Automate a content workflow tutorial
Automates a product content workflows with various Firefly Services APIs.
Overview
In this tutorial, let's imagine we are working for a creative marketing team at a gourmet food chain specializing in premium burgers. Our goal is to develop a visually stunning online menu and promotional materials that highlight the mouthwatering appeal of our products to customers worldwide. We will leverage Adobe's Firefly Services APIs to automate our content workflow:
- Remove Backgrounds: use the Photoshop Remove Background API to eliminate distracting backgrounds from our product images, allowing the items to stand out.
- Enhance Images with Generate Object Composite: Use the Firefly Generate Object Composite API to add creative and contextually relevant backgrounds that enhance the aesthetic appeal of each product.
- Optimize Image Quality: Utilize the Lightroom Auto Tone API to automatically adjust lighting and color balance, ensuring consistent and professional-quality images across our catalog.
Prerequisites
Credentials
If you don't already have a Firefly Services Client ID and Client Secret (which gives you access to Firefly APIs, Photoshop APIs, Lightroom APIs, and more), retrieve them from your Adobe Developer Console project before reading further. Securely store these credentials and never expose them in client-side or public code.
Set up your environment
Before we begin this tutorial, run the following in a secure terminal:
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JavaScript
mkdir firefly-services-content-workflow-tutorial
cd firefly-services-content-workflow-tutorial
npm init --y
npm install axios qs
touch index.js
Python
mkdir firefly-services-content-workflow-tutorial
cd firefly-services-content-workflow-tutorial
python -m pip install requests
touch main.py
Pre-signed URLs
To interact with Adobe's Firefly Services APIs, you'll need to generate pre-signed URLs. These URLs grant temporary access to your storage resources without exposing your credentials. For more details about pre-signed URLs, see AWS Sharing objects with presigned URLs, or Azure Storage resources using shared access signatures.
In this tutorial, you will need:
- A pre-signed URL with read access for the input image. Save this sample image to your cloud storage and generate a pre-signed URL:
- A pre-signed URL with read access for the style reference image below. Save this sample image to your cloud storage and generate a pre-signed URL:
- A pre-signed URL with a read/write token for the modified image.
Depending on your learning style, you may prefer to walk through this tutorial step-by-step or jump immediately to the full source code.
Retrieve an access token
Open a secure terminal and export your Client ID and Client Secret as environment variables so that your later commands can access them:
export FIREFLY_SERVICES_CLIENT_ID=yourClientIdAsdf123
export FIREFLY_SERVICES_CLIENT_SECRET=yourClientSecretAsdf123
Generate an access token:
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cURL
curl --location 'https://ims-na1.adobelogin.com/ims/token/v3' \
--header 'Content-Type: application/x-www-form-urlencoded' \
--data-urlencode 'grant_type=client_credentials' \
--data-urlencode "client_id=$FIREFLY_SERVICES_CLIENT_ID" \
--data-urlencode "client_secret=$FIREFLY_SERVICES_CLIENT_SECRET" \
--data-urlencode 'scope=openid,AdobeID,session,additional_info,read_organizations,firefly_api,ff_apis'
Python
def retrieve_access_token():
client_id = os.environ['FIREFLY_SERVICES_CLIENT_ID']
client_secret = os.environ['FIREFLY_SERVICES_CLIENT_SECRET']
token_url = 'https://ims-na1.adobelogin.com/ims/token/v3'
payload = {
'grant_type': 'client_credentials',
'client_id': client_id,
'client_secret': client_secret,
'scope': 'openid,AdobeID,session,additional_info,read_organizations,firefly_api,ff_apis'
}
response = requests.post(token_url, data=payload)
response.raise_for_status()
token_data = response.json()
print("Access Token Retrieved")
return token_data['access_token']
JavaScript
async function retrieveAccessToken() {
const data = qs.stringify({
grant_type: 'client_credentials',
client_id: process.env.FIREFLY_SERVICES_CLIENT_ID,
client_secret: process.env.FIREFLY_SERVICES_CLIENT_SECRET,
scope: 'openid,AdobeID,session,additional_info,read_organizations,firefly_api,ff_apis',
});
const config = {
method: 'post',
url: 'https://ims-na1.adobelogin.com/ims/token/v3',
headers: { 'Content-Type': 'application/x-www-form-urlencoded' },
data: data,
};
try {
const response = await axios.request(config);
console.log('Access Token Retrieved');
return response.data.access_token;
} catch (error) {
console.error('Error retrieving access token:', error.response.data);
}
}
The response will look like this:
{"access_token":"yourAccessTokenAsdf123","token_type":"bearer","expires_in":86399}
Export this access token in your secure terminal so that the next script can conveniently access it:
export FIREFLY_SERVICES_ACCESS_TOKEN=yourAccessTokenAsdf123
Remove Background - Photoshop API
Next, call the Photoshop Remove Background API:
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cURL
curl --location 'https://image.adobe.io/sensei/cutout' \
--header 'Content-Type: application/json' \
--header 'Accept: application/json' \
--header "x-api-key: $FIREFLY_SERVICES_CLIENT_ID" \
--header "Authorization: Bearer $FIREFLY_SERVICES_ACCESS_TOKEN" \
--data '{
"input":{
"href":"https://your-storage-bucket-name.blob.core.windows.net:443/container/input.jpeg?sv...&query=params...",
"storage":"azure"
},
"output":{
"href":"https://your-storage-bucket-name.blob.core.windows.net:443/container/output.jpeg?sv...&query=params...",
"storage":"azure"
}
}'
Python
# Replace with your actual pre-signed URLs and storage option
SIGNED_GET_URL = 'https://your-storage-bucket-name.blob.core.windows.net:443/images/asdf-12345?lots=of&query=params...'
SIGNED_POST_URL = 'https://your-storage-bucket-name.blob.core.windows.net:443/images/asdf-12345?lots=of&query=params...'
STORAGE = 'azure' # e.g., 'external', 'azure'
def remove_background(access_token):
headers = {
'Content-Type': 'application/json',
'Accept': 'application/json',
'x-api-key': os.environ['FIREFLY_SERVICES_CLIENT_ID'],
'Authorization': f'Bearer {access_token}'
}
data = {
'input': {
'href': SIGNED_GET_URL,
'storage': STORAGE
},
'output': {
'href': SIGNED_POST_URL,
'storage': STORAGE
}
}
response = requests.post('https://image.adobe.io/sensei/cutout', headers=headers, json=data)
response.raise_for_status()
job_response = response.json()
print("Remove Background Job Submitted:", job_response)
return job_response
JavaScript
const SIGNED_GET_URL = "https://your-storage-bucket-name.blob.core.windows.net:443/images/asdf-12345?lots=of&query=params...";
const SIGNED_POST_URL = "https://your-storage-bucket-name.blob.core.windows.net:443/images/asdf-12345?lots=of&query=params...";
const STORAGE = "azure"; // e.g., 'external', 'azure'
async function removeBackground(accessToken) {
const headers = {
'Content-Type': 'application/json',
Accept: 'application/json',
'x-api-key': process.env.FIREFLY_SERVICES_CLIENT_ID,
Authorization: `Bearer ${accessToken}`,
};
const data = {
input: { href: SIGNED_GET_URL, storage: STORAGE },
output: { href: SIGNED_POST_URL, storage: STORAGE },
};
const config = {
method: 'post',
url: 'https://image.adobe.io/sensei/cutout',
headers: headers,
data: data,
};
try {
const response = await axios.request(config);
console.log('Remove Background Job Submitted:', response.data);
return response.data;
} catch (error) {
console.error('Error during removeBackground:', error.response.data);
}
}
The response will look like this:
{
"_links": {
"self": {
"href": "https://image.adobe.io/sensei/status/<:jobId>"
}
}
}
Wait for a success status of this job.
Generate Object Composite - Firefly API
Next, call the Firefly Generate Object Composite API:
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cURL
curl --location 'https://firefly-api.adobe.io/v3/images/generate-object-composite-async' \
--header 'Content-Type: application/json' \
--header 'Accept: application/json' \
--header "x-api-key: $FIREFLY_SERVICES_CLIENT_ID" \
--header "Authorization: Bearer $FIREFLY_SERVICES_ACCESS_TOKEN" \
--data '{
"prompt": "A delicious fiery background",
"contentClass": "photo",
"image": {
"source": {
"url": "https://your-storage-bucket-name.blob.core.windows.net:443/container/input.jpeg?sv...&query=params..."
}
},
"placement": {
"alignment": {
"horizontal": "center",
"vertical": "center"
}
},
"style": {
"imageReference": {
"source": {
"url": "https://your-storage-bucket-name.blob.core.windows.net:443/container/style_ref.jpeg?sv...&query=params..."
}
},
"strength": 50
}
}'
Python
# Replace with your actual pre-signed URLs
SIGNED_IMAGE_GET_URL = 'https://your-storage-bucket-name.blob.core.windows.net:443/container/input.jpeg?sv...&query=params...'
SIGNED_STYLEREF_GET_URL = 'https://your-storage-bucket-name.blob.core.windows.net:443/container/style_ref.jpeg?sv...&query=params...'
def generate_object_composite(access_token):
headers = {
'Content-Type': 'application/json',
'Accept': 'application/json',
'x-api-key': os.environ['FIREFLY_SERVICES_CLIENT_ID'],
'Authorization': f'Bearer {access_token}'
}
data = {
'prompt': 'A delicious fiery background', # Replace with your actual prompt
'contentClass': 'photo',
'image': {
'source': {
'url': SIGNED_IMAGE_GET_URL
}
},
'placement': {
'alignment': {
'horizontal': 'center',
'vertical': 'center'
}
},
'style': {
'imageReference': {
'source': {
'url': SIGNED_STYLEREF_GET_URL
}
},
'strength': 50
}
}
response = requests.post(
'https://firefly-api.adobe.io/v3/images/generate-object-composite-async',
headers=headers,
json=data
)
response.raise_for_status()
job_response = response.json()
print("Generate Object Composite Job Submitted:", job_response)
return job_response
JavaScript
const SIGNED_IMAGE_GET_URL = 'https://your-storage-bucket-name.blob.core.windows.net:443/container/input.jpeg?sv...&query=params...'; // Replace with your image URL
const SIGNED_STYLEREF_GET_URL = 'https://your-storage-bucket-name.blob.core.windows.net:443/container/input.jpeg?sv...&query=params...'; // Replace with your mask URL
async function generateObjectComposite(accessToken) {
const headers = {
"Content-Type": "application/json",
Accept: "application/json",
"x-api-key": process.env.FIREFLY_SERVICES_CLIENT_ID,
Authorization: `Bearer ${accessToken}`,
};
const data = {
prompt: "A delicious firey background", // Replace with your actual prompt
contentClass: "photo",
image: {
source: {
url: SIGNED_IMAGE_GET_URL,
},
},
placement: {
alignment: {
horizontal: "center",
vertical: "center"
}
},
style: {
imageReference: {
source: {
url: SIGNED_STYLEREF_GET_URL
}
},
strength: 50
}
};
const config = {
method: "post",
url: "https://firefly-api.adobe.io/v3/images/generate-object-composite-async",
headers: headers,
data: data,
};
try {
const response = await axios.request(config);
return response.data;
} catch (error) {
console.error("Error during generateObjectComposite:", error);
}
}
The response will look like this:
{
"jobId": "urn:ff:jobs:eso851211:86ffe2ea-d765-4bd3-b2fd-1111",
"statusUrl": "https://firefly-api.adobe.io/v3/status/urn:ff:jobs:eso851211:86ffe2ea-d765-4bd3-b2fd-1111",
"cancelUrl": "https://firefly-api.adobe.io/v3/cancel/urn:ff:jobs:eso851211:86ffe2ea-d765-4bd3-b2fd-1111"
}
Wait for a success status of this job.
Auto Tone - Lightroom API
Next, call the Lightroom Auto Tone API:
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cURL
curl --location 'https://image.adobe.io/lrService/autoTone' \
--header 'Content-Type: application/json' \
--header 'Accept: application/json' \
--header "x-api-key: $FIREFLY_SERVICES_CLIENT_ID" \
--header "Authorization: Bearer $FIREFLY_SERVICES_ACCESS_TOKEN" \
--data '{
"inputs":{
"href":"https://your-storage-bucket-name.blob.core.windows.net:443/container/input.jpeg?sv...&query=params...",
"storage":"azure"
},
"outputs":[{
"href":"https://your-storage-bucket-name.blob.core.windows.net:443/container/output.jpeg?sv...&query=params...",
"storage":"azure",
"type":"image/jpeg"
}]
}'
Python
# Replace with your actual pre-signed URLs and storage option
SIGNED_GET_URL = 'https://your-storage-bucket-name.blob.core.windows.net:443/container/input.jpeg?sv...&query=params...'
SIGNED_POST_URL = 'https://your-storage-bucket-name.blob.core.windows.net:443/container/output.jpeg?sv...&query=params...'
storage = 'azure' # e.g., 'external', 'azure'
def auto_tone(access_token):
headers = {
'Content-Type': 'application/json',
'Accept': 'application/json',
'x-api-key': os.environ['FIREFLY_SERVICES_CLIENT_ID'],
'Authorization': f'Bearer {access_token}'
}
data = {
'inputs': {
'href': SIGNED_GET_URL,
'storage': STORAGE
},
'outputs': [{
'href': SIGNED_POST_URL,
'storage': STORAGE,
'type': 'image/jpeg'
}]
}
response = requests.post('https://image.adobe.io/lrService/autoTone', headers=headers, json=data)
response.raise_for_status()
job_response = response.json()
print("Auto Tone Job Submitted:", job_response)
return job_response
JavaScript
const SIGNED_GET_URL = "https://your-storage-bucket-name.blob.core.windows.net:443/container/input.jpeg?sv...&query=params...";
const SIGNED_POST_URL = "https://your-storage-bucket-name.blob.core.windows.net:443/container/output.jpeg?sv...&query=params...";
const STORAGE = "azure"; // e.g., 'external', 'azure'
async function autoTone(accessToken) {
const headers = {
"Content-Type": "application/json",
Accept: "application/json",
"x-api-key": process.env.FIREFLY_SERVICES_CLIENT_ID,
Authorization: `Bearer ${accessToken}`,
};
const data = {
inputs: {
href: SIGNED_GET_URL,
storage: storage,
},
outputs: [
{
href: SIGNED_POST_URL,
storage: storage,
type: "image/jpeg",
},
],
};
const config = {
method: "post",
url: "https://image.adobe.io/lrService/autoTone",
headers: headers,
data: data,
};
try {
const response = await axios.request(config);
return response.data;
} catch (error) {
console.error("Error during autoTone:", error);
}
}
The response will look like this:
{
"_links": {
"self": {
"href": "https://image.adobe.io/lrService/status/<:jobId>"
}
}
}
Wait for a success status of this job.
View final image
Access the final at the outputs[0]._links.self.href URL (the SIGNED_POST_URL provided earlier). 🎉
Full example
You can review the prerequisites section to understand how to set up your environment prior to running this code. Note that this is an example only and is not production-ready and requires additional error handling, logging, security measures, and more before you can run it at scale in a live application.
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Python
import os
import time
import requests
# Replace with your actual pre-signed URLs and storage option
SIGNED_PRODUCT_URL = 'https://your-storage-bucket-name.blob.core.windows.net:443/images/asdf-12345?lots=of&query=params...' # Input product URL for Photoshop
SIGNED_GET_POST_URL = 'https://your-storage-bucket-name.blob.core.windows.net:443/images/asdf-12345?lots=of&query=params...' # Output product URL for Photoshop and Lightroom
SIGNED_STYLE_REF_URL = 'https://your-storage-bucket-name.blob.core.windows.net:443/images/asdf-12345?lots=of&query=params...' # Style reference image URL for Firefly
STORAGE = 'azure' # e.g., 'external', 'azure'
def main():
access_token = retrieve_access_token()
# Step 1: Remove Background
remove_bg_response = remove_background(access_token)
remove_bg_job_id = extract_job_id(remove_bg_response)
check_photoshop_job_status(remove_bg_job_id, access_token)
# Step 2: Generate Object Composite
generate_object_composite_response = generate_object_composite(access_token)
generate_object_composite_job_id = generate_object_composite_response['jobId']
generate_object_composite_output = check_firefly_job_status(generate_object_composite_job_id, access_token)
# Step 3: Auto Tone
auto_tone_response = auto_tone(access_token, generate_object_composite_output)
auto_tone_job_id = extract_job_id(auto_tone_response)
check_lightroom_job_status(auto_tone_job_id, access_token)
def retrieve_access_token():
client_id = os.environ['FIREFLY_SERVICES_CLIENT_ID']
client_secret = os.environ['FIREFLY_SERVICES_CLIENT_SECRET']
token_url = 'https://ims-na1.adobelogin.com/ims/token/v3'
payload = {
'grant_type': 'client_credentials',
'client_id': client_id,
'client_secret': client_secret,
'scope': 'openid,AdobeID,session,additional_info,read_organizations,firefly_api,ff_apis'
}
response = requests.post(token_url, data=payload)
response.raise_for_status()
token_data = response.json()
print("Access Token Retrieved")
return token_data['access_token']
def remove_background(access_token):
headers = {
'Content-Type': 'application/json',
'Accept': 'application/json',
'x-api-key': os.environ['FIREFLY_SERVICES_CLIENT_ID'],
'Authorization': f'Bearer {access_token}'
}
data = {
'input': {
'href': SIGNED_PRODUCT_URL,
'storage': STORAGE
},
'output': {
'href': SIGNED_GET_POST_URL,
'storage': STORAGE
}
}
response = requests.post('https://image.adobe.io/sensei/cutout', headers=headers, json=data)
response.raise_for_status()
job_response = response.json()
print("Remove Background Job Submitted:", job_response)
return job_response
def check_photoshop_job_status(job_id, access_token):
headers = {
'x-api-key': os.environ['FIREFLY_SERVICES_CLIENT_ID'],
'Authorization': f'Bearer {access_token}'
}
url = f'https://image.adobe.io/sensei/status/{job_id}'
status = 'submitted'
while status not in ['succeeded', 'failed']:
time.sleep(5) # Wait for 5 seconds
response = requests.get(url, headers=headers)
response.raise_for_status()
status_response = response.json()
status = status_response.get('status')
print(f'Photoshop Job Status: {status}')
if status == 'succeeded':
print('Background removal completed successfully!')
else:
print('Background removal failed.')
def generate_object_composite(access_token):
headers = {
'Content-Type': 'application/json',
'Accept': 'application/json',
'x-api-key': os.environ['FIREFLY_SERVICES_CLIENT_ID'],
'Authorization': f'Bearer {access_token}'
}
data = {
'prompt': 'A delicious fiery background', # Replace with your actual prompt
'contentClass': 'photo',
'image': {
'source': {
'url': SIGNED_GET_POST_URL
}
},
'placement': {
'alignment': {
'horizontal': 'center',
'vertical': 'center'
}
},
'style': {
'imageReference': {
'source': {
'url': SIGNED_STYLE_REF_URL
}
},
'strength': 50
}
}
response = requests.post(
'https://firefly-api.adobe.io/v3/images/generate-object-composite-async',
headers=headers,
json=data
)
response.raise_for_status()
job_response = response.json()
print("Generate Object Composite Job Submitted:", job_response)
return job_response
def check_firefly_job_status(job_id, access_token):
client_id = os.environ['FIREFLY_SERVICES_CLIENT_ID']
headers = {
'x-api-key': client_id,
'Authorization': f'Bearer {access_token}'
}
url = f'https://firefly-api.adobe.io/v3/status/{job_id}'
status = 'pending'
while status not in ['succeeded', 'failed', 'cancelled']:
time.sleep(5) # Wait for 5 seconds
response = requests.get(url, headers=headers)
response.raise_for_status()
status_response = response.json()
status = status_response.get('status')
print(f'Firefly Job Status: {status}')
if status == 'succeeded':
print('Object composite generation completed successfully!')
image_url = status_response['result']['outputs'][0]['image']['url']
print(f'You can access the image at: {image_url}')
return image_url
else:
print('Object composite generation failed.')
def auto_tone(access_token, signed_input_url):
client_id = os.environ['FIREFLY_SERVICES_CLIENT_ID']
headers = {
'Content-Type': 'application/json',
'Accept': 'application/json',
'x-api-key': client_id,
'Authorization': f'Bearer {access_token}'
}
data = {
'inputs': {
'href': signed_input_url,
'storage': 'external'
},
'outputs': [{
'href': SIGNED_GET_POST_URL,
'storage': STORAGE,
'type': 'image/jpeg'
}]
}
response = requests.post('https://image.adobe.io/lrService/autoTone', headers=headers, json=data)
response.raise_for_status()
job_response = response.json()
print("Auto Tone Job Submitted:", job_response)
return job_response
def check_lightroom_job_status(job_id, access_token):
client_id = os.environ['FIREFLY_SERVICES_CLIENT_ID']
headers = {
'x-api-key': client_id,
'Authorization': f'Bearer {access_token}'
}
url = f'https://image.adobe.io/lrService/status/{job_id}'
status = 'pending'
while status not in ['succeeded', 'failed']:
time.sleep(5) # Wait for 5 seconds
response = requests.get(url, headers=headers)
response.raise_for_status()
status_response = response.json()
outputs = status_response.get('outputs', [])
if outputs:
status = outputs[0].get('status')
print(f'Lightroom Job Status: {status}')
if status == 'succeeded':
print('Auto tone completed successfully!')
print('You can access the image at your SIGNED_POST_URL.')
else:
print('Auto tone failed.')
def extract_job_id(response):
href = response['_links']['self']['href']
return href.split('/')[-1]
if __name__ == '__main__':
main()
JavaScript
const axios = require('axios');
const qs = require('qs');
// Replace with your actual pre-signed URLs and storage option
const SIGNED_PRODUCT_URL = 'https://your-storage-bucket-name.blob.core.windows.net:443/images/asdf-12345?lots=of&query=params...'; // Input product URL for Photoshop
const SIGNED_GET_POST_URL = 'https://your-storage-bucket-name.blob.core.windows.net:443/images/asdf-12345?lots=of&query=params...'; // Output product URL for Photoshop and Lightroom
const SIGNED_STYLE_REF_URL = 'https://your-storage-bucket-name.blob.core.windows.net:443/images/asdf-12345?lots=of&query=params...'; // Style reference image URL for Firefly
const STORAGE = 'azure'; // e.g., 'external', 'azure'
(async () => {
const accessToken = await retrieveAccessToken();
// Step 1: Remove Background
const removeBgResponse = await removeBackground(accessToken);
const removeBgJobId = extractJobId(removeBgResponse);
await checkPhotoshopJobStatus(removeBgJobId, accessToken);
// Step 2: Generate Object Composite
const generateObjectCompositeResponse = await generateObjectComposite(accessToken);
const generateObjectCompositeJobId = generateObjectCompositeResponse.jobId;
const compositeOutputUrl = await checkFireflyJobStatus(generateObjectCompositeJobId, accessToken);
// Step 3: Auto Tone
const autoToneResponse = await autoTone(accessToken, compositeOutputUrl);
const autoToneJobId = extractJobId(autoToneResponse);
await checkLightroomJobStatus(autoToneJobId, accessToken);
})();
async function retrieveAccessToken() {
const clientId = process.env.FIREFLY_SERVICES_CLIENT_ID;
const clientSecret = process.env.FIREFLY_SERVICES_CLIENT_SECRET;
const data = qs.stringify({
grant_type: 'client_credentials',
client_id: clientId,
client_secret: clientSecret,
scope: 'openid,AdobeID,session,additional_info,read_organizations,firefly_api,ff_apis',
});
const config = {
method: 'post',
url: 'https://ims-na1.adobelogin.com/ims/token/v3',
headers: {
'Content-Type': 'application/x-www-form-urlencoded',
},
data: data,
};
try {
const response = await axios(config);
console.log('Access Token Retrieved');
return response.data.access_token;
} catch (error) {
console.error('Error retrieving access token:', error.response?.data || error.message);
}
}
async function removeBackground(accessToken) {
const headers = {
'Content-Type': 'application/json',
Accept: 'application/json',
'x-api-key': process.env.FIREFLY_SERVICES_CLIENT_ID,
Authorization: `Bearer ${accessToken}`,
};
const data = {
input: {
href: SIGNED_PRODUCT_URL,
storage: STORAGE,
},
output: {
href: SIGNED_GET_POST_URL,
storage: STORAGE,
},
};
const config = {
method: 'post',
url: 'https://image.adobe.io/sensei/cutout',
headers: headers,
data: data,
};
try {
const response = await axios(config);
console.log('Remove Background Job Submitted:', response.data);
return response.data;
} catch (error) {
console.error('Error during removeBackground:', error.response?.data || error.message);
}
}
async function checkPhotoshopJobStatus(jobId, accessToken) {
const headers = {
'x-api-key': process.env.FIREFLY_SERVICES_CLIENT_ID,
Authorization: `Bearer ${accessToken}`,
};
const url = `https://image.adobe.io/sensei/status/${jobId}`;
let status = 'submitted';
while (status !== 'succeeded' && status !== 'failed') {
await new Promise((resolve) => setTimeout(resolve, 5000)); // Wait for 5 seconds
const response = await axios.get(url, { headers: headers });
status = response.data.status;
console.log(`Photoshop Job Status: ${status}`);
}
if (status === 'succeeded') {
console.log('Background removal completed successfully!');
} else {
console.error('Background removal failed.');
}
}
async function generateObjectComposite(accessToken) {
const headers = {
'Content-Type': 'application/json',
Accept: 'application/json',
'x-api-key': process.env.FIREFLY_SERVICES_CLIENT_ID,
Authorization: `Bearer ${accessToken}`,
};
const data = {
prompt: 'A delicious fiery background', // Replace with your actual prompt
contentClass: 'photo',
image: {
source: {
url: SIGNED_GET_POST_URL,
},
},
placement: {
alignment: {
horizontal: 'center',
vertical: 'center',
},
},
style: {
imageReference: {
source: {
url: SIGNED_STYLE_REF_URL,
},
},
strength: 50,
},
};
const config = {
method: 'post',
url: 'https://firefly-api.adobe.io/v3/images/generate-object-composite-async',
headers: headers,
data: data,
};
try {
const response = await axios(config);
console.log('Generate Object Composite Job Submitted:', response.data);
return response.data;
} catch (error) {
console.error('Error during generateObjectComposite:', error.response?.data || error.message);
}
}
async function checkFireflyJobStatus(jobId, accessToken) {
const headers = {
'x-api-key': process.env.FIREFLY_SERVICES_CLIENT_ID,
Authorization: `Bearer ${accessToken}`,
};
const url = `https://firefly-api.adobe.io/v3/status/${jobId}`;
let status = 'pending';
let imageUrl = null;
while (status !== 'succeeded' && status !== 'failed' && status !== 'cancelled') {
await new Promise((resolve) => setTimeout(resolve, 5000)); // Wait for 5 seconds
const response = await axios.get(url, { headers: headers });
status = response.data.status;
console.log(`Firefly Job Status: ${status}`);
}
if (status === 'succeeded') {
console.log('Object composite generation completed successfully!');
imageUrl = response.data.result.outputs[0].image.url;
console.log(`You can access the image at: ${imageUrl}`);
return imageUrl;
} else {
console.error('Object composite generation failed.');
}
}
async function autoTone(accessToken, signedInputUrl) {
const headers = {
'Content-Type': 'application/json',
Accept: 'application/json',
'x-api-key': process.env.FIREFLY_SERVICES_CLIENT_ID,
Authorization: `Bearer ${accessToken}`,
};
const data = {
inputs: {
href: signedInputUrl,
storage: 'external',
},
outputs: [
{
href: SIGNED_GET_POST_URL,
storage: STORAGE,
type: 'image/jpeg',
},
],
};
const config = {
method: 'post',
url: 'https://image.adobe.io/lrService/autoTone',
headers: headers,
data: data,
};
try {
const response = await axios(config);
console.log('Auto Tone Job Submitted:', response.data);
return response.data;
} catch (error) {
console.error('Error during autoTone:', error.response?.data || error.message);
}
}
async function checkLightroomJobStatus(jobId, accessToken) {
const headers = {
'x-api-key': process.env.FIREFLY_SERVICES_CLIENT_ID,
Authorization: `Bearer ${accessToken}`,
};
const url = `https://image.adobe.io/lrService/status/${jobId}`;
let status = 'pending';
while (status !== 'succeeded' && status !== 'failed') {
await new Promise((resolve) => setTimeout(resolve, 5000)); // Wait for 5 seconds
const response = await axios.get(url, { headers: headers });
const outputs = response.data.outputs || [];
if (outputs.length > 0) {
status = outputs[0].status;
}
console.log(`Lightroom Job Status: ${status}`);
}
if (status === 'succeeded') {
console.log('Auto tone completed successfully!');
console.log('You can access the image at your SIGNED_GET_POST_URL.');
} else {
console.error('Auto tone failed.');
}
}
function extractJobId(response) {
const href = response._links.self.href;
return href.split('/').pop();
}
Deepen your understanding
Dive deeper into Firefly Services by exploring our Firefly API task tutorials.