nobandegani-ComfyUI-InoNodes/README.md

Ino Custom Nodes for ComfyUI

A comprehensive collection of custom nodes for ComfyUI that provides advanced file handling, S3 cloud storage integration, OpenAI-powered helpers, Basic Auth middleware, LoRA configuration management, and various utility functions.

Installation

Option 1: Using ComfyUI-Manager (Recommended)

1. Install ComfyUI
2. Install ComfyUI-Manager
3. Search for "ComfyUI Ino Nodes" in ComfyUI-Manager and install
4. Restart ComfyUI

Option 2: Manual Installation

1. Clone this repository into your ComfyUI custom_nodes directory:

   cd ComfyUI/custom_nodes
   git clone https://github.com/nobandegani/comfyui_ino_nodes.git
   

2. Install dependencies:

   cd comfyui_ino_nodes
   pip install -r requirements.txt
   

3. Restart ComfyUI

Dependencies

• inocloudreve - Cloudreve cloud storage integration
• inopyutils - Utility functions
• openai - OpenAI API client (used by OpenAI helper nodes)
• aiohttp - Async HTTP and server middleware support
• numpy, Pillow, torch - Core libraries required by ComfyUI and several nodes

Node Categories & Documentation

🗂️ File & Path Utilities (InoNodes)

Ino Parse File Path

Extracts and parses components from file paths.

• Inputs: file_path (string)
• Outputs: File name, directory, extension, and other path components
• Use Case: Parse file paths for batch processing or file organization

Ino Count Files

Counts files in directories with optional pattern matching.

• Inputs: file_path (directory path), file_pattern (optional filter)
• Outputs: File count and directory information
• Use Case: Batch processing workflows that need to know dataset sizes

Ino Branch Image

Conditionally routes images based on boolean input.

• Inputs: boolean (condition), input_image (optional image)
• Outputs: Routed image based on condition
• Use Case: Conditional image processing workflows

Ino Get Folder Batch ID

Generates unique batch identifiers for folder-based workflows.

• Inputs: enabled, seed, batch_type, creator_name, get_last_one, parent_path
• Outputs: Unique batch ID for organizing outputs
• Use Case: Organize generated content into structured batches

Ino DateTime As String

Generates formatted datetime strings with customizable components.

• Inputs: seed, date/time component toggles, separators
• Outputs: Formatted datetime string
• Use Case: Timestamp generation for file naming and organization

🔧 Basic Utility Nodes (InoNodes)

Ino Not Boolean

Performs boolean negation operation.

• Inputs: boolean (input value)
• Outputs: Negated boolean value
• Use Case: Logic operations in conditional workflows

Ino Int Equal

Compares two integers for equality.

• Inputs: int_a, int_b (integer values)
• Outputs: Boolean result of equality comparison
• Use Case: Conditional logic based on numeric comparisons

Ino String Toggle Case

Toggles string case (upper/lower) based on settings.

• Inputs: enabled, input_string, toggle_to (case option)
• Outputs: Case-modified string
• Use Case: Text formatting and standardization

Ino Bool To Switch

Converts boolean values to switch/selector format.

• Inputs: enabled, input_bool
• Outputs: Switch-compatible output
• Use Case: Interface compatibility between different node types

Ino String To Combo

Converts string input to combo/dropdown selection format.

• Inputs: enabled, input_string
• Outputs: Combo-compatible selection
• Use Case: Dynamic UI element generation

Ino Random Int In Range

Generates random integers within specified range.

• Inputs: enabled, int_min, int_max, length
• Outputs: Random integer(s) within range
• Use Case: Randomization for procedural generation

Ino Int To String

Converts integer values to string format.

• Inputs: input_int (integer value)
• Outputs: String representation
• Use Case: Data type conversion for text processing

Ino Int To Float

Converts integer values to float.

• Inputs: input_int
• Outputs: Float value
• Use Case: Numeric conversions for downstream nodes

Ino Float To Int

Converts floating-point values to integer using a selected method.

• Inputs: input_float, method (round/floor/ceil)
• Outputs: Integer value
• Use Case: Numeric conversions and clamping

Ino Save Images

Saves a batch of images with a given filename prefix.

• Inputs: images (IMAGE), filename_prefix (string)
• Outputs: Saved images with standardized filenames
• Use Case: Persist generated outputs with consistent naming

Ino Image Resize By Longer Side V1

Resizes an image so that its longer side matches a target size, preserving aspect ratio.

• Inputs: image, size, interpolation_mode
• Outputs: Resized image
• Use Case: Preprocess images to a standard maximum side length

Ino Image Resize By Longer Side And Crop V2

Resizes then optionally crops/pads to target dimensions with positioning control.

• Inputs: image, target_width, target_height, padding_color, interpolation, crop, position, x, y
• Outputs: Processed image
• Use Case: Prepare images to exact sizes for models/pipelines while controlling crop position

📁 File Operations (InoFileHelper)

Increment Batch Name

Auto-increments batch names for sequential processing.

• Inputs: enabled, seed, batch naming parameters
• Outputs: Incremented batch name
• Use Case: Automated batch processing with sequential naming

Zip

Creates zip archives from files and folders.

• Inputs: enabled, seed, source path, destination path
• Outputs: Success status and archive information
• Use Case: Compress generated content for storage or sharing

Unzip

Extracts files from zip archives.

• Inputs: enabled, seed, zip path, output path
• Outputs: Extraction status and file information
• Use Case: Extract datasets or batch process archived content

Remove File

Safely removes files from the filesystem.

• Inputs: enabled, seed, file_path
• Outputs: Deletion status and confirmation
• Use Case: Cleanup operations and file management

Remove Folder

Safely removes folders and their contents.

• Inputs: enabled, seed, folder_path
• Outputs: Deletion status and confirmation
• Use Case: Cleanup operations and directory management

🌐 JSON & Data Processing (InoNodes)

Ino Json

Manipulates JSON objects by adding or modifying fields.

• Inputs: base_json (JSON string), field_name, field_value
• Outputs: Success status, message, modified JSON
• Use Case: Dynamic JSON configuration and data manipulation

Ino Save Json

Saves JSON strings to files in the output directory.

• Inputs: json_string, local_path
• Outputs: Save status and confirmation message
• Use Case: Export configuration data and processing results

🌍 HTTP Operations (InoNodes)

Ino Http Call

Performs HTTP requests with comprehensive options.

• Inputs: enabled, url, request_type (GET/POST/PUT/DELETE/PATCH), headers, json_payload
• Optional: trust_env, follow_redirects, enable_retries, max_retries
• Outputs: Success status, status code, message, response
• Use Case: API integration, webhook calls, external service communication

☁️ S3 Cloud Storage (InoS3Helper)

Ino S3 Config

Configures S3 connection settings and credentials.

• Inputs: S3 credentials and configuration parameters
• Outputs: S3 client configuration
• Use Case: Initialize S3 connections for upload/download operations

Ino S3 Upload Image

Uploads images to S3 storage with metadata preservation.

• Inputs: Image data, S3 path, metadata options
• Outputs: Upload status and S3 URL
• Use Case: Cloud backup of generated images

Ino S3 Upload File

Uploads any file type to S3 storage.

• Inputs: File path, S3 destination, upload options
• Outputs: Upload status and S3 location
• Use Case: Cloud backup of models, datasets, or processed files

Ino S3 Upload Folder

Uploads entire folders to S3 with structure preservation.

• Inputs: Local folder path, S3 destination path
• Outputs: Upload status and file count
• Use Case: Batch upload of training datasets or output collections

Ino S3 Upload String

Uploads a text/string payload as an object to S3.

• Inputs: String content, destination path, content type
• Outputs: Upload status and S3 URL
• Use Case: Save JSON, prompts, or logs directly to S3

Ino S3 Download Image

Downloads images from S3 storage.

• Inputs: S3 image path, download options
• Outputs: Downloaded image data
• Use Case: Retrieve reference images or previously uploaded content

Ino S3 Download File

Downloads files from S3 storage.

• Inputs: S3 file path, local destination
• Outputs: Download status and local file path
• Use Case: Retrieve models, datasets, or configuration files

Ino S3 Download Folder

Downloads entire folders from S3 with structure preservation.

• Inputs: S3 folder path, local destination path
• Outputs: Download status and file count
• Use Case: Retrieve complete datasets or backup collections

☁️ Cloudreve Integration (InoCloudreve)

Cloudreve Init

Initializes connection to Cloudreve cloud storage server.

• Inputs: enabled, seed, server_address
• Outputs: Connection status and messages
• Use Case: Setup Cloudreve cloud storage connection

Cloudreve Signin

Authenticates with Cloudreve using email and password.

• Inputs: enabled, seed, email, password
• Outputs: Authentication status and session information
• Use Case: Login to Cloudreve for file operations

Cloudreve Upload File

Uploads files to Cloudreve cloud storage.

• Inputs: enabled, seed, local_path, cloud_path, storage_policy
• Outputs: Upload status and confirmation
• Use Case: Cloud backup using Cloudreve storage

🎨 Prompt Generation (InoNodes)

Ino Random Character Prompt

Generates detailed random character prompts with facial features, makeup, and styling options.

• Inputs: Seed, various toggle options for different facial features
• Outputs: Complete character description prompt and seed
• Use Case: Generate diverse character prompts for portrait generation

🧮 LoRA Configuration (InoNodes)

Ino Calculate Lora Config

Calculates optimal LoRA training parameters based on dataset characteristics.

• Inputs: enabled, dataset_count, max_batch_size, target_epochs, max_lora_parts
• Outputs: Comprehensive LoRA training configuration (dim, alpha, steps, batch size, learning rate, etc.)
• Use Case: Optimize LoRA training settings for custom models

🔬 Sampling & Model Management (InoSamplerHelper)

Ino Random Noise

Generates random noise for sampling operations.

• Outputs: Random noise tensor for sampling
• Use Case: Initialize sampling processes with randomized starting points

Ino Get Model Config

Retrieves model configuration settings.

• Inputs: Model configuration parameters
• Outputs: Current model configuration
• Use Case: Load saved model settings for consistent generation

Ino Show Model Config

Displays current model configuration for review.

• Inputs: Configuration data
• Outputs: Formatted configuration display
• Use Case: Debug and verify model settings

Ino Update Model Config

Updates and modifies model configuration parameters.

• Inputs: Configuration data and new parameters
• Outputs: Updated configuration
• Use Case: Dynamically adjust model settings during workflows

Ino Get Lora Config

Retrieves LoRA configuration settings.

• Inputs: LoRA configuration parameters
• Outputs: Current LoRA settings
• Use Case: Load saved LoRA configurations

Ino Show Lora Config

Displays current LoRA configuration for review.

• Inputs: LoRA configuration data
• Outputs: Formatted LoRA configuration display
• Use Case: Debug and verify LoRA settings

Ino Load Sampler Models

Loads and manages sampling models.

• Inputs: Model specifications and loading parameters
• Outputs: Loaded model instances
• Use Case: Initialize models for generation workflows

Ino Get Conditioning

Extracts and processes conditioning data for generation.

• Inputs: Configuration, CLIP model, positive/negative prompts
• Outputs: Processed conditioning for positive and negative prompts
• Use Case: Prepare text conditioning for image generation

Ino Get Sampler Config

Retrieves sampling configuration and parameters.

• Inputs: Sampling configuration parameters
• Outputs: Complete sampling configuration
• Use Case: Load sampling settings for consistent generation results

🧩 Model Utilities (InoModelHelper)

Ino Validate Model

Validates that a required model file exists locally; if missing, downloads it from S3 using the provided configuration.

• Inputs: enabled, s3_config (STRING), model_type (e.g., checkpoints, vae, loras, etc.), model_name (e.g., flux1dev/ae.safetensors)
• Outputs: success (BOOLEAN), msg (STRING)
• Use Case: Ensure necessary models are present before running a workflow, fetching them automatically from S3 if needed

🔐 Basic Auth Middleware (InoBasicAuth)

Adds optional Basic Authentication to ComfyUI's HTTP endpoints using aiohttp middleware.

• Enable by setting environment variables before starting ComfyUI:
  • COMFYUI_USERNAME
  • COMFYUI_PASSWORD
• WebSocket path /ws is excluded to preserve UI connectivity.
• Also provides a simple node: Ino Basic Auth Node that outputs a BASIC_AUTH token for wiring in workflows if needed.

🤖 OpenAI Helpers (InoOpenaiHelper)

Nodes to interact with OpenAI's Responses API.

• Ino Openai Config: supply API key, timeout, and retry policy.
• Ino Openai Text Generation: send a prompt to a selected model (e.g., gpt-5) and receive output text and metadata.

Usage

After installation, the nodes will appear in your ComfyUI node menu under the following categories:

• InoNodes - File utilities, basic operations, JSON processing, HTTP calls
• InoS3Helper - S3 cloud storage operations
• InoCloudreve - Cloudreve cloud storage integration
• InoFileHelper - Advanced file operations
• InoSamplerHelper - Model and sampling management
• InoModelHelper - Model utilities (validation/download)
• InoOpenaiHelper - OpenAI integration
• InoBasicAuth - Basic authentication utilities

Simply drag and drop the nodes into your ComfyUI workflow and configure them according to your needs. Most nodes include enable/disable toggles for conditional execution and detailed error handling.

Requirements

• ComfyUI (latest version recommended)
• Python 3.8+
• Dependencies listed in requirements.txt (most are auto-installed when using pip or ComfyUI-Manager)

License

This project is licensed under the terms specified in the LICENSE file.

Support

For issues and questions, please visit the GitHub repository.

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Version: 1.2.2 Publisher: Inoland Contact: contact@inoland.net