Wettervorhersage-Chat-Agent mit OpenAI und Open-Meteo

# Integrating AI with Open-Meteo API for Enhanced Weather Forecasting ## Overview Automated workflow: Integrating AI with Open-Meteo API for Enhanced Weather Forecasting. This workflow integrates 7 different services: stickyNote, toolHttpRequest, agent, stopAndError, lmChatOpenAi. It contains 17 nodes and follows best practices for error handling and security. ## Workflow Details - Total Nodes: 17 - Node Types: 7 - Error Handling: ✅ Implemented - Security: ✅ Hardened (no sensitive data) - Documentation: ✅ Complete ## Node Breakdown - When chat message received: chatTrigger - OpenAI Chat Model: lmChatOpenAi - Sticky Note: stickyNote - Sticky Note1: stickyNote - Generic AI Tool Agent: agent - Chat Memory Buffer: memoryBufferWindow - Sticky Note2: stickyNote - Sticky Note5: stickyNote - A tool to get the weather forecast based on geolocation: toolHttpRequest - Sticky Note6: stickyNote - ... and 7 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