astrux 0.1.2
Astrux Python SDK
License: MIT
Requires Python: >=3.8

# Astrux Python SDK

[![PyPI version](https://img.shields.io/pypi/v/astrux.svg)](https://pypi.org/project/astrux/)
[![Python versions](https://img.shields.io/pypi/pyversions/astrux.svg)](https://pypi.org/project/astrux/)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

The official Python SDK for interacting with the Astrux API. Make machine learning predictions in just a few lines of code.

## Installation

```bash
pip install astrux
```

## Quick Start

```python
from astrux import Astrux

# Initialize the client
client = Astrux(api_key="sk_your_api_key")

# Make a prediction
result = client.models.predict(
    model="my-model",
    input={"feature1": 10, "feature2": 20}
)

print(result["score"])  # Prediction score
```

## Configuration

### API Key

You can provide your API key in two ways:

**1. As a parameter (recommended):**
```python
client = Astrux(api_key="sk_your_api_key")
```

**2. Via environment variable:**
```bash
export ASTRUX_API_KEY=sk_your_api_key
```
```python
client = Astrux()  # Automatically loads from ASTRUX_API_KEY
```

### Custom Timeout

The default timeout is 30 seconds. You can customize it:

```python
client = Astrux(api_key="sk_your_api_key", timeout=60.0)
```

## Usage

### Simple Prediction

```python
from astrux import Astrux

client = Astrux(api_key="sk_your_api_key")

# Regression
result = client.models.predict(
    model="house-prices",
    input={
        "sqft": 120,
        "bedrooms": 3,
        "city": "Paris"
    }
)
print(f"Estimated price: {result['score']}")
```

### Prediction with Specific Version

```python
# Use a specific model version
result = client.models.predict(
    model="sentiment-analysis",
    input={"text": "This product is excellent!"},
    version=2
)
```

### Classification

For classification tasks, the response includes the predicted class and probabilities:

```python
result = client.models.predict(
    model="image-classification",
    input={"image_url": "https://example.com/image.jpg"}
)

print(f"Class: {result['class_']}")  # Predicted class
print(f"Probabilities: {result['proba']}")  # List of probabilities
```

### Model Metadata

The response may include metadata about the model used:

```python
result = client.models.predict(
    model="my-model",
    input={"feature": 42}
)

print(f"Model ID: {result.get('model_id')}")
print(f"Model name: {result.get('model_name')}")
print(f"Version: {result.get('version')}")
print(f"Task type: {result.get('task_type')}")
```

## Error Handling

The SDK provides specific exceptions for different error types:

```python
from astrux import Astrux
from astrux._errors import (
    AuthenticationError,
    NotFoundError,
    ValidationError,
    RateLimitError,
    ServerError,
    AstruxError
)

client = Astrux(api_key="sk_your_api_key")

try:
    result = client.models.predict(
        model="my-model",
        input={"feature": "value"}
    )
except AuthenticationError as e:
    print(f"Authentication error: {e}")
except NotFoundError as e:
    print(f"Model not found: {e}")
except ValidationError as e:
    print(f"Invalid data: {e}")
    print(f"Details: {e.payload}")
except RateLimitError as e:
    print(f"Rate limit exceeded: {e}")
except ServerError as e:
    print(f"Server error: {e}")
except AstruxError as e:
    print(f"Astrux error: {e}")
    print(f"Status code: {e.status}")
```

## Closing the Client

To release resources, close the client after use:

```python
client = Astrux(api_key="sk_your_api_key")

try:
    result = client.models.predict(model="my-model", input={"x": 1})
    print(result)
finally:
    client.close()
```

## Response Structure

### Regression
```python
{
    "score": 42.5,
    "model_id": "abc123",
    "model_name": "my-model",
    "version": 1,
    "task_type": "regression"
}
```

### Classification
```python
{
    "score": 0.95,
    "class_": "positive",  # Note: remapped from "class"
    "proba": [0.05, 0.95],
    "model_id": "def456",
    "model_name": "sentiment",
    "version": 2,
    "task_type": "classification"
}
```

## Requirements

- Python >= 3.8
- httpx >= 0.27.0

## Links

- **Homepage**: [https://astrux.io](https://astrux.io)
- **Documentation**: [https://astrux.io/docs](https://astrux.io/docs)
- **PyPI**: [https://pypi.org/project/astrux/](https://pypi.org/project/astrux/)

## License

MIT - see [LICENSE](LICENSE) file for details.

## Author

Thomas Bodénan - [thomas.bodenan@gmail.com](mailto:thomas.bodenan@gmail.com)

## Support

For questions or issues, consult the [official documentation](https://astrux.io/docs) or contact Astrux support.