EmbeddingGemma 2: an open, lightweight multimodal embedding model
deepmind.google·6d ago
AI Engineering
Hacker News·Aug 3·5 min read
SearXNG in Rust
TL;DR
A new metadata search engine inspired by SearXNG has been developed in Rust, enabling concurrent queries to multiple search engines. It effectively deduplicates results and ranks them using Reciprocal Rank Fusion.
✦ Why It Matters
Consider contributing to or using this Rust-based search engine for enhanced metadata retrieval in your projects.
Key Takeaways
- Use reqwest for concurrent HTTP requests to search engines.
- Implement Reciprocal Rank Fusion for better result ranking.
- Deduplicate results by normalizing URLs before scoring.
- Run unit and live tests to ensure search engine reliability.
How It Works
The search engine sends a query to multiple search engines simultaneously, retrieves HTML results, and parses them using CSS selectors. It deduplicates results by normalizing URLs, which involves removing unnecessary parameters.
The RRF scoring system boosts the rank of results that appear across multiple engines, ensuring that the most relevant pages are prioritized.