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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
1548_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

Browse all integrations →

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 (19-node n8n automation, aggregate, memoryBufferWindow, chat, openAi, httpRequest, splitOut, markdown) is free on OpenRuna — view the graph and export the JSON to import into n8n.

What this workflow does

"Make OpenAI Citation for File Retrieval RAG" automates a aggregate-to-memoryBufferWindow flow in n8n across 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 renders the node graph and offers the JSON export so you can import and adapt it in minutes. Use it to learn integration patterns, fork it for your own use case, or deploy it quickly after reconnecting credentials.

Use cases

  • Share it with your team as a documented reference for scheduled/triggered automations in the aggregate stack.
  • Study how data moves from aggregate to memoryBufferWindow before building your own variant.
  • Use it as a starting template when wiring aggregate, memoryBufferWindow, chat, openAi, httpRequest, splitOut, markdown — adjust node parameters to your accounts and record IDs.
  • 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.

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. Open each node after import to map credentials to your own aggregate and memoryBufferWindow accounts. Run it once in test mode to verify any branch logic (Switch/IF nodes) before enabling production triggers.

Tips by platform

Claude

Paste the exported JSON for "Make OpenAI Citation for File Retrieval RAG" into Claude and ask it to explain each of the 19 nodes. Claude is good at suggesting credential mappings for aggregate, memoryBufferWindow, chat, openAi, httpRequest, splitOut, markdown, plus error-handling and idempotency improvements before you run it in production.

ChatGPT

Have ChatGPT generate a checklist for adapting "Make OpenAI Citation for File Retrieval RAG" to your accounts — which aggregate, memoryBufferWindow, chat, openAi, httpRequest, splitOut, markdown credentials to create and which node parameters to change first.

Cursor

Open the downloaded JSON in Cursor and use Agent mode to refactor hard-coded URLs into env vars, or to generate tests for any Code nodes. Keep the OpenRuna flow diagram open so you do not break connection order across the 19 nodes.

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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