AI Agents

Build an intelligent chat agent with local language models

5 nodes 298 133 Automatic trigger
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Workflow Description

An automation that creates a conversational agent powered by local language models, receiving user queries through a chat interface and processing them using Ollama, then returning intelligent responses while maintaining complete data privacy and offline operation.

How it works

  1. 1.Enable the chat trigger to receive incoming user messages
  2. 2.Process the message through the local Ollama language model
  3. 3.Chain multiple LLM calls to refine the response and deliver the result

Use cases

  • Create a customer support bot that operates independently without external API dependencies
  • Build an internal company assistant that keeps sensitive data on-premises

Requirements

  • Ollama installed on your server with a downloaded language model
  • n8n configured with direct connectivity to your Ollama instance

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 5
Apps 3
Views 298
Downloads 133

How to Use

  1. 1.Click "Download Template"
  2. 2.Open your n8n dashboard
  3. 3.Go to Workflows > Import from File
  4. 4.Select downloaded file and configure credentials

Nodes Used (5)

When chat message received

Chat Trigger

#1

Ollama Chat Model

Lm Chat Ollama

#2

Sticky Note

Sticky Note

#3

Sticky Note1

Sticky Note

#4

Chat LLM Chain

LLM Chain

#5