Metadata-Version: 2.4
Name: sol-ai-core
Version: 0.1.0
Summary: A professional Python Library for automated data cleaning, model selection, and visualization.
Project-URL: Homepage, https://github.com/yourusername/sol-ai-core
Author-email: Your Name <your.email@example.com>
License: MIT
Requires-Python: >=3.8
Requires-Dist: matplotlib>=3.4.0
Requires-Dist: openai>=1.0.0
Requires-Dist: pandas>=1.3.0
Requires-Dist: scikit-learn>=1.0.0
Description-Content-Type: text/markdown

# sol-ai-core

**SOL Engine** is now `sol-ai-core`, a professional, environment-agnostic Python library for automated data cleaning, machine learning model selection, and visualization.

## Features
- **Logic Separated:** Works seamlessly in any Python environment (Jupyter, VS Code, CI/CD) without requiring Streamlit.
- **Class-Based Design:** Easy to use object-oriented approach.
- **End-to-End Automation:** Pass a DataFrame, auto-clean it, train models, and generate insights in just a few lines of code.

## Installation

You can install the package via pip once published to PyPI:

```bash
pip install sol-ai-core
```

For local development:

```bash
git clone https://github.com/yourusername/sol-ai-core.git
cd sol-ai-core
pip install -e .
```

## Usage

```python
import pandas as pd
from sol_core.engine import SolEngine

# 1. Load your data
df = pd.read_csv("data.csv")

# 2. Initialize the engine
engine = SolEngine(df)

# 3. Clean the data automatically
clean_df = engine.auto_clean()

# 4. Train a model automatically (Classification or Regression)
report = engine.select_and_train_model(target_column="target")
print(report)

# 5. Generate Visualizations (Returns Matplotlib figure objects)
figures = engine.generate_visualizations(target_column="target")
figures['target_distribution'].show()
```

## Publishing to PyPI

To build and publish this library to PyPI, use the following commands:

```bash
# Install build tools and twine
pip install build twine

# Build the package (creates dist/ directory)
python -m build

# Upload to PyPI (will prompt for username and password/token)
python -m twine upload dist/*
```
