https://github.com/engageintellect/gsa-rag-frontend

GSA Rag application frontend code
https://github.com/engageintellect/gsa-rag-frontend

daisyui next13 nextjs tailwindcss

Last synced: about 1 month ago
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GSA Rag application frontend code

• Host: GitHub
• URL: https://github.com/engageintellect/gsa-rag-frontend
• Owner: engageintellect
• Created: 2024-02-04T09:33:19.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2024-02-20T23:36:36.000Z (over 2 years ago)
• Last Synced: 2025-09-12T00:43:37.641Z (9 months ago)
• Topics: daisyui, next13, nextjs, tailwindcss
• Language: TypeScript
• Homepage: https://resonant-logic-search.vercel.app
• Size: 11.4 MB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

          
# Langchain, Pinecone, and GPT with Next.js

## Technologies Used

- Next.js

- LangchainJS

- Pineceone Vector Database

- GPT3

## Getting Started

### Prerequisites

To run this app, you need the following:

1. An [OpenAI](https://platform.openai.com/) API key

2. [Pinecone](https://app.pinecone.io/) API Key

### Up and running

To run the app locally, follow these steps:

1. Clone this repo

```sh

git clone https://github.com/engageintellect/pinecone-gpt.git

```

2. Change into the directory and install the dependencies using either NPM, PNPM or Yarn

3. Copy `.example.env.local` to a new file called `.env.local` and update with your API keys and environment.

   **Be sure your environment is an actual environment given to you by Pinecone, like `us-west4-gcp-free`**

4. (Optional) - Add your own custom text or markdown files into the `/documents` folder.

5. Run the app:

```sh

pnpm run dev

```

# resonant-logic-search