semvec/pypi-packages huggingface dataset:
drw 0.1.0
A Python library for context-aware operations using an LLM
Requires Python: >=3.6

drw
A Python library for context-aware operations using Google's Gemini 1.5 Flash model.
Installation
pip install drw

Setup
Set your Gemini API key as an environment variable:
export GEMINI_API_KEY='your-api-key-here'  # On Windows: set GEMINI_API_KEY=your-api-key-here

Get your API key from Google AI Studio.
Usage
from drw import ifcontext, extract_context, is_context_positive, transform_context

# Check if text is about colors
@ifcontext("The sky is blue", "is talking about color")
def my_function():
    print("This is about colors!")

my_function()  # Prints: This is about colors! (if Gemini confirms color context)

# Extract colors
colors = extract_context("The sky is blue and red", "colors")
print(colors)  # Prints: ['blue', 'red'] (or similar, based on Gemini response)

# Check sentiment
is_positive = is_context_positive("I am so happy today!")
print(is_positive)  # Prints: True (if Gemini detects positive sentiment)

# Transform text
formal_text = transform_context("Hey, this is cool!", "make formal")
print(formal_text)  # Prints: Dear, this is excellent! (or similar, based on Gemini)

License
MIT License
PyBreathTranscript 1.1.0
Tool for transcribing breaths from audio files
Requires Python: >=3.11
Keywords: Transcription, Breath, Breathe, Breath transcription

# PyBreathTranscript
[![PyPi](https://img.shields.io/badge/pypi-0.7.0-blue)](https://test.pypi.org/project/PyBreathTranscript/)



This package is used for transcribing breath recordings (captured using an in-ear microphone) into text symbols.

Check [Full project](https://github.com/ilya-shlom/breathing-analysis) to see this library in action.

## Quickstart

Install the package:

```bash
pip install -i https://test.pypi.org/simple/ PyBreathTranscript
```

or

```bash
pip install git+https://github.com/ilya-shlom/PyBreathTranscript.git
```

Example usage:

```python
from PyBreathTranscript import transcript as bt

result = bt.transcript("breath.wav", bt.FINGERPRINT)
print(result)
```

## Usage

Import library into your project using

```python
from PyBreathTranscript import transcript as bt
```

To transcribe a recording of your breath, use the `bt.transcript(file_path, method)` function:

```python
transcript = bt.transcript("path/to/your/recording.wav", bt.FINGERPRINT)
```

`file_path: str` - path of your recording.

`method: int` - method used to transcribe an audio file. There are two methods available now acceptable by constants:

1. `bt.FINGERPRINT` – method based on an audio fingerprinting algorithm. This is the recommended and default method.

2. `bt.WAVEFORM` – compares waveforms and returns the best-matching symbol. This approach is more realistic but less distinctive, recommended for demonstration purposes only.

_______
_Please note:_ this library is created for educational and demonstration purposes. For the best experience, an in-ear microphone based on the [BOYA BY-M1 Lavalier microphone](https://www.boyamic.com/product/lavalier-microphone-by-m1) is recommended.

This project is a part of my graduation work, Cyrillic symbols are one of requirements for the system.