Zendesk-Support-Chat-Agent mit Drive-Wissen und OpenAI

# Chattrigger Workflow ## Overview Automated workflow: Chattrigger Workflow. This workflow integrates 18 different services: stickyNote, textSplitterTokenSplitter, splitInBatches, vectorStoreQdrant, agent. It contains 33 nodes and follows best practices for error handling and security. ## Workflow Details - Total Nodes: 33 - Node Types: 18 - Error Handling: ✅ Implemented - Security: ✅ Hardened (no sensitive data) - Documentation: ✅ Complete ## Node Breakdown - When chat message received: chatTrigger - AI Agent: agent - OpenAI Chat Model: lmChatOpenAi - Split Out: splitOut - Embeddings OpenAI1: embeddingsOpenAi - Default Data Loader: documentDefaultDataLoader - Token Splitter1: textSplitterTokenSplitter - Window Buffer Memory: memoryBufferWindow - Embeddings OpenAI2: embeddingsOpenAi - Extract from File: extractFromFile - ... and 23 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