Goodreads quote extraction with Bright Data and Gemini

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Important notice

This workflow is provided as-is. Please review and test before using in production.

1. Workflow Overview

Goodreads Quote Extraction with Bright Data and Gemini This workflow demonstrates how to fetch data specifically from Goodreads web pages using Bright Data and then extract specific information (qu...

Best for

Miscellaneous automation workflows
AI Summarization automation workflows
intermediate n8n builders looking for reusable templates

Tools used

n8n-nodes-base.manualtrigger, n8n-nodes-base.set, @n8n/n8n-nodes-langchain.lmchatgooglegemini, @n8n/n8n-nodes-langchain.informationextractor, n8n-nodes-base.httprequest

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Dvir Sharon.

Original n8n.io source

1.1 Workflow description

Title: Goodreads quote extraction with Bright Data and Gemini
Workflow name: Goodreads quote extraction with Bright Data and Gemini

Goodreads Quote Extraction with Bright Data and Gemini

This workflow demonstrates how to fetch data specifically from Goodreads web pages using Bright Data and then extract specific information (quotes) from that data using a Google Gemini AI model.

How it works

The workflow is triggered manually.
It sends a request to a Bright Data collector to scrape data from a predefined list of Goodreads URLs.
The collected text data from Goodreads is then passed to a Google Gemini AI node.
The AI node processes the text and extracts quotes based on a specified JSON schema output format.

Set up steps

Setting up this workflow should take only a few minutes.

You will need a Bright Data API key to configure the 'Header Auth' credential.
You will need a Google Gemini API key to configure the 'Google Gemini(PaLM) Api account' credential.
Ensure the correct Bright Data collector ID is set in the 'Perform Bright Data Web Request' node URL.
Make sure the full list of target Goodreads URLs is correctly added to the 'Perform Bright Data Web Request' node's body.
Link your created credentials to the respective nodes ('Perform Bright Data Web Request' and 'Quotes Extractor').
Keep detailed descriptions for specific node configurations in sticky notes inside your workflow canvas.

1.2 Logical Blocks

This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.

2. Block-by-Block Analysis

Block 1 - When clicking ‘Test workflow’

Type / Role: n8n-nodes-base.manualTrigger - manualTrigger
Config choices: Version 1

Block 2 - Set the fields

Type / Role: n8n-nodes-base.set - set
Config choices: Version 3.4

Block 3 - Google Gemini Chat Model

Type / Role: @n8n/n8n-nodes-langchain.lmChatGoogleGemini - lmChatGoogleGemini
Config choices: Version 1

Block 4 - Quotes Extractor

Type / Role: @n8n/n8n-nodes-langchain.informationExtractor - informationExtractor
Config choices: Version 1

Block 5 - Perform Bright Data Web Request

Type / Role: n8n-nodes-base.httpRequest - httpRequest
Config choices: Version 4.2

3. Summary Table

Workflow	Goodreads quote extraction with Bright Data and Gemini
Complexity	intermediate
Nodes	5
Categories	Miscellaneous, AI Summarization
Author	Dvir Sharon
Published	27 May 2025

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

Use the JSON export at /data/workflows/4438/4438.json as the source template for this automation.
2. Import the template into n8n

Open n8n, import the downloaded JSON, and review each node before activating the workflow.
3. Configure credentials and variables

Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
4. Test with sample data

Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
5. Activate and monitor

Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.

5. General Notes & Resources

Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.

Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.

Download workflow JSON Original n8n.io source Miscellaneous workflows AI Summarization workflows

Frequently asked questions

What does Goodreads quote extraction with Bright Data and Gemini do?

What do I need before importing this workflow?

Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.

Can I customize this workflow?

Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Miscellaneous, AI Summarization use case.

Dvir Sharon

8 workflows

Nodes

n8n-nodes-base.manualtrigger n8n-nodes-base.set @n8n/n8n-nodes-langchain.lmchatgooglegemini @n8n/n8n-nodes-langchain.informationextractor n8n-nodes-base.httprequest

Complexity

intermediate

Published 27 May 2025

Likes 0

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Install path: /data/workflows/4438/4438.json

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Goodreads quote extraction with Bright Data and Gemini

Workflow preview

Important notice

1. Workflow Overview

Best for

Tools used

Source and attribution

1.1 Workflow description

Goodreads Quote Extraction with Bright Data and Gemini

How it works

Set up steps

1.2 Logical Blocks

2. Block-by-Block Analysis

Block 1 - When clicking ‘Test workflow’

Block 2 - Set the fields

Block 3 - Google Gemini Chat Model

Block 4 - Quotes Extractor

Block 5 - Perform Bright Data Web Request

3. Summary Table

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

2. Import the template into n8n

3. Configure credentials and variables

4. Test with sample data

5. Activate and monitor

5. General Notes & Resources

Frequently asked questions