Ygrep: Fast, local, indexed code search tool optimized for AI coding assistants (github.com)

Ygrep has launched as a new, fast, local code search tool designed specifically for AI coding assistants. Built in Rust and utilizing the Tantivy library for full-text indexing, it supports advanced search capabilities, including literal text matching and regular expressions. Its features include a code-aware tokenizer that preserves relevant symbols, instant results through BM25 ranking, and optional semantic search using a local model, enhancing query responses for natural language queries. With file watching capabilities for incremental updates, Ygrep is set to streamline the coding process for developers. The significance of Ygrep lies in its optimization for AI coding environments, making it easier for developers to integrate code searches into their workflows. By supporting popular AI coding assistants like Claude Code, OpenCode, and Codex, Ygrep facilitates more effective interaction between human developers and AI, ultimately aiming to improve productivity in software development. Its hybrid search mode, combining text and semantic searches, offers scalability and enhanced performance for programming tasks, and its user-friendly command-line interface ensures that developers can quickly adapt and utilize its advanced functionalities.