GitHub - tabularis-ai/augini: augini: AI-Powered Tabular Data Assistant

from augini import DataEngineer, DataAnalyzer
import pandas as pd

# Sample customer data
df = pd.DataFrame({
    'CustomerID': ['C001', 'C002'],
    'Age': [25, 45],
    'MonthlyCharges': [50.0, 75.0]
})

# Initialize with your API key (supports OpenAI, OpenRouter, Azure)
engineer = DataEngineer(
    api_key="your-api-key",
    model="gpt-4o-mini",  # Use OpenRouter's GPT-4
    base_url="https://openrouter.ai/api/v1"  # Optional: use OpenRouter
)

# Generate customer insights
df = engineer.generate_features(
    df=df,
    new_feature_specs=[
        {
            'new_feature_name': 'CustomerSegment',
            'new_feature_description': 'Classify customer segment based on age and spending',
            'output_type': 'category',
            'constraints': {'categories': ['Premium', 'Regular', 'Budget']}
        },
        {
            'new_feature_name': 'ChurnRisk',
            'new_feature_description': 'Calculate churn risk score (0-100)',
            'output_type': 'float',
            'constraints': {'min': 0, 'max': 100}
        }
    ]
)

# Initialize analyzer for natural language insights
analyzer = DataAnalyzer(
    api_key="your-api-key",
    model="gpt-4o-mini",
)

# Fit data and ask questions
analyzer.fit(df)
insights = analyzer.chat("What patterns do you see in customer segments?")
print(insights)