Build an intelligent agent with memory and conversation

How it works

1. 1.Receive user messages through the chat trigger and capture intent
2. 2.Load previous context from the memory module to ensure conversation continuity
3. 3.Process the request via a local language model and generate appropriate responses
4. 4.Store the new exchange in memory for future reference
5. 5.Send the reply to the user while preserving full context

Use cases

• Build a context-aware assistant that answers sequential questions and maintains topic threads
• Create an automated customer support system that retains chat history and handles personalized inquiries
• Develop a consulting agent that learns from user interactions to provide increasingly relevant guidance

Requirements

• Set up a local or accessible Ollama model deployment
• Run n8n with extensions enabling agent and memory features

Service Value

Ready-made workflow template for automation delivery and service execution.