AI Agents
Extract personal data using self-hosted language models
13 nodes
297
173
Automatic trigger
Workflow Description
An automation that receives text inputs through a chat interface, processes them with a self-hosted language model (Ollama) to extract personal data automatically, then analyzes and formats results in a structured, reliable format.
How it works
- 1.Receive text input via chat trigger
- 2.Send text to self-hosted Ollama language model for processing
- 3.Analyze outputs and automatically correct extraction errors
- 4.Format extracted data into predefined structured format
Use cases
- Extract contact information from unstructured messages
- Process manually filled forms to retrieve personal details
- Handle sensitive data locally without external server dependencies
Requirements
- Ollama installed and running on your server
- Appropriate language model loaded in Ollama
- Embedded chat interface in n8n
- Clear definition of data format to extract
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
Output Parser
LLM Chain
Details
Trigger
Automatic trigger
Nodes
13
Apps
4
Views
297
Downloads
173
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 (13)
/
When chat message received
Chat Trigger
Ollama Chat Model
Lm Chat Ollama
Auto-fixing Output Parser
Output Parser Autofixing
Structured Output Parser
Output Parser Structured
Basic LLM Chain
LLM Chain
On Error
No Op
Sticky Note
Sticky Note
Sticky Note1
Sticky Note
Sticky Note2
Sticky Note
Extract JSON Output
Set
Sticky Note3
Sticky Note
Sticky Note6
Sticky Note
Sticky Note7
Sticky Note