Automation library · AI assistants

Analyze and modernize university curricula with OpenAI

Started by an event in a connected app, and works across in-memory vectors and n8n data table. It puts OpenAI behind a retrieval step, so answers are drawn from documents you supply rather than from the model alone. 24 steps: large, and worth reading before you trust it with anything live.

LargeCalls a model: OpenAIRetrieval

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24 stepsLarge: read it before trusting it with anything live
0Branches: places the flow splits
0Loops or waits
2Services it connects to

The flow

Starts it 1Model 16Logic 2Service 5

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

  1. 1Start Curriculum AnalysisManual triggerStarts it
  2. 2Split Curriculum TextText Splitter Recursive Character Text SplitterModel
  3. 3Generate EmbeddingsEmbeddings Open AiModel
  4. 4Query EmbeddingsEmbeddings Open AiModel
  5. 5Employment Data Query ToolData Table ToolService
  6. 6Cognitive Load CalculatorTool CodeModel
  7. 7Alignment Agent ModelLm Chat Open AiModel
  8. 8Alignment Output ParserOutput Parser StructuredModel
  9. 9Forecast Agent ModelLm Chat Open AiModel
  10. 10Forecast Output ParserOutput Parser StructuredModel
  11. 11Supervisor ModelLm Chat Open AiModel
  12. 12Supervisor Output ParserOutput Parser StructuredModel
  13. 13Load Graduate Employment DataData TableService
  14. 14Load Enrollment PatternsData TableService
  15. 15Extract Course SyllabiExtract From FileService
  16. 16Load Curriculum DocumentsDocument Default Data LoaderModel
  17. 17Curriculum Knowledge BaseVector Store In MemoryModel
  18. 18Semantic Retrieval ToolVector Store In MemoryModel
  19. 19Industry Demand Forecast AgentAgent ToolModel
  20. 20Learning Outcome Alignment AgentAgent ToolModel
  21. 21Curriculum Modernization SupervisorAgentModel
  22. 22Combine Data SourcesMergeLogic
  23. 23Prepare Results for StorageSetLogic
  24. 24Store Analysis ResultsData TableService

How it's built

Starts on
An event in a connected app
Steps
24
Size
Large: read it before trusting it with anything live
Connects to
in-memory vectors, n8n data table
Model
OpenAI
Retrieval
Answers are drawn from documents you supply, not from the model alone

Questions

What does it need to run?

An n8n account, plus your own in-memory vectors account, and a key for OpenAI. You connect your own accounts after importing it; none are included.

What starts it?

It starts on an event in a connected app.

Does it use AI?

Yes. It calls OpenAI. Its answers draw on documents you give it, not on the model alone. Model calls are billed by the provider, not by n8n.

How long does it take to set up?

Take your time. At 24 steps it is large: read it before trusting it with anything live.

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 24 steps before you point it at anything that matters.