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Make OpenAI Citation for File Retrieval RAG

19 nodes · aggregate, memoryBufferWindow, chat, openAi, httpRequest, splitOut

Engine
n8n
Nodes
19
Trigger
scheduled/triggered
Source file
1059_Splitout_Code_Automation_Webhook.json

Workflow flow

IntegrationsAggregateMemoryBufferWindowChatOpenAIHTTPSplit OutMarkdown@n8n/n8n-nodes-langchain.memoryBufferWindow@n8n/n8n-nodes-langchain.chat@n8n/n8n-nodes-langchain.openAiSetCode
100%

Window Buffer Memory

@n8n/n8n-nodes-langchain.memoryBufferWindow

TRIGGER

Create a simple Trigger to have the Chat button within N8N

@n8n/n8n-nodes-langchain.chat

OpenAI Assistant with Vector Store

@n8n/n8n-nodes-langchain.openAi

Get ALL Thread Content

HTTP

Split all message iterations from a thread

Split Out

Split all content from a single message

Split Out

Split all citations from a single message

Split Out

Retrieve file name from a file ID

HTTP

Regularize output

Set

Aggregate

Aggregate

Finnaly format the output

Code

Optional Markdown to HTML

Markdown

12 steps · flows top to bottom, branches left to right

Browse by integration

aggregatememoryBufferWindowchatopenAihttpRequestsplitOutmarkdown
Browse all integrations →
Download n8n JSONDownload sanitized JSONDownload flow graph

Import into n8n

  1. Download the n8n JSON file (full or sanitized).
  2. In n8n: Workflows → Import from file.
  3. Open each node and reconnect credentials to your accounts.
  4. Test with manual execution before enabling triggers.

Sanitized JSON removes credential IDs — safer for sharing. Flow graph JSON is OpenRuna's lightweight format for diagrams and other tools, not n8n import.

View source corpus ↗

Overview

Make OpenAI Citation for File Retrieval RAG is a free n8n workflow on OpenRuna — 19 nodes connecting aggregate, memoryBufferWindow, chat, openAi, httpRequest, splitOut, markdown. Download the JSON, view the flow diagram, and import it into your n8n instance.

What this workflow does

This n8n workflow, "Make OpenAI Citation for File Retrieval RAG", wires together aggregate, memoryBufferWindow, chat, openAi, httpRequest, splitOut, markdown in 19 nodes. 19 nodes · aggregate, memoryBufferWindow, chat, openAi, httpRequest, splitOut Execution begins at the scheduled/triggered trigger and flows through the 19 configured nodes. OpenRuna shows the full flow diagram, an integration breakdown, and a one-click JSON export for n8n's "Import from file". Use it to learn integration patterns, fork it for your own use case, or deploy it quickly after reconnecting credentials.

Use cases

  • Fork it to add error handling, retries, or a notification step without designing the 19-node flow from scratch.
  • Benchmark it against your current aggregate integration to spot missing steps or redundant nodes.
  • Import "Make OpenAI Citation for File Retrieval RAG" into n8n, reconnect credentials for aggregate, memoryBufferWindow, chat, openAi, httpRequest, splitOut, markdown, and run the same automation in your own workspace.
  • Use it as a starting template when wiring aggregate, memoryBufferWindow, chat, openAi, httpRequest, splitOut, markdown — adjust node parameters to your accounts and record IDs.

Example output

Imported into n8n, "Make OpenAI Citation for File Retrieval RAG" exposes 19 configured nodes. Trigger type: scheduled/triggered. Integrations: aggregate, memoryBufferWindow, chat, openAi, httpRequest, splitOut, markdown. Set your credentials on the aggregate node, then verify each downstream node picks them up. Run it once in test mode to verify any branch logic (Switch/IF nodes) before enabling production triggers.

Tips by platform

Claude

Ask Claude to turn the "Make OpenAI Citation for File Retrieval RAG" JSON into a plain-English runbook, node by node. It can flag where aggregate rate limits or missing retries might bite before you go live.

ChatGPT

Drop the workflow JSON or this OpenRuna page URL into ChatGPT and ask for a step-by-step runbook: triggers, branches, and which fields to customise for aggregate, memoryBufferWindow, chat, openAi, httpRequest, splitOut, markdown. Handy for onboarding teammates new to n8n.

Cursor

In Cursor, ask Agent mode to parameterise "Make OpenAI Citation for File Retrieval RAG" — extract aggregate IDs and secrets into environment variables without changing the 19-node structure.

Frequently asked questions

How do I import "Make OpenAI Citation for File Retrieval RAG" into n8n?
Click Download n8n JSON on this page, then in n8n choose Workflows → Import from file and select the downloaded file. Reconnect credentials on each node — the export carries credential IDs from the original author's instance, not working secrets.
Which integrations does "Make OpenAI Citation for File Retrieval RAG" use?
It uses: aggregate, memoryBufferWindow, chat, openAi, httpRequest, splitOut, markdown. The flow diagram above shows how each service connects across the 19 nodes. Filter OpenRuna by integration to find related workflows and tools.
Can I import a sanitized export without credentials?
Yes. Use "Download sanitized JSON" to strip credential references before sharing internally. You will still add your own aggregate and memoryBufferWindow credentials in n8n after import.
What trigger type does "Make OpenAI Citation for File Retrieval RAG" use?
Trigger type: scheduled/triggered. After import, confirm the trigger node (webhook, schedule, or app event) matches your environment, then activate the workflow when you are ready to run it.
Is "Make OpenAI Citation for File Retrieval RAG" free to use?
OpenRuna catalogs community n8n workflows under open licenses. Check the source corpus link for the original license; commercial use may require verifying the third-party API terms for aggregate, memoryBufferWindow, chat, openAi, httpRequest, splitOut, markdown.

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