Detect hallucinations using specialised Ollama model bespoke-minicheck
Ready for 3.0Ready for 3.0. This template uses no nodes that n8n 3.0 removes. No removed nodes, versions or helpers found. Static check, last run 2026-10-19.
What this workflow does
This AI workflow has 13 nodes and runs when another workflow calls it (plus 1 other trigger). Along the way it connects Ollama Chat Model and Ollama Model.
How it runs
Trigger: When another workflow calls it (plus 1 other trigger).
- Code: runs custom JavaScript code
- Merge: merges the data from its input branches
- Edit Fields (Edit Fields (Set)): sets 2 fields: facts, text
- Split Out: splits a list into separate items
- Merge: merges the data from its input branches
- Basic LLM Chain: sends a prompt to an LLM, with model: Ollama Chat Model
- Filter: keeps only the items that match a condition
- Aggregate: combines items into one
- Basic LLM Chain: sends a prompt to an LLM, with model: Ollama Model
Services it uses
Before you upgrade to n8n 3.0
Nothing in this workflow is removed in n8n 3.0, so it should import and run after the upgrade.
Nodes used (11)
- Code
n8n-nodes-base.code - Split Out
n8n-nodes-base.splitOut - Basic LLM Chain
@n8n/n8n-nodes-langchain.chainLlm - Ollama Chat Model
@n8n/n8n-nodes-langchain.lmChatOllama - Manual Trigger
n8n-nodes-base.manualTrigger - Edit Fields (Set)
n8n-nodes-base.set - Merge
n8n-nodes-base.merge - Filter
n8n-nodes-base.filter - Execute Workflow Trigger
n8n-nodes-base.executeWorkflowTrigger - Aggregate
n8n-nodes-base.aggregate - Ollama Model
@n8n/n8n-nodes-langchain.lmOllama
From the author
Fact-Checking Workflow Documentation Overview This workflow is designed for automated fact-checking of texts. It uses AI models to compare a given text with a list of facts and identify potential discrepancies or hallucinations. Components 1. Input - The…