semvec/pypi-packages huggingface dataset:
holboxai-health 0.1.1
A package for medical scribing using AWS Transcribe for the healthcare domain

# HealthScribe

A Python package for medical scribing using AWS Transcribe Medical service.

## Overview

HealthScribe is a package focused on the healthcare domain. It enables medical scribing by transcribing audio files (e.g., doctor-patient conversations) using AWS Transcribe Medical service. The package uploads the provided audio file to an S3 bucket, starts a transcription job, and retrieves a summary from the job's JSON output.

## Installation

```sh
 pip install holboxai-health
```
## Usage

You can use the command-line interface:

```bash
healthscribe-cli <audio_file> <job_name> <data_access_role_arn> <s3_bucket> 
```

For example:

```bash
healthscribe-cli conversation.wav myJob arn:aws:iam::aws_accountid:role/your-role my-s3-bucket s3-key
```

You can use this in python script: 
```sh 
import os
import holboxai_health

# Set the environment variables for the AWS SDK
os.environ['AWS_ACCESS_KEY_ID'] = aws_access_key_id
os.environ['AWS_SECRET_ACCESS_KEY'] = aws_secret_access_key
os.environ['AWS_REGION'] = aws_region

# Call the function with sensitive information masked
summary = holboxai_health.healthscribe(
    audio_file="/path/to/audio.mp3",
    job_name="job_name",
    data_access_role_arn="arn:aws:iam::accountid:role/your-role",
    s3_bucket="s3_bucket"
)

print(summary)
```


## License

This project is licensed under the MIT License.
autodoc-django 0.1.1
Provide an automatic documentation for Django's Apps
Requires Python: >=3.6

# Autodoc-Django

An auto documentation tool for Django's Apps with [MermaidJS](https://mermaid.live/) in MarkDown files.
<p style="text-align: center;">

```mermaid
graph TD
    A[Django developer] --> B{Has docs?};
    B -- Yes --> C[Ship it!];
    B -- No --> D[Use django-autodoc];
    D --> E[Generate docs];
    E --> F[Ship it!];

```
</p>

### Installation and Setup
To install Autodoc-Django, run the following command:

```bash
pip install autodoc-django
```
In `settings.py` file, add `autodoc` on `INSTALLED_APPS` constant.
```
INSTALLED_APPS = [
    ...
    "autodoc",
]
```

### Usage
To generate a **Flow Chart** documentation for your Django project, use the following command:

```bash
python3 manage.py autodoc_flow <app_name>
```

To generate a **Sequence Diagram** documentation for your Django project, use the following command:

```bash
python3 manage.py autodoc_sequence <app_name>
```

This will create documentation based on your Django models and views.

### Contributing
Contributions to Autodoc-Django are welcome! Please fork the repository and submit a pull request.

### License
Autodoc-Django is licensed under the MIT License.
argos-monitoring 0.9.0
Distributed supervision tool for HTTP.

# Argos monitoring

A monitoring and status board for your websites.

![Screenshot of Argos’ status page](docs/dashboard.jpg)

1. Define a list of websites to monitor
2. Specify a list of checks to run on these websites.
3. Argos will run the checks periodically and alert you if something goes wrong.

Internally, a HTTP API is exposed, and a job queue is used to distribute the checks to the agents.

- [Online documentation](https://argos-monitoring.framasoft.org/)
- [Issue tracker](https://framagit.org/framasoft/framaspace/argos/-/issues)

## Requirements

- **Python**: 3.11+
- **Backends**: SQLite (development), PostgreSQL 14+ (production)

## License

Copyright © 2023 Alexis Métaireau, Framasoft

This program is free software: you can redistribute it and/or modify
it under the terms of the GNU Affero 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 Affero General Public License](LICENSE) for more details.
fairdiverse 1.0.0
A unified, comprehensive fairness- and diversity-aware IR library
Requires Python: >=3.6

FairDiverse is developed based on Python for reproducing and developing fairness- and diversity-aware IR algorithms in a unified, comprehensive framework for research purpose. In the first version, our library includes 28 fairness- and diversity algorithms and 16 base models, covering pre-processing, in-processing and post-processingfor more information: https://github.com/XuChen0427/FairDiverse