This workflow is designed to automate website data extraction, including scraping URLs, retrieving website content, and extracting social media profile links. It integrates multiple nodes such as web requests, HTML parsing, language models, and database operations to streamline data collection for marketing, competitive analysis, or data enrichment purposes.
The process begins with manual triggers that initiate different data retrieval workflows: one for gathering all URLs from a website, another for extracting textual content, and a third for collecting company information from a database.
In the URL workflows, the system visits target websites, extracts all links, deduplicates them, and filters out invalid or empty URLs. It then constructs full URLs from relative paths, optionally adds protocols, and makes HTTP requests to fetch webpage HTML content.
For content analysis, the workflows utilize a language model (GPT-4) to crawl websites and extract social media profile links from the webpage content, combining the data into a structured JSON format.
The workflow also supports managing company data from a database like Supabase, associating company names with websites, and storing enriched data back into the database. Additional features include converting HTML to Markdown for easy readability and inserting notes or instructions for workflow maintenance.
Practical use cases include monitoring competitors’ online presence, gathering social media contact info, or enriching corporate data for marketing campaigns. This workflow can be customized to scrape different types of data or interface with various databases, making it a versatile tool for web automation tasks.
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