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Deploy TruthShield AI backend
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# TruthShield ML Backend
Local FastAPI inference service for the trained EfficientNet-B0 AIGC image detector and RoBERTa M4 text detector.
## Start
```powershell
python -m uvicorn backend.app:app --host 127.0.0.1 --port 8010 --reload
```
The React app calls:
```txt
http://127.0.0.1:8010/predict-image
http://127.0.0.1:8010/predict-text
```
## Class Order
The checkpoint only contains weights, not `class_to_idx`. The default class order is:
```powershell
real,fake
```
That matches the Hugging Face AIGC benchmark labels used for the new model: `0 = real`, `1 = fake`.
If predictions look reversed, restart with:
```powershell
$env:TRUTHSHIELD_CLASS_ORDER="fake,real"
python -m uvicorn backend.app:app --host 127.0.0.1 --port 8010 --reload
```
## Text Model
The default text model folder is:
```txt
ML/text/truthshield_text_roberta_m4
```
The default text class order is:
```powershell
human,ai
```
That matches the training labels: `0 = human-written`, `1 = AI-generated`.