n8n Research Chatbot Workflow: Gemini + Wikipedia + Sheets

Turn chat into structured research with n8n + Google Gemini

This n8n Research Chatbot Workflow: Gemini + Wikipedia + Sheets lets users ask questions in an n8n-powered chat, receive Gemini-powered answers with Wikipedia lookups (and arithmetic via a calculator), and automatically log each question with a topic label into Google Sheets. Perfect for research assistants, support knowledge discovery, and tracking what people actually ask.

What this workflow does

• Receives a user message through the workflow’s built-in chat webhook trigger.
• Sends the message to a Google Gemini agent that can consult Wikipedia for factual lookups and use a Calculator tool for arithmetic.
• Maintains conversational context using a buffer memory window, so follow-up questions stay coherent.
• Streams the agent’s response back to the chat in plain language.
• In parallel, uses Google Gemini to generate a short 1–3 word topic label for the question.
• Appends the original question + topic label to a Google Sheets tab (the “Questions” sheet) for tracking.

Use cases

• SaaS operators who want a lightweight internal “ask-the-facts” assistant for product research and FAQs.
• Automation engineers prototyping an n8n automation workflow that combines chat, LLM research, and data logging.
• Teams running knowledge hunts who need a visible audit trail of what questions were asked and how they were categorized.

Technical details

• n8n chat trigger: receives messages via the workflow’s public chat URL.
• Google Gemini (PaLM) API credentials: used both for the research agent and for topic-tagging.
• Wikipedia tool: enables factual lookups during the Gemini agent run.
• Calculator tool: supports arithmetic as part of answers.
• Google Sheets (OAuth2): logs the question and the generated 1–3 word topic label into the “Questions” sheet.

Set it up in minutes, share the chat URL, and start collecting structured research requests automatically.