conversallink 0.4.2
Lightweight CLI for Recording & Transcribing with Whisper Accuracy
License: MIT
Requires Python: >=3.7

![cover](https://raw.githubusercontent.com/gchatzigianniss/ConversalLink/refs/heads/main/assets/cover.png?token=GHSAT0AAAAAADC4YPPQ3T6BJL2TZVX4YGEO2BHYDLA)


# ConversalLink

**Conversation Recorder & Transcriber**



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## 🎯 Features

* 🎙️ Record audio in 16kHz mono WAV format
* ✍️ Take timestamped notes while recording
* 📂 Use existing audio files (WAV, MP3, FLAC, OGG…)
* 🧠 Transcribe using **Faster-Whisper** (select model: tiny → large)
* 🔗 Auto-align notes with transcript segments
* 📤 Export as:
  - Markdown
  - JSON
  - Plain text
  - Beautiful HTML (with dark mode, audio player, jump-to-note)

---

## 📦 Installation

### From PyPI (Recommended)

```bash
pip install conversallink
```

### From Source

- Clone the repository
```bash
git clone https://github.com/gchatzigianniss/ConversalLink
```

- Install dependencies
```bash
pip install -r requirements.txt
```

- Run the script
```bash
python conversallink.py --file conversation.wav --notes conversation_notes.json
```

---

## 🚀 Quick Usage Examples

### 1. Record + Take Notes

```bash
# Run as a command-line tool
conversallink --record conversation.wav --model small --out markdown

# Or using Python module syntax
python -m conversallink --record conversation.wav --model small --out markdown
```

### 2. Transcribe an Existing File + Merge Notes

```bash
python conversallink.py --file conversation.wav --notes conversation_notes.json
```

### 3. Transcribe Only

```bash
python conversallink.py --file podcast.mp3 --model medium --out html
```


## 🤖 Transcription Models

ConversalLink uses Faster-Whisper models for transcription. You can select the model size based on your needs for accuracy vs. speed and resource usage.

| Model Size | Parameters | Accuracy | Speed | VRAM Usage | Disk Space | Use Case |
|------------|------------|----------|------|------------|------------|----------|
| `tiny`     | 39M        | Low      | Very Fast | ~1GB      | ~80MB     | Quick drafts, low-resource environments |
| `base`     | 74M        | Basic    | Fast | ~1GB      | ~150MB    | Simple recordings, clear speech |
| `small`    | 244M       | Good     | Medium | ~1GB      | ~500MB    | General purpose, good balance |
| `medium`   | 769M       | Very Good | Medium-Slow | ~2GB      | ~1.5GB    | Professional transcripts |
| `large-v2` | 1550M      | Excellent | Slow | ~3GB      | ~3GB      | Highest accuracy needs |
| `large-v3` | 1550M      | Best     | Slow | ~3GB      | ~3GB      | Latest model with best results |

To select a model, use the `--model` parameter:

```bash
conversallink --file recording.wav --model medium
```

> **Note**: Larger models provide better accuracy but require more computational resources and run slower. The `small` model offers a good balance for most use cases.

---


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## 📦 Dependencies

Install everything with:

```bash
pip install -r requirements.txt
```

**Core:**
- `sounddevice`
- `soundfile`
- `faster-whisper`
- `rich`

**Optional (for non-WAV input):**
- `pydub`
- `ffmpeg` (must be available in your system PATH)

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## ✅ Output Files

```
conversation_transcript.md     # 📝 Markdown
conversation_transcript.json   # 🗄️ JSON (full data)
conversation_transcript.html   # 🌐 Interactive HTML player
conversation_transcript.txt    # 📄 Plain text
conversation_notes.json        # 🧷 Timestamped notes
```

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## 📄 License

This project is open source under the [MIT License](https://github.com/gchatzigianniss/ConversalLink/blob/main/LICENSE).

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## 👨‍💻 Author

**gchatzigianniss**