using System.Text;
using System.Text.Json;
using eprintServer.Enums;
using eprintServer.Interfaces;
using eprintServer.Requests;
using System.Text.Json.Serialization;
namespace eprintServer.Services
{
    public class GeminiService : IGeminiService
    {
        private readonly HttpClient _httpClient;
        private readonly IConfiguration _configuration;
       private readonly ILogger<GeminiService> _logger;

    public GeminiService(
        HttpClient httpClient, 
        IConfiguration configuration,
        ILogger<GeminiService> logger) // Add <GeminiService>
    {
        _httpClient = httpClient;
        _configuration = configuration;
        _logger = logger;
    }
    
public async Task<ImageGenerationResponse> GenerateImageAsync(GeminiImageRequest request)
{
    var apiKey = "0bb245be-d2f2-4e5a-9701-e88b654f5f6e:e145463c60171124fd3cb84801b5567e";
    var url = "https://fal.run/fal-ai/flux/schnell";

    var falRequest = new
    {
        prompt = request.Prompt,
        image_size = request.AspectRatio switch
        {
            "16:9" => "landscape_16_9",
            "9:16" => "portrait_16_9",
            "4:3" => "landscape_4_3",
            "3:4" => "portrait_4_3",
            _ => "square"
        },
        num_inference_steps = 4,
        num_images = 1,
        enable_safety_checker = false
    };

    var httpRequest = new HttpRequestMessage(HttpMethod.Post, url);
    httpRequest.Headers.Add("Authorization", $"Key {apiKey}");
    httpRequest.Content = new StringContent(
        JsonSerializer.Serialize(falRequest),
        Encoding.UTF8,
        "application/json");

    _logger.LogInformation("Sending request to Fal.ai with prompt: {Prompt}", request.Prompt);

    var response = await _httpClient.SendAsync(httpRequest);
    var content = await response.Content.ReadAsStringAsync();

    _logger.LogInformation("Fal.ai response status: {StatusCode}, Content: {Content}", 
        response.StatusCode, content);

    if (!response.IsSuccessStatusCode)
    {
        _logger.LogError($"Fal.ai API error ({response.StatusCode}): {content}");
        throw new HttpRequestException($"Fal.ai API error: {response.StatusCode}");
    }

    var falResponse = JsonSerializer.Deserialize<FalAiResponse>(content);

    // Log the response structure to debug
    _logger.LogInformation("Parsed Fal.ai response: {Response}", 
        JsonSerializer.Serialize(falResponse));

    if (falResponse?.Images != null && falResponse.Images.Length > 0)
    {
        var imageUrl = falResponse.Images[0].Url;
        _logger.LogInformation("Image URL received: {Url}", imageUrl);

        // Download the image and convert to base64
        using var imageClient = new HttpClient();
        var imageBytes = await imageClient.GetByteArrayAsync(imageUrl);
        var base64Image = Convert.ToBase64String(imageBytes);
        
        _logger.LogInformation("Successfully converted image to base64, size: {Size} bytes", 
            imageBytes.Length);
        
        return new ImageGenerationResponse
        {
            Url = $"data:image/png;base64,{base64Image}",
            Width = falResponse.Images[0].Width,
            Height = falResponse.Images[0].Height
        };
    }

    _logger.LogError("No images found in Fal.ai response");
    throw new InvalidOperationException("No image data returned from Fal.ai");
}
public class FalAiResponse
{
    [JsonPropertyName("images")]
    public FalAiImage[] Images { get; set; }
    
    [JsonPropertyName("timings")]
    public object Timings { get; set; }
    
    [JsonPropertyName("seed")]
    public long Seed { get; set; }
    
    [JsonPropertyName("has_nsfw_concepts")]
    public bool[] HasNsfwConcepts { get; set; }
    
    [JsonPropertyName("prompt")]
    public string Prompt { get; set; }
}

public class FalAiImage
{
    [JsonPropertyName("url")]
    public string Url { get; set; }
    
    [JsonPropertyName("width")]
    public int Width { get; set; }
    
    [JsonPropertyName("height")]
    public int Height { get; set; }
    
    [JsonPropertyName("content_type")]
    public string ContentType { get; set; }
}
public async Task<ImageGenerationResponse> EditImageAsync(GeminiEditRequest request)
{
    var apiKey = "0bb245be-d2f2-4e5a-9701-e88b654f5f6e:e145463c60171124fd3cb84801b5567e";
    var url = "https://fal.run/fal-ai/flux/schnell/image-to-image";

    // Convert base64 to proper format if needed
    var imageData = request.ImageBase64;
    if (imageData.StartsWith("data:"))
    {
        imageData = imageData.Split(',')[1];
    }

    var falRequest = new
    {
        prompt = request.Prompt,
        image_url = $"data:image/jpeg;base64,{imageData}",
        image_size = request.AspectRatio switch
        {
            "16:9" => "landscape_16_9",
            "9:16" => "portrait_16_9",
            "4:3" => "landscape_4_3",
            "3:4" => "portrait_4_3",
            _ => "square"
        },
        num_inference_steps = 4,
        strength = 0.8, // How much to change the image (0.0 - 1.0)
        num_images = 1
    };

    var httpRequest = new HttpRequestMessage(HttpMethod.Post, url);
    httpRequest.Headers.Add("Authorization", $"Key {apiKey}");
    httpRequest.Content = new StringContent(
        JsonSerializer.Serialize(falRequest),
        Encoding.UTF8,
        "application/json");

    _logger.LogInformation("Sending image edit request to Fal.ai with prompt: {Prompt}", request.Prompt);

    var response = await _httpClient.SendAsync(httpRequest);
    var content = await response.Content.ReadAsStringAsync();

    _logger.LogInformation("Fal.ai edit response status: {StatusCode}, Content: {Content}", 
        response.StatusCode, content);

    if (!response.IsSuccessStatusCode)
    {
        _logger.LogError($"Fal.ai API error ({response.StatusCode}): {content}");
        throw new HttpRequestException($"Fal.ai API error: {response.StatusCode}");
    }

    var falResponse = JsonSerializer.Deserialize<FalAiResponse>(content);

    if (falResponse?.Images != null && falResponse.Images.Length > 0)
    {
        var imageUrl = falResponse.Images[0].Url;
        _logger.LogInformation("Image URL received: {Url}", imageUrl);

        // Download the image and convert to base64
        using var imageClient = new HttpClient();
        var imageBytes = await imageClient.GetByteArrayAsync(imageUrl);
        var base64Image = Convert.ToBase64String(imageBytes);
        
        _logger.LogInformation("Successfully converted edited image to base64, size: {Size} bytes", 
            imageBytes.Length);
        
        return new ImageGenerationResponse
        {
            Url = $"data:image/png;base64,{base64Image}",
            Width = falResponse.Images[0].Width,
            Height = falResponse.Images[0].Height
        };
    }

    _logger.LogError("No images found in Fal.ai edit response");
    throw new InvalidOperationException("No image data returned from Fal.ai");
}
    }
}