Search & Summarize Web Data with Perplexity, Gemini AI & Bright Data to Webhooks
This workflow integrates web scraping, intelligent search, and language processing technologies to achieve automated web data search, extraction, and summarization functions. Users can quickly obtain key information and utilize Webhook for result push notifications, significantly enhancing information retrieval efficiency. It is suitable for market research, content monitoring, and data-driven decision-making, providing analysts, product managers, and developers with an efficient solution that facilitates the convenience and quality of information processing.
Tags
Workflow Name
Search & Summarize Web Data with Perplexity, Gemini AI & Bright Data to Webhooks
Key Features and Highlights
This workflow integrates Bright Data’s web scraping and snapshot capabilities, Perplexity search requests, and the powerful language understanding and text processing abilities of Google Gemini AI. It enables automated web data searching, extraction, and intelligent summarization, with results pushed via Webhook for efficient information acquisition and distribution. The process also employs a recursive character splitter to optimize text handling, ensuring summaries are both comprehensive and accurate.
Core Problems Addressed
This solution tackles the challenge of rapidly obtaining high-quality, highly readable key information from vast and unstructured web data. By automating data crawling, status monitoring, content extraction, and intelligent summarization, it significantly reduces the time and effort required for manual filtering and reading, thereby enhancing information utilization efficiency.
Application Scenarios
- Market Research & Competitor Analysis: Quickly gather the latest information on target websites’ products or services and summarize key points
- Content Monitoring & Intelligence Gathering: Automatically track changes on specified web pages and extract summaries for notification
- Data-Driven Decision Support: Aggregate web data and generate concise reports to assist business decisions
- AI-Assisted Information Extraction and Natural Language Processing experiments and applications
Main Workflow Steps
- Manually trigger the workflow to initiate a search request (Manual Trigger)
- Send a Perplexity search request and invoke Bright Data API to start data crawling and snapshot creation
- Poll the snapshot ID to monitor crawling progress until data collection is complete
- Download the completed snapshot data
- Use Google Gemini AI model to extract readable content from the web pages
- Recursively split text to optimize content structure
- Generate content summaries using the Google Gemini model
- Send the final summary results via Webhook to a specified URL for result delivery and notification
Involved Systems or Services
- Bright Data (Web data crawling and snapshot management)
- Perplexity (Search request interface)
- Google Gemini AI Model (Language understanding, content extraction, and summarization)
- Webhook (Result push and notification)
Target Users and Value
- Data Analysts & Market Researchers: Quickly obtain structured web information summaries to support analysis
- Product Managers & Business Decision Makers: Efficiently access competitive intelligence and industry trends to aid decision-making
- Developers & Automation Engineers: Build intelligent data collection and processing pipelines to improve work efficiency
- AI Researchers & Content Operators: Explore AI applications in information extraction and text summarization
By combining multiple systems and AI technologies, this workflow delivers an automated, efficient, and intelligent solution for web data search and summarization, greatly enhancing the convenience and quality of information processing.
MONDAY GET FULL ITEM
This workflow is designed to automatically retrieve complete information about specified tasks from Monday.com, including all data related to main tasks, sub-tasks, and associated tasks. Through multi-level data scraping and integration, it ultimately outputs a well-structured JSON format data, facilitating subsequent processing and analysis. It effectively addresses the cumbersome and error-prone issues of manual data collection, enhancing the efficiency and accuracy of data retrieval, and is suitable for scenarios such as project management, report generation, and data integration.
Convert the JSON Data Received from the CocktailDB API into XML
This workflow is manually triggered to call the CocktailDB's random cocktail API to obtain data in JSON format, which is then automatically converted to XML format for easier processing and integration by downstream systems. It effectively addresses the issue of mismatched data formats returned by the API and the requirements of downstream systems, simplifying the data format conversion process and avoiding errors caused by manual operations. It is suitable for developers and data integration personnel to quickly implement automatic data format conversion in various scenarios.
International Space Station (ISS) Real-Time Location Push Workflow
This workflow automates the real-time acquisition and dissemination of the International Space Station's location. It retrieves the latest longitude, latitude, and timestamp every minute through a public API and publishes the data to a specified topic via the MQTT protocol. This process addresses the issue of low traditional data update frequency, enhancing the timeliness of the space station's location data. It is suitable for space enthusiasts, educational institutions, developers, and IoT operators, facilitating real-time monitoring and application integration.
Github Day Trend
Github Day Trend is an automated workflow that fetches and summarizes trending open-source projects from GitHub every day, enabling you to efficiently stay updated with the latest technology trends.