Automation library · Data collection

Generate & optimize brand stories with Ollama LLMs

Started by someone opening a chat with it, and works across Google Sheets. It hands the judgement calls to a local model. 9 steps, 1 branch: a working afternoon to understand properly.

MediumCalls a model: a local model

9 stepsMedium: a working afternoon
1Branch: places the flow splits
0Loops or waits
1Service it connects to

The flow

Starts it 1Model 5Logic 2Service 1

The steps in the order they run, from what starts it.

  1. 1Ollama Chat ModelLm Chat OllamaModel
  2. 2Ollama Chat Model1Lm Chat OllamaModel
  3. 3Chat Input: Start Story FlowChat triggerStarts it
  4. 4Brand Storytelling AgentAgentModel
  5. 5Evaluator AgentAgentModel
  6. 6Optimizer AgentAgentModel
  7. 7Set Brand variableSetLogic
  8. 8Evaluation CheckIfLogic
  9. 9Save Brand Story to SheetsGoogle SheetsService

How it's built

Starts on
Someone opening a chat with it
Steps
9, with 1 branch
Size
Medium: a working afternoon
Connects to
Google Sheets
Model
a local model

Questions

What does it need to run?

An n8n account, plus your own Google Sheets account, and a key for a local model. You connect your own accounts after importing it; none are included.

What starts it?

It starts on someone opening a chat with it.

Does it use AI?

Yes. It calls a local model. Model calls are billed by the provider, not by n8n.

How long does it take to set up?

Plan an afternoon. 9 steps is enough that you should read each one before running it.

How do I import it?

Copy the workflow, open a new workflow in n8n and paste. The steps appear on the canvas, ready for your own accounts.

Before you run it

Nothing here has been tested by us. It is somebody's working automation, read and described from its own steps. Treat the connections it wants as a list of accounts it will touch, and read the 9 steps before you point it at anything that matters.