Oli Prompt Tools

Last Commit	5d27dac (March 11, 2026 12:00 am)
Repository	https://github.com/magicoli/oli-prompt-tools
License	GNU AFFERO GENERAL PUBLIC LICENSE

A collection of practical ComfyUI utility nodes designed to reduce workflow complexity. Each node solves a specific recurring problem — avoiding VRAM crashes, picking prompts deterministically, filtering incompatible LoRAs, or labelling model pipelines. No external dependencies beyond the standard ComfyUI environment.

Nodes

Node	Category	Purpose
Mega Lora Loader	Oli/loaders	Stackable multi-LoRA loader with automatic compatibility filtering
Prompt Line Pick	Oli/prompt	Seed-driven line picker — uniform distribution, fully independent instances
Video Frame Limit	Oli/utils	Caps video duration to avoid VRAM out-of-memory crashes
Model Info	Oli/utils	Returns architecture details of any connected model
Node Label	Oli/utils	Reads and passes through the upstream node’s title

Installation

Via ComfyUI Manager (recommended): search for Oli Prompt Tools and click Install.

Manually:

cd ComfyUI/custom_nodes
git clone https://github.com/magicoli/oli-prompt-tools

Restart ComfyUI. No additional dependencies required.

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Mega Lora Loader (Oli)

Stackable multi-LoRA loader inspired by rgthree’s Power Lora Loader. Key additions: stackable, and each LoRA’s safetensors header is checked against the connected model’s key map before loading — incompatible LoRAs are silently skipped rather than producing errors or corrupted output.

• Add as many LoRA rows as needed with the ➕ Add LoRA button.
• Each row has an on/off toggle, a LoRA selector, and a strength slider.
• Incompatible LoRAs are highlighted in the UI (orange = incompatible, grey = disabled).
• Connect the enable input to a boolean condition to bypass all LoRAs at once — useful with switch or router nodes.
• Two usage modes: connect model/clip to apply LoRAs immediately, or leave them unconnected to only build a LORA_STACK without applying it. In stack-only mode the node acts as a LoRA definition block — chain several together, then feed the final stack to a downstream loader that has model/clip connected. This lets you define LoRAs once and apply them to multiple models at different points in the workflow.

Inputs

Input	Type	Default	Description
lora_stack	LORA_STACK	—	Incoming stack from another loader (optional)
model	MODEL	—	Model to apply LoRAs to (optional)
clip	CLIP	—	CLIP encoder to apply LoRAs to (optional)
(lora rows)	—	—	Added dynamically via the ➕ button
enable	BOOLEAN	true	When false, passes model/clip/lora_stack through unchanged

Outputs

Output	Type	Description
lora_stack	LORA_STACK	Full stack including upstream entries
MODEL	MODEL	Model with all compatible LoRAs applied
CLIP	CLIP	CLIP with all compatible LoRAs applied

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Prompt Line Pick (Oli)

Seed-driven reimplementation of the easy promptLine concept. Replaces start_index + max_rows with a single seed input. The selected line is determined by sha256(seed:node_id) % len(lines).

• Uniform distribution — every line has equal probability regardless of list length.
• Full independence — multiple instances in the same workflow each pick independently, even with the same seed, because the node ID acts as a channel discriminator.
• No prime modulo management — the SHA-256 hash eliminates correlation between lists of similar length.
• Preserves the COMBO output for use with COMBO-typed inputs.

Inputs

Input	Type	Default	Description
prompt	STRING	—	One item per line
seed	INT	0	Workflow seed — share with KSampler for reproducible pairs
remove_empty_lines	BOOLEAN	true	Strip blank lines before picking

Outputs: STRING, COMBO

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Video Frame Limit (Oli)

Caps video generation duration to avoid VRAM out-of-memory crashes. The frame budget is derived from transformer peak memory first principles rather than empirical constants:

bytes_per_latent_frame = TENSOR_COPIES × (width÷8) × (height÷8) × hidden_dim × 2
max_frames             = total_vram × safety_margin ÷ bytes_per_latent_frame

Where TENSOR_COPIES = 5 (Q, K, V, attention output, residual activations) and hidden_dim is auto-detected from the connected model. Uses total VRAM rather than free VRAM — ComfyUI offloads weights layer-by-layer, so peak activation memory scales with total VRAM, not the remainder after model loading.

The node displays detected VRAM, model name, hidden dim, requested and capped frames directly on the canvas after each execution — making it usable as a standalone config panel for the whole generation.

Inputs

Input	Type	Default	Description
width	INT	832	Generation width in pixels
height	INT	480	Generation height in pixels
fps	FLOAT	16	Frames per second
duration	FLOAT	10	Requested duration in seconds
safety_margin	FLOAT	0.95	Fraction of total VRAM to budget (0.95 = 5% headroom)
model	MODEL	—	Optional — enables hidden_dim auto-detection

Outputs

Output	Type	Description
width	INT	Pass-through
height	INT	Pass-through
frames	INT	Capped frame count
fps	FLOAT	Pass-through
duration	FLOAT	Actual duration after capping

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Model Info (Oli)

Returns architecture details of any connected model (MODEL, CLIP, VAE, or any other type). Also reads the upstream node’s title. Useful for debugging model pipelines, inspecting what arrived on a bus, or driving conditional logic based on model class.

Inputs

Input	Type	Description
model	*	Any model type (optional)

Outputs

Output	Type	Description
class_name	STRING	Python class name of the model (e.g. WAN21, Flux)
dim	INT	Hidden dimension auto-detected from the model
label	STRING	Title of the upstream node that produced the model

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Node Label (Oli)

Passes any value through and outputs the title of the upstream node at a configurable traversal depth. Useful for labelling outputs, routing between branches, or building self-documenting workflows where node titles carry semantic meaning.

Inputs

Input	Type	Default	Description
depth	INT	1	Hops to travel upstream (1 = direct parent, 2 = grandparent…)
node	*	—	Any value — passed through unchanged (optional)

Outputs

Output	Type	Description
node	*	Pass-through of the input value
label	STRING	Title of the node depth hops upstream

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Examples

The examples/ directory contains minimal starter workflows for each node. Open them in ComfyUI and wire them into your own workflow.

File	Node demonstrated
examples/mega_lora_loader.json	Mega Lora Loader
examples/prompt_line_pick.json	Prompt Line Pick
examples/video_frame_limit.json	Video Frame Limit
examples/model_info.json	Model Info
examples/node_label.json	Node Label

License

GNU Affero General Public License v3.0