AI Agents
Build an intelligent chat agent using local language models
3 nodes
625
198
Automatic trigger
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Workflow Description
Automation that creates an interactive conversational agent powered by local language models like Ollama, enabling natural dialogue without relying on external servers while maintaining privacy and performance throughout interactions.
How it works
- 1.Receive user messages through the embedded chat interface
- 2.Process text using a local language model (Ollama) for understanding and analysis
- 3.Apply LLM chain processing to generate intelligent and coherent responses
Use cases
- Self-service customer support without external API call costs
- Internal applications requiring secure and private conversations
- Rapid prototyping of advanced dialogue systems
Requirements
- Install and run Ollama locally with a supported language model
- Enable local port connectivity to the Ollama server
- Sufficient configuration to tune the agent's behavioral responses
Service Value
Ideal as a smart automation service combining integrations and AI to produce ready-to-use results.
Apps Used
Chat Trigger
Lm Chat Ollama
LLM Chain
Details
Trigger
Automatic trigger
Nodes
3
Apps
3
Views
625
Downloads
198
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 (3)
When chat message received
Chat Trigger
Ollama Chat Model
Lm Chat Ollama
Sticky Note
Sticky Note
Sticky Note1
Sticky Note
Chat LLM Chain
LLM Chain
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