이메일 관련 질문을 SQL 쿼리로 변환하고 실행
고급
이것은Building Blocks, AI, IT Ops분야의자동화 워크플로우로, 26개의 노드를 포함합니다.주로 If, Set, Merge, Postgres, ConvertToFile 등의 노드를 사용하며인공지능 기술을 결합하여 스마트 자동화를 구현합니다. 이메일 어시스턴트: Phi4-mini와 PostgreSQL를 사용하여 자연어를 SQL 쿼리로 변환
사전 요구사항
- •PostgreSQL 데이터베이스 연결 정보
사용된 노드 (26)
워크플로우 미리보기
노드 연결 관계를 시각적으로 표시하며, 확대/축소 및 이동을 지원합니다
워크플로우 내보내기
다음 JSON 구성을 복사하여 n8n에 가져오면 이 워크플로우를 사용할 수 있습니다
{
"id": "AC4paL1SXMFURgmc",
"meta": {
"instanceId": "8a3ba313628b26e4e4cf0504ff23322f235d6b433d92e59bcf8762764730ed80",
"templateCredsSetupCompleted": true
},
"name": "Translate questions about e-mails into SQL queries and run them",
"tags": [],
"nodes": [
{
"id": "dd63600a-6bee-43cd-a1d2-87aae2089ed4",
"name": "출력에 테이블명 추가",
"type": "n8n-nodes-base.set",
"position": [
840,
160
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "764176d6-3c89-404d-9c71-301e8a406a68",
"name": "table",
"type": "string",
"value": "={{ $('List all tables in a database').item.json.table_name ?? 'emails_metadata'}}"
}
]
},
"includeOtherFields": true
},
"typeVersion": 3.4
},
{
"id": "1bf02b6d-e8e4-4b1b-8ee2-c91a8c390a21",
"name": "데이터를 바이너리로 변환",
"type": "n8n-nodes-base.convertToFile",
"position": [
1040,
160
],
"parameters": {
"options": {},
"operation": "toJson"
},
"typeVersion": 1.1
},
{
"id": "cf930fa2-03bd-46fa-af4d-df282262f965",
"name": "로컬에 파일 저장",
"type": "n8n-nodes-base.readWriteFile",
"position": [
1220,
160
],
"parameters": {
"options": {},
"fileName": "=/files/pgsql-{{ $workflow.id }}.json",
"operation": "write"
},
"typeVersion": 1
},
{
"id": "48bc8812-7e1b-4d08-8610-884e00069f3c",
"name": "파일에서 데이터 추출",
"type": "n8n-nodes-base.extractFromFile",
"position": [
920,
620
],
"parameters": {
"options": {},
"operation": "fromJson"
},
"typeVersion": 1
},
{
"id": "0d6a0a55-a7cb-4471-ba80-a336324d2939",
"name": "채팅 트리거",
"type": "@n8n/n8n-nodes-langchain.chatTrigger",
"position": [
260,
520
],
"webhookId": "c308dec7-655c-4b79-832e-991bd8ea891f",
"parameters": {
"options": {}
},
"typeVersion": 1.1
},
{
"id": "8f39276c-4ce7-4b27-b022-231607a9cfb3",
"name": "스티키 노트",
"type": "n8n-nodes-base.stickyNote",
"position": [
160,
-60
],
"parameters": {
"color": 3,
"width": 1505,
"height": 486,
"content": "## This can run manually\nThis section:\n* loads a list of all tables from the database\n* extracts the database schema for each table and adds the table name\n* converts the schema into a binary JSON format\n* saves the schema file locally"
},
"typeVersion": 1
},
{
"id": "4fb5174f-a3ed-413f-98f7-41b0b46b62ae",
"name": "\"Test workflow\" 클릭 시",
"type": "n8n-nodes-base.manualTrigger",
"position": [
260,
160
],
"parameters": {},
"typeVersion": 1
},
{
"id": "cf6e9426-18ca-4d6e-bff2-d517ae7b4c1e",
"name": "스키마 데이터와 채팅 입력 결합",
"type": "n8n-nodes-base.set",
"position": [
1140,
620
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "42abd24e-419a-47d6-bc8b-7146dd0b8314",
"name": "sessionId",
"type": "string",
"value": "={{ $('Chat Trigger').isExecuted && $('Chat Trigger').first().json.sessionId }}"
},
{
"id": "39244192-a1a6-42fe-bc75-a6fba1f264df",
"name": "action",
"type": "string",
"value": "={{ $('Chat Trigger').isExecuted && $('Chat Trigger').first().json.action }}"
},
{
"id": "f78c57d9-df13-43c7-89a7-5387e528107e",
"name": "chatinput",
"type": "string",
"value": "={{ $('WorkflowTrigger').isExecuted ? $('WorkflowTrigger').first().json.natural_language_query: $('Chat Trigger').first().json.chatInput }}"
},
{
"id": "e42b39eb-dfbd-48d9-94ed-d658bdd41454",
"name": "schema",
"type": "string",
"value": "={{ $json.data }}"
}
]
}
},
"executeOnce": true,
"typeVersion": 3.4
},
{
"id": "6a960e03-ea13-4090-8ef8-9b294963fa63",
"name": "로컬 파일에서 스키마 로드",
"type": "n8n-nodes-base.readWriteFile",
"onError": "continueRegularOutput",
"maxTries": 2,
"position": [
480,
620
],
"parameters": {
"options": {},
"fileSelector": "=/files/pgsql-{{ $workflow.id }}.json"
},
"retryOnFail": false,
"typeVersion": 1,
"alwaysOutputData": true
},
{
"id": "0bad6e46-e8ed-4ba6-a7d9-2d69fd11227b",
"name": "SQL 쿼리 추출",
"type": "n8n-nodes-base.set",
"position": [
1740,
620
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "ebbe194a-4b8b-44c9-ac19-03cf69d353bf",
"name": "query",
"type": "string",
"value": "={{ ($json.output.match(/SELECT[^;]*/i) || [])[0] || \"\" }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "2aa91c40-8648-4fba-899d-5599866122e3",
"name": "쿼리 존재 여부 확인",
"type": "n8n-nodes-base.if",
"position": [
2400,
620
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "2963d04d-9d79-49f9-b52a-dc8732aca781",
"operator": {
"type": "string",
"operation": "notEmpty",
"singleValue": true
},
"leftValue": "={{ $json.query }}",
"rightValue": ""
}
]
}
},
"typeVersion": 2.2
},
{
"id": "24b59747-7f9b-473c-9d31-660e17867986",
"name": "쿼리 결과 형식화",
"type": "n8n-nodes-base.set",
"position": [
2840,
460
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "f944d21f-6aac-4842-8926-4108d6cad4bf",
"name": "sqloutput",
"type": "string",
"value": "={{ Object.keys($jmespath($input.all(),'[].json')[0]).join(' | ') }} \n{{ ($jmespath($input.all(),'[].json')).map(obj => Object.values(obj).join(' | ')).join('\\n') }}"
}
]
}
},
"executeOnce": true,
"typeVersion": 3.4
},
{
"id": "a25acba2-74c5-4af6-a1e4-46cfd1364b44",
"name": "쿼리 결과와 채팅 응답 결합",
"type": "n8n-nodes-base.merge",
"position": [
3060,
540
],
"parameters": {
"mode": "combine",
"options": {
"includeUnpaired": true
},
"combineBy": "combineByPosition"
},
"typeVersion": 3
},
{
"id": "a1cde4a1-7b47-4aa2-bd2c-a7090bfb0bb2",
"name": "테이블의 모든 열 나열",
"type": "n8n-nodes-base.postgres",
"position": [
640,
160
],
"parameters": {
"query": "SELECT\n column_name, \n udt_name as data_type, \n CASE WHEN data_type = 'ARRAY' THEN TRUE ELSE FALSE END AS is_array,\n is_nullable \nFROM INFORMATION_SCHEMA.COLUMNS where table_name = '{{ $json.table_name }}'",
"options": {},
"operation": "executeQuery"
},
"credentials": {},
"typeVersion": 2.6
},
{
"id": "cf167b64-007d-469a-bb3e-1144fe435a17",
"name": "데이터베이스의 모든 테이블 나열",
"type": "n8n-nodes-base.postgres",
"position": [
460,
160
],
"parameters": {
"query": "SELECT table_name FROM INFORMATION_SCHEMA.TABLES WHERE table_schema='public'",
"options": {},
"operation": "executeQuery"
},
"credentials": {},
"typeVersion": 2.6
},
{
"id": "6f6fd892-d779-41d4-ac19-1d5630674f67",
"name": "Ollama 채팅 모델",
"type": "@n8n/n8n-nodes-langchain.lmChatOllama",
"position": [
1440,
840
],
"parameters": {
"model": "phi4-mini:latest",
"options": {}
},
"credentials": {},
"typeVersion": 1
},
{
"id": "6cb76f04-3183-4bce-aa15-0724205d0ab3",
"name": "Postgres",
"type": "n8n-nodes-base.postgres",
"onError": "continueRegularOutput",
"position": [
2620,
460
],
"parameters": {
"query": "{{ $json.query }}",
"options": {},
"operation": "executeQuery"
},
"credentials": {},
"typeVersion": 2.6,
"alwaysOutputData": true
},
{
"id": "9c2a4d74-c2e6-4fac-a00d-2a84a5150027",
"name": "후행 세미콜론 추가",
"type": "n8n-nodes-base.set",
"position": [
2180,
540
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "15622b82-a226-4f54-9c0e-3f30b2c0cf4b",
"name": "query",
"type": "string",
"value": "={{ $json.query }};"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "7725f9c3-9c5d-41d6-b4d1-fc444122ae2f",
"name": "후행 세미콜론 확인",
"type": "n8n-nodes-base.if",
"position": [
1960,
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],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "94bd2686-21e7-44aa-b6a8-be5a17bd0242",
"operator": {
"type": "string",
"operation": "notEmpty",
"singleValue": true
},
"leftValue": "={{ $json.query }}",
"rightValue": ""
},
{
"id": "f22c8914-62f3-4f15-be6f-dd23de5a099a",
"operator": {
"type": "string",
"operation": "notEndsWith"
},
"leftValue": "={{ $json.query }}",
"rightValue": ";"
}
]
}
},
"typeVersion": 2.2
},
{
"id": "c7dd1e14-a8f6-4222-a12a-802928b10f56",
"name": "워크플로 트리거",
"type": "n8n-nodes-base.executeWorkflowTrigger",
"position": [
260,
720
],
"parameters": {
"workflowInputs": {
"values": [
{
"name": "natural_language_query"
}
]
}
},
"typeVersion": 1.1
},
{
"id": "f658fbba-54e3-40f5-9217-a0c8730b1ff4",
"name": "수동 실행 시",
"type": "n8n-nodes-base.if",
"position": [
1420,
160
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "or",
"conditions": [
{
"id": "c761a475-43ac-483b-827c-0eb69dfebc9a",
"operator": {
"type": "boolean",
"operation": "true",
"singleValue": true
},
"leftValue": "={{ $('When clicking \"Test workflow\"').isExecuted }}",
"rightValue": ""
}
]
}
},
"typeVersion": 2.2
},
{
"id": "67810482-afb7-47b0-ba0d-8b79a140e890",
"name": "파일 존재 또는 재생성 완료 시",
"type": "n8n-nodes-base.if",
"position": [
700,
620
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "or",
"conditions": [
{
"id": "28000886-13f4-4628-b1c0-afaaf596ec56",
"operator": {
"type": "object",
"operation": "exists",
"singleValue": true
},
"leftValue": "={{ $input.item.binary }}",
"rightValue": ""
},
{
"id": "ddcd8702-8774-4075-a2d0-6d99cf0cb2c2",
"operator": {
"type": "boolean",
"operation": "true",
"singleValue": true
},
"leftValue": "={{ $('If ran manually').isExecuted }}",
"rightValue": ""
}
]
}
},
"typeVersion": 2.2
},
{
"id": "38121ff4-b0d2-4274-92bf-be346b71c1e9",
"name": "스티키 노트1",
"type": "n8n-nodes-base.stickyNote",
"position": [
160,
440
],
"parameters": {
"width": 720,
"height": 540,
"content": "## This is triggered by chat or as a sub-workflow\nNatural language requests can be asked, and a SQL query as well as its results will be returned."
},
"typeVersion": 1
},
{
"id": "05dce292-4d93-4b0d-87e1-09e8b1dab70a",
"name": "AI 에이전트",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
1360,
620
],
"parameters": {
"text": "=You have access to a database containing all my personal email and documents.\n\nToday's date is {{ $now.toLocaleString() }}\n\nThe database schema is:\n```\n{{ $json.schema }}\n```\n\nGenerate a SQL query that will:\n```\n{{ $json.chatinput }}\n```\n\nIMPORTANT: \n1. ONLY use column names that exist in the schema above\n2. NEVER invent columns or assume JSON fields that aren't listed\n3. The only metadata fields are emails_metadata.id and emails_metadata.thread_id\n4. Use operators appropriate for each data type:\n - Text fields → ILIKE '%term%'\n - Date fields → Date comparisons (>,<,BETWEEN)\n - Array fields → @>, ANY(), IS NOT NULL\n5. Output ONLY the raw SQL statement ending with a semicolon\n6. The database cannot contain emails from the future",
"options": {
"systemMessage": "=You are an expert SQL query generator that creates precise PostgreSQL queries based on natural language requests. You must strictly adhere to the provided database schema and NEVER invent columns that don't exist.\n\nCRITICAL SCHEMA ADHERENCE RULES:\n\n1. ONLY use columns explicitly listed in the schema\n2. The metadata fields are strictly limited to:\n - emails_metadata.id\n - emails_metadata.thread_id\n3. NEVER invent fields like \"priority\", \"category\", or any metadata attributes not in the schema\n4. NEVER use JSON operators (->>, @>) unless the schema shows JSONB columns\n\nDATA TYPE HANDLING:\n\n1. TEXT/VARCHAR FIELDS:\n - Use ILIKE '%term%' for case-insensitive pattern matching\n - Example: WHERE email_subject ILIKE '%meeting%'\n\n2. TIMESTAMP/DATE FIELDS:\n - NEVER use LIKE/ILIKE on date fields\n - \"yesterday\" → date > CURRENT_DATE - INTERVAL '1 day' AND date < CURRENT_DATE\n - \"last week\" → date > CURRENT_DATE - INTERVAL '7 days'\n - Example: WHERE date > CURRENT_DATE - INTERVAL '3 days'\n\n3. ARRAY FIELDS:\n - Use @> for checking if array contains elements\n - Example: WHERE attachments IS NOT NULL\n\n4. BOOLEAN LOGIC:\n - Always use parentheses to clarify operator precedence\n - Example: WHERE (email_subject ILIKE '%report%' OR email_text ILIKE '%report%') AND date > '2023-01-01'\n\nQUERY CONSTRUCTION GUIDELINES:\n- Start with \"SELECT * FROM\" unless specific fields are requested\n- Use ORDER BY date DESC for recency when appropriate\n- Apply LIMIT only when specifically requested or implied by quantity terms\n- End all statements with semicolons\n- Output only the raw SQL without explanations or code blocks\n- Mind the difference between emails _about_ future dates references, and emails _received_ in specific date references. The database cannot contain emails from the future.\n\nEXAMPLE QUERIES:\n1. \"recent emails about projects from Sarah with attachments\"\n SELECT * FROM emails_metadata \n WHERE (email_subject ILIKE '%project%' OR email_text ILIKE '%project%')\n AND email_from ILIKE '%sarah%' \n AND attachments IS NOT NULL\n ORDER BY date DESC;\n\n2. \"emails received yesterday\"\n SELECT * FROM emails_metadata \n WHERE date > CURRENT_DATE - INTERVAL '1 day' AND date < CURRENT_DATE;\n\n3. \"one email about budget\"\n SELECT * FROM emails_metadata \n WHERE (email_subject ILIKE '%budget%' OR email_text ILIKE '%budget%')\n LIMIT 1;\n\n4. \"Find emails about interviews scheduled from April 28 to May 4\"\n SELECT * FROM emails_metadata\n WHERE (email_subject ILIKE '%interview%' OR email_text ILIKE '%interview%');\n\n5. \"Find emails from April about interviews\"\n SELECT * FROM emails_metadata \n WHERE (email_subject ILIKE '%interview%' OR email_text ILIKE '%interview%') AND date BETWEEN '2025-04-01' AND '2025-04-30';\n\n6. \"emails in thread 123\"\n SELECT * FROM emails_metadata \n WHERE thread_id = '123';\n\n7. \"what's my latest email?\"\n SELECT * FROM emails_metadata\n ORDER BY date DESC LIMIT 1;\n"
},
"promptType": "define"
},
"typeVersion": 1.8
},
{
"id": "6961fed9-4dcf-4a7f-97eb-bbf9e66dff3e",
"name": "빈 출력 형식화",
"type": "n8n-nodes-base.set",
"position": [
2620,
760
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "aa55e186-1535-4923-aee4-e088ca69575b",
"name": "query",
"type": "string",
"value": "={{ $json.query ?? '' }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "8138aed4-e38d-4c3c-9850-a200bd4d762e",
"name": "스티키 노트2",
"type": "n8n-nodes-base.stickyNote",
"position": [
1320,
440
],
"parameters": {
"width": 340,
"height": 540,
"content": "## Quite the prompt 😅\nSome refined prompt engineering work here.\n\nIt may or may not been done aided by Kagi's Assistant and Claude 3.7 Sonnet 👀"
},
"typeVersion": 1
}
],
"active": false,
"pinData": {},
"settings": {
"executionOrder": "v1"
},
"versionId": "c4e0962f-2c7f-4d14-af37-df491db2ebd0",
"connections": {
"05dce292-4d93-4b0d-87e1-09e8b1dab70a": {
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},
"6cb76f04-3183-4bce-aa15-0724205d0ab3": {
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}
]
]
},
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"main": [
[
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"type": "main",
"index": 0
}
]
]
},
"f658fbba-54e3-40f5-9217-a0c8730b1ff4": {
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[],
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]
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},
"c7dd1e14-a8f6-4222-a12a-802928b10f56": {
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"type": "main",
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}
]
]
},
"6f6fd892-d779-41d4-ac19-1d5630674f67": {
"ai_languageModel": [
[
{
"node": "05dce292-4d93-4b0d-87e1-09e8b1dab70a",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"cf930fa2-03bd-46fa-af4d-df282262f965": {
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[
{
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"type": "main",
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}
]
]
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"24b59747-7f9b-473c-9d31-660e17867986": {
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}
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},
"2aa91c40-8648-4fba-899d-5599866122e3": {
"main": [
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[]
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},
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[
{
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[
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]
}
}
}자주 묻는 질문
이 워크플로우를 어떻게 사용하나요?
위의 JSON 구성 코드를 복사하여 n8n 인스턴스에서 새 워크플로우를 생성하고 "JSON에서 가져오기"를 선택한 후, 구성을 붙여넣고 필요에 따라 인증 설정을 수정하세요.
이 워크플로우는 어떤 시나리오에 적합한가요?
고급 - 빌딩 블록, 인공지능, IT 운영
유료인가요?
이 워크플로우는 완전히 무료이며 직접 가져와 사용할 수 있습니다. 다만, 워크플로우에서 사용하는 타사 서비스(예: OpenAI API)는 사용자 직접 비용을 지불해야 할 수 있습니다.
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