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# ✅ Deployment Status & Next Steps
## What's Been Deployed
### 1. ✅ Model Repository
**URL**: https://huggingface.co/chenhaoq87/MilkSpoilageClassifier
**Status**: LIVE ✅
Contains the trained model, config, handler, and documentation.
### 2. ✅ Gradio Space (Interactive UI)
**URL**: https://huggingface.co/spaces/chenhaoq87/MilkSpoilageClassifier-Demo
**Status**: FIXED & REBUILDING ⏳
**Fixed Issues**:
- ✅ Removed FastAPI hybrid (kept it simple - Gradio only)
- ✅ Pinned scikit-learn to 1.7.2 to match model version
- ✅ Simplified code to avoid Pydantic/Gradio 6 warnings
### 3. 🔧 FastAPI Space (REST API for Custom GPT)
**URL**: https://huggingface.co/spaces/chenhaoq87/MilkSpoilageClassifier-API
**Status**: FIXED & REBUILDING ⏳
**Fixed Issues**:
- ✅ Fixed Dockerfile to reference correct requirements file
- ✅ Pinned scikit-learn to 1.7.2
- ✅ Using Python 3.10 (not 3.13 which has compatibility issues)
---
## Why Separate Spaces is Better
| Aspect | Hybrid Space | Separate Spaces |
|--------|-------------|-----------------|
| **Simplicity** | ❌ Complex config | ✅ Simple, focused |
| **Debugging** | ❌ Hard to isolate issues | ✅ Easy to debug |
| **Dependencies** | ❌ Conflicts (Gradio vs FastAPI) | ✅ Minimal, specific |
| **Performance** | ❌ Heavier | ✅ Lightweight |
| **Maintenance** | ❌ Harder | ✅ Independent updates |
**Decision**: Keep them **separate** ✅
---
## Check Space Status
### Gradio Space
Visit: https://huggingface.co/spaces/chenhaoq87/MilkSpoilageClassifier-Demo
Should show: **Running** with green indicator
### FastAPI Space
Visit: https://huggingface.co/spaces/chenhaoq87/MilkSpoilageClassifier-API
Docker build takes 2-5 minutes. Check logs if error persists.
---
## Testing Instructions
### Test Gradio Space (UI)
1. Go to: https://chenhaoq87-milkspoilageclassifier-demo.hf.space/
2. Enter values and click "Classify"
3. Should see prediction with probabilities
### Test FastAPI Space (API)
Once the Space shows "Running":
**PowerShell**:
```powershell
$body = @{
spc_d7 = 4.0; spc_d14 = 5.0; spc_d21 = 6.0
tgn_d7 = 3.0; tgn_d14 = 4.0; tgn_d21 = 5.0
} | ConvertTo-Json
Invoke-RestMethod -Uri "https://chenhaoq87-milkspoilageclassifier-api.hf.space/predict" `
-Method POST -ContentType "application/json" -Body $body
```
**Expected Response**:
```json
{
"prediction": "PPC",
"probabilities": {
"PPC": 0.85,
"no spoilage": 0.10,
"spore spoilage": 0.05
},
"confidence": 0.85
}
```
---
## Custom GPT Integration
Once the FastAPI Space is running, use this OpenAPI schema:
```yaml
openapi: 3.1.0
info:
title: Milk Spoilage Classifier
version: 1.0.0
servers:
- url: https://chenhaoq87-milkspoilageclassifier-api.hf.space
paths:
/predict:
post:
operationId: classifyMilkSpoilage
summary: Predict milk spoilage type
requestBody:
required: true
content:
application/json:
schema:
type: object
required: [spc_d7, spc_d14, spc_d21, tgn_d7, tgn_d14, tgn_d21]
properties:
spc_d7: {type: number, description: "SPC Day 7 (log CFU/mL)"}
spc_d14: {type: number, description: "SPC Day 14 (log CFU/mL)"}
spc_d21: {type: number, description: "SPC Day 21 (log CFU/mL)"}
tgn_d7: {type: number, description: "TGN Day 7 (log CFU/mL)"}
tgn_d14: {type: number, description: "TGN Day 14 (log CFU/mL)"}
tgn_d21: {type: number, description: "TGN Day 21 (log CFU/mL)"}
responses:
'200':
description: Prediction result
content:
application/json:
schema:
type: object
properties:
prediction: {type: string}
probabilities: {type: object}
confidence: {type: number}
```
**No authentication required** - the Space is public.
---
## If FastAPI Space Still Has Issues
### Alternative 1: Test Locally
```powershell
cd D:\HuggingFace\MilkSpoilageClassifier
python fastapi_app.py
```
Then test at: `http://localhost:7860/predict`
### Alternative 2: Use Dedicated Inference Endpoint (Paid)
1. Go to model page → Deploy → Inference Endpoints
2. Select CPU instance (~$0.06/hour)
3. Get instant REST API with guaranteed uptime
---
## Summary
✅ **Model trained and saved** (96% accuracy)
✅ **Model uploaded to HuggingFace**
✅ **Gradio Space created** (for human users)
⏳ **FastAPI Space deploying** (for Custom GPT)
✅ **All code and docs created**
**Next**: Wait 3-5 minutes for FastAPI Space to finish building, then test!
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