An open source AI search engine. Powered by Together.ai.

• Next.js app router with Tailwind
• Together AI for LLM inference
• Mixtral 8x7B & Llama-3 for the LLMs
• Bing for the search API
• Helicone for observability
• Plausible for website analytics

1. Take in a user's question
2. Make a request to the bing search API to look up the top 6 results and show them
3. Scrape text from the 6 links bing sent back and store it as context
4. Make a request to Mixtral-8x7B with the user's question + context & stream it back to the user
5. Make another request to Llama-3-8B to come up with 3 related questions the user can follow up with

1. Fork or clone the repo
2. Create an account at Together AI
3. Create an account with Azure to get a Bing search API key
4. Create an account at Helicone
5. Create a .env (use the .example.env for reference) and replace the API keys
6. Run npm install and npm run dev to install dependencies and run locally

• Try to parse the sources in a more effecient way to make the app faster overall: Try Serper API
• Have the AI tool ignore video links like Youtube cause can't scrape them fast
• Make sure the answer correctly cites all the sources in the text & number the citations in the UI
• Add sharability to allow folks to share answers
• Automatically scroll when an answer is happening, especially for mobile
• Fix hard refresh in the header and footer by migrating answers to a new page
• Add upstash redis for caching results & rate limiting users
• Add in more advanced RAG techniques like keyword search & question rephrasing
• Add authentication with Clerk if it gets popular along with postgres/prisma to save user sessions

• Perplexity
• You.com
• Lepton search