Metadata-Version: 2.1
Name: snowflake-ai
Version: 0.1.0
Summary: A Snowflake centic Enterprise AI/ML framework with tight integration of popular data science libraries
Home-page: https://github.com/tonyxliu/snowflake-ai#readme
License: BSD-3-Clause
Keywords: AI,ML,Snowflake,Enterprise,AI/ML
Author: Tony Liu
Author-email: tony.liu@yahoo.com
Requires-Python: >=3.8.15,<3.9.0
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires-Dist: cryptography (>=40.0.1,<40.1.0)
Requires-Dist: importlib-resources (>=5.12.0,<5.13.0)
Requires-Dist: matplotlib (>=3.7.1,<3.8.0)
Requires-Dist: numpy (>=1.24.2,<1.25.0)
Requires-Dist: pandas (>=1.5.2,<1.6.0)
Requires-Dist: scikit-learn (>=1.2.2,<1.3.0)
Requires-Dist: snowflake-connector-python (>=3.0.2,<3.1.0)
Requires-Dist: snowflake-snowpark-python (>=1.2.0,<1.3.0)
Requires-Dist: toml (>=0.10.2,<0.11.0)
Description-Content-Type: text/markdown

[![Python 3.8](https://img.shields.io/badge/python-3.8-blue.svg)](https://www.python.org/downloads/release/python-380/)

Snowflake-AI
=======

*Snowflake_AI* is a Snowflake-centric **Enterprise AI/ML** framework with tight integration of popular Python data science libraries, e.g., *Pandas*, *Scikit-Learn*, *Tensorflow*, *Pytorch*, *MLFlow*, etc. This project simplifies the process of integrating your company's Snowflake data with those popular libraries, making it easier to develop and deploy machine learning models.

Installation
------

Before getting started, ensure you have *Poetry* installed on your system. You can install Poetry by following the instructions [here](https://python-poetry.org/docs/).

Next, clone [*this*](https://github.com/tonyxliu/snowflake-ai.git) repository and navigate to the project directory (assume you are in bash terminal):

```bash
git clone https://github.com/tonyxliu/snowflake-ai.git
cd snowflake-ai
```

Then, use Poetry to install all dependencies:

```bash
poetry install
```

Configuration
-------

Copy the sample configuration file and update the Snowflake connection parameters:

```bash
mkdir -p ~/snowflake_ai/conf
cp snowflake_ai/conf/app_config.toml ~/snowflake-ai/conf/
```

Edit snowflake_ai/conf/app_config.toml with your Snowflake connection details.

Usage
------

To get started with Snowflake-AI, import SnowConnect and DataFrameFactory from the library:

```python
from snowflake_ai.common import SnowConnect
from snowflake_ai.common import DataFrameFactory
```

Create a SnowConnect instance:

```python
connect = SnowConnect()
```

Specify the table/view or sql you want to work with and create a DataFrame:

```python
tbl_nm = 'SNOWFLAKE_SAMPLE_DATA.TPCH_SF1.CUSTOMER'
sdf = DataFrameFactory.create_df(tbl_nm, connect)
```

Display the contents of the DataFrame:

```python
sdf.show()
```

From here, you can use Snowflake-AI to preprocess and manipulate your data using Pandas and Scikit-Learn, train machine learning models, and perform predictions. Stay tuned, as there are many features in the pipelines waiting to be released.

Enjoy building your next AI/ML project with Snowflake-AI!

License
------

This project is licensed under the BSD 3-Clause License - see the [LICENSE](https://github.com/tonyxliu/snowflake-ai/blob/master/LICENSE) file for details.

