The SBrowserV2 search engine is built on an asynchronous architecture using FastAPI and Manticore Search. The system is containerized with Docker and includes an asynchronous gateway, a search layer, an AI booster for external queries, and a background crawler for indexing.
The ranking core utilizes the 'Theory of Connections' concept, which adjusts search results based on user click behavior. This approach creates a dynamic graph that prioritizes relevant links over SEO-optimized content.
The infrastructure is hosted on a VPS with 1 CPU and 2 GB of RAM. The system consumes 375 MB of RAM during runtime, while repeat search queries are processed in 0.433 milliseconds.
Development challenges included resolving SSL handshake issues with external gateways, which required updating system certificates within the Docker environment.
