semvec/pypi-packages huggingface dataset:
whatsapp-utilsFAPI 0.36.0
whatsapp_utilsFAPI
License: MIT
Requires Python: >=3.11

# WhatsApp Utils

A Python package for handling WhatsApp audio messages with Azure AI services integration.

## Features

- Send and receive WhatsApp audio messages
- Speech-to-text conversion using Azure Cognitive Services
- Text-to-speech conversion using Azure Cognitive Services
- AI-powered responses using Azure OpenAI

## Installation

```bash
python -m build
pip install whatsapp_utilsFAPI
python-yate 0.5.0
An (asyncio enabled) python library for yate IVRs and extmodules
License: MIT

# Python support for yate-pbx

This package implements library support for the external module protocol used
by the yate pbx. There is support for the basic wire protocol and higher level
abstractions using asyncio - including special support for IVRs (interactive voice
response) systems.

# Examples

Have a look at the examples folder to see how to use the IVR support library.

Moreover, there is a call generator example in the tools folder.
gke-cache-builder 1.0.7
[Protected] GKE Multi-Cluster Cache Builder with Fuzzy Search
License: MIT
Requires Python: >=3.8
Keywords: gke, kubernetes, cache, fuzzy-search, multi-cluster

"""
# GKE Cache Builder

Multi-cluster GKE cache builder with fuzzy search capabilities for hosts, namespaces, and clients.

## Installation

```bash
pip install gke-cache-builder
```

## Quick Start

```python
from gke_cache_builder import build_cache, get_cache, fuzzy_search_hosts

# Build cache from GCP organization
cache = build_cache(org_id="123456789")

# Get cached data
cache_data = get_cache()

# Fuzzy search for hosts
results = fuzzy_search_hosts("example.com", max_results=5)
```

## Features

- Multi-cluster GKE discovery
- Host-to-namespace mapping
- Fuzzy search for hosts, namespaces, and clients
- CSV-based client name mapping
- NFS storage mapping support
- Thread-safe operations

## Configuration

Set environment variables:

```bash
export GOOGLE_APPLICATION_CREDENTIALS=/path/to/service-account.json
export GCP_ORG_ID=123456789
export CLIENT_MAPPINGS_CSV=client_mappings.csv
```

## Usage Examples

### Building Cache

```python
from gke_cache_builder import build_cache

# Build from organization
cache = build_cache(org_id="123456789")

# Build from folder
cache = build_cache(folder_id="987654321")
```

### Searching

```python
from gke_cache_builder import fuzzy_search_hosts, fuzzy_search_namespaces

# Search hosts
host_results = fuzzy_search_hosts("acme", max_results=5, min_score=0.4)

# Search namespaces
ns_results = fuzzy_search_namespaces("prod", max_results=5)
```

### Client CSV Mapping

```python
from gke_cache_builder import get_csv_handler, create_sample_csv

# Create sample CSV
create_sample_csv("client_mappings.csv")

# Use CSV handler
handler = get_csv_handler()
client_data = handler.get_client_data("www.example.com")
```

## License

MIT License
"""
noahs-tts 0.1.2
A wrapper class to get started using Text To Speech quickly
License: MIT
Requires Python: >=3.9

## Usage: `noahs_tts`

### Getting Started

First, install the library:

```bash
pip install noahs_tts
```

## Quick start

```python
from noahs_tts import TTS  # if you saved the class in tts.py

tts = TTS()
tts.say("Hello world!")  # blocks until finished
```

Speak sentence-by-sentence (default) for snappier responsiveness:

```python
tts.say("First sentence. Second sentence! Third sentence?")
```

Speak the whole string as one chunk:

```python
tts.say("This will be spoken as a single utterance.", split_sentences=False)
```

Speak the contents of a stream generator:

```python
def example_generator():
    for s in ["hello there", "this is a stream", "last chunk here"]:
        yield s

tts.say_stream(example_generator())
```

---

## Voice management

List available voices (id, name, locale, gender when available):

```python
voices = tts.voices()
for v in voices:
    print(v["id"], v["name"], v["locale"], v["gender"])
```

Pick a voice by **name** or **id** (partial match allowed):

```python
tts = TTS(voice="Zira")          # Windows example
tts = TTS(voice="Samantha")      # macOS example
tts = TTS(voice="english-us")    # Linux/eSpeak example
```

---

## Control rate

Rate is engine-specific “words per minute” style. This wrapper casts to `int`.

```python
tts = TTS(rate=180)      # set default on init
tts.say("Speaking at 180 wpm (approx).")

tts.say("Speed this one up.", split_sentences=False)
```

You can also override per-call when saving/synthesizing:

```python
data = tts.synth("Faster line.", rate=220)
```

---

## Save audio

Get WAV bytes:

```python
wav_bytes = tts.synth("Save me to a file later.")
with open("out.wav", "wb") as f:
    f.write(wav_bytes)
```

Or save directly:

```python
tts.save("Write this straight to disk.", "speech.wav", voice="Samantha", rate=170)
```

---


### Check out Source Code

`https://github.com/jonesnoah45010/noahs_tts`