semvec/pypi-packages huggingface dataset:
Robustness-Framework 0.0.3
An efficient framework for establishing a baseline for standard and adversarial machine learning training projects
Requires Python: >=3.8

# Robustness Framework

<div align="center">

<img alt="Robustness Framework" src="https://raw.githubusercontent.com/khalooei/robustness-framework/main/img-robustness-framework.jpg" width="800px" style="max-width: 100%;">

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**A robustness framework for baseline of standard and adversarial machine learning research projects**

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</div>

The robustness framework is based on top-tier machine learning libraries based on Pytorch. Additionally, it allows for embedding different model architectures and training processes in addition to fixing all research issues.
This framework integrates the following libraries:
 * Pytorch-Lightning
 * Hydra
 * torchattacks

The following architectures are covered in this framework and other networks will be added as needed:
 * MKToyNet
 * LeNet
 * DenseNet
 * ResNet
 * WideResNet

The logging system of this framework is also customizable and resolves all your ideas. As a result, we can take advantage of the efficiency of the following libraries:
 * TorchMetrics 
 * Loggings
 * Neptune
 * Comet
 * MLFlow
 * ...

## Installation
To install this interesting framework for standard and adversarial machine learning, follow the steps below, and don't waste your time developing an efficient baseline.
For installing robustness framework, we have two approaches:

### 1- Manual installation
```
git clone https://github.com/khalooei/robustness-framework.git
pip install -r requirements.txt
```

### 2- Automatic installation
```
pip install robustness-framework
```


## Usage
You can just follow the `main.py` file as a main anchor of this framework. You can define your own configurations in `configs` directory as we defined `training_mnist.yaml` and `training_cifar10.yaml` configuration. 
You can run this framework for running on CIFAR10 dataset as below:
 ```
   python main.py +configs=training_cifar10
 ```

[TOBE COMPLETED]


## Acknowledgements
Thanks to the people behind Pytorch, Lightning, torchattacks hydra, and MLOps libraries whose work inspired this repository. Furthermore, I would like to thank my supervisors Prof. Mohammad Mehdi Homayounpour and Dr. Maryam Amirmazlagnani for their efforts and guidance.
codegpt-sdk 1.0.3
CODEGPT python package
Requires Python: >=3.6

# CODEGPT Python Package

This package provides you with an easy way to interact with the CODEGPT API in your Python applications.

## Install

To install the package, simply run the following command:

```bash
pip install codegpt-sdk
```

## Usege

Below is a sample code demonstrating how to use the CODEGPT package in your Python application:

```python

# Import the package
import asyncio
from codegpt.agent import Agent

def main():
    # Replace with your actual API key and URL ID
    api_key = "your_api_key_here"
    agent_id = "your_agent_id_here"

    # Initialize the CODEGPT class
    agent_instance = Agent(api_key, agent_id)

    # Optional: update API key or URL ID if needed
    agent_instance.set_api_key("new_api_key")
    agent_instance.set_agent_id("new_agent_id")

    # Create the prompt
    prompt = "tell me short story about blue turtle"

    # Make a completion request
    response = asyncio.run(agent_instance.completion(prompt, stream=False))

    # Handle the response as needed
    print(response)

if __name__ == "__main__":
    main()
```
ValiMail 0.1.0
A library for advanced email verification.

# ValiMail - Email Verification Library

ValiMail is a library designed for advanced and effective verification of email addresses.

## Features

- Verify the format and validity of email addresses.
- Detect if an email address exists in a leaked database.
- Support email domain verification.
- Support email comparison against a blacklist.
- Integration with popular email service providers.

## Installation

You can install the library using the following command:

```python
pip install ValiMail
```

## How To Use

# Import the library
```python
from ValiMail import vali_mail, check_domain_name, check_if_known,is_dispose_email
```

# Use library functions to check email addresses

```python
email = "example@email.com"
is_valid = vali_mail(email)
is_in_database = check_if_known(email)
is_valid_domain = check_domain_name(email)
is_dispose = is_dispose_email(email)
```
```python
# Print the results
print(f"Is valid email: {is_valid}")
print(f"Is in database: {is_in_database}")
print(f"Has valid domain: {is_valid_domain}")
print(f"Is blacklisted: {is_dispose}")
```

#Ihad Been Added The RealTime Examples in The File example.py