Privacy SDK — Python, Node.js, cURL Examples
Analyze, anonymize, encrypt, decrypt PII via REST API. Token-based pricing (200 free tokens). Bearer token auth. Sub-200ms response time. Code examples for Python, Node.js, JavaScript, cURL.
SDK & Code Examples
🐍 Python SDK
pip install anonym-legal
# Coming soon
import anonymize
client = anonymize.Client(
api_key="YOUR_API_KEY",
base_url="https://anonym.legal/api"
)
result = client.analyze(
text="John Smith, SSN 123-45-6789",
language="en"
)
print(result.entities)
📦 Node.js SDK
npm install @anonym-legal/sdk
# Coming soon
const { AnonymClient } = require(
"@anonym-legal/sdk"
);
const client = new AnonymClient({
apiKey: process.env.API_KEY
});
const result = await client.analyze({
text: "Jane Doe, email jane@ex.com",
language: "en"
});
console.log(result.entities);
API Endpoints
📋 /analyze
Detect & extract PII entities from text. Returns entity types, positions, confidence scores.
🔒 /anonymize
Replace detected PII with redactions, masks, hashes, or encryption. Returns anonymized text.
🔓 /decrypt
Decrypt previously encrypted PII. Requires decryption key. Bearer token auth.
cURL Example: Analyze
curl -X POST https://anonym.legal/api/presidio/analyze \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"text": "John Smith works at Acme Corp",
"language": "en"
}'
# Response
{
"entities": [
{
"type": "PERSON",
"value": "John Smith",
"start": 0,
"end": 10,
"score": 0.95
},
{
"type": "ORGANIZATION",
"value": "Acme Corp",
"start": 21,
"end": 30,
"score": 0.88
}
]
}
Token-Based Pricing
Free Plan
200 tokens/month. 1 token per 100 characters analyzed. Ideal for learning & testing.
Pro Plan
€3/1,000 tokens. Scale to 100K+ characters/month. Priority support.
Use Case: AI Pipeline Integration
LLM Privacy Layer
from langchain.chat_models import ChatOpenAI
from anonym_legal import AnonymClient
client = AnonymClient(api_key=KEY)
llm = ChatOpenAI(model="gpt-4")
# Customer input with PII
user_input = "My name is John, SSN 123-45-6789"
# Sanitize before LLM
sanitized = client.anonymize(
text=user_input,
method="mask"
)
# Safe to send to LLM
response = llm.predict(text=sanitized)
Watch the API In Action
See PII detection and anonymization via REST API and MCP Server
Get Started with API
Sign up for free API key. 200 tokens included. Code examples in Python, Node.js, cURL. Sub-200ms response time.
Get API KeyAlso from anonym.legal