ComfyUI-YogurtNodes
ComfyUI-YogurtNodes is a collection of custom nodes for ComfyUI, providing a series of practical image processing and workflow enhancement functionalities.
Nodes (184)
Slap a caption on your output — before it leaves ComfyUI
A pass-through node with thirty-two built-in sinks
Up to 32 images, one batch — without the resolution headache
Seedream Has Two Doors and This Is the One You Can Pay For
Pick a checkpoint and get its filename as a string — the automation enabler
Claude Chat Wants No Anthropic Key, and That's the Whole Trick
Pull one node's results out of a remote run — by id or by title
Run a whole workflow on another ComfyUI — this node is the remote
Submit and wait — the node that actually fires the remote job
Dial the remote workflow's decimals from your local graph
Upload a local image into the remote workflow's Load Image node
Patch an integer input on the remote workflow, mid-graph
Seed every sampler on the remote in one shot
Write the prompt into the remote workflow, from a local string
Sew the repainted crops back onto the base image, seams invisible
Pick a ControlNet by name without a second loader in sight
Rename LoRA keys by JSON — the fix when a LoRA just won't load
The two-wire node that quietly un-breaks your save paths
The translation table when one LoRA's keys don't fit another
One input, one output, and a footgun hidden in the name
Crop only the regions your mask wants repainted — dynamic, not fixed
For the Model That Shipped After the Pack Did
Type a Model ID, See What Bites
Qwen Image and Wan, If You Pick the Right Continent
The 'how big is this thing' node your workflows quietly need
Pickle round-trip for any Python object — and the security warning that comes with it
Ask 'is this key there?' and get a boolean back
Check for a value in any dict — handy when you care about contents, not names
Slice a dict down to the entries you actually care about
Two lists in, one dict out — with an escape hatch for ragged lists
Pull a value out of any dict without the KeyError ambush
Flip a dict upside down — values become keys, with a duplicate-safety switch
See what a dict actually contains — the debugging node you'll use constantly
How many keys are in this dict? An integer, instantly
Slam up to 32 dicts together — and decide who wins the collisions
Extract just the fields you need from a dict
Strip a dict down to its contents — keys optional
A dropdown for diffusion models that hands the trigger word along too
The node with 32 inputs, no outputs, and one very specific job
Generate images from a cloud API, no local GPU required
The obscure 'unrestricted' LLM node, for when you need it
Ask a cloud vision model what's actually in your image
The Unfiltered Endpoint With Almost No Paper Trail
The Safety Slider Is the Interesting Part
Google's image model, piped straight into your ComfyUI graph
Gemini 2.5 in your graph — with chat history and the thinking shown
Your images, described by Gemini — no local model, no VRAM cost
Nine outputs off one wire, and the quiet workhorse of adaptive workflows
Feed a whole folder of images into ComfyUI without typing paths by hand
The AI Studio Provider
Point Gemini Nodes at Someone Else's Server
Vision Prompts and the Preamble Problem
Sizes, Transparency, and Where the Moderation Dial Sits
The VLM That Refuses Less Than the Others
Closed-source image gen inside ComfyUI, with zero local VRAM spent
An LLM in the graph for prompt-writing, captioning, and workflow logic
A vision model that reads your images and feeds the answer back in
Three Reference Images and No Lecture
Nano Banana without a GPU — GRSAI's hosted image API, in your graph
The Relay Provider With No Paper Trail At All
Giving the pack's LLM nodes a memory across turns
Put detail back into soft upscales — a frequency-split restore with knobs
Crop exactly to the mask — and get the coordinates back
Resize to a pixel budget, not a resolution — with a mask proving it
The crop-and-stitch upscale pipeline, minus the seams
Sew your tiles back together without the seam lines
The tiny boolean check that keeps your workflows from derailing
Copy a JSON object so mutating it doesn't wreck the original
Turn a nested config into flat keys — and back again
Pull one value out of a JSON blob with a path, not a pile of nodes
Merge JSON objects the deep way — no more lost keys
Turn a JSON string into a real object the graph can use
Ask 'is this key there?' before you try to read it
Write one value into a nested JSON object without rebuilding it
Turn an object back into text — for loggers, LLMs, and API payloads
Reassemble flat keys into the nested JSON you actually wanted
Confirm your JSON is the right shape before you trust it
One node for union, intersection, zips, and every other two-list trick
Jam up to 32 lists into one — the merge your batch workflow is missing
One Boolean that decides your whole workflow
Keep only the list items you actually want
Where in the list is it? Ask ListFind
Grab the Nth thing out of any list — including backwards
You have a list. Make it a sentence.
Count what you've got before you loop over it
Slice a list the Python way — mind the stop value
Dedupe a list without scrambling the order
Feed audio into ComfyUI without fighting the file browser
Load audio from a path, not the input folder
Raw file bytes in — the boring bridge node that makes automation work
Yes, it's basically LoadImage — and that's fine
Load an image from a path, not from the input dropdown
Load a LoRA without applying it — the front door to LoRA surgery
Pull a video in, trim it, feed your video workflow
Get a video into your graph without a file browser, with a time range
Merging a rank-128 style with a rank-8 character without the wreckage
Surgically zeroing or scaling specific blocks inside a LoRA
Merge up to five LoRAs into one file — exactly, not approximately
Shrink a LoRA's rank with SVD without trashing its effect
Bake a LoRA's strength into its alpha so you can just use 1.0
Turn a weak LoRA into a strong one by scaling the tensors themselves
A LoRA picker that hands you the metadata too
Two LoRAs, one weighted sum — the quick blend, not the exact merge
Before you regex your LoRA into pieces, look at its keys
It Invents the Detail, That's the Feature
The paid upscaler, wired straight into your graph
Keep the Photo, Add the Pixels
One Key, Two Upscale Nodes, a Long Wait
Plan crop-first repaint tiles so you don't regenerate the whole image
Applying a LoRA that's already a graph object, not a filename
Fourteen Reference Images in One Node
The Node That Outputs Nothing (And Why You'll Want It)
Point ComfyUI at Ollama, LM Studio, or Any Relay
Generate Images With OpenAI, Straight Into a Sampler-Ready Tensor
An LLM Call, Wired Straight Into Your Workflow Logic
Ask a Vision Model About Your Image, In-Graph
What the Blank Key Field Actually Does
Image Generation via OpenRouter
Text Generation via OpenRouter
One API key, every vision model — this node shops for you
OpenRouter — one key, and a vote on who actually runs your model
Bundle 32 Values Down One Wire
Path Math Without Opening a Terminal
Compositing that makes the pasted object stop looking pasted
The node that shows you what's actually flowing through that wire
Preview Any Data as Text (While It Passes Through)
Preview Your Images Wherever They're Flowing
The End-of-Branch Twin of the Image Preview Bridge
See Your Masks Without Ending the Branch
See your mask in the graph while the dims ride along
See Your Repaint Tiles Before You Commit Compute
Qwen Image Generation and Editing, Via Alibaba's DashScope
Qwen Image — the 20B model nobody runs, called from a node instead
A Range Node for LoRA Sweeps and Batch Runs
Grab One Value Out of a Range
Extract and Rewrite Text With Regex, Inside Your Graph
Fix Ugly Delimiters in One Node
Swapping one bad frame out of a video batch without the rebuild
Save Raw Bytes (Not Just Images) to Your Output Folder
Save Bytes Mid-Graph Without Ending the Line
The save node that doesn't stop the graph
The save bridge, but with any file extension you want
Save anywhere, in any format, without the spotlight
Saving without showing up in the output list
The save bridge with the settings stripped out
A no-frills save that stays out of the results
Save a LoRA state back to disk, not just load one
Save masks like you save images — and keep them in the graph
Save masks in any format the pack's plain node won't
The flexible mask saver that keeps its head down
Mask saver that writes the file and skips the spotlight
The four-knob mask saver
The quietest way to save a mask
Write text, JSON, or markdown to disk without ending the graph
The text logger that never shows up in results
Seedream — ByteDance's image model, the one with no weights to download
ByteDance's Seedream, dropped straight into your graph
Stuff any Python object into a bytes file
Connected components for repaint workflows
Turn one file path into six useful pieces
Stitch up to eight strings together, and toggle each one
Python's f-string, minus the f, for prompts that build themselves
Glue text together without a tangle of catenate nodes
Count the lines in your prompt lists, so your workflow knows how much it's about to do
Pull line 3 out of a prompt list and feed it somewhere else
Turn one comma-separated text blob into a real list
The fastest way to turn '42' into a number ComfyUI can actually use
A regex-powered case statement for your workflow
The glue node that makes tiled upscaling graphs actually wire together
Turn key-value pairs into a real dictionary, with a safety net for missing values
The type-coercion node that makes stubborn data fit the list sockets
Topaz Generative Upscale — when the image doesn't have the detail to begin with
The paid upscaling baseline, as a cloud call in your workflow
Topaz Labs — your Topaz credits, straight from the graph
Topaz Upscale — bigger pixels, without giving the model permission to invent
The other half of PackAny — split one bundled wire back into up to 32 outputs
Gemini image generation, inside your local ComfyUI graph — if you can stomach the GCP setup
A Gemini text node that does either AI Studio or Vertex — your pick
Give your workflow a second pair of eyes — Gemini looks at your renders
Vertex AI — Gemini through your Google Cloud project, not AI Studio
Volcengine Ark — the door Seedream actually lives behind
The only way to touch 'Wan' image generation without renting a data center
Wan Image — nine reference images, and a model you can't download
XAI — the direct line to Grok, no router in the middle
ComfyUI-YogurtNodes
ComfyUI-YogurtNodes is a collection of custom nodes for ComfyUI, providing a series of practical image processing and workflow enhancement functionalities.
✨ Features
- Custom node integration
- Easy-to-use image processing functions
- Full compatibility with ComfyUI workflows
- Text and image manipulation capabilities
- Advanced string processing utilities
- Model management and selection tools
- Comprehensive I/O operations support
- Integrated Gemini API for language and image understanding
- Logic control nodes for complex workflows
📦 Installation
Requirements
- ComfyUI (installed and running)
- Python 3.x
- Required Python packages:
- numpy
- pillow
- google-genai (for Gemini nodes)
- openai (for OpenAI and OpenRouter nodes)
- requests (for API calls)
- opencv-python (for Poisson Blend)
Installation Steps
- Navigate to your ComfyUI custom nodes directory:
cd custom_nodes
- Clone this repository:
git clone https://github.com/yogurt7771/ComfyUI-YogurtNodes.git
- Install dependencies:
cd ComfyUI-YogurtNodes
pip install -r requirements.txt
🚀 Usage
- Start ComfyUI
- Look for "Yogurt Nodes" category in the node browser
- Drag and drop desired nodes into your workflow
🔧 Available Nodes
All exported nodes are listed here. ComfyUI display names keep the " (Yogurt Nodes)" suffix at runtime.
This section is auto-generated from exported node classes and their docstrings. Run python tools/generate_readme.py to refresh.
Total exported nodes: 183.
| Group | Count | | --- | ---: | | Image Processing Nodes | 11 | | Mask Nodes | 5 | | Number Processing Nodes | 2 | | String Processing Nodes | 8 | | Logic Processing Nodes | 41 | | Model Nodes | 17 | | I/O Operation Nodes | 36 | | Language Model Nodes | 55 | | Network Nodes | 8 |
Image Processing Nodes
| Node | Class ID | Category | Description |
| --- | --- | --- | --- |
| Add Text To Image | YogurtAddTextToImage | YogurtNodes/Image | Add text to image. |
| Batch Images | YogurtBatchImages | YogurtNodes/Image | Batch images. |
| Get Image Size | YogurtGetImageSize | YogurtNodes/Image | Get image size information. |
| H/L Frequency Detail Restore Threshold | YogurtHLFrequencyDetailRestoreThreshold | YogurtNodes/Image | H/L frequency detail restore with independent high/low delta thresholds. |
| Image Crop By Mask | YogurtImageCropByMask | YogurtNodes/Image | Crop image to the minimum bounding box of the mask above threshold. |
| Image Scale To Total Pixels Advanced | YogurtImageScaleToTotalPixelsAdvanced | YogurtNodes/Image | Image Scale To Total Pixels Advanced. |
| Image Tile (Seam Mask) | YogurtImageTileWithSeamMask | YogurtNodes/Image | Split image into overlapped tiles and generate inpaint masks (white=inpaint, black=reference). |
| Image Untile (Seam Mask) | YogurtImageUntileWithSeamMask | YogurtNodes/Image | Merge overlapped tiles back to one image with seam feathering (mask + overlap-based smooth transition). |
| Poisson Blend | YogurtPoissonBlend | YogurtNodes/Image | 使用OpenCV泊松融合(seamlessClone)将前景融合到背景。 |
| Replace Image In Batch | YogurtReplaceImageInBatch | YogurtNodes/Image | Replace one image inside an image batch at the given index. |
| Tile Info To TTP Image Assy Args | YogurtTileInfoToTTPImageAssyArgs | YogurtNodes/Image | Convert tile_info to TTP_Image_Assy inputs: positions/original_size/grid_size/padding. |
Mask Nodes
| Node | Class ID | Category | Description |
| --- | --- | --- | --- |
| Composite Repaint Regions | YogurtCompositeRepaintRegions | YogurtNodes/Masks | Composite repainted region crops back onto a base image. |
| Crop Image By Regions | YogurtCropImageByRegions | YogurtNodes/Masks | Crop repaint image and mask batches from dynamic mask regions. |
| Mask Region Planner | YogurtMaskRegionPlanner | YogurtNodes/Masks | Plan dynamic fixed-size repaint tiles from a mask batch. |
| Preview Repaint Regions | YogurtPreviewRepaintRegions | YogurtNodes/Masks | Draw planned repaint region boxes over the image. |
| Split Mask | YogurtSplitMask | YogurtNodes/Masks | Split a combined mask into one mask batch item per connected component. |
Number Processing Nodes
| Node | Class ID | Category | Description |
| --- | --- | --- | --- |
| Range | YogurtRange | YogurtNodes/Number | get a number from a range |
| RangeItem | YogurtRangeItem | YogurtNodes/Number | get a value from a range |
String Processing Nodes
| Node | Class ID | Category | Description |
| --- | --- | --- | --- |
| Regex Node | YogurtRegexNode | YogurtNodes/String | Regex-based extraction and replacement for multiline text. |
| Replace Delimiter | YogurtReplaceDelimiter | YogurtNodes/String | Replace delimiter in string. Support regex |
| String Concat | YogurtStringConcat | YogurtNodes/String | 拼接多个字符串，支持自定义分隔符和可变数量的输入 |
| String Format | YogurtStringFormat | YogurtNodes/String | Format strings |
| String Join | YogurtStringJoin | YogurtNodes/String | 将多个字符串使用指定连接符连接 |
| String Lines Count | YogurtStringLinesCount | YogurtNodes/String | Get the number of lines in a multiline string |
| String Lines Switch | YogurtStringLinesSwitch | YogurtNodes/String | Get line from multiline string by index |
| String To Value | YogurtStringToValue | YogurtNodes/String | Get value from string |
Logic Processing Nodes
| Node | Class ID | Category | Description |
| --- | --- | --- | --- |
| DataSize | YogurtDataSize | YogurtNodes/Logic | Get the size/length of any data structure |
| DictContainsKey | YogurtDictContainsKey | YogurtNodes/Logic | Check if a dictionary contains a specific key |
| DictContainsValue | YogurtDictContainsValue | YogurtNodes/Logic | Check if a dictionary contains a specific value |
| DictFilter | YogurtDictFilter | YogurtNodes/Logic | Filter dictionary entries based on key or value patterns |
| DictFromLists | YogurtDictFromLists | YogurtNodes/Logic | Create a dictionary from a list of keys and a list of values |
| DictGet | YogurtDictGet | YogurtNodes/Logic | Get a value by key from any dict-like object |
| DictInvert | YogurtDictInvert | YogurtNodes/Logic | Invert a dictionary (swap keys and values) |
| DictKeys | YogurtDictKeys | YogurtNodes/Logic | Get all keys from any dict-like object |
| DictLength | YogurtDictLength | YogurtNodes/Logic | Get the length (number of keys) of any dict-like object |
| DictMerge | YogurtDictMerge | YogurtNodes/Logic | Merge multiple dictionaries |
| DictSubset | YogurtDictSubset | YogurtNodes/Logic | Get a subset of a dict-like object by specifying keys |
| DictValues | YogurtDictValues | YogurtNodes/Logic | Get all values from any dict-like object |
| EndNode | YogurtEndNode | YogurtNodes/Logic | End |
| IsEmpty | YogurtIsEmpty | YogurtNodes/Logic | Check if a data structure is empty |
| JsonDeepCopy | YogurtJsonDeepCopy | YogurtNodes/Logic | Create a deep copy of JSON object |
| JsonFlatten | YogurtJsonFlatten | YogurtNodes/Logic | Flatten nested JSON object to flat key-value pairs |
| JsonGetPath | YogurtJsonGetPath | YogurtNodes/Logic | Get value from JSON object using JSONPath |
| JsonMerge | YogurtJsonMerge | YogurtNodes/Logic | Merge multiple JSON objects using deep merge |
| JsonParse | YogurtJsonParse | YogurtNodes/Logic | Parse JSON string to object |
| JsonPathExists | YogurtJsonPathExists | YogurtNodes/Logic | Check if a path exists in JSON object |
| JsonSetPath | YogurtJsonSetPath | YogurtNodes/Logic | Set value in JSON object using JSONPath |
| JsonStringify | YogurtJsonStringify | YogurtNodes/Logic | Convert object to JSON string |
| JsonUnflatten | YogurtJsonUnflatten | YogurtNodes/Logic | Unflatten flat JSON object back to nested structure |
| JsonValidate | YogurtJsonValidate | YogurtNodes/Logic | Validate JSON data structure |
| ListBinaryOps | YogurtListBinaryOps | YogurtNodes/Logic | Perform union, intersection, difference, zip and related operations on two lists. |
| ListConcat | YogurtListConcat | YogurtNodes/Logic | Concatenate multiple lists |
| ListContains | YogurtListContains | YogurtNodes/Logic | Check if a list contains a specific element |
| ListFilter | YogurtListFilter | YogurtNodes/Logic | Filter list elements based on regex pattern |
| ListFind | YogurtListFind | YogurtNodes/Logic | Find the index of an element in a list |
| ListIndex | YogurtListIndex | YogurtNodes/Logic | 通过索引从任何列表类型对象中获取元素 |
| ListJoin | YogurtListJoin | YogurtNodes/Logic | Join list elements into a string |
| ListLength | YogurtListLength | YogurtNodes/Logic | 获取任何列表类型对象的长度 |
| ListSlice | YogurtListSlice | YogurtNodes/Logic | 从任何列表类型对象中获取切片 |
| ListUnique | YogurtListUnique | YogurtNodes/Logic | Remove duplicate elements from a list while preserving order |
| None | YogurtNoneNode | YogurtNodes/Logic | Return None. |
| PackAny | YogurtPackAny | YogurtNodes/Logic | Pack any |
| StringSplit | YogurtStringSplit | YogurtNodes/Logic | Split a string into a list |
| Switch | YogurtSwitch | YogurtNodes/Logic | Switch |
| ToDict | YogurtToDict | YogurtNodes/Logic | Convert pairs or mapping to a dictionary |
| ToList | YogurtToList | YogurtNodes/Logic | Convert any iterable to a list |
| UnpackAny | YogurtUnpackAny | YogurtNodes/Logic | Unpack any |
Model Nodes
| Node | Class ID | Category | Description |
| --- | --- | --- | --- |
| Checkpoint Selector | YogurtCheckpointSelector | YogurtNodes/Models | Select Checkpoint |
| ControlNet Selector | YogurtControlNetSelector | YogurtNodes/Models | Select ControlNet |
| Convert LoRA Keys | YogurtConvertLoraKeys | YogurtNodes/Models | Rename LoRA keys by mapping JSON. |
| Create LoRA Mapping JSON | YogurtCreateLoraMappingJson | YogurtNodes/Models | Build a best-effort mapping from LoRA A keys to LoRA B keys. |
| Diffusion Model Selector | YogurtDiffusionModelSelector | YogurtNodes/Models | Select Diffusion Model |
| LoRA Add (Rank Aware) | YogurtLoraAdd | YogurtNodes/Models | Merge two LoRAs, with SVD rank alignment when ranks differ. |
| LoRA Compress | YogurtLoraRankCompress | YogurtNodes/Models | Compress LoRA rank with SVD for standard .lora_down/.lora_up pairs. Optionally absorb alpha/rank first to preserve the actual LoRA effect before compression. |
| LoRA Layers Operation | YogurtLoraLayersOperation | YogurtNodes/Models | Modify only selected LoRA layers by index. |
| LoRA Load Only | YogurtLoadLoraOnly | YogurtNodes/Models | Load a LoRA without applying it. Use with other LoRA operation nodes. |
| LoRA Merge Full Rank | YogurtLoraMerge | YogurtNodes/Models | Merge up to five standard LoRAs exactly by concatenating rank dimensions. Fast and preserves the summed model-side effect exactly, but output rank/file size grow. Does not support DoRA or LoCon/reshape variants. |
| LoRA Scale Alpha | YogurtLoraScaleAlpha | YogurtNodes/Models | Scale only LoRA alpha metadata so the adjusted LoRA can be saved downstream. |
| LoRA Scale Weights | YogurtLoraScaleWeights | YogurtNodes/Models | Scale LoRA tensor weights globally so effect can be tuned while using strength=1. |
| LoRA Simple Add | YogurtLoraSimpleAdd | YogurtNodes/Models | Simple weighted sum of two LoRA states. |
| LoRA Stat Viewer | YogurtLoraStatViewer | YogurtNodes/Models | Inspect LoRA key patterns to help define regex and layer selection. |
| Lora Selector | YogurtLoraSelector | YogurtNodes/Models | Select Lora |
| Merge LoRA To Model | YogurtMergeLoraToModel | YogurtNodes/Models | Apply loaded LoRA to model and optional CLIP. |
| Save LoRA | YogurtSaveLora | YogurtNodes/Models | Save LoRA state as safetensors. |
I/O Operation Nodes
| Node | Class ID | Category | Description |
| --- | --- | --- | --- |
| Any Bridge | YogurtAnyBridge | YogurtNodes/IO | Any Bridge |
| Create Directory | YogurtCreateDirectory | YogurtNodes/IO | Create a directory |
| Create Parent Directory | YogurtCreateParentDirectory | YogurtNodes/IO | Create a parent directory |
| Deserialize Any | YogurtDeserializeAny | YogurtNodes/IO | Deserialize bytes data to Python object using pickle |
| Glob Files | YogurtGlobFiles | YogurtNodes/IO | Use glob pattern to traverse the folder, return the matching file path list |
| Load Audio Path | YogurtLoadAudioPath | YogurtNodes/IO | Load audio from path. |
| Load Bytes | YogurtLoadBytes | YogurtNodes/IO | Load bytes data from a file |
| Load Image | YogurtLoadImage | YogurtNodes/IO | Load image. |
| Load Image Path | YogurtLoadImagePath | YogurtNodes/IO | Load image from path. |
| Load Video | YogurtLoadVideo | YogurtNodes/IO | Load video. |
| Load Video Path | YogurtLoadVideoPath | YogurtNodes/IO | Load video from path. |
| Path Operator | YogurtPathOperator | YogurtNodes/IO | Execute join, relative, or common path operations. |
| Preview Any Bridge | YogurtPreviewAnyBridge | YogurtNodes/IO | Preview Any Bridge |
| Preview Any Bridge (Output) | YogurtPreviewAnyBridgeOutput | YogurtNodes/IO | Preview Any Bridge (Output) node. |
| Preview Image Bridge | YogurtPreviewImageBridge | YogurtNodes/IO | Preview the input images. |
| Preview Image Bridge (Output) | YogurtPreviewImageBridgeOutput | YogurtNodes/IO | Preview Image Bridge (Output) node. |
| Preview Mask Bridge | YogurtPreviewMaskBridge | YogurtNodes/IO | Preview the input masks. |
| Preview Mask Bridge (Output) | YogurtPreviewMaskBridgeOutput | YogurtNodes/IO | Preview Mask Bridge (Output) node. |
| Save Bytes Bridge | YogurtSaveBytesBridge | YogurtNodes/IO | Saves the input bytes data to your ComfyUI output directory. |
| Save Bytes Bridge (Non Output) | YogurtSaveBytesBridgeNonOutput | YogurtNodes/IO | Save Bytes Bridge (Non Output) node. |
| Save Image Bridge | YogurtSaveImageBridge | YogurtNodes/IO | Saves the input images to your ComfyUI output directory. |
| Save Image Bridge (Non Output) | YogurtSaveImageBridgeNonOutput | YogurtNodes/IO | Save Image Bridge (Non Output) node. |
| Save Image Bridge Ex | YogurtSaveImageBridgeEx | YogurtNodes/IO | Saves the input images to your ComfyUI output directory. |
| Save Image Bridge Ex (Non Output) | YogurtSaveImageBridgeExNonOutput | YogurtNodes/IO | Save Image Bridge Ex (Non Output) node. |
| Save Image Bridge Simple | YogurtSaveImageBridgeSimple | YogurtNodes/IO | Saves the input images to your ComfyUI output directory. |
| Save Image Bridge Simple (Non Output) | YogurtSaveImageBridgeSimpleNonOutput | YogurtNodes/IO | Save Image Bridge Simple (Non Output) node. |
| Save Mask Bridge | YogurtSaveMaskBridge | YogurtNodes/IO | Saves the input masks to your ComfyUI output directory. |
| Save Mask Bridge | YogurtSaveMaskBridgeEx | YogurtNodes/IO | Saves the input masks to your ComfyUI output directory. |
| Save Mask Bridge | YogurtSaveMaskBridgeSimple | YogurtNodes/IO | Saves the input masks to your ComfyUI output directory. |
| Save Mask Bridge (Non Output) | YogurtSaveMaskBridgeExNonOutput | YogurtNodes/IO | Save Mask Bridge (Non Output) node. |
| Save Mask Bridge (Non Output) | YogurtSaveMaskBridgeNonOutput | YogurtNodes/IO | Save Mask Bridge (Non Output) node. |
| Save Mask Bridge Simple (Non Output) | YogurtSaveMaskBridgeSimpleNonOutput | YogurtNodes/IO | Save Mask Bridge Simple (Non Output) node. |
| Save Text Bridge | YogurtSaveTextBridge | YogurtNodes/IO | Saves the input text to your ComfyUI output directory. |
| Save Text Bridge (Non Output) | YogurtSaveTextBridgeNonOutput | YogurtNodes/IO | Save Text Bridge (Non Output) node. |
| Serialize Any | YogurtSerializeAny | YogurtNodes/IO | Serialize any Python object to bytes using pickle |
| Split Path | YogurtSplitPath | YogurtNodes/IO | Split path to parts |
Language Model Nodes
| Node | Class ID | Category | Description |
| --- | --- | --- | --- |
| Chat (Custom Model) | YogurtCustomModelChat | YogurtNodes/LLM | Chat with any model id on the connected provider. |
| Claude Chat | YogurtClaudeChat | YogurtNodes/LLM | Anthropic Claude via OpenRouter or an OpenAI-compatible relay. |
| FreedomGPT Generate Image (Legacy) | YogurtFreedomGPTGenerateImage | YogurtNodes/LLM | Generate images using FreedomGPT API |
| FreedomGPT Generate Text (Legacy) | YogurtFreedomGPTGenerateText | YogurtNodes/LLM | Generate text using FreedomGPT API |
| FreedomGPT Image Understand (Legacy) | YogurtFreedomGPTImageUnderstand | YogurtNodes/LLM | Understand image content using FreedomGPT vision models |
| GPT Chat | YogurtGPTChat | YogurtNodes/LLM | OpenAI GPT text generation with optional image understanding and chat history. |
| GPT Image | YogurtGPTImageGenerateImage | YogurtNodes/LLM | OpenAI GPT Image generation and editing (2.5 / 2 / 1.5 / 1 / 1 Mini). |
| GRSAI Generate Image (Legacy) | YogurtGRSAIGenerateImage | YogurtNodes/LLM | Generate or edit images with the GRSAI API and return torch tensors |
| Gemini Chat | YogurtGeminiChat | YogurtNodes/LLM | Gemini text generation with optional image understanding and chat history. |
| Gemini Generate Image (Legacy) | YogurtGeminiGenerateImage | YogurtNodes/LLM | Generate image using Gemini API and return as torch.Tensor (h,w,c) and text |
| Gemini Generate Text (Legacy) | YogurtGeminiGenerateText | YogurtNodes/LLM | Generate text using Gemini API |
| Gemini Image Understand (Legacy) | YogurtGeminiImageUnderstand | YogurtNodes/LLM | Understand images using Gemini API |
| Grok Chat | YogurtGrokChat | YogurtNodes/LLM | xAI Grok text generation with optional image understanding and chat history. |
| Grok Generate Image (Legacy) | YogurtGrokGenerateImage | YogurtNodes/LLM | Generate image using xAI Grok API and return as torch.Tensor (h,w,c) and text |
| Grok Generate Text (Legacy) | YogurtGrokGenerateText | YogurtNodes/LLM | Generate text using xAI API |
| Grok Image Understand (Legacy) | YogurtGrokImageUnderstand | YogurtNodes/LLM | Understand image content using xAI vision models |
| Grok Imagine | YogurtGrokImagineGenerateImage | YogurtNodes/LLM | xAI Grok Imagine image generation and editing. |
| History Builder | YogurtHistoryBuilder | YogurtNodes/LLM | 构建与 LLM 节点兼容的会话历史 |
| Image Generation (Custom Model) | YogurtCustomModelGenerateImage | YogurtNodes/LLM | Image generation with any model id on the connected provider. |
| Magnific Creative Upscale | YogurtMagnificCreativeUpscale | YogurtNodes/LLM | Magnific creative upscaling with prompt, creativity and engine controls. |
| Magnific Image Upscale API (Legacy) | YogurtMagnificImageUpscaleAPI | YogurtNodes/LLM | Call the Magnific image upscaler API, wait for completion, and return an IMAGE batch. |
| Magnific Precision Upscale | YogurtMagnificPrecisionUpscale | YogurtNodes/LLM | Magnific precision upscaling (V2 with flavors, or V1). |
| Nano Banana | YogurtNanoBananaGenerateImage | YogurtNodes/LLM | Nano Banana image generation and editing (2.1 / 2 / 2 Lite / Pro / 1). |
| OpenAI Generate Image (Legacy) | YogurtOpenAIGenerateImage | YogurtNodes/LLM | Generate image using OpenAI API and return as torch.Tensor (h,w,c) and text |
| OpenAI Generate Text (Legacy) | YogurtOpenAIGenerateText | YogurtNodes/LLM | Generate text using OpenAI API |
| OpenAI Image Understand (Legacy) | YogurtOpenAIImageUnderstand | YogurtNodes/LLM | Understand image content using OpenAI vision models |
| OpenRouter Generate Image (Legacy) | YogurtOpenRouterGenerateImage | YogurtNodes/LLM | Generate image using OpenRouter API and return as torch.Tensor (h,w,c) and text |
| OpenRouter Generate Text (Legacy) | YogurtOpenRouterGenerateText | YogurtNodes/LLM | Generate text using OpenRouter API |
| OpenRouter Image Understand (Legacy) | YogurtOpenRouterImageUnderstand | YogurtNodes/LLM | Understand image content using OpenRouter API |
| Provider: Alibaba DashScope | YogurtDashScopeProvider | YogurtNodes/LLM | Alibaba Cloud DashScope (Bailian) provider for Qwen Image and Wan. |
| Provider: BytePlus ModelArk | YogurtBytePlusArkProvider | YogurtNodes/LLM | BytePlus ModelArk (international) provider for Seedream models. |
| Provider: FreedomGPT | YogurtFreedomGPTProvider | YogurtNodes/LLM | FreedomGPT provider; use with the custom-model chat and image nodes. |
| Provider: GRSAI | YogurtGRSAIProvider | YogurtNodes/LLM | GRSAI drawing relay provider (Nano Banana / GPT Image). |
| Provider: Google AI Studio | YogurtGoogleAIStudioProvider | YogurtNodes/LLM | Google AI Studio (Gemini API) provider; connect to Gemini / Nano Banana nodes. |
| Provider: Google GenAI Compatible | YogurtGoogleGenAICompatibleProvider | YogurtNodes/LLM | Any Gemini-API-compatible endpoint with a custom base URL. |
| Provider: Magnific | YogurtMagnificProvider | YogurtNodes/LLM | Magnific upscaler API provider. |
| Provider: OpenAI | YogurtOpenAIProvider | YogurtNodes/LLM | Official OpenAI API provider. |
| Provider: OpenAI Compatible | YogurtOpenAICompatibleProvider | YogurtNodes/LLM | Any OpenAI-compatible endpoint (chat completions / images) with a custom base URL. |
| Provider: OpenRouter | YogurtOpenRouterProvider | YogurtNodes/LLM | OpenRouter provider with optional upstream provider routing. |
| Provider: Topaz Labs | YogurtTopazProvider | YogurtNodes/LLM | Topaz Labs Image API provider. |
| Provider: Vertex AI | YogurtVertexAIProvider | YogurtNodes/LLM | Vertex AI provider (express-mode API key or service-account credentials). |
| Provider: Volcengine Ark | YogurtVolcengineArkProvider | YogurtNodes/LLM | Volcengine Ark (China) provider for Seedream and Doubao models. |
| Provider: xAI | YogurtXAIProvider | YogurtNodes/LLM | xAI (Grok) API provider. |
| Qwen Generate/Edit Image (Legacy) | YogurtQwenGenerateImage | YogurtNodes/LLM | 使用阿里云百炼 Qwen 图片模型进行文生图或多图编辑 |
| Qwen Image | YogurtQwenImageGenerateImage | YogurtNodes/LLM | Alibaba Qwen Image generation and editing. |
| SeeDream Generate Image (Legacy) | YogurtSeeDreamGenerateImage | YogurtNodes/LLM | 使用豆包SeeDream API生成图像，支持文生图、图生图、多图生图和序列图像生成 |
| Seedream | YogurtSeedreamGenerateImage | YogurtNodes/LLM | ByteDance Seedream image generation and editing (5.0 Pro / Flash / Lite, 4.5, 4.0). |
| Topaz Generative Upscale | YogurtTopazGenerativeUpscale | YogurtNodes/LLM | Topaz generative upscaling (Wonder 3.5, Bloom 2, Reimagine, Redefine, Recovery V2). |
| Topaz Image Upscale API (Legacy) | YogurtTopazImageUpscaleAPI | YogurtNodes/LLM | Call the Topaz Labs Image API, wait for completion, and return an IMAGE batch. |
| Topaz Upscale | YogurtTopazUpscale | YogurtNodes/LLM | Topaz precision upscaling (Standard V2, Low Resolution V2, High Fidelity V2, CGI, Text Refine). |
| Vertex AI Generate Image (Legacy) | YogurtVertexAIGenerateImage | YogurtNodes/LLM | Generate image using Vertex AI API and return as torch.Tensor (h,w,c) and text |
| Vertex AI Generate Text (Legacy) | YogurtVertexAIGenerateText | YogurtNodes/LLM | Generate text using Vertex AI |
| Vertex Image Understand (Legacy) | YogurtVertexAIImageUnderstand | YogurtNodes/LLM | Understand images using Vertex AI |
| Wan Generate/Edit Image (Legacy) | YogurtWanGenerateImage | YogurtNodes/LLM | 使用阿里云百炼 Wan 图片模型进行文生图或图像编辑 |
| Wan Image | YogurtWanImageGenerateImage | YogurtNodes/LLM | Alibaba Wan image generation and editing. |
Network Nodes
| Node | Class ID | Category | Description |
| --- | --- | --- | --- |
| ComfyUI Client Get Output | YogurtComfyUIClientGetOutput | YogurtNodes/Net | 根据节点 ID/名称，从结果包中取出该节点的全部输出列表 |
| ComfyUI Client Load | YogurtComfyUIClientLoad | YogurtNodes/Net | 配置 ComfyUI 客户端实例，供后续节点复用 |
| ComfyUI Client Run | YogurtComfyUIClientRun | YogurtNodes/Net | 提交工作流并等待结果返回 |
| ComfyUI Client Set Float | YogurtComfyUIClientSetFloat | YogurtNodes/Net | 向工作流节点输入设置浮点数 |
| ComfyUI Client Set Image | YogurtComfyUIClientSetImage | YogurtNodes/Net | 上传图片并写入工作流节点输入 |
| ComfyUI Client Set Int | YogurtComfyUIClientSetInt | YogurtNodes/Net | 向工作流节点输入设置整数 |
| ComfyUI Client Set Seed | YogurtComfyUIClientSetSeed | YogurtNodes/Net | 为工作流中的节点设置随机种子 |
| ComfyUI Client Set String | YogurtComfyUIClientSetString | YogurtNodes/Net | 向工作流节点输入设置字符串 |
🔑 Gemini API Key Setup
Before using Gemini-related nodes, you must obtain and configure your Gemini API Key. There are three supported methods, in the following order of priority:
-
Code Argument
- Pass the
api_keyargument directly when initializingGeminiClient(highest priority).
- Pass the
-
api_key.json File
- Create an
api_key.jsonfile incustom_nodes/ComfyUI-YogurtNodes/yogurt_nodes/llm/with the following content:{ "gemini": "YOUR_API_KEY" } - This will be used only if the code argument is not provided.
- Create an
-
Environment Variable
- Set the environment variable
GEMINI_API_KEY(used only if the above two are not set). - Example (Windows command line):
set GEMINI_API_KEY=YOUR_API_KEY
- Set the environment variable
If the API Key is not configured correctly, Gemini nodes will not work. You can obtain your API Key from Google AI Studio.
🔑 OpenAI API Key Setup
Before using OpenAI-related nodes, you must obtain and configure your OpenAI API Key. There are three supported methods, in the following order of priority:
-
Code Argument
- Pass the
api_keyargument directly when initializingOpenAIClient(highest priority).
- Pass the
-
api_key.json File
- Create an
api_key.jsonfile incustom_nodes/ComfyUI-YogurtNodes/yogurt_nodes/llm/with the following content:{ "openai": "YOUR_API_KEY", "openai_base_url": "https://api.openai.com/v1" } - The
openai_base_urlis optional and defaults to the official OpenAI API. - This will be used only if the code argument is not provided.
- Create an
-
Environment Variable
- Set the environment variables
OPENAI_API_KEYand optionallyOPENAI_BASE_URL(used only if the above two are not set). - Example (Windows command line):
set OPENAI_API_KEY=YOUR_API_KEY set OPENAI_BASE_URL=https://api.openai.com/v1
- Set the environment variables
Custom Base URL Support
The OpenAI nodes support custom base URLs, making them compatible with:
- Official OpenAI API
- Azure OpenAI Service
- OpenAI-compatible APIs (like LocalAI, Ollama, etc.)
- Self-hosted OpenAI-compatible servers
Simply set the base_url parameter to your preferred endpoint.
If the API Key is not configured correctly, OpenAI nodes will not work. You can obtain your API Key from OpenAI Platform.
🔑 OpenRouter API Key Setup
Before using OpenRouter-related nodes, you must obtain and configure your OpenRouter API Key. There are three supported methods, in the following order of priority:
-
Code Argument
- Pass the
api_keyargument directly when initializingOpenRouterClient(highest priority).
- Pass the
-
api_key.json File
- Create an
api_key.jsonfile incustom_nodes/ComfyUI-YogurtNodes/yogurt_nodes/llm/with the following content:{ "openrouter": "YOUR_API_KEY" } - This will be used only if the code argument is not provided.
- Create an
-
Environment Variable
- Set the environment variable
OPENROUTER_API_KEY(used only if the above two are not set). - Example (Windows command line):
set OPENROUTER_API_KEY=YOUR_API_KEY
- Set the environment variable
If the API Key is not configured correctly, OpenRouter nodes will not work. You can obtain your API Key from OpenRouter Platform.
🧩 LLM / Image / Upscale Nodes: Providers and Models
LLM-related nodes come in two kinds that are wired together:
- Model nodes (
YogurtNodes/LLM/Image,Text,Upscale): one node per model family, e.g. Nano Banana, GPT Image, Seedream, Gemini Chat, Claude Chat, Topaz Upscale. Themodeldropdown switches versions, and the inputs below it change to show only what that version supports. - Provider nodes (
YogurtNodes/LLM/Providers): hold the connection settings (key, base URL, proxy, timeout) and output aproviderthat you connect to a model node. The same model can be called through different providers, e.g. Nano Banana via Google AI Studio, Vertex AI, OpenRouter or GRSAI.
Notes:
- When a model node's
providerinput is not connected, the family's default official provider is used, with the key read from theapi_key.jsonkey or environment variable listed below. - Connecting a provider that does not offer the selected model fails with an error listing the supported providers.
- OpenAI Compatible and Google GenAI Compatible are for custom base URLs (relays). Their
api_keymust be filled in the node; they never fall back to the official keys inapi_key.json. - Reference image inputs are dynamic: connecting one adds the next slot.
timeout0 means no limit; image generation usually takes tens of seconds to minutes.- Use the advanced
extrainput (a JSON object) to pass parameters that are not exposed yet. - For models that are not built in yet, use
Custom modelin a family's dropdown, or theChat (Custom Model)/Image Generation (Custom Model)nodes with a model id. - The previous nodes remain under
YogurtNodes/LLM/Legacywith a(Legacy)suffix, so existing workflows keep working.
| Provider node | api_key.json key | Environment variable | Default for model nodes |
| --- | --- | --- | --- |
| Google AI Studio | gemini | GEMINI_API_KEY | Nano Banana, Gemini Chat |
| Vertex AI | vertex_ai_json, vertex_ai_project, vertex_ai_region | GOOGLE_APPLICATION_CREDENTIALS | — |
| Google GenAI Compatible | must be set in the node | — | — |
| OpenAI | openai, openai_base_url | OPENAI_API_KEY, OPENAI_BASE_URL | GPT Image, GPT Chat, custom-model nodes |
| OpenAI Compatible | must be set in the node | — | — |
| OpenRouter | openrouter | OPENROUTER_API_KEY | Claude Chat |
| xAI | xai (or grok), xai_base_url | XAI_API_KEY (or GROK_API_KEY) | Grok Imagine, Grok Chat |
| GRSAI | grsai, grsai_base_url | GRSAI_API_KEY | — |
| FreedomGPT | freedomgpt | FREEDOMGPT_API_KEY | — |
| Volcengine Ark | seedream (or ark) | ARK_API_KEY | Seedream |
| BytePlus ModelArk | byteplus | BYTEPLUS_API_KEY | — |
| Alibaba DashScope | dashscope (or qwen, wan), dashscope_base_url | DASHSCOPE_API_KEY | Qwen Image, Wan Image |
| Topaz Labs | topaz, topaz_base_url | TOPAZ_API_KEY | Topaz Upscale, Topaz Generative Upscale |
| Magnific | magnific, magnific_base_url | MAGNIFIC_API_KEY | Magnific Creative / Precision Upscale |
See yogurt_nodes/llm/EXTENDING.md for adding providers and models.
🤝 Contributing
Pull Requests are welcome to help improve the project!
📄 License
This project is licensed under the MIT License - see the LICENSE file for details.
📞 Contact
For questions, bug reports, or feature requests, please open an issue.
🙏 Acknowledgments
- ComfyUI Community
- All Contributors