AI-powered knowledge assistant using Google Sheets, OpenAI, and Supabase Vector Search

Name: AI-powered knowledge assistant using Google Sheets, OpenAI, and Supabase Vector Search
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Rating: 4.5 (52 reviews)
Author: Alex Huy

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Description An intelligent conversational AI system that provides contextual responses by combining chat history, vector database knowledge retrieval, and web search capabilities. How it Works (High-level steps)

Message Detection: Google Sheets trigger monitors for new user messages and filters out already-processed entries Context Preparation: Extracts user message, retrieves chat history, and formats conversation context with system prompt Knowledge Retrieval: AI agent searches vector database for relevant context using Supabase + OpenAI embeddings Response Generation: LangChain agent processes the request using:

OpenAI GPT-4 language model Vector store tool for knowledge base queries SerpAPI tool for web search when needed Buffer memory for conversation continuity

Response Storage: Updates Google Sheets with AI response and assigns unique timestamp ID

Setup Steps

Configure Google Sheets with columns: user_message, ai_respond, id Set up Supabase vector store with OpenAI embeddings Connect OpenAI API credentials (GPT-4 + embeddings) Configure SerpAPI for web search functionality Set up Google Sheets trigger and update permissions

Alex Huy

0 workflows

Nodes

set gmail telegram agent google-gemini

Complexity

advanced

Published 29 May 2025

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