3D-Modell-Triplexe erzeugen mit Midjourney und GPT-4o-Image API
Dies ist ein Design, AI-Bereich Automatisierungsworkflow mit 10 Nodes. Hauptsächlich werden If, Code, Wait, HttpRequest, ManualTrigger und andere Nodes verwendet, kombiniert mit KI-Technologie für intelligente Automatisierung. Erstellungsworkflow für orthogonale 3D-Modellanzeigen
- •Möglicherweise sind Ziel-API-Anmeldedaten erforderlich
Verwendete Nodes (10)
Kategorie
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"meta": {
"instanceId": "1e003a7ea4715b6b35e9947791386a7d07edf3b5bf8d4c9b7ee4fdcbec0447d7"
},
"name": "3D Figurine Orthographic Views with Midjourney and GPT-4o-Image API",
"tags": [],
"nodes": [
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"name": "Beim Klicken auf 'Workflow testen'",
"type": "n8n-nodes-base.manualTrigger",
"position": [
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"parameters": {},
"typeVersion": 1
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{
"id": "26cb9d6e-6a73-4a27-805d-8577c84101fa",
"name": "Midjourney Generator",
"type": "n8n-nodes-base.httpRequest",
"position": [
940,
220
],
"parameters": {
"url": "https://api.piapi.ai/api/v1/task",
"method": "POST",
"options": {},
"jsonBody": "{\n \"model\": \"midjourney\",\n \"task_type\": \"imagine\",\n \"input\": {\n \"prompt\": \"IP design, pop mart style, cartoon-style characters, a little girl with a red satche on her back, a pair of big eyes, long eyelashes, with pigtails, wearing a red beret, red shoes, chubby body, wearing a red and white striped dress, clean white background, crystal-clear material::5, 3D rendering, 3D modeling --ar 3:4 --niji 6\",\n \"aspect_ratio\": \"3:2\",\n \"process_mode\": \"turbo\",\n \"skip_prompt_check\": false\n }\n}",
"sendBody": true,
"sendHeaders": true,
"specifyBody": "json",
"headerParameters": {
"parameters": [
{
"name": "x-api-key"
}
]
}
},
"typeVersion": 4.2
},
{
"id": "4220555c-f4f4-43ab-8d03-1ae4b959bdd1",
"name": "Midjourney-URL abrufen",
"type": "n8n-nodes-base.httpRequest",
"position": [
760,
460
],
"parameters": {
"url": "=https://api.piapi.ai/api/v1/task/{{ $json.data.task_id }}",
"options": {},
"sendHeaders": true,
"headerParameters": {
"parameters": [
{
"name": "x-api-key",
"value": "72858adea87ad16865d5b0a24c3d9b9f58a6e7b1a8a8a8a0d6b81a9f3a9812f3"
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}
},
"typeVersion": 4.2
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{
"id": "e81311ee-4522-4fb3-929f-1c062427c859",
"name": "URL-Erfassung überprüfen",
"type": "n8n-nodes-base.if",
"position": [
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460
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
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"combinator": "and",
"conditions": [
{
"id": "a0f8758e-d6fd-44f8-bd79-bc3c4dceddcf",
"operator": {
"name": "filter.operator.equals",
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $json.data.status }}",
"rightValue": "completed"
}
]
}
},
"typeVersion": 2.2
},
{
"id": "9519899e-c246-474e-8fd6-7dd16cf27a5b",
"name": "Auf Generierung warten",
"type": "n8n-nodes-base.wait",
"position": [
980,
700
],
"webhookId": "f3bcf634-8c4b-4bf9-a7f2-d4ee369f5349",
"parameters": {},
"typeVersion": 1.1
},
{
"id": "693348ab-12ab-4896-9fda-a9141263ccbf",
"name": "Zufällige Bild-URL abrufen",
"type": "n8n-nodes-base.code",
"position": [
1240,
520
],
"parameters": {
"jsCode": "// JavaScript Code for Function Node\nreturn {\n random_temp_url: $input.all()[0].json.data.output.temporary_image_urls[\n Math.floor(Math.random() * $input.all()[0].json.data.output.temporary_image_urls.length)\n ]\n};"
},
"typeVersion": 2
},
{
"id": "18f030a6-7333-45df-af1d-f8c5492084c6",
"name": "3-Ansichten-Bild mit GPT-4o-Image generieren",
"type": "n8n-nodes-base.httpRequest",
"position": [
1440,
520
],
"parameters": {
"url": "https://api.piapi.ai/v1/chat/completions",
"method": "POST",
"options": {},
"jsonBody": "={\n \"model\": \"gpt-4o-image-preview\",\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": [\n {\n \"type\": \"image_url\",\n \"image_url\": {\n \"url\": \"{{ $json.random_temp_url }}\"\n }\n },\n {\n \"type\": \"text\",\n \"text\": \"Convert this image into a 3D figurine image, with front view, side view, and back view in one page. Generate a turnaround sheet showing the figurine’s front with full details, profile, and back views in left-to-right sequence. ar=10:3\"\n }\n ]\n }\n ],\n \"stream\": true\n}",
"sendBody": true,
"sendHeaders": true,
"specifyBody": "json",
"authentication": "genericCredentialType",
"genericAuthType": "httpHeaderAuth",
"headerParameters": {
"parameters": [
{
"name": "Authorization",
"value": "Bearer "
}
]
}
},
"credentials": {
"httpHeaderAuth": {
"id": "fsJeCNd9BkJ1CIrt",
"name": "Header Auth account 2"
}
},
"typeVersion": 4.2
},
{
"id": "4d758715-79d5-4c2e-94d2-d1cfe1bdda6d",
"name": "Überprüfen, ob die URL erhalten wurde",
"type": "n8n-nodes-base.if",
"position": [
1840,
520
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "08a2ebe6-dc95-4b8a-ada1-1173645cc3f4",
"operator": {
"name": "filter.operator.equals",
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $json.finish_reason }}",
"rightValue": "not_found"
},
{
"id": "ed245d42-677f-4465-a3f1-d23c6e609f5e",
"operator": {
"name": "filter.operator.equals",
"type": "string",
"operation": "equals"
},
"leftValue": "",
"rightValue": ""
}
]
}
},
"typeVersion": 2.2
},
{
"id": "690c002c-8641-4bb9-8c55-8b5cd6f01f2c",
"name": "Endausgabe abrufen",
"type": "n8n-nodes-base.code",
"position": [
2080,
540
],
"parameters": {
"jsCode": "// Method 2: n8n workflow compatible version\nreturn $input.all().map(item => {\n return {\n image_url: item.json.image_url\n };\n});"
},
"typeVersion": 2
},
{
"id": "db38b578-1078-4a89-b429-55ba337a21fc",
"name": "Bild abrufen",
"type": "n8n-nodes-base.code",
"position": [
1660,
520
],
"parameters": {
"jsCode": "const chunks = $input.first().json.data.split('\\n\\n');\n\nlet imageUrl = null;\n\n// 反向遍历 chunks (从最新数据开始检查)\nfor (let i = chunks.length - 1; i >= 0; i--) {\n const chunk = chunks[i];\n \n if (!chunk.startsWith('data: ')) continue;\n \n try {\n const jsonStr = chunk.substring(6); // 去掉 \"data: \" 前缀\n if (jsonStr.trim() === '[DONE]') continue;\n \n const data = JSON.parse(jsonStr);\n \n // 检查是否包含图片标记(Markdown 图片语法)\n if (data.choices && data.choices[0].delta.content) {\n const content = data.choices[0].delta.content;\n const urlMatch = content.match(/!\\[.*?\\]\\((https?:\\/\\/[^\\s]+)\\)/);\n \n if (urlMatch && urlMatch[1]) {\n imageUrl = urlMatch[1];\n break;\n }\n }\n } catch (e) {\n continue;\n }\n}\n\nreturn {\n image_url: imageUrl,\n finish_reason: imageUrl ? \"success\" : \"not_found\"\n};"
},
"typeVersion": 2
}
],
"active": false,
"pinData": {},
"settings": {
"executionOrder": "v1"
},
"versionId": "0e663ca1-c9b2-4fb2-a8bb-14ed8bb63d11",
"connections": {
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},
"9519899e-c246-474e-8fd6-7dd16cf27a5b": {
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"693348ab-12ab-4896-9fda-a9141263ccbf": {
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}
}
}Wie verwende ich diesen Workflow?
Kopieren Sie den obigen JSON-Code, erstellen Sie einen neuen Workflow in Ihrer n8n-Instanz und wählen Sie "Aus JSON importieren". Fügen Sie die Konfiguration ein und passen Sie die Anmeldedaten nach Bedarf an.
Für welche Szenarien ist dieser Workflow geeignet?
Fortgeschritten - Design, Künstliche Intelligenz
Ist es kostenpflichtig?
Dieser Workflow ist völlig kostenlos. Beachten Sie jedoch, dass Drittanbieterdienste (wie OpenAI API), die im Workflow verwendet werden, möglicherweise kostenpflichtig sind.
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