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Chatbots & Messaging Bots
Sell Products with an OpenAI Chatbot Backed by MySQL
When a chat message arrives, an OpenAI chatbot with Postgres memory looks up products in a MySQL database and answers customer questions.
What it does
# modelo do chatbot ## Overview Automated workflow: modelo do chatbot. This workflow integrates 9 different services: stickyNote, toolHttpRequest, mySqlTool, memoryPostgresChat, set. It contains 18 nodes and follows best practices for error handling and security. ## Workflow Details - Total Nodes: 18 - Node Types: 9 - Error Handling: ✅ Implemented - Security: ✅ Hardened (no sensitive data) - Documentation: ✅ Complete ## Node Breakdown - If Node: if - Edit Fields1: set - Edit Fields2: set - OpenAI: openAi - Chat Trigger: chatTrigger - Postgres Chat Memory: memoryPostgresChat - Postgres Chat Memory1: memoryPostgresChat - Products in Daatabase: mySqlTool - Knowledge Base: toolHttpRequest - External API: toolHttpRequest - ... and 8 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
The steps
- Manual Trigger
- If Node
- Edit Fields1
- Edit Fields2
- OpenAI
- Chat Trigger
- Postgres Chat Memory
- Postgres Chat Memory1
- Products in Daatabase
- Knowledge Base
- External API
- OpenAI2
- Error Handler
- Stopanderror 1
33 steps in total.
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