Automated Daily Student Motivation with RAG and Weaviate

Overview

This n8n workflow is designed to automate the delivery of daily motivational messages to students. It employs a RAG (Retrieval Augmented Generation) agent that integrates with Weaviate, a vector database, to provide contextually relevant information. The workflow starts with a Webhook Trigger, which can be used to initiate the process. The incoming data is then processed using a Text Splitter and Embeddings (OpenAI) to prepare it for storage in Weaviate. The Weaviate Insert node stores these embeddings, allowing for efficient retrieval later. A Weaviate Query node retrieves relevant information based on a query, which is then used by the Vector Tool. This tool, along with Window Memory and a Chat Model (OpenAI), powers the RAG Agent. The RAG Agent processes the retrieved context and user input to generate a motivational message. Finally, the output is logged to a Google Sheet using the Append Sheet node, and a Slack Alert is configured for error handling. This workflow automates the generation and logging of motivational content, saving time and ensuring consistent engagement.