AI Agents
Build an AI Agent Responding to Messages with Memory
7 nodes
346
162
Automatic trigger
Workflow Description
An automation that creates an intelligent agent receiving messages through a chat interface, maintaining conversation context in memory, and using OpenAI models to respond intelligently with the ability to search and retrieve additional information when needed.
How it works
- 1.Receive incoming message from user via chat trigger
- 2.Store conversation context and previous messages in a rolling memory buffer
- 3.Route request to an AI agent powered by OpenAI language model
- 4.Execute search tools when needed to retrieve supplementary information
- 5.Send final response to user while preserving conversation context
Use cases
- Automated customer support that remembers conversation history and delivers personalized solutions
- Multi-purpose virtual assistant combining AI intelligence with real-time information retrieval
- Question-answering chatbot that learns from context and continuously improves responses
Requirements
- Valid OpenAI API key to power GPT language models
- Enabled chat trigger on target platform (website or application)
- Configured search tool with external data sources or APIs (optional)
- Minimum stored messages in memory buffer (3-10 previous messages)
Service Value
Ideal as a smart automation service combining integrations and AI to produce ready-to-use results.
Apps Used
Chat Trigger
Memory
AI Agent
Tool
OpenAI
Details
Trigger
Automatic trigger
Nodes
7
Apps
5
Views
346
Downloads
162
How to Use
- 1.Click "Download Template"
- 2.Open your n8n dashboard
- 3.Go to Workflows > Import from File
- 4.Select downloaded file and configure credentials
Nodes Used (7)
When chat message received
Chat Trigger
Simple Memory
Memory Buffer Window
AI Agent
Agent
Sticky Note
Sticky Note
Sticky Note1
Sticky Note
SearchApi
Search Api Tool
OpenAI Chat Model
OpenAI