Run a human-approved shopping assistant with GPT-4.1-mini, product APIs and Slack
n8n-workflow-18185.n8n.io
· n8n.io
Quick overview This workflow powers a chat-based shopping assistant using OpenAI for conversation, an HTTP product-catalog search API for live item data, and a checkout/order API to place orders with explicit user approval, then posts the final order status to a Slack channel. How it works 1. Triggers from an n8n Chat Trigger (or a manual test run) when a user submits a shopping request. 2. Uses OpenAI (GPT-4.1-mini) with short-term memory and function calling to query a product-catalog search API for real-time price and availability before recommending up to three items. 3. Parses the agent’s structured JSON response into a reply, an optional product shortlist, and a purchase-intent signal with selected product and quantity. 4. If there is no purchase intent, returns the direct reply message; if there is purchase intent, pauses for the user to confirm the product selection via a resume webhook. 5. Pauses again for an explicit purchase approval via a second resume webhook, then submits
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| Agent card | https://n8n.io/workflows/18185 |
| Provider | https://n8n.io |
| Docs | https://n8n.io/workflows/18185 |
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"icon": "\ud83d\udcc8",
"label": "A low-code bitcoin ticker built with QuestDB and n8n.io"
},
{
"url": "https://n8n.io/blog/how-to-set-up-a-ci-cd-pipeline-with-no-code/",
"icon": "\ud83c\udfa1",
"label": "How to set up a no-code CI/CD pipeline with GitHub and TravisCI"
},
{
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"icon": "\ud83c\udf96",
"label": "Benefits of automation and n8n: An interview with HubSpot's Hugh Durkin"
},
{
"url": "https://n8n.io/blog/how-goomer-automated-their-operations-with-over-200-n8n-workflows/",
"icon": "\ud83d\udef5",
"label": "How Goomer automated their operations with over 200 n8n workflows"
},
{
"url": "https://n8n.io/blog/aws-workflow-automation/",
"label": "7 no-code workflow automations for Amazon Web Services"
}
],
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"url": "https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.set/"
}
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},
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"subcategories": {
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}
}
},
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},
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},
"displayName": "Edit Fields (Set)",
"typeVersion": 3,
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}
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},
{
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"icon": "file:slack.svg",
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},
{
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},
{
"url": "https://n8n.io/blog/how-to-get-started-with-crm-automation-and-no-code-workflow-ideas/",
"icon": "\ud83d\udc65",
"label": "How to get started with CRM automation (with 3 no-code workflow ideas"
},
{
"url": "https://n8n.io/blog/5-tasks-you-can-automate-with-notion-api/",
"icon": "\u26a1\ufe0f",
"label": "5 tasks you can automate with the new Notion API "
},
{
"url": "https://n8n.io/blog/build-your-own-virtual-assistant-with-n8n-a-step-by-step-guide/",
"icon": "\ud83d\udc66",
"label": "Build your own virtual assistant with n8n: A step by step guide"
},
{
"url": "https://n8n.io/blog/how-to-automatically-give-kudos-to-contributors-with-github-slack-and-n8n/",
"icon": "\ud83d\udc4f",
"label": "How to automatically give kudos to contributors with GitHub, Slack, and n8n"
},
{
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"icon": "\u2728",
"label": "How Common Knowledge use workflow automation for activism"
}
],
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}
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},
{
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}
]
},
{
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"icon": "fa:pause-circle",
"name": "n8n-nodes-base.wait",
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},
{
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"label": "7 no-code workflow automations for Amazon Web Services"
}
],
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}
]
},
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],
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"codexVersion": "1.0",
"subcategories": {
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]
}
}
},
"group": "[\"organization\"]",
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"name": "Wait",
"color": "#804050"
},
"iconData": {
"icon": "pause-circle",
"type": "icon"
},
"displayName": "Wait",
"typeVersion": 1,
"nodeCategories": [
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"name": "Core Nodes"
}
]
},
{
"id": 565,
"icon": "fa:sticky-note",
"name": "n8n-nodes-base.stickyNote",
"codex": {
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"Notes",
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],
"categories": [
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],
"nodeVersion": "1.0",
"codexVersion": "1.0",
"subcategories": {
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}
}
},
"group": "[\"input\"]",
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"color": "#FFD233"
},
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},
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}
]
},
{
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"icon": "file:code.svg",
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"JS",
"Python",
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],
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"resources": {
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}
]
},
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"subcategories": {
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}
}
},
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},
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},
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"id": 5,
"name": "Development"
},
{
"id": 9,
"name": "Core Nodes"
}
]
},
{
"id": 838,
"icon": "fa:mouse-pointer",
"name": "n8n-nodes-base.manualTrigger",
"codex": {
"data": {
"resources": {
"generic": [],
"primaryDocumentation": [
{
"url": "https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.manualworkflowtrigger/"
}
]
},
"categories": [
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],
"nodeVersion": "1.0",
"codexVersion": "1.0"
}
},
"group": "[\"trigger\"]",
"defaults": {
"name": "When clicking \u2018Execute workflow\u2019",
"color": "#909298"
},
"iconData": {
"icon": "mouse-pointer",
"type": "icon"
},
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}
]
},
{
"id": 1119,
"icon": "fa:robot",
"name": "@n8n/n8n-nodes-langchain.agent",
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"Conversational",
"Plan and Execute",
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],
"resources": {
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{
"url": "https://docs.n8n.io/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.agent/"
}
]
},
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"Langchain"
],
"subcategories": {
"AI": [
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"Root Nodes"
]
}
}
},
"group": "[\"transform\"]",
"defaults": {
"name": "AI Agent",
"color": "#404040"
},
"iconData": {
"icon": "robot",
"type": "icon"
},
"displayName": "AI Agent",
"typeVersion": 3,
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{
"id": 25,
"name": "AI"
},
{
"id": 26,
"name": "Langchain"
}
]
},
{
"id": 1153,
"icon": "file:openAiLight.svg",
"name": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
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"resources": {
"primaryDocumentation": [
{
"url": "https://docs.n8n.io/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.lmchatopenai/"
}
]
},
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"Langchain"
],
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"AI": [
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"Root Nodes"
],
"Language Models": [
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]
}
}
},
"group": "[\"transform\"]",
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"name": "OpenAI Chat Model"
},
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},
"displayName": "OpenAI Chat Model",
"typeVersion": 1,
"nodeCategories": [
{
"id": 25,
"name": "AI"
},
{
"id": 26,
"name": "Langchain"
}
]
},
{
"id": 1163,
"icon": "fa:database",
"name": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
"codex": {
"data": {
"resources": {
"primaryDocumentation": [
{
"url": "https://docs.n8n.io/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.memorybufferwindow/"
}
]
},
"categories": [
"AI",
"Langchain"
],
"subcategories": {
"AI": [
"Memory"
],
"Memory": [
"For beginners"
]
}
}
},
"group": "[\"transform\"]",
"defaults": {
"name": "Simple Memory"
},
"iconData": {
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},
"displayName": "Simple Memory",
"typeVersion": 1,
"nodeCategories": [
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"id": 25,
"name": "AI"
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"id": 26,
"name": "Langchain"
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},
{
"id": 1247,
"icon": "fa:comments",
"name": "@n8n/n8n-nodes-langchain.chatTrigger",
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"data": {
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"primaryDocumentation": [
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"url": "https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-langchain.chattrigger/"
}
]
},
"categories": [
"Core Nodes",
"Langchain"
]
}
},
"group": "[\"trigger\"]",
"defaults": {
"name": "When chat message received"
},
"iconData": {
"icon": "comments",
"type": "icon"
},
"displayName": "Chat Trigger",
"typeVersion": 1,
"nodeCategories": [
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"id": 9,
"name": "Core Nodes"
},
{
"id": 26,
"name": "Langchain"
}
]
}
]
},
"detail": {
"description": "Quick overview This workflow powers a chat-based shopping assistant using OpenAI for conversation, an HTTP product-catalog search API for live item data, and a checkout/order API to place orders with explicit user approval, then posts the final order status to a Slack channel. How it works 1. Triggers from an n8n Chat Trigger (or a manual test run) when a user submits a shopping request. 2. Uses OpenAI (GPT-4.1-mini) with short-term memory and function calling to query a product-catalog search API for real-time price and availability before recommending up to three items. 3. Parses the agent\u2019s structured JSON response into a reply, an optional product shortlist, and a purchase-intent signal with selected product and quantity. 4. If there is no purchase intent, returns the direct reply message; if there is purchase intent, pauses for the user to confirm the product selection via a resume webhook. 5. Pauses again for an explicit purchase approval via a second resume webhook, then submits the order to the store checkout API with the selected item, quantity, customer, payment method, and shipping details. 6. Waits for an asynchronous order-confirmation callback via a third resume webhook, then formats the order status and posts it to Slack. Setup 1. Add credentials for OpenAI, Slack, and HTTP Header Auth for both the product-catalog search API and the checkout/order API. 2. Update the configuration values for catalog and order base URLs, currency, customer ID, default shipping address, payment method ID, max budget, and the target Slack channel. 3. Copy the resume webhook URLs from the selection, approval, and order-confirmation wait steps and wire them into your chat UI buttons and your store/payment provider\u2019s order-status callback."
}
}