digitalhera/heranathalie - 다른 생성기
중급
이것은Content Creation, Multimodal AI분야의자동화 워크플로우로, 15개의 노드를 포함합니다.주로 If, Set, Code, Wait, HttpRequest 등의 노드를 사용하며. 사용 HeraNathalie 모델과 Replicate로 텍스트 힌트에서 이미지 생성
사전 요구사항
- •대상 API의 인증 정보가 필요할 수 있음
워크플로우 미리보기
노드 연결 관계를 시각적으로 표시하며, 확대/축소 및 이동을 지원합니다
워크플로우 내보내기
다음 JSON 구성을 복사하여 n8n에 가져오면 이 워크플로우를 사용할 수 있습니다
{
"meta": {
"instanceId": "635292d4-c8fe-4019-8342-2a24aaf766a6",
"model_name": "heranathalie",
"model_type": "other",
"version_id": "c4e122b4dceba454469d84b69b855b38625b89ca6e922e1c1b1a817ea8f7e340",
"model_owner": "digitalhera",
"generated_at": "2025-08-01T14:50:46.746736"
},
"name": "digitalhera/heranathalie - Other Generator",
"nodes": [
{
"id": "e82383b3-8d0d-4ac9-b51f-a1716ac9508b",
"name": "수동 트리거",
"type": "n8n-nodes-base.manualTrigger",
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"parameters": {},
"typeVersion": 1
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{
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"name": "API 토큰 설정",
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"position": [
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],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "api_token",
"name": "api_token",
"type": "string",
"value": "YOUR_REPLICATE_API_TOKEN"
}
]
}
},
"typeVersion": 3.3
},
{
"id": "8405efc4-1bc4-4ad9-8a0e-38d31266ba72",
"name": "기타 매개변수 설정",
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"position": [
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"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "api_token",
"name": "api_token",
"type": "string",
"value": "={{ $('Set API Token').item.json.api_token }}"
},
{
"id": "mask",
"name": "mask",
"type": "string",
"value": "https://via.placeholder.com/512x512/000000/FFFFFF.png"
},
{
"id": "seed",
"name": "seed",
"type": "number",
"value": -1
},
{
"id": "image",
"name": "image",
"type": "string",
"value": "https://picsum.photos/512/512"
},
{
"id": "model",
"name": "model",
"type": "string",
"value": "dev"
},
{
"id": "width",
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"value": 512
},
{
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},
{
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"type": "string",
"value": "Create something amazing"
},
{
"id": "go_fast",
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"type": "boolean",
"value": false
},
{
"id": "extra_lora",
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"type": "string",
"value": ""
},
{
"id": "lora_scale",
"name": "lora_scale",
"type": "number",
"value": 1
},
{
"id": "megapixels",
"name": "megapixels",
"type": "string",
"value": "1"
},
{
"id": "num_outputs",
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"type": "number",
"value": 1
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{
"id": "aspect_ratio",
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"type": "string",
"value": "1:1"
},
{
"id": "output_format",
"name": "output_format",
"type": "string",
"value": "webp"
},
{
"id": "guidance_scale",
"name": "guidance_scale",
"type": "number",
"value": 3
},
{
"id": "output_quality",
"name": "output_quality",
"type": "number",
"value": 80
},
{
"id": "prompt_strength",
"name": "prompt_strength",
"type": "number",
"value": 0.8
},
{
"id": "extra_lora_scale",
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"type": "number",
"value": 1
},
{
"id": "replicate_weights",
"name": "replicate_weights",
"type": "string",
"value": ""
},
{
"id": "num_inference_steps",
"name": "num_inference_steps",
"type": "number",
"value": 28
},
{
"id": "disable_safety_checker",
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}
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"typeVersion": 3.3
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{
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"type": "n8n-nodes-base.httpRequest",
"position": [
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"parameters": {
"url": "https://api.replicate.com/v1/predictions",
"method": "POST",
"options": {
"response": {
"response": {
"neverError": true,
"responseFormat": "json"
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}
},
"jsonBody": "={\n \"version\": \"digitalhera/heranathalie:c4e122b4dceba454469d84b69b855b38625b89ca6e922e1c1b1a817ea8f7e340\",\n \"input\": {\n \"mask\": \"{{ $json.mask }}\",\n \"seed\": {{ $json.seed }},\n \"image\": \"{{ $json.image }}\",\n \"model\": \"{{ $json.model }}\",\n \"width\": {{ $json.width }},\n \"height\": {{ $json.height }},\n \"prompt\": \"{{ $json.prompt }}\",\n \"go_fast\": {{ $json.go_fast }},\n \"extra_lora\": \"{{ $json.extra_lora }}\",\n \"lora_scale\": {{ $json.lora_scale }},\n \"megapixels\": \"{{ $json.megapixels }}\",\n \"num_outputs\": {{ $json.num_outputs }},\n \"aspect_ratio\": \"{{ $json.aspect_ratio }}\",\n \"output_format\": \"{{ $json.output_format }}\",\n \"guidance_scale\": {{ $json.guidance_scale }},\n \"output_quality\": {{ $json.output_quality }},\n \"prompt_strength\": {{ $json.prompt_strength }},\n \"extra_lora_scale\": {{ $json.extra_lora_scale }},\n \"replicate_weights\": \"{{ $json.replicate_weights }}\",\n \"num_inference_steps\": {{ $json.num_inference_steps }},\n \"disable_safety_checker\": {{ $json.disable_safety_checker }}\n }\n}",
"sendBody": true,
"sendHeaders": true,
"specifyBody": "json",
"headerParameters": {
"parameters": [
{
"name": "Authorization",
"value": "=Bearer {{ $json.api_token }}"
},
{
"name": "Prefer",
"value": "wait"
}
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{
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{
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"name": "상태 확인",
"type": "n8n-nodes-base.httpRequest",
"position": [
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],
"parameters": {
"url": "=https://api.replicate.com/v1/predictions/{{ $('Create Other Prediction').item.json.id }}",
"options": {
"response": {
"response": {
"neverError": true,
"responseFormat": "json"
}
}
},
"sendHeaders": true,
"headerParameters": {
"parameters": [
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"value": "=Bearer {{ $('Set API Token').item.json.api_token }}"
}
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},
"typeVersion": 4.1
},
{
"id": "8359b7c6-2d38-4b58-acb8-4a75068afd56",
"name": "완료 여부?",
"type": "n8n-nodes-base.if",
"position": [
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"parameters": {
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"options": {
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"leftValue": "",
"caseSensitive": true,
"typeValidation": "loose"
},
"combinator": "and",
"conditions": [
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"id": "c93d7ba1-0ef9-4087-aa10-389cb2a2c6bd",
"operator": {
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $json.status }}",
"rightValue": "succeeded"
}
]
}
},
"typeVersion": 2
},
{
"id": "68a6875b-8198-4944-a1e2-53295dfd700a",
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"rightValue": "failed"
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{
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"webhookId": "51a05aef-e220-406d-8c2c-e59c82c3e26e",
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{
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"type": "n8n-nodes-base.set",
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"parameters": {
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"assignments": {
"assignments": [
{
"id": "success-response",
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"type": "object",
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},
"typeVersion": 3.3
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{
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"name": "오류 응답",
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"position": [
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],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "error-response",
"name": "response",
"type": "object",
"value": "={{ { success: false, error: $json.error || 'Other generation failed', prediction_id: $json.id, status: $json.status, message: 'Failed to generate other' } }}"
}
]
}
},
"typeVersion": 3.3
},
{
"id": "87cf4259-4471-43de-8773-1d1ab0a52930",
"name": "결과 표시",
"type": "n8n-nodes-base.set",
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"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "final-result",
"name": "final_result",
"type": "object",
"value": "={{ $json.response }}"
}
]
}
},
"typeVersion": 3.3
},
{
"id": "327b496d-ba13-4689-a873-ea02b9daa703",
"name": "요청 로깅",
"type": "n8n-nodes-base.code",
"position": [
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"parameters": {
"jsCode": "// Log generation details for monitoring\nconst data = $input.all()[0].json;\n\nconsole.log('digitalhera/heranathalie Request:', {\n timestamp: new Date().toISOString(),\n prediction_id: data.id,\n model_type: 'other'\n});\n\nreturn $input.all();"
},
"typeVersion": 2
},
{
"id": "79796ec0-7e48-48cc-bedd-137f55d590ae",
"name": "스티커 노트9",
"type": "n8n-nodes-base.stickyNote",
"position": [
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"parameters": {
"color": 4,
"width": 580,
"height": 320,
"content": "=======================================\n HERANATHALIE GENERATOR\n=======================================\nFor any questions or support, please contact:\n Yaron@nofluff.online\n\nExplore more tips and tutorials here:\n - YouTube: https://www.youtube.com/@YaronBeen/videos\n - LinkedIn: https://www.linkedin.com/in/yaronbeen/\n======================================="
},
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"type": "n8n-nodes-base.stickyNote",
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"content": "## 🤖 **DIGITALHERA/HERANATHALIE - OTHER GENERATION WORKFLOW**\n\n**🔥 Powered by Replicate API and n8n Automation**\n\n---\n\n### 📝 **Model Overview**\n\n- **Owner**: digitalhera\n- **Model**: heranathalie\n- **Type**: Other Generation\n- **API Endpoint**: https://api.replicate.com/v1/predictions\n\n**🎯 What This Model Does:**\nNone\n\n---\n\n### 📋 **Parameter Reference**\n\n**🔴 Required Parameters:** prompt\n**🔵 Optional Parameters:** mask, seed, image, model, width, height, go_fast, extra_lora (and 12 more)\n\n**📖 Detailed Parameter Guide:**\n- **mask** (string): Image mask for image inpainting mode. If provided, aspect_ratio, width, and height inputs are ign...\n- **seed** (integer): Random seed. Set for reproducible generation\n- **image** (string): Input image for image to image or inpainting mode. If provided, aspect_ratio, width, and height i...\n- **model** (string): Which model to run inference with. The dev model performs best with around 28 inference steps but... (Default: dev)\n- **width** (integer): Width of generated image. Only works if `aspect_ratio` is set to custom. Will be rounded to neare...\n- **height** (integer): Height of generated image. Only works if `aspect_ratio` is set to custom. Will be rounded to near...\n- **prompt** (string): Prompt for generated image. If you include the `trigger_word` used in the training process you ar...\n- **go_fast** (boolean): Run faster predictions with model optimized for speed (currently fp8 quantized); disable to run i... (Default: False)\n- *...and 13 more parameters*\n\n---\n\n### 🔧 **Workflow Components Explained**\n\n**🎯 Manual Trigger**\n- Starts the workflow execution\n- Click to begin other generation process\n\n**🔐 Set API Token** \n- Configures your Replicate API authentication\n- Replace 'YOUR_REPLICATE_API_TOKEN' with your actual token\n- Essential for accessing the digitalhera/heranathalie model\n\n**⚙️ Set Other Parameters**\n- Configures all input parameters for the model\n- Includes both required and optional parameters\n- Pre-filled with sensible defaults for testing\n\n**🚀 Create Other Prediction**\n- Sends the generation request to Replicate API\n- Uses the other parameters you configured\n- Returns a prediction ID for status tracking\n\n**⏳ Wait & Status Checking Loop**\n- Waits 5 seconds then checks prediction status\n- Continues checking until completion or failure\n- Implements intelligent retry logic with 10-second delays\n\n**✅ Success/Error Handling**\n- Routes successful completions to success response\n- Handles failures gracefully with error details\n- Returns structured JSON response with URLs/errors\n\n**📊 Logging & Monitoring**\n- Logs all requests for debugging and monitoring\n- Tracks timestamps and prediction IDs\n- Helps identify issues during development\n\n---\n\n### 🌟 **Key Benefits**\n\n- **🎨 Instant Other Generation**: Transform ideas into others using state-of-the-art AI\n- **🔄 Automated Workflow**: Handles the complete generation pipeline automatically\n- **🛡️ Error Resilience**: Built-in retry logic and comprehensive error handling\n- **📈 Production Ready**: Includes logging, monitoring, and structured responses\n- **🔧 Customizable**: Easy to modify parameters and extend functionality\n- **⚡ Efficient Processing**: Optimized API calls with intelligent status checking\n\n---\n\n### 🚀 **Quick Start Instructions**\n\n1. **🔑 Get Your API Key**\n - Sign up at https://replicate.com\n - Navigate to your account settings\n - Copy your API token\n\n2. **🔧 Configure the Workflow**\n - Replace 'YOUR_REPLICATE_API_TOKEN' with your actual token\n - Adjust parameters in the 'Set Other Parameters' node\n - Customize the prompt or other inputs as needed\n\n3. **▶️ Execute the Workflow**\n - Click the 'Manual Trigger' to start\n - Monitor the execution in the n8n interface\n - Check logs for detailed execution information\n\n4. **📥 Get Your Results**\n - Successful generations return a URL to your other\n - Download or use the generated content as needed\n - Results are available immediately upon completion\n\n---\n\n### 🔍 **Troubleshooting Guide**\n\n**Common Issues:**\n- **Invalid API Token**: Ensure your Replicate token is valid and has sufficient credits\n- **Parameter Validation**: Check that required parameters match expected types\n- **Generation Timeout**: Some others take longer - monitor the logs\n- **Output Format**: Verify the model returns the expected output format\n\n**Best Practices:**\n- Test with default parameters first\n- Monitor your Replicate usage and billing\n- Keep API tokens secure and never commit them to code\n- Use appropriate parameter values for your use case\n\n---\n\n**🔗 Additional Resources:**\n- Model Documentation: https://replicate.com/digitalhera/heranathalie\n- Replicate API Docs: https://replicate.com/docs\n- n8n Documentation: https://docs.n8n.io\n\n---"
},
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"active": false,
"pinData": {},
"versionId": "1",
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}자주 묻는 질문
이 워크플로우를 어떻게 사용하나요?
위의 JSON 구성 코드를 복사하여 n8n 인스턴스에서 새 워크플로우를 생성하고 "JSON에서 가져오기"를 선택한 후, 구성을 붙여넣고 필요에 따라 인증 설정을 수정하세요.
이 워크플로우는 어떤 시나리오에 적합한가요?
중급 - 콘텐츠 제작, 멀티모달 AI
유료인가요?
이 워크플로우는 완전히 무료이며 직접 가져와 사용할 수 있습니다. 다만, 워크플로우에서 사용하는 타사 서비스(예: OpenAI API)는 사용자 직접 비용을 지불해야 할 수 있습니다.
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15 노드Yaron Been
콘텐츠 제작
Dessix Moss Ttsd 텍스트 생성기
Replicate Moss-TTSD를 사용하여 대화 스크립트를 자연스러운 음성으로 변환
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9 노드Yaron Been
콘텐츠 제작
ibm-granite/granite-speech-3.3-8b - 텍스트 생성기
Replicate API를 사용하여 IBM Granite 3.3 8B 모델을 통해 음성을 텍스트로 변환합니다.
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15 노드Yaron Been
콘텐츠 제작
moicarmonas/2ndmoises_generator - 다른 생성기
사용하여 2nd Moises 생성器및 Replicate로 텍스트 힌트에서 이미지를 생성합니다.
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15 노드Yaron Been
콘텐츠 제작
moicarmonas/3rdmoises_generator_oldversion - 다른 생성기
사용하여 3rd Moises 생성器및 Replicate로 텍스트 힌트에서 이미지를 생성합니다.
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15 노드Yaron Been
콘텐츠 제작
alitas126/alitas2 - 다른 생성기
사용하여 Alitas2 모델과 Replicate로 텍스트 힌트에서 이미지를 생성합니다.
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15 노드Yaron Been
콘텐츠 제작
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저자
Yaron Been
@yaron-nofluffBuilding AI Agents and Automations | Growth Marketer | Entrepreneur | Book Author & Podcast Host If you need any help with Automations, feel free to reach out via linkedin: https://www.linkedin.com/in/yaronbeen/ And check out my Youtube channel: https://www.youtube.com/@YaronBeen/videos
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