Эмбеддинги файлов с FTP в векторной базе Qdrant

# Qdrant Vector Database Embedding Pipeline ## Overview Automated workflow: Qdrant Vector Database Embedding Pipeline. This workflow integrates 9 different services: stickyNote, vectorStoreQdrant, ftp, documentDefaultDataLoader, stopAndError. It contains 14 nodes and follows best practices for error handling and security. ## Workflow Details - Total Nodes: 14 - Node Types: 9 - Error Handling: ✅ Implemented - Security: ✅ Hardened (no sensitive data) - Documentation: ✅ Complete ## Node Breakdown - Qdrant Vector Store: vectorStoreQdrant - When clicking ‘Test workflow’: manualTrigger - Embeddings OpenAI: embeddingsOpenAi - Default Data Loader: documentDefaultDataLoader - Character Text Splitter: textSplitterCharacterTextSplitter - Sticky Note: stickyNote - Sticky Note1: stickyNote - Sticky Note2: stickyNote - Sticky Note3: stickyNote - List all the files: ftp - ... and 4 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