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Automate Etsy Data Mining with Bright Data Scrape & Google Gemini

19 nodes · manual, httpRequest, lmChatGoogleGemini, splitInBatches, informationExtractor, readWriteFile

Engine
n8n
Nodes
19
Trigger
scheduled/triggered
Source file
1721_Splitout_Manual_Automate_Webhook.json

Workflow flow

IntegrationsManualHTTPLmChatGoogleGeminiSplitInBatchesInformationExtractorReadWriteFileSplit OutLmChatOpenAiSet@n8n/n8n-nodes-langchain.lmChatGoogleGemini@n8n/n8n-nodes-langchain.informationExtractorFunction+1 more
100%
TRIGGER

When clicking ‘Test workflow’

Manual

Google Gemini Chat Model

@n8n/n8n-nodes-langchain.lmChatGoogleGemini

Google Gemini Chat Model for product info

@n8n/n8n-nodes-langchain.lmChatGoogleGemini

Extract Paginated Resultset With OpenAI

@n8n/n8n-nodes-langchain.informationExtractor

OpenAI Chat Model

@n8n/n8n-nodes-langchain.lmChatOpenAi

Set Esty Search Query

Set

Perform Esty Web Request

HTTP

Extract Paginated Resultset

@n8n/n8n-nodes-langchain.informationExtractor

Split Out

Split Out

Extract Item List with the Product Info

@n8n/n8n-nodes-langchain.informationExtractor

Initiate a Webhook Notification for the extracted data

HTTP

Create a binary data

Function

Loop Over Items

SplitInBatches

Write the scraped content to disk

ReadWriteFile

Perform Esty web request over the loop

HTTP

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

Browse by integration

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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

Free n8n workflow: Automate Etsy Data Mining with Bright Data Scrape & Google Gemini. 19 nodes across manual, httpRequest, lmChatGoogleGemini, splitInBatches, informationExtractor, readWriteFile, splitOut, lmChatOpenAi, with a downloadable JSON and a visual flow diagram on OpenRuna.

What this workflow does

Built in n8n, "Automate Etsy Data Mining with Bright Data Scrape & Google Gemini" chains 19 nodes to move data between manual, httpRequest, lmChatGoogleGemini, splitInBatches, informationExtractor, readWriteFile, splitOut, lmChatOpenAi. 19 nodes · manual, httpRequest, lmChatGoogleGemini, splitInBatches, informationExtractor, readWriteFile Execution begins at the scheduled/triggered trigger and flows through the 19 configured nodes. On OpenRuna you get the visual graph, the integration list, and a downloadable JSON ready to import into n8n. 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 manual integration to spot missing steps or redundant nodes.
  • Study how data moves from manual to httpRequest before building your own variant.
  • Share it with your team as a documented reference for scheduled/triggered automations in the manual stack.

Example output

Imported into n8n, "Automate Etsy Data Mining with Bright Data Scrape & Google Gemini" exposes 19 configured nodes. Trigger type: scheduled/triggered. Integrations: manual, httpRequest, lmChatGoogleGemini, splitInBatches, informationExtractor, readWriteFile, splitOut, lmChatOpenAi. Set your credentials on the manual 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 "Automate Etsy Data Mining with Bright Data Scrape & Google Gemini" JSON into a plain-English runbook, node by node. It can flag where manual 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 manual, httpRequest, lmChatGoogleGemini, splitInBatches, informationExtractor, readWriteFile, splitOut, lmChatOpenAi. Handy for onboarding teammates new to n8n.

Cursor

In Cursor, ask Agent mode to parameterise "Automate Etsy Data Mining with Bright Data Scrape & Google Gemini" — extract manual IDs and secrets into environment variables without changing the 19-node structure.

Frequently asked questions

How do I import "Automate Etsy Data Mining with Bright Data Scrape & Google Gemini" 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 "Automate Etsy Data Mining with Bright Data Scrape & Google Gemini" use?
It uses: manual, httpRequest, lmChatGoogleGemini, splitInBatches, informationExtractor, readWriteFile, splitOut, lmChatOpenAi. 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 manual and httpRequest credentials in n8n after import.
What trigger type does "Automate Etsy Data Mining with Bright Data Scrape & Google Gemini" 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 "Automate Etsy Data Mining with Bright Data Scrape & Google Gemini" 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 manual, httpRequest, lmChatGoogleGemini, splitInBatches, informationExtractor, readWriteFile, splitOut, lmChatOpenAi.

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