augini

Build and Enhance Custom Datasets for your Use Case

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Data Augmentation

Enhance and enrich your datasets with AI-generated features, contextual insights, and domain-specific knowledge.

Data Anonymization

Achieve privacy with k-anonymity and l-diversity while maintaining data utility through synthetic identifiers.

Synthetic Data Generation & Extantion

Create realistic, diverse datasets that preserve statistical integrity and enable coherent synthetic profiles.

> Installation

pip install augini

> Example

from augini import Augini
import pandas as pd

api_key = "OpenAI or OpenRouter"

# OpenAI
augini = Augini(api_key=api_key,  model='gpt-4-turbo', use_openrouter=False)

# OpenRouter 
augini = Augini(api_key=api_key, use_openrouter=True, model='meta-llama/llama-3-8b-instruct')

# Create a sample DataFrame
data = {
    'Place of Birth': ['New York', 'London', 'Tokyo'],
    'Age': [30, 25, 40],
    'Gender': ['Male', 'Female', 'Male']
}
df = pd.DataFrame(data)

# Add synthetic features
result_df = augini.augment_columns(df, ['NAME', 'OCCUPATION', 'FAVORITE_DRINK'])

print(result_df)