Generate and audit original revenge stories with OpenAI
Ready for 3.0What this workflow does
This AI workflow has 38 nodes and runs manually, when you click “Execute workflow”. Along the way it connects OpenAI Chat Model.
How it runs
Trigger: Manually, when you click “Execute workflow”.
- Set Story Configuration (Edit Fields (Set)): sets or maps fields
- Set Inspiration Source (Edit Fields (Set)): sets or maps fields
- Extract Narrative Elements (Information Extractor): extracts structured fields from text with AI, with model: AI Model - OpenClaw
- Generate Story Premise (Basic LLM Chain): sends a prompt to an LLM, with model: AI Model - OpenClaw
- Format Approved Premise (Code): runs custom JavaScript code
- Audit Premise Integrity (Basic LLM Chain): sends a prompt to an LLM, with model: AI Model - OpenClaw; output parser: Parse Structured Output
- Check Premise Integrity (If): checks a condition and branches into true / false
- Build Story Input (Code): runs custom JavaScript code
- Organize Rebuild Input (Code): runs custom JavaScript code
- Craft Original Story (Basic LLM Chain): sends a prompt to an LLM, with model: AI Model - OpenClaw
…plus 18 more steps. See the full node list below.
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 (8)
- Manual Trigger
n8n-nodes-base.manualTrigger - Edit Fields (Set)
n8n-nodes-base.set - Information Extractor
@n8n/n8n-nodes-langchain.informationExtractor - Basic LLM Chain
@n8n/n8n-nodes-langchain.chainLlm - Structured Output Parser
@n8n/n8n-nodes-langchain.outputParserStructured - If
n8n-nodes-base.if - Code
n8n-nodes-base.code - OpenAI Chat Model
@n8n/n8n-nodes-langchain.lmChatOpenAi
From the author
Quick overview This workflow uses OpenAI in n8n to turn a short inspiration text into an original first-person story, generating a new premise from abstract “story DNA” and enforcing originality, structural integrity, and quality through automated audits,…