Metadata-Version: 2.4
Name: transcribeai
Version: 0.1.0
Summary: Local-first audio transcription CLI using Whisper. No cloud, no API costs, 100% offline.
Author: transcribeai contributors
License: MIT
Project-URL: Homepage, https://github.com/morata43-png/transcribeai
Project-URL: Issues, https://github.com/morata43-png/transcribeai/issues
Keywords: transcription,whisper,audio,speech-to-text,cli,offline,local-first
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Topic :: Multimedia :: Sound/Audio :: Speech
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: typer>=0.9.0
Requires-Dist: rich>=13.0.0
Requires-Dist: openai-whisper>=20231117
Provides-Extra: dev
Requires-Dist: pytest>=7.0; extra == "dev"
Requires-Dist: pytest-cov>=4.0; extra == "dev"
Requires-Dist: ruff>=0.1.0; extra == "dev"
Dynamic: license-file

# pytranscribe

> Local-first audio transcription CLI using Whisper. 100% offline, no API costs.

A lightweight CLI tool that transcribes audio files using OpenAI's Whisper model running **locally** on your machine. No cloud, no API keys, no internet required after setup.

## Why pytranscribe?

- ✅ **No API costs**: Whisper runs locally, no OpenAI/Anthropic dependency
- ✅ **100% offline**: After first model download, no internet needed
- ✅ **Privacy**: Your audio never leaves your machine
- ✅ **Multi-format**: mp3, wav, m4a, flac, ogg, opus, mp4, webm
- ✅ **Multi-language**: Whisper supports 99 languages
- ✅ **Open source**: MIT license, code on GitHub

## Installation

```bash
pipx install pytranscribe
```

Note: First run will download the Whisper model (~40MB for `tiny`).

## Usage

### Basic transcription

```bash
# Use smallest model (~40MB), auto-detect language
pytranscribe transcribe audio.mp3

# Use better quality model
pytranscribe transcribe audio.mp3 --model base

# Force language
pytranscribe transcribe audio.mp3 --language es

# Save to file (auto-detects format from extension)
pytranscribe transcribe audio.mp3 --output transcript.txt

# Generate SRT subtitles
pytranscribe transcribe audio.mp3 --srt --output subtitles.srt
```

### List available models

```bash
pytranscribe models
```

## Models

| Model | Size | Speed | Quality |
|-------|------|-------|---------|
| `tiny` | 40 MB | Fastest | Good |
| `base` | 150 MB | Fast | Better |
| `small` | 500 MB | Medium | Great |
| `medium` | 1.5 GB | Slow | Excellent |
| `large` | 3 GB | Slowest | Best |

English-only variants (`tiny.en`, `base.en`, etc.) are faster but only work for English.

## Pricing

| Tier | Price | Features |
|------|-------|----------|
| **Free** | $0/mes | 30 min/mes, `tiny` model |
| **Pro** | **$3/mes** | Unlimited usage, all models, SRT export, batch processing |
| **One-time** | $10 | All Pro features, lifetime |

## License

MIT
