Integrations

Supercharge Runware with Relevance AI

Runware is an integration platform that provides AI-driven image generation, manipulation, and analysis through a simple API. With Relevance AI, you can elevate your image processing tasks by leveraging AI Agents for smarter, more efficient workflows.

Give your AI Agents Runware Superpowers

Runware offers powerful image generation and manipulation tools, while Relevance AI empowers these capabilities with intelligent AI Agents that can automate and optimize your image tasks.

Visual Intelligence Mastery

Empowers agents with advanced image analysis and manipulation capabilities across multiple visual processing tasks.

Workflow Orchestration

Enables seamless automation of complex processes by connecting multiple specialized tools in a unified sequence.

Adaptive Intelligence

Learns and optimizes workflows based on real-time performance data and execution patterns.

Tools

Equip AI Agents with the Runware Tools they need

Relevance AI seamlessly integrates with Runware to enhance your image processing workflows with advanced AI capabilities.

Runware - Image Inference
A powerful image generation tool that leverages Stable Diffusion to create images from text prompts, with support for various generation modes including text-to-image, image-to-image, inpainting, and refinement
Runware - Image Upscale
An image enhancement tool that increases image resolution while maintaining quality, allowing for upscaling by factors of 2-4x the original dimensions
Runware - Image Background Removal
Advanced tool for removing image backgrounds with precision, featuring alpha matting and mask processing capabilities for clean edge detection and smooth transitions
Runware - Prompt Enhance
AI-powered prompt optimization tool that expands and improves text prompts to generate better results in image generation tasks
Runware - Image Control Net Preprocess
Specialized preprocessing tool for ControlNet applications, supporting multiple preprocessing types including canny edge detection, depth mapping, and pose estimation
Runware - Image Caption
Automated image analysis tool that generates descriptive captions for images using advanced computer vision and natural language processing
Name
Runware API Call
Description
Make an authorized request to a Runware API
Parameters
["oauth_account_id", "method", "path", "body", "headers"]
Use Case
A data science team uses Runware API Call to automatically fetch and analyze AI model performance metrics across multiple projects. This enables them to monitor model accuracy and make timely adjustments without manual data collection.

Security & Reliability

The Runware integration platform utilizes secure OAuth authentication, ensuring that only authorized applications can access its powerful AI image generation and manipulation capabilities. Relevance AI manages API operations (like image generation, upscaling, and background removal) seamlessly in the background—eliminating concerns about errors, formatting, or rate limits.

With built-in validation and type conversion, your workflows can execute smoothly, even when dealing with various image formats and processing requirements.

No training on your data

Your data remains private and is never utilized for model training purposes.

Security first

We never store anything we don’t need to. The inputs or outputs of your tools are never stored.

Get Started

Best Practices for Non-Technical Users

To get the most out of the Runware + Relevance AI integration without writing code:
  • Start with a clear configuration: Ensure your `runware.config.js` file is properly set up with the correct base URL and headers.
  • Utilize pre-defined models: Leverage the available Stable Diffusion models for common tasks like image generation and background removal to streamline your workflow.
  • Test API calls: Use sample images and prompts to validate your API requests before implementing them in production.
  • Monitor API usage: Keep track of your API calls to avoid hitting rate limits and manage costs effectively.
  • Implement error handling: Use try-catch blocks to gracefully handle errors and log them for troubleshooting.