semvec/pypi-packages huggingface dataset:
synaptik 0.1.0
A Python library for neural connections, memory formation, and intelligence
License: MIT
Requires Python: >=3.10
Keywords: neural, memory, intelligence, ai, machine-learning

# Synaptik

A Python library for neural connections, memory formation, and intelligence.

## Installation

Install from PyPI:

```bash
pip install synaptik
```

Or install from source:

```bash
git clone https://github.com/hemprasadbadgujar/synaptik.git
cd synaptik
pip install -e .
```

## Quick Start

```python
from synaptik import hello_world

print(hello_world())
# Output: Hello, World! Welcome to Synaptik!
```

## Development

### Setup Development Environment

```bash
git clone https://github.com/hemprasadbadgujar/synaptik.git
cd synaptik
pip install -e ".[dev]"
```

### Running Tests

```bash
pytest
```

## Publishing to PyPI

This package is automatically published to PyPI when a new release is created on GitHub.

### Manual Publishing

1. Update the version in `pyproject.toml` and `setup.py`
2. Build the package:
   ```bash
   python -m build
   ```
3. Upload to PyPI:
   ```bash
   python -m twine upload dist/*
   ```

### Automatic Publishing via GitHub Actions

The package is automatically published when you:
1. Create a new release on GitHub (tagged release)
2. Or manually trigger the workflow from GitHub Actions

**Note:** You need to configure PyPI trusted publishing:
1. Go to PyPI → Account Settings → API tokens
2. Add a new API token with "Trusted publishing"
3. Add your GitHub repository to the trusted publishers

## License

MIT License - see LICENSE file for details.

## Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

## Author

Hemprasad Badgujar
monlam-stt 0.1.0
Tibetan speech-to-text (STT) utilities extracted from monlamai-API.
License: MIT
Requires Python: >=3.8

# monlam-stt

`monlam-stt` is a small Python library that exposes the core speech-to-text (STT) logic
from the Monlam AI API as a reusable package.

It provides helpers to:

- Convert audio bytes to FLAC using `ffmpeg`
- Send base64-encoded audio to a Hugging Face STT model

## Installation

After publishing to PyPI, you will be able to install it with:

```bash
pip install monlam-stt
```

For local development inside this repo:

```bash
cd monlam_stt_pkg
pip install -e .
```

## Usage

Basic async usage:

```python
import asyncio
from monlam_stt import transcribe_bytes

async def main():
    with open("example.wav", "rb") as f:
        audio = f.read()
    text = await transcribe_bytes(audio)
    print(text)

asyncio.run(main())
```

Environment variables expected:

- `MODEL_AUTH` – Bearer token for the Hugging Face model
- `STT_MODEL_URL_TIBETAN` – URL of the STT model endpoint

## Development

Build the distribution:

```bash
cd monlam_stt_pkg
python -m pip install --upgrade build
python -m build
```

Upload to PyPI:

```bash
python -m pip install --upgrade twine
python -m twine upload dist/*
```