Workflow n8n
Automatisation Chatbot avec n8n : intégration Postgres et QuickCharts
Ce workflow n8n a pour objectif de créer un chatbot intelligent capable d'interagir avec une base de données Postgres et de générer des graphiques via QuickCharts. Dans un contexte où les entreprises cherchent à optimiser leurs interactions clients, ce type d'automatisation permet de répondre rapidement aux demandes des utilisateurs tout en fournissant des visualisations de données pertinentes. Les cas d'usage incluent la gestion des requêtes clients, l'analyse de données en temps réel et la création de rapports visuels dynamiques.
- Étape 1 : le workflow est déclenché par la réception d'un message de chat.
- Étape 2 : une requête SQL est exécutée sur la base de données Postgres pour récupérer les informations nécessaires.
- Étape 3 : en fonction des résultats, le chatbot peut générer des graphiques via QuickCharts, en utilisant des agents spécifiques pour traiter les données et formuler des réponses adaptées. Les nœuds tels que 'Sticky Note' sont utilisés pour structurer les informations et les réponses fournies. En intégrant des outils comme GPT-4, ce workflow améliore l'interaction utilisateur et optimise la gestion des données. Les bénéfices pour les entreprises incluent une réduction du temps de réponse, une meilleure satisfaction client et une visualisation efficace des données, ce qui renforce la prise de décision.
Tags clés :automatisationPostgresQuickChartschatbotn8n
Catégorie: Webhook · Tags: automatisation, Postgres, QuickCharts, chatbot, n8n❤ 0
Workflow n8n Postgres, QuickCharts, chatbot : vue d'ensemble
Schéma des nœuds et connexions de ce workflow n8n, généré à partir du JSON n8n.
Workflow n8n Postgres, QuickCharts, chatbot : détail des nœuds
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"id": "Q63cSgFlcqz291ec",
"meta": {
"instanceId": "31e69f7f4a77bf465b805824e303232f0227212ae922d12133a0f96ffeab4fef",
"templateCredsSetupCompleted": true
},
"name": "✨📊Multi-AI Agent Chatbot for Postgres/Supabase DB and QuickCharts + Tool Router",
"tags": [],
"nodes": [
{
"id": "3a332532-a56e-42f5-a114-4a7e138b5e0f",
"name": "When chat message received",
"type": "@n8n/n8n-nodes-langchain.chatTrigger",
"position": [
-180,
-1420
],
"webhookId": "faddb40a-7048-4398-a0f9-d239a19c32ce",
"parameters": {
"options": {}
},
"typeVersion": 1.1
},
{
"id": "6c707ee7-95e9-4ebd-9373-a2dac0ea73a7",
"name": "Execute SQL Query",
"type": "n8n-nodes-base.postgresTool",
"position": [
460,
-500
],
"parameters": {
"query": "{{ $fromAI(\"sql_query\", \"SQL Query\") }}",
"options": {},
"operation": "executeQuery",
"descriptionType": "manual",
"toolDescription": "Use this tool to query the database with SQL queries"
},
"credentials": {
"postgres": {
"id": "wZnget4L3P3bnlfh",
"name": "Postgres account"
}
},
"typeVersion": 2.5
},
{
"id": "1d5572e1-de5a-4e67-8ba1-82196bd62e9b",
"name": "When Executed by Another Workflow",
"type": "n8n-nodes-base.executeWorkflowTrigger",
"position": [
-480,
-360
],
"parameters": {
"workflowInputs": {
"values": [
{
"name": "user_prompt"
},
{
"name": "route"
},
{
"name": "db_records"
}
]
}
},
"typeVersion": 1.1
},
{
"id": "e3caa1b3-7bdb-43c1-a749-74ae02912d84",
"name": "query_db_tool",
"type": "@n8n/n8n-nodes-langchain.toolWorkflow",
"position": [
720,
-1100
],
"parameters": {
"name": "query_database_tool",
"workflowId": {
"__rl": true,
"mode": "id",
"value": "={{ $workflow.id }}"
},
"description": "Use this tool to query the database",
"workflowInputs": {
"value": {
"route": "query_database_tool",
"user_prompt": "={{ $('When chat message received').item.json.chatInput }}"
},
"schema": [
{
"id": "user_prompt",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "user_prompt",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "route",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "route",
"defaultMatch": false,
"canBeUsedToMatch": true
}
],
"mappingMode": "defineBelow",
"matchingColumns": [
"user_prompt"
],
"attemptToConvertTypes": false,
"convertFieldsToString": false
}
},
"typeVersion": 2
},
{
"id": "594e6fd3-084a-4100-ac16-1cc4068e03c1",
"name": "generate_quickchart_tool",
"type": "@n8n/n8n-nodes-langchain.toolWorkflow",
"position": [
980,
-1100
],
"parameters": {
"name": "generate_chart_tool",
"workflowId": {
"__rl": true,
"mode": "id",
"value": "={{ $workflow.id }}"
},
"description": "Use this tool to generate a chart with QuickChart",
"workflowInputs": {
"value": {
"route": "generate_chart_tool",
"db_records": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('db_records', `The database records`, 'string') }}",
"user_prompt": "={{ $('When chat message received').item.json.chatInput }}"
},
"schema": [
{
"id": "user_prompt",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "user_prompt",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "route",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "route",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "db_records",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "db_records",
"defaultMatch": false,
"canBeUsedToMatch": true
}
],
"mappingMode": "defineBelow",
"matchingColumns": [
"user_prompt"
],
"attemptToConvertTypes": false,
"convertFieldsToString": false
}
},
"typeVersion": 2
},
{
"id": "580426ac-0fb7-4f14-af7b-e497b7cb08f8",
"name": "Create QuickChart",
"type": "n8n-nodes-base.httpRequest",
"position": [
780,
-140
],
"parameters": {
"url": "={{ encodeURI($json.url) }}",
"options": {}
},
"typeVersion": 4.2
},
{
"id": "b7085357-ebe9-4564-868d-b31fc2e9734a",
"name": "QuickChart Object Schema",
"type": "@n8n/n8n-nodes-langchain.outputParserStructured",
"position": [
460,
140
],
"parameters": {
"jsonSchemaExample": "{\n \"type\": \"bar\",\n \"data\": {\n \"labels\": [\"R270684\", \"R274295\", \"R276352\", \"R277914\", \"R280108\"],\n \"datasets\": [\n {\n \"label\": \"List Price\",\n \"data\": [2149000, 924900, 924900, 1288000, 1198000],\n \"backgroundColor\": \"#FF6384\"\n },\n {\n \"label\": \"Days On Market\",\n \"data\": [101, 91, 123, 136, 185],\n \"backgroundColor\": \"#36A2EB\"\n }\n ]\n },\n \"options\": {\n \"scales\": {\n \"y\": {\n \"min\": 0,\n \"max\": 2200000\n }\n }\n }\n}"
},
"typeVersion": 1.2
},
{
"id": "b1037112-f5af-4e61-8bd1-0d9b0a9ad2e1",
"name": "gpt-4o-mini",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
200,
-1100
],
"parameters": {
"model": {
"__rl": true,
"mode": "list",
"value": "gpt-4o-mini"
},
"options": {
"responseFormat": "text"
}
},
"credentials": {
"openAiApi": {
"id": "jEMSvKmtYfzAkhe6",
"name": "OpenAi account"
}
},
"typeVersion": 1.2
},
{
"id": "5ea5ba56-2368-4e95-a98f-2c7548a66a9b",
"name": "gpt-4o-mini-2",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
200,
140
],
"parameters": {
"model": {
"__rl": true,
"mode": "id",
"value": "=gpt-4o-mini"
},
"options": {
"responseFormat": "text"
}
},
"credentials": {
"openAiApi": {
"id": "jEMSvKmtYfzAkhe6",
"name": "OpenAi account"
}
},
"typeVersion": 1.2
},
{
"id": "4b8f9978-9d46-48f5-93ca-002ade008887",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
80,
-1500
],
"parameters": {
"color": 5,
"width": 1100,
"height": 600,
"content": "## 🤖Primary AI Manager Agent"
},
"typeVersion": 1
},
{
"id": "f6534374-cc07-429a-b27c-b38835c96465",
"name": "🤖Primary Agent",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
480,
-1420
],
"parameters": {
"options": {
"systemMessage": "You are a helpful assistant that answers the users questions by using the tools provided.\n\n## TOOLS\n- query_database_tool: Use this tool to query the database\n- generate_chart_tool: Use this tool to generate a chart with QuickChart\n\nAlways provide the results of the database query and the link for the chart when applicable."
}
},
"typeVersion": 1.7
},
{
"id": "cf246e46-b3e4-4c9f-96f9-be1b91c0a3eb",
"name": "🤖Secondary Postgres Agent",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
480,
-780
],
"parameters": {
"text": "={{ $json.user_prompt }}",
"options": {
"systemMessage": "You are a helpful assistant with tools for querying a SQL database. Use the tools provided to query the database."
},
"promptType": "define"
},
"typeVersion": 1.7
},
{
"id": "02d741d3-4b6e-4e19-8aca-3e15175e9667",
"name": "🤖Secondary QuickChart Agent",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
240,
-140
],
"parameters": {
"text": "=Your task is to generate a Chart.js configuration object with the following specifications:\n- Chart type: bar unless otherwise indicated\n- Labels: Use the ML # from each record unless otherwise indicated\n- Show bar for list price if not otherwise indicated\n- Return only the raw JSON object without code fences or explanations\n\nThis is the user prompt: {{ $json.user_prompt }}\nThis is the result of the SQL query: {{ $json.db_records }}",
"options": {},
"promptType": "define",
"hasOutputParser": true
},
"typeVersion": 1.7
},
{
"id": "4f41690b-313a-4ce3-ba65-a2ce2c3ee9b9",
"name": "🔀Tool Agent Router",
"type": "n8n-nodes-base.switch",
"position": [
-180,
-360
],
"parameters": {
"rules": {
"values": [
{
"outputKey": "🔍query",
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "35b1e13e-6157-48d0-85af-3cd33260eae1",
"operator": {
"name": "filter.operator.equals",
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $json.route }}",
"rightValue": "=query_database_tool"
}
]
},
"renameOutput": true
},
{
"outputKey": "📊chart",
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "ff5f97fb-0f18-4bf9-b16c-3d0b3bc3c7f4",
"operator": {
"name": "filter.operator.equals",
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $json.route }}",
"rightValue": "=generate_chart_tool"
}
]
},
"renameOutput": true
}
]
},
"options": {}
},
"typeVersion": 3.2
},
{
"id": "27c30d2c-3af3-4d05-aadb-9f18751fb9ce",
"name": "Table Definitions",
"type": "n8n-nodes-base.postgresTool",
"position": [
980,
-500
],
"parameters": {
"query": "select\n c.column_name,\n c.data_type,\n c.is_nullable,\n c.column_default,\n tc.constraint_type,\n ccu.table_name AS referenced_table,\n ccu.column_name AS referenced_column\nfrom\n information_schema.columns c\nLEFT join\n information_schema.key_column_usage kcu\n ON c.table_name = kcu.table_name\n AND c.column_name = kcu.column_name\nLEFT join\n information_schema.table_constraints tc\n ON kcu.constraint_name = tc.constraint_name\n AND tc.constraint_type = 'FOREIGN KEY'\nLEFT join\n information_schema.constraint_column_usage ccu\n ON tc.constraint_name = ccu.constraint_name\nwhere\n c.table_name = '{{ $fromAI(\"table_name\") }}'\n AND c.table_schema = '{{ $fromAI(\"schema_name\") }}'\norder by\n c.ordinal_position",
"options": {},
"operation": "executeQuery",
"descriptionType": "manual",
"toolDescription": "Use this tool to get table definition to find all columns and types"
},
"credentials": {
"postgres": {
"id": "wZnget4L3P3bnlfh",
"name": "Postgres account"
}
},
"typeVersion": 2.5
},
{
"id": "59dfd315-fb02-425c-a6ca-2d63167c2e24",
"name": "Postgres Chat Memory",
"type": "@n8n/n8n-nodes-langchain.memoryPostgresChat",
"position": [
460,
-1100
],
"parameters": {
"tableName": "={{ $workflow.id }}_chat_history"
},
"credentials": {
"postgres": {
"id": "wZnget4L3P3bnlfh",
"name": "Postgres account"
}
},
"typeVersion": 1.3
},
{
"id": "81dd8b73-0809-4f30-a867-bf98ff6a80bc",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
900,
-1180
],
"parameters": {
"color": 7,
"height": 240,
"content": "## QuickChart Tool"
},
"typeVersion": 1
},
{
"id": "1a08bc08-510b-4cda-b96e-179bd3abe164",
"name": "Sticky Note2",
"type": "n8n-nodes-base.stickyNote",
"position": [
640,
-1180
],
"parameters": {
"color": 7,
"height": 240,
"content": "## Postgres Tool"
},
"typeVersion": 1
},
{
"id": "9cc5e958-0f93-42ad-813e-83c8b5bb126e",
"name": "Sticky Note3",
"type": "n8n-nodes-base.stickyNote",
"position": [
120,
-1180
],
"parameters": {
"color": 7,
"height": 240,
"content": "## LLM"
},
"typeVersion": 1
},
{
"id": "920f9fe4-e182-4159-9152-e81586ec5304",
"name": "Sticky Note4",
"type": "n8n-nodes-base.stickyNote",
"position": [
380,
-1180
],
"parameters": {
"color": 7,
"height": 240,
"content": "## Chat Memory"
},
"typeVersion": 1
},
{
"id": "d2a24dce-1add-49d6-8d2f-6547fca35bfb",
"name": "Sticky Note5",
"type": "n8n-nodes-base.stickyNote",
"position": [
-300,
-1500
],
"parameters": {
"color": 4,
"width": 340,
"height": 280,
"content": "## 👍Start Here"
},
"typeVersion": 1
},
{
"id": "d0df3ea6-9765-4f4d-a8f7-b2356ea1cf26",
"name": "Sticky Note6",
"type": "n8n-nodes-base.stickyNote",
"position": [
80,
-860
],
"parameters": {
"color": 6,
"width": 1100,
"height": 560,
"content": "## ⚒️🤖Secondary Postgres Tool Agent "
},
"typeVersion": 1
},
{
"id": "fe990853-fce6-4cbe-9cc2-fc04f53742e8",
"name": "Sticky Note7",
"type": "n8n-nodes-base.stickyNote",
"position": [
120,
-580
],
"parameters": {
"color": 7,
"height": 240,
"content": ""
},
"typeVersion": 1
},
{
"id": "c5086736-4dfe-44a3-a5dc-6cace0593334",
"name": "Sticky Note8",
"type": "n8n-nodes-base.stickyNote",
"position": [
640,
-580
],
"parameters": {
"color": 7,
"height": 240,
"content": ""
},
"typeVersion": 1
},
{
"id": "6b848863-10b2-42e4-8bd5-ed4663b9e5cb",
"name": "Sticky Note9",
"type": "n8n-nodes-base.stickyNote",
"position": [
900,
-580
],
"parameters": {
"color": 7,
"height": 240,
"content": ""
},
"typeVersion": 1
},
{
"id": "75231fcf-8314-4ee6-96a7-99d842b6ee4f",
"name": "Sticky Note10",
"type": "n8n-nodes-base.stickyNote",
"position": [
380,
-580
],
"parameters": {
"color": 7,
"height": 240,
"content": ""
},
"typeVersion": 1
},
{
"id": "c54439c7-ccb1-41a4-ad76-8ed39f7fc5e6",
"name": "Sticky Note11",
"type": "n8n-nodes-base.stickyNote",
"position": [
-300,
-460
],
"parameters": {
"color": 3,
"width": 340,
"height": 320,
"content": "## Tool Agent Router 🔀"
},
"typeVersion": 1
},
{
"id": "b51ffe20-2ae4-478b-9573-fc5456935483",
"name": "Sticky Note12",
"type": "n8n-nodes-base.stickyNote",
"position": [
80,
-260
],
"parameters": {
"color": 6,
"width": 1100,
"height": 600,
"content": "## ⚒️🤖Secondary QuickChart Tool Agent"
},
"typeVersion": 1
},
{
"id": "ffb9da23-f79c-4d20-81a3-656471bdda33",
"name": "Sticky Note13",
"type": "n8n-nodes-base.stickyNote",
"position": [
380,
60
],
"parameters": {
"color": 7,
"height": 240,
"content": ""
},
"typeVersion": 1
},
{
"id": "61532d90-1f65-48d0-a408-2e6edd9511b1",
"name": "Sticky Note15",
"type": "n8n-nodes-base.stickyNote",
"position": [
120,
60
],
"parameters": {
"color": 7,
"height": 240,
"content": ""
},
"typeVersion": 1
},
{
"id": "5b125fa6-8017-437e-bb20-b9deb5d52c63",
"name": "Final QuickChart URL",
"type": "n8n-nodes-base.set",
"position": [
980,
-140
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "63bab42a-9b9b-4756-88d2-f41cff9a1ded",
"name": "quickchart_url",
"type": "string",
"value": "={{ encodeURI($json.url) }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "2c66055d-1ca2-40f3-a082-57232402fdd1",
"name": "QuickChart GET URL",
"type": "n8n-nodes-base.set",
"position": [
580,
-140
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "d69995ae-413e-49e7-b6ec-17e9e034e4b6",
"name": "url",
"type": "string",
"value": "={{ \"https://quickchart.io/chart?width=250&height=150&chart=\" + $json.output.toJsonString() }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "0a0f024d-24fa-43e9-bfa6-b841902b5e5e",
"name": "Sticky Note14",
"type": "n8n-nodes-base.stickyNote",
"position": [
-540,
-1600
],
"parameters": {
"color": 7,
"width": 1760,
"height": 1980,
"content": "# ✨📊Multi-AI Agent Chatbot for Postgres/Supabase DB and QuickCharts + Tool Router"
},
"typeVersion": 1
},
{
"id": "a50b4d31-7e9e-4cd0-84b9-f4755deb6efd",
"name": "Sticky Note16",
"type": "n8n-nodes-base.stickyNote",
"position": [
-500,
-1180
],
"parameters": {
"width": 540,
"height": 240,
"content": "## Setup\n\n1. Create a Postgres compatible database (Supabase)\n\n2. Add your Postgres and OpenAI credentials\n\n3. Click Chat button and start chatting with your database and creating QuickChart to visualize the results\n"
},
"typeVersion": 1
},
{
"id": "3df0304a-323b-4bd4-96ce-2907367ede8d",
"name": "Sticky Note17",
"type": "n8n-nodes-base.stickyNote",
"position": [
-500,
-860
],
"parameters": {
"width": 542,
"height": 296,
"content": "## Postgres Tools Used\n\n1. **Execute SQL Query** \nUsed to execute any query generated by the agent.\n\n2. **DB Schema and Tables** \nReturns the list of all the tables with its schema name.\n\n3. **Table Definition** \nReturns table details like column names, foreign keys and more of a particular table in a schema."
},
"typeVersion": 1
},
{
"id": "feaeaf6d-f5b8-4dbe-a39b-d07882142ead",
"name": "Sticky Note19",
"type": "n8n-nodes-base.stickyNote",
"position": [
-500,
-40
],
"parameters": {
"width": 542,
"height": 376,
"content": "## Generate a Quickchart\n\n**Secondary QuickChart Agent Tool**\nThis section handles the chart generation process through several steps by sending the database records and user prompt to OpenAI to create a JSON object based on Chart.js and QuickChart.io definitions\n\n**QuickChart GET URL node**\nThis sections adds chart definitions to a QuickChart.io URL\n\n**Create QuickChart node**\nThis sections sends chart queries to QuickCharts with a defined JSON format\n\n\n\nThis integration allows you to dynamically generate charts based on data queries, with AI assistance for formatting and optimization.\n\n\n"
},
"typeVersion": 1
},
{
"id": "6c9be4d2-46e9-44ae-8751-f4f4964323e9",
"name": "DB Schema and Tables",
"type": "n8n-nodes-base.postgresTool",
"position": [
720,
-500
],
"parameters": {
"query": "SELECT \n table_schema,\n table_name\nFROM information_schema.tables\nWHERE table_type = 'BASE TABLE'\n AND table_schema NOT IN ('pg_catalog', 'information_schema')\nORDER BY table_schema, table_name;",
"options": {},
"operation": "executeQuery",
"descriptionType": "manual",
"toolDescription": "Use this tool to get a list of all tables with their schema in the database"
},
"credentials": {
"postgres": {
"id": "wZnget4L3P3bnlfh",
"name": "Postgres account"
}
},
"typeVersion": 2.5
},
{
"id": "4e779b6f-963c-4efb-af43-bec0e5c3228c",
"name": "gpt-40-mini-1",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
200,
-500
],
"parameters": {
"model": {
"__rl": true,
"mode": "list",
"value": "gpt-4o-mini"
},
"options": {
"responseFormat": "text"
}
},
"credentials": {
"openAiApi": {
"id": "jEMSvKmtYfzAkhe6",
"name": "OpenAi account"
}
},
"typeVersion": 1.2
},
{
"id": "a6cc9a4e-b016-47f6-9f9f-9c77a15c2be2",
"name": "Sticky Note18",
"type": "n8n-nodes-base.stickyNote",
"position": [
640,
180
],
"parameters": {
"width": 440,
"height": 120,
"content": "## QuickChart Schema\nAdjust the QuickChart Schema to match your use case.\n\nhttps://quickchart.io/documentation/"
},
"typeVersion": 1
},
{
"id": "9855ba6a-d46b-4461-a397-02108023abc5",
"name": "Sticky Note20",
"type": "n8n-nodes-base.stickyNote",
"position": [
640,
60
],
"parameters": {
"width": 440,
"height": 100,
"content": "## Chart Size\nAdjust the chart size in the QuickChart GET URL node.\n"
},
"typeVersion": 1
}
],
"active": false,
"pinData": {
"When Executed by Another Workflow": [
{
"json": {
"route": "generate_chart_tool",
"db_records": "[{\"mls_num\":\"R292309\",\"list_price\":1148000},{\"mls_num\":\"R292302\",\"list_price\":1298000},{\"mls_num\":\"R294786\",\"list_price\":1280000},{\"mls_num\":\"V17840\",\"list_price\":939000},{\"mls_num\":\"V10178\",\"list_price\":420000},{\"mls_num\":\"V18007\",\"list_price\":296500},{\"mls_num\":\"V18136\",\"list_price\":379000},{\"mls_num\":\"V18643\",\"list_price\":329000},{\"mls_num\":\"V17755\",\"list_price\":236000},{\"mls_num\":\"V19126\",\"list_price\":245500}]",
"user_prompt": "provide a bar chart showing mls# and list price"
}
}
]
},
"settings": {
"executionOrder": "v1"
},
"versionId": "9781f576-38ef-4e18-9fbe-8383565cb032",
"connections": {
"gpt-4o-mini": {
"ai_languageModel": [
[
{
"node": "🤖Primary Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"gpt-40-mini-1": {
"ai_languageModel": [
[
{
"node": "🤖Secondary Postgres Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"gpt-4o-mini-2": {
"ai_languageModel": [
[
{
"node": "🤖Secondary QuickChart Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"query_db_tool": {
"ai_tool": [
[
{
"node": "🤖Primary Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"Create QuickChart": {
"main": [
[
{
"node": "Final QuickChart URL",
"type": "main",
"index": 0
}
]
]
},
"Execute SQL Query": {
"ai_tool": [
[
{
"node": "🤖Secondary Postgres Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"Table Definitions": {
"ai_tool": [
[
{
"node": "🤖Secondary Postgres Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"🤖Primary Agent": {
"main": [
[]
]
},
"QuickChart GET URL": {
"main": [
[
{
"node": "Create QuickChart",
"type": "main",
"index": 0
}
]
]
},
"DB Schema and Tables": {
"ai_tool": [
[
{
"node": "🤖Secondary Postgres Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"Postgres Chat Memory": {
"ai_memory": [
[
{
"node": "🤖Primary Agent",
"type": "ai_memory",
"index": 0
}
]
]
},
"🔀Tool Agent Router": {
"main": [
[
{
"node": "🤖Secondary Postgres Agent",
"type": "main",
"index": 0
}
],
[
{
"node": "🤖Secondary QuickChart Agent",
"type": "main",
"index": 0
}
]
]
},
"QuickChart Object Schema": {
"ai_outputParser": [
[
{
"node": "🤖Secondary QuickChart Agent",
"type": "ai_outputParser",
"index": 0
}
]
]
},
"generate_quickchart_tool": {
"ai_tool": [
[
{
"node": "🤖Primary Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"When chat message received": {
"main": [
[
{
"node": "🤖Primary Agent",
"type": "main",
"index": 0
}
]
]
},
"🤖Secondary Postgres Agent": {
"main": [
[]
]
},
"🤖Secondary QuickChart Agent": {
"main": [
[
{
"node": "QuickChart GET URL",
"type": "main",
"index": 0
}
]
]
},
"When Executed by Another Workflow": {
"main": [
[
{
"node": "🔀Tool Agent Router",
"type": "main",
"index": 0
}
]
]
}
}
}Workflow n8n Postgres, QuickCharts, chatbot : pour qui est ce workflow ?
Ce workflow s'adresse aux entreprises technologiques, aux équipes de développement et aux professionnels de la data qui souhaitent automatiser les interactions avec leurs bases de données. Il convient aux organisations de taille moyenne à grande, ayant une certaine expertise technique.
Workflow n8n Postgres, QuickCharts, chatbot : problème résolu
Ce workflow résout le problème de la lenteur et de l'inefficacité dans la gestion des requêtes clients. En automatisant les réponses via un chatbot intégré à une base de données, il élimine les frustrations liées aux délais de réponse. Les utilisateurs bénéficient d'une interaction fluide et instantanée, avec des visualisations de données qui facilitent la compréhension et l'analyse des informations.
Workflow n8n Postgres, QuickCharts, chatbot : étapes du workflow
Étape 1 : le workflow est déclenché par la réception d'un message de chat.
- Étape 1 : une requête SQL est exécutée sur la base de données Postgres pour récupérer les données pertinentes.
- Étape 2 : en fonction des résultats, le système utilise des agents pour générer des réponses adaptées et des graphiques via QuickCharts.
- Étape 3 : les informations sont structurées à l'aide de nœuds 'Sticky Note' pour une meilleure présentation.
- Étape 4 : le chatbot répond à l'utilisateur avec les données et les visualisations demandées.
Workflow n8n Postgres, QuickCharts, chatbot : guide de personnalisation
Pour personnaliser ce workflow, vous pouvez modifier les paramètres de la requête SQL dans le nœud 'Execute SQL Query' pour adapter les données récupérées. Il est également possible de changer les configurations des agents pour ajuster les réponses générées par le chatbot. Pour intégrer d'autres outils, vous pouvez ajouter des nœuds supplémentaires ou modifier les nœuds existants pour répondre à des besoins spécifiques. Assurez-vous de sécuriser les données en configurant correctement les accès à la base de données et en surveillant les performances du flux.