Translate Form Submissions Using RAG and Supabase

Overview

This n8n workflow automates the process of translating and storing form submissions. It acts as a powerful tool for managing multilingual form data by integrating AI capabilities with a robust data storage solution. The workflow begins with a Webhook Trigger to receive incoming form data. This data is then processed by a Text Splitter and converted into embeddings using Embeddings (OpenAI). These embeddings are stored in Supabase using the Supabase Insert node, creating a searchable vector database. A Supabase Query node retrieves relevant information from this database, which is then utilized by the RAG Agent (Retrieval-Augmented Generation) in conjunction with Chat Model and Window Memory. This enables the agent to provide contextually aware translations or responses based on the stored form submissions. The Append Sheet node logs the workflow's execution status, and a Slack Alert is configured to notify users of any errors encountered during the process.