using DataAccess.Data;
using DataAccess.Models;
using Radzen;
using System.Diagnostics;

namespace KIKunstKirstenKlöckner.Data;

public class ImageGenerator
{
    private readonly HttpClient _client = new();
    private readonly BildInfoData _bildInfoData;

    public ImageGenerator(IConfiguration config, BildInfoData bildInfoData)
    {
        _bildInfoData = bildInfoData;

        string? inferenceApiKey = config.GetValue<string>("API:HF_Inference");

        _client.DefaultRequestHeaders.Clear();
        _client.DefaultRequestHeaders.Add("Authorization", $"Bearer {inferenceApiKey}");
    }
    
    /// <summary>
    /// Geneiert das Bild für den aktuellen <see cref="_imagePrompt"/>
    /// </summary>
    public async Task<string?> GenerateImageAsync(string prompt, string negativePromt, int? width, int? height, WunschInfoModel wunschInfo, bool isRetry = false)
    {
        var postData = new
        {
            inputs = prompt,
            parameters = new 
            {
                negative_prompt = negativePromt, //"photorealistic, highly detailed, 8K, portrait",
                width = width,
                height = height
            },
            options = new
            {
                // Cache deaktivieren, damit Huggingface für den selben Prompt unterschiedliche Ergebnisse liefert
                use_cache = false,
                // Erst wenn wir bereits in einem retry sind warten wir implizit auf das Model. (ignoriert quasi 503-Fehler)
                wait_for_model = true
            }
        };

        JsonContent content = JsonContent.Create(postData);

        try
        {
            //const string modelName = "Nacken/kkkk-sdxl-5000";
            const string modelName = "Nacken/kkk-sdxl-18000";

            var inferenceModelUrl = $"https://api-inference.huggingface.co/models/{modelName}";

            var response = await _client.PostAsync(inferenceModelUrl, content);

            if (response?.IsSuccessStatusCode == true)
            {
                await using Stream imageStream = await response.Content.ReadAsStreamAsync();

                using Image image = await Image.LoadAsync(imageStream);

                DateTime imageDate = DateTime.Now;
                
                BildInfoModel bildInfo = new()
                {
                    Dateiname = "PlaceHolder",
                    Datum = imageDate,
                    ImageModel = modelName,
                    WunschId = wunschInfo.Id
                };
                
                await _bildInfoData.AddBildInfoAsync(bildInfo);

                string imgUrl = $"generated_images/Image_{bildInfo.Id}.jpg";

                string mapPath = $"./wwwroot/{imgUrl}";
                await image.SaveAsJpegAsync(mapPath);

                bildInfo.Dateiname = imgUrl;
                await _bildInfoData.UpdateBildInfoDateinameAsync(bildInfo);

                return imgUrl;
            }
            else
            {
                Console.WriteLine($"Image conversion failed: {response}");

                if (Debugger.IsAttached)
                    Debugger.Break();

                return null;
            }
        }
        catch (Exception exception)
        {
            Console.WriteLine($"Image request failed: {exception}");

            if (Debugger.IsAttached)
                Debugger.Break();

            return null;
        }
    }
}