Assistant IA pour dialoguer avec Airtable et analyser des données
Avancé
Ceci est unEngineering, AIworkflow d'automatisation du domainecontenant 41 nœuds.Utilise principalement des nœuds comme If, Set, Merge, Switch, Airtable, combinant la technologie d'intelligence artificielle pour une automatisation intelligente. Assistant IA pour dialoguer et analyser des données avec Airtable
Prérequis
- •Clé API Airtable
- •Peut nécessiter les informations d'identification d'authentification de l'API cible
- •Clé API OpenAI
Nœuds utilisés (41)
Catégorie
Aperçu du workflow
Visualisation des connexions entre les nœuds, avec support du zoom et du déplacement
Exporter le workflow
Copiez la configuration JSON suivante dans n8n pour importer et utiliser ce workflow
{
"nodes": [
{
"id": "799d2e0c-29b9-494c-b11a-d79c7ed4a06d",
"name": "Modèle de chat OpenAI",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
920,
480
],
"parameters": {
"options": {}
},
"credentials": {
"openAiApi": {
"id": "zJhr5piyEwVnWtaI",
"name": "OpenAi club"
}
},
"typeVersion": 1
},
{
"id": "6254ef4e-9699-404e-96a4-569326cce48d",
"name": "Agent IA",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
1160,
200
],
"parameters": {
"text": "={{ $('When chat message received').item.json.chatInput }}",
"agent": "openAiFunctionsAgent",
"options": {
"maxIterations": 10,
"systemMessage": "You are Airtable assistant. \nYou need to process user's requests and run relevant tools for that. \n\nPlan and execute in right order runs of tools to get data for user's request.\n\nFeel free to ask questions before do actions - especially if you noticed some inconcistency in user requests that might be error/misspelling. \n\nIMPORTANT Always check right table and base ids before doing queries.\n\nIMPORTANT Use Code function to do aggregation functions that requires math like - count, sum, average and etc. Aggegation function could be recognized by words like \"how many\",\"count\",\"what number\" and etc.\nUse Code function to generate graph and images.\n\nIMPORTANT If search with filter failed - try to fetch records without filter\n\nIMPORTANT Ask yourself before answering - am I did everything is possible? Is the answer is right? Is the answer related to user request?\n\nIMPORTANT Always return in response name of Base and Table where records from. "
},
"promptType": "define"
},
"typeVersion": 1.6
},
{
"id": "227a5427-c270-47dc-bc08-4bb321314926",
"name": "Note adhésive",
"type": "n8n-nodes-base.stickyNote",
"position": [
1740,
620
],
"parameters": {
"height": 80,
"content": "### Replace Mapbox public key - <your_public_key> in code"
},
"typeVersion": 1
},
{
"id": "667751f4-9815-45b7-8dd2-9a0821a7a5a7",
"name": "Note adhésive1",
"type": "n8n-nodes-base.stickyNote",
"position": [
840,
640
],
"parameters": {
"height": 80,
"content": "### Replace OpenAI connection"
},
"typeVersion": 1
},
{
"id": "a9cdec25-4167-44a9-9d3c-fb04aac7bb32",
"name": "Window Buffer Mémoire",
"type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
"position": [
1080,
480
],
"parameters": {
"sessionKey": "={{ $('When chat message received').item.json.sessionId }}",
"sessionIdType": "customKey"
},
"typeVersion": 1.3
},
{
"id": "dfab4eb2-ba30-4756-8a52-5d73de9fba53",
"name": "À la réception du message",
"type": "@n8n/n8n-nodes-langchain.chatTrigger",
"position": [
940,
200
],
"webhookId": "abf9ab75-eaca-4b91-b3ba-c0f83d3daba4",
"parameters": {
"options": {}
},
"typeVersion": 1.1
},
{
"id": "259e3d13-ca92-4756-af69-34065dbe08f3",
"name": "Déclencheur d'exécution",
"type": "n8n-nodes-base.executeWorkflowTrigger",
"position": [
760,
1340
],
"parameters": {},
"typeVersion": 1
},
{
"id": "5b80c2c8-7649-40f2-b9be-d090d8bd5ae9",
"name": "Response",
"type": "n8n-nodes-base.set",
"position": [
2740,
1360
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "cfdbe2f5-921e-496d-87bd-9c57fdc22a7a",
"name": "response",
"type": "object",
"value": "={{$json}}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "761f5593-f85c-44cd-abbd-aeac78bc31f8",
"name": "Commutateur",
"type": "n8n-nodes-base.switch",
"position": [
980,
1320
],
"parameters": {
"rules": {
"values": [
{
"outputKey": "get_bases",
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"operator": {
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $('Execute Workflow Trigger').item.json.command }}",
"rightValue": "get_bases"
}
]
},
"renameOutput": true
},
{
"outputKey": "get_base_tables_schema",
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "26a3ffe8-c8a6-4564-8d18-5494a8059372",
"operator": {
"name": "filter.operator.equals",
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $('Execute Workflow Trigger').item.json.command }}",
"rightValue": "get_base_tables_schema"
}
]
},
"renameOutput": true
},
{
"outputKey": "search",
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "0f51cc26-2e42-42e1-a5c2-cb1d2e384962",
"operator": {
"name": "filter.operator.equals",
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $('Execute Workflow Trigger').item.json.command }}",
"rightValue": "search"
}
]
},
"renameOutput": true
},
{
"outputKey": "code",
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "51031140-5ceb-48aa-9f33-d314131a9653",
"operator": {
"name": "filter.operator.equals",
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $('Execute Workflow Trigger').item.json.command }}",
"rightValue": "code"
}
]
},
"renameOutput": true
}
]
},
"options": {}
},
"typeVersion": 3.2
},
{
"id": "d6252c5b-a820-4ded-b59b-ab2fb2e277c3",
"name": "Agréger",
"type": "n8n-nodes-base.aggregate",
"position": [
1780,
980
],
"parameters": {
"options": {},
"aggregate": "aggregateAllItemData"
},
"typeVersion": 1
},
{
"id": "1442ca2e-1793-4029-b398-61d6e6f1c346",
"name": "Agréger1",
"type": "n8n-nodes-base.aggregate",
"position": [
1780,
1140
],
"parameters": {
"options": {},
"aggregate": "aggregateAllItemData"
},
"typeVersion": 1
},
{
"id": "a81b4dcc-c999-43be-a0ea-e37f3c7c9f9d",
"name": "Fusionner",
"type": "n8n-nodes-base.merge",
"position": [
1960,
1360
],
"parameters": {},
"typeVersion": 3
},
{
"id": "8029213c-fd8a-4673-a2a0-11b90fd23971",
"name": "Agréger2",
"type": "n8n-nodes-base.aggregate",
"position": [
2260,
1360
],
"parameters": {
"options": {
"mergeLists": true
},
"fieldsToAggregate": {
"fieldToAggregate": [
{
"fieldToAggregate": "records"
}
]
}
},
"typeVersion": 1
},
{
"id": "f5f99038-9d19-49ed-9f50-3cd0270bf9ce",
"name": "If1",
"type": "n8n-nodes-base.if",
"position": [
2120,
1720
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "fcb24127-53f9-4498-b0fd-463bd4966ac9",
"operator": {
"type": "string",
"operation": "notExists",
"singleValue": true
},
"leftValue": "={{ $json.data[0].attachments[0].file_id }}",
"rightValue": ""
},
{
"id": "016ecba7-f6af-4881-a7d6-780dcb43223c",
"operator": {
"type": "string",
"operation": "notExists",
"singleValue": true
},
"leftValue": "={{ $json.data[0].content.find(x=>x.type==\"image_file\").image_file.file_id }}",
"rightValue": ""
}
]
}
},
"typeVersion": 2.2
},
{
"id": "abc7ddae-9ca9-4cf6-89a4-a63da8c1e036",
"name": "Response1",
"type": "n8n-nodes-base.set",
"position": [
2760,
1720
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "cfdbe2f5-921e-496d-87bd-9c57fdc22a7a",
"name": "response",
"type": "string",
"value": "={{ $json.data.url.replace('org/','org/dl/') }}"
}
]
},
"includeOtherFields": true
},
"typeVersion": 3.4
},
{
"id": "6f40d50f-70e8-4b64-aa42-ae9262fb8381",
"name": "Note adhésive4",
"type": "n8n-nodes-base.stickyNote",
"position": [
2080,
1520
],
"parameters": {
"width": 160,
"height": 80,
"content": "### Replace Airtable connection"
},
"typeVersion": 1
},
{
"id": "de99a161-5ab3-4b54-bdf7-340d74aa5a93",
"name": "Note adhésive5",
"type": "n8n-nodes-base.stickyNote",
"position": [
1740,
1600
],
"parameters": {
"width": 160,
"height": 80,
"content": "### Replace OpenAI connection"
},
"typeVersion": 1
},
{
"id": "c1e030fd-4449-43ca-a4e7-a863f9487614",
"name": "Note adhésive6",
"type": "n8n-nodes-base.stickyNote",
"position": [
1540,
860
],
"parameters": {
"width": 160,
"height": 80,
"content": "### Replace Airtable connection"
},
"typeVersion": 1
},
{
"id": "4375d3a4-0b3b-4de6-9db7-42af4148af2b",
"name": "Note adhésive3",
"type": "n8n-nodes-base.stickyNote",
"position": [
1360,
1900
],
"parameters": {
"width": 1180,
"height": 80,
"content": "### Replace OpenAI connection"
},
"typeVersion": 1
},
{
"id": "138f813c-d0b0-4a2b-8833-69f1decc9253",
"name": "Note adhésive7",
"type": "n8n-nodes-base.stickyNote",
"position": [
700,
0
],
"parameters": {
"color": 6,
"width": 1320,
"height": 780,
"content": "### Workflow 1"
},
"typeVersion": 1
},
{
"id": "ca87c7b7-ab34-4ff9-8d74-cef90e6f1e5e",
"name": "Note adhésive8",
"type": "n8n-nodes-base.stickyNote",
"position": [
700,
840
],
"parameters": {
"color": 6,
"width": 2240,
"height": 1180,
"content": "### Workflow 2"
},
"typeVersion": 1
},
{
"id": "a5cdf41a-f2ca-4203-94ce-45795395ea92",
"name": "Note adhésive9",
"type": "n8n-nodes-base.stickyNote",
"position": [
300,
680
],
"parameters": {
"color": 7,
"width": 330.5152611046425,
"height": 239.5888196628349,
"content": "### ... or watch set up video [20 min]\n[](https://youtu.be/SotqsAZEhdc)\n"
},
"typeVersion": 1
},
{
"id": "697889c4-15e7-4099-89b8-f4e2e3a3abac",
"name": "Note adhésive10",
"type": "n8n-nodes-base.stickyNote",
"position": [
0,
0
],
"parameters": {
"color": 7,
"width": 636,
"height": 657,
"content": "\n## AI Agent to chat with Airtable and analyze data\n**Made by [Mark Shcherbakov](https://www.linkedin.com/in/marklowcoding/) from community [5minAI](https://www.skool.com/5minai)**\n\nEngaging with data stored in Airtable often requires manual navigation and time-consuming searches. This workflow allows users to interact conversationally with their datasets, retrieving essential information quickly while minimizing the need for complex queries.\n\nThis workflow enables an AI agent to facilitate chat interactions over Airtable data. The agent can:\n- Retrieve order records, product details, and other relevant data.\n- Execute mathematical functions to analyze data such as calculating averages and totals.\n- Optionally generate maps for geographic data visualization.\n\n1. **Dynamic Data Retrieval**: The agent uses user prompts to dynamically query the dataset.\n2. **Memory Management**: It retains context during conversations, allowing users to engage in a more natural dialogue.\n3. **Search and Filter Capabilities**: Users can perform tailored searches with specific parameters or filters to refine their results."
},
"typeVersion": 1
},
{
"id": "a9f7c4fd-c07a-4c7c-875d-74b27e3f1fbf",
"name": "Note adhésive11",
"type": "n8n-nodes-base.stickyNote",
"position": [
0,
680
],
"parameters": {
"color": 7,
"width": 280,
"height": 346,
"content": "### Set up steps\n\n1. **Separate workflows**:\n\t- Create additional workflow and move there Workflow 2.\n\n2. **Replace credentials**:\n\t- Replace connections and credentials in all nodes.\n\n3. **Start chat**:\n\t- Ask questions and don't forget to mention required base name."
},
"typeVersion": 1
},
{
"id": "0c86638f-7220-415d-a920-13761da925a6",
"name": "Search records",
"type": "@n8n/n8n-nodes-langchain.toolWorkflow",
"position": [
1500,
480
],
"parameters": {
"name": "search",
"fields": {
"values": [
{
"name": "command",
"stringValue": "search"
}
]
},
"schemaType": "manual",
"workflowId": {
"__rl": true,
"mode": "list",
"value": "zVd0G4m33K6KrBvV",
"cachedResultName": "Airtable Agent Tools"
},
"description": "Search records in specific base and table.\n\n- Use Filter (optional) rules for filtering - describe what logic you want to see in filter including field names. \nIMPORTANT - specify all related fields with types for Filter query with right names based on schema. Tool doesn't know schema and type of fields.\n\n- Use Limit (optional) to get more/less records - default = All records. IMPORTANT use default value only when user ask to get all records for analysis.\n\n- Always try to limit list of fields based on user request or in case of number of fields > 30. IMPORTANT Use fields names only.\n \n- Sort by one/multiple fields if needed - order in array is order of level for sorting.\n\nInput example:\nbase_id - appHwXgLVrBujox4J\ntable_id - tblrGzFneREP5Dktl\nlimit - 100\nsort (optional) - [{\"field\":\"Name\",\"direction\":\"asc\"}]\nfilter_desc (optional) - field Name (string) should be equal/contains Mark\nfields (optional) - [\"Name\",\"Email\"]\n\nOutput example:\nRecord 1 - value 1, value 2",
"inputSchema": "{\n \"type\": \"object\",\n \"properties\": {\n \"base_id\": {\n \"type\": \"string\",\n \"description\": \"ID of the base to search in\"\n },\n \"table_id\": {\n \"type\": \"string\",\n \"description\": \"ID of the table to search in\"\n },\n \"limit\": {\n \"type\": \"number\",\n \"description\": \"Number of records to retrieve (default is all records)\"\n },\n \"filter_desc\": {\n \"type\": \"string\",\n \"description\": \"Text description of the filter logic\"\n },\n \"sort\": {\n \"type\": \"array\",\n \"items\": {\n \"type\": \"object\",\n \"properties\": {\n \"field\": { \"type\": \"string\" },\n \"direction\": { \"type\": \"string\", \"enum\": [\"asc\", \"desc\"] }\n },\n \"required\": [\"field\", \"direction\"]\n },\n \"description\": \"Array of sorting rules for the query\"\n },\n \"fields\": {\n \"type\": \"array\",\n \"items\": { \"type\": \"string\" },\n \"description\": \"List of fields to retrieve\"\n }\n },\n \"required\": [\"base_id\", \"table_id\"]\n}",
"specifyInputSchema": true
},
"typeVersion": 1.2
},
{
"id": "7ba1d6ac-f1a2-4b8d-a9a5-ce92eaa4e7fa",
"name": "Process data with code",
"type": "@n8n/n8n-nodes-langchain.toolWorkflow",
"position": [
1640,
480
],
"parameters": {
"name": "code",
"fields": {
"values": [
{
"name": "command",
"stringValue": "code"
}
]
},
"schemaType": "manual",
"workflowId": {
"__rl": true,
"mode": "list",
"value": "zVd0G4m33K6KrBvV",
"cachedResultName": "Airtable Agent Tools"
},
"description": "Process data with code. Use for math functions and image (graphs) generation. \nIMPORTANT Provide raw data only, don't preprocess or use math functions by yourself\n\nInput example:\nrequest - Count average\ndata - 1,2,3\n\nOutput example:\nAverage is 2\nImage file",
"inputSchema": "{\n \"type\": \"object\",\n \"properties\": {\n \"request\": {\n \"type\": \"string\",\n \"description\": \"Description of the operation to perform.\"\n },\n \"data\": {\n \"type\": \"string\",\n \"description\": \"Stringified data - JSON, strings, arrays and etc.\"\n }\n },\n \"required\": [\"request\", \"data\"]\n}",
"specifyInputSchema": true
},
"typeVersion": 1.2
},
{
"id": "3754175c-6f74-4750-b2e7-00e2bd3caf6d",
"name": "Create map image",
"type": "@n8n/n8n-nodes-langchain.toolCode",
"position": [
1800,
480
],
"parameters": {
"name": "create_map",
"jsCode": "// Example: convert the incoming query to uppercase and return it\n\nreturn `https://api.mapbox.com/styles/v1/mapbox/streets-v12/static/${query.markers}/-96.9749,41.8219,3.31,0/800x500?before_layer=admin-0-boundary&access_token=<your_public_key>`;",
"schemaType": "manual",
"description": "Create link with image for map graph.\nUse addresses' longitude and latitude to create input data.\n\nInput Example:\npin-s+555555(-74.006,40.7128),pin-s+555555(-118.2437,34.0522)\n\nOutput Example:\nImage link.",
"inputSchema": "{\n\"type\": \"object\",\n\"properties\": {\n\t\"markers\": {\n\t\t\"type\": \"string\",\n\t\t\"description\": \"List of markers with longitude and latitude data separated by comma. Keep the same color 555555|Example: pin-s+555555(-74.006,40.7128),pin-s+555555(-118.2437,34.0522)\"\n\t\t}\n\t}\n}",
"specifyInputSchema": true
},
"typeVersion": 1.1
},
{
"id": "135078ea-6a3f-4aee-9f60-c6d5832e446e",
"name": "Get list of bases",
"type": "@n8n/n8n-nodes-langchain.toolWorkflow",
"position": [
1220,
480
],
"parameters": {
"name": "get_bases",
"fields": {
"values": [
{
"name": "command",
"stringValue": "get_bases"
}
]
},
"workflowId": {
"__rl": true,
"mode": "list",
"value": "zVd0G4m33K6KrBvV",
"cachedResultName": "Airtable Agent Tools"
},
"description": "Fetches the list of available bases.\n\nOutput:\n- List of bases with their IDs and names."
},
"typeVersion": 1.2
},
{
"id": "cd4781d0-f873-4aea-951c-6809358c1db6",
"name": "Get base schema",
"type": "@n8n/n8n-nodes-langchain.toolWorkflow",
"position": [
1360,
480
],
"parameters": {
"name": "get_base_tables_schema",
"fields": {
"values": [
{
"name": "command",
"stringValue": "get_base_tables_schema"
}
]
},
"schemaType": "manual",
"workflowId": {
"__rl": true,
"mode": "list",
"value": "zVd0G4m33K6KrBvV",
"cachedResultName": "Airtable Agent Tools"
},
"description": "Fetches the schema of tables in a specific base by id.\n\nInput:\nbase_id: appHwXgLVrBujox4J\n\nOutput:\ntable 1: field 1 - type string, fields 2 - type number",
"inputSchema": "{\n \"type\": \"object\",\n \"properties\": {\n \"base_id\": {\n \"type\": \"string\",\n \"description\": \"ID of the base to retrieve the schema for. Format - appHwXgLVrBujox4J\"\n }\n },\n \"required\": [\"base_id\"]\n}",
"specifyInputSchema": true
},
"typeVersion": 1.2
},
{
"id": "45c8b2eb-f43a-48b1-a270-9caeda9da0b0",
"name": "Get Bases",
"type": "n8n-nodes-base.airtable",
"position": [
1580,
980
],
"parameters": {
"options": {},
"resource": "base"
},
"credentials": {
"airtableTokenApi": {
"id": "xZwG0YpqsxpWrzVM",
"name": "Mark Airtable account"
}
},
"typeVersion": 2.1
},
{
"id": "bb8036bc-1c23-461b-bd03-2461e31c6cb6",
"name": "Get Base/Tables schema",
"type": "n8n-nodes-base.airtable",
"position": [
1580,
1140
],
"parameters": {
"base": {
"__rl": true,
"mode": "id",
"value": "={{ $('Execute Workflow Trigger').item.json.query.base_id }}"
},
"resource": "base",
"operation": "getSchema"
},
"credentials": {
"airtableTokenApi": {
"id": "xZwG0YpqsxpWrzVM",
"name": "Mark Airtable account"
}
},
"typeVersion": 2.1
},
{
"id": "dab309d9-3629-44ba-9f0a-ede55f96488f",
"name": "If filter description exists",
"type": "n8n-nodes-base.if",
"position": [
1340,
1360
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "fcb24127-53f9-4498-b0fd-463bd4966ac9",
"operator": {
"type": "string",
"operation": "notExists",
"singleValue": true
},
"leftValue": "={{ $('Execute Workflow Trigger').item.json.query.filter_desc }}",
"rightValue": ""
}
]
}
},
"typeVersion": 2.2
},
{
"id": "4cc416aa-50bd-4b60-ae51-887c4ee97c88",
"name": "Airtable - Search records",
"type": "n8n-nodes-base.httpRequest",
"onError": "continueErrorOutput",
"position": [
2100,
1360
],
"parameters": {
"url": "=https://api.airtable.com/v0/{{ $('Execute Workflow Trigger').item.json.query.base_id }}/{{ $('Execute Workflow Trigger').item.json.query.table_id }}/listRecords",
"method": "POST",
"options": {
"pagination": {
"pagination": {
"parameters": {
"parameters": [
{
"name": "offset",
"type": "body",
"value": "={{ $response.body.offset}}"
}
]
},
"completeExpression": "={{ $response.body.offset==undefined}}",
"paginationCompleteWhen": "other"
}
}
},
"jsonBody": "={{ \n Object.fromEntries(\n Object.entries({\n sort: $('Execute Workflow Trigger').item.json.query.sort,\n limit: $('Execute Workflow Trigger').item.json.query.limit,\nfields: $('Execute Workflow Trigger').item.json.query.fields,\nfilterByFormula: $('Merge').item.json.choices == undefined ? undefined : JSON.parse($json.choices[0].message.content).filter\n }).filter(([key, value]) => value !== undefined)\n )\n}}",
"sendBody": true,
"specifyBody": "json",
"authentication": "predefinedCredentialType",
"nodeCredentialType": "airtableTokenApi"
},
"credentials": {
"httpQueryAuth": {
"id": "1DXeuNaLSixqGPaU",
"name": "Query Auth account Youtube"
},
"airtableTokenApi": {
"id": "xZwG0YpqsxpWrzVM",
"name": "Mark Airtable account"
}
},
"typeVersion": 4.2
},
{
"id": "9dc71d31-8499-4b69-b87c-898217447d50",
"name": "OpenAI - Generate search filter",
"type": "n8n-nodes-base.httpRequest",
"position": [
1760,
1420
],
"parameters": {
"url": "=https://api.openai.com/v1/chat/completions",
"method": "POST",
"options": {},
"jsonBody": "={\n \"model\": \"gpt-4o-mini\",\n \"messages\": [\n {\n \"role\": \"system\",\n \"content\": {{ JSON.stringify($('Set schema and prompt').item.json.prompt) }}\n },\n {\n \"role\": \"user\",\n \"content\": \"{{ $('Execute Workflow Trigger').item.json.query.filter_desc }}\"\n }],\n \"response_format\":{ \"type\": \"json_schema\", \"json_schema\": {{ $('Set schema and prompt').item.json.schema }}\n\n }\n }",
"sendBody": true,
"specifyBody": "json",
"authentication": "predefinedCredentialType",
"nodeCredentialType": "openAiApi"
},
"credentials": {
"openAiApi": {
"id": "zJhr5piyEwVnWtaI",
"name": "OpenAi club"
}
},
"typeVersion": 4.2
},
{
"id": "16e4ea97-ea73-45a0-aa88-0f9a2969a6a3",
"name": "Définir schema and prompt",
"type": "n8n-nodes-base.set",
"position": [
1560,
1420
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "dc09a5b4-ff6a-4cee-b87e-35de7336ac05",
"name": "prompt",
"type": "string",
"value": "=Analyse user request for Airtable filtration. User filter rules to build right formula. Think smart about filter (e.g. instead of search where Name equal to value - search where name contains lowercase value)\nIMPORTANT Check examples and best practices before building formula. \n\nIMPORTANT best practices:\n\nSEARCH(LOWER('example'), LOWER({Field})) ensures both the search term and field are compared in lowercase for consistent case-insensitive matching\n\nIMPORTANT Examples:\n\n- AND(SEARCH('urgent', {Notes}), {Priority} > 3) fetch records where “Notes” contain “urgent” and “Priority” is greater than 3\n- AND({Status} = 'Pending', IS_BEFORE({Due Date}, TODAY())) fetch records where “Status” is “Pending” and “Due Date” is before today\n- OR(SEARCH('error', {Logs}), SEARCH('warning', {Logs})) fetch records where “Logs” contain “error” or “warning”\n- AND(LEN({Description}) > 10, {Price} > 50) fetch records where “Description” is longer than 10 characters and “Price” is greater than 50\n- RECORD_ID() = 'rec12345' fetch a specific record by its ID\n- SEARCH('rec67890', ARRAYJOIN({Linked Records}, ',')) fetch records linked to a specific record ID rec67890\n- AND(SEARCH('rec12345', ARRAYJOIN({Linked Records}, ',')), {Status} = 'Active') fetch records where “Linked Records” contain rec12345 and “Status” is “Active”\n\nFormula rules:\nOperators - =,!=,>,<,>=,<= \n- AND(condition1, condition2, ...) logical AND\n- OR(condition1, condition2, ...) logical OR\n- NOT(condition) logical NOT\n- SEARCH('substring', {Field}) finds position of substring, case-insensitive\n- FIND('substring', {Field}) finds position of substring, case-sensitive\n- IS_BEFORE({Date}, 'YYYY-MM-DD') checks if date is before\n- IS_AFTER({Date}, 'YYYY-MM-DD') checks if date is after\n- IS_SAME({Date1}, {Date2}, 'unit') checks if dates are the same by unit\n- RECORD_ID() = 'recXXXXXX' filters by record ID\n- {Field} = '' field is blank\n- {Field} != '' field is not blank\n- ARRAYJOIN({Linked Field}, ',') joins linked records into a string\n- LOWER({Field}) converts to lowercase for case-insensitive comparison\n- UPPER({Field}) converts to uppercase for case-insensitive comparison\n- VALUE({Text}) converts text to number for numeric comparisons\n- LEN({Field}) gets text length\n- ROUND(number, precision) rounds number\n- TODAY() current date\n- NOW() current timestamp\n- IF(condition, true_value, false_value) conditional logic\n- DATETIME_FORMAT({Date}, 'format') formats date as text\n- DATETIME_DIFF(date1, date2, 'unit') difference between dates\n- DATEADD({Date}, number, 'unit') adds time to date\n- LEFT({Text}, number) extracts leftmost characters\n- RIGHT({Text}, number) extracts rightmost characters\n- AND({Field1} = 'Value1', {Field2} > 50) multiple conditions\n- SEARCH('Value', {Field}) substring match\n- ROUND({Field1} / {Field2}, 2) numeric calculation\n- AND(IS_BEFORE({Date}, TODAY()), {Status} = 'Active') filter by date and status\n- ISERROR(expression) checks if an expression has an error\n- ABS(number) absolute value\n- MIN(value1, value2) minimum value\n- MAX(value1, value2) maximum value\n\n"
},
{
"id": "4e0f9af6-517f-42af-9ced-df0e8a7118b0",
"name": "schema",
"type": "string",
"value": "={\n \"name\": \"filter\",\n \"schema\": {\n \"type\": \"object\",\n \"properties\": {\n \"filter\": {\n \"type\": \"string\"\n }\n },\n \"required\": [\n \"filter\"\n ],\n \"additionalProperties\": false\n },\n \"strict\": true\n}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "6e670074-8508-4282-9c40-600cc445b10f",
"name": "Upload file to get link",
"type": "n8n-nodes-base.httpRequest",
"onError": "continueRegularOutput",
"position": [
2580,
1720
],
"parameters": {
"url": "=https://tmpfiles.org/api/v1/upload",
"method": "POST",
"options": {},
"sendBody": true,
"contentType": "multipart-form-data",
"bodyParameters": {
"parameters": [
{
"name": "file",
"parameterType": "formBinaryData",
"inputDataFieldName": "data"
}
]
}
},
"typeVersion": 4.2
},
{
"id": "b7569d19-3a10-41e5-932b-4be04260a58e",
"name": "OpenAI - Télécharger fichier",
"type": "n8n-nodes-base.httpRequest",
"position": [
2360,
1720
],
"parameters": {
"url": "=https://api.openai.com/v1/files/{{ $json.data[0].attachments[0]?.file_id ?? $json.data[0].content.find(x=>x.type==\"image_file\")?.image_file.file_id }}/content",
"options": {},
"sendHeaders": true,
"authentication": "predefinedCredentialType",
"headerParameters": {
"parameters": [
{
"name": "OpenAI-Beta",
"value": "assistants=v2"
}
]
},
"nodeCredentialType": "openAiApi"
},
"credentials": {
"openAiApi": {
"id": "vBLHyjEnMK9EaWwQ",
"name": "Mark OpenAi "
}
},
"typeVersion": 4.2
},
{
"id": "bf378b21-07fb-4f9e-bfc5-9623ebcb8236",
"name": "OpenAI - Get messages",
"type": "n8n-nodes-base.httpRequest",
"position": [
1960,
1720
],
"parameters": {
"url": "=https://api.openai.com/v1/threads/{{ $('OpenAI - Create thread').item.json.id }}/messages",
"options": {},
"sendHeaders": true,
"authentication": "predefinedCredentialType",
"headerParameters": {
"parameters": [
{
"name": "OpenAI-Beta",
"value": "assistants=v2"
}
]
},
"nodeCredentialType": "openAiApi"
},
"credentials": {
"openAiApi": {
"id": "zJhr5piyEwVnWtaI",
"name": "OpenAi club"
}
},
"typeVersion": 4.2
},
{
"id": "9874eec1-61e2-45fe-8c57-556957a15473",
"name": "OpenAI - Run assistant",
"type": "n8n-nodes-base.httpRequest",
"position": [
1760,
1720
],
"parameters": {
"url": "=https://api.openai.com/v1/threads/{{ $('OpenAI - Create thread').item.json.id }}/runs",
"method": "POST",
"options": {},
"sendBody": true,
"sendHeaders": true,
"authentication": "predefinedCredentialType",
"bodyParameters": {
"parameters": [
{
"name": "assistant_id",
"value": "asst_PGUuvzEGJWOE8p8vwV56INLO"
},
{
"name": "stream",
"value": "={{true}}"
},
{
"name": "tool_choice",
"value": "={{ {\"type\": \"code_interpreter\"} }}"
},
{
"name": "tools",
"value": "={{ [{\"type\": \"code_interpreter\"}] }}"
}
]
},
"headerParameters": {
"parameters": [
{
"name": "OpenAI-Beta",
"value": "assistants=v2"
}
]
},
"nodeCredentialType": "openAiApi"
},
"credentials": {
"openAiApi": {
"id": "fLfRtaXbR0EVD0pl",
"name": "OpenAi account"
}
},
"typeVersion": 4.2
},
{
"id": "e5339ad2-36c7-40c5-846b-2bd242f41ea5",
"name": "OpenAI - Send message",
"type": "n8n-nodes-base.httpRequest",
"position": [
1560,
1720
],
"parameters": {
"url": "=https://api.openai.com/v1/threads/{{ $('OpenAI - Create thread').item.json.id }}/messages ",
"method": "POST",
"options": {},
"sendBody": true,
"sendHeaders": true,
"authentication": "predefinedCredentialType",
"bodyParameters": {
"parameters": [
{
"name": "role",
"value": "user"
},
{
"name": "content",
"value": "=Request:\n{{ $('Execute Workflow Trigger').item.json.query.request }}\n\nData:\n{{ $('Execute Workflow Trigger').item.json.query.data }}"
}
]
},
"headerParameters": {
"parameters": [
{
"name": "OpenAI-Beta",
"value": "assistants=v2"
}
]
},
"nodeCredentialType": "openAiApi"
},
"credentials": {
"openAiApi": {
"id": "fLfRtaXbR0EVD0pl",
"name": "OpenAi account"
}
},
"typeVersion": 4.2
},
{
"id": "5b822c15-af63-43f6-ac30-61a34dcd91ee",
"name": "OpenAI - Create thread",
"type": "n8n-nodes-base.httpRequest",
"position": [
1360,
1720
],
"parameters": {
"url": "https://api.openai.com/v1/threads",
"method": "POST",
"options": {},
"sendHeaders": true,
"authentication": "predefinedCredentialType",
"headerParameters": {
"parameters": [
{
"name": "OpenAI-Beta",
"value": "assistants=v2"
}
]
},
"nodeCredentialType": "openAiApi"
},
"credentials": {
"openAiApi": {
"id": "vBLHyjEnMK9EaWwQ",
"name": "Mark OpenAi "
}
},
"typeVersion": 4.2
}
],
"pinData": {},
"connections": {
"f5f99038-9d19-49ed-9f50-3cd0270bf9ce": {
"main": [
[
{
"node": "5b80c2c8-7649-40f2-b9be-d090d8bd5ae9",
"type": "main",
"index": 0
}
],
[
{
"node": "OpenAI - Download File",
"type": "main",
"index": 0
}
]
]
},
"Merge": {
"main": [
[
{
"node": "4cc416aa-50bd-4b60-ae51-887c4ee97c88",
"type": "main",
"index": 0
}
]
]
},
"Switch": {
"main": [
[
{
"node": "45c8b2eb-f43a-48b1-a270-9caeda9da0b0",
"type": "main",
"index": 0
}
],
[
{
"node": "bb8036bc-1c23-461b-bd03-2461e31c6cb6",
"type": "main",
"index": 0
}
],
[
{
"node": "dab309d9-3629-44ba-9f0a-ede55f96488f",
"type": "main",
"index": 0
}
],
[
{
"node": "5b822c15-af63-43f6-ac30-61a34dcd91ee",
"type": "main",
"index": 0
}
]
]
},
"Aggregate": {
"main": [
[
{
"node": "5b80c2c8-7649-40f2-b9be-d090d8bd5ae9",
"type": "main",
"index": 0
}
]
]
},
"45c8b2eb-f43a-48b1-a270-9caeda9da0b0": {
"main": [
[
{
"node": "Aggregate",
"type": "main",
"index": 0
}
]
]
},
"Aggregate1": {
"main": [
[
{
"node": "5b80c2c8-7649-40f2-b9be-d090d8bd5ae9",
"type": "main",
"index": 0
}
]
]
},
"Aggregate2": {
"main": [
[
{
"node": "5b80c2c8-7649-40f2-b9be-d090d8bd5ae9",
"type": "main",
"index": 0
}
]
]
},
"0c86638f-7220-415d-a920-13761da925a6": {
"ai_tool": [
[
{
"node": "AI Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"cd4781d0-f873-4aea-951c-6809358c1db6": {
"ai_tool": [
[
{
"node": "AI Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"3754175c-6f74-4750-b2e7-00e2bd3caf6d": {
"ai_tool": [
[
{
"node": "AI Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"135078ea-6a3f-4aee-9f60-c6d5832e446e": {
"ai_tool": [
[
{
"node": "AI Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"OpenAI Chat Model": {
"ai_languageModel": [
[
{
"node": "AI Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Window Buffer Memory": {
"ai_memory": [
[
{
"node": "AI Agent",
"type": "ai_memory",
"index": 0
}
]
]
},
"bf378b21-07fb-4f9e-bfc5-9623ebcb8236": {
"main": [
[
{
"node": "f5f99038-9d19-49ed-9f50-3cd0270bf9ce",
"type": "main",
"index": 0
}
]
]
},
"e5339ad2-36c7-40c5-846b-2bd242f41ea5": {
"main": [
[
{
"node": "9874eec1-61e2-45fe-8c57-556957a15473",
"type": "main",
"index": 0
}
]
]
},
"Set schema and prompt": {
"main": [
[
{
"node": "9dc71d31-8499-4b69-b87c-898217447d50",
"type": "main",
"index": 0
}
]
]
},
"bb8036bc-1c23-461b-bd03-2461e31c6cb6": {
"main": [
[
{
"node": "Aggregate1",
"type": "main",
"index": 0
}
]
]
},
"5b822c15-af63-43f6-ac30-61a34dcd91ee": {
"main": [
[
{
"node": "e5339ad2-36c7-40c5-846b-2bd242f41ea5",
"type": "main",
"index": 0
}
]
]
},
"OpenAI - Download File": {
"main": [
[
{
"node": "6e670074-8508-4282-9c40-600cc445b10f",
"type": "main",
"index": 0
}
]
]
},
"9874eec1-61e2-45fe-8c57-556957a15473": {
"main": [
[
{
"node": "bf378b21-07fb-4f9e-bfc5-9623ebcb8236",
"type": "main",
"index": 0
}
]
]
},
"7ba1d6ac-f1a2-4b8d-a9a5-ce92eaa4e7fa": {
"ai_tool": [
[
{
"node": "AI Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"6e670074-8508-4282-9c40-600cc445b10f": {
"main": [
[
{
"node": "abc7ddae-9ca9-4cf6-89a4-a63da8c1e036",
"type": "main",
"index": 0
}
]
]
},
"Execute Workflow Trigger": {
"main": [
[
{
"node": "Switch",
"type": "main",
"index": 0
}
]
]
},
"4cc416aa-50bd-4b60-ae51-887c4ee97c88": {
"main": [
[
{
"node": "Aggregate2",
"type": "main",
"index": 0
}
],
[
{
"node": "5b80c2c8-7649-40f2-b9be-d090d8bd5ae9",
"type": "main",
"index": 0
}
]
]
},
"When chat message received": {
"main": [
[
{
"node": "AI Agent",
"type": "main",
"index": 0
}
]
]
},
"dab309d9-3629-44ba-9f0a-ede55f96488f": {
"main": [
[
{
"node": "Merge",
"type": "main",
"index": 0
}
],
[
{
"node": "Set schema and prompt",
"type": "main",
"index": 0
}
]
]
},
"9dc71d31-8499-4b69-b87c-898217447d50": {
"main": [
[
{
"node": "Merge",
"type": "main",
"index": 1
}
]
]
}
}
}Foire aux questions
Comment utiliser ce workflow ?
Copiez le code de configuration JSON ci-dessus, créez un nouveau workflow dans votre instance n8n et sélectionnez "Importer depuis le JSON", collez la configuration et modifiez les paramètres d'authentification selon vos besoins.
Dans quelles scénarios ce workflow est-il adapté ?
Avancé - Ingénierie, Intelligence Artificielle
Est-ce payant ?
Ce workflow est entièrement gratuit et peut être utilisé directement. Veuillez noter que les services tiers utilisés dans le workflow (comme l'API OpenAI) peuvent nécessiter un paiement de votre part.
Workflows recommandés
Assistant IA intelligent : Discuter avec les fichiers de Supabase Storage et Google Drive
AIintelligentassistant：与Supabase存储etGoogle Drive文件对话
If
Set
Wait
+
If
Set
Wait
62 NœudsMark Shcherbakov
Ingénierie
Agent IA qui dialogue avec les fichiers de Supabase Storage
与Supabase存储中文件对话deAIintelligent体
If
Merge
Switch
+
If
Merge
Switch
33 NœudsMark Shcherbakov
Ingénierie
Modèle de contrôle d'accès par proxy
Contrôle d'accès pour agents IA avec Airtable et Telegram (RBAC)
If
Set
Airtable
+
If
Set
Airtable
36 NœudsMario
Ingénierie
Explorer les nœuds n8n dans la bibliothèque de références visuelles
Explorer les nœuds n8n dans la base de références visuelles
If
Ftp
Set
+
If
Ftp
Set
113 NœudsI versus AI
Autres
Extraction et analyse des insights des commentaires YouTube via le chat avec un agent IA
viaAIintelligent体chatextractionetanalyseYouTube评论洞察
Set
Switch
Http Request
+
Set
Switch
Http Request
29 NœudsMark Shcherbakov
Intelligence Artificielle
AIe-mail分诊与GPT-4警报系统及Telegramnotification
AIe-mail分诊与GPT-4警报系统及Telegramnotification
If
Set
Gmail
+
If
Set
Gmail
104 NœudsPeter Joslyn
Support
Informations sur le workflow
Niveau de difficulté
Avancé
Nombre de nœuds41
Catégorie2
Types de nœuds15
Description de la difficulté
Auteur
Mark Shcherbakov
@lowcodingdevI am a business analyst with a development background, dedicated to helping small businesses and entrepreneurs leverage cloud services for increased efficiency. My expertise lies in automating manual workflows, integrating data from multiple cloud service providers, creating insightful dashboards, and building custom CRM systems.
Liens externes
Voir sur n8n.io →
Partager ce workflow