In the rapidly evolving world of AI development, there’s always an exciting new tool or technique to explore. Whether you’re already familiar with tools like bolt.new or just beginning your journey with AI, this guide is all about leveling up your workflow. If you prefer to learn through video, check out our tutorial here: Enhancing MoodFlip with Cline and OpenRouter. If text is more your style, let’s dive in!
Overview
In our recent project, we took our basic MoodFlip app and transformed it into a more powerful, feature-rich application. We used Cline, a VS Code extension that’s like GitHub Copilot but supercharged, and OpenRouter to access multiple AI models seamlessly. By leveraging these tools, we implemented various upgrades, including AI-powered responses, emoji-enhanced messages, and a flip history feature.
The aim was to build a production-ready app that incorporated both free and paid AI models, all while maintaining an efficient workflow. Here’s how we did it.
Why Cline?
We initially used bolt.new but found it challenging to switch between repositories seamlessly. Enter Cline, which turned out to be a game-changer. Think of Cline as your personal AI assistant, integrated directly into VS Code. It creates new files, runs commands, and adapts effortlessly to the tasks at hand.
To avoid compatibility issues with StackBlitz, we switched to GitHub Codespaces, which provided a more stable environment for integrating Cline, allowing us to proceed smoothly with our MoodFlip enhancements. Setting up Cline in Codespaces allowed us to proceed with our MoodFlip enhancements, and we made good use of its various capabilities.
Key Features We Built
Here are the main features we added to our MoodFlip app using Cline and OpenRouter:
- AI-Enhanced Free-Text Input: Users can now input any situation, and the app will generate an AI-powered positive flip. We integrated OpenRouter to manage multiple models, including free ones, to minimize costs.
- Emoji-Enriched Responses: We used Cline to make the generated responses more engaging by adding emojis and keeping them concise.
- Flip History with Pagination: Every flip is saved, and users can view previous flips with pagination. This was made possible by utilizing Svelte store and localStorage.
- Social Media Sharing: Users can share their positive flips directly to social media, such as Twitter, Facebook, and LinkedIn.
- Component Refactoring: To keep our codebase organized, we refactored the app into smaller components, making it easier to maintain and scale.
- Production Deployment: Once the changes were complete, we deployed the app to Netlify, which we had set up with GitHub for continuous integration and deployment.
Cline’s Real-World Use Cases
Throughout the process, we experienced both the strengths and limitations of Cline. It was incredibly helpful for repetitive tasks like adding components, setting up API integration, and creating share buttons. However, there were times when we had to step in manually, especially when handling large components or debugging tricky errors.
The great part about Cline was its integration with OpenRouter, which made switching between models simple. For certain tasks, like generating high-quality code, we used a paid model (Claude 3.5 Sonnet), but we also demonstrated how free models could be used to save money.
Pro Tips for AI Developers
- Choosing the Right AI Model: Using free models when possible can significantly reduce your costs. OpenRouter makes switching models easy.
- bolt.new vs. Cline: If you need quick prototyping, bolt.new is great. For more extensive projects with code management needs, Cline shines.
- Securing API Keys: Be careful with API keys—if they’re embedded in the client-side code, they can easily be exposed. We plan to address this in our next update by implementing a backend to securely manage these keys.
- Continuous Deployment: Setting up continuous deployment with tools like GitHub and Netlify ensures that every time you push a change, your production app is automatically updated.
Challenges Faced
No project is without challenges, and we ran into a few while enhancing the app. One recurring issue was the API cost when using certain models, as each change and debugging attempt added up. In the end, we found that breaking down large components and leveraging Cline for refactoring was key to reducing errors and keeping our app running smoothly.
What’s Next?
In the upcoming videos, we’ll explore another AI assistant called Aider as an alternative to Cline, particularly for scenarios where Cline falls short. We also plan to introduce a backend system to secure API keys and save flip history in a real database, providing a safer and more scalable solution.
If you’re interested in seeing these features in action, head over to the video tutorial: Watch Now. Whether you’re looking to learn more about AI development or improve your coding skills, we hope this guide and video help you on your journey.
Happy coding!
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Good blogs thanks