Извлечение структурированных веб-данных с Bright Data и Gemini

# Structured Data Extract, Data Mining with Bright Data & Google Gemini ## Overview Automated workflow: Structured Data Extract, Data Mining with Bright Data & Google Gemini. This workflow integrates 10 different services: stickyNote, httpRequest, lmChatGoogleGemini, readWriteFile, chainLlm. It contains 31 nodes and follows best practices for error handling and security. ## Workflow Details - Total Nodes: 31 - Node Types: 10 - Error Handling: ✅ Implemented - Security: ✅ Hardened (no sensitive data) - Documentation: ✅ Complete ## Node Breakdown - When clicking ‘Test workflow’: manualTrigger - Sticky Note: stickyNote - Sticky Note1: stickyNote - Markdown to Textual Data Extractor: chainLlm - Set URL and Bright Data Zone: set - Initiate a Webhook Notification for Markdown to Textual Data Extraction: httpRequest - Initiate a Webhook Notification for AI Sentiment Analyzer: httpRequest - Google Gemini Chat Model for Data Extract: lmChatGoogleGemini - Google Gemini Chat Model for Sentiment Analyzer: lmChatGoogleGemini - Perform Bright Data Web Request: httpRequest - ... and 21 more nodes ## Usage Instructions 1. Configure Credentials: Set up all required API keys and credentials 2. Update Variables: Replace any placeholder values with actual data 3. Test Workflow: Run in test mode to verify functionality 4. Deploy: Activate the workflow for production use ## Security Notes - All sensitive data has been removed or replaced with placeholders - Error handling is implemented for reliability - Follow security best practices when configuring credentials ## Troubleshooting - Check error logs if workflow fails - Verify all credentials are properly configured - Ensure all required services are accessible