Multi-Platform Package Manager for Stable Diffusion
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using System.Diagnostics.CodeAnalysis;
using System.Drawing;
using StabilityMatrix.Core.Extensions;
using StabilityMatrix.Core.Models.Api.Comfy.NodeTypes;
using StabilityMatrix.Core.Models.Database;
using StabilityMatrix.Core.Models.Tokens;
namespace StabilityMatrix.Core.Models.Api.Comfy.Nodes;
/// <summary>
/// Builder functions for comfy nodes
/// </summary>
[SuppressMessage("ReSharper", "MemberCanBePrivate.Global")]
public class ComfyNodeBuilder
{
public NodeDictionary Nodes { get; } = new();
public Dictionary<Type, NodeConnectionBase> GlobalConnections { get; } = new();
private static string GetRandomPrefix() => Guid.NewGuid().ToString()[..8];
public static NamedComfyNode<LatentNodeConnection> VAEEncode(
string name,
ImageNodeConnection pixels,
VAENodeConnection vae
)
{
return new NamedComfyNode<LatentNodeConnection>(name)
{
ClassType = "VAEEncode",
Inputs = new Dictionary<string, object?>
{
["pixels"] = pixels.Data,
["vae"] = vae.Data
}
};
}
public static NamedComfyNode<ImageNodeConnection> VAEDecode(
string name,
LatentNodeConnection samples,
VAENodeConnection vae
)
{
return new NamedComfyNode<ImageNodeConnection>(name)
{
ClassType = "VAEDecode",
Inputs = new Dictionary<string, object?>
{
["samples"] = samples.Data,
["vae"] = vae.Data
}
};
}
public static NamedComfyNode<LatentNodeConnection> 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<LatentNodeConnection>(name)
{
ClassType = "KSampler",
Inputs = new Dictionary<string, object?>
{
["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<LatentNodeConnection> KSamplerAdvanced(
string name,
ModelNodeConnection model,
bool addNoise,
ulong noiseSeed,
int steps,
double cfg,
ComfySampler sampler,
ComfyScheduler scheduler,
ConditioningNodeConnection positive,
ConditioningNodeConnection negative,
LatentNodeConnection latentImage,
int startAtStep,
int endAtStep,
bool returnWithLeftoverNoise
)
{
return new NamedComfyNode<LatentNodeConnection>(name)
{
ClassType = "KSamplerAdvanced",
Inputs = new Dictionary<string, object?>
{
["model"] = model.Data,
["add_noise"] = addNoise ? "enable" : "disable",
["noise_seed"] = noiseSeed,
["steps"] = steps,
["cfg"] = cfg,
["sampler_name"] = sampler.Name,
["scheduler"] = scheduler.Name,
["positive"] = positive.Data,
["negative"] = negative.Data,
["latent_image"] = latentImage.Data,
["start_at_step"] = startAtStep,
["end_at_step"] = endAtStep,
["return_with_leftover_noise"] = returnWithLeftoverNoise ? "enable" : "disable"
}
};
}
public static NamedComfyNode<LatentNodeConnection> EmptyLatentImage(
string name,
int batchSize,
int height,
int width
)
{
return new NamedComfyNode<LatentNodeConnection>(name)
{
ClassType = "EmptyLatentImage",
Inputs = new Dictionary<string, object?>
{
["batch_size"] = batchSize,
["height"] = height,
["width"] = width,
}
};
}
public static NamedComfyNode<LatentNodeConnection> LatentFromBatch(
string name,
LatentNodeConnection samples,
int batchIndex,
int length
)
{
return new NamedComfyNode<LatentNodeConnection>(name)
{
ClassType = "LatentFromBatch",
Inputs = new Dictionary<string, object?>
{
["samples"] = samples.Data,
["batch_index"] = batchIndex,
["length"] = length,
}
};
}
public static NamedComfyNode<ImageNodeConnection> ImageUpscaleWithModel(
string name,
UpscaleModelNodeConnection upscaleModel,
ImageNodeConnection image
)
{
return new NamedComfyNode<ImageNodeConnection>(name)
{
ClassType = "ImageUpscaleWithModel",
Inputs = new Dictionary<string, object?>
{
["upscale_model"] = upscaleModel.Data,
["image"] = image.Data
}
};
}
public static NamedComfyNode<UpscaleModelNodeConnection> UpscaleModelLoader(
string name,
string modelName
)
{
return new NamedComfyNode<UpscaleModelNodeConnection>(name)
{
ClassType = "UpscaleModelLoader",
Inputs = new Dictionary<string, object?> { ["model_name"] = modelName }
};
}
public static NamedComfyNode<ImageNodeConnection> ImageScale(
string name,
ImageNodeConnection image,
string method,
int height,
int width,
bool crop
)
{
return new NamedComfyNode<ImageNodeConnection>(name)
{
ClassType = "ImageScale",
Inputs = new Dictionary<string, object?>
{
["image"] = image.Data,
["upscale_method"] = method,
["height"] = height,
["width"] = width,
["crop"] = crop ? "center" : "disabled"
}
};
}
public static NamedComfyNode<VAENodeConnection> VAELoader(string name, string vaeModelName)
{
return new NamedComfyNode<VAENodeConnection>(name)
{
ClassType = "VAELoader",
Inputs = new Dictionary<string, object?> { ["vae_name"] = vaeModelName }
};
}
public static NamedComfyNode<ModelNodeConnection, ClipNodeConnection> LoraLoader(
string name,
ModelNodeConnection model,
ClipNodeConnection clip,
string loraName,
double strengthModel,
double strengthClip
)
{
return new NamedComfyNode<ModelNodeConnection, ClipNodeConnection>(name)
{
ClassType = "LoraLoader",
Inputs = new Dictionary<string, object?>
{
["model"] = model.Data,
["clip"] = clip.Data,
["lora_name"] = loraName,
["strength_model"] = strengthModel,
["strength_clip"] = strengthClip
}
};
}
public static NamedComfyNode<ModelNodeConnection> CheckpointLoaderSimple(
string name,
string modelName
)
{
return new NamedComfyNode<ModelNodeConnection>(name)
{
ClassType = "CheckpointLoaderSimple",
Inputs = new Dictionary<string, object?> { ["ckpt_name"] = modelName }
};
}
public static NamedComfyNode<ModelNodeConnection> FreeU(
string name,
ModelNodeConnection model,
double b1,
double b2,
double s1,
double s2
)
{
return new NamedComfyNode<ModelNodeConnection>(name)
{
ClassType = "FreeU",
Inputs = new Dictionary<string, object?>
{
["model"] = model.Data,
["b1"] = b1,
["b2"] = b2,
["s1"] = s1,
["s2"] = s2
}
};
}
public static NamedComfyNode<ConditioningNodeConnection> ClipTextEncode(
string name,
ClipNodeConnection clip,
string text
)
{
return new NamedComfyNode<ConditioningNodeConnection>(name)
{
ClassType = "CLIPTextEncode",
Inputs = new Dictionary<string, object?> { ["clip"] = clip.Data, ["text"] = text }
};
}
/// <summary>
/// Create a LoadImage node.
/// </summary>
/// <param name="name">Name of the node</param>
/// <param name="relativeInputPath">Path relative to the Comfy input directory</param>
public static NamedComfyNode<ImageNodeConnection, ImageMaskConnection> LoadImage(
string name,
string relativeInputPath
)
{
return new NamedComfyNode<ImageNodeConnection, ImageMaskConnection>(name)
{
ClassType = "LoadImage",
Inputs = new Dictionary<string, object?> { ["image"] = relativeInputPath }
};
}
public static NamedComfyNode<ImageNodeConnection> ImageSharpen(
string name,
ImageNodeConnection image,
int sharpenRadius,
double sigma,
double alpha
)
{
return new NamedComfyNode<ImageNodeConnection>(name)
{
ClassType = "ImageSharpen",
Inputs = new Dictionary<string, object?>
{
["image"] = image.Data,
["sharpen_radius"] = sharpenRadius,
["sigma"] = sigma,
["alpha"] = alpha
}
};
}
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;
}
/// <summary>
/// Get a global connection for a given type
/// </summary>
public TConnection GetConnection<TConnection>()
where TConnection : NodeConnectionBase
{
if (GlobalConnections.TryGetValue(typeof(TConnection), out var connection))
{
return (TConnection)connection;
}
throw new InvalidOperationException($"No global connection of type {typeof(TConnection)}");
}
/// <summary>
/// Set a global connection for a given type
/// </summary>
public void SetConnection<TConnection>(TConnection connection)
where TConnection : NodeConnectionBase
{
GlobalConnections[typeof(TConnection)] = connection;
}
/// <summary>
/// Create a group node that upscales a given image with a given model
/// </summary>
public NamedComfyNode<ImageNodeConnection> Group_UpscaleWithModel(
string name,
string modelName,
ImageNodeConnection image
)
{
var modelLoader = Nodes.AddNamedNode(
UpscaleModelLoader($"{name}_UpscaleModelLoader", modelName)
);
var upscaler = Nodes.AddNamedNode(
ImageUpscaleWithModel($"{name}_ImageUpscaleWithModel", modelLoader.Output, image)
);
return upscaler;
}
/// <summary>
/// Create a group node that scales a given image to a given size
/// </summary>
public NamedComfyNode<LatentNodeConnection> Group_UpscaleToLatent(
string name,
LatentNodeConnection latent,
VAENodeConnection vae,
ComfyUpscaler upscaleInfo,
int width,
int height
)
{
if (upscaleInfo.Type == ComfyUpscalerType.Latent)
{
return Nodes.AddNamedNode(
new NamedComfyNode<LatentNodeConnection>($"{name}_LatentUpscale")
{
ClassType = "LatentUpscale",
Inputs = new Dictionary<string, object?>
{
["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($"Unknown upscaler type: {upscaleInfo.Type}");
}
/// <summary>
/// Create a group node that scales a given image to image output
/// </summary>
public NamedComfyNode<ImageNodeConnection> Group_LatentUpscaleToImage(
string name,
LatentNodeConnection latent,
VAENodeConnection vae,
ComfyUpscaler upscaleInfo,
int width,
int height
)
{
if (upscaleInfo.Type == ComfyUpscalerType.Latent)
{
var latentUpscale = Nodes.AddNamedNode(
new NamedComfyNode<LatentNodeConnection>($"{name}_LatentUpscale")
{
ClassType = "LatentUpscale",
Inputs = new Dictionary<string, object?>
{
["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}");
}
/// <summary>
/// Create a group node that scales a given image to image output
/// </summary>
public NamedComfyNode<ImageNodeConnection> Group_UpscaleToImage(
string name,
ImageNodeConnection image,
ComfyUpscaler upscaleInfo,
int width,
int height
)
{
if (upscaleInfo.Type == ComfyUpscalerType.Latent)
{
return Nodes.AddNamedNode(
new NamedComfyNode<ImageNodeConnection>($"{name}_LatentUpscale")
{
ClassType = "ImageScale",
Inputs = new Dictionary<string, object?>
{
["image"] = image,
["upscale_method"] = upscaleInfo.Name,
["width"] = width,
["height"] = height,
["crop"] = "disabled",
}
}
);
}
if (upscaleInfo.Type == ComfyUpscalerType.ESRGAN)
{
// Do group upscale
var modelUpscaler = Group_UpscaleWithModel(
$"{name}_ModelUpscale",
upscaleInfo.Name,
image
);
// 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}");
}
/// <summary>
/// Create a group node that loads multiple Lora's in series
/// </summary>
public NamedComfyNode<ModelNodeConnection, ClipNodeConnection> Group_LoraLoadMany(
string name,
ModelNodeConnection model,
ClipNodeConnection clip,
IEnumerable<(string FileName, double? ModelWeight, double? ClipWeight)> loras
)
{
NamedComfyNode<ModelNodeConnection, ClipNodeConnection>? 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");
}
/// <summary>
/// Create a group node that loads multiple Lora's in series
/// </summary>
public NamedComfyNode<ModelNodeConnection, ClipNodeConnection> Group_LoraLoadMany(
string name,
ModelNodeConnection model,
ClipNodeConnection clip,
IEnumerable<(LocalModelFile ModelFile, double? ModelWeight, double? ClipWeight)> loras
)
{
NamedComfyNode<ModelNodeConnection, ClipNodeConnection>? currentNode = null;
foreach (var (i, loraNetwork) in loras.Enumerate())
{
currentNode = Nodes.AddNamedNode(
LoraLoader(
$"{name}_LoraLoader_{i + 1}",
model,
clip,
loraNetwork.ModelFile.RelativePathFromSharedFolder,
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");
}
/// <summary>
/// Convert to a NodeDictionary
/// </summary>
public NodeDictionary ToNodeDictionary()
{
Nodes.NormalizeConnectionTypes();
return Nodes;
}
public class NodeBuilderConnections
{
public ulong Seed { get; set; }
public ModelNodeConnection? BaseModel { get; set; }
public VAENodeConnection? BaseVAE { get; set; }
public ClipNodeConnection? BaseClip { get; set; }
public ConditioningNodeConnection? BaseConditioning { get; set; }
public ConditioningNodeConnection? BaseNegativeConditioning { get; set; }
public ModelNodeConnection? RefinerModel { get; set; }
public VAENodeConnection? RefinerVAE { get; set; }
public ClipNodeConnection? RefinerClip { get; set; }
public ConditioningNodeConnection? RefinerConditioning { get; set; }
public ConditioningNodeConnection? RefinerNegativeConditioning { get; set; }
public LatentNodeConnection? Latent { get; set; }
public Size LatentSize { get; set; }
public ImageNodeConnection? Image { get; set; }
public Size ImageSize { get; set; }
public List<NamedComfyNode> OutputNodes { get; } = new();
public IEnumerable<string> OutputNodeNames => OutputNodes.Select(n => n.Name);
/// <summary>
/// Gets the latent size scaled by a given factor
/// </summary>
public Size GetScaledLatentSize(double scale)
{
return new Size(
(int)Math.Floor(LatentSize.Width * scale),
(int)Math.Floor(LatentSize.Height * scale)
);
}
/// <summary>
/// Gets the image size scaled by a given factor
/// </summary>
public Size GetScaledImageSize(double scale)
{
return new Size(
(int)Math.Floor(ImageSize.Width * scale),
(int)Math.Floor(ImageSize.Height * scale)
);
}
public VAENodeConnection GetRefinerOrBaseVAE()
{
return RefinerVAE ?? BaseVAE ?? throw new NullReferenceException("No VAE");
}
public ModelNodeConnection GetRefinerOrBaseModel()
{
return RefinerModel ?? BaseModel ?? throw new NullReferenceException("No Model");
}
public ConditioningNodeConnection GetRefinerOrBaseConditioning()
{
return RefinerConditioning
?? BaseConditioning
?? throw new NullReferenceException("No Conditioning");
}
public ConditioningNodeConnection GetRefinerOrBaseNegativeConditioning()
{
return RefinerNegativeConditioning
?? BaseNegativeConditioning
?? throw new NullReferenceException("No Negative Conditioning");
}
}
public NodeBuilderConnections Connections { get; } = new();
}