Generate & optimize brand stories with Ollama LLMs and Google Sheets
Needs changesWhat this workflow does
This AI workflow has 9 nodes and runs when a chat message arrives. Along the way it connects Ollama Chat Model and Google Sheets.
How it runs
Trigger: When a chat message arrives.
- Brand Storytelling Agent (AI Agent): runs an AI agent, with model: Ollama Chat Model
- Set Brand variable (Edit Fields (Set)): sets or maps fields
- Evaluator Agent (AI Agent): runs an AI agent, with model: Ollama Chat Model
- Evaluation Check (If): checks a condition and branches into true / false
- Save Brand Story to Sheets (Google Sheets): uses Google Sheets
- Optimizer Agent (AI Agent): runs an AI agent, with model: Ollama Chat Model
Services it uses
Before you upgrade to n8n 3.0
1 thing in this workflow is removed in n8n 3.0. Fix it before you upgrade:
- AI Agent v1 (old agent modes) in Evaluator Agent (v1.7), Optimizer Agent (v1.7), Brand Storytelling Agent (v1.7): replace with Latest AI Agent node (Tools Agent). For SQL Agent, use a Postgres or MySQL tool with a recent AI Agent.
Rather not rewrite it? Many of these flows can be rebuilt in Make (free plan).
| Removed in 3.0 | Replace with |
|---|---|
| AI Agent v1 (old agent modes) Evaluator Agent (v1.7), Optimizer Agent (v1.7), Brand Storytelling Agent (v1.7) | Latest AI Agent node (Tools Agent). For SQL Agent, use a Postgres or MySQL tool with a recent AI Agent. |
Nodes used (6)
- AI Agent
@n8n/n8n-nodes-langchain.agent - Ollama Chat Model
@n8n/n8n-nodes-langchain.lmChatOllama - Chat Trigger
@n8n/n8n-nodes-langchain.chatTrigger - Edit Fields (Set)
n8n-nodes-base.set - Google Sheets
n8n-nodes-base.googleSheets - If
n8n-nodes-base.if
From the author
Overview This n8n automation template allows marketers, branding teams, and creative professionals to auto-generate, evaluate, and iteratively optimize brand stories using Ollama-hosted LLMs and LangChain agents. Each story is refined until it meets quality…