Automated workflow
Workflow Description
An automated workflow that integrates an intelligent agent powered by a local language model to handle messages and inquiries. It maintains continuous conversation history through a buffer memory system, enabling coherent contextual interactions without relying on external cloud services.
How it works
- 1.Receive messages through the chat trigger endpoint
- 2.Process inquiries using the local Ollama language model
- 3.Execute intelligent agent actions based on detected context
- 4.Store conversation history in the buffer memory window
- 5.Return contextually relevant responses to the user
Use cases
- Build an offline-capable smart assistant for customer inquiry responses
- Automate handling of repetitive queries while maintaining conversation context
- Create a conversational agent that learns from prior interactions within a session
Requirements
- Ollama installed and running with a supported language model
- Chat trigger configured to connect with your communication channel
- Memory buffer window sized appropriately for conversation volume
Service Value
Ready-made workflow template for automation delivery and service execution.
Apps Used
Details
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 (16)
When chat message received
Chat Trigger
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Ollama Dynamic LLM
Lm Chat Ollama
LLM Router
Agent
AI Agent with Dynamic LLM
Agent
Ollama phi4
Lm Chat Ollama
Router Chat Memory
Memory Buffer Window
Agent Chat Memory
Memory Buffer Window
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