This does not align with their vision.

Creating a simple generative search engine is straightforward and can be accomplished over a weekend.

Essential components include: - A search engine API (such as Bing or Google's) - Integration of search engine results with a Large Language Model (LLM)

This framework, known as Retrieval-Augmented Generation (RAG), was the foundation for the initial version of Perplexity.

The challenging aspect lies in refining the generation outcomes, which involves more proprietary techniques.

Currently, we display terms on Notion pages, which may not be viewable in your browser. We plan to transfer this content to our website shortly.

You can view the terms here: https://indexlabs.notion.site/Term-of-Service-6ca77cbc49504c...

frontend: next.js + react + vercel

backend: go/rust/python + gin + mysql + pinecone + es + redis + aws

llm: openai/azure + aws gpu + aws bedrock

Hi, Devv founder here.

Thank you for your valuable feedback; it's an excellent suggestion! In fact, we've already begun implementing this feature with our initial step being the introduction of GitHub Mode. This new functionality will enable seamless integration with your personal GitHub repositories. We've developed a bespoke indexer tailored to various programming languages to enhance this experience.

Furthermore, we can expand this capability to include documentation and other resources as well. The architecture is designed to be extensible, so all that's needed is the creation of additional indexers to support these materials.