This comprehensive n8n workflow automates the entire process of managing and interacting with documents stored in Google Drive. It begins by monitoring a specified Google Drive folder for new files such as PDFs, CSVs, or Google Docs, automatically downloading and extracting their text content. The workflow employs AI models like Google Gemini to generate metadata titles and descriptions, and splits the documents into manageable chunks using intelligent algorithms. These chunks are then embedded into vector representations via OpenAI’s API and stored in a Supabase vector database for semantic search. The stored data enables advanced AI-powered chat interactions, where users can ask questions about their documents, and the system intelligently retrieves relevant information from the database to provide accurate and source-cited responses. This workflow is highly useful for organizations looking to create searchable document repositories and interactive AI assistants for internal knowledge management.
Automated Document Processing & AI Search Workflow
Node Count | >20 Nodes |
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Nodes Used | @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.chainLlm, @n8n/n8n-nodes-langchain.chatTrigger, @n8n/n8n-nodes-langchain.documentDefaultDataLoader, @n8n/n8n-nodes-langchain.embeddingsOpenAi, @n8n/n8n-nodes-langchain.lmChatGoogleGemini, @n8n/n8n-nodes-langchain.lmChatOpenAi, @n8n/n8n-nodes-langchain.memoryBufferWindow, @n8n/n8n-nodes-langchain.outputParserStructured, @n8n/n8n-nodes-langchain.textSplitterCharacterTextSplitter, @n8n/n8n-nodes-langchain.vectorStoreSupabase, code, extractFromFile, googleDrive, googleDriveTrigger, limit, set, splitInBatches, splitOut, stickyNote, summarize, switch |
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