title	Akaike Email Classifier 🚀
emoji	✉️
colorFrom	blue
colorTo	green
sdk	gradio
sdk_version	3.50.2
app_file	app.py
pinned	false

Akaike Email Classification API 🚀

This project implements an Email Classification System that:

• 🔒 Masks Personally Identifiable Information (PII) from incoming support emails.
• 🧠 Classifies emails into predefined categories like Billing Issues, Technical Support, Account Management, etc.
• 🚀 Deploys the full pipeline as an interactive API using Gradio.

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📋 Features

• Regex + SpaCy NER based PII masking (without using heavy LLMs)
• TF-IDF + Logistic Regression based email classification
• Gradio Interface for quick testing and deployment
• Clean structured JSON output showing masked email and detected PII entities

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🛠 Technologies Used

• Python 3.12.9
• Scikit-learn (Model Training & Evaluation)
• SpaCy (Named Entity Recognition)
• Gradio (User Interface Deployment on Hugging Face)
• FastAPI Architecture Principles
• Pandas (Data Handling)

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🚀 Setup Instructions

# Clone or download the repository

# Optional: Create a virtual environment
python -m venv env
source env/bin/activate  # Linux/macOS
# OR
env\Scripts\activate     # Windows

# Install project dependencies
pip install -r requirements.txt

# Download SpaCy English model
python -m spacy download en_core_web_sm

# (Optional) Re-train the model if needed
python train_models.py

# Launch the Gradio App
python app.py

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📤 API Usage

Input:

• Email text via Gradio textbox.

Output:

• Masked Email
• Predicted Category
• List of Detected Entities (position, type, original text)

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🧠 Author

• Sarthak | Akaike Assignment | 2025