# Document-based AI chatbot with RAG and OpenAI: n8n workflow

> Started by someone opening a chat with it, and works across Google Drive and Supabase vectors.

Source: https://millionrounds.com/workflow/document-based-ai-chatbot-with-rag-and-openai (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)

# Document-based AI chatbot with RAG and OpenAI

Started by someone opening a chat with it, and works across Google Drive and Supabase vectors. It puts OpenAI behind a retrieval step, so answers are drawn from documents you supply rather than from the model alone. 13 steps: a working afternoon to understand properly.

Medium Calls a model: OpenAI Retrieval

[Download free](https://millionrounds.com/login?next=%2Fapp%2Fworkflow%2Fdocument-based-ai-chatbot-with-rag-and-openai)

**13 steps** Medium: a working afternoon

**0** Branches: places the flow splits

**0** Loops or waits

**2** Services it connects to

## The flow

Starts it 2 Model 9 Service 2

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

- 1 **Chat Interface** Chat trigger *Starts it*
- 2 **AI Model (OpenAI)** Lm Chat Open Ai *Model*
- 3 **Search Embeddings** Embeddings Open Ai *Model*
- 4 **Conversation Memory** Memory Buffer Window *Model*
- 5 **Load Documents Trigger** Manual trigger *Starts it*
- 6 **Document Embeddings** Embeddings Open Ai *Model*
- 7 **Process Document Text** Document Default Data Loader *Model*
- 8 **Cohere Reranker** Reranker Cohere *Model*
- 9 **RAG Agent** Agent *Model*
- 10 **Knowledge Base Search** Vector Store Supabase *Model*
- 11 **Download PDF from Drive** Google Drive *Service*
- 12 **Store in Vector Database** Vector Store Supabase *Model*
- 13 **Extract PDF Content** Extract From File *Service*

## How it's built

- **Starts on:** Someone opening a chat with it
- **Steps:** 13
- **Size:** Medium: a working afternoon
- **Connects to:** Google Drive, Supabase vectors
- **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 Google Drive and Supabase vectors accounts, 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. 13 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 13 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%2Fdocument-based-ai-chatbot-with-rag-and-openai)
- **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.

## Connects to

Each opens the other workflows that use it.

[Google Drive](https://millionrounds.com/workflows?service=Google+Drive#library)[Supabase vectors](https://millionrounds.com/workflows?service=Supabase+vectors#library)

## Workflows like it

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

- [**Automate multi-language text translation with OpenAI** 13 steps · calls a model · Google Drive](https://millionrounds.com/workflow/automate-multi-language-text-translation-with-openai)
- [**Build a PDF Q&A system with LlamaIndex and OpenAI** 13 steps · calls a model · Google Drive, Pinecone](https://millionrounds.com/workflow/build-a-pdf-q-and-a-system-with-llamaindex-and-openai)
- [**Build a document QA system with RAG and Milvus** 13 steps · calls a model · Google Drive](https://millionrounds.com/workflow/build-a-document-qa-system-with-rag-and-milvus)
- [**Build a retrieval-based chatbot with Telegram and OpenAI** 13 steps · calls a model · Google Drive, Telegram](https://millionrounds.com/workflow/build-a-retrieval-based-chatbot-with-telegram-and-openai)
- [**Google Drive AI Document Classifier with DeepSeek** 13 steps · calls a model · Google Drive](https://millionrounds.com/workflow/google-drive-ai-document-classifier-with-deepseek)
- [**Google Drive AI documents classifier with DeepSeek** 13 steps · calls a model · Google Drive](https://millionrounds.com/workflow/google-drive-ai-documents-classifier-with-deepseek)