Prerequisites
Before you begin, you’ll need:
- A free API key (get one instantly - click “Get API Key”)
- Python 3.8+, Node.js 18+, or Java 17+
Test keys (rv_test_*) are free and include 100 requests/day. No credit card required.
Installation
Install the Rotavision SDK for your preferred language:
Initialize the Client
from rotavision import Rotavision
client = Rotavision(api_key="rv_live_...")
# Or use environment variable ROTAVISION_API_KEY
client = Rotavision()
Your First API Call
Let’s analyze a model prediction for fairness using Vishwas:
# Analyze fairness of a loan approval model
result = client.vishwas.analyze(
model_id="loan-approval-v2",
dataset={
"features": ["age", "income", "credit_score", "gender", "location"],
"predictions": predictions,
"actuals": actuals,
"protected_attributes": ["gender", "location"]
},
metrics=["demographic_parity", "equalized_odds", "calibration"]
)
print(f"Fairness Score: {result.overall_score}")
print(f"Bias Detected: {result.bias_detected}")
for metric in result.metrics:
print(f" {metric.name}: {metric.value:.3f} ({metric.status})")
Example Response
{
"id": "analysis_abc123",
"model_id": "loan-approval-v2",
"overall_score": 0.82,
"bias_detected": true,
"metrics": [
{
"name": "demographic_parity",
"value": 0.78,
"threshold": 0.80,
"status": "warning",
"affected_groups": ["location:rural"]
},
{
"name": "equalized_odds",
"value": 0.91,
"threshold": 0.80,
"status": "pass"
},
{
"name": "calibration",
"value": 0.85,
"threshold": 0.80,
"status": "pass"
}
],
"recommendations": [
{
"severity": "medium",
"message": "Rural applicants have 22% lower approval rate despite similar creditworthiness",
"action": "Review feature weights for location-correlated variables"
}
],
"created_at": "2026-02-01T10:30:00Z"
}
Next Steps
Authentication
Learn about API keys, scopes, and security best practices
Vishwas Deep Dive
Explore all fairness metrics and explanation methods
Set Up Monitoring
Configure Guardian to monitor your models in production
Extract Documents
Use Dastavez to process Indian documents