCtcModelConfig(),
    var tokens: String = "",
    var numThreads: Int = 1,
    var debug: Boolean = false,
    var provider: String = "cpu",
    var modelType: String = "",
    var modelingUnit: String = "",
    var bpeVocab: String = "",
)

data class OnlineLMConfig(
    var model: String = "",
    var scale: Float = 0.5f,
)

data class OnlineCtcFstDecoderConfig(
    var graph: String = "",
    var maxActive: Int = 3000,
)

data class OnlineRecognizerConfig(
    var featConfig: FeatureConfig = FeatureConfig(),
    var modelConfig: OnlineModelConfig = OnlineModelConfig(),
    var lmConfig: OnlineLMConfig = OnlineLMConfig(),
    var ctcFstDecoderConfig: OnlineCtcFstDecoderConfig = OnlineCtcFstDecoderConfig(),
    var hr: HomophoneReplacerConfig = HomophoneReplacerConfig(),
    var endpointConfig: EndpointConfig = EndpointConfig(),
    var enableEndpoint: Boolean = true,
    var decodingMethod: String = "greedy_search",
    var maxActivePaths: Int = 4,
    var hotwordsFile: String = "",
    var hotwordsScore: Float = 1.5f,
    var ruleFsts: String = "",
    var ruleFars: String = "",
    var blankPenalty: Float = 0.0f,
)

data class OnlineRecognizerResult(
    val text: String,
    val tokens: Array<String>,
    val timestamps: FloatArray,
    val ysProbs: FloatArray,
    // TODO(fangjun): Add more fields
)

class OnlineRecognizer(
    assetManager: AssetManager? = null,
    val config: OnlineRecognizerConfig,
) {
    private var ptr: Long

    init {
        ptr = if (assetManager != null) {
            newFromAsset(assetManager, config)
        } else {
            newFromFile(config)
        }
        require(ptr != 0L) {
            "Invalid OnlineRecognizerConfig: failed to create native OnlineRecognizer"
        }
    }

    protected fun finalize() {
        if (ptr != 0L) {
            delete(ptr)
            ptr = 0
        }
    }

    fun release() = finalize()

    fun createStream(hotwords: String = ""): OnlineStream {
        val p = createStream(ptr, hotwords)
        return OnlineStream(p)
    }

    fun reset(stream: OnlineStream) = reset(ptr, stream.ptr)
    fun decode(stream: OnlineStream) = decode(ptr, stream.ptr)
    fun isEndpoint(stream: OnlineStream) = isEndpoint(ptr, stream.ptr)
    fun isReady(stream: OnlineStream) = isReady(ptr, stream.ptr)
    fun getResult(stream: OnlineStream): OnlineRecognizerResult {
        return getResult(ptr, stream.ptr)
    }

    private external fun delete(ptr: Long)

    private external fun newFromAsset(
        assetManager: AssetManager,
        config: OnlineRecognizerConfig,
    ): Long

    private external fun newFromFile(
        config: OnlineRecognizerConfig,
    ): Long

    private external fun createStream(ptr: Long, hotwords: String): Long
    private external fun reset(ptr: Long, streamPtr: Long)
    private external fun decode(ptr: Long, streamPtr: Long)
    private external fun isEndpoint(ptr: Long, streamPtr: Long): Boolean
    private external fun isReady(ptr: Long, streamPtr: Long): Boolean
    private external fun getResult(ptr: Long, streamPtr: Long): OnlineRecognizerResult

    companion object {
        init {
            System.loadLibrary("sherpa-onnx-jni")
        }

        @JvmStatic
        external fun prependAdspLibraryPath(newPath: String) // for qnn
    }
}