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What is Replicate

Replicate lets you run open-source machine learning models with just a few lines of code—no ML expertise required.

It’s an API platform where developers can generate images, videos, audio, and more using community-built or custom AI models. Whether you’re building an MVP, prototyping creative features, or adding production-grade AI to your app, Replicate gives you fast, flexible access to state-of-the-art models.

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Why use Replicate with Lovable?

Replicate fits naturally into Lovable’s AI-first app-building workflow. You can:

  • Generate dynamic visuals (e.g. course banners, avatars, scenes)
  • Use multimodal AI (image, video, speech, text-to-speech)
  • Add real-time content generation without running your own model infrastructure

With Lovable’s built-in knowledge of Replicate’s API and models, integration takes minutes—not days. Just describe what you want, and Lovable handles the rest.

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Step by Step Tutorial

In this tutorial, we walk through how to integrate Replicate into a Lovable application to dynamically generate course banner images, adding a new layer of interactivity and polish to your product. You’ll also learn how Replicate fits into Lovable’s broader AI workflow—including how to pair it with OpenAI for course content, Superbase for backend logic, and real-time AI conversations using OpenAI’s WebRTC API.

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Step 1 – Build a Language Tutor App

We start by creating a Spanish-learning web app with Lovable. This includes:

  • A user login flow
  • AI-powered chat for Spanish tutoring
  • Voice recording and playback
  • Translation features

This gives users a personalized AI tutor that they can talk to, type to, and learn with.

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Step 2 – Generate Courses with AI

We enhance the app with AI-generated courses:

  • Users define a topic (e.g., Questions to ask at a barbecue).
  • An OpenAI-powered function creates 10 multiple choice questions in Spanish.
  • Courses are saved to the user’s account with Supabase and can be revisited anytime.
  • Users get feedback on each question with explanations.
  • Automatically generate a course banner image that matches the topic. Replicate uses the Flux Schnell model for fast image generation and dynamically inject the image into the course page.

How it Works:

  1. We call the Replicate API when a new course is created.
  2. The prompt is dynamically generated based on the course topic.
  3. Replicate returns an image URL, which is used as the banner for the course.

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Step 3 – Add Visuals with Replicate

Now, let’s make things visual with Replicate.

Example Prompt:

A beautiful, educational, and engaging scene about topic in digital art style. Vibrant colors. No text on image.

Example Response Handling:

Some Replicate models return a single image URL, others return an array. Make sure your Lovable function correctly extracts the output, e.g.:

const imageUrl = response.output[0]
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Step 4 – Use Replicate Playground for Fine-Tuning

Replicate’s Playground makes it easy to test prompts and get code snippets:

  • Tweak prompts until you’re happy with the output
  • Use the API snippet generator for Node.js, Python, etc.
  • Copy-paste directly into Lovable’s backend functions

Use Playground Beta to compare multiple outputs at once.

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Step 5 – Real-Time Conversations with OpenAI

To simulate human conversations, we added a real-time Spanish-speaking feature using OpenAI’s WebRTC API:

  • Users can speak directly to their AI tutor.
  • The AI understands, responds, and corrects pronunciation in real time.
  • This makes language learning much more immersive and practical.

This feature integrates smoothly with Lovable’s voice input, WebRTC handling, and frontend chat UI.

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Tips & Gotchas

  • Model Output Variance: Replicate models differ in how they return outputs. Always inspect the actual JSON returned from the playground.
  • Prompt Iteration is Key: Small prompt changes can greatly affect image quality. Use the playground to experiment.
  • Backend Logs: Use Supabase Edge logs to debug your API calls. Lovable supports in-app log fetching.
  • Version Control in Lovable: Each prompt edit is auto-committed, but you can manually track checkpoints using the “Deploy” feature for production-ready states.

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FAQ

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Resources