# Nilor Nodes Documentation 👺 A collection of utility nodes for ComfyUI focusing on list manipulation, batch operations, and advanced I/O functionality. ## Prerequisites - `comfyui-kjnodes` custom_nodes repo ## 🏭 Generators

Interpolated Float List

Generates a list of interpolated float values based on sections. | Input | Type | Description | |-------|------|-------------| | number_of_floats | INT | Total number of float values to generate | | number_of_sections | INT | Number of sections to divide into | | section_number | INT | Current section being processed | | interpolation_type | ["slinear", "quadratic", "cubic"] | Type of interpolation | | Output | Type | Description | |--------|------|-------------| | floats | FLOAT | List of interpolated float values | **Notes**: Creates smooth transitions between values using scipy's interpolation.

One Minus Float List

Creates an inverted list of float values (1 - x). | Input | Type | Description | |-------|------|-------------| | list_of_floats | FLOAT | Input float list | | Output | Type | Description | |--------|------|-------------| | floats | FLOAT | Inverted float values | **Notes**: Simple inversion operation, useful for creating complementary values.

Remap Float List

Remaps a list of float values from one range to another. | Input | Type | Description | |-------|------|-------------| | list_of_floats | FLOAT | Input float list | | min_input | FLOAT | Minimum input value (default: 0.0) | | max_input | FLOAT | Maximum input value (default: 1.0) | | min_output | FLOAT | Minimum output value (default: 0.0) | | max_output | FLOAT | Maximum output value (default: 1.0) | | Output | Type | Description | |--------|------|-------------| | remapped_floats | FLOAT | Remapped float values | **Notes**: Useful for scaling values between different ranges while preserving relationships.

Inverse Map Float List

Creates a mirror mapping of float values around their midpoint. | Input | Type | Description | |-------|------|-------------| | list_of_floats | FLOAT | Input float list | | Output | Type | Description | |--------|------|-------------| | floats | FLOAT | Inverse mapped values | **Notes**: Automatically determines min/max from input list.

## 🛠️ Utilities

Int To List Of Bools

Converts an integer into a list of boolean values. | Input | Type | Description | |-------|------|-------------| | number_of_images | INT | Number to convert | | Output | Type | Description | |--------|------|-------------| | booleans | BOOLEAN | List of boolean values | **Notes**: Creates a list where first N values are True, rest are False.

List of Ints

Generates a sequential or shuffled list of integers. | Input | Type | Description | |-------|------|-------------| | min | INT | Starting integer (default: 0) | | max | INT | Ending integer (default: 9) | | shuffle | BOOLEAN | Whether to randomize order | | Output | Type | Description | |--------|------|-------------| | ints | INT | List of integers | **Notes**: Output is always a list, even for single values.

Select Index From List

Extracts a single item from a list at the specified index. | Input | Type | Description | |-------|------|-------------| | list_of_any | any | Input list of any type | | index | INT | Index to select (default: 0) | | Output | Type | Description | |--------|------|-------------| | any | any | Selected item | **Notes**: Uses custom AnyType to accept any input type. Handles tensor unpacking automatically.

Shuffle Image Batch

Randomly reorders images in a batch. | Input | Type | Description | |-------|------|-------------| | images | IMAGE | Batch of images | | seed | INT | Random seed for shuffling | | Output | Type | Description | |--------|------|-------------| | images | IMAGE | Shuffled image batch | **Notes**: Maintains batch dimensions while randomizing order.

## 💾 I/O Operations

Save Image To HF Dataset

Uploads images to a HuggingFace dataset. | Input | Type | Description | |-------|------|-------------| | image | IMAGE | Image to upload | | repository_id | STRING | HuggingFace dataset repository | | hf_auth_token | STRING | HuggingFace authentication token | | filename_prefix | STRING | Prefix for saved files | **Notes**: Requires HuggingFace authentication token and repository access.

Save EXR Arbitrary

Saves multi-channel data as an OpenEXR file. | Input | Type | Description | |-------|------|-------------| | channels | any | List of tensor channels | | filename_prefix | STRING | Output filename prefix | **Notes**: Supports arbitrary number of channels. Each channel must have same dimensions.

Save Video To HF Dataset

Uploads video files to a HuggingFace dataset. | Input | Type | Description | |-------|------|-------------| | filenames | VHS_FILENAMES | List of video files | | repository_id | STRING | HuggingFace dataset repository | | hf_auth_token | STRING | HuggingFace authentication token | | filename_prefix | STRING | Prefix for saved files | **Notes**: Handles batch upload of multiple video files.

## 📡 Core Nilor Services

Worker Consumer Service

The `worker_consumer.py` script is a background service that runs on each ComfyUI worker. It is responsible for pulling jobs from the central ElasticMQ `jobs_to_process` queue and submitting them to its local ComfyUI instance for processing. This service is essential for the distributed architecture of the system. **Key Responsibilities:** - Continuously polls the `jobs_to_process` queue for new jobs using long polling. - When a job is received, it extracts the workflow data and submits it to the local ComfyUI server. - Normalizes OS-sensitive path formatting in the ComfyUI `prompt` graph (e.g. converts `Flux1/ae.safetensors` ↔ `Flux1\ae.safetensors`) so workflows authored on Linux/Windows run on the current worker OS. - Deletes the job message from the queue upon successful submission to prevent reprocessing. - If submission fails, the message remains on the queue to be picked up by another worker. **Workflow normalization toggle:** - Set `NILOR_WORKFLOW_OS_NORMALIZATION_ENABLED=false` (via environment or `config/config.json5`) to disable this behavior (default: enabled).

## ⚙️ Configuration and Runtime Model The sidecar uses a small, typed configuration loader with JSON5 defaults and optional environment overrides. - **Precedence**: environment variables > `config/config.json5` (controlled by `allow_env_override: true`). - **No hot‑reload**: configuration is loaded once at process start and passed to components. - **Paths/keys**: JSON5 at `ComfyUI/custom_nodes/nilor-nodes/config/config.json5` with `NILOR_*` keys (e.g., `NILOR_COMFYUI_API_URL`, `NILOR_SQS_ENDPOINT_URL`). Secrets (AWS secret) must be set via `.env`. - **Typed object**: loader returns a `NilorNodesConfig` with `comfy`, `worker`, and `hygiene` sections. Pseudocode usage: ```pseudo cfg = load_nilor_nodes_config() # Comfy endpoints http_url = cfg.comfy.api_url + "/prompt" ws_url = cfg.comfy.ws_url + "/ws" # SQS client params endpoint = cfg.worker.sqs_endpoint_url region = cfg.worker.aws_region access_key = cfg.worker.aws_access_key_id secret_key = cfg.worker.aws_secret_access_key client_id = cfg.worker.worker_client_id ``` Current integrations: - `worker_consumer.py`: loads config at startup, reuses a single HTTP session, and uses `cfg.comfy`/`cfg.worker` exclusively. - `media_stream.py`: uses `cfg.worker` for SQS completion notifications.

Environment Variables

The `nilor-nodes` require a `.env` file to be present in the `ComfyUI` directory to configure the connection to the core services (MinIO, ElasticMQ, and the Brain API). To set it up, create a file named `.env` in the root of your `ComfyUI` directory by copying the `.env.example` template. **Instructions:** 1. Create a new file named `.env` in the `ComfyUI` directory. 2. Copy the contents of the `.env.example` file into your new `.env` file. 3. Replace the placeholder values with your actual credentials and endpoint URLs for your local or production environment.

Name	Type	Default	Description
input_name	STRING	my_string_input	—
value	STRING		—

Name	Type	Description
string	STRING	—
_controller_hook	CONTROLLER_HOOK	—

👺 User Input (String)

Inputs (2)

Outputs (2)