家居装饰AI（Google Nano Banana）- Santhej Kallada
上級
これはContent Creation, Multimodal AI分野の自動化ワークフローで、28個のノードを含みます。主にIf, Set, Code, Merge, Airtableなどのノードを使用。 Google Geminiを基盤としたAI画像生成・編集およびTelegramボット
前提条件
- •Airtable API Key
- •Telegram Bot Token
- •Google Drive API認証情報
- •ターゲットAPIの認証情報が必要な場合あり
使用ノード (28)
ワークフロープレビュー
ノード接続関係を可視化、ズームとパンをサポート
ワークフローをエクスポート
以下のJSON設定をn8nにインポートして、このワークフローを使用できます
{
"id": "dOynwI3sAYdHex7x",
"meta": {
"instanceId": "d3c17a28b831505b1128b4be827611328e2ecd2d4b635d3c4ca5c08fd677a016",
"templateCredsSetupCompleted": true
},
"name": "Home Furnishing AI (Google Nano Banana) - Santhej Kallada",
"tags": [
{
"id": "o5lUbXtRS653224b",
"name": "tutorials",
"createdAt": "2025-10-29T07:23:26.446Z",
"updatedAt": "2025-10-29T07:23:26.446Z"
}
],
"nodes": [
{
"id": "47fbda3a-c350-4dc8-8e4d-a02b989b44fc",
"name": "Telegram トリガー",
"type": "n8n-nodes-base.telegramTrigger",
"position": [
-528,
1680
],
"webhookId": "fb264149-5f6f-41ef-9b49-aca9304879cc",
"parameters": {
"updates": [
"message"
],
"additionalFields": {}
},
"typeVersion": 1.2
},
{
"id": "54e2b068-775c-47d4-a1bc-9ddfe17e3d88",
"name": "If1",
"type": "n8n-nodes-base.if",
"position": [
-304,
1680
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "loose"
},
"combinator": "and",
"conditions": [
{
"id": "a43f58c6-dccc-41fd-bbaf-7bb3f299adc7",
"operator": {
"type": "object",
"operation": "exists",
"singleValue": true
},
"leftValue": "={{ $json.message.photo[0] }}",
"rightValue": ""
}
]
},
"looseTypeValidation": true
},
"typeVersion": 2.2
},
{
"id": "093a6d6a-ae91-4906-a7f3-5e6a63b382ee",
"name": "Edit Fields1",
"type": "n8n-nodes-base.set",
"position": [
1040,
1760
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "2cb56c0e-aa56-4fe4-830e-8e42f2dee528",
"name": "message",
"type": "string",
"value": "={{ $('Telegram Trigger').item.json.message.text }}"
},
{
"id": "f7063ef9-30fe-4364-9ef2-043f55bcf591",
"name": "id",
"type": "string",
"value": "={{ $('Telegram Trigger').item.json.message.from.id }}"
},
{
"id": "e05afa5d-3824-41a6-8f7b-6cee3b0f5f36",
"name": "base_image_link",
"type": "string",
"value": "={{ $('Search records').item.json.base_image_link }}"
},
{
"id": "95219c2c-700b-41c6-a8d3-b635270a232f",
"name": "base_image64",
"type": "string",
"value": "={{ $json.data }}"
},
{
"id": "107928c3-4056-4e14-b7cd-13d6dccb0dac",
"name": "image_exits",
"type": "boolean",
"value": true
}
]
}
},
"typeVersion": 3.4
},
{
"id": "3a62cd46-9b63-4dac-ab7b-ea562e62a828",
"name": "Search records",
"type": "n8n-nodes-base.airtable",
"position": [
-80,
1696
],
"parameters": {
"base": {
"__rl": true,
"mode": "list",
"value": "apppCImnrYx31QQ4S",
"cachedResultUrl": "https://airtable.com/apppCImnrYx31QQ4S",
"cachedResultName": "Home Furnish AI"
},
"table": {
"__rl": true,
"mode": "list",
"value": "tblfIbgIrLUoUXFyA",
"cachedResultUrl": "https://airtable.com/apppCImnrYx31QQ4S/tblfIbgIrLUoUXFyA",
"cachedResultName": "Table 1"
},
"options": {},
"operation": "search",
"filterByFormula": "={ID} = \"{{ $('Telegram Trigger').item.json.message.from.id }}\""
},
"typeVersion": 2.1,
"alwaysOutputData": true
},
{
"id": "5ef4c48c-1c9e-4272-bb80-22b08720dec1",
"name": "画像編集",
"type": "n8n-nodes-base.httpRequest",
"position": [
1264,
1760
],
"parameters": {
"url": "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash-image-preview:generateContent",
"method": "POST",
"options": {},
"jsonBody": "={\n \"contents\": [{\n \"parts\": [\n {\n \"text\": {{ JSON.stringify($json.message) }}\n },\n {\n \"inline_data\": {\n \"mime_type\": \"image/jpeg\",\n \"data\": \"{{ $('Edit Fields1').item.json.base_image64 }}\"\n }\n }\n ]\n }]\n}",
"sendBody": true,
"jsonHeaders": "{\n \"x-goog-api-key\": \"put your api key here\",\n \"Content-Type\": \"application/json\"\n}",
"sendHeaders": true,
"specifyBody": "json",
"specifyHeaders": "json"
},
"typeVersion": 4.2
},
{
"id": "ea28d393-8e4f-47ce-8ac6-766aca28f795",
"name": "Send a photo message",
"type": "n8n-nodes-base.telegram",
"position": [
1840,
1824
],
"webhookId": "f12c1e45-334d-4629-bb73-f9caae62f4f1",
"parameters": {
"chatId": "={{ $('Telegram Trigger').item.json.message.from.id }}",
"operation": "sendPhoto",
"binaryData": true,
"additionalFields": {}
},
"typeVersion": 1.2
},
{
"id": "b4225b8e-eae3-4ad0-8ffe-bfe5932bf56a",
"name": "Create or update a record1",
"type": "n8n-nodes-base.airtable",
"position": [
1888,
1616
],
"parameters": {
"base": {
"__rl": true,
"mode": "list",
"value": "apppCImnrYx31QQ4S",
"cachedResultUrl": "https://airtable.com/apppCImnrYx31QQ4S",
"cachedResultName": "Home Furnish AI"
},
"table": {
"__rl": true,
"mode": "list",
"value": "tblfIbgIrLUoUXFyA",
"cachedResultUrl": "https://airtable.com/apppCImnrYx31QQ4S/tblfIbgIrLUoUXFyA",
"cachedResultName": "Table 1"
},
"columns": {
"value": {
"ID": "={{ $('Telegram Trigger').item.json.message.from.id }}",
"base_image_link": "={{ $json.webContentLink }}"
},
"schema": [
{
"id": "ID",
"type": "number",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "ID",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "base_image_link",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "base_image_link",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "baseImage_64",
"type": "string",
"display": true,
"removed": true,
"readOnly": false,
"required": false,
"displayName": "baseImage_64",
"defaultMatch": false,
"canBeUsedToMatch": true
}
],
"mappingMode": "defineBelow",
"matchingColumns": [
"ID"
],
"attemptToConvertTypes": false,
"convertFieldsToString": false
},
"options": {},
"operation": "upsert"
},
"typeVersion": 2.1
},
{
"id": "a7ce2cca-93a0-4b0d-8ba3-eb51d24e1362",
"name": "Download Image1",
"type": "n8n-nodes-base.telegram",
"position": [
-352,
928
],
"webhookId": "fc1c495a-005e-454e-b92b-66cf1f130634",
"parameters": {
"fileId": "={{ $json.message.photo[2].file_id }}",
"resource": "file",
"additionalFields": {}
},
"typeVersion": 1.2
},
{
"id": "fed96b49-66fa-4479-8c66-b89370907341",
"name": "Transform to base",
"type": "n8n-nodes-base.extractFromFile",
"position": [
-160,
928
],
"parameters": {
"options": {},
"operation": "binaryToPropery"
},
"typeVersion": 1
},
{
"id": "2bcd11a9-94a2-4b78-86a7-3e31529ee4c0",
"name": "Upload file",
"type": "n8n-nodes-base.googleDrive",
"position": [
-48,
1264
],
"parameters": {
"name": "={{ $json.result.file_unique_id }}",
"driveId": {
"__rl": true,
"mode": "list",
"value": "My Drive",
"cachedResultUrl": "https://drive.google.com/drive/my-drive",
"cachedResultName": "My Drive"
},
"options": {},
"folderId": {
"__rl": true,
"mode": "list",
"value": "1Wu1bv38J1izuaCRQmXE0RfEwKR3o3Iwi",
"cachedResultUrl": "https://drive.google.com/drive/folders/1Wu1bv38J1izuaCRQmXE0RfEwKR3o3Iwi",
"cachedResultName": "Home Furnishing AI"
}
},
"typeVersion": 3
},
{
"id": "1d00c8bf-191f-4086-a385-1840f56767a2",
"name": "マージ",
"type": "n8n-nodes-base.merge",
"position": [
208,
1264
],
"parameters": {},
"typeVersion": 3.2
},
{
"id": "7de5184c-2ab8-40b8-8e5d-af68f42c8f36",
"name": "集計",
"type": "n8n-nodes-base.aggregate",
"position": [
400,
1264
],
"parameters": {
"options": {},
"aggregate": "aggregateAllItemData"
},
"typeVersion": 1
},
{
"id": "845d6a60-14fb-4c94-9b97-fc44d04a54c2",
"name": "Edit Fields",
"type": "n8n-nodes-base.set",
"position": [
624,
1264
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "32b9d6c1-61ed-4f6a-8757-3209ebb7e4d4",
"name": "image_link",
"type": "string",
"value": "={{ $json.data[0].webContentLink }}"
},
{
"id": "55cb05ec-b1b8-4b54-9a08-fb6c545ef32b",
"name": "image_hash",
"type": "string",
"value": "={{ $json.data[1].data }}"
},
{
"id": "d0511aaf-95f2-46fb-afcb-ad0eefa18485",
"name": "id",
"type": "string",
"value": "={{ $('Telegram Trigger').item.json.message.from.id }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "53655955-c77f-4a95-ade0-021895f197ba",
"name": "Create or update a record",
"type": "n8n-nodes-base.airtable",
"disabled": true,
"position": [
864,
1264
],
"parameters": {
"base": {
"__rl": true,
"mode": "list",
"value": "apppCImnrYx31QQ4S",
"cachedResultUrl": "https://airtable.com/apppCImnrYx31QQ4S",
"cachedResultName": "Home Furnish AI"
},
"table": {
"__rl": true,
"mode": "list",
"value": "tblfIbgIrLUoUXFyA",
"cachedResultUrl": "https://airtable.com/apppCImnrYx31QQ4S/tblfIbgIrLUoUXFyA",
"cachedResultName": "Table 1"
},
"columns": {
"value": {
"ID": "={{ $json.id }}",
"base_image_link": "={{ $json.image_link }}"
},
"schema": [
{
"id": "id",
"type": "string",
"display": true,
"removed": false,
"readOnly": true,
"required": false,
"displayName": "id",
"defaultMatch": true
},
{
"id": "ID",
"type": "number",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "ID",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "base_image_link",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "base_image_link",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "baseImage_64",
"type": "string",
"display": true,
"removed": true,
"readOnly": false,
"required": false,
"displayName": "baseImage_64",
"defaultMatch": false,
"canBeUsedToMatch": true
}
],
"mappingMode": "defineBelow",
"matchingColumns": [
"ID"
],
"attemptToConvertTypes": false,
"convertFieldsToString": false
},
"options": {},
"operation": "upsert"
},
"typeVersion": 2.1
},
{
"id": "0b8c5466-58ca-47ea-89cf-5d5ee95e90ef",
"name": "Send a text message1",
"type": "n8n-nodes-base.telegram",
"position": [
1072,
1264
],
"webhookId": "7a160598-996f-4e02-ada6-2149a9a1c12b",
"parameters": {
"text": "Thank you for providing the image. Please let us know the edits you require",
"chatId": "={{ $('Telegram Trigger').item.json.message.from.id }}",
"additionalFields": {
"appendAttribution": false
}
},
"typeVersion": 1.2
},
{
"id": "e06f6e8f-5f00-43ee-bec3-75e4deca92a3",
"name": "ファイルから抽出",
"type": "n8n-nodes-base.extractFromFile",
"position": [
832,
1760
],
"parameters": {
"options": {},
"operation": "binaryToPropery"
},
"typeVersion": 1
},
{
"id": "97d63a01-3a54-4e4f-8941-928e98185b3b",
"name": "ファイルダウンロード",
"type": "n8n-nodes-base.httpRequest",
"position": [
672,
1760
],
"parameters": {
"url": "={{ $('Search records').item.json.base_image_link }}",
"options": {}
},
"typeVersion": 4.2
},
{
"id": "623e5e22-e227-4aa1-b866-ee74301bc407",
"name": "Upload file1",
"type": "n8n-nodes-base.googleDrive",
"position": [
1664,
1616
],
"parameters": {
"name": "={{ $('Telegram Trigger').item.json.message.from.id }}_base",
"driveId": {
"__rl": true,
"mode": "list",
"value": "My Drive"
},
"options": {},
"folderId": {
"__rl": true,
"mode": "list",
"value": "1Wu1bv38J1izuaCRQmXE0RfEwKR3o3Iwi",
"cachedResultUrl": "https://drive.google.com/drive/folders/1Wu1bv38J1izuaCRQmXE0RfEwKR3o3Iwi",
"cachedResultName": "Home Furnishing AI"
}
},
"typeVersion": 3
},
{
"id": "5db3e15a-fbbc-487d-93c5-c71e042e8478",
"name": "Convert To File",
"type": "n8n-nodes-base.code",
"position": [
1424,
1760
],
"parameters": {
"jsCode": "// Enhanced n8n code node for base64 to PNG conversion\nconst inputData = $input.all();\nconst outputData = [];\n\n// Helper function to safely get nested property\nfunction getNestedProperty(obj, path) {\n return path.split('.').reduce((current, key) => {\n return current && current[key] !== undefined ? current[key] : null;\n }, obj);\n}\n\n// Helper function to validate base64\nfunction isValidBase64(str) {\n if (!str || typeof str !== 'string') return false;\n try {\n // Basic base64 pattern check\n const base64Pattern = /^[A-Za-z0-9+/]*={0,2}$/;\n return base64Pattern.test(str) && str.length % 4 === 0;\n } catch (err) {\n return false;\n }\n}\n\n// Helper function to detect image format from base64\nfunction detectImageFormat(base64String) {\n try {\n const header = base64String.substring(0, 20);\n const decoded = Buffer.from(header, 'base64');\n \n // PNG signature: 89 50 4E 47\n if (decoded[0] === 0x89 && decoded[1] === 0x50 && decoded[2] === 0x4E && decoded[3] === 0x47) {\n return 'png';\n }\n // JPEG signature: FF D8 FF\n if (decoded[0] === 0xFF && decoded[1] === 0xD8 && decoded[2] === 0xFF) {\n return 'jpeg';\n }\n // GIF signature: 47 49 46\n if (decoded[0] === 0x47 && decoded[1] === 0x49 && decoded[2] === 0x46) {\n return 'gif';\n }\n // WebP signature: starts with \"RIFF\" and contains \"WEBP\"\n const str = decoded.toString('ascii', 0, 12);\n if (str.startsWith('RIFF') && str.includes('WEBP')) {\n return 'webp';\n }\n return 'unknown';\n } catch (error) {\n return 'unknown';\n }\n}\n\nfor (const [index, item] of inputData.entries()) {\n try {\n let base64String = null;\n let sourcePath = null;\n \n // Define possible paths where base64 data might be located\n const possiblePaths = [\n 'candidates.0.content.parts.1.inlineData.data',\n 'candidates.0.content.parts.0.inlineData.data',\n // Add other possible variations\n 'candidates.0.content.parts.1.inline_data.data',\n 'candidates.0.content.parts.0.inline_data.data',\n // Check if there are multiple parts\n 'candidates.0.content.parts.2.inlineData.data',\n 'candidates.0.content.parts.3.inlineData.data',\n // Fallback to common base64 field names\n 'base64',\n 'data',\n 'image',\n 'content'\n ];\n \n // Try to find base64 data in any of the possible paths\n for (const path of possiblePaths) {\n const value = getNestedProperty(item.json, path);\n if (value && typeof value === 'string' && value.length > 100) { // Minimum length check for image data\n // Handle data URL format if present\n let cleanValue = value;\n if (value.includes('data:image/') && value.includes('base64,')) {\n cleanValue = value.split('base64,')[1];\n }\n \n // Validate if it's proper base64\n if (isValidBase64(cleanValue)) {\n base64String = cleanValue;\n sourcePath = path;\n break;\n }\n }\n }\n \n // Also check if there are multiple parts and scan through them\n if (!base64String && item.json.candidates && item.json.candidates[0] && item.json.candidates[0].content && item.json.candidates[0].content.parts) {\n const parts = item.json.candidates[0].content.parts;\n for (let i = 0; i < parts.length; i++) {\n if (parts[i] && parts[i].inlineData && parts[i].inlineData.data) {\n const value = parts[i].inlineData.data;\n if (isValidBase64(value)) {\n base64String = value;\n sourcePath = `candidates.0.content.parts.${i}.inlineData.data`;\n break;\n }\n }\n // Also check for inline_data (underscore variant)\n if (parts[i] && parts[i].inline_data && parts[i].inline_data.data) {\n const value = parts[i].inline_data.data;\n if (isValidBase64(value)) {\n base64String = value;\n sourcePath = `candidates.0.content.parts.${i}.inline_data.data`;\n break;\n }\n }\n }\n }\n \n if (!base64String) {\n throw new Error('No valid base64 image data found in any of the expected paths');\n }\n \n // Convert to buffer\n const imageBuffer = Buffer.from(base64String, 'base64');\n \n // Detect original format\n const originalFormat = detectImageFormat(base64String);\n \n // Generate filename\n const timestamp = new Date().getTime();\n const filename = `converted_image_${timestamp}_${index}.png`;\n \n // Create output item\n const outputItem = {\n json: {\n success: true,\n filename: filename,\n mimeType: 'image/png',\n fileSize: imageBuffer.length,\n originalFormat: originalFormat,\n sourcePath: sourcePath,\n convertedAt: new Date().toISOString(),\n itemIndex: index\n },\n binary: {\n data: {\n data: base64String, // Use the clean base64 string\n mimeType: 'image/png',\n fileName: filename,\n fileExtension: 'png'\n }\n }\n };\n \n outputData.push(outputItem);\n \n } catch (error) {\n // Create error output with debugging information\n const errorItem = {\n json: {\n success: false,\n error: error.message,\n itemIndex: index,\n availablePaths: Object.keys(item.json).length > 0 ? \n JSON.stringify(item.json, null, 2).substring(0, 500) + '...' : 'No data',\n timestamp: new Date().toISOString()\n }\n };\n \n outputData.push(errorItem);\n }\n}\n\nreturn outputData;"
},
"typeVersion": 2
},
{
"id": "e6d8ca2d-e16e-48e0-9521-0318f4756c96",
"name": "If",
"type": "n8n-nodes-base.if",
"position": [
144,
1808
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "bc63b8aa-dd00-4672-920d-d08033c701ee",
"operator": {
"type": "number",
"operation": "exists",
"singleValue": true
},
"leftValue": "={{ $json.ID }}",
"rightValue": ""
}
]
},
"looseTypeValidation": true
},
"typeVersion": 2.2
},
{
"id": "3480ecd9-ed69-4d51-a749-e447bb97a0c6",
"name": "Send a text message",
"type": "n8n-nodes-base.telegram",
"position": [
288,
1664
],
"webhookId": "3f4a95c3-1460-4b5a-a85b-c6033977a1c2",
"parameters": {
"text": "Please wait 30 Seconds while we work our magic.",
"chatId": "={{ $json.ID }}",
"additionalFields": {
"appendAttribution": false
}
},
"typeVersion": 1.2
},
{
"id": "9c5ca8a8-ca2f-4c64-8091-e1616c598713",
"name": "Send a text message2",
"type": "n8n-nodes-base.telegram",
"position": [
288,
1952
],
"webhookId": "843019ac-000f-4de3-95ef-c476bb29f46c",
"parameters": {
"text": "Please upload a image to to edit.",
"chatId": "={{ $('Telegram Trigger').item.json.message.from.id }}",
"additionalFields": {
"appendAttribution": false
}
},
"typeVersion": 1.2
},
{
"id": "5d13dd2c-44fa-4f0b-aa3e-f806f12336f5",
"name": "付箋",
"type": "n8n-nodes-base.stickyNote",
"position": [
-688,
288
],
"parameters": {
"width": 992,
"height": 464,
"content": "## Google Nano Banana Image Generator: Overview\n### How it works\nThis workflow is used to create AI images through Telegram messages. When a user sends any text or command in Telegram, that message is collected by n8n using the Telegram trigger. Then the text is cleaned and used as a prompt for Nano Banana, which is a small AI image model. The workflow sends this prompt to Nano Banana by using HTTP request node. The model then returns one generated image file. This image is again sent to the same user in Telegram chat automatically.\n\nThe whole process is done inside n8n without any other tools. You can also add a small OpenAI node in between if you want to make better image descriptions. The workflow is built in a simple way so anyone can test, learn, and extend it easily.\n\n### Setup steps\n1. Create your Telegram Bot by using BotFather and copy its token.\n2. Add your Telegram credentials in n8n.\n3. Copy your Nano Banana API key and paste it in HTTP Request node.\n4. (Optional) Add OpenAI credentials for refining prompt.\n5. Turn the workflow on and test by sending a message from your Telegram app."
},
"typeVersion": 1
},
{
"id": "969c8e2e-8175-47aa-9873-c2a36863f0e2",
"name": "付箋1",
"type": "n8n-nodes-base.stickyNote",
"position": [
-704,
1536
],
"parameters": {
"color": 6,
"width": 576,
"height": 384,
"content": "## Telegram Input\nThis part collects user messages or images from Telegram. The trigger starts the workflow each time user sends something. IF node checks message type and sends it to the correct branch for next action.\n"
},
"typeVersion": 1
},
{
"id": "eedd4464-fb3b-494f-9d5a-b905b0fd7282",
"name": "付箋2",
"type": "n8n-nodes-base.stickyNote",
"position": [
-688,
816
],
"parameters": {
"color": 6,
"width": 992,
"height": 272,
"content": "## Image Download and Preparation\nHere the workflow downloads the image that came from Telegram and changes it into base64 string. This format is easy to send further to Drive or to any API that needs encoded file.\n"
},
"typeVersion": 1
},
{
"id": "4e7bc232-9a87-49de-b65f-ea06d5d0ce6d",
"name": "付箋3",
"type": "n8n-nodes-base.stickyNote",
"position": [
-96,
1136
],
"parameters": {
"color": 6,
"width": 1344,
"height": 320,
"content": "## Upload and Record Update\nThis top flow uploads the file to Google Drive and then updates the connected record. After that, a text message is sent in Telegram to confirm that the upload and update is completed properly.\n"
},
"typeVersion": 1
},
{
"id": "c3588192-7477-44d5-bc05-d5a1a6d0a630",
"name": "付箋4",
"type": "n8n-nodes-base.stickyNote",
"position": [
-96,
1504
],
"parameters": {
"color": 6,
"width": 672,
"height": 608,
"content": "## Conditional Message Handling\nThis part is used for checking if the incoming message matches any saved record or keyword. Depending on result, Telegram sends one of the two reply messages to guide the user further.\n"
},
"typeVersion": 1
},
{
"id": "02ec6043-51a2-46d8-889f-0c3ec3e2fac2",
"name": "付箋5",
"type": "n8n-nodes-base.stickyNote",
"position": [
640,
1520
],
"parameters": {
"color": 6,
"width": 1472,
"height": 480,
"content": "## Image Editing and Return Flow\nThis section manages full image process. It downloads the earlier stored image, extracts the content, and edits it using image API. The final image file is made and uploaded again, then sent back to Telegram chat as photo message.\n"
},
"typeVersion": 1
}
],
"active": false,
"pinData": {
"Telegram Trigger": [
{
"json": {
"message": {
"chat": {
"id": 6397287561,
"type": "private",
"last_name": "K",
"first_name": "S"
},
"date": 1757313325,
"from": {
"id": 6397287561,
"is_bot": false,
"last_name": "K",
"first_name": "S",
"language_code": "en"
},
"photo": [
{
"width": 90,
"height": 90,
"file_id": "AgACAgUAAxkBAAOwaL55LZCAqkqmrjN0scLJuSFYZY0AAsnDMRtJZfBVFUPlS6nhAAFYAQADAgADcwADNgQ",
"file_size": 1322,
"file_unique_id": "AQADycMxG0ll8FV4"
},
{
"width": 320,
"height": 320,
"file_id": "AgACAgUAAxkBAAOwaL55LZCAqkqmrjN0scLJuSFYZY0AAsnDMRtJZfBVFUPlS6nhAAFYAQADAgADbQADNgQ",
"file_size": 15801,
"file_unique_id": "AQADycMxG0ll8FVy"
},
{
"width": 775,
"height": 775,
"file_id": "AgACAgUAAxkBAAOwaL55LZCAqkqmrjN0scLJuSFYZY0AAsnDMRtJZfBVFUPlS6nhAAFYAQADAgADeAADNgQ",
"file_size": 39961,
"file_unique_id": "AQADycMxG0ll8FV9"
}
],
"message_id": 176
},
"update_id": 388279181
}
}
]
},
"settings": {
"executionOrder": "v1"
},
"versionId": "273d8db8-3328-4877-a4b9-8061e360fe36",
"connections": {
"e6d8ca2d-e16e-48e0-9521-0318f4756c96": {
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[
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"54e2b068-775c-47d4-a1bc-9ddfe17e3d88": {
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[
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"type": "main",
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},
"Merge": {
"main": [
[
{
"node": "Aggregate",
"type": "main",
"index": 0
}
]
]
},
"Aggregate": {
"main": [
[
{
"node": "845d6a60-14fb-4c94-9b97-fc44d04a54c2",
"type": "main",
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]
]
},
"Edit Image": {
"main": [
[
{
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"type": "main",
"index": 0
}
]
]
},
"845d6a60-14fb-4c94-9b97-fc44d04a54c2": {
"main": [
[
{
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"type": "main",
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}
]
]
},
"2bcd11a9-94a2-4b78-86a7-3e31529ee4c0": {
"main": [
[
{
"node": "Merge",
"type": "main",
"index": 0
}
]
]
},
"093a6d6a-ae91-4906-a7f3-5e6a63b382ee": {
"main": [
[
{
"node": "Edit Image",
"type": "main",
"index": 0
}
]
]
},
"623e5e22-e227-4aa1-b866-ee74301bc407": {
"main": [
[
{
"node": "b4225b8e-eae3-4ad0-8ffe-bfe5932bf56a",
"type": "main",
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}
]
]
},
"Download File": {
"main": [
[
{
"node": "Extract from File",
"type": "main",
"index": 0
}
]
]
},
"3a62cd46-9b63-4dac-ab7b-ea562e62a828": {
"main": [
[
{
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}
]
]
},
"5db3e15a-fbbc-487d-93c5-c71e042e8478": {
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[
{
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"type": "main",
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{
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"type": "main",
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]
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},
"a7ce2cca-93a0-4b0d-8ba3-eb51d24e1362": {
"main": [
[
{
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"type": "main",
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{
"node": "2bcd11a9-94a2-4b78-86a7-3e31529ee4c0",
"type": "main",
"index": 0
}
]
]
},
"Telegram Trigger": {
"main": [
[
{
"node": "54e2b068-775c-47d4-a1bc-9ddfe17e3d88",
"type": "main",
"index": 0
}
]
]
},
"Extract from File": {
"main": [
[
{
"node": "093a6d6a-ae91-4906-a7f3-5e6a63b382ee",
"type": "main",
"index": 0
}
]
]
},
"fed96b49-66fa-4479-8c66-b89370907341": {
"main": [
[
{
"node": "Merge",
"type": "main",
"index": 1
}
]
]
},
"3480ecd9-ed69-4d51-a749-e447bb97a0c6": {
"main": [
[
{
"node": "Download File",
"type": "main",
"index": 0
}
]
]
},
"53655955-c77f-4a95-ade0-021895f197ba": {
"main": [
[
{
"node": "0b8c5466-58ca-47ea-89cf-5d5ee95e90ef",
"type": "main",
"index": 0
}
]
]
}
}
}よくある質問
このワークフローの使い方は？
上記のJSON設定コードをコピーし、n8nインスタンスで新しいワークフローを作成して「JSONからインポート」を選択、設定を貼り付けて認証情報を必要に応じて変更してください。
このワークフローはどんな場面に適していますか？
上級 - コンテンツ作成, マルチモーダルAI
有料ですか？
このワークフローは完全無料です。ただし、ワークフローで使用するサードパーティサービス（OpenAI APIなど）は別途料金が発生する場合があります。
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