Step 1: Initial Request (get Invoice)

Send your base64 image. You will receive a 402 Payment Required response with a Lightning invoice.

Request body:

{
  "image": "<base64-encoded-image>"
}

Example curl command:

curl -X POST https://sats4ai.com/api/l402/detect-nsfw \
-H "Content-Type: application/json" \
-d '{
  "image": "<base64-encoded-image>"
}' \
-i

Expected response headers:

www-authenticate: L402 macaroon="<YOUR_MACAROON>", invoice="<LIGHTNING_INVOICE>"

Step 2: Pay the Lightning Invoice

Pay the invoice with any Lightning wallet (Phoenix, Muun, Alby, Wallet of Satoshi, etc.). Save the preimage your wallet provides after payment.

Step 3: Re-send with Payment Proof

Send the exact same request again with the Authorization header.

The JSON payload must be identical to Step 1.

curl -X POST https://sats4ai.com/api/l402/detect-nsfw \
-H "Content-Type: application/json" \
-H "Authorization: L402 <YOUR_MACAROON>:<YOUR_PREIMAGE>" \
-d '{
  "image": "<base64-encoded-image>"
}'

Example response:

{
  "classification": "normal",
  "is_nsfw": false
}

Easier: Use lnget

lnget handles the full L402 flow automatically — invoice, payment, and re-request in one command.

IMAGE_B64=$(base64 -w0 photo.png)

lnget -X POST https://sats4ai.com/api/l402/detect-nsfw \
  --json "{\"image\":\"$IMAGE_B64\"}"

Python Example

import requests, base64

# Encode image
with open("photo.png", "rb") as f:
    image_b64 = base64.b64encode(f.read()).decode()

payload = { "image": image_b64 }

# Step 1 — get invoice
r = requests.post("https://sats4ai.com/api/l402/detect-nsfw",
    json=payload,
    headers={"Content-Type": "application/json"})
# r.status_code == 402
# Parse macaroon and invoice from r.headers["www-authenticate"]

# Step 2 — pay invoice with your Lightning wallet, get preimage

# Step 3 — re-send with auth
r2 = requests.post("https://sats4ai.com/api/l402/detect-nsfw",
    json=payload,
    headers={
        "Content-Type": "application/json",
        "Authorization": "L402 <macaroon>:<preimage>"
    })
result = r2.json()
print(result["classification"])  # "normal", "suggestive", or "explicit"
print(result["is_nsfw"])         # true or false

Request Parameters

Pricing

2 sats per image.

Use Cases

• Content moderation pipelines for user-uploaded images
• Pre-filter images before processing with other AI tools
• Automated safety checks in agent workflows
• Batch classification of image datasets