Project developed on Rocketseat's NLW IA Mastery Track. Web Part - Project Front.
Project | Technologies | Usage | About the project | License
The project consists of a generator of descriptions and titles for YouTube
videos based on content transcription.
The project's front-end is available in this GitHub repository. The back-end is now available: here.
This template provides a minimal setup to get React working in Vite with
HMR and some ESLint rules.
This project was developed using technologies:
-
React
-
TypeScript
-
ESLint
-
Tailwind CSS
-
Axios
-
Vite
-
FFmpeg
-
Radix UI
-
PostCSS
-
To run the application on your machine locally, make sure you have
Node.js
andpnpm
installed before proceeding with the steps below:
- Clone the project:
$ git clone https://github.com/ludiemert/Nlw_IA_Web_Front
- Access the project folder:
$ cd Nlw_IA_Web_Front
- Install dependencies:
$ pnpm install
- Start the server:
$ npm run dev
-
At the Rocketseat NLW event, with a special edition focused on Artificial Intelligence (AI). A project was developed using the OpenAI API, which involves uploading a video for the API to transcribe into text. It generates coherent titles and descriptions based on the content of the uploaded video. For front-end development, React.js, Tailwind.css, Shadcn for stylized components and Web Assembly were used. Web Assembly is a technology that allows us to run things on the web that are not traditionally web-based, among other technologies. On the back-end, Node.js was used, along with Fastify to handle API requests and routes, and Prisma as the database ORM, among other technologies.
This project is under the MIT license. See the [LICENSE](LICENSE) file for more details.
- Rocketseat
🛠 Junior Web Developer | HTML | CSS | JavaScript | ReactJS | NodeJS | Full Stack
Developer Jr.
📍 São Jose dos Campos – SP - Brazil
- Thank you #Rocketseat team