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Zhongwei Li
518
commands/n8n-builder.md
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518
commands/n8n-builder.md
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---
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description: Generate complete n8n workflow JSON files
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---
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# n8n Workflow Builder
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Generate production-ready n8n workflow JSON files.
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## Usage
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When the user requests an n8n workflow, analyze their requirements and create a complete, importable workflow JSON file.
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## Workflow Templates
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### 1. AI Email Responder
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```json
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{
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"name": "AI Email Auto-Responder",
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"nodes": [
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{
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"parameters": {
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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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"simple": true,
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"filters": {
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"labelIds": ["INBOX"]
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}
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},
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"id": "1",
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"name": "Gmail Trigger",
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"type": "n8n-nodes-base.gmailTrigger",
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"typeVersion": 1,
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"position": [250, 300]
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},
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{
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"parameters": {
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"model": "gpt-4",
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"messages": {
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"values": [
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{
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"content": "=Draft a professional response to this email:\n\nFrom: {{ $json.from }}\nSubject: {{ $json.subject }}\nBody: {{ $json.body }}\n\nWrite a helpful, friendly response."
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}
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]
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}
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},
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"id": "2",
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"name": "OpenAI",
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"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
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"typeVersion": 1,
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"position": [450, 300],
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"credentials": {
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"openAiApi": {
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"id": "1",
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"name": "OpenAI API"
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}
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}
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},
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{
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"parameters": {
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"sendTo": "={{ $('Gmail Trigger').item.json.from }}",
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"subject": "=Re: {{ $('Gmail Trigger').item.json.subject }}",
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"message": "={{ $json.output }}",
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"options": {}
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},
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"id": "3",
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"name": "Gmail Send",
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"type": "n8n-nodes-base.gmail",
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"typeVersion": 2,
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"position": [650, 300],
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"credentials": {
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"gmailOAuth2": {
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"id": "1",
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"name": "Gmail OAuth2"
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}
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}
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}
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],
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"connections": {
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"Gmail Trigger": {
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"main": [
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[
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{
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"node": "OpenAI",
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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": {
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"main": [
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[
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{
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"node": "Gmail Send",
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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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}
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```
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### 2. Data Processing Pipeline
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```json
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{
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"name": "CSV to Database with AI Enhancement",
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"nodes": [
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{
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"parameters": {
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"fileFormat": "csv",
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"options": {}
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},
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"id": "1",
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"name": "Read CSV",
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"type": "n8n-nodes-base.spreadsheetFile",
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"typeVersion": 2,
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"position": [250, 300]
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},
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{
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"parameters": {
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"batchSize": 10,
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"options": {}
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},
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"id": "2",
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"name": "Loop Over Items",
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"type": "n8n-nodes-base.splitInBatches",
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"typeVersion": 3,
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"position": [450, 300]
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},
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{
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"parameters": {
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"model": "gpt-4",
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"messages": {
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"values": [
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{
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"content": "=Enhance this data record with additional context:\n{{ JSON.stringify($json) }}"
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}
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]
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}
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},
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"id": "3",
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"name": "AI Enhancement",
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"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
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"typeVersion": 1,
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"position": [650, 300]
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},
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{
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"parameters": {
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"operation": "insert",
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"schema": {
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"__rl": true,
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"value": "public",
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"mode": "list"
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},
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"table": {
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"__rl": true,
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"value": "records",
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"mode": "list"
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},
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"columns": {
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"mappingMode": "autoMapInputData",
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"value": {}
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},
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"options": {}
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},
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"id": "4",
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"name": "PostgreSQL Insert",
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"type": "n8n-nodes-base.postgres",
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"typeVersion": 2.4,
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"position": [850, 300]
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}
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],
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"connections": {
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"Read CSV": {
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"main": [
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[
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{
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"node": "Loop Over Items",
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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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"Loop Over Items": {
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"main": [
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[
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{
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"node": "AI Enhancement",
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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 Enhancement": {
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"main": [
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[
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{
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"node": "PostgreSQL Insert",
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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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}
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```
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### 3. Content Pipeline
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```json
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{
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"name": "RSS to Social Media with AI",
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"nodes": [
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{
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"parameters": {
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"url": "https://example.com/feed.xml",
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"options": {}
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},
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"id": "1",
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"name": "RSS Feed",
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"type": "n8n-nodes-base.rssFeedRead",
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"typeVersion": 1,
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"position": [250, 300]
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},
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{
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"parameters": {
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"conditions": {
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"dateTime": [
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{
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"value1": "={{ $json.pubDate }}",
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"operation": "after",
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"value2": "={{ $now.minus({ hours: 24 }) }}"
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}
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]
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}
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},
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"id": "2",
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"name": "Filter New Items",
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"type": "n8n-nodes-base.filter",
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"typeVersion": 2,
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"position": [450, 300]
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},
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{
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"parameters": {
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"model": "gpt-4",
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"messages": {
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"values": [
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{
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"content": "=Create a compelling social media post from this article:\n\nTitle: {{ $json.title }}\nSummary: {{ $json.contentSnippet }}\n\nMake it engaging and include relevant hashtags."
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}
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]
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}
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},
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"id": "3",
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"name": "Generate Post",
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"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
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"typeVersion": 1,
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"position": [650, 300]
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},
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{
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"parameters": {
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"text": "={{ $json.output }}",
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"additionalFields": {}
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},
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"id": "4",
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"name": "Twitter Post",
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"type": "n8n-nodes-base.twitter",
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"typeVersion": 2,
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"position": [850, 300]
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}
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],
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"connections": {
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"RSS Feed": {
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"main": [
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[
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{
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"node": "Filter New Items",
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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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"Filter New Items": {
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"main": [
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[
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{
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"node": "Generate Post",
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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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"Generate Post": {
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"main": [
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[
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{
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"node": "Twitter Post",
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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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}
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```
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### 4. Lead Qualification
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```json
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{
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"name": "Lead Scoring and Routing",
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"nodes": [
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{
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"parameters": {
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"path": "lead-webhook",
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"options": {}
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},
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"id": "1",
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"name": "Webhook",
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"type": "n8n-nodes-base.webhook",
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"typeVersion": 2,
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"position": [250, 300]
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},
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{
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"parameters": {
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"model": "gpt-4",
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"messages": {
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"values": [
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{
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"content": "=Score this lead from 0-100 based on fit:\n\nCompany: {{ $json.company }}\nRole: {{ $json.role }}\nIndustry: {{ $json.industry }}\nBudget: {{ $json.budget }}\n\nProvide score and reasoning."
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}
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]
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}
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},
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"id": "2",
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"name": "AI Score",
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"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
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"typeVersion": 1,
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"position": [450, 300]
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},
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{
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"parameters": {
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"conditions": {
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"number": [
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{
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"value1": "={{ $json.score }}",
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"operation": "larger",
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"value2": 70
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}
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]
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}
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},
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"id": "3",
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"name": "IF High Score",
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"type": "n8n-nodes-base.if",
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"typeVersion": 2,
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"position": [650, 300]
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},
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{
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"parameters": {
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"resource": "deal",
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"operation": "create"
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},
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"id": "4",
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"name": "Create CRM Deal",
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"type": "n8n-nodes-base.hubspot",
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"typeVersion": 2,
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"position": [850, 250]
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},
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{
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"parameters": {
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"resource": "email",
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"operation": "send",
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"subject": "New Lead Follow Up",
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"message": "={{ $json.reasoning }}"
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},
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"id": "5",
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"name": "Nurture Email",
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"type": "n8n-nodes-base.gmail",
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"typeVersion": 2,
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"position": [850, 350]
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}
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],
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"connections": {
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"Webhook": {
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"main": [
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[
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{
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"node": "AI Score",
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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 Score": {
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"main": [
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[
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{
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"node": "IF High Score",
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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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"IF High Score": {
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"main": [
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[
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{
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"node": "Create CRM Deal",
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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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"node": "Nurture Email",
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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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}
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```
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## Features
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- Complex branching logic
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- Loops and iterations
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- Error handling and retries
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- Custom code nodes
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- 200+ integrations
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- Self-hostable
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- AI model integration
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- Database operations
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- API calls and webhooks
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## Best Practices
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1. **Always add error handling** - Use error workflows or try-catch nodes
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2. **Test with small datasets first** - Validate before processing large volumes
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3. **Use environment variables for secrets** - Never hardcode API keys
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4. **Implement logging for debugging** - Add notes or database logging
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5. **Version control your workflows** - Export and commit to git
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6. **Monitor resource usage** - Watch execution times and API costs
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7. **Use descriptive node names** - Make workflows self-documenting
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8. **Implement rate limiting** - Respect API limits with Wait nodes
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9. **Batch processing for scale** - Use Split in Batches for large datasets
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10. **Regular backups** - Export workflows regularly
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## Output Format
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When generating a workflow, provide:
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1. **Workflow Name** - Clear, descriptive name
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2. **Architecture Diagram** - Visual flow of nodes
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3. **Complete JSON** - Importable workflow file
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4. **Setup Instructions** - Credentials, settings needed
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5. **Testing Steps** - How to validate the workflow
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6. **Deployment Notes** - Self-hosted vs cloud considerations
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7. **Cost Estimation** - Expected API and resource costs
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## Example Response
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```markdown
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# Workflow: AI Customer Support Automation
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## Architecture
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```
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Ticket Created → Classify (AI) → Route by Priority → Draft Response (AI) → Human Review → Send
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```
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## Nodes
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1. Webhook trigger for new tickets
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2. OpenAI classification
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3. IF node for routing
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4. OpenAI response generation
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5. Slack notification for review
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6. Email send on approval
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## Setup
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1. Create webhook in your ticketing system
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2. Add OpenAI API credentials
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3. Configure Slack webhook
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4. Set up email credentials
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5. Test with sample ticket
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## JSON
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||||
[Complete importable JSON here]
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## Testing
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- Send test ticket through webhook
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- Verify classification accuracy
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- Check routing logic
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- Review AI-generated responses
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- Test Slack notifications
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## Cost Estimate
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- ~$0.01 per ticket (GPT-4 usage)
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- Self-hosted n8n: Free (Docker)
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- Cloud n8n: $20/month (standard plan)
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```
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This workflow builder helps users create production-ready n8n automations with AI integration, error handling, and best practices built in.
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Reference in New Issue
Block a user