This workflow follows the Chainllm → HTTP Request recipe pattern — see all workflows that pair these two integrations.
The workflow JSON
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{
"nodes": [
{
"id": "79849bb5-00a4-42e6-92c4-b06c7a20eb3e",
"name": "OpenAI Chat Model",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
1580,
340
],
"parameters": {
"model": "gpt-4-turbo-preview",
"options": {
"temperature": 0,
"responseFormat": "json_object"
}
},
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "85df0106-1f78-4412-8751-b84d417c8bf9",
"name": "Convert education to HTML",
"type": "n8n-nodes-base.code",
"position": [
2420,
180
],
"parameters": {
"mode": "runOnceForEachItem",
"jsCode": "function convertToHTML(list) {\n let html = '';\n\n list.forEach((education, index) => {\n if (index > 0) {\n html += '<br /><br />'; // Adiciona uma nova linha se n\u00e3o for o primeiro item\n }\n html += `<b>Institui\u00e7\u00e3o:</b> ${education.institution}<br />\n<b>Ano de in\u00edcio:</b> ${education.start_year}<br />\n<b>Curso:</b> ${education.degree}`;\n });\n\n return html;\n}\n\n// Assumindo que payload j\u00e1 est\u00e1 definido\nconst payload = $input.item.json.education;\n\nconst htmlOutput = convertToHTML(payload);\nreturn {\n htmlOutput\n};"
},
"typeVersion": 2
},
{
"id": "da4fc45d-712f-4171-b72a-66b74b4d8e05",
"name": "Auto-fixing Output Parser",
"type": "@n8n/n8n-nodes-langchain.outputParserAutofixing",
"position": [
1820,
340
],
"parameters": {},
"typeVersion": 1
},
{
"id": "225a7513-6fd4-4672-9b40-b10b00f121a7",
"name": "OpenAI Chat Model1",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
1740,
520
],
"parameters": {
"options": {
"temperature": 0
}
},
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "0606c99d-a080-4277-b071-1bc0c93bb2e3",
"name": "Structured Output Parser",
"type": "@n8n/n8n-nodes-langchain.outputParserStructured",
"position": [
1960,
520
],
"parameters": {
"jsonSchema": "{\n \"type\": \"object\",\n \"properties\": {\n \"personal_info\": {\n \"type\": \"object\",\n \"properties\": {\n \"name\": { \"type\": \"string\" },\n \"address\": { \"type\": \"string\" },\n \"email\": { \"type\": \"string\", \"format\": \"email\" },\n \"github\": { \"type\": \"string\"},\n \"linkedin\": { \"type\": \"string\" }\n }\n },\n \"employment_history\": {\n \"type\": \"array\",\n \"items\": {\n \"type\": \"object\",\n \"properties\": {\n \"position\": { \"type\": \"string\" },\n \"company\": { \"type\": \"string\" },\n \"duration\": { \"type\": \"string\" },\n \"responsibilities\": {\n \"type\": \"array\",\n \"items\": { \"type\": \"string\" }\n }\n }\n }\n },\n \"education\": {\n \"type\": \"array\",\n \"items\": {\n \"type\": \"object\",\n \"properties\": {\n \"institution\": { \"type\": \"string\" },\n \"start_year\": { \"type\": \"integer\" },\n \"degree\": { \"type\": \"string\" }\n }\n }\n },\n \"projects\": {\n \"type\": \"array\",\n \"items\": {\n \"type\": \"object\",\n \"properties\": {\n \"name\": { \"type\": \"string\" },\n \"year\": { \"type\": \"integer\" },\n \"description\": { \"type\": \"string\" },\n \"technologies\": {\n \"type\": \"array\",\n \"items\": { \"type\": \"string\" }\n }\n }\n }\n },\n \"volunteering\": {\n \"type\": \"array\",\n \"items\": {\n \"type\": \"object\",\n \"properties\": {\n \"activity\": { \"type\": \"string\" },\n \"location\": { \"type\": \"string\" },\n \"date\": { \"type\": \"string\" },\n \"description\": { \"type\": \"string\" }\n }\n }\n },\n \"programming_languages\": {\n \"type\": \"object\",\n \"properties\": {\n \"languages\": {\n \"type\": \"array\",\n \"items\": { \"type\": \"string\" }\n },\n \"tools\": {\n \"type\": \"array\",\n \"items\": { \"type\": \"string\" }\n },\n \"methodologies\": {\n \"type\": \"array\",\n \"items\": { \"type\": \"string\" }\n }\n }\n },\n \"foreign_languages\": {\n \"type\": \"array\",\n \"items\": {\n \"type\": \"object\",\n \"properties\": {\n \"language\": { \"type\": \"string\" },\n \"level\": { \"type\": \"string\" }\n }\n }\n }\n }\n}\n"
},
"typeVersion": 1
},
{
"id": "027975cd-768a-4048-858d-9060f48ab622",
"name": "Convert employment history to HTML",
"type": "n8n-nodes-base.code",
"position": [
2420,
-20
],
"parameters": {
"mode": "runOnceForEachItem",
"jsCode": "function convertToHTML(list) {\n let html = '';\n\n list.forEach((item, index) => {\n if (index > 0) {\n html += '<br />'; // Adiciona uma nova linha se n\u00e3o for o primeiro item\n }\n html += `<b>Cargo:</b> ${item.position}\n<b>Empresa:</b> ${item.company}\n<br />\n<b>Dura\u00e7\u00e3o:</b> ${item.duration}\n<br />\n<b>Responsabilidades:</b>\n`;\n\n item.responsibilities.forEach((responsibility, i) => {\n html += `- ${responsibility}`;\n if (i < item.responsibilities.length - 1 || index < list.length - 1) {\n html += '<br />'; // Adiciona nova linha se n\u00e3o for a \u00faltima responsabilidade do \u00faltimo item\n }\n });\n });\n\n return html;\n}\n\n// Assumindo que payload j\u00e1 est\u00e1 definido\nconst payload = $input.item.json.employment_history;\n\nconst htmlOutput = convertToHTML(payload);\nreturn {\n htmlOutput\n};"
},
"typeVersion": 2
},
{
"id": "823a241d-1c68-40a9-8f2c-f1bdfaab7603",
"name": "Convert projects to HTML",
"type": "n8n-nodes-base.code",
"position": [
2420,
380
],
"parameters": {
"mode": "runOnceForEachItem",
"jsCode": "function convertToHTML(list) {\n let html = '';\n\n list.forEach((project, index) => {\n if (index > 0) {\n html += '<br />'; // Adiciona uma nova linha se n\u00e3o for o primeiro projeto\n }\n html += `<b>Nome:</b> ${project.name}<br />\n<b>Ano:</b> ${project.year}<br />\n<b>Descri\u00e7\u00e3o:</b> ${project.description}<br /><br />\n<b>Tecnologias:</b>\n<br />`;\n\n project.technologies.forEach((technology, i) => {\n html += `- ${technology}`;\n if (i < project.technologies.length - 1 || index < list.length - 1) {\n html += '<br />'; // Adiciona nova linha se n\u00e3o for a \u00faltima tecnologia do \u00faltimo projeto\n }\n });\n });\n\n return html;\n}\n\n// Assumindo que payload j\u00e1 est\u00e1 definido\nconst payload = $input.item.json.projects;\n\nconst htmlOutput = convertToHTML(payload);\nreturn {\n htmlOutput\n};\n"
},
"typeVersion": 2
},
{
"id": "a12eb0e1-1cb9-4b83-a1ec-42dd8214f6bc",
"name": "Convert volunteering to HTML",
"type": "n8n-nodes-base.code",
"position": [
2420,
580
],
"parameters": {
"mode": "runOnceForEachItem",
"jsCode": "function convertToHTML(list) {\n let html = '';\n\n list.forEach((event, index) => {\n if (index > 0) {\n html += '<br />'; // Adiciona uma nova linha se n\u00e3o for o primeiro evento de voluntariado\n }\n html += `<b>Atividade:</b> ${event.activity}<br />\n<b>Local:</b> ${event.location}<br />\n<b>Data:</b> ${event.date}<br />\n<b>Descri\u00e7\u00e3o:</b> ${event.description}<br />`;\n });\n\n return html;\n}\n\n// Assumindo que payload j\u00e1 est\u00e1 definido\nconst payload = $input.item.json.volunteering;\n\nconst htmlOutput = convertToHTML(payload);\nreturn {\n htmlOutput\n};\n"
},
"typeVersion": 2
},
{
"id": "70b67b80-d22d-4eea-8c97-3d2cb2b9bbfc",
"name": "Telegram trigger",
"type": "n8n-nodes-base.telegramTrigger",
"position": [
360,
340
],
"parameters": {
"updates": [
"message"
],
"additionalFields": {}
},
"credentials": {
"telegramApi": {
"name": "<your credential>"
}
},
"typeVersion": 1.1
},
{
"id": "21bead1d-0665-44d5-b623-b0403c9abd6c",
"name": "Auth",
"type": "n8n-nodes-base.if",
"position": [
600,
340
],
"parameters": {
"options": {},
"conditions": {
"options": {
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "7ca4b4c3-e23b-4896-a823-efc85c419467",
"operator": {
"type": "number",
"operation": "equals"
},
"leftValue": "={{ $json.message.chat.id }}",
"rightValue": 0
}
]
}
},
"typeVersion": 2
},
{
"id": "de76d6ec-3b0e-44e0-943d-55547aac2e46",
"name": "No operation (unauthorized)",
"type": "n8n-nodes-base.noOp",
"position": [
860,
520
],
"parameters": {},
"typeVersion": 1
},
{
"id": "439f5e2c-be7d-486b-a1f1-13b09f77c2c8",
"name": "Check if start message",
"type": "n8n-nodes-base.if",
"position": [
860,
220
],
"parameters": {
"options": {},
"conditions": {
"options": {
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "1031f14f-9793-488d-bb6b-a021f943a399",
"operator": {
"type": "string",
"operation": "notEquals"
},
"leftValue": "={{ $json.message.text }}",
"rightValue": "/start"
}
]
}
},
"typeVersion": 2
},
{
"id": "af5f5622-c338-40c0-af72-90e124ed7ce1",
"name": "No operation (start message)",
"type": "n8n-nodes-base.noOp",
"position": [
1120,
360
],
"parameters": {},
"typeVersion": 1
},
{
"id": "2efae11a-376b-44aa-ab91-9b3dea82ede0",
"name": "Get file",
"type": "n8n-nodes-base.telegram",
"position": [
1120,
120
],
"parameters": {
"fileId": "={{ $json.message.document.file_id }}",
"resource": "file"
},
"credentials": {
"telegramApi": {
"name": "<your credential>"
}
},
"typeVersion": 1.1
},
{
"id": "88fd1002-ad2c-445f-92d4-11b571db3788",
"name": "Extract text from PDF",
"type": "n8n-nodes-base.extractFromFile",
"position": [
1380,
120
],
"parameters": {
"options": {},
"operation": "pdf"
},
"typeVersion": 1
},
{
"id": "9dfc204b-c567-418a-93a3-9b72cf534a8c",
"name": "Set parsed fileds",
"type": "n8n-nodes-base.set",
"position": [
2040,
120
],
"parameters": {
"options": {}
},
"typeVersion": 3.2
},
{
"id": "314c771a-5ff2-484f-823b-0eab88f43ea3",
"name": "Personal info",
"type": "n8n-nodes-base.set",
"position": [
2420,
-380
],
"parameters": {
"fields": {
"values": [
{
"name": "personal_info",
"stringValue": "=<b><u>Informa\u00e7\u00f5es pessoais</u></b>\n<br /><br />\n<b>Nome:</b> {{ $json.personal_info.name }}\n<br />\n<b>Endere\u00e7o:</b> {{ $json.personal_info.address }}\n<br />\n<b>E-mail:</b> {{ $json.personal_info.email }}\n<br />\n<b>GitHub:</b> {{ $json.personal_info.github }}\n<br />"
}
]
},
"include": "none",
"options": {}
},
"typeVersion": 3.2
},
{
"id": "be6b32e8-6000-4235-a723-0e22828ead45",
"name": "Technologies",
"type": "n8n-nodes-base.set",
"position": [
2420,
-200
],
"parameters": {
"fields": {
"values": [
{
"name": "technologies",
"stringValue": "=<b><u>Tecnologias</u></b>\n<br /><br />\n<b>Linguagens de programa\u00e7\u00e3o:</b> {{ $json.programming_languages.languages.join(', ') }}\n<br />\n<b>Ferramentas:</b> {{ $json.programming_languages.tools.join(', ') }}\n<br />\n<b>Metodologias:</b> {{ $json.programming_languages.methodologies.join(', ') }}\n<br />"
}
]
},
"include": "none",
"options": {}
},
"typeVersion": 3.2
},
{
"id": "ab726d61-84b8-4af7-a195-33e1add89153",
"name": "Employment history",
"type": "n8n-nodes-base.set",
"position": [
2640,
-20
],
"parameters": {
"fields": {
"values": [
{
"name": "employment_history",
"stringValue": "=<b><u>Hist\u00f3rico profissional</u></b>\n<br /><br />\n{{ $json[\"htmlOutput\"] }}"
}
]
},
"include": "none",
"options": {}
},
"typeVersion": 3.2
},
{
"id": "692f9555-6102-4d3c-b0a1-868e27e3c343",
"name": "Education",
"type": "n8n-nodes-base.set",
"position": [
2640,
180
],
"parameters": {
"fields": {
"values": [
{
"name": "education",
"stringValue": "=<b><u>Forma\u00e7\u00e3o</u></b>\n<br /><br />\n{{ $json[\"htmlOutput\"] }}"
}
]
},
"include": "none",
"options": {}
},
"typeVersion": 3.2
},
{
"id": "258728f2-1f03-4786-8197-feb9f1bc4dfe",
"name": "Projects",
"type": "n8n-nodes-base.set",
"position": [
2640,
380
],
"parameters": {
"fields": {
"values": [
{
"name": "projects",
"stringValue": "=<b><u>Projetos</u></b>\n<br /><br />\n{{ $json[\"htmlOutput\"] }}"
}
]
},
"include": "none",
"options": {}
},
"typeVersion": 3.2
},
{
"id": "3c819ce4-235a-4b12-a396-d33dca9f80da",
"name": "Volunteering",
"type": "n8n-nodes-base.set",
"position": [
2640,
580
],
"parameters": {
"fields": {
"values": [
{
"name": "volunteering",
"stringValue": "=<b><u>Voluntariado</u></b>\n<br /><br />\n{{ $json[\"htmlOutput\"] }}"
}
]
},
"include": "none",
"options": {}
},
"typeVersion": 3.2
},
{
"id": "41bd7506-7330-4c25-8b43-aa3c836736fc",
"name": "Merge education and employment history",
"type": "n8n-nodes-base.merge",
"position": [
2880,
100
],
"parameters": {
"mode": "combine",
"options": {},
"combinationMode": "multiplex"
},
"typeVersion": 2.1
},
{
"id": "d788da36-360b-4009-82ad-2f206fad8e53",
"name": "Merge projects and volunteering",
"type": "n8n-nodes-base.merge",
"position": [
2880,
500
],
"parameters": {
"mode": "combine",
"options": {},
"combinationMode": "multiplex"
},
"typeVersion": 2.1
},
{
"id": "57c20e19-3d84-41c0-a415-1d55cb031da1",
"name": "Merge personal info and technologies",
"type": "n8n-nodes-base.merge",
"position": [
3140,
-160
],
"parameters": {
"mode": "combine",
"options": {},
"combinationMode": "multiplex"
},
"typeVersion": 2.1
},
{
"id": "f12be010-8375-4ff7-ba8e-9c2c870f648b",
"name": "Merge all",
"type": "n8n-nodes-base.merge",
"position": [
3400,
200
],
"parameters": {
"mode": "combine",
"options": {},
"combinationMode": "multiplex"
},
"typeVersion": 2.1
},
{
"id": "d6428167-2c75-42a5-a905-7590ff1d6a25",
"name": "Set final data",
"type": "n8n-nodes-base.set",
"position": [
3620,
200
],
"parameters": {
"fields": {
"values": [
{
"name": "output",
"stringValue": "={{ $json.personal_info }}\n<br /><br />\n{{ $json.employment_history }}\n<br /><br />\n{{ $json.education }}\n<br /><br />\n{{ $json.projects }}\n<br /><br />\n{{ $json.volunteering }}\n<br /><br />\n{{ $json.technologies }}"
}
]
},
"include": "none",
"options": {}
},
"typeVersion": 3.2
},
{
"id": "9ea13c62-2e09-4b37-b889-66edaef1fcf1",
"name": "Convert raw to base64",
"type": "n8n-nodes-base.code",
"position": [
3840,
200
],
"parameters": {
"mode": "runOnceForEachItem",
"jsCode": "const encoded = Buffer.from($json.output).toString('base64');\n\nreturn { encoded };"
},
"typeVersion": 2
},
{
"id": "c4474fa1-b1b5-432f-b30e-100201c9ec7c",
"name": "Convert to HTML",
"type": "n8n-nodes-base.convertToFile",
"position": [
4060,
200
],
"parameters": {
"options": {
"fileName": "index.html",
"mimeType": "text/html"
},
"operation": "toBinary",
"sourceProperty": "encoded"
},
"typeVersion": 1.1
},
{
"id": "3c4d2010-1bdc-4f01-bb1a-bd0128017787",
"name": "Generate plain PDF doc",
"type": "n8n-nodes-base.httpRequest",
"position": [
4340,
200
],
"parameters": {
"url": "http://gotenberg:3000/forms/chromium/convert/html",
"method": "POST",
"options": {
"response": {
"response": {
"responseFormat": "file"
}
}
},
"sendBody": true,
"contentType": "multipart-form-data",
"bodyParameters": {
"parameters": [
{
"name": "files",
"parameterType": "formBinaryData",
"inputDataFieldName": "data"
}
]
}
},
"typeVersion": 4.1
},
{
"id": "2b3cd55f-21a3-4c14-905f-82b158aa3fd0",
"name": "Send PDF to the user",
"type": "n8n-nodes-base.telegram",
"position": [
4640,
200
],
"parameters": {
"chatId": "={{ $('Telegram trigger').item.json[\"message\"][\"chat\"][\"id\"] }}",
"operation": "sendDocument",
"binaryData": true,
"additionalFields": {
"fileName": "={{ $('Set parsed fileds').item.json[\"personal_info\"][\"name\"].toLowerCase().replace(' ', '-') }}.pdf"
}
},
"credentials": {
"telegramApi": {
"name": "<your credential>"
}
},
"typeVersion": 1.1
},
{
"id": "54fe1d2d-eb9d-4fe1-883f-1826e27ac873",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
540,
180
],
"parameters": {
"width": 226.21234567901217,
"height": 312.917333333334,
"content": "### Adicione o chat ID\nLembre-se de definir seu ID real para acionar a automa\u00e7\u00e3o pelo Telegram."
},
"typeVersion": 1
},
{
"id": "b193a904-260b-4d45-8a66-e3cb46fc7ce4",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
800,
83.43940740740783
],
"parameters": {
"width": 229.64938271604922,
"height": 293.54824691358016,
"content": "### Ignorar mensagem inicial\nO fluxo ignora a mensagem inicial `/start` enviada ao bot."
},
"typeVersion": 1
},
{
"id": "d5c95d8f-b699-4a8e-9460-a4f5856b5e6f",
"name": "Sticky Note2",
"type": "n8n-nodes-base.stickyNote",
"position": [
1066,
-20
],
"parameters": {
"width": 211.00246913580224,
"height": 302.41975308642,
"content": "### Baixar arquivo do curr\u00edculo\nCom base no file ID, o n\u00f3 realiza o download do arquivo enviado pelo usu\u00e1rio."
},
"typeVersion": 1
},
{
"id": "2de0751d-8e11-457e-8c38-a6dcca59190c",
"name": "Sticky Note4",
"type": "n8n-nodes-base.stickyNote",
"position": [
1320,
-20
],
"parameters": {
"width": 217.87654320987633,
"height": 302.41975308642,
"content": "### Extrair texto do PDF\nO n\u00f3 extrai o texto leg\u00edvel do PDF."
},
"typeVersion": 1
},
{
"id": "4b9ccab8-ff6c-408f-93fe-f148034860a0",
"name": "Sticky Note5",
"type": "n8n-nodes-base.stickyNote",
"position": [
1580,
-20
],
"parameters": {
"width": 410.9479506172837,
"height": 302.41975308642,
"content": "### Fazer parse dos dados do curr\u00edculo\nCria dados estruturados a partir do texto extra\u00eddo do curr\u00edculo. A chain usa o modelo `gpt-4-turbo-preview` da OpenAI e o modo de resposta em JSON. **Ajuste o JSON schema no output parser conforme suas necessidades.**"
},
"typeVersion": 1
},
{
"id": "bfb1d382-90fa-4bff-8c38-04e53bcf5f58",
"name": "Parse resume data",
"type": "@n8n/n8n-nodes-langchain.chainLlm",
"position": [
1660,
120
],
"parameters": {
"prompt": "={{ $json.text }}",
"messages": {
"messageValues": [
{
"message": "Sua tarefa \u00e9 extrair todos os dados necess\u00e1rios, como nome, sobrenome, experi\u00eancia, tecnologias dominadas etc., do texto do curr\u00edculo fornecido e retornar em um formato JSON bem unificado. N\u00e3o invente informa\u00e7\u00f5es."
}
]
}
},
"typeVersion": 1.3
},
{
"id": "7e8eb10a-f21c-4a9c-90b1-b71537b78356",
"name": "Merge other data",
"type": "n8n-nodes-base.merge",
"position": [
3140,
340
],
"parameters": {
"mode": "combine",
"options": {},
"combinationMode": "multiplex"
},
"typeVersion": 2.1
},
{
"id": "7c4398de-7b4d-4095-b38f-eaf099d2991b",
"name": "Sticky Note6",
"type": "n8n-nodes-base.stickyNote",
"position": [
2340,
-491.4074074074074
],
"parameters": {
"width": 1196.8442469135782,
"height": 1260.345679012346,
"content": "### Formatar HTML\nFormate o HTML para cada se\u00e7\u00e3o do curr\u00edculo (hist\u00f3rico profissional, projetos etc.)."
},
"typeVersion": 1
},
{
"id": "9de2f504-6ff0-4b00-8e0d-436c789b4e23",
"name": "Sticky Note7",
"type": "n8n-nodes-base.stickyNote",
"position": [
3580,
40
],
"parameters": {
"width": 638.6516543209876,
"height": 322.5837037037037,
"content": "### Criar arquivo HTML\nA partir da sa\u00edda formatada, crie o arquivo `index.html` para executar a convers\u00e3o em PDF."
},
"typeVersion": 1
},
{
"id": "11abdff5-377e-490d-9136-15c24ff6a05e",
"name": "Sticky Note8",
"type": "n8n-nodes-base.stickyNote",
"position": [
4260,
39.83604938271645
],
"parameters": {
"color": 3,
"width": 262.0096790123454,
"height": 322.5837037037035,
"content": "### Converter arquivo para PDF\nA partir do `index.html`, gere o PDF usando o [Gotenberg](https://gotenberg.dev/). Se voc\u00ea n\u00e3o conhece esse software, d\u00ea uma olhada no [meu tutorial no YouTube](https://youtu.be/bo15xdjXf1Y?si=hFZMTfjzfSOLOLPK)."
},
"typeVersion": 1
},
{
"id": "73fb81d0-5218-4311-aaec-7fa259d8cbd3",
"name": "Sticky Note9",
"type": "n8n-nodes-base.stickyNote",
"position": [
4560,
40
],
"parameters": {
"width": 262.0096790123454,
"height": 322.5837037037035,
"content": "### Enviar arquivo PDF ao usu\u00e1rio\nEntregue o PDF convertido ao usu\u00e1rio do Telegram (com base no chat ID)."
},
"typeVersion": 1
},
{
"id": "bb5fa375-4cc9-4559-a014-7b618d6c5f32",
"name": "Sticky Note10",
"type": "n8n-nodes-base.stickyNote",
"position": [
-280,
128
],
"parameters": {
"width": 432.69769500990674,
"height": 364.2150828344463,
"content": "## \u26a0\ufe0f Aviso\n\nEste \u00e9 o fluxo *extrator de curr\u00edculos* que tive o prazer de apresentar no [n8n community hangout](https://youtu.be/eZacuxrhCuo?si=KkJQrgQuvLxj-6FM&t=1701\n) em 7 de mar\u00e7o de 2024.\n\n1. Lembre-se de adicionar suas credenciais e configurar os n\u00f3s.\n2. Este n\u00f3 requer o [Gotenberg](https://gotenberg.dev/) instalado para a gera\u00e7\u00e3o de PDF. Se voc\u00ea n\u00e3o conhece esse software, d\u00ea uma olhada no [meu tutorial no YouTube](https://youtu.be/bo15xdjXf1Y?si=hFZMTfjzfSOLOLPK). Se n\u00e3o quiser self-hostear o Gotenberg, use outro provedor de gera\u00e7\u00e3o de PDF (PDFMonkey, ApiTemplate ou similar).\n3. Se voc\u00ea gostou deste fluxo, inscreva-se no [meu canal do YouTube](https://www.youtube.com/@workfloows) e/ou na [minha newsletter](https://workfloows.com/).\n\n**Obrigado pelo seu apoio!**"
},
"typeVersion": 1
}
],
"connections": {
"Auth": {
"main": [
[
{
"node": "Check if start message",
"type": "main",
"index": 0
}
],
[
{
"node": "No operation (unauthorized)",
"type": "main",
"index": 0
}
]
]
},
"Get file": {
"main": [
[
{
"node": "Extract text from PDF",
"type": "main",
"index": 0
}
]
]
},
"Projects": {
"main": [
[
{
"node": "Merge projects and volunteering",
"type": "main",
"index": 0
}
]
]
},
"Education": {
"main": [
[
{
"node": "Merge education and employment history",
"type": "main",
"index": 1
}
]
]
},
"Merge all": {
"main": [
[
{
"node": "Set final data",
"type": "main",
"index": 0
}
]
]
},
"Technologies": {
"main": [
[
{
"node": "Merge personal info and technologies",
"type": "main",
"index": 1
}
]
]
},
"Volunteering": {
"main": [
[
{
"node": "Merge projects and volunteering",
"type": "main",
"index": 1
}
]
]
},
"Personal info": {
"main": [
[
{
"node": "Merge personal info and technologies",
"type": "main",
"index": 0
}
]
]
},
"Set final data": {
"main": [
[
{
"node": "Convert raw to base64",
"type": "main",
"index": 0
}
]
]
},
"Convert to HTML": {
"main": [
[
{
"node": "Generate plain PDF doc",
"type": "main",
"index": 0
}
]
]
},
"Merge other data": {
"main": [
[
{
"node": "Merge all",
"type": "main",
"index": 1
}
]
]
},
"Telegram trigger": {
"main": [
[
{
"node": "Auth",
"type": "main",
"index": 0
}
]
]
},
"OpenAI Chat Model": {
"ai_languageModel": [
[
{
"node": "Parse resume data",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Parse resume data": {
"main": [
[
{
"node": "Set parsed fileds",
"type": "main",
"index": 0
}
]
]
},
"Set parsed fileds": {
"main": [
[
{
"node": "Convert employment history to HTML",
"type": "main",
"index": 0
},
{
"node": "Convert education to HTML",
"type": "main",
"index": 0
},
{
"node": "Convert projects to HTML",
"type": "main",
"index": 0
},
{
"node": "Personal info",
"type": "main",
"index": 0
},
{
"node": "Convert volunteering to HTML",
"type": "main",
"index": 0
},
{
"node": "Technologies",
"type": "main",
"index": 0
}
]
]
},
"Employment history": {
"main": [
[
{
"node": "Merge education and employment history",
"type": "main",
"index": 0
}
]
]
},
"OpenAI Chat Model1": {
"ai_languageModel": [
[
{
"node": "Auto-fixing Output Parser",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Convert raw to base64": {
"main": [
[
{
"node": "Convert to HTML",
"type": "main",
"index": 0
}
]
]
},
"Extract text from PDF": {
"main": [
[
{
"node": "Parse resume data",
"type": "main",
"index": 0
}
]
]
},
"Check if start message": {
"main": [
[
{
"node": "Get file",
"type": "main",
"index": 0
}
],
[
{
"node": "No operation (start message)",
"type": "main",
"index": 0
}
]
]
},
"Generate plain PDF doc": {
"main": [
[
{
"node": "Send PDF to the user",
"type": "main",
"index": 0
}
]
]
},
"Convert projects to HTML": {
"main": [
[
{
"node": "Projects",
"type": "main",
"index": 0
}
]
]
},
"Structured Output Parser": {
"ai_outputParser": [
[
{
"node": "Auto-fixing Output Parser",
"type": "ai_outputParser",
"index": 0
}
]
]
},
"Auto-fixing Output Parser": {
"ai_outputParser": [
[
{
"node": "Parse resume data",
"type": "ai_outputParser",
"index": 0
}
]
]
},
"Convert education to HTML": {
"main": [
[
{
"node": "Education",
"type": "main",
"index": 0
}
]
]
},
"Convert volunteering to HTML": {
"main": [
[
{
"node": "Volunteering",
"type": "main",
"index": 0
}
]
]
},
"Merge projects and volunteering": {
"main": [
[
{
"node": "Merge other data",
"type": "main",
"index": 1
}
]
]
},
"Convert employment history to HTML": {
"main": [
[
{
"node": "Employment history",
"type": "main",
"index": 0
}
]
]
},
"Merge personal info and technologies": {
"main": [
[
{
"node": "Merge all",
"type": "main",
"index": 0
}
]
]
},
"Merge education and employment history": {
"main": [
[
{
"node": "Merge other data",
"type": "main",
"index": 0
}
]
]
}
}
}
Credentials you'll need
Each integration node will prompt for credentials when you import. We strip credential IDs before publishing — you'll add your own.
openAiApitelegramApi
Pro
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About this workflow
57-Curriculo-Extraido-Pdf-Padronizado. Uses lmChatOpenAi, outputParserAutofixing, outputParserStructured, telegramTrigger. Event-driven trigger; 43 nodes.
Source: https://github.com/mascenaa/AutoPronto/blob/d3dafe08d296506b85c3bd29aba5d98df9c9906a/pacotes/kit-completo/57-curriculo-extraido-pdf-padronizado.json — original creator credit. Request a take-down →
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