Process Documents & Build Semantic Search with OpenAI, Gemini & Qdrant

This n8n workflow streamlines document processing by pulling files from Google Drive folders or web form uploads, converting them as needed, and batching them to avoid memory overload. It leverages Google Gemini for intelligent metadata extraction and context understanding, then generates high-quality vector embeddings via OpenAI for semantic search. Vectors are stored in Qdrant, enabling fast similarity searches across indexed content.

Key benefits include reliable error handling, execution tracking, and configurable options like automatic file deletion from Drive post-processing. The built-in interactive chatbot allows real-time testing of queries against the knowledge base, making it ideal for rapid deployment.

Use cases span knowledge base creation for organizations, compliance document indexing (e.g., Fair Work policies), content management systems, research libraries, and customer support bots that provide instant answers from documentation.