Deployment Guide - Two Options

You now have TWO deployment options for your model:

Option 1: Gradio Space (Current - Interactive UI)

URL: https://huggingface.co/spaces/chenhaoq87/MilkSpoilageClassifier-Demo

Features:

✅ Interactive web interface
✅ Visual inputs and outputs
❌ No direct REST API for Custom GPT

Best for: Human users testing the model manually

Option 2: FastAPI Space (Recommended for Custom GPT)

Create a second Space with pure REST API:

Step 1: Create New Space

Go to https://huggingface.co/new-space
Name: MilkSpoilageClassifier-API
SDK: Docker
Click "Create Space"

Step 2: Upload Files

Upload these files to the new Space:

Files to upload:

apps/fastapi/app.py → upload as app.py
model/model.joblib → upload as model.joblib
apps/fastapi/Dockerfile → upload as Dockerfile
apps/fastapi/requirements.txt → upload as requirements.txt

Dockerfile:

FROM python:3.10-slim

WORKDIR /app

# Copy files
COPY requirements.txt .
COPY app.py .
COPY model.joblib .

# Install dependencies
RUN pip install --no-cache-dir -r requirements.txt

# Expose port
EXPOSE 7860

# Run app
CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]

requirements.txt:

fastapi>=0.100
uvicorn[standard]>=0.24
pydantic>=2.0
scikit-learn>=1.0
joblib>=1.0
numpy>=1.20

Step 3: Use with Custom GPT

Once the Space is running, your REST API will be at:

https://chenhaoq87-milkspoilageclassifier-api.hf.space/predict

OpenAPI Schema (see API_DOCUMENTATION.md)

Quick Command to Create FastAPI Space

Run this in PowerShell:

cd D:\HuggingFace\MilkSpoilageClassifier

# Upload to new Space
python -c "from huggingface_hub import HfApi, create_repo; api = HfApi(); create_repo('chenhaoq87/MilkSpoilageClassifier-API', repo_type='space', space_sdk='docker', exist_ok=True); api.upload_file('apps/fastapi/Dockerfile', 'Dockerfile', 'chenhaoq87/MilkSpoilageClassifier-API', repo_type='space'); api.upload_file('apps/fastapi/app.py', 'app.py', 'chenhaoq87/MilkSpoilageClassifier-API', repo_type='space'); api.upload_file('apps/fastapi/requirements.txt', 'requirements.txt', 'chenhaoq87/MilkSpoilageClassifier-API', repo_type='space'); api.upload_file('model/model.joblib', 'model.joblib', 'chenhaoq87/MilkSpoilageClassifier-API', repo_type='space'); print('FastAPI Space created!')"

Summary

Feature	Gradio Space	FastAPI Space
Interactive UI	✅	❌
REST API	❌	✅
Custom GPT	❌	✅
Human Testing	✅	❌
API Docs	❌	✅ (/docs)

Recommendation: Keep both!

Use Gradio Space for manual testing
Use FastAPI Space for Custom GPT integration