using System.Collections.Generic;
using System.Linq;
using System.Text.Json.Serialization;
using VideoAnalysisCore.Common;
using SherpaOnnx;

namespace VideoAnalysisCore.AICore.SherpaOnnx
{

    /// <summary>
    /// 说话人模型
    /// <para>pyannote  </para>
    /// </summary>
    public class Speaker
    {
        private static OfflineSpeakerDiarization? SD;
        /// <summary>
        /// 初始化 Speaker
        /// </summary>
        /// <param name="speakerNumber"></param>
        /// <param name="threshold"></param>
        /// <param name="useGPU"></param>
        public static void Init(int speakerNumber = 2, float threshold = 0.6f,bool useGPU = false)
        {
            Console.WriteLine("初始化 Speaker");
            var config = new OfflineSpeakerDiarizationConfig();
            //Pyannote模型地址
            config.Segmentation.Pyannote.Model = Path.Combine(AppCommon.AIModelFile, "sherpa-onnx-pyannote-segmentation-3-0", "model.onnx");
            //验证模型
            config.Embedding.Model = Path.Combine(AppCommon.AIModelFile, "wespeaker", "wespeaker_zh_cnceleb_resnet34_LM.onnx");
            //说话人数量
            config.Clustering.NumClusters = speakerNumber;
            config.Embedding.NumThreads = 4;
            //需要使用GPU
            if (!useGPU)
                config.Embedding.Provider = "cuda";
#if DEBUG
            config.Embedding.Debug = 1;
#endif

            //说话人判定阈值
            config.Clustering.Threshold = threshold;
            SD = new OfflineSpeakerDiarization(config);
        }
        /// <summary>
        /// 运行 说话人日志
        /// </summary>
        /// <param name="task"></param>
        public static async Task Run(string task)
        {
            var filePath = Path.Combine(task.LocalPath(), task + ".wav");
            if (string.IsNullOrEmpty(filePath) || !File.Exists(filePath))
                throw new Exception("task 音频路径未找到");

            if (SD is null)
                throw new Exception("Speaker 未进行初始化");
            var waveReader = new WaveReader(filePath);
            if (SD.SampleRate != waveReader.SampleRate)
                throw new Exception($"预期采样率:{SD.SampleRate}. 传入: {waveReader.SampleRate}");

            var i = 0;
            var segments = SD.ProcessWithCallback(waveReader.Samples,
                (numProcessedChunks, numTotalChunks, arg) =>
                {
                    i++;
                    if(i%20 !=0)
                        return 1;
                    var progress = (float)numProcessedChunks / numTotalChunks * 100;
                    RedisExpand.SetTaskProgress(task, progress);
                    return 1;
                }, nint.Zero);
            var res = segments.Select(s => new OfflineSpeakerRes(s));
            await RedisExpand.Redis.HSetAsync(RedisExpandKey.Task(task), "Speaker", res);
            //加入下一队列
            RedisExpand.InsertChannel(Enum.RedisChannelEnum.ChatModelAnalysis, task);

        }
    }
    /// <summary>
    /// 讲话人日志结果
    /// </summary>
    public class OfflineSpeakerRes
    {
        /// <summary>
        /// 总持续时间
        /// </summary>
        [JsonIgnore]
        public float Total => End - Start;
        /// <summary>
        /// 开始时间
        /// </summary>
        public float Start { get; set; }
        /// <summary>
        /// 结束时间
        /// </summary>
        public float End { get; set; }
        /// <summary>
        /// 讲话人索引
        /// </summary>
        public int SpeakerIndex { get; set; }

        /// <summary>
        /// 讲话人日志结果
        /// </summary>
        /// <param name="sds"></param>
        public OfflineSpeakerRes()
        {
        }
        /// <summary>
        /// 讲话人日志结果
        /// </summary>
        /// <param name="sds"></param>
        public OfflineSpeakerRes(OfflineSpeakerDiarizationSegment sds)
        {
            Start = (float)Math.Round(sds.Start, 2, MidpointRounding.AwayFromZero);
            End = (float)Math.Round(sds.End, 2, MidpointRounding.AwayFromZero);
            SpeakerIndex = sds.Speaker;
        }
    }
}