Library / Web Scraping & Research
Web Scraping & Research
Run Web Research Requests with ScrapeGraphAI and OpenAI
When a research request arrives by webhook, the workflow splits it into search queries, scrapes sources with ScrapeGraphAI, has OpenAI analyze them and stores findings in Google Sheets.
What it does
# Step 5: Data Storage & Response 📊 Secure storage of research findings and structured response delivery for seamless integration with other systems. ## Google Sheets Storage - Sheet Structure: Research_Data with comprehensive columns - Data Retention: Historical research for trend analysis - Access Control: Secure OAuth2 authentication - Format: Structured data ready for analysis and reporting ## Response Delivery - Format: JSON with status and metadata - Content: Session ID, completion status, source count - Integration: Ready for webhook consumers and APIs - Tracking: Unique session IDs for research correlation ## Data Management Features - Versioning: Track research iterations - Export: Multiple format support - Sharing: Team collaboration capabilities - Analytics: Built-in Google Sheets analysis tools ## Use Cases - Market Research: Competitive analysis and trends - Academic Research: Literature reviews and citations - Business Intelligence: Industry insights and reports
The steps
- Research Request Webhook
- Research Configuration Processor
- Split Search Queries
- Query Selector
- AI Research Scraper
- News Sources Scraper
- Academic Sources Scraper
- Merge Research Sources
- Research Data Processor
- Research Data Storage
- Research Complete Response
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