pathwaycom/llm-app
Ready-to-run cloud templates for building real-time RAG, AI pipelines, and enterprise search applications that synchronize with various live data sources.
Awesome Infra for AI › Vector Databases & Retrieval Infrastructure
yoanbernabeu/grepai
grepai is a command-line interface tool designed for semantic code search, allowing users to query codebases by intent rather than exact text or regular expressions. It leverages vector embeddings to understand the meaning of code, facilitating the discovery of conceptually related code snippets even when naming conventions differ. A key feature of grepai is its 100% local operation, ensuring that code never leaves the user's machine, which strongly supports privacy. The tool includes a file watcher that automatically keeps its index up-to-date. One of its primary benefits highlighted is its ability to drastically reduce AI agent input tokens by providing highly relevant context. It is designed to be "AI agent ready," with out-of-the-box compatibility with tools like Claude Code, Cursor, and Windsurf. Furthermore, grepai can function as an MCP (Multi-Modal Communicating Processes) server, allowing AI agents to call it directly as a tool for code analysis. Beyond semantic search, it offers functionality to trace call graphs, helping developers understand function dependencies. The project emphasizes that traditional `grep` tools, built for exact text matching, are insufficient for modern codebases, while `grepai` provides a semantic understanding necessary for current development practices.
https://github.com/yoanbernabeu/grepai
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