AI Agents
Build an intelligent agent that processes conversations with continuous memory
15 nodes
415
187
Automatic trigger
Workflow Description
An advanced template that creates a smart agent receiving chat messages, processing them using multiple language models (OpenAI and Ollama), while maintaining context through a sliding memory buffer to enhance response quality and coherence.
How it works
- 1.Receive user message via chat trigger interface
- 2.Process request using intelligent agent with language models
- 3.Store conversation context in memory buffer
- 4.Send processed response back to user
Use cases
- Create a sophisticated assistant that maintains conversation history and context
- Integrate multiple language models in one workflow for enhanced capabilities
Requirements
- OpenAI API credentials configured
- Ollama model endpoint setup or access
- Knowledge of LLM chain operations and memory management
Service Value
Ideal as a smart automation service combining integrations and AI to produce ready-to-use results.
Apps Used
Chat Trigger
AI Agent
OpenAI
Memory
LLM Chain
Lm Chat Ollama
Details
Trigger
Automatic trigger
Nodes
15
Apps
6
Views
415
Downloads
187
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 (15)
/
When chat message received
Chat Trigger
AI Agent
Agent
DeepSeek
OpenAI
Window Buffer Memory
Memory Buffer Window
Basic LLM Chain2
LLM Chain
Sticky Note
Sticky Note
Sticky Note1
Sticky Note
Ollama DeepSeek
Lm Chat Ollama
Sticky Note2
Sticky Note
Sticky Note3
Sticky Note
DeepSeek JSON Body
HTTP Request
DeepSeek Raw Body
HTTP Request
Sticky Note4
Sticky Note
Sticky Note5
Sticky Note
Sticky Note6
Sticky Note