using System.Diagnostics.CodeAnalysis;
using StabilityMatrix.Core.Extensions;
using StabilityMatrix.Core.Models.Api.Comfy.NodeTypes;
using StabilityMatrix.Core.Models.Tokens;
namespace StabilityMatrix.Core.Models.Api.Comfy.Nodes;
///
/// Builder functions for comfy nodes
///
[SuppressMessage("ReSharper", "MemberCanBePrivate.Global")]
public class ComfyNodeBuilder
{
private readonly NodeDictionary nodes;
public ComfyNodeBuilder(NodeDictionary nodes)
{
this.nodes = nodes;
}
private static string GetRandomPrefix() => Guid.NewGuid().ToString()[..8];
public static NamedComfyNode VAEEncode(
string name,
ImageNodeConnection pixels,
VAENodeConnection vae
)
{
return new NamedComfyNode(name)
{
ClassType = "VAEEncode",
Inputs = new Dictionary
{
["pixels"] = pixels.Data,
["vae"] = vae.Data
}
};
}
public static NamedComfyNode VAEDecode(
string name,
LatentNodeConnection samples,
VAENodeConnection vae
)
{
return new NamedComfyNode(name)
{
ClassType = "VAEDecode",
Inputs = new Dictionary
{
["samples"] = samples.Data,
["vae"] = vae.Data
}
};
}
public static NamedComfyNode KSampler(
string name,
ModelNodeConnection model,
ulong seed,
int steps,
double cfg,
ComfySampler sampler,
ComfyScheduler scheduler,
ConditioningNodeConnection positive,
ConditioningNodeConnection negative,
LatentNodeConnection latentImage,
double denoise
)
{
return new NamedComfyNode(name)
{
ClassType = "KSampler",
Inputs = new Dictionary
{
["model"] = model.Data,
["seed"] = seed,
["steps"] = steps,
["cfg"] = cfg,
["sampler_name"] = sampler.Name,
["scheduler"] = scheduler.Name,
["positive"] = positive.Data,
["negative"] = negative.Data,
["latent_image"] = latentImage.Data,
["denoise"] = denoise
}
};
}
public static NamedComfyNode ImageUpscaleWithModel(
string name,
UpscaleModelNodeConnection upscaleModel,
ImageNodeConnection image
)
{
return new NamedComfyNode(name)
{
ClassType = "ImageUpscaleWithModel",
Inputs = new Dictionary
{
["upscale_model"] = upscaleModel.Data,
["image"] = image.Data
}
};
}
public static NamedComfyNode UpscaleModelLoader(
string name,
string modelName
)
{
return new NamedComfyNode(name)
{
ClassType = "UpscaleModelLoader",
Inputs = new Dictionary { ["model_name"] = modelName }
};
}
public static NamedComfyNode ImageScale(
string name,
ImageNodeConnection image,
string method,
int height,
int width,
bool crop
)
{
return new NamedComfyNode(name)
{
ClassType = "ImageScale",
Inputs = new Dictionary
{
["image"] = image.Data,
["upscale_method"] = method,
["height"] = height,
["width"] = width,
["crop"] = crop ? "center" : "disabled"
}
};
}
public static NamedComfyNode VAELoader(string name, string vaeModelName)
{
return new NamedComfyNode(name)
{
ClassType = "VAELoader",
Inputs = new Dictionary { ["vae_name"] = vaeModelName }
};
}
public static NamedComfyNode LoraLoader(
string name,
ModelNodeConnection model,
ClipNodeConnection clip,
string loraName,
double strengthModel,
double strengthClip
)
{
return new NamedComfyNode(name)
{
ClassType = "LoraLoader",
Inputs = new Dictionary
{
["model"] = model.Data,
["clip"] = clip.Data,
["lora_name"] = loraName,
["strength_model"] = strengthModel,
["strength_clip"] = strengthClip
}
};
}
public ImageNodeConnection Lambda_LatentToImage(
LatentNodeConnection latent,
VAENodeConnection vae
)
{
return nodes.AddNamedNode(VAEDecode($"{GetRandomPrefix()}_VAEDecode", latent, vae)).Output;
}
public LatentNodeConnection Lambda_ImageToLatent(
ImageNodeConnection pixels,
VAENodeConnection vae
)
{
return nodes.AddNamedNode(VAEEncode($"{GetRandomPrefix()}_VAEEncode", pixels, vae)).Output;
}
///
/// Create a group node that upscales a given image with a given model
///
public NamedComfyNode Group_UpscaleWithModel(
string name,
string modelName,
ImageNodeConnection image
)
{
var modelLoader = nodes.AddNamedNode(
UpscaleModelLoader($"{name}_UpscaleModelLoader", modelName)
);
var upscaler = nodes.AddNamedNode(
ImageUpscaleWithModel($"{name}_ImageUpscaleWithModel", modelLoader.Output, image)
);
return upscaler;
}
///
/// Create a group node that scales a given image to a given size
///
public NamedComfyNode Group_UpscaleToLatent(
string name,
LatentNodeConnection latent,
VAENodeConnection vae,
ComfyUpscaler upscaleInfo,
int width,
int height
)
{
if (upscaleInfo.Type == ComfyUpscalerType.Latent)
{
return nodes.AddNamedNode(
new NamedComfyNode($"{name}_LatentUpscale")
{
ClassType = "LatentUpscale",
Inputs = new Dictionary
{
["upscale_method"] = upscaleInfo.Name,
["width"] = width,
["height"] = height,
["crop"] = "disabled",
["samples"] = latent.Data,
}
}
);
}
if (upscaleInfo.Type == ComfyUpscalerType.ESRGAN)
{
// Convert to image space
var samplerImage = nodes.AddNamedNode(VAEDecode($"{name}_VAEDecode", latent, vae));
// Do group upscale
var modelUpscaler = Group_UpscaleWithModel(
$"{name}_ModelUpscale",
upscaleInfo.Name,
samplerImage.Output
);
// Since the model upscale is fixed to model (2x/4x), scale it again to the requested size
var resizedScaled = nodes.AddNamedNode(
ImageScale(
$"{name}_ImageScale",
modelUpscaler.Output,
"bilinear",
height,
width,
false
)
);
// Convert back to latent space
return nodes.AddNamedNode(VAEEncode($"{name}_VAEEncode", resizedScaled.Output, vae));
}
throw new InvalidOperationException($"Unknown upscaler type: {upscaleInfo.Type}");
}
///
/// Create a group node that scales a given image to image output
///
public NamedComfyNode Group_UpscaleToImage(
string name,
LatentNodeConnection latent,
VAENodeConnection vae,
ComfyUpscaler upscaleInfo,
int width,
int height
)
{
if (upscaleInfo.Type == ComfyUpscalerType.Latent)
{
var latentUpscale = nodes.AddNamedNode(
new NamedComfyNode($"{name}_LatentUpscale")
{
ClassType = "LatentUpscale",
Inputs = new Dictionary
{
["upscale_method"] = upscaleInfo.Name,
["width"] = width,
["height"] = height,
["crop"] = "disabled",
["samples"] = latent.Data,
}
}
);
// Convert to image space
return nodes.AddNamedNode(VAEDecode($"{name}_VAEDecode", latentUpscale.Output, vae));
}
if (upscaleInfo.Type == ComfyUpscalerType.ESRGAN)
{
// Convert to image space
var samplerImage = nodes.AddNamedNode(VAEDecode($"{name}_VAEDecode", latent, vae));
// Do group upscale
var modelUpscaler = Group_UpscaleWithModel(
$"{name}_ModelUpscale",
upscaleInfo.Name,
samplerImage.Output
);
// Since the model upscale is fixed to model (2x/4x), scale it again to the requested size
var resizedScaled = nodes.AddNamedNode(
ImageScale(
$"{name}_ImageScale",
modelUpscaler.Output,
"bilinear",
height,
width,
false
)
);
// No need to convert back to latent space
return resizedScaled;
}
throw new InvalidOperationException($"Unknown upscaler type: {upscaleInfo.Type}");
}
///
/// Create a group node that loads multiple Lora's in series
///
public NamedComfyNode Group_LoraLoadMany(
string name,
ModelNodeConnection model,
ClipNodeConnection clip,
IEnumerable<(string FileName, double? ModelWeight, double? ClipWeight)> loras
)
{
NamedComfyNode? currentNode = null;
foreach (var (i, loraNetwork) in loras.Enumerate())
{
currentNode = nodes.AddNamedNode(
LoraLoader(
$"{name}_LoraLoader_{i + 1}",
model,
clip,
loraNetwork.FileName,
loraNetwork.ModelWeight ?? 1,
loraNetwork.ClipWeight ?? 1
)
);
// Connect to previous node
model = currentNode.Output1;
clip = currentNode.Output2;
}
return currentNode ?? throw new InvalidOperationException("No lora networks given");
}
}