Perplexed

Open-source app inspired by the amazing web search product, Perplexity.

Live Demo

Implementation

Given a user query, the app conducts a web search, downloads the top N resulting web pages, then analyzes those pages with an LLM.
The LLM can be any smaller, consumer-grade with at least 5k context window (assuming each web page ~1k tokens)

Deployment Instructions

Python Server

1. cd backend
   copy config.json.sample config.json
   

2. In config.json, fill in GOOGLE_SEARCH_API_KEY and GOOGLE_SEARCH_ENGINE_ID credentials from Google Custom Search API.
3. Fill in GROQ_API_KEY credentials from Groq.
4. Setup virtual environment, packages, and deploy the server

   virtualenv venv
   . venv/bin/activate
   pip install -r requirements.txt
   python app.py
   

   In the future, only need to do:

   . venv/bin/activate
   python app.py
   

React Frontend

1. Update API_URL in constants.js to point to your server

2. npm install
   

3. In dev, to start the server:

   npm run start
   

   In production, to start the server:

   npm i -g npm@latest
   rm -rf node_modules
   rm -rf package-lock.json
   npm cache clean --force
   npm i --no-optional --omit=optional
   npm run build
   npm install -g serve
   server -s build