This workflow follows the Chainllm → Chat Trigger recipe pattern — see all workflows that pair these two integrations.
The workflow JSON
Copy or download the full n8n JSON below. Paste it into a new n8n workflow, add your credentials, activate. Full import guide →
{
"createdAt": "2025-02-02T15:48:49.139Z",
"updatedAt": "2025-02-10T12:45:27.037Z",
"id": "zrMOR7Bph0Qrt5Dl",
"name": "Siscad DB AI",
"active": false,
"nodes": [
{
"parameters": {
"options": {}
},
"type": "@n8n/n8n-nodes-langchain.chatTrigger",
"typeVersion": 1.1,
"position": [
-1600,
-440
],
"id": "f9aaa3bc-d856-4f4d-9482-871ad97d249c",
"name": "When chat message received"
},
{
"parameters": {
"assignments": {
"assignments": [
{
"id": "757c1e74-7caa-40f9-ae01-aa7838367742",
"name": "tables",
"value": "['v_members', 'v_plans', 'v_cities', 'v_regions']",
"type": "string"
}
]
},
"options": {}
},
"type": "n8n-nodes-base.set",
"typeVersion": 3.4,
"position": [
-1400,
-680
],
"id": "9f84bb57-da53-44ad-b298-d0142d48ef6b",
"name": "Edit Fields"
},
{
"parameters": {
"options": {}
},
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"typeVersion": 1,
"position": [
-1200,
-480
],
"id": "4994d636-1500-4ba2-970b-b4111f37b935",
"name": "Google Gemini Chat Model",
"credentials": {
"googlePalmApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"operation": "executeQuery",
"query": "{{ $json.text }}",
"options": {}
},
"type": "n8n-nodes-base.postgres",
"typeVersion": 2.5,
"position": [
-860,
-680
],
"id": "b1b040b3-9055-463b-98e1-8f82fc3343f8",
"name": "EXECUTE QUERY EXTRACT SCHEMA",
"credentials": {
"postgres": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"jsCode": "return {\n schema: JSON.stringify($('EXECUTE QUERY EXTRACT SCHEMA').all())\n}"
},
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
-640,
-680
],
"id": "98848bef-4b6b-48aa-a12e-74d60b06d764",
"name": "PREPARE SCHEMA DBS"
},
{
"parameters": {
"modelName": "models/gemini-1.0-pro-001",
"options": {}
},
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"typeVersion": 1,
"position": [
-420,
-500
],
"id": "c7bef772-6e8a-44de-8d51-600aa2d783de",
"name": "Google Gemini Chat Model1",
"credentials": {
"googlePalmApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"operation": "executeQuery",
"query": "{{ $json.result }}",
"options": {}
},
"type": "n8n-nodes-base.postgres",
"typeVersion": 2.5,
"position": [
160,
-680
],
"id": "b39e20ea-0c6a-4429-958a-3b4dd0a8ac19",
"name": "EXECUTE QUERY TO EXTRACT INFORMATION",
"credentials": {
"postgres": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"jsCode": "const query = $input.first().json.text // Certifique-se de que 'query' \u00e9 o nome do campo de entrada\nconst match = query.match(/```sql\\n([\\s\\S]*?)\\n```/);\nreturn [{ json: { result: match ? match[1].trim() : query.trim() } }];\n"
},
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
-60,
-680
],
"id": "fcc30638-db7b-4543-b849-9da3757bdf41",
"name": "Code"
},
{
"parameters": {
"promptType": "define",
"text": "=Dado as tabelas a seguir, preciso que voc\u00ea altere a query para utilizada para extrair o schema do banco somente para as tabelas informadas.\n\nTABELAS\n{{ $json.tables }}\n\n### QUERY A SER ALTERADA\nSELECT table_name, column_name, data_type \nFROM information_schema.columns \nWHERE table_schema = 'public' \nAND table_name in () \nORDER BY table_name, ordinal_position;\n\n### O QUE FAZER\n1. RETORNAR APENAS A QUERY FINAL\n2. GARANTIR QUE O RETORNO VAI SER EXECUTADO PELO DB COM SUCESSO\n\n### O QUE N\u00c3O FAZER\n1. INCLUIR EXPLICA\u00c7\u00c3O OU OPINI\u00c3O\n2. N\u00c3O INCLUIR EM BLOCO DE C\u00d3DIGO COMO POR EXEMPLO \"```sql\"\n"
},
"type": "@n8n/n8n-nodes-langchain.chainLlm",
"typeVersion": 1.5,
"position": [
-1220,
-680
],
"id": "1a1e6340-82fe-40cb-8c91-8c6436db7db8",
"name": "EXTRACT SCHEMA DBS"
},
{
"parameters": {
"promptType": "define",
"text": "={{ $('When chat message received').last().json.chatInput }}",
"messages": {
"messageValues": [
{
"message": "=Voc\u00ea agora \u00e9 um DBA experiente em montar queries para extrair as informa\u00e7\u00f5es do banco solicitadas pelo usu\u00e1rio.\n\nPreciso que voc\u00ea analise a solicita\u00e7\u00e3o do usu\u00e1rio e utilizando o schema predefinido elabore a query para extrair as informa\u00e7\u00f5es desejadas.\n\n### SCHEMA DISPON\u00cdVEL\n{{ $json.schema }}\n\n### O QUE VOC\u00ca DEVE FAZER\n1. RETORNAR APENAS A QUERY FINAL;\n2. GARANTIR QUE O RETORNO VAI SER EXECUTADO PELO DB COM SUCESSO;\n3. SEMPRE UTILIZE ILIKE PARA OS CAMPOS VARCHAR, CHAR, STRING, TEXT;\n4. Remova TODOS e quaisquer caracteres antes e depois da query, deixando apenas o c\u00f3digo SQL puro como no exemplo abaixo:\n\"SELECT COUNT(*) AS total FROM table_name;\"\n\n### CONSIDERAC\u00d4ES PARA A CRIACAO DE UMA SQL CORRETA:\n1. SITUACAO DOS SOCIOS:\n 1.1. S\u00f3cios ativos equivale status_id = '2';\n 1.2. S\u00f3cios inativos equivale status_id = '1';\n\n2. INFORMACOES:\n 2.1 TODAS AS INFORMACOES ESTAO CONTIDAS NA TABELA INFORMADA;\n\n3. PLANOS DOS SOCIOS:\n 3.1 Plano especial equivale plan_id = '1';\n 3.2 Plano normal equivale plan_id = '2';\n 3.3 Plano inss equivale plan_id = '3';\n 3.4 Plano contribuinte equivale plan_id = '4';\n 3.5 Plano ipe equivale plan_id = '5';\n\n4. RELACAO ENTRE TABELAS:\n 4.1 Utilizar os nomes dos campos originais das tabelas quando possivel;\n 4.2 NAO DEVERA SER REALIZADA NENHUM RELACIONAMENTO COM OUTRAS TABELAS;\n"
}
]
}
},
"type": "@n8n/n8n-nodes-langchain.chainLlm",
"typeVersion": 1.5,
"position": [
-440,
-680
],
"id": "a65584b8-1a69-44ff-a300-305912092f4d",
"name": "GENERATE QUERY TO EXTRACT DBS"
}
],
"connections": {
"When chat message received": {
"main": [
[
{
"node": "Edit Fields",
"type": "main",
"index": 0
}
]
]
},
"Edit Fields": {
"main": [
[
{
"node": "EXTRACT SCHEMA DBS",
"type": "main",
"index": 0
}
]
]
},
"Google Gemini Chat Model": {
"ai_languageModel": [
[
{
"node": "EXTRACT SCHEMA DBS",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"EXECUTE QUERY EXTRACT SCHEMA": {
"main": [
[
{
"node": "PREPARE SCHEMA DBS",
"type": "main",
"index": 0
}
]
]
},
"PREPARE SCHEMA DBS": {
"main": [
[
{
"node": "GENERATE QUERY TO EXTRACT DBS",
"type": "main",
"index": 0
}
]
]
},
"Google Gemini Chat Model1": {
"ai_languageModel": [
[
{
"node": "GENERATE QUERY TO EXTRACT DBS",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Code": {
"main": [
[
{
"node": "EXECUTE QUERY TO EXTRACT INFORMATION",
"type": "main",
"index": 0
}
]
]
},
"EXECUTE QUERY TO EXTRACT INFORMATION": {
"main": [
[]
]
},
"EXTRACT SCHEMA DBS": {
"main": [
[
{
"node": "EXECUTE QUERY EXTRACT SCHEMA",
"type": "main",
"index": 0
}
]
]
},
"GENERATE QUERY TO EXTRACT DBS": {
"main": [
[
{
"node": "Code",
"type": "main",
"index": 0
}
]
]
}
},
"settings": {
"executionOrder": "v1"
},
"staticData": null,
"meta": {
"templateCredsSetupCompleted": true
},
"versionId": "bcb0b7df-d0bc-4d86-ad7a-9ae39de5c605",
"triggerCount": 0,
"tags": []
}
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.
googlePalmApipostgres
Pro
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About this workflow
Siscad DB AI. Uses chatTrigger, lmChatGoogleGemini, postgres, chainLlm. Chat trigger; 10 nodes.
Source: https://github.com/ManusAafc/n8n/blob/33594463d360d5fda53843f65e53a80f29c53857/backup/zrMOR7Bph0Qrt5Dl.json — original creator credit. Request a take-down →
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