Transform Single OpenAI Responses into Multiple Actionable Text Parts
Ever generated AI content in your Bubble app only to receive one massive block of text when you actually need multiple separate pieces? This common challenge frustrates many no-code builders working with OpenAI integration in their Bubble applications.
In this comprehensive tutorial, we demonstrate exactly how to take AI-generated content from OpenAI and intelligently split it into multiple, manageable text components that your users can interact with individually.
The Problem: Single Block AI Responses
When you prompt OpenAI to generate multiple items - like three social media posts, several product descriptions, or multiple email subject lines - the API typically returns everything as one continuous text block. This creates usability issues when you want users to:
• Copy individual pieces to their clipboard
• Save specific items to their database
• Edit or customize separate components
• Display content in organized, digestible formats
The Solution: Smart Text Splitting with Repeating Groups
The key to solving this challenge lies in understanding how to craft reliable OpenAI prompts that return consistently formatted output, then leveraging Bubble's powerful split by function within repeating groups.
Our approach involves using custom states to store the AI response, then creating a repeating group that transforms that single text item into a list of separate text components. The magic happens when you configure the data source to split by specific delimiters that OpenAI consistently uses in its responses.
Advanced Features: Individual Copy Functionality
Once you've successfully split your AI content, you can enhance user experience by adding copy-to-clipboard functionality for each individual text piece. This requires dynamic element IDs and proper workflow configuration to ensure each copy button targets the correct text content.
The tutorial covers essential concepts including:
• Configuring repeating groups for dynamic text content
• Using split by functions with OpenAI response patterns
• Implementing copy-to-clipboard plugins with dynamic targeting
• Creating unique element IDs for multiple instances
Beyond Basic Splitting: Database Integration
While this tutorial focuses on the fundamental splitting technique, advanced implementations often require saving split content to your database. This involves backend workflows and iteration processes to handle variable numbers of generated items - a technique that becomes crucial when building scalable AI-powered applications.
For no-code builders serious about creating sophisticated AI integrations in Bubble, mastering text splitting opens up countless possibilities for creating user-friendly interfaces that make AI-generated content truly actionable.
Master Advanced OpenAI Integration Techniques
This tutorial represents just one piece of building comprehensive AI-powered applications in Bubble. Planet No Code members get access to our complete OpenAI integration series, including advanced prompting techniques, database optimization strategies, and scalable backend workflows that professional no-code developers use to build production-ready applications.