The video demonstrates a FastAPI web application for knowledge distillation, allowing users to input a topic and generate sentences related to it using GPT-4o. Users can interact with the generated content, including expanding, deleting, and saving sentences as articles or markdown files, creating an interactive and educational experience for exploring various topics such as gravitational waves or object-oriented programming in Python.
In the video, a FastAPI web application for knowledge distillation is demonstrated. Users can input a topic like “gravitational waves” and select the number of sentences they want generated, defaulting to three. By clicking on “generate sentences,” GPT-4o is queried to generate sentences related to the topic. Users can expand on or delete sentences as desired, enabling exploration of various topics such as object-oriented programming in Python. The application allows users to delve deeper into specific sentences and generate articles or markdown files based on the content.
The user interface of the web app features elements like an input box for topics, a selection for the number of sentences, buttons to generate sentences, article, and markdown, as well as a spinner for processing indication. JavaScript functions handle interactions with the backend, making fetch calls to endpoints in the FastAPI app to generate, expand, and manipulate sentences. The frontend displays the generated content and allows users to interact with it by expanding, deleting, or saving the sentences as articles or markdown files.
The FastAPI application serves the index.html file to users, and various endpoints are defined for generating sentences, expanding on sentences, creating articles, and generating markdown files. The backend logic involves receiving user input, passing it to GPT-4o for sentence generation or expansion, and returning the results in JSON format. The JavaScript in the frontend processes the responses from the backend and dynamically updates the UI to show the generated sentences, articles, or markdown content.
The application structure includes a static folder for scripts and CSS files, a template folder for HTML files, and the FastAPI app itself. The script streamlines the communication between the frontend and backend, with functions to handle different user actions like generating sentences, expanding on them, creating articles, or generating markdown files. The backend logic ensures that the generated content is accurate and relevant to the user’s input, providing a seamless experience for exploring and learning about various topics.
Overall, the FastAPI web application for knowledge distillation showcases a user-friendly interface for exploring and expanding on topics of interest. By leveraging GPT-4o for sentence generation and expansion, users can delve deeper into subjects like gravitational waves or object-oriented programming in Python. The application architecture, combining frontend JavaScript interactions with backend FastAPI endpoints, enables seamless content generation, expansion, and saving capabilities, providing an interactive and educational experience for users.