semvec/pypi-packages huggingface dataset:
versioninfo_helper 1.0.0
VersionInfo helper script for PyInstaller
Requires Python: >=3.9
Keywords: PyInstaller, VersionInfo, development

# VersionInfo helper script for PyInstaller

This repository contains helper scripts to dynamically create VersionInfo objects that can be embedded in .exe files created by PyInstaller.

This project was created because existing solutions to embed version information inside executables relied on creating artifact files that get read (and eval-ed) by PyInstaller during the build process.
Dynamically creating such files essentially boiled down to inserting data in a string template, with no guides to the user if their entered data is valid or not.
A bit of exploration of PyInstaller's source code and official Microsoft documentation revealed that it should be possible to
provide PyInstaller with necessary data straight from .spec files without file-read-and-eval step.
This approach has the added bonus of being type hint compatible, offering rich auto-complete in supported IDEs.

## Installation

`pip install versioninfo_helper`

## Usage

See [example_simple.onefile.spec](example_simple.onefile.spec) and [example_dynamic.onefile.spec](example_dynamic.onefile.spec) for examples on how to integrate VersionInfo creation directly into PyInstaller .spec files.
S3Explorer 0.0.1
A simple but effective terminal based interface (TUI) for S3.

# S3 Explorer

:construction: **Currently in development** :construction:

## IDEAS

Take a look at [this](docs/ideas.md)

## Licence

![Variants of the GPLv3 logo by José Obed](https://www.gnu.org/graphics/gplv3-rounded-red-180x60.jpg "GPLv3 logo")

s3explorer

Copyright (C) 2025  Bouchet Matéo and Conde Cyril

This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.

This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU General Public License for more details.

You should have received a copy of the GNU General Public License
along with this program.  If not, see <http://www.gnu.org/licenses/>.
pypasteee 0.0.2
A simple API wrapper for paste.ee 
Requires Python: >=3.9

# pypasteee

A simple Python wrapper for the [paste.ee](https://paste.ee/)  


## Instalation 
```
pip install pypasteee
```


## Usage

Initialization
```python
from pypasteee import Pasteee, Paste, Section

api = Pasteee(API_TOKEN)
```


Get a list of your pastes
```python
...
pastes = api.getPastesList()
for i in pastes:
    print(f'ID: {i.id}. Description: {i.description}. Views: {i.views}. Created at: {i.created_at}')
```


Get paste info
```python
...
pastes = api.getPaste('<id>')
```

Create a new paste
```python
...

new_paste = Paste(description='First paste from pypasteee', encrypted=False, sections=[Section(syntax="autodetect", name='Section1', content='Feels great')]) 
api.paste(new_paste)
```

Delete paste
```python
...
api.deletePaste('<id>')
```
neuroflux 2.4
MRI and CT Brain Tumor Diagnosis and Grad-CAM Visualization

# Neuroflux
Neuroflux is a Python package that analyzes MRI and CT scans of brains and highlights regions of tumor damage on a heat map.

## Installation
To install neuroflux, you can use pip:

```
pip install neuroflux
```

The recommended import is:
```
import neuroflux
```

# MRI Scans

## Setup
To begin, declare the following variables:
- case_folder: The folder where the input MRI scans are located (set it to "" if the input files are in the same folder as the program)
- input_flair: The file name of the input FLAIR
- input_t1ce: The file name of the input T1ce
- model_weights: The file name of the predefined model weights

Example setup:
```
case_folder = "BraTS20"
input_flair = "01_flair.nii"
input_t1ce = "01_t1ce.nii"
model_weights = "mri_weights.h5"
```

## Usage
Neuroflux has three main functions:
- prepare_mri_model(model_weights, img_size=128)
    - Creates the U-Net (first step)
- display_slice(folder, input_flair, input_t1ce, slice_num, model, target_layer_name="conv2d_1", img_size=128)
    - Displays the Grad-CAM heat map at a given slice number
- display_grid(folder, input_flair, input_t1ce, model, num_slices=84, rows=7, cols=12, start_slice=20, target_layer_name="conv2d_1")
    - Displays a grid containing a given number of slices beginning at a given slice number

Example usage:
```
model = neuroflux.mri.prepare_mri_model(model_weights=model_weights, img_size=img_size)
neuroflux.mri.display_slice(folder=case_folder, input_flair=input_flair, input_t1ce=input_t1ce, slice_num=77, model=model)
neuroflux.mri.display_grid(folder=case_folder,input_flair=input_flair, input_t1ce=input_t1ce, model=model)
```

# CT Scans

## Setup
To begin, declare the following variables:
- case_folder: The folder where the input CT scans are located (set it to "" if the input files are in the same folder as the program)
- input: The file name of the input CT scan (can be .jpg, .jpeg, or .png)
- model_weights: The file name of the predefined model weights

Example setup:
```
case_folder = "CT Scans"
input = "01.jpg"
model_weights = "ct_weights.pth"
```

## Usage
Neuroflux has three main functions:
- prepare_ct_model(model_weights)
    - Creates the neural network (first step)
- display_gradcam(folder, input, model)
    - Displays the Grad-CAM heat map overlaid on the CT scan

Example usage:
```
model = neuroflux.ct.prepare_ct_model(model_weights=model_weights)
neuroflux.ct.display_gradcam(folder=case_folder, input=input, model=model)
```

# Notes
- The model weights are not built into this package. Our [GitHub](https://github.com/Neuroflux-AI/neuroflux) contains two options to attain model weights for MRI and CT: Use our pre-trained weights (recommended) or run the Google Colab notebook to create your own unique weights.
- To get more involved, see our [website](https://www.neurofluxai.org), read our [research paper](http://doi.org/10.36838/v7i6.64), or contact us at neurofluxai@gmail.com.
nexusai-sdk 1.0.1
Python SDK for NexusAI - AI Agent Platform for Businesses
Requires Python: >=3.8
Keywords: ai, agents, nlp, voice, vision, multimodal, business, africa

# NexusAI Python SDK

Python SDK for **NexusAI** - The AI Agent Platform designed for African businesses.

## Features

- 🤖 **Text AI Agents** - ChatGPT-powered conversational AI
- 🎤 **Voice AI Agents** - Real-time voice conversations
- 👁️ **Vision AI Agents** - Image and video analysis
- 📞 **Phone Integration** - Emergency services, customer support
- 🌍 **African Market Focus** - Built for African businesses
- 🔧 **Business Logic Adapters** - Customize AI behavior for your industry

## Quick Start

```bash
pip install nexusai-sdk
```

```python
from nexusai_sdk import NexusAIClient, AgentConfig

# Initialize client
client = NexusAIClient("https://your-nexusai-instance.com")

# Create an agent session
config = AgentConfig(
    agent_id="customer_support",
    instructions="You are a helpful customer support agent for an African telecom company.",
    capabilities=["text", "voice"],
    business_logic_adapter="telecom_support"
)

session = client.create_agent_session(config)

# Send a message
response = session.send_message("Hello, I need help with my mobile data plan")
print(response.content)
```

## Use Cases

### 🏥 Emergency Services

```python
# Emergency dispatcher AI
emergency_config = AgentConfig(
    agent_id="emergency_dispatcher",
    business_logic_adapter="emergency_services",
    capabilities=["text", "voice", "phone"]
)
```

### 📚 Language Learning

```python
# Language learning tutor
learning_config = AgentConfig(
    agent_id="french_tutor",
    business_logic_adapter="language_learning",
    capabilities=["text", "voice"]
)
```

### 🏪 Customer Support

```python
# Business customer support
support_config = AgentConfig(
    agent_id="support_agent",
    business_logic_adapter="customer_support",
    capabilities=["text", "voice", "vision"]
)
```

## Documentation

Visit [nexusai.com/docs](https://nexusai.com/docs) for complete documentation.

## License

MIT License - See LICENSE file for details.