Scrape Books from URL with Dumpling AI, Clean HTML, Save to Sheets, Email as CSV

This workflow automatically generates 10 data entries after being manually triggered and processes them one by one. During the processing, flexible flow control is achieved through conditional judgments. When processing the 6th data entry, a specific operation is triggered, and the loop ends. This design effectively addresses the need for executing tasks on batch data one by one while allowing for immediate interruption of subsequent operations when specific conditions are met, thereby improving processing efficiency and intelligence. It is suitable for scenarios such as data cleaning and approval processes.

This workflow integrates Bright Data and Google Gemini AI to achieve intelligent web data scraping and processing. Users only need to input the target URL and format instructions, and the AI agent will automatically select the appropriate scraping tool, supporting multiple data format outputs, and push the results via Webhook. At the same time, the scraped content will be saved as a local file for easy subsequent analysis. This system lowers the technical barriers to web scraping, improves efficiency, and is suitable for various scenarios such as market research, content aggregation, and data analysis.

This workflow implements the automatic collection and sentiment analysis of customer feedback, ensuring that data processing is efficient and accurate. After customers submit feedback through a customized form, the system automatically utilizes AI technology for sentiment classification and integrates the analysis results with the original data, ultimately storing it in Google Sheets. This process not only enhances the response speed of the customer service team but also helps product managers and market researchers quickly gain insights into customer satisfaction and needs, facilitating improved business decision-making and service quality.

This workflow combines web data scraping and large language models to achieve structured data extraction and deep analysis of web pages. Users can automatically retrieve and parse web content, extract themes, identify trends, and conduct sentiment analysis, generating easy-to-understand reports. It supports saving results as local files and provides real-time notifications via Webhook, making it suitable for various scenarios such as media monitoring, market research, and data processing, significantly improving the efficiency and accuracy of data analysis.

The main function of this workflow is to automatically retrieve website traffic data from Google Analytics, analyzing page engagement, search performance, and country distribution over the past two weeks. By utilizing AI to intelligently interpret the data, it generates professional SEO optimization recommendations and saves the results to a Baserow database for easier management and tracking. This process simplifies data comparison and analysis, enhancing the efficiency and accuracy of SEO decision-making, making it highly suitable for website operators and digital marketing teams.

This workflow is designed to convert webpage HTML content into structured Markdown format and extract all links from the webpage. By utilizing the Firecrawl.dev API, it supports batch processing of URLs, automatically managing request rates to ensure stable and efficient content crawling and conversion. It is suitable for scenarios such as data analysis, content aggregation, and market research, helping users quickly acquire and process large amounts of webpage information, reducing manual operations and improving work efficiency.

The smart factory data generator periodically generates simulated operational data for factory machines, including machine ID, temperature, runtime, and timestamps, and sends it to a designated message queue via the AMQP protocol. This workflow effectively addresses the lack of real-time data sources in smart factory and industrial IoT environments, supporting developers and testers in system functionality validation, performance tuning, and data analysis without the need for real devices, thereby enhancing overall work efficiency.

This workflow is a web content scraping and processing tool that can automatically retrieve web page content from specified URLs and convert it into Markdown format. It supports two scraping modes: complete and simplified. The simplified mode reduces links and images to prevent excessively long content from wasting computational resources. The built-in error handling mechanism intelligently responds to request exceptions, ensuring the stability and accuracy of the scraping process. It is suitable for various scenarios such as AI chatbots, data scraping, and content summarization.