From Code to Cocktails: Crafting a Full-Stack Benchmarking Delight with Pythagora – The AI That Writes So You Don’t Have To!
Welcome to the strange but wonderful world of using artificial intelligence to build a full-stack Benchmarking Application using Pythagora. This is not just any run-of-the-mill application; we are about to construct a theoretical beast that will benchmark various Large Language Models (LLMs). Why, you ask? Because testing AI should be as fun as watching paint dry, but way more rewarding!
What is Pythagora?
Pythagora is like having a team of developers in your pocket—all you have to do is ask! In this digital fairy tale, we are not just slapping together a simple to-do list application. No! We are forging a cutting-edge application that you’ll actually want to use!
Understanding the Project
Imagine being able to input a variety of test questions for LLMs and automatically evaluate their performance! That’s what our Benchmarking Application will do. We will build a system where:
- Users can create tests for LLMs.
- The results can be published for the world to see.
- Everything runs smoother than a well-oiled machine from a science fiction movie.
The Building Blocks
Before setting off on this coding adventure, ensure you have Node.js and MongoDB installed. With Pythagora, you can create new applications in a fraction of the time it takes to brew a cup of coffee. You’ll create an application called “Benchmark” and write a prompt so detailed that it could be a novella!
Here’s a taste of what my application will include:
- A homepage that invites users like a warm hug on a cold day
- User authentication for rigorous security
- An admin dashboard, because who doesn’t love dashboards?
- A test creation page that makes inputting data as easy as pie
Interaction Cycle with Pythagora
The Pythagorean trio of agents works tirelessly:
- Spec Writer: Evaluates the complexity of your project.
- Architect Agent: Plans the project like an architect with a blue print for the next skyscraper!
- Code Monkey: A delightful little helper that writes and rewrites your code as if its evolution depended on it (which, in a way, it does).
The best part? When you need to input something, Pythagora highlights what’s required, as if it were saying, “Hey, human! Over here!”
Face to Face with Code
Every developer knows the sweet rush of seeing code write itself. Once you start deploying one command after another, it feels like a well-choreographed dance. From creating an admin user to crafting a listing of tests for our LLMs, every function populates your MongoDB faster than you can hit ‘refresh’. The process is so organized that I half expect it to serve me a cocktail at any moment!
A Final Twist of the Code
As we steered our ship through the tumultuous waters of testing and debugging, it truly turned into a collaborative effort between human intuition and AI prowess. Each npm run command performed isn’t just a command; it’s the heartbeat of the Benchmark application pulsing with promise and potential.
Conclusion
We’ve managed, with the help of our AI assistant Pythagora, to build a fully functional benchmarking tool to evaluate LLMs—all without lifting a finger to write actual code ourselves. That’s right, folks, I crafted over 1,600 lines of code that I can now take out for dinner!
So here is my challenge to you—embark on this journey yourself, and don’t forget: let the AI handle the dirty work while you focus on the big picture. If Pythagora was good enough to get us here, imagine what it could do next! And remember, every great project starts with a single line of code… or perhaps a strong coffee!
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