Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/sadmann7/binge-gpt
https://github.com/sadmann7/binge-gpt
ai gpt-3 t3-stack
Last synced: about 1 month ago
JSON representation
- Host: GitHub
- URL: https://github.com/sadmann7/binge-gpt
- Owner: sadmann7
- Created: 2023-02-18T20:28:08.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2023-03-05T18:23:22.000Z (almost 2 years ago)
- Last Synced: 2024-10-06T02:41:51.099Z (3 months ago)
- Topics: ai, gpt-3, t3-stack
- Language: TypeScript
- Homepage: https://watchcopilot.vercel.app
- Size: 1010 KB
- Stars: 7
- Watchers: 2
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# [BingeGPT](https://bingegpt.vercel.app/)
This project recommends tv shows and movies with OpenAI. The show details are fetched from the TMDB api on click of any recommended show. It is bootstrapped with the [T3 Stack](https://create.t3.gg/).
[![BingeGPT](./public/screenshot.png)](https://bingegpt.vercel.app/)
## Tech Stack
- [Next.js](https://nextjs.org)
- [Prisma](https://prisma.io)
- [Tailwind CSS](https://tailwindcss.com)
- [tRPC](https://trpc.io)
- [OpenAI GPT-3 API](https://platform.openai.com/overview)
- [TMDB API](https://developers.themoviedb.org/3/getting-started/introduction)## Features
- Recommend tv shows and movies based on user inputed shows
- Fetch show details from TMDB api on click of any recommended show
- Add shows to the favorites list
- Category wise filtering of the favorites list## Installation
### 1. Clone the repository
```bash
git clone https://github.com/sadmann7/binge-gpt.git
```### 2. Install dependencies
```bash
yarn install
```### 3. Create a `.env` file
Create a `.env` file in the root directory and add the environment variables as shown in the `.env.example` file. You can get the OpenAI API key from [here](https://platform.openai.com/account/api-keys). You can get the TMDB API key from [here](https://developers.themoviedb.org/3/getting-started/introduction).
### 4. Run the application
```bash
yarn run dev
```The application will be available at `http://localhost:3000`.
## Deployment
Follow the deployment guides for [Vercel](https://create.t3.gg/en/deployment/vercel), [Netlify](https://create.t3.gg/en/deployment/netlify) and [Docker](https://create.t3.gg/en/deployment/docker) for more information.