Transforming Images with Moderation

Project Setup

# Create a project directory.
mkdir prodia-image-transformation
cd prodia-image-transformation

Install Node (if not already installed):

brew install node
# Close the current terminal and open a new one so that node is available.

apt install node
# Close the current terminal and open a new one so that node is available.

winget install -e --id OpenJS.NodeJS.LTS
# Close the current terminal and open a new one so that node is available.

Create project skeleton:

# Requires node --version >= 18
# Initialize the project with npm.
npm init -y

# Install the prodia-js library.
npm install prodia --save

Install Python (if not already installed):

brew install python
# Close the current terminal and open a new one so that python is available.

apt install python3 python3-venv python-is-python3
# Close the current terminal and open a new one so that python is available.

winget install -e --id Python.Python.3.12
# Close the current terminal and open a new one so that python is available.

# Requires python --version >= 3.12
python -m venv venv
source venv/bin/activate
pip install requests

Install curl (if not already installed):

brew install curl
# Close the current terminal and open a new one so that curl is available.

apt install curl
# Close the current terminal and open a new one so that curl is available.

# NOTE: Windows 10 and up have curl installed by default and this can be
# skipped.
winget install -e --id cURL.cURL
# Close the current terminal and open a new one so that curl is available.

# Export your token so it can be used by the main code.
export PRODIA_TOKEN=your-token-here

Create a main file for your project:

const { createProdia } = require("prodia/v2");

const prodia = createProdia({
    token: process.env.PRODIA_TOKEN // get it from environment
});

Create the following main.py

from requests.adapters import HTTPAdapter, Retry
import os
import requests
import sys


prodia_token = os.getenv('PRODIA_TOKEN')
prodia_url = 'https://inference.prodia.com/v2/job'

session = requests.Session()
retries = Retry(status_forcelist=Retry.RETRY_AFTER_STATUS_CODES)
session.mount('http://', HTTPAdapter(max_retries=retries))
session.mount('https://', HTTPAdapter(max_retries=retries))
session.headers.update({'Authorization': f"Bearer {prodia_token}"})

set -euo pipefail

You’re now ready to make some API calls!

Transform an image (inside a workflow)

const { createProdia } = require("prodia/v2"); // v2 :)
const fs = require("node:fs/promises"); // add this to imports at the top

const prodia = createProdia({
  token: process.env.PRODIA_TOKEN, // get it from environment
});

(async () => {
  // get input image
  const sunnyDay = await (await fetch("https://docs.prodia.com/sunny-day.jpg")).arrayBuffer();

  const job = await prodia.job({
    type: "workflow.serial.v1",
    config: {
      jobs: [
        {
          type: "inference.flux.schnell.img2img.v1",
          config: {
            prompt: "rainy landscape, 4k",
            strength: 0.8,
          },
        },
      ],
    },
  }, {
    inputs: [ sunnyDay ],
  });

  const rainyDay = await job.arrayBuffer();

  await fs.writeFile("rainy-day.jpg", new Uint8Array(rainyDay));
  // open rainy-day.jpg
})();

node main.js

from requests.adapters import HTTPAdapter, Retry
from io import BytesIO
import json
import os
import requests
import sys


prodia_token = os.getenv('PRODIA_TOKEN')
prodia_url = 'https://inference.prodia.com/v2/job'

session = requests.Session()
retries = Retry(status_forcelist=Retry.RETRY_AFTER_STATUS_CODES)
session.mount('http://', HTTPAdapter(max_retries=retries))
session.mount('https://', HTTPAdapter(max_retries=retries))
session.headers.update({'Authorization': f"Bearer {prodia_token}"})

try:
    with open('sunny-day.jpg', 'rb') as f:
        sunny_day = f.read()
except FileNotFoundError:
    res = requests.get('https://docs.prodia.com/sunny-day.jpg')
    sunny_day = BytesIO(res.content)
    with open('sunny-day.jpg', 'wb') as f:
        f.write(res.content)
except Exception as e:
    raise e

headers = {
    'Accept': 'image/png',
}

job = {
    'type': 'workflow.serial.v1',
    'config': {
        'jobs': [
            {
                'type': 'inference.flux.schnell.img2img.v1',
                'config': {
                    'prompt': 'rainy landscape, 4k',
                    'strength': 0.8,
                },
            },
        ],
    },
}

files = [
    ('job', ('job.json', BytesIO(json.dumps(job).encode('utf-8')), 'application/json')),
    ('input', ('sunny-day.jpg', sunny_day, 'image/jpeg')),
]

res = session.post(prodia_url, headers=headers, files=files)
print(f"Request ID: {res.headers['x-request-id']}")
print(f"Status: {res.status_code}")

if res.status_code != 200:
    print(res.text)
    sys.exit(1)

with open('rainy-day.jpg', 'wb') as f:
    f.write(res.content)

python main.py

set -euo pipefail

cat <<EOF > job.json
{
  "type": "workflow.serial.v1",
  "config": {
    "jobs": [
      {
        "type": "inference.flux.schnell.img2img.v1",
        "config": {
          "prompt": "rainy landscape, 4k",
          "strength": 0.8
        }
      }
    ]
  }
}
EOF

if ! [[ -f sunny-day.jpg ]]; then
  curl -Lo sunny-day.jpg 'https://docs.prodia.com/sunny-day.jpg'
fi

curl -sSf \
  -H "Authorization: Bearer $PRODIA_TOKEN" \
  -H 'Accept: image/jpeg' \
  -F [email protected] \
  -F [email protected] \
  --output rainy-day.jpg \
  --retry 3 \
  https://inference.prodia.com/v2/job

bash main.sh

open rainy-day.jpg

xdg-open rainy-day.jpg

start rainy-day.jpg

Adding content moderation

const { createProdia } = require("prodia/v2"); // v2 :)
const fs = require("node:fs/promises"); // add this to imports at the top

const prodia = createProdia({
  token: process.env.PRODIA_TOKEN, // get it from environment
});

(async () => {
  // get input image
  const sunnyDay = await (await fetch("https://docs.prodia.com/sunny-day.jpg")).arrayBuffer();

  const job = await prodia.job({
    type: "workflow.serial.v1",
    config: {
      jobs: [
        {
          type: "workflow.moderate.v1",
          config: {
            threshold: 0.95,
          },
        },
        {
          type: "inference.flux.schnell.img2img.v1",
          config: {
            prompt: "rainy landscape, 4k",
            strength: 0.8,
          },
        },
        {
          type: "workflow.moderate.v1",
          config: {
            threshold: 0.95,
          },
        },
      ],
    },
  }, {
    inputs: [ sunnyDay ],
  });

  const rainyDay = await job.arrayBuffer();

  await fs.writeFile("rainy-day.jpg", new Uint8Array(rainyDay));
  // open rainy-day.jpg
})();

node main.js

from requests.adapters import HTTPAdapter, Retry
from io import BytesIO
import json
import os
import requests
import sys


prodia_token = os.getenv('PRODIA_TOKEN')
prodia_url = 'https://inference.prodia.com/v2/job'

session = requests.Session()
retries = Retry(status_forcelist=Retry.RETRY_AFTER_STATUS_CODES)
session.mount('http://', HTTPAdapter(max_retries=retries))
session.mount('https://', HTTPAdapter(max_retries=retries))
session.headers.update({'Authorization': f"Bearer {prodia_token}"})

try:
    with open('sunny-day.jpg', 'rb') as f:
        sunny_day = f.read()
except FileNotFoundError:
    res = requests.get('https://docs.prodia.com/sunny-day.jpg')
    sunny_day = BytesIO(res.content)
    with open('sunny-day.jpg', 'wb') as f:
        f.write(res.content)
except Exception as e:
    raise e

headers = {
    'Accept': 'image/png',
}

job = {
    'type': 'workflow.serial.v1',
    'config': {
        'jobs': [
            {
                'type': 'workflow.moderate.v1',
                'config': {
                    'threshold': 0.95,
                },
            },
            {
                'type': 'inference.flux.schnell.img2img.v1',
                'config': {
                    'prompt': 'rainy landscape, 4k',
                    'strength': 0.8,
                },
            },
            {
                'type': 'workflow.moderate.v1',
                'config': {
                    'threshold': 0.95,
                },
            },
        ],
    },
}

files = [
    ('job', ('job.json', BytesIO(json.dumps(job).encode('utf-8')), 'application/json')),
    ('input', ('sunny-day.jpg', sunny_day, 'image/jpeg')),
]

res = session.post(prodia_url, headers=headers, files=files)
print(f"Request ID: {res.headers['x-request-id']}")
print(f"Status: {res.status_code}")

if res.status_code != 200:
    print(res.text)
    sys.exit(1)

with open('rainy-day.jpg', 'wb') as f:
    f.write(res.content)

python main.py

set -euo pipefail

cat <<EOF > job.json
{
  "type": "workflow.serial.v1",
  "config": {
    "jobs": [
      {
        "type": "workflow.serial.v1",
        "config": {
          "threshold": 0.95
        }
      },
      {
        "type": "inference.flux.schnell.img2img.v1",
        "config": {
          "prompt": "rainy landscape, 4k",
          "strength": 0.8
        }
      },
      {
        "type": "workflow.serial.v1",
        "config": {
          "threshold": 0.95
        }
      }
    ]
  }
}
EOF

if ! [[ -f sunny-day.jpg ]]; then
  curl -Lo sunny-day.jpg 'https://docs.prodia.com/sunny-day.jpg'
fi

curl -sSf \
  -H "Authorization: Bearer $PRODIA_TOKEN" \
  -H 'Accept: image/jpeg' \
  -F [email protected] \
  -F [email protected] \
  --output rainy-day.jpg \
  --retry 3 \
  https://inference.prodia.com/v2/job

bash main.sh

open rainy-day.jpg

xdg-open rainy-day.jpg

start rainy-day.jpg