semvec/pypi-packages huggingface dataset:
la-rag 0.1.5
Layout Aware RAG
Requires Python: >=3.11

# Layout-Aware RAG (LA-RAG)

This is the source code repository for Python package [la-rag](https://pypi.org/project/la-rag/)

## Why Layout-Aware RAG?
The impressive abilities of large language models (LLMs) offer exciting possibilities for large-scale document analysis. However, a significant challenge remains in making text from extensive documents, such as large PDFs, accessible to LLMs due to their limited context window, which restricts the amount of text they can process at a time.

Retrieval Augmented Generation (RAG) systems address this challenge by combining LLMs with advanced retrieval techniques. Common chunking technologies used in LangChain, such as TextSplitter, RecursiveCharacterTextSplitter, etc break documents into smaller sections to fit within the LLM’s context window.
But, these methods will allow the system to lose the semantic connection of layout features, such as sections & subsections, tables, lists, bullet points, etc. For example, in a bullet-pointed list, all the points can be interrelated, and each point is connected to the paragraph or the last sentence of the paragraph given above the list.

ayout-aware RAG considers the layout features of the document and the semantic connection between them.

![alt text](<layout aware chunking demo.png>)

## Important Note
Although I have made the repository public and released the python package, I am still working on this project. I will be adding more details on the installation and building projects using la-rag soon. I encourage you to look into the tests\sample.py for reference to a sample code to see how to use the package. 

If you are interested to collaborate on this project, please email me at muafirathasnikt@gmail.com
fileup.py 0.1.1
A Python package that simplifies the auto-update process by updating individual files with remote versions based on file-specific version comments.
Requires Python: >=3.6

# fileup

`fileup` is a Python package that simplifies the auto-update process by updating individual files with remote versions based on file-specific version comments.

## Installation

Install the package using pip:

``` pip install fileup ```

## Usage
1. Set the remote file URL in your script.
2. Call the `update` function from the `fileup` package.

### Example

```python
import fileup

REMOTE_FILE_URL = "https://example.com/path/to/your/script.py"

def main():
    # Your main script logic here
    print("Running the main script...")

if __name__ == "__main__":
    fileup.update(REMOTE_FILE_URL)
    main()
bitoli 0.1.1
Adaptive compression and encryption of data
Requires Python: >=3.6

bitoli
======

bitoli is a Python package for adaptive compression and encryption of data. It offers simple methods to securely encode and decode data using AES encryption in CFB mode and adaptive compression techniques.

Features
--------

- Adaptive compression using zlib
- AES encryption with CFB mode
- Base85 encoding for non-compressed data
- Simple API for encoding and decoding data

Installation
------------

You can install bitoli using pip:

.. code:: bash

    pip install bitoli

Usage
-----

Here is a simple example of how to use bitoli:

.. code:: python

    from bitoli import encode, decode

    key = "your_password"
    data = "This is some data to encrypt and compress."

    # Encode data
    encoded_data = encode(data, key)
    print("Encoded data:", encoded_data)

    # Decode data
    decoded_data = decode(encoded_data, key)
    print("Decoded data:", decoded_data)

API
---

- `encode(data, key)`: Encrypts and compresses the data using the provided key.
- `decode(data, key)`: Decompresses and decrypts the data using the provided key.

License
-------

This project is licensed under the MIT License.
probability-tb 0.0.1
A simple probability package which has a type probability
Requires Python: >=3.8

# Probability Package

This is a simple probability package which has the type probability which is a value between 0 and 1. 

# Importing

You can import the probability package by:
``` 
from probability_tb import probability
```

# Using Probability

You can use the probabilties using:
```
p = probability.probabilty(.5)
```
which has the value:
```
p.value
```
of .5.