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Vision-Based AI Web Scraper

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For the Vision-Based AI Agent Scraper, automate data extraction from webpages using screenshots and HTML. This workflow integrates Google Sheets for managing URLs and storing results, ScrapingBee for capturing full-page screenshots, and the Gemini-1.5-Pro AI model for accurate data parsing. It efficiently converts HTML to Markdown, optimizing processing costs, and is designed for e-commerce scraping, ensuring structured data is easily accessible and customizable for various needs.

Workflow Overview

For the Vision-Based AI Agent Scraper, automate data extraction from webpages using screenshots and HTML. This workflow integrates Google Sheets for managing URLs and storing results, ScrapingBee for capturing full-page screenshots, and the Gemini-1.5-Pro AI model for accurate data parsing. It efficiently converts HTML to Markdown, optimizing processing costs, and is designed for e-commerce scraping, ensuring structured data is easily accessible and customizable for various needs.

This workflow is ideal for:

  • E-commerce Businesses: Companies looking to gather product data from competitor websites for pricing analysis, inventory management, or market research.
  • Data Analysts: Professionals who need to extract structured data from various online sources for reporting and analysis.
  • Web Developers: Developers who want to automate the process of data collection from web pages for their applications.
  • Digital Marketers: Marketers aiming to track promotional offers and product details across different platforms for campaign optimization.

This workflow addresses the challenge of manually extracting data from web pages, which is often time-consuming and prone to errors. By leveraging a vision-based AI Agent alongside ScrapingBee, it automates the process of capturing screenshots and retrieving HTML data, ensuring accurate and structured information extraction. This is particularly beneficial for users who need to gather data quickly and efficiently, without the need for extensive coding or technical expertise.

  1. Manual Trigger: The workflow begins when the user manually triggers it by clicking ‘Test workflow’.
  2. Google Sheets Integration: It retrieves a list of URLs from a specified Google Sheet, which contains the pages to be scraped.
  3. Set Fields: The workflow sets the necessary parameters, particularly the URL, to be sent to the ScrapingBee API for data extraction.
  4. ScrapingBee - Get Page Screenshot: It captures a full-page screenshot of the specified URL using ScrapingBee, which is crucial for the AI Agent to analyze the content visually.
  5. Vision-Based Scraping Agent: The AI Agent analyzes the screenshot to extract relevant product information, such as titles, prices, and promotional details. If it encounters difficulties, it falls back on an HTML-based scraping tool.
  6. HTML-Based Scraping Tool: If needed, the agent retrieves the HTML content of the page for further analysis, ensuring no data is missed.
  7. Structured Output Parser: Extracted data is formatted into a structured JSON format suitable for easy integration into Google Sheets.
  8. Split Out: The structured data is split into individual rows for better organization.
  9. Google Sheets - Create Rows: Finally, the workflow appends the extracted data as new rows in the designated Google Sheets results sheet.

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Quick Info

Categories
Complex Workflow
Manual Triggered
+2
Complexity
complex

Tags

manual
advanced
api
integration
complex
sticky note
langchain
googlesheets
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