Automated Essay Mining and Retrieval with Milvus and AI

This Workflow automates the process of scraping, analyzing, and storing essays from Paul Graham’s website, then allowing efficient AI-based querying. Starting with a manual trigger, it fetches a list of essays from the designated URL, extracts essay links, and limits to the first three for processing. It then retrieves the full text of each selected essay, cleans and splits the content into manageable chunks, and loads the data into a Milvus vector store. Using OpenAI’s embedding models, the system creates vector representations of the essays for fast similarity searches. When a question is received through a webhook trigger, the system retrieves relevant chunks from Milvus, processes them, and generates a helpful AI-based answer with citations, making it ideal for research automation, content analysis, or building intelligent information retrieval systems.