This n8n workflow automates the process of managing, analyzing, and utilizing documents within a Chat AI environment. It integrates Google Drive to monitor new or updated files in a specific folder, downloads and extracts content from different file types (PDF, Excel, Google Docs), and then stores this information in a vector database for retrieval. The workflow features a chat interface that allows users to ask questions, which are answered using retrieved relevant documents via a LangChain-powered AI agent, leveraging LLama models and Ollama embeddings for context-aware responses. Practical use cases include automated document ingestion, chat-based support systems, and knowledge base updates, making it ideal for teams managing large document repositories and seeking to enable AI-driven Q&A functionalities.

Node Count

>20 Nodes

Nodes Used

@n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.chatTrigger, @n8n/n8n-nodes-langchain.documentDefaultDataLoader, @n8n/n8n-nodes-langchain.embeddingsOllama, @n8n/n8n-nodes-langchain.lmChatOllama, @n8n/n8n-nodes-langchain.lmOllama, @n8n/n8n-nodes-langchain.memoryPostgresChat, @n8n/n8n-nodes-langchain.textSplitterCharacterTextSplitter, @n8n/n8n-nodes-langchain.toolVectorStore, @n8n/n8n-nodes-langchain.vectorStoreSupabase, aggregate, extractFromFile, googleDrive, googleDriveTrigger, respondToWebhook, set, stickyNote, summarize, supabase, switch, webhook