CURL_EXAMPLES.md

# CURL Examples for ML Text Classification API

## Local Testing

### 1. Health Check
```bash
curl http://localhost:8000/health
```

Expected Response:
```json
{"status": "healthy"}
```

### 2. Root Endpoint
```bash
curl http://localhost:8000/
```

Expected Response:
```json
{
  "message": "ML Text Classification API",
  "version": "1.0.0",
  "endpoints": {
    "health": "/health",
    "predict": "/predict"
  }
}
```

### 3. Prediction Endpoint (Main)
```bash
curl -X POST "http://localhost:8000/predict" \
  -H "Content-Type: application/json" \
  -d '{"text": "Hi ||| Hi anh"}'
```

Expected Response:
```json
{
  "results": [
    {"label": "label_name_1", "score": 0.95},
    {"label": "label_name_2", "score": 0.03},
    ...
  ]
}
```

## Vercel / Production Deployment

After deploying, replace `your-project.vercel.app` with your actual domain:

### 1. Health Check
```bash
curl https://your-project.vercel.app/health
```

### 2. Root Endpoint
```bash
curl https://your-project.vercel.app/
```

### 3. Prediction Endpoint
```bash
curl -X POST "https://your-project.vercel.app/predict" \
  -H "Content-Type: application/json" \
  -d '{"text": "Hi ||| Hi anh"}'
```

## Advanced Examples

### Using jq for Pretty Output
```bash
curl -X POST "http://localhost:8000/predict" \
  -H "Content-Type: application/json" \
  -d '{"text": "Hi ||| Hi anh"}' | jq '.'
```

### Sorting Results by Score
```bash
curl -X POST "http://localhost:8000/predict" \
  -H "Content-Type: application/json" \
  -d '{"text": "Hi ||| Hi anh"}' | jq '.results | sort_by(.score) | reverse'
```

### Getting Top 3 Predictions
```bash
curl -X POST "http://localhost:8000/predict" \
  -H "Content-Type: application/json" \
  -d '{"text": "Hi ||| Hi anh"}' | jq '.results | sort_by(.score) | reverse | .[0:3]'
```

## Testing with Different Text

### Example 1
```bash
curl -X POST "http://localhost:8000/predict" \
  -H "Content-Type: application/json" \
  -d '{"text": "Hello ||| Hi there"}'
```

### Example 2
```bash
curl -X POST "http://localhost:8000/predict" \
  -H "Content-Type: application/json" \
  -d '{"text": "Xin chào ||| Chào bạn"}'
```

## Error Handling

### Empty Text (400 Error)
```bash
curl -X POST "http://localhost:8000/predict" \
  -H "Content-Type: application/json" \
  -d '{"text": ""}'
```

Expected Response:
```json
{
  "detail": "Text field is required and cannot be empty"
}
```

### Missing Text Field (422 Error)
```bash
curl -X POST "http://localhost:8000/predict" \
  -H "Content-Type: application/json" \
  -d '{}'
```

Expected Response:
```json
{
  "detail": [
    {
      "type": "missing",
      "loc": ["body", "text"],
      "msg": "Field required",
      "input": {}
    }
  ]
}
```

## Python Requests Examples

If you prefer Python instead of curl:

```python
import requests

# Prediction
response = requests.post(
    "http://localhost:8000/predict",
    json={"text": "Hi ||| Hi anh"}
)
print(response.json())
```

## JavaScript/Fetch Examples

```javascript
fetch('http://localhost:8000/predict', {
  method: 'POST',
  headers: {
    'Content-Type': 'application/json',
  },
  body: JSON.stringify({
    text: 'Hi ||| Hi anh'
  })
})
.then(response => response.json())
.then(data => console.log(data));
```