semvec/pypi-packages huggingface dataset:
ghostai 1.3.1
A Python library for interacting with the GhostAI API
License: MIT
Requires Python: >=3.6

# GhostAI

[![PyPI version](https://badge.fury.io/py/ghostaiapi.svg)](https://badge.fury.io/py/ghostaiapi)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

Python library for interacting with the GhostAI API.

## Installation

You can install `ghostai` via pip:

```
pip install ghostai
```

## Usage

```python
import ghostai

# Example usage for ghostai
chat("api_key", "model", "prompt") # Model is either chat or img

# Api key can be found by emailing
# cyberzendev@gmail.com


# Example usage for generating a chat
response = chat("api_key", "chat", "prompt")

print(response)

# Example usage for generating an image

import ghostai

# Define your API key and model
api_key = "YOUR_API_KEY"
model = "YOUR_MODEL"

# Send a message and receive the response with an image
message = "Your prompt here"
decoded_image = ghostai.chat_with_image(api_key, model, message)

# Display the decoded image
if decoded_image:
    decoded_image.show()
else:
    print("Failed to receive or decode the image.")

```

## API Key

You need to obtain an API key from GhostAI to use this library. Visit [GhostAI](https://ghostai.me) for more information.

## License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
mnx-solver 0.1.0.3
A method numerical analysis package
License: MIT
Keywords: numerical, analysis, math, methods

# MNx: A Numeric Methods Library

`MNx` is a robust and efficient Python library designed to solve complex numerical problems. It provides a wide range of methods for solving linear systems, including the Gauss and Gauss-Jordan methods. The library is designed with flexibility in mind, allowing for the input of single arrays or lists of arrays.

## Features

- **Gauss Method**: Solve linear systems using the Gauss method.
- **Gauss-Jordan Method**: Solve linear systems using the Gauss-Jordan method.
- **Optimization**: Choose the best method for solving a system based on the given input.
- **Flexibility**: Accepts both single arrays and lists of arrays as input.

## Installation

You can install `mnx` using pip:

```bash
pip install mnx
```

## Usage

Here's a simple example of how to use `mnx`:

```python
import numpy as np
from mnx.exact_linear_methods.Solver import LinearSolver

# Define the system
A = np.array([[3, 2], [1, 2]])
b = np.array([2, 1])

# Create a GaussMethod instance
mnx = LinearSolver(A, b)

# Solve the system
print(mnx)
```

## License

`mnx` is licensed under the [MIT License](LICENSE).

## Contact

If you have any questions or feedback, please feel free to [contact us](mailto:juancamilogallego70@icloud.com).