semvec/pypi-packages huggingface dataset:
freewayai 0.1.3
A new open-standard specification for LLM-backed systems and an SDK for building on it
Requires Python: >=3.9

# FreewayAI

## Welcome to FreewayAI: a new open-standard specification for LLM-backed systems  
Freeway is meant to provide a simple, flexible, enxtensible and lightweight standard for managing prompt templates, database query templates, user input points, and LLM-backed system diagrams. 

## The units of FreewayAI  
The unit elements of Freeway are as follows:  
- Prompt Templates  
- Database Query Templates  
- User Inputs  

These units can then be used to construct a diagram of a system structure, to indicate the general flow of data.  
We know that systems built on LLMs are full of json parsing, for loops, if statements, and regexes. We just think that you should focus on outlining the LLM-specific components of a system.

We also believe that prompt templates should be managed out of code, where they can be edited on their own lifecycle.

## Installation

```bash
pip install freewayai
```


## Usage

### Project Structure

```
system_configs/
├─ my_system/
│  ├─ database_templates.json
│  ├─ prompt_templates.json
│  ├─ system_structure.json
│  ├─ user_inputs.json
├─ my_second_system/
│  ├─ database_templates.json
│  ├─ prompt_templates.json
│  ├─ system_structure.json
│  ├─ user_inputs.json
index.py
```

### Example `prompt_templates.json` file

```json
{
  "templates": {
    "pirate_talk": {
      "prompt_id": "pirate_talk",
      "prompt_template": "Respond to this question from the user but talk like a pirate: {question}. Answer: ",
      "variables": [
        {
          "name": "question",
          "source": "user"
        }
      ]
    },
    "shakespeare_talk": {
      "prompt_id": "shakespeare_talk",
      "prompt_template": "Respond to this question from the user but talk like Shakespeare: {question}. Answer: ",
      "variables": [
        {
          "name": "question",
          "source": "user"
        }
      ]
    },
  }
}
```

### Example SDK Usage

```python
from openai import OpenAI
from freewayai import LLMSystem

SYSTEM_LOCATION = "system_configs/"

my_system = LLMSystem(SYSTEM_LOCATION, "my_system")

variables = {
  "question": input()
}

pirate_prompt = my_system.get_formatted_prompt("pirate_talk", variables)
formatted_pirate_prompt = pirate_prompt.to_openai()

client = OpenAI()
completion = client.chat.completions.create(
    model="gpt-3.5-turbo-0125",
    messages = formatted_pirate_prompt,
    temperature=0.2
)

print(completion.choices[0].message.content)
```
ch00cy 0.0.1
TSRCNN_Texture Synthesis with Rotation using CNN package
Requires Python: >=3.8

TSRCNN : Texture Synthesis with Rotation using CNN
We improved the existing CNN texture synthesis technique by rotating the texture image to provide directionality.

How to use :

TSRCNN(image, rotateNum=8, outputScale=2, generateRotation = True, resultNameRotate="resultTextureImg", resultSave=False,
            Patch_before_limit=False, Patch_before_scale=120)

param image: 이미지 경로 - 필수 입력 (ex)"절대경로")
param rotateNum: 360도(중심 기준)/n 만큼 회전시켜 총 n 개의 회전 예제 텍스처를 생성 (n=8개)
param outputScale: 결과 이미지 사이즈 얼마나 배로 늘릴것인가 (2배)
param generateRotation: 회전 예제 이미지를 생성할것인가? (True) - False 일 경우 기존 회전 예제 이미지 사용할 것을 대비.
param resultNameRotate: 저장할 결과 이름 ("resultTextureImg"+".png")
param resultSave: 결과를 저장할 것인가? (False)
param Patch_before_limit: 초기 이미지 크기 제한 여부 (Flase) - 가로세로 길이가 모두 제한크기 이상 넘어갈 경우 제한크기로 크기조절
param Patch_before_scale: 초기 이미지 제한 크기 (120픽셀) - 클수록 합성 시간 오래 걸림

return: PIL image - Texture Synthesis result
physicX 0.0.11927
mathematics and physics library
Requires Python: >=3.7

# PhysicX library for python
  
This project with LICENSE GNU-GPLv3, in fact created for developers , physicist , mathematicians and this project
<pre>pre-released</pre>
github:https://github.com/anonymous14725/physicX <br/>
pypi:https://pypi.org/project/physicX

## Installation with pypi
To install physicX in python, just write the following command:
```
pip install physicX
```
shog 1.0.0
A simple Python package
Requires Python: >=3.6

MIT License

Copyright (c) ShogAI 2024

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
gguf-selector 0.0.5
GGUF selector

### GGUF selector

[<img src="https://raw.githubusercontent.com/calcuis/gguf-selector/master/selector.gif" width="128" height="128">](https://github.com/calcuis/gguf-selector)
[![Static Badge](https://img.shields.io/badge/selector-0.0.5-pink?logo=github)](https://github.com/calcuis/gguf-selector/releases)

This package is a simple graphical user interface (GUI) application that uses the llama.cpp to interact with a chat model for generating responses.

#### include the module in your code
```
from gguf_selector import connector
```

You could pull any (pre-trained model) GGUF file(s) inside the folder and it will automatically be detected by the program.

[<img src="https://raw.githubusercontent.com/calcuis/chatgpt-model-selector/master/demo.gif" width="350" height="280">](https://github.com/calcuis/chatgpt-model-selector/blob/main/demo.gif)
[<img src="https://raw.githubusercontent.com/calcuis/chatgpt-model-selector/master/demo1.gif" width="350" height="280">](https://github.com/calcuis/chatgpt-model-selector/blob/main/demo1.gif)