ComfyUI Pruna API

ComfyUI custom nodes for running Pruna API models directly inside ComfyUI workflows.

Nodes

Pruna Text to Image

Generate images from text prompts using the Pruna API.

Inputs

Input	Type	Description
prompt	string	Text description of the image to generate
model	dropdown	Pruna API model to use
aspect_ratio	dropdown	Output image aspect ratio
api_key	string	Your Pruna API key (or set PRUNA_API_KEY env var)

Output: IMAGE — compatible with any ComfyUI node that accepts an image.

Supported models: p-image

Supported aspect ratios: 1:1, 16:9, 9:16, 4:3, 3:4, 3:2, 2:3

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Pruna Text to Image LoRA

Generate images from text prompts with a custom LoRA using the Pruna API.

LoRA weights must be a HuggingFace URL in the format huggingface.co/<username>/<repo>[/<filename>]. LoRAs must be trained with p-image-trainer.

Inputs

Input	Type	Description
prompt	string	Text description of the image to generate
model	dropdown	Pruna API model to use
lora_weights	string	HuggingFace path to LoRA weights
lora_scale	float	LoRA influence scale (−1.0 – 3.0, default 0.5)
aspect_ratio	dropdown	Output image aspect ratio
api_key	string	Your Pruna API key (or set PRUNA_API_KEY env var)
hf_api_token	string (optional)	HuggingFace token for private repos

Output: IMAGE

Supported models: p-image-lora

Supported aspect ratios: 1:1, 16:9, 9:16, 4:3, 3:4, 3:2, 2:3

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Pruna Image Edit

Edit an image with a text instruction using the Pruna API.

Inputs

Input	Type	Description
image	IMAGE	Input image to edit
prompt	string	Edit instruction
model	dropdown	Pruna API model to use
aspect_ratio	dropdown	Output aspect ratio (match_input_image preserves the original)
api_key	string	Your Pruna API key (or set PRUNA_API_KEY env var)

Output: IMAGE

Supported models: p-image-edit

Supported aspect ratios: match_input_image, 1:1, 16:9, 9:16, 4:3, 3:4, 3:2, 2:3

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Pruna Image Edit LoRA

Edit an image with a text instruction and a custom LoRA using the Pruna API.

LoRA weights must be a HuggingFace URL in the format huggingface.co/<username>/<repo>[/<filename>]. LoRAs must be trained with p-image-edit-trainer.

Inputs

Input	Type	Description
image	IMAGE	Input image to edit
prompt	string	Edit instruction
model	dropdown	Pruna API model to use
lora_weights	string	HuggingFace path to LoRA weights
lora_scale	float	LoRA influence scale (−1.0 – 3.0, default 0.5)
aspect_ratio	dropdown	Output aspect ratio
api_key	string	Your Pruna API key (or set PRUNA_API_KEY env var)
hf_api_token	string (optional)	HuggingFace token for private repos

Output: IMAGE

Supported models: p-image-edit-lora

Supported aspect ratios: match_input_image, 1:1, 16:9, 9:16, 4:3, 3:4, 3:2, 2:3

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Pruna Image Upscale

AI-upscale an image to a target megapixel size using the Pruna API.

Inputs

Input	Type	Description
image	IMAGE	Input image to upscale
target_mp	int	Target size in megapixels (1–8, default 4)
enhance_details	boolean	Apply detail enhancement pass
enhance_realism	boolean	Apply realism enhancement pass
api_key	string	Your Pruna API key (or set PRUNA_API_KEY env var)

Output: IMAGE

Model: p-image-upscale (fixed)

Pricing: $0.005/image for 1–4 MP target · $0.01/image for 5–8 MP target

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Pruna Video

Generate a video from a text prompt using the Pruna API. Optionally connect an image to animate it instead of generating from scratch (image-to-video mode).

Inputs

Input	Type	Description
prompt	string	Text description of the video
duration	int	Video length in seconds (1–20, default 5)
resolution	dropdown	Output resolution (720p or 1080p)
aspect_ratio	dropdown	Output aspect ratio
draft	boolean	Use draft mode (faster, lower cost)
api_key	string	Your Pruna API key (or set PRUNA_API_KEY env var)
image	IMAGE (optional)	Source image to animate (image-to-video mode)

Output: STRING (video URL) — pass to a video preview or download node.

Model: p-video (fixed)

Supported aspect ratios: 16:9, 9:16, 4:3, 3:4, 3:2, 2:3, 1:1

Pricing:

Resolution	Draft OFF	Draft ON
720p	$0.02/sec	$0.005/sec
1080p	$0.04/sec	$0.01/sec

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Installation

Via ComfyUI Manager (recommended)

Search for ComfyUI Pruna API in the ComfyUI Manager and click Install.

Manual installation

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

Restart ComfyUI. The nodes appear under the pruna ai category in the node browser.

Authentication

Get your API key from the Pruna developer portal.

You can provide your key in two ways:

Option 1 — Node field: Type your key directly into the api_key input on the node.

Option 2 — Environment variable (recommended): Set PRUNA_API_KEY before launching ComfyUI:

# macOS / Linux
export PRUNA_API_KEY="your-key-here"
python main.py

# Windows
set PRUNA_API_KEY="your-key-here"
python main.py

If both are provided, the node field takes priority.

License

MIT