Part 6/10:
Once the infrastructure is in place, it’s time for the exciting part: creating a fully functional Retrieval-Augmented Generation (RAG) AI agent. To access your self-hosted n8n, navigate to localhost:5678. This interface simplifies the creation of workflows that utilize the PostgreSQL chat memory, Quadrant for RAG, and Llama for language modeling.
The Workflow Breakdown
The workflow consists of two essential components:
The Chat Agent Interface: A built-in chat widget allows users to interact with their custom AI agent seamlessly.
Google Drive Integration: The workflow also includes triggers to ingest documents from Google Drive into your local knowledge base, enhancing your AI's learning capabilities.