Build an Automated RAG Pipeline for Dynamic Document QueryingBuild an Automated RAG Pipeline for Dynamic Document Querying
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A completely automated Retrieval-Augmented Generation (RAG) pipeline designed for dynamic document querying. This workflow monitors a Google Drive folder for new documents, instantly downloads them, chunks the text, and generates OpenAI embeddings to store in a Pinecone vector database. Users can then query an AI agent to instantly fetch highly accurate information based strictly on the uploaded documents.
Tech Stack: n8n, LangChain, OpenAI, Pinecone, Google Drive.
Impact: Turns static document repositories into an interactive, conversational search engine with zero manual maintenance.
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Creatives on Contra have earned over $150M and we are just getting started