Automated Data Handling with Supabase and AI Integration

This n8n workflow streamlines data management and AI-driven interactions using Supabase, Google Gemini 2.0, and language models. Triggered manually for testing, it begins with setting sample input variables such as ‘session_id,’ ‘name,’ and ‘chatInput.’ The workflow then feeds the chat input into the Gemini AI model, configured to act as a helpful assistant. The AI’s output is stored in a dedicated Postgres database session, enabling context-aware conversations. If specific data, like ‘name,’ doesn’t exist in the database, the workflow updates the database with the current input values. The process is useful for automating chatbot interactions, maintaining conversation context, and storing user data efficiently. This setup is ideal for developing intelligent customer support bots, dynamic content generation, or personalized user experiences within WordPress or other platforms.