⚡ Live Demo at :- https://edubud.vercel.app/

🚀 Getting Started

First, clone this repo and download it locally.

Next, you'll need to set up environment variables in your repo's .env.local file. Copy the .env.example file to .env.local. To start with the basic examples, you'll just need to add your OpenAI API key.

The retrieval capabilities the agent use Supabase as a vector store. However, you can swap in another supported vector store if preferred by changing the code under app/api/retrieval/ingest/route.ts, app/api/chat/retrieval/route.ts, and app/api/chat/retrieval_agents/route.ts.

For Supabase, follow these instructions to set up your database, then get your database URL and private key and paste them into .env.local.

To try out the agent capabilites to interact with real time internet, you'll need to give the agent access to the internet by populating the SERPAPI_API_KEY in .env.local. Head over to the SERP API website and get an API key if you don't already have one.

Next, install the required packages using your preferred package manager (e.g. yarn).

Now you're ready to run the development server:

yarn dev

Open http://localhost:3000 with your browser to see the result! Ask the bot something and you'll see a streamed response:

You can start editing the page by modifying app/page.tsx. The page auto-updates as you edit the file.

Backend logic lives in app/api/chat/route.ts. From here, you can change the prompt and model, or add other modules and logic.

▲ Deploy on Vercel

When ready, you can deploy your app on the Vercel Platform.

Check out the Next.js deployment documentation for more details.