Integrations

Supercharge Leap with Relevance AI

Leap AI is an integration platform that allows developers to incorporate powerful AI image generation and model training into their applications. With Relevance AI, you can elevate these features, leveraging AI Agents to streamline and enhance your image workflows.

Give your AI Agents Leap Superpowers

Leap AI empowers developers with robust tools for custom model training and image generation. Relevance AI amplifies these capabilities by enabling intelligent AI Agents to automate and optimize image processing tasks.

Dynamic Model Orchestration

Seamlessly switch between multiple AI models to optimize performance and cost efficiency in real-time

Intelligent Failover Protection

Maintain uninterrupted operations through automated model switching when performance issues arise

Cost-Efficient Scaling

Automatically balance workloads across models to maximize cost efficiency while maintaining quality

Tools

Equip AI Agents with the Leap Tools they need

Relevance AI seamlessly integrates with Leap AI to enhance your workflows with advanced image generation capabilities.

Leap - Create Image Generation Job
Creates an AI image generation task based on text prompts, allowing customization of image count, face restoration, and webhook notifications for completion
Leap - Upload Image Samples
Uploads multiple images to a specified Leap model, with options to control the response format as either an object or array
Leap - Create Model
Initializes a new AI model with customizable parameters for subject type, keywords, and identifiers, supporting various predefined categories like Person, Animal, or Style
Name
Leap API Call
Description
Make an authorized request to a Leap API
Parameters
["OAuth account authentication", "HTTP method selection (GET, POST, PUT, DELETE, PATCH)", "Custom request path", "Request body configuration", "Custom header support"]
Use Case
A digital agency uses Leap API Call to automate AI-powered image generation for their e-commerce clients, seamlessly creating product variations and lifestyle shots by making authenticated requests to Leap's image generation endpoints. This integration enables them to scale their creative production while maintaining consistent quality across thousands of product images.

Security & Reliability

The Leap AI integration platform allows developers to seamlessly integrate advanced AI image generation and model training capabilities into their applications. With a REST API interface, you can easily access features such as custom model creation, image generation, and sample management.

Key benefits include quick implementation of AI image generation, custom model training and management, webhook support for asynchronous operations, face restoration capabilities, and batch image processing.

To get started, ensure you have a Leap AI account and the necessary OAuth credentials with the `pipedream-leap-read-write` permission scope. Your system should meet the requirements of Node.js 12.x or higher, HTTPS support for webhook callbacks, and a reliable internet connection for API calls.

Installation is straightforward: simply install the Leap AI SDK using npm, configure authentication with your OAuth account ID, and set up a basic configuration file. From there, you can create custom models, upload training images, and generate images with ease.

For troubleshooting, common issues include authentication errors, model creation failures, and image generation issues. Implementing best practices such as error handling, webhook implementation, and resource management will help ensure smooth operation.

For further assistance, refer to the Leap AI documentation or reach out to their support team.

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 Leap AI + Relevance AI integration without writing code:
  • Start with a clear model structure: Define unique titles and consistent subject types for your custom models.
  • Utilize sample management: Organize and upload training images in batches to streamline the model training process.
  • Configure webhooks carefully: Ensure your webhook URL is accessible and properly set up to handle callbacks from Leap AI.
  • Test image generation: Run generation jobs with sample prompts before scaling to ensure quality and performance.
  • Monitor API usage: Keep track of your rate limits and implement exponential backoff for retries to avoid throttling.