In the video, the creator demonstrates how to build a full-stack benchmarking application for large language models using Pythagora, an AI-powered development tool, without writing any code. They showcase the iterative development process, highlighting features like user authentication, test management, and deployment, while emphasizing the collaborative nature of working with Pythagora to create a functional application.
In the video, the creator demonstrates how to build a full-stack benchmarking application for large language models (LLMs) using Pythagora, an AI-powered development tool. The application, named “Benchmark,” is designed to allow users to create tests for various LLMs, run those tests, and publish the results. The creator emphasizes that this is not a simple project but a valuable application that can be used in real-world scenarios. The video showcases the iterative process of building the app, highlighting the ease of use and efficiency of Pythagora in managing the development workflow.
The creator begins by setting up the project in Visual Studio Code, ensuring that the necessary frameworks and extensions are installed. After creating a new app, they provide a detailed description of the application’s functionality, which includes user authentication, an admin dashboard, and the ability to create and manage tests. Pythagora’s various agents, such as the spec writer and architect, assist in planning and executing the project, selecting appropriate technologies like Node.js and MongoDB for the backend.
As the development progresses, the creator interacts with Pythagora to input API keys and make necessary adjustments. The AI tool generates code for different components of the application, including user authentication and the admin dashboard. The creator tests each feature as it is implemented, verifying that everything works correctly. They appreciate the iterative nature of the process, where Pythagora prompts for human input when needed and provides debugging assistance.
Throughout the video, the creator showcases various functionalities being added to the application, such as test creation, execution, and result evaluation. They demonstrate how to populate the database with sample test data and implement features like pagination and access control. The creator also highlights the importance of providing detailed feedback to Pythagora, which helps the AI improve its responses and code generation. The collaborative nature of the development process is emphasized, with the creator and Pythagora working together to build a robust application.
In the final stages of development, the creator implements the ability to publish tests and update the homepage to display published results. After thorough testing and debugging, they successfully deploy the application, showcasing its functionality live on the web. The video concludes with the creator reflecting on the impressive outcome of building a complex application without writing any code, thanks to Pythagora’s capabilities. They encourage viewers to try the application and express gratitude for the partnership with Pythagora, inviting feedback and engagement from the audience.