RAG-чатбот с управлением базой знаний

★ 6.0 · n8n

This set of 4 n8n workflows implements a full-featured RAG chatbot with CRUD document management for its knowledge base. Use it when you want to deploy a chatbot that answers questions from your company's internal documents, when the knowledge base changes regularly and you need to add, update, or delete entries without restarting the system, or when you want a ready-made RAG pipeline without writing code. Workflow 01 receives a user question, retrieves relevant chunks from a vector store, and generates an answer; workflows 02, 03, and 04 handle document creation, updates, and deletion. The repo is framed around a grooming business but the RAG architecture is generic and reusable. Import all 4 JSON files into any n8n instance and configure a vector database (Pinecone, Qdrant, or equivalent) plus an LLM API key. Best for small businesses and teams building a chatbot on their own data. Not ideal for very large document corpora without tuning the chunking strategy.