Extensions/Kraken Tools
ComfyUI Extension

Kraken Tools

15 productivity nodes: Kraken Unbound Prompt (vision-enabled prompt builder with Qwen2-VL), WAN Prompt Splitter (cinematic styling), Ollama Prompt Chat (LLM…

By krakenunbound·Created 7 months ago·Updated 7 months ago· 2
krakenunbound/comfyui-kraken-tools
Nodes15
On cloudLocal install
CategoryKraken/Loaders, kraken/latent
Stars2
Updated7 months ago

Nodes (15)

🐙 Kraken Checkpoint Loader
Kraken/Loaders
🐙 Kraken Dual CLIP Loader
Kraken/Loaders
🐙 Kraken Empty Latent Image
kraken/latent
🐙 Kraken Image Processor
Kraken/Image
🐙 Kraken Image Resize
Kraken/Image
🐙 Kraken KSampler
🦑 Kraken Tools/Sampling
🐙 Kraken Last Frame + Meta
⚓ Kraken/WAN
🐙 Kraken LoRA Loader (3)
Kraken/LoRA
🐙 Kraken Ollama Prompt Chat
🦑 Kraken/LLM
🐙 Kraken Preset From Image
🦑 Kraken Tools/Upscaling
🐙 Kraken Resolution Helper
kraken/resize
🐙 Kraken Unbound Prompt
🦑 Kraken / Prompt
🐙 Kraken Upscale & Tile Calc
kraken/upscale
🐙 Kraken WAN Helper
⚓ Kraken/WAN
🐙 Kraken WAN Prompt Splitter
🦑 Kraken / Prompt
Readme

Kraken Tools for ComfyUI

A collection of productivity custom nodes for ComfyUI, designed to streamline image generation workflows with smart defaults, advanced features, and quality-of-life improvements.

Installation

Via ComfyUI Manager (Recommended)

Search for "Kraken Tools" in ComfyUI Manager and click Install.

Manual Installation

cd ComfyUI/custom_nodes
git clone https://github.com/yourusername/kraken_tools.git
cd kraken_tools
pip install -r requirements.txt

Requirements

  • ComfyUI
  • Python 3.10+
  • PyTorch 2.0+
  • transformers >= 4.45.0 (for Kraken Unbound Prompt)
  • Pillow
  • requests (for CivitAI trigger word fetching)
  • opencv-python (for image processing)
  • scipy (for image processing)
  • ollama (optional, for Kraken Ollama Prompt Chat)

Nodes Overview (15 Nodes)

Prompt & Text Nodes

🐙 Kraken Unbound Prompt

Advanced prompt builder with built-in vision model support for image-to-text captioning.

Features:

  • Vision Mode: Use Qwen2-VL-2B-Instruct to generate prompts from images
  • Prompt Enhancement: Automatically enhance prompts using AI
  • Style Presets: Choose from photorealistic, cinematic, anime, manga, fantasy, sci-fi, and more
  • Lighting Options: Soft, dramatic, cinematic, studio, natural, golden hour, neon, rim, backlighting
  • Camera Settings: Lens type, f-stop, bokeh effect, DSLR style
  • Persistent Prompt: Add text that always appears (e.g., "blue skies", "brand logo")
  • Negative Prompt: Separate negative prompt output
  • Position Control: Prepend or append style settings to your prompt
  • VRAM Management: Control model loading/unloading with keep_alive_minutes

Inputs: | Input | Type | Description | |-------|------|-------------| | prompt | STRING | Your base prompt text | | use_image_as_source | BOOLEAN | Use vision model to caption an image | | input_image | IMAGE | Image for vision mode | | enhance_prompt | BOOLEAN | Use AI to enhance the prompt | | enhancer_style | DROPDOWN | Modern, Classic Tags, Instructional, or WAN style | | negative_prompt | STRING | Negative prompt text | | persistent | STRING | Text always added to the prompt | | style/lighting/camera_lens/f_stop | DROPDOWNS | Style settings | | position | DROPDOWN | Prepend or append style settings | | force_unload | BOOLEAN | Unload model after use to free VRAM |

Outputs:

  • positive_prompt (STRING): The final positive prompt
  • negative_prompt (STRING): The negative prompt
  • persistent (STRING): The persistent prompt (passthrough)

🐙 Kraken WAN Prompt Splitter

Split and style prompts for WAN video generation with comprehensive cinematic presets.

Features:

  • Prompt Splitting: Split a single prompt into up to 5 segments using delimiters (---, ###, etc.)
  • WAN Packs: Pre-configured style packs (Cinematic Natural, Moody Neon, Documentary Daylight, Epic Vista, Noir Classic)
  • Shot Type: extreme close-up, close-up, medium shot, cowboy shot, wide shot, aerial, POV, etc.
  • Lens Selection: 24mm to 200mm, anamorphic, tilt-shift, fisheye, macro
  • Aperture: f/1.4 dreamy bokeh to f/16 deep focus
  • Lighting: natural daylight, golden hour, neon mix, studio 3-point, film noir, candlelight, etc.
  • Film Stocks: photoreal, portra-like, cinestill-like, black-and-white, vintage chrome, etc.
  • Color Grading: warm amber teal, cool cyan steel, muted pastels, high contrast, etc.
  • Composition: rule of thirds, centered symmetry, leading lines, dutch angle, etc.
  • Environment: clear, fog, rain, snowfall, dust storm, haze
  • Texture: ultra-detailed, fine film grain, clean minimal, gritty texture

Inputs: | Input | Type | Description | |-------|------|-------------| | prompt | STRING | Main prompt (use --- to split) | | persistent | STRING | Text added to all prompts | | wan_pack | DROPDOWN | Pre-configured style pack | | shot_type/lens/aperture/etc. | DROPDOWNS | Individual style controls | | combine_persistent | BOOLEAN | Add persistent text to prompts | | combine_style_presets | BOOLEAN | Add style settings to prompts |

Outputs:

  • Prompt 1 through Prompt 5 (STRING): Split and styled prompts

🐙 Kraken Ollama Prompt Chat

Connect to a local Ollama LLM instance for interactive prompt enhancement.

Features:

  • Connect to any Ollama server
  • Use any Ollama model (llama3.2, mistral, etc.)
  • Interactive chat for refining prompts
  • Specialized system prompt for AI art generation

Inputs: | Input | Type | Description | |-------|------|-------------| | host | STRING | Ollama server URL (e.g., http://localhost:11434) | | model | STRING | Model name (e.g., llama3.2) | | action | DROPDOWN | Connect, Send Message, Clear Chat, Use Last Response | | user_message | STRING | Your message to the LLM |

Outputs:

  • prompt_output (STRING): The generated prompt
  • ai_response (STRING): Full AI response
  • conversation_log (STRING): Chat history

Model Loading Nodes

🐙 Kraken Checkpoint Loader

Enhanced checkpoint loader with model tracking.

Features:

  • Load checkpoints with optional dtype control (fp16, bf16, fp32)
  • Output model name for metadata tracking
  • Compute SHA-256 hash (first 10 chars) for version tracking

Outputs:

  • MODEL, CLIP, VAE: Standard model outputs
  • model_name (STRING): Filename of loaded checkpoint
  • ckpt_sha10 (STRING): First 10 chars of SHA-256 hash

🐙 Kraken Dual CLIP Loader

Full-featured dual text encoder loader for modern models.

Features:

  • Support for Flux, SDXL, SD3, and Hunyuan models
  • Load CLIP-L + T5 text encoders
  • Modes: dual, t5-only, clip-only
  • Device placement control (auto, cuda, cpu)
  • Precision override (fp16, bf16, fp32)
  • Optional warmup for faster first inference

Outputs:

  • clip (CLIP): Combined CLIP object
  • diagnostics (STRING): Loading information

🐙 Kraken LoRA Loader (3)

Load up to 3 LoRAs with automatic trigger word fetching.

Features:

  • Load 3 LoRAs simultaneously with individual enable toggles
  • Per-LoRA strength control for both model and CLIP
  • Per-LoRA CLIP skip setting
  • CivitAI Integration: Automatically fetch trigger words from CivitAI
  • API key stored securely in ~/Documents/ComfyUI/user/kraken_config.json
  • Trigger word placement: prepend, append, or replace
  • Caches trigger words locally for offline use

Inputs: | Input | Type | Description | |-------|------|-------------| | model/clip | MODEL/CLIP | Input model and clip | | lora_X_enabled | BOOLEAN | Enable/disable each LoRA | | lora_X_file | DROPDOWN | LoRA file selection | | lora_X_model_strength | FLOAT | Model weight (-2.0 to 2.0) | | lora_X_clip_strength | FLOAT | CLIP weight (-2.0 to 2.0) | | lora_X_clip_skip | INT | CLIP skip (0 = off) | | lora_X_force_fetch | BOOLEAN | Re-fetch trigger words | | fetch_triggers | BOOLEAN | Enable CivitAI fetching | | placement | DROPDOWN | prepend, append, or replace |

Outputs:

  • model (MODEL), clip (CLIP): Modified model/clip
  • prompt (STRING): Prompt with trigger words
  • lora_names, triggers, tags (STRING_LIST): Metadata

Latent & Resolution Nodes

🐙 Kraken Empty Latent Image

Create empty latent images with preset aspect ratios.

Features:

  • Megapixel selection: 0.5 to 3.0 MP or Custom
  • Preset aspect ratios organized by category:
    • Vertical/Portrait (9:20, 9:16, 2:3, 3:4, 4:5)
    • Square (1:1)
    • Landscape (5:4, 4:3, 3:2, 16:10, 16:9)
    • Cinematic (1.85:1, 2:1, 21:9, 2.39:1)
    • Screen sizes (Android, iPhone, Full HD, 4K)
    • Social media sizes (Instagram, YouTube, Facebook)
  • Custom aspect ratio input
  • Divisible-by alignment (8, 16, 32, 64)

Outputs:

  • latent (LATENT): Empty latent for generation
  • width_out, height_out (INT): Dimensions
  • resolution (STRING): "1024 x 1024" format
  • preset_out (STRING): For connecting to upscale calculator

🐙 Kraken Resolution Helper

Ensures final output matches a specific target resolution. Batch-safe for video.

Features:

  • Multiple modes: fill/crop, pad, keep proportion, stretch
  • Interpolation: lanczos, bicubic, bilinear, nearest
  • Anchor positioning for crop/pad (left/center/right, top/center/bottom)
  • Upscale prevention option
  • Works with batched images (video frames)

Inputs: | Input | Type | Description | |-------|------|-------------| | image | IMAGE | Input image batch | | mode | DROPDOWN | Resize mode | | target_resolution_in | STRING | Target as "WxH" | | preset_in | STRING | From Kraken Empty Latent |

🐙 Kraken Upscale & Tile Calc

Calculate parameters for Ultimate SD Upscale.

Features:

  • Connects to Kraken Empty Latent Image via resolution_in and preset_in
  • Calculates optimal upscale factor to reach target
  • Computes tile width/height for USDU
  • Handles seam fix parameters
  • Minimum upscale policy (auto, off, 1.5x, 2.0x, custom)
  • Generates preview showing predicted vs target resolution

Outputs:

  • image_out (IMAGE): Passthrough
  • upscale_by (FLOAT): Scale factor for USDU
  • tile_width, tile_height (INT): Tile dimensions
  • mask_blur, tile_padding (INT): USDU parameters
  • seam_fix_width, seam_fix_mask_blur, seam_fix_padding (INT)
  • predicted_resolution, target_resolution, target_preset (STRING)

🐙 Kraken Preset From Image

Extract dimensions from an image for upscaling calculations.

Features:

  • Multiple sizing modes:
    • Factor: Multiply by scale factor (e.g., 2x)
    • Long side: Target longest edge
    • Short side: Target shortest edge
    • Megapixels: Target total megapixels
  • Alignment to model-friendly multiples
  • Optional max width/height clamping

Outputs:

  • preset_out (STRING): Resolution as "WxH" (e.g., "2048x1536")

Sampling Nodes

🐙 Kraken KSampler

Smart KSampler wrapper with AMP handling for modern models.

Why this exists: WAN/Flow/FP8 models manage their own precision internally. Wrapping them in an additional autocast context causes crashes like "RuntimeError: Unexpected floating ScalarType in at::autocast::prioritize". This node automatically detects such models and disables outer AMP.

Features:

  • AMP Mode (auto/on/off): Auto-detect WAN/Flow/FP8 models
  • All standard KSampler controls
  • Negative prompt handling (auto/use/ignore)
  • Built-in decode option (standard or tiled)
  • Compatible with ComfyUI 0.3.x+ and PyTorch 2.x

Inputs: | Input | Type | Description | |-------|------|-------------| | model | MODEL | Diffusion model | | positive/negative | CONDITIONING | Prompts | | amp_mode | DROPDOWN | auto, on, or off | | decode_switch | DROPDOWN | on/off for VAE decode | | tiled_decode | DROPDOWN | on/off for large images | | tile_size | INT | Tile size for tiled decode |

Outputs:

  • LATENT: Sampled latent
  • IMAGE: Decoded image (or placeholder if decode off)

Image Processing Nodes

🐙 Kraken Image Resize

Comprehensive image resizing with multiple methods.

Features:

  • Source: Upload or upstream connection
  • Resize modes: longest_side, width, height, fit, fill, stretch
  • Interpolation: lanczos, bicubic, bilinear, nearest, area
  • Option to prevent upscaling smaller images
  • Background color for fill mode

Outputs:

  • image (IMAGE): Resized image
  • width, height (INT): Final dimensions
  • info (STRING): Processing summary

🐙 Kraken Image Processor

Versatile pre/post-processing for upscaling pipelines.

Features:

  • Denoising: Bilateral, Gaussian, median, non-local means, GPU-accelerated Gaussian
  • Contrast Enhancement: Auto-contrast, manual contrast/brightness
  • Sharpening: Unsharp mask, edge enhance, custom kernel
  • Color Correction: Saturation, gamma
  • Film Grain: Adjustable amount and size (post-processing only)
  • Alpha channel preservation
  • Quality metrics output
  • 16-bit processing precision option

Modes:

  • pre_process: Prepare image for upscaling
  • post_process: Refine upscaled image (gentler settings auto-applied)

Video / WAN Nodes

🐙 Kraken WAN Helper

Quick parameter selection for WAN video generation.

Features:

  • Performance tiers: 720p Quality or 480p Speed
  • Duration slider: 1-10 seconds
  • FPS options: 8, 12, 16, 24, 30
  • Automatic aspect ratio detection from first frame
  • First/last frame preprocessing
  • Bookend frame option for looping

Outputs:

  • processed_first_frame, processed_last_frame (IMAGE)
  • width, height (INT)
  • frames(length) (INT): Total frame count
  • fps (FLOAT)
  • resolution_text (STRING)

🐙 Kraken Last Frame + Meta

Extract last frame from video for creating extended sequences.

Use case: Generate 5-second video clips, then use the last frame of each as the first frame of the next to create seamless longer videos.

Features:

  • Extracts last frame from image batch
  • Forwards all WAN metadata (width, height, frames, fps)
  • Optional frame duplication

Outputs:

  • last_frame (IMAGE): The last frame
  • first_frame_out (IMAGE): Same as last_frame (for chaining)
  • width, height, frames(length), fps, resolution_text: Metadata passthrough

Typical Workflow Examples

Basic Image Generation with LoRAs

Kraken Checkpoint Loader --> Kraken LoRA Loader (3) --> Kraken KSampler
                                      ^
Kraken Unbound Prompt --> CLIP Text Encode --+

Upscaling with Ultimate SD Upscale

Kraken Empty Latent Image
      |
      +--> resolution_out --> Kraken Upscale & Tile Calc --> Ultimate SD Upscale
      |                              |
      +--> preset_out ---------------+

After USDU:
Ultimate SD Upscale --> Kraken Resolution Helper --> Kraken Image Processor --> Save Image

WAN Video Generation

Kraken WAN Prompt Splitter --> WAN Text Encode
                                     |
Kraken WAN Helper -----------------> WAN Generation --> Kraken Last Frame + Meta
                                                              |
                                          (Loop back to WAN Generation as first_frame)

Configuration

CivitAI API Key (for LoRA trigger words)

Create or edit ~/Documents/ComfyUI/user/kraken_config.json:

{
    "civitai_api_key": "your_api_key_here"
}

The key is optional - public model data can be fetched without it.

Ollama Setup (for Prompt Chat)

  1. Install Ollama: https://ollama.ai
  2. Pull a model: ollama pull llama3.2
  3. Configure host in the node (default: http://localhost:11434)

Node List Summary

| Node | Category | Description | |------|----------|-------------| | 🐙 Kraken Unbound Prompt | Prompt | Vision-enabled prompt builder with styles | | 🐙 Kraken WAN Prompt Splitter | Prompt | Split & style prompts for WAN video | | 🐙 Kraken Ollama Prompt Chat | Prompt | LLM-powered prompt enhancement | | 🐙 Kraken Checkpoint Loader | Loaders | Checkpoint loader with SHA tracking | | 🐙 Kraken Dual CLIP Loader | Loaders | Dual text encoder for Flux/SD3 | | 🐙 Kraken LoRA Loader (3) | Loaders | 3-slot LoRA with CivitAI integration | | 🐙 Kraken Empty Latent Image | Latent | Latent with aspect ratio presets | | 🐙 Kraken Resolution Helper | Resolution | Enforce target resolution | | 🐙 Kraken Upscale & Tile Calc | Resolution | Calculate USDU parameters | | 🐙 Kraken Preset From Image | Resolution | Extract dimensions from image | | 🐙 Kraken KSampler | Sampling | Smart sampler with AMP handling | | 🐙 Kraken Image Resize | Image | Comprehensive image resizing | | 🐙 Kraken Image Processor | Image | Pre/post-processing pipeline | | 🐙 Kraken WAN Helper | Video | WAN video parameter helper | | 🐙 Kraken Last Frame + Meta | Video | Extract last frame for looping |

License

MIT License - See individual file headers for details.

Credits

Created by The Kraken (@KrakenUnbound)

Built for the ComfyUI community.