semvec/pypi-packages huggingface dataset:
prompt-as 0.2.0
GPT
License: MIT
Requires Python: >=3.9

# Prompt as Function
**"Don't write any code, just tell what to do!"**

This is a significant milestone for Large Language Models (LLMs) and the coding process. The `prompt-as` library serves as a foundation for using prompts to perform tasks in Python. We are currently developing this mindset for several features in our products. With our open-source initiative <3, you can use it just like we do.


```console
pip install prompt-as
```


```python
from prompt_as import prompt_as_config, pf 

prompt_as_config.OPENAI_API_KEY = "sk-**"

@pf
def sleep(second:str) -> bool:
    """
    Sleeps for the given seconds and returns True.
    """


```

[Example @pf Functions](https://github.com/Upsonic/prompt-as-function/blob/master/examples.md)



# Testing and Settings

<details>
<h1>Model Settings</h1>
You can change the OpenAI model that have been used for `prompt-as`.

```python
from prompt_as import prompt_as_config, pf


prompt_as_config.OPENAI_MODEL = "gpt-4-turbo"
# Model Setting

prompt_as_config.OPENAI_API_KEY = "sk-**"

@pf
def sleep(second:str) -> bool:
    """
    Sleeps for the given seconds and returns True.
    """



```


<h1>Testing</h1>

If you want to test this library on a large scale, you can use our test system as well.

```python

from prompt_as import prompt_as_config, pf

prompt_as_config.OPENAI_API_KEY = "sk-**"

@pf
def sleep(second:str) -> bool:
    """
    Sleeps for the given seconds and returns True.
    """



# Testing

from prompt_as import Prompt_As_Test_System


Prompt_As_Test_System(sleep_time, [(["2"], {})], [True], [False]).run_test()
# (function_name, test_args_and_kwargs, expected_outputs, bad_outputs)

```

</details>
Face-recognition-Tokenizer 0.1.0
A toolkit for facial recognition and mapping using OpenCV and Dlib.
License: MIT
Requires Python: >=3.6

# Face Recognition Toolkit

## Description

The Face Recognition Toolkit is a Python package for facial recognition and mapping using OpenCV and Dlib. It provides functionality to detect faces, map facial landmarks, and generate unique token IDs for each captured face, which can be integrated with onboarding platforms for web, iOS, and Android.

## Features

- Detect faces in an image using OpenCV.
- Map facial landmarks using Dlib.
- Generate unique token IDs for each captured face.
- Save processed images with landmarks.
- Easy integration with web, iOS, and Android platforms.

## Installation

```bash
pip install face_recognition_toolkit
git clone https://github.com/Nguthirukar/face_recognition_toolkit