# Make OpenAI citation for file retrieval RAG: n8n workflow

> Started by someone opening a chat with it. It calls services over plain HTTP rather than through connectors.

Source: https://millionrounds.com/workflow/make-openai-citation-for-file-retrieval-rag (Millionrounds; every figure on the page links to its filing or article)

[Automation library](https://millionrounds.com/workflows) · [Documents and files](https://millionrounds.com/workflows?category=Documents+and+files#library)

# Make OpenAI citation for file retrieval RAG

Started by someone opening a chat with it. It calls services over plain HTTP rather than through connectors. It puts OpenAI behind a retrieval step, so answers are drawn from documents you supply rather than from the model alone. 12 steps: a working afternoon to understand properly.

Medium Calls a model: OpenAI Retrieval

[Download free](https://millionrounds.com/login?next=%2Fapp%2Fworkflow%2Fmake-openai-citation-for-file-retrieval-rag)

**12 steps** Medium: a working afternoon

**0** Branches: places the flow splits

**0** Loops or waits

**0** Services by connector: it calls them over plain HTTP

## The flow

Starts it 1 Model 2 Logic 7 Service 2

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

- 1 **Window Buffer Memory** Memory Buffer Window *Model*
- 2 **Create a simple Trigger to have the Chat button within N8N** Chat trigger *Starts it*
- 3 **OpenAI Assistant with Vector Store** Open Ai *Model*
- 4 **Get ALL Thread Content** Http Request *Service*
- 5 **Split all message iterations from a thread** Split Out *Logic*
- 6 **Split all content from a single message** Split Out *Logic*
- 7 **Split all citations from a single message** Split Out *Logic*
- 8 **Retrieve file name from a file ID** Http Request *Service*
- 9 **Regularize output** Set *Logic*
- 10 **Aggregate** Aggregate *Logic*
- 11 **Finnaly format the output** Code *Logic*
- 12 **Optional Markdown to HTML** Markdown *Logic*

## How it's built

- **Starts on:** Someone opening a chat with it
- **Steps:** 12
- **Size:** Medium: a working afternoon
- **Connects to:** Nothing by connector; it calls services over plain HTTP
- **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, and a key for OpenAI. 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 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?

Plan an afternoon. 12 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 12 steps before you point it at anything that matters.

## Run it in n8n

- **Create your n8n account** Free to start. n8n is where the workflow runs. [Create an n8n account ↗](https://millionrounds.com/n8n)
- **Download the workflow** Free with a Millionrounds account. [Download free](https://millionrounds.com/login?next=%2Fapp%2Fworkflow%2Fmake-openai-citation-for-file-retrieval-rag)
- **Paste it into n8n** Open a new workflow in n8n and paste. Then connect your own accounts.

Stored with the author's traces removed: canvas notes, instance identifiers, saved credential names and any live document they had left behind.

## Workflows like it

Also documents and files, with the same services where possible, closest in size first.

- [**AI agent: Find the right LinkedIn profiles in seconds** 12 steps · calls a model · Google Sheets](https://millionrounds.com/workflow/ai-agent-find-the-right-linkedin-profiles-in-seconds)
- [**AI-powered company documents Q&A assistant with Google Drive** 12 steps · calls a model · Google Drive, in-memory vectors](https://millionrounds.com/workflow/ai-powered-company-documents-q-and-a-assistant-with-google-d)
- [**Ask questions about a PDF with OpenAI and Google Drive** 12 steps · calls a model · Google Drive, Pinecone](https://millionrounds.com/workflow/ask-questions-about-a-pdf-with-openai-and-google-drive)
- [**Audit ADM compliance in contracts with Google Drive and Gemini** 12 steps · calls a model · Google Drive, Google Sheets](https://millionrounds.com/workflow/audit-adm-compliance-in-contracts-with-google-drive-and-gemi)
- [**Chat with Telegram and Supabase** 12 steps · calls a model · Google Drive, Supabase vectors](https://millionrounds.com/workflow/chat-with-telegram-and-supabase)
- [**Extract and organize contract details from PDFs with Slack** 12 steps · calls a model · Google Sheets, Slack](https://millionrounds.com/workflow/extract-and-organize-contract-details-from-pdfs-with-slack)