AI-based CO-wise mark splitter with Excel export for assessments.
Project description
🧠 AI Splitter
AI-Based CO-Wise Mark Splitter with Excel Export for Assessments
By Sathish Ramanujam • https://professor-sathish.github.io/
📌 Overview
AI Splitter is a simple and powerful tool for generating Course Outcome (CO)–wise mark split-ups for assessments. It uses AI-powered logic to automatically distribute marks based on your inputs and exports clean, formatted Excel split-up sheets instantly.
This tool is built for:
- Faculty members
- Assessment coordinators
- Examination cell teams
- Academic departments
The entire app runs in a Streamlit UI and exposes a single command:
ai-splitter
which opens the app immediately.
🚀 Features
- ✔ Automatic CO-wise mark splitting
- ✔ Instant Excel export (openpyxl)
- ✔ Clean Streamlit UI
- ✔ Works for all assessments (CIA, Assignment, Model, etc.)
- ✔ Lightweight & fast
- ✔ No configuration needed
- ✔ 100% offline after installation
📥 Installation
1. Install via pip
pip install ai-splitter
2. Run the app
ai-splitter
This launches your browser with the full Streamlit UI.
▶️ Usage
Once the app launches:
- Enter Assessment Name
- Enter Total Marks
- Enter Required CO Split Breakdown
- Click Generate
- Download the Excel output
Simple, fast, accurate.
🖥️ Launching the App Manually (Optional)
If you want to run the app manually:
streamlit run ai_splitter/app.py
OR using Python:
python -m streamlit run ai_splitter/app.py
⚠️ Windows Users — Important (PATH Fix)
If you installed Python from the Microsoft Store, the ai-splitter command may not work immediately.
You may see:
'ai-splitter' is not recognized as an internal or external command
This happens because Microsoft Store Python does not add the Scripts folder to PATH.
✔ Fix
Add this folder to your PATH:
%LocalAppData%\Packages\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\LocalCache\local-packages\Python311\Scripts
Steps:
- Press Win + R → type
sysdm.cpl→ Enter - Go to Advanced → Environment Variables
- Under User variables, select Path
- Click Edit → New
- Paste:
%LocalAppData%\Packages\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\LocalCache\local-packages\Python311\Scripts
- Save → close CMD → open new CMD
- Run:
ai-splitter
✔ Recommended Alternative (Best Practice)
Install Python from:
https://www.python.org/downloads/
Enable:
- Add Python to PATH
- Install for all users
🧩 CLI Command Reference
Launch the application:
ai-splitter
Show help:
ai-splitter --help
📦 Version
Current version: 0.1.2
👨💻 Developer
AI Splitter
Created by Sathish Ramanujam
Website: https://professor-sathish.github.io/
Department of Information Technology, KGiSL Institute of Technology
🔖 License
MIT License
Free for academic and educational use.
❤️ Acknowledgements
- Built with Python 3.9+
- UI powered by Streamlit
- Excel generation using openpyxl
- Developed with love for the academic community
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file ai_splitter-0.1.3.tar.gz.
File metadata
- Download URL: ai_splitter-0.1.3.tar.gz
- Upload date:
- Size: 12.6 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.13.7
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
f9fd1a2043815135bf63217191a478288528bc5a4592cbe6c8bba6b321ce6820
|
|
| MD5 |
1e2fbb389b2c9a65f1a5cdde5e6de514
|
|
| BLAKE2b-256 |
aa1757b87a4aabc2a79436732a735604f83056adf8d798457a5ed51634f3bce2
|
File details
Details for the file ai_splitter-0.1.3-py3-none-any.whl.
File metadata
- Download URL: ai_splitter-0.1.3-py3-none-any.whl
- Upload date:
- Size: 11.9 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.13.7
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
21167b1c4640487f1fe1ac462fce238d24bad33c553ce88bbf0cd3e0e8ccfb1c
|
|
| MD5 |
751dd6828b080e1f972c35d3965b5934
|
|
| BLAKE2b-256 |
06adfd8fe10150fa692053bb1976076115f5c3ed4e5c81854ec36eab15bd5bfc
|