Venice AI

Use Venice AI for chat, image generation, embeddings, and more

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Overview

The node integrates with Venice AI to generate images from text prompts using various configurable parameters. It supports advanced image generation models and options for customizing the output, such as size, style, format, and safety filters. This node is useful in scenarios where automated image creation is needed based on descriptive text, such as generating artwork, concept visuals, marketing materials, or creative content.

For example, a user can input a prompt describing a fantasy landscape and receive a generated image matching that description. The node also supports returning the image either as base64-encoded JSON or as raw binary data, enabling flexible downstream processing.

Properties

Name Meaning
Model Image generation model to use (e.g., "hidream").
Prompt Text description of the image to generate.
Negative Prompt Elements or features that should be excluded from the image.
Width Width of the generated image in pixels.
Height Height of the generated image in pixels.
Steps Number of inference steps controlling generation quality/detail.
CFG Scale Controls how closely the image follows the prompt (higher means stricter adherence).
Seed Random seed for reproducibility of results.
Format Output image format; options are WebP, PNG, JPEG.
Safe Mode Whether to blur adult content for safety.
Hide Watermark Option to hide the Venice watermark on the image.
Style Preset Optional style preset to apply (e.g., "3D Model", "Anime").
Return Binary If true, returns the image as binary data instead of base64 JSON.

Output

  • The node outputs an array of items, each containing a json field with the API response.
  • For image generation with return_binary set to false (default), the output JSON contains the generated image data encoded in base64 or URL form depending on the operation variant.
  • If return_binary is true, the node outputs the image as binary data under the binary.data property, with the filename extension matching the selected format (e.g., .webp, .png, .jpeg).
  • This binary output allows direct usage or saving of the image without additional decoding steps.

Dependencies

  • Requires an active connection to the Venice AI API service.
  • Needs an API key credential configured in n8n for authentication with Venice AI.
  • The node uses internal helper functions to make HTTP requests to Venice AI endpoints for image generation.

Troubleshooting

  • Missing Binary Data Property: When performing operations like upscaling or editing, if the specified binary property does not exist on the input item, the node throws an error indicating the missing binary data property. Ensure the input item contains the correct binary image data under the specified property name.
  • API Request Failures: Network issues or invalid API credentials may cause request failures. Verify API key validity and network connectivity.
  • Invalid Parameter Values: Providing unsupported values for properties like image format or model may result in errors. Use only supported options as listed in the properties.
  • Large Image Sizes: Requesting very large image dimensions or high step counts may increase processing time or exceed API limits.

Links and References

This summary covers the static analysis of the node's image generation operation, focusing on its inputs, outputs, and typical usage patterns.

Discussion