import 'dart:io';

import 'package:comfyui_api_sdk/comfyui_api_sdk.dart';
import 'package:uuid/uuid.dart';

bool jobFinished = false;

void main() async {
  // Create the API client
  final clientId = Uuid().v4().replaceAll('-', '');
  final api = ComfyUiApi(host: 'http://mennos-server:7860', clientId: clientId);

  // Connect to the WebSocket for progress updates
  await api.connectWebSocket();

  // Listen for progress updates
  api.onProgressChanged((progress) {
    print(
        '⏱️ Progress: ${progress.value} / ${progress.max} for ${progress.promptId}');
  });

  // Register for prompt start events
  api.onPromptStart((promptId) {
    print('🚀 Prompt started: $promptId');
  });

  // Register for prompt finished events
  api.onPromptFinished((promptId) async {
    print('✅ Prompt finished: $promptId');

    // Fetch the history when a prompt finishes
    try {
      final history = await api.getHistory(maxItems: 5);
      print('Recent history:');
      history.items.forEach((promptId, item) {
        print(' - $promptId: ${item.status.statusStr}');
      });

      final prompt = history.items[promptId];
      if (prompt != null) {
        print('🖼 Prompt $promptId: ${prompt.status.statusStr}');

        if (prompt.outputs.nodes.isNotEmpty) {
          for (var node in prompt.outputs.nodes.values) {
            for (var image in node.images) {
              print(
                  '    - Image: ${image.filename} URL: ${api.host}/api/view?filename=${image.filename}');

              // Write image to disk using image.fetchImageBytes(api.host)
              final bytes = await image.fetchImageBytes(api.host);

              // Ensure pwd/images exists
              Directory('images').createSync();

              // We can save this to the disk under $pwd/images/${image.filename}
              final file = File('images/${image.filename}');
              await file.writeAsBytes(bytes);
            }
          }
        }
      }
    } catch (e) {
      print('Error fetching history: $e');
    }

    jobFinished = true;
  });

  // Let's get a list of available checkpoints
  try {
    final checkpoints = await api.getCheckpoints();
    print('📦 Checkpoints: ${checkpoints.length}');
    for (var checkpoint in checkpoints) {
      print(' - ${checkpoint.name}');
    }
  } catch (e) {
    print('❌ Error fetching checkpoints: $e');
  }

  // Let's get a list of vaes
  try {
    final vaes = await api.getVaes();
    print('🧠 VAES: ${vaes.length}');
    for (var vae in vaes) {
      print(' - ${vae.name}');
    }
  } catch (e) {
    print('❌ Error fetching vaes: $e');
  }

  // Let's get a list of Loras
  try {
    final loras = await api.getLoras();
    print('📡 Loras: ${loras.length}');
    for (var lora in loras) {
      print(' - ${lora.name}');
    }
  } catch (e) {
    print('❌ Error fetching loras: $e');
  }

  // Let's get a list of possible samplers to use
  try {
    final samplers = await api.getKSamplers();
    print('🎲 Samplers: ${samplers.length}');
    for (var sampler in samplers) {
      print(' - ${sampler}');
    }
  } catch (e) {
    print('❌ Error fetching samplers: $e');
  }

  // Let's get a list of possible schedulers to use
  try {
    final schedulers = await api.getSchedulers();
    print('📅 Schedulers: ${schedulers.length}');
    for (var scheduler in schedulers) {
      print(' - ${scheduler}');
    }
  } catch (e) {
    print('❌ Error fetching schedulers: $e');
  }

  var randomSeed = DateTime.now().millisecondsSinceEpoch;

  // Fetch object info for validation (optional)
  Map<String, dynamic> objectInfo = {};
  try {
    objectInfo = await api.getObjectInfo();
  } catch (e) {
    print('❌ Error fetching object info: $e');
  }

  // Use PromptBuilder to create a workflow
  final promptBuilder = PromptBuilder(clientId: api.clientId)
    ..addNode(
      "CheckpointLoaderSimple",
      {"ckpt_name": "Anime/prefectPonyXL_v50.safetensors"},
      title: "Load Checkpoint",
      outputTags: {"MODEL": "model", "CLIP": "clip", "VAE": "vae"},
    )
    ..addNode(
      "EmptyLatentImage",
      {"width": 512, "height": 512, "batch_size": 1},
      title: "Empty Latent Image",
      outputTags: {"LATENT": "latent_image"},
    )
    ..addNode(
      "CLIPTextEncode",
      {
        "text": "beautiful scenery nature glass bottle landscape",
        "clip": ["clip", 1] // Explicitly use the "clip" output
      },
      title: "CLIP Text Encode (Positive Prompt)",
      outputTags: {"CONDITIONING": "positive_conditioning"},
    )
    ..addNode(
      "CLIPTextEncode",
      {
        "text": "negative, dark, scary, horror, spooky",
        "clip": ["clip", 1] // Explicitly use the "clip" output
      },
      title: "CLIP Text Encode (Negative Prompt)",
      outputTags: {"CONDITIONING": "negative_conditioning"},
    )
    ..addNode(
      "KSampler",
      {
        "seed": randomSeed,
        "steps": 25,
        "cfg": 4,
        "sampler_name": "euler",
        "scheduler": "normal",
        "denoise": 1,
        "model": ["model", 0], // Explicitly use the "model" output
        "positive": [
          "positive_conditioning",
          0
        ], // Explicitly use the positive conditioning
        "negative": [
          "negative_conditioning",
          0
        ], // Explicitly use the negative conditioning
        "latent_image": ["latent_image", 0] // Explicitly use the latent image
      },
      title: "KSampler",
      outputTags: {"LATENT": "denoised_latent"},
    )
    ..addNode(
      "VAEDecode",
      {
        "samples": ["denoised_latent", 0], // Explicitly use the denoised latent
        "vae": ["vae", 2] // Explicitly use the "vae" output
      },
      title: "VAE Decode",
      outputTags: {"IMAGE": "final_image"},
    )
    ..addNode(
      "SaveImage",
      {
        "filename_prefix": "ComfyUI",
        "images": ["final_image", 0] // Explicitly use the final image
      },
      title: "Save Image",
    );

  // Validate the workflow (optional)
  try {
    promptBuilder.validate(objectInfo);
  } catch (e) {
    print('❌ Validation error: $e');
    return;
  }

  // Submit the workflow
  try {
    final result = await api.submitPrompt(promptBuilder.build());
    print('💼 Prompt submitted: ${result.promptId}');
  } catch (e) {
    print('❌ Error submitting prompt: $e');
  }

  // Wait until job is finished
  while (!jobFinished) {
    await Future.delayed(Duration(seconds: 1));
  }

  // Clean up
  api.dispose();
}