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.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
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.Step 1 – Build a Language Tutor App
- A user login flow
- AI-powered chat for Spanish tutoring
- Voice recording and playback
- Translation features

Step 2 – Generate Courses with AI

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

Step 3 – Add Visuals with Replicate

Step 4 – Use Replicate Playground for Fine-Tuning
- 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

Step 5 – Real-Time Conversations with OpenAI
- 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.

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.
FAQ
What is Replicate, in simple terms?
What is Replicate, in simple terms?
Who typically uses Replicate?
Who typically uses Replicate?
Do I need my own Replicate API key?
Do I need my own Replicate API key?
What models can I use on Replicate?
What models can I use on Replicate?
- Image generation (e.g. Flux Schnell)
- Video generation
- Audio and text-to-speech
- Language models (though not Replicate’s main focus)
- Custom Cog models (open-source Dockerized models you can deploy)
How do I know which model is right for my use case?
How do I know which model is right for my use case?
What’s the difference between Replicate's old and new API endpoints?
What’s the difference between Replicate's old and new API endpoints?
- The original (
/predictions
) endpoint: most widely known and used. - The newer
/models/{owner}/{model}/versions/{id}/predictions
endpoint: more efficient and flexible.
What if a model returns a different JSON structure than expected?
What if a model returns a different JSON structure than expected?
Can I trigger Replicate image generation only once, or on every course view?
Can I trigger Replicate image generation only once, or on every course view?
- One-time generation on course creation: Saves compute costs and creates a consistent visual identity.
- Dynamic generation per session: If you want fresh visuals each time.
Does Lovable know how to work with Replicate out of the box?
Does Lovable know how to work with Replicate out of the box?
How does Lovable handle package installation like replicate for Node.js?
How does Lovable handle package installation like replicate for Node.js?
What’s the workflow for debugging Replicate errors in Lovable?
What’s the workflow for debugging Replicate errors in Lovable?
- Use Lovable’s Superbase Edge function logs to trace issues.
- If there’s a mismatch between expected vs. actual Replicate response, update your JSON handling.
- Use the “Fix this” button in Lovable to retry or refactor the function logic.
Can I checkpoint my working app state in Lovable?
Can I checkpoint my working app state in Lovable?
- Use the History tab to navigate commits (including bookmarking commits)
- Deploy a version to make it a production checkpoint
- GitHub sync is available for custom version control
How does GitHub integration work with Lovable?
How does GitHub integration work with Lovable?
- Lovable pushes changes to GitHub
- You (or your team) can make changes in an IDE and push back
- Works great for frontend in Lovable + backend in your own editor
What are LLM-friendly .lm.txt or .lm.md files?
What are LLM-friendly .lm.txt or .lm.md files?
Do I need to handle prompt tuning myself?
Do I need to handle prompt tuning myself?
Resources
- Explore Replicate API Docs, Replicate’s model catalog
- Learn more about OpenAI Function Calling, OpenAI WebRTC