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feat: add meeting transcription app scaffolding
- Add Python backend structure with FastAPI for transcription/summarization
- Add React UI with audio recording, transcript, and summary views
- Configure Tauri to manage Python backend lifecycle
- Set up Windows cross-compilation with cargo-xwin
- Add Gitea CI workflow for lint, test, and multi-platform builds
- Configure ESLint, Prettier, and Vitest for code quality

Note: App scaffolding only - Python env and models not yet set up
2026-01-21 20:18:03 -08:00

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# Chronara - Local Meeting Transcription & Summarization
A Windows desktop application that transcribes, diarizes, and summarizes meetings using only locally-running models.
## Features
- 🎙️ Real-time audio transcription with speaker diarization (WhisperX)
- 📝 Intelligent meeting summarization (Llama 3.2)
- 🖥️ Everything runs locally - no cloud services required
- 📦 All models bundled - no separate downloads needed
## Tech Stack
- **Transcription**: WhisperX (Whisper + speaker diarization)
- **Summarization**: Llama 3.2 1B/3B
- **Backend**: Python with FastAPI
- **Frontend**: Tauri + React
- **Model Runtime**: llama-cpp-python
## Project Structure
```
chronara/
├── src/
│ ├── backend/ # Python FastAPI backend
│ ├── components/ # React components
│ └── App.tsx # Main React app
├── src-tauri/ # Tauri configuration
├── models/ # Bundled model files
├── scripts/ # Build and setup scripts
└── assets/ # Icons, resources
```
## Development Setup
### Prerequisites
- Node.js 18+ with pnpm
- Python 3.10+
- Rust (for Tauri)
- Windows build tools (for native modules)
### Installation
1. Clone the repository:
```bash
git clone https://github.com/naomi-lgbt/chronara.git
cd chronara
```
2. Install frontend dependencies:
```bash
pnpm install
```
3. Install Python dependencies:
```bash
pip install -r requirements.txt
```
4. Download the AI models:
```bash
python scripts/download_models.py
```
5. Run in development mode:
```bash
pnpm tauri:dev
```
## Building for Production
### Windows
1. Download models if not already done:
```bash
python scripts/download_models.py
```
2. Build the Windows executable:
```bash
python scripts/build_windows.py
```
The installer will be created in `src-tauri/target/release/bundle/nsis/`.
## Usage
1. **Start Recording**: Click the "Start Recording" button to begin capturing audio
2. **Real-time Transcription**: Watch as the conversation is transcribed with speaker labels
3. **Generate Summary**: After recording, click "Generate Summary" for an AI-powered meeting summary
4. **Export**: Download both the full transcript and summary as text files
## Model Information
### Transcription (WhisperX)
- **Model**: OpenAI Whisper base model with WhisperX enhancements
- **Features**: Speaker diarization, timestamp alignment
- **Size**: ~150MB
### Summarization (Llama 3.2)
- **1B Model**: Fast, good for basic summaries (~1.2GB)
- **3B Model**: Better quality summaries (~2.5GB)
- **Format**: GGUF quantized models
## Privacy & Security
- All processing happens locally on your machine
- No audio or text data is sent to external servers
- Models are bundled with the application
- Meeting data stays on your device