AI Chatbot with Knowledge Base and Web Integration

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This workflow creates an intelligent AI chatbot that interacts via Google Sheets, leveraging advanced language models, a vector database, and web search capabilities for providing informed responses. The system is designed to process user messages, maintain context, retrieve relevant knowledge, and generate accurate replies.

Starting with a Google Sheets trigger, the workflow detects new user messages. It then checks if the message has already been responded to, preventing duplicates. The system extracts the message and retrieves the chat history to ensure conversation continuity.

The core component is an AI agent powered by OpenAI’s GPT-4, integrated with LangChain, which processes the formatted conversation, including recent context and the current user message. The agent utilizes a vector store, built with Supabase, to perform semantic searches for relevant documents in the knowledge base and can perform real-time web searches via SerpAPI when additional information is needed.

The retrieved context and web search results are fed into the AI for generating a well-informed response. The reply is stored back into Google Sheets, completing the interaction cycle. Additional nodes handle the generation of unique IDs, updating responses, and maintaining memory buffers for conversation context.

This workflow is practical for customer support, FAQ automation, or any scenario requiring dynamic, informed AI interactions with ongoing context and external data sources.

Node Count

11 – 20 Nodes

Nodes Used

@n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.embeddingsOpenAi, @n8n/n8n-nodes-langchain.lmChatOpenAi, @n8n/n8n-nodes-langchain.memoryBufferWindow, @n8n/n8n-nodes-langchain.toolSerpApi, @n8n/n8n-nodes-langchain.toolVectorStore, @n8n/n8n-nodes-langchain.vectorStoreSupabase, function, googleSheets, googleSheetsTrigger, if, merge, set, stickyNote

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