AI Agents
Extract personal data using self-hosted language model
13 nodes
283
144
Automatic trigger
Workflow Description
Workflow that receives chat messages, processes them through a self-hosted Ollama language model, and automatically extracts personal data in structured format with built-in error correction to ensure data consistency.
How it works
- 1.Receive message input from chat trigger
- 2.Process text through local Ollama model
- 3.Parse and auto-correct output structure
- 4.Extract and format personal data fields
Use cases
- Automatically convert form submissions into structured customer data
- Parse unstructured text messages to extract contact and profile information
Requirements
- Ollama language model installed and running locally
- Access to chat interface for receiving and processing messages
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
283
Downloads
144
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)
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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