PDF Search

Built for Zed to enable semantic searching of PDF documents using a Qdrant vector database and OpenAI embeddings.

This PDF Search extension for Zed, developed by stano, enables semantic searching of PDF documents and integrates results with Zed's AI Assistant. It uses a Qdrant vector database for storing document embeddings and OpenAI's API for generating them. The extension implements a RAG-style approach, allowing users to query PDF content through Zed's interface. Built with Rust and Python, it offers a unique combination of Zed integration and semantic PDF search capabilities. This tool is particularly useful for researchers, students, or professionals who frequently work with PDF documents and need quick, context-aware access to their contents within their coding environment.