This public URL uses a deprecated compatibility host outside the api-service host. It remains supported for now, but will soon move under
https://api.eachlabs.ai. Keep integrations configurable and switch to the api-service URL once it is published.Text-to-Image Pipeline
A neat two-step workflow that enhances a prompt with an LLM, then generates an image from it.{
"name": "Enhanced Image Generator",
"description": "Uses AI to enhance the prompt before generating an image",
"definition": {
"version": "v1",
"input_schema": {
"type": "object",
"required": ["prompt"],
"properties": {
"prompt": {"type": "string"},
"aspect_ratio": {
"type": "string",
"enum": ["1:1", "16:9", "9:16"],
"default": "1:1"
}
}
},
"steps": [
{
"step_id": "enhance_prompt",
"type": "model",
"model": "openai-chatgpt-5",
"params": {
"system_prompt": "Enhance the following image prompt with vivid details. Return only the enhanced prompt.",
"user_prompt": "{{inputs.prompt}}"
}
},
{
"step_id": "generate_image",
"type": "model",
"model": "flux-1-1-pro",
"params": {
"prompt": "{{enhance_prompt.output}}",
"aspect_ratio": "{{inputs.aspect_ratio}}"
},
"fallback": {
"enabled": true,
"model": "flux-dev",
"params": {
"prompt": "{{enhance_prompt.output}}"
}
}
}
]
}
}
Image-to-Video with Upscaling
Generate a portrait image, bring it to life with animation, and upscale the final result.{
"name": "Portrait to Video",
"description": "Generate a portrait and animate it into a high-quality video",
"definition": {
"version": "v1",
"input_schema": {
"type": "object",
"required": ["description"],
"properties": {
"description": {"type": "string"},
"duration": {
"type": "integer",
"minimum": 3,
"maximum": 30,
"default": 5
}
}
},
"steps": [
{
"step_id": "generate_portrait",
"type": "model",
"model": "nano-banana-pro",
"params": {
"prompt": "{{inputs.description}}, portrait photo, natural lighting",
"aspect_ratio": "1:1"
}
},
{
"step_id": "animate",
"type": "model",
"model": "kling-2-1-image-to-video",
"params": {
"image": "{{generate_portrait.primary}}",
"duration": "{{inputs.duration}}"
}
},
{
"step_id": "upscale",
"type": "model",
"model": "topaz-upscale-video",
"params": {
"video": "{{animate.primary}}",
"scale": 2
}
}
]
}
}
Parallel Branching: Multi-Format Generation
Run image-to-video, image editing, and text-to-image all at once, then conditionally upscale based on the output format.{
"name": "Multi-Format Generator with Conditional Upscale",
"description": "Generates video, edited image, and new image in parallel, then upscales based on output type",
"definition": {
"version": "v1",
"input_schema": {
"type": "object",
"required": ["prompt"],
"properties": {
"prompt": {"type": "string"},
"source_image": {"type": "string"}
}
},
"steps": [
{
"id": "step1",
"type": "parallel",
"branches": [
{
"name": "Video Generation",
"steps": [
{
"id": "step1_branch_0",
"type": "model",
"model": "kling-v3-pro-image-to-video",
"params": {
"prompt": "{{inputs.prompt}}, smooth cinematic motion",
"start_image_url": "{{inputs.source_image}}",
"duration": "5",
"aspect_ratio": "16:9",
"negative_prompt": "blur, distort, low quality"
}
}
]
},
{
"name": "Image Edit",
"steps": [
{
"id": "step1_branch_1",
"type": "model",
"model": "flux-2-edit",
"params": {
"prompt": "{{inputs.prompt}}",
"image_url": "{{inputs.source_image}}"
}
}
]
},
{
"name": "New Image",
"steps": [
{
"id": "step1_branch_2",
"type": "model",
"model": "flux-2-max",
"params": {
"prompt": "{{inputs.prompt}}",
"aspect_ratio": "16:9"
}
}
]
}
]
},
{
"id": "step2",
"type": "choice",
"condition": {
"expression": "$.step1.primary",
"operator": "string_matches",
"value": ".mp4"
},
"condition_met_branch": {
"name": "condition_met",
"step_id": "step2_condition_met",
"steps": [
{
"id": "step2_branch_0",
"type": "model",
"model": "topaz-upscale-video",
"params": {
"video": "{{step1.primary}}",
"scale": 2
}
}
]
},
"default_branch": {
"name": "default",
"step_id": "step2_default",
"steps": [
{
"id": "step2_default",
"type": "model",
"model": "topaz-upscale-image",
"params": {
"image_url": "{{step1.primary}}",
"scale": 2
}
}
]
}
}
]
}
}
- Parallel step: Three branches run concurrently for video generation, image editing, and text-to-image
- Choice step: Checks if the primary output is a video (
.mp4) and routes to the right upscaler
Logical Conditions: AND/OR Operators
You can use logical operators to combine multiple conditions in a choice step. This example only upscales when the output is a PNG and the user explicitly requested upscaling:{
"id": "conditional_upscale",
"type": "choice",
"condition": {
"and": [
{
"expression": "$.step1.primary",
"operator": "string_matches",
"value": ".png"
},
{
"expression": "$.inputs.upscale",
"operator": "equals",
"value": true
}
]
},
"condition_met_branch": {
"name": "condition_met",
"step_id": "upscale_branch",
"steps": [
{
"id": "upscale",
"type": "model",
"model": "topaz-upscale-image",
"params": {
"image_url": "{{step1.primary}}",
"scale": 4
}
}
]
},
"default_branch": {
"name": "default",
"step_id": "skip_branch",
"steps": [
{
"id": "passthrough",
"type": "pass",
"result": "{{step1.primary}}"
}
]
}
}
or to match multiple formats:
{
"condition": {
"or": [
{"expression": "$.step1.primary", "operator": "string_matches", "value": ".mp4"},
{"expression": "$.step1.primary", "operator": "string_matches", "value": ".webm"}
]
}
}
not to negate a condition:
{
"condition": {
"not": {"expression": "$.step1.primary", "operator": "is_null"}
}
}
Batch Processing with Bulk Trigger
Fire off the same workflow with multiple inputs in one go:curl -X POST https://workflows.eachlabs.run/api/v1/WF_ID/bulk-trigger \
-H "Content-Type: application/json" \
-H "X-API-Key: YOUR_API_KEY" \
-d '{
"inputs": [
{"description": "Professional woman, 30s, confident smile"},
{"description": "Young man, casual outfit, warm expression"},
{"description": "Elderly gentleman, distinguished, wise"}
],
"webhook_url": "https://your-app.com/webhooks/batch-complete"
}'
curl "https://workflows.eachlabs.run/api/v1/workflows/WF_ID/executions?bulk_id=BULK_ID" \
-H "X-API-Key: YOUR_API_KEY"
End-to-End Python Example
import requests
import time
API_KEY = "YOUR_API_KEY"
BASE_URL = "https://workflows.eachlabs.run/api/v1"
HEADERS = {
"Content-Type": "application/json",
"X-API-Key": API_KEY
}
# 1. Create workflow
workflow = requests.post(f"{BASE_URL}/workflows", headers=HEADERS, json={
"name": "Quick Image Generator",
"description": "Simple text-to-image workflow",
"definition": {
"version": "v1",
"input_schema": {
"type": "object",
"required": ["prompt"],
"properties": {"prompt": {"type": "string"}}
},
"steps": [{
"step_id": "generate",
"type": "model",
"model": "flux-1-1-pro",
"params": {"prompt": "{{inputs.prompt}}"}
}]
}
}).json()
workflow_id = workflow["workflow_id"]
print(f"Created workflow: {workflow_id}")
# 2. Trigger execution
execution = requests.post(
f"{BASE_URL}/{workflow_id}/trigger",
headers=HEADERS,
json={"inputs": {"prompt": "A serene zen garden at sunrise"}}
).json()
execution_id = execution["execution_id"]
print(f"Execution started: {execution_id}")
# 3. Poll for results
while True:
result = requests.get(
f"{BASE_URL}/executions/{execution_id}",
headers=HEADERS
).json()
if result["status"] in ("completed", "failed", "cancelled"):
break
print(f"Status: {result['status']}...")
time.sleep(3)
if result["status"] == "completed":
print(f"Output: {result['output']}")
else:
print(f"Error: {result.get('error_cause')}")