351 lines
12 KiB
JSON
351 lines
12 KiB
JSON
{
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"meta": {
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"instanceId": "6a5e68bcca67c4cdb3e0b698d01739aea084e1ec06e551db64aeff43d174cb23",
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"templateCredsSetupCompleted": true
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},
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"nodes": [
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{
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"id": "bc49829b-45f2-4910-9c37-907271982f14",
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"name": "Sticky Note3",
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"type": "n8n-nodes-base.stickyNote",
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"position": [
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-140,
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320
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],
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"parameters": {
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"width": 780,
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"height": 540,
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"content": "### 4. Do you need more details?\nFind a step-by-step guide in this tutorial\n\n[🎥 Watch My Tutorial](https://www.youtube.com/watch?v=kQ8dO_30SB0)"
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},
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"typeVersion": 1
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},
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{
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"id": "40c6e16a-3b4f-4e28-b0a1-7066e0efab5d",
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"name": "AI Agent",
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"type": "@n8n/n8n-nodes-langchain.agent",
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"position": [
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-460,
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-80
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],
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"parameters": {
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"text": "=Email Subject: {{ $json.subject }}\nEmail Body: \n{{ $json.text }}",
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"options": {
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"systemMessage": "=You are an assistant that processes emails related to inbound orders from Hermas.\n\nEach email has the subject line containing a purchase order reference (e.g., \"PO45231\").\nIn the email body, you will find:\n\nAn expected delivery date, typically in formats like 27/03/2025 or 2025-03-27.\n\nOne or more order lines, where each line contains:\n\nAn SKU (e.g., HERM-SHOE-001)\n\nA quantity (e.g., 120)\n\nYour goal is to extract the following fields:\n\npurchase_order: The PO number from the subject line (e.g., PO45231)\n\nexpected_delivery_date: In ISO format (e.g., 2025-03-27)\n\nlines: A list of objects with sku and quantity for each order line\n\nReturn your output strictly as a valid JSON object using the format below."
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},
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"promptType": "define",
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"hasOutputParser": true
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},
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"typeVersion": 1.8
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},
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{
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"id": "e9cb7bb1-40e7-463e-8b3f-417602338e5c",
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"name": "OpenAI Chat Model",
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"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
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"position": [
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-520,
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120
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],
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"parameters": {
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"model": {
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"__rl": true,
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"mode": "list",
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"value": "gpt-4o-mini"
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},
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"options": {}
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},
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"typeVersion": 1.2
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},
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{
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"id": "468bdb39-223f-4bae-8bdb-a72272ab57c3",
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"name": "Structured Output Parser",
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"type": "@n8n/n8n-nodes-langchain.outputParserStructured",
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"position": [
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-180,
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120
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],
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"parameters": {
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"jsonSchemaExample": "{\n \"purchase_order\": \"PO45231\",\n \"expected_delivery_date\": \"2025-03-27\",\n \"lines\": [\n { \"sku\": \"HERM-SHOE-001\", \"quantity\": 120 },\n { \"sku\": \"HERM-BAG-032\", \"quantity\": 45 },\n { \"sku\": \"HERM-WATCH-105\", \"quantity\": 30 },\n { \"sku\": \"HERM-SCARF-018\", \"quantity\": 80 }\n ]\n}\n"
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},
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"typeVersion": 1.2
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},
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{
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"id": "667a8d43-1ce5-4ec8-871a-26007356a89e",
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"name": "Sticky Note1",
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"type": "n8n-nodes-base.stickyNote",
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"position": [
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-1000,
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-460
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],
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"parameters": {
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"color": 7,
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"width": 380,
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"height": 720,
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"content": "### 1. Workflow Trigger with Gmail Trigger\nThe workflow is triggered by a new email received in your Gmail mailbox. \nIf the subject includes the string \"Inbound Order\" we proceed, if not we do nothing.\n\n#### How to setup?\n- **Gmail Trigger Node:** set up your Gmail API credentials\n[Learn more about the Gmail Trigger Node](https://docs.n8n.io/integrations/builtin/trigger-nodes/n8n-nodes-base.gmailtrigger)\n"
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},
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"typeVersion": 1
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},
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{
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"id": "e1e2d95a-9bbd-4bd5-92ec-7a4835db21a2",
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"name": "Sticky Note2",
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"type": "n8n-nodes-base.stickyNote",
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"position": [
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-600,
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-460
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],
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"parameters": {
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"color": 7,
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"width": 660,
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"height": 720,
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"content": "### 2. AI Agent equipped with the query tool\nThe email body and subject are sent to the AI agent for parsing. The results include the **PO Number**, **expected delivery date** and all the order lines with **SKU ID** and **order quantity**. Outputs are formatted by the code node to fit in a Google Sheet.\n\n#### How to setup?\n- **AI Agent with the Chat Model**:\n 1. Add a **chat model** with the required credentials *(Example: Open AI 4o-mini)*\n 2. Adapt the system prompt to the format of your emails\n [Learn more about the AI Agent Node](https://docs.n8n.io/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.agent)"
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},
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"typeVersion": 1
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},
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{
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"id": "53375c17-a36c-431e-9ba6-07a9a84fc4c9",
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"name": "Sticky Note4",
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"type": "n8n-nodes-base.stickyNote",
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"position": [
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80,
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-460
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],
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"parameters": {
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"color": 7,
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"width": 460,
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"height": 540,
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"content": "### 3. Store the orderlines in a Google Sheet\nThe table generated by the **code node** includes all the order lines with the **PO Number** and the **expected delivery date**. This **Google Sheet Node** loads the content in a Google Sheet.\n\n#### How to setup?\n- **Add Results in Google Sheets**:\n 1. Add your Google Sheet API credentials to access the Google Sheet file\n 2. Select the file using the list, an URL or an ID\n 3. Select the sheet in which the vocabulary list is stored\n 4. Create the columns: **PO_NUMBER, EXPECTED_DELIVERY DATE, SKU_ID, QUANTITY**\n [Learn more about the Google Sheet Node](https://docs.n8n.io/integrations/builtin/app-nodes/n8n-nodes-base.googlesheets)"
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},
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"typeVersion": 1
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},
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{
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"id": "776cfc0e-264b-44cc-b534-dc387b0c9fce",
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"name": "Store Purchase Order Lines",
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"type": "n8n-nodes-base.googleSheets",
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"position": [
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180,
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-80
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],
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"parameters": {
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"columns": {
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"value": {
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"SKU_ID": "={{ $json.sku }}",
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"QUANTITY": "={{ $json.quantity }}",
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"PO_NUMBER": "={{ $json.purchase_order }}",
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"EXPECTED_DELIVERY DATE": "={{ $json.expected_delivery_date }}"
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},
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"schema": [
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{
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"id": "PO_NUMBER",
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"type": "string",
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"display": true,
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"required": false,
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"displayName": "PO_NUMBER",
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"defaultMatch": false,
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"canBeUsedToMatch": true
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},
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{
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"id": "EXPECTED_DELIVERY DATE",
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"type": "string",
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"display": true,
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"required": false,
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"displayName": "EXPECTED_DELIVERY DATE",
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"defaultMatch": false,
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"canBeUsedToMatch": true
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},
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{
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"id": "SKU_ID",
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"type": "string",
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"display": true,
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"required": false,
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"displayName": "SKU_ID",
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"defaultMatch": false,
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"canBeUsedToMatch": true
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},
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{
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"id": "QUANTITY",
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"type": "string",
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"display": true,
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"required": false,
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"displayName": "QUANTITY",
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"defaultMatch": false,
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"canBeUsedToMatch": true
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}
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],
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"mappingMode": "defineBelow",
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"matchingColumns": [],
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"attemptToConvertTypes": false,
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"convertFieldsToString": false
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},
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"options": {},
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"operation": "append",
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"sheetName": {
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"__rl": true,
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"mode": "list",
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"value": "gid=0",
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"cachedResultUrl": "=",
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"cachedResultName": "="
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},
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"documentId": {
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"__rl": true,
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"mode": "list",
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"value": "1HnaJJ-DqzqgWJo2YwQDcgB6BgWiU6eMlnGvv4kapubg",
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"cachedResultUrl": "=",
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"cachedResultName": "="
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}
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},
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"notesInFlow": true,
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"typeVersion": 4.5
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},
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{
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"id": "d5c52625-fef2-47a9-b2a4-bf005d8b9e05",
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"name": "Email Received",
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"type": "n8n-nodes-base.gmailTrigger",
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"position": [
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-980,
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-80
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],
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"parameters": {
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"simple": false,
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"filters": {},
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"options": {},
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"pollTimes": {
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"item": [
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{
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"mode": "everyMinute"
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}
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]
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}
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},
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"typeVersion": 1.2
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},
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{
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"id": "6dc9e5cc-9ab3-469c-ad93-e0e7817ccbf7",
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"name": "Is PO?",
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"type": "n8n-nodes-base.if",
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"position": [
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-760,
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-80
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],
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"parameters": {
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"options": {},
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"conditions": {
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"options": {
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"version": 2,
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"leftValue": "",
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"caseSensitive": true,
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"typeValidation": "strict"
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},
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"combinator": "and",
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"conditions": [
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{
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"id": "f300ae2b-5de4-4efc-88ae-130a957588cb",
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"operator": {
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"type": "string",
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"operation": "contains"
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},
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"leftValue": "={{ $json.subject }}",
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"rightValue": "Inbound Order"
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}
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]
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}
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},
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"typeVersion": 2.2
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},
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{
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"id": "385db736-0867-46b9-9274-380e7c255fc4",
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"name": "Format Purchase Order Lines",
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"type": "n8n-nodes-base.code",
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"position": [
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-120,
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-80
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],
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"parameters": {
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"jsCode": "const {purchase_order, expected_delivery_date, lines} = $input.first().json.output;\n\nreturn lines.map( line => ({\n json: {\n purchase_order,\n expected_delivery_date,\n sku: line.sku,\n quantity: line.quantity\n }\n}))\n"
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},
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"typeVersion": 2
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},
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{
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"id": "b2e39591-70be-4d7f-a5d4-1505741d6310",
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"name": "Sticky Note",
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"type": "n8n-nodes-base.stickyNote",
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"position": [
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-1000,
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320
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],
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"parameters": {
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"width": 780,
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"height": 720,
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"content": "### Test the workflow with this email!\n\n#### How?\n1. Send this email to the Gmail box you set up in your credentials.\n2. Click on Test workflow\n\n### Email\n**Email Subject:** Inbound Order PO45231 – Expected Delivery on 2025-03-27\n\n**Email Body:** \nDear LogiGreen Team,\n\nPlease find below the details of the upcoming inbound order.\n\nPurchase Order: PO45231\nExpected Delivery Date: 27/03/2025\n\nOrder Lines:\n\nSKU: HERM-SHOE-001 — Qty: 120\n\nSKU: HERM-BAG-032 — Qty: 45\n\nSKU: HERM-WATCH-105 — Qty: 30\n\nSKU: HERM-SCARF-018 — Qty: 80\n\nLet us know if you need any additional details.\n\nBest regards,\nSophie Lambert\nAdmin Assistant – Hermas Logistics\n📞 +33 1 23 45 67 89 78 84\n✉️ sophie.lambert@hermas.com\n"
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},
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"typeVersion": 1
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}
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],
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"pinData": {},
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"connections": {
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"Is PO?": {
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"main": [
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[
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{
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"node": "AI Agent",
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"type": "main",
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"index": 0
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}
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]
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]
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},
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"AI Agent": {
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"main": [
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[
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{
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"node": "Format Purchase Order Lines",
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"type": "main",
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"index": 0
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}
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]
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]
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},
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"Email Received": {
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"main": [
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[
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{
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"node": "Is PO?",
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"type": "main",
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"index": 0
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}
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]
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]
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},
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"OpenAI Chat Model": {
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"ai_languageModel": [
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[
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{
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"node": "AI Agent",
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"type": "ai_languageModel",
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"index": 0
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}
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]
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]
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},
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"Structured Output Parser": {
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"ai_outputParser": [
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[
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{
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"node": "AI Agent",
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"type": "ai_outputParser",
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"index": 0
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}
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]
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]
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},
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"Format Purchase Order Lines": {
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"main": [
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[
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{
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"node": "Store Purchase Order Lines",
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"type": "main",
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"index": 0
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}
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]
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]
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}
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}
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} |