Extract & Summarize Bing Copilot Search Results with Gemini AI and Bright Data
This workflow automatically scrapes Bing Copilot's search results through the Bright Data API and utilizes the Google Gemini AI model for structured data extraction and content summarization. It addresses the issue of disorganized traditional search result data, enhancing information utilization efficiency. Users can quickly obtain search information related to keywords, aiding in market research, competitive intelligence analysis, and content creation. Ultimately, the processed results are pushed via Webhook, facilitating subsequent integration and automation.
Tags
Workflow Name
Extract & Summarize Bing Copilot Search Results with Gemini AI and Bright Data
Key Features and Highlights
This workflow is triggered by Bright Data’s Web Scraper API to capture Bing Copilot search results, leveraging Google Gemini AI models for structured data extraction and content summarization from the scraped data.
- Automatically executes Bing Copilot queries and retrieves snapshot data
- Enhances text processing efficiency through recursive text splitting and default data loading
- Applies Google Gemini’s advanced language models for structured data parsing and summary generation
- Supports error detection and automatic retry mechanisms to ensure data completeness and accuracy
- Delivers structured data and summaries via Webhook notifications for seamless downstream integration and processing
Core Problems Addressed
Traditional search result scraping often yields disorganized data that is difficult to parse automatically, making it challenging to quickly obtain high-quality structured information and concise summaries. This workflow solves the challenges of automated search data collection, structured parsing, and intelligent summarization, significantly improving information utilization efficiency.
Use Cases
- Market Research: Rapidly acquire search results for target keywords and extract key insights
- Competitive Intelligence Analysis: Automate scraping and analysis of competitor-related search data
- Content Creation Support: Generate summaries based on the latest search results to assist copywriting
- Data Integration and Automated Notifications: Push processed results to third-party systems to enable workflow automation
Main Process Steps
- Manually trigger the workflow to call Bright Data’s API and initiate a Bing Copilot search request
- Set and save the search snapshot ID
- Poll to check if the snapshot data is ready; if not, wait and retry
- Download the snapshot data and preprocess text using a recursive text splitter
- Extract structured data using the Google Gemini model
- Format results with a structured output parser
- Generate concise content summaries using the Google Gemini model
- Push structured data and summaries separately to designated notification endpoints via Webhook
Involved Systems or Services
- Bright Data Web Scraper API (for capturing Bing Copilot search snapshots)
- Google Gemini AI (PaLM) Model (for text parsing and summary generation)
- HTTP Webhook (for pushing structured data and summary notifications)
- n8n Automation Platform Nodes (HTTP requests, conditional checks, waiting, text splitting, data setting, etc.)
Target Users and Value
- Data Analysts and Market Researchers: Automate acquisition and structured processing of search information, saving significant manual effort
- Content Creators and Editors: Quickly distill core insights from large volumes of search content to enhance content production efficiency
- Product Managers and Business Decision Makers: Rapidly grasp market trends and user needs through intelligent summaries and structured data
- Automation Engineers and Developers: Serve as a demonstration template to flexibly extend integration with more data sources and AI models, building intelligent data processing pipelines
In summary, this workflow integrates web scraping, AI comprehension, and automated delivery to create an efficient and intelligent solution for processing search result data, suitable for enhancing information handling and decision-making efficiency across various business scenarios.
Brand Content Extract, Summarize & Sentiment Analysis with Bright Data
This workflow utilizes advanced web scraping and artificial intelligence technologies to automatically capture, extract text, generate summaries, and perform sentiment analysis on the content of specified brand webpages. By overcoming web scraping restrictions, it enables real-time access to high-quality content, systematically analyzes consumer attitudes towards the brand, and provides clear text summaries and sentiment classifications. It is suitable for brand monitoring, market research, and user feedback processing, helping relevant personnel quickly gain deep insights and optimize decisions and strategies.
Remove PII from CSV Files (Automated Personal Information Masking for CSV Files)
This workflow automatically monitors a Google Drive folder for new CSV files, and once a new file is detected, it initiates the process. It utilizes OpenAI to intelligently identify personally identifiable information (PII) columns and automatically removes this sensitive data, generating a de-identified file and re-uploading it to the designated folder. The entire process is efficient, intelligent, and requires no manual intervention, effectively reducing the risk of data breaches, making it suitable for businesses and teams that need to process privacy data in bulk.
Google Page Entity Extraction Template
This workflow utilizes the Google Natural Language API to automatically extract named entities such as people, organizations, and locations from any webpage, enabling structured analysis of information. Users submit the webpage URL via a webhook, and the system automatically fetches the content and performs entity recognition, returning detailed entity information along with its importance score. This tool is particularly suitable for scenarios such as media monitoring, market research, and data integration, significantly enhancing the efficiency and accuracy of information processing and helping users quickly obtain key data.
Extract Text from PDF and Images Using Vertex AI (Gemini) into CSV
This workflow can automatically extract text from newly uploaded PDF files and images in a specified Google Drive folder, using Google Vertex AI and Openrouter AI for intelligent recognition and analysis. The extracted transaction data will be converted into a CSV file with classification information and automatically uploaded back to Google Drive, thereby streamlining the manual data entry and classification process, improving the efficiency and accuracy of data processing, and making it suitable for various scenarios such as financial management and data analysis.
Calculate the Centroid of a Set of Vectors
This workflow can automatically receive and process multiple vectors, ensuring the consistency of input data dimensions. It calculates the centroid of these vectors, which is the average value across all dimensions, and returns the results in a user-friendly format. It effectively addresses common issues in multidimensional data processing and is applicable in fields such as data analysis, machine learning, and geographic information systems, enhancing the automation and accuracy of data processing.
AI Agent Conversational Assistant for Supabase/PostgreSQL Database
This workflow builds an intelligent dialogue assistant that combines natural language processing with database management, allowing users to query and analyze data using natural language without needing to master SQL skills. It can dynamically generate SQL queries, retrieve database table structures, process JSON data, and provide clear and understandable feedback on query results. This tool significantly lowers the barrier to database operations and is suitable for scenarios such as internal data analysis, customer service, product support, and education and training, enhancing the convenience and efficiency of data querying.
Spot Workplace Discrimination Patterns with AI
This workflow automates the scraping and analysis of employee review data from Glassdoor, utilizing AI technology to deeply analyze company ratings and the differences in workplace experiences among various demographic groups. It calculates statistical indicators and generates visual charts. It helps HR and management quantify workplace discrimination, supports fair improvement measures, promotes organizational culture enhancement and inclusivity assessments, and enables the effective implementation of data-driven diversity, equity, and inclusion initiatives.
Automatic Conversion of JSON Email Attachments to Spreadsheets
This workflow automates the retrieval of JSON files from the latest emails in Gmail and converts them into CSV format spreadsheets. It efficiently extracts binary JSON data from emails, automates the handling of email attachments, and eliminates the need for manual downloading and organizing, significantly enhancing data processing efficiency and reducing human errors. It is suitable for businesses and data analysts to quickly archive and analyze email data in their daily work, supporting data-driven decision-making.