README.md

metadata

title: PersonaMind – ML Model for Extrovert vs Introvert Classification
emoji: 🧠
colorFrom: blue
colorTo: red
sdk: streamlit
sdk_version: 1.40.0
app_file: app.py
pinned: false
license: mit

PersonalityClassifier — Introvert vs Extrovert Predictor

A lightweight Streamlit app that predicts whether a person is likely an Introvert or Extrovert from simple daily-behavior inputs.

---

Table of Contents

• Demo
• Features
• Installation / Setup
• Usage
• Configuration / Options
• Contributing
• License
• Acknowledgements / Credits

---

Demo

Real demo assets found in ./demo/:

• Image: ./demo/demo.png
• Video: ./demo/demo.mp4

Example render:

If your viewer supports video playback in Markdown, you can also preview the short clip:

./demo/demo.mp4

---

Features

• Simple UI built with streamlit for quick interaction.
• Preprocessing utilities in utils.py convert raw inputs to model-ready features.
• Saved model loading via joblib from ./models/model.pkl.
• Deterministic inference using a binary classifier (Introvert vs Extrovert).

---

Installation / Setup

Use a Python virtual environment for isolation.

# Create a virtual environment
python -m venv .venv

# Activate it
# On Linux/Mac:
source .venv/bin/activate
# On Windows:
.venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

---

Usage

Run the Streamlit app locally:

streamlit run app.py

App entrypoint: app.py

• Loads the model using utils.load_model("./models/model.pkl").
• Renders inputs and predictions using helpers in ui.py.

Expected project structure:

PersonalityClassifier/
├─ app.py
├─ ui.py
├─ utils.py
├─ models/
│  └─ model.pkl
└─ demo/
   ├─ demo.png
   └─ demo.mp4

---

Configuration / Options

• Model path: ./models/model.pkl (default in app.py). Replace the file if you want another trained model. Ensure the environment includes the libraries used to train/serialize it (e.g., scikit-learn).
• Caching: utils.load_model uses @st.cache_resource to cache the loaded model across reruns.

---

Contributing

Contributions are welcome! Please:

• Open an issue to discuss proposed changes.
• Create a PR with a clear description, small focused commits, and screenshots for UI changes.

---

License

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

---

Acknowledgements / Credits

• Streamlit for rapid web UI development.
• scikit-learn and joblib for model training/serialization workflows.