DEPLOY.md

🚀 Deployment Guide

Google Colab (Recommended for Mac M2)

Perfect for Mac M2 users - avoids PyTorch MPS mutex lock issues!

Quick Start

1. Open Google Colab
2. Create a new notebook
3. Run:

!pip install -q transformers torch pandas gradio kagglehub
!git clone https://github.com/ChauHPham/AITextDetector.git
%cd AITextDetector
!git checkout main
!python gradio_app.py

4. Get your public link: After running, you'll see:

   * Running on public URL: https://xxxxx.gradio.live
   

   This link is shareable and works as long as the Colab notebook is running!

Keep It Running

• Enable "Keep runtime alive" in Colab's runtime settings
• The public link expires after 1 week of inactivity
• For permanent hosting, use Hugging Face Spaces (see below)

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Hugging Face Spaces (Permanent Hosting)

Deploy your app permanently to Hugging Face Spaces for free!

Option 1: Deploy from Google Colab

Perfect for Mac M2 users - deploy directly from Colab!

# 1. Install dependencies
!pip install -q gradio huggingface_hub

# 2. Clone your repo (if not already done)
!git clone https://github.com/ChauHPham/AITextDetector.git
%cd AITextDetector

# 3. Login to Hugging Face (you'll need a token)
# Get your token from: https://huggingface.co/settings/tokens
from huggingface_hub import login
login()  # Paste your token when prompted

# 4. Deploy!
!gradio deploy

Follow the prompts:

1. Enter your Hugging Face username
2. Choose/create a Space name (e.g., ai-text-detector)
3. Wait for deployment (~5-10 minutes)

Your app will be live at: https://huggingface.co/spaces/YOUR_USERNAME/YOUR_SPACE_NAME

Option 2: Using Gradio CLI (Local)

# Install gradio if not already installed
pip install gradio

# Deploy from your project directory
gradio deploy

Follow the prompts to:

1. Login to Hugging Face (or create account)
2. Choose/create a Space
3. Deploy!

Option 3: Manual Deployment

1. Create a new Space on Hugging Face Spaces
2. Choose "Gradio" as the SDK
3. Upload your files:
   • gradio_app.py
   • ai_text_detector/ (entire package)
   • requirements.txt
   • README.md

4. Add a README.md in the Space with: ```yaml

   title: AI Text Detector emoji: 🔍 colorFrom: blue colorTo: purple sdk: gradio app_file: gradio_app.py pinned: false

5. The Space will automatically build and deploy!

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Local Deployment

Requirements

• Python 3.8+
• See requirements.txt

Run Locally

# Install dependencies
pip install -r requirements.txt
pip install -e .

# Run Gradio app
python gradio_app.py

Note for Mac M2 users: Local training may fail due to PyTorch MPS bugs. Use Google Colab for training instead.

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Docker Deployment

# Build
docker build -t ai-text-detector .

# Run
docker run -p 7860:7860 ai-text-detector

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Troubleshooting

Mac M2 Issues

If you encounter mutex.cc lock blocking errors on Mac M2:

• ✅ Use Google Colab (recommended)
• ✅ Use Docker with Linux base image
• ❌ Local training may not work due to PyTorch MPS bugs

Model Loading Issues

The app automatically uses the Desklib pre-trained model if no trained model is found. The model downloads automatically on first use (~1.7GB).