sql-ai-faker 1.0.0

AI-powered fake data generator for SQLAlchemy models using LLMs

AI Faker

AI-powered fake data generator for SQLAlchemy models using LLMs (OpenAI, Gemini).

Features

• Generate realistic fake data using AI/LLM
• Batch generation for efficiency
• Support for OpenAI and Google's Gemini
• SQLAlchemy integration
• Type-aware data generation
• Unique constraint handling
• Relationship support

Installation

# Install with OpenAI support
pip install ai_faker[openai]

# Install with Gemini support
pip install ai_faker[gemini]

# Install with all providers
pip install ai_faker[all]

Quick Start

from sqlalchemy import create_engine, Column, Integer, String
from sqlalchemy.orm import declarative_base
from ai_faker import DataGenerator, LLMInterface
from ai_faker.core.llm_providers import OpenAIProvider

# Create your SQLAlchemy model
Base = declarative_base()

class User(Base):
    __tablename__ = 'users'
    id = Column(Integer, primary_key=True)
    username = Column(String(50), unique=True)
    email = Column(String(100), unique=True)

# Initialize the provider and generator
provider = OpenAIProvider(api_key="your-api-key")
llm = LLMInterface(provider)
generator = DataGenerator(llm)

# Generate fake data
fake_users = generator.generate_fake_data(User, count=50)

print(fake_users)

Environment Variables

Create a .env file:

# OpenAI
OPENAI_API_KEY=your-openai-key

# Gemini
GOOGLE_API_KEY=your-google-key

Supported Providers

OpenAI

• Uses GPT models
• Requires OpenAI API key

Gemini

• Uses Google's Gemini models
• Requires Google API key

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.