🤖 Build a Documentation Expert Chatbot with Gemini RAG Pipeline

How it works This template is a complete, hands-on tutorial for building a RAG (Retrieval-Augmented Generation) pipeline. In simple terms, you'll teach an AI to become an expert on a specific topic—in this case, the official n8n documentation—and then build a chatbot to ask it questions. Think of it like this: instead of a general-knowledge AI, you're building an expert librarian. The workflow is split into two main parts: Part 1: Indexing the Knowledge (Building the Library) This is a one-time process you run manually. The workflow automatically scrapes all pages of the n8n documentation, breaks them down into small, digestible chunks, and uses an AI model to create a special numerical repr

Help me set up the n8n workflow "🤖 Build a Documentation Expert Chatbot with Gemini RAG Pipeline" (https://n8n.io/workflows/6137). It uses: HTTP Request, HTML, AI Agent, Simple Memory, Recursive Character Text Splitter, Simple Vector Store, Default Data Loader, Embeddings Google Gemini, Google Gemini Chat Model. Import the template JSON into my n8n instance, list every credential I need to create, and walk me through testing it.