Block 1 - OpenAI Chat Model2
- Type / Role
- @n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
- Config choices
- Version 1.2
This workflow is provided as-is. Please review and test before using in production.
How it works This workflow creates a complete AI powered restaurant ordering system through WhatsApp. It receives customer messages, processes multimedia content (text, voice, images, PDFs, locatio...
@n8n/n8n-nodes-langchain.lmchatopenai, @n8n/n8n-nodes-langchain.memorypostgreschat, n8n-nodes-base.wait, n8n-nodes-base.httprequest, n8n-nodes-base.code, n8n-nodes-base.whatsapp, n8n-nodes-base.set, n8n-nodes-base.stickynote
This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Rodrigo.
Original n8n.io sourceThis workflow creates a complete AI-powered restaurant ordering system through WhatsApp. It receives customer messages, processes multimedia content (text, voice, images, PDFs, location), uses GPT-4 to understand customer intent and manage conversations, handles the complete ordering flow from menu selection to payment verification, and sends formatted orders to restaurant staff. The system maintains conversation memory, verifies payment receipts using OCR, and provides automated responses in multiple languages.
Restaurant owners, food delivery services, and hospitality businesses looking to automate customer service and order management through WhatsApp without hiring additional staff.
[PHONE_NUMBER] placeholders with your actual restaurant and staff phone numbers[RESTAURANT_NAME], [RESTAURANT_OWNER_NAME], and [BANK_ACCOUNT_NUMBER] with your informationThis catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.
Showing the first 24 of 55 workflow blocks. Download the JSON for the full node graph.
| Workflow | Restaurant order & delivery system for WhatsApp with GPT-4o and Supabase |
|---|---|
| Complexity | advanced |
| Nodes | 55 |
| Categories | Support Chatbot, Multimodal AI |
| Author | Rodrigo |
| Published | 12 Aug 2025 |
Use the JSON export at /data/workflows/7298/7298.json as the source template for this automation.
Open n8n, import the downloaded JSON, and review each node before activating the workflow.
Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.
Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.
Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.
How it works This workflow creates a complete AI powered restaurant ordering system through WhatsApp. It receives customer messages, processes multimedia content (text, voice, images, PDFs, locatio...
Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.
Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Support Chatbot, Multimodal AI use case.