# Scrape and ingest web pages into a Pinecone RAG stack: n8n workflow

> Started by someone opening a chat with it, and works across Pinecone. It puts OpenAI and OpenRouter behind a retrieval step, so answers are drawn from...

Source: https://millionrounds.com/workflow/scrape-and-ingest-web-pages-into-a-pinecone-rag-stack (Millionrounds; every figure on the page links to its filing or article)

[Automation library](https://millionrounds.com/workflows) · [Data collection](https://millionrounds.com/workflows?category=Data+collection#library)

# Scrape and ingest web pages into a Pinecone RAG stack

Started by someone opening a chat with it, and works across Pinecone. It puts OpenAI and OpenRouter behind a retrieval step, so answers are drawn from documents you supply rather than from the model alone. 15 steps: a working afternoon to understand properly.

Medium Calls a model: OpenAI, OpenRouter Retrieval

[Download free](https://millionrounds.com/login?next=%2Fapp%2Fworkflow%2Fscrape-and-ingest-web-pages-into-a-pinecone-rag-stack)

**15 steps** Medium: a working afternoon

**0** Branches: places the flow splits

**0** Loops or waits

**1** Service it connects to

## The flow

Starts it 4 Model 9 Logic 1 Service 1

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

- 1 **Receive URL** Webhook *Starts it*
- 2 **Generate OpenAI embeddings** Embeddings Open Ai *Model*
- 3 **Load scraped content** Document Default Data Loader *Model*
- 4 **Receive chat message** Chat trigger *Starts it*
- 5 **OpenRouter LLM** Lm Chat Open Router *Model*
- 6 **Chat memory** Memory Buffer Window *Model*
- 7 **Generate OpenAI embeddings1** Embeddings Open Ai *Model*
- 8 **Rerank results with Cohere** Reranker Cohere *Model*
- 9 **Validate and normalize URL** Code *Logic*
- 10 **Store embeddings in Pinecone** Vector Store Pinecone *Model*
- 11 **Answer query from knowledge base** Agent *Model*
- 12 **Retrieve documents from Pinecone** Vector Store Pinecone *Model*
- 13 **Scrape page with Firecrawl** Firecrawl *Service*
- 14 **Return URL validation error** Respond To Webhook *Starts it*
- 15 **Return ingestion result** Respond To Webhook *Starts it*

## How it's built

- **Starts on:** Someone opening a chat with it
- **Steps:** 15
- **Size:** Medium: a working afternoon
- **Connects to:** Pinecone
- **Model:** OpenAI, OpenRouter
- **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 Pinecone account, and a key for OpenAI and OpenRouter. 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 and OpenRouter. 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. 15 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 15 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%2Fscrape-and-ingest-web-pages-into-a-pinecone-rag-stack)
- **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.

[Pinecone](https://millionrounds.com/workflows?service=Pinecone#library)

## Workflows like it

Also data collection, with the same services where possible, closest in size first.

- [**Create AI-ready vector datasets for LLMs with Bright Data** 16 steps · calls a model · Pinecone](https://millionrounds.com/workflow/create-ai-ready-vector-datasets-for-llms-with-bright-data)
- [**Guide students with RAG and OpenAI** 14 steps · calls a model · Google Sheets, Pinecone](https://millionrounds.com/workflow/guide-students-with-rag-and-openai)
- [**Synchronize MySQL database schemas to Pinecone with OpenAI** 17 steps · calls a model · MySQL, Pinecone](https://millionrounds.com/workflow/synchronize-mysql-database-schemas-to-pinecone-with-openai)
- [**Export WordPress to Pinecone vector store with OpenAI** 19 steps · calls a model · Pinecone](https://millionrounds.com/workflow/export-wordpress-to-pinecone-vector-store-with-openai)
- [**AI-powered Asana task prioritization with OpenAI and Pinecone** 10 steps · calls a model · Asana, Pinecone](https://millionrounds.com/workflow/ai-powered-asana-task-prioritization-with-openai-and-pinecon)
- [**Send personalized SaaS welcome emails with Stripe and Pinecone** 10 steps · calls a model · Gmail, Google Sheets](https://millionrounds.com/workflow/send-personalized-saas-welcome-emails-with-stripe-and-pineco)