AI-Powered PDF Q&A Chat with Pinecone & OpenAI

This n8n workflow automates intelligent Q&A on PDF documents using Retrieval-Augmented Generation (RAG). It starts by fetching a PDF (e.g., Bitcoin whitepaper) from Google Drive, splitting it into chunks, generating embeddings, and indexing them in Pinecone. Once loaded, a manual chat trigger accepts user queries, embeds them, retrieves the most relevant document chunks from Pinecone, and feeds them to OpenAI for context-aware, accurate responses.

Key benefits include semantic search beyond keyword matching, reducing hallucinations in AI answers, and easy scalability for any PDF-based knowledge base. It's ideal for research, internal docs, customer support, or legal reviews where quick, precise answers from large files are needed.

To use: Create a 1536-dimension Pinecone index, execute 'Test Workflow' to index data, then 'Chat' for queries. Requires n8n 1.19.4+. High time-saving for AI document analysis without custom coding.