ilimikudi 0.3.1

Datasets for Gen AI customer care and data processing for Nigerian Banks and Fintech

IlimiKudi

IlimiKudi provides access to Fintech and Banking datasets like blog posts and support articles from platforms such as GTBank, Paystack, Moniepoint, and OPay. It is designed for use in AI-powered customer applications, including retrieval-augmented generation (RAG) for NLP.

Features

• Access datasets stored in CSV format.
• Query an integrated database with multiple data sources.

Installation

Install the required dependencies via pip:

pip install pandas duckdb

Usage

Accessing CSV Datasets

Load datasets using the following classes:

from ilimikudi import GTBSupportPosts

# Access GTB Support Posts data
gtb_posts = GTBSupportPosts()
data = gtb_posts.get_data()  # Return as pandas DataFrame
print(data.head())

Available classes for CSV files:

• GTBSupportPosts
• MergedData
• MoniepointBlogPosts
• OpayBlogPosts
• PaystackBlogPosts
• PaystackSupportPosts

Querying the Integrated Database

Query the integrated database:

from ilimikudi import MergedDB

# Query the integrated database
db = MergedDB()
result = db.query()  # Default: SELECT * FROM unified
print(result.head())

Custom queries can also be executed:

custom_query = "SELECT column_name FROM unified WHERE condition"
result = db.query(custom_query)
print(result)

License

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