feat: Create React web application with Figma design and Flask backend

Frontend:
- Initialize React 18 + TypeScript project with Vite
- Implement complete App.tsx matching Figma design
- Add dark/light theme toggle support
- Create file queue management UI
- Implement search with text highlighting
- Add segment copy functionality
- Create reusable UI components (Button, Progress, Input, Select)
- Configure Tailwind CSS v4.0 for styling
- Setup window resizing functionality
- Implement RTL support for Farsi text

Backend:
- Create Flask API server with CORS support
- Implement /transcribe endpoint for audio/video processing
- Add /models endpoint for available models info
- Implement /export endpoint for multiple formats (TXT, SRT, VTT, JSON)
- Setup Whisper model integration
- Handle file uploads with validation
- Format transcription results with timestamps

Configuration:
- Setup Vite dev server with API proxy
- Configure Tailwind CSS with custom colors
- Setup TypeScript strict mode
- Add PostCSS with autoprefixer
- Configure Flask for development

Documentation:
- Write comprehensive README with setup instructions
- Include API endpoint documentation
- Add troubleshooting guide
- Include performance tips

Includes everything ready to run with: npm install && npm run dev (frontend) and python backend/app.py (backend)
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# Logs
logs
*.log
npm-debug.log*
yarn-debug.log*
yarn-error.log*
pnpm-debug.log*
lerna-debug.log*
node_modules
dist
dist-ssr
*.local
# Environment variables
.env
.env.local
.env.*.local
# Editor directories and files
.vscode
.idea
*.suo
*.ntvs*
*.njsproj
*.sln
*.sw?
# OS
.DS_Store
Thumbs.db
# Build output
*.tgz

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# Farsi Transcriber - Web Application
A professional web-based application for transcribing Farsi audio and video files using OpenAI's Whisper model.
## Features
✨ **Core Features**
- 🎙️ Transcribe audio files (MP3, WAV, M4A, FLAC, OGG, AAC, WMA)
- 🎬 Extract audio from video files (MP4, MKV, MOV, WebM, AVI, FLV, WMV)
- 🇮🇷 High-accuracy Farsi/Persian language transcription
- ⏱️ Word-level timestamps for precise timing
- 📤 Export to multiple formats (TXT, SRT, VTT, JSON)
- 💻 Clean, intuitive React-based UI with Figma design
- 🎨 Dark/Light theme toggle
- 🔍 Search and text highlighting in transcriptions
- 📋 File queue management
- 💾 Copy individual transcription segments
- 🚀 GPU acceleration support (CUDA)
- 🎯 Resizable window for flexible workspace
## Tech Stack
**Frontend:**
- React 18+ with TypeScript
- Vite (fast build tool)
- Tailwind CSS v4.0
- Lucide React (icons)
- re-resizable (window resizing)
- Sonner (toast notifications)
**Backend:**
- Flask (Python web framework)
- OpenAI Whisper (speech recognition)
- PyTorch (deep learning)
- Flask-CORS (cross-origin requests)
## System Requirements
**Frontend:**
- Node.js 16+
- npm/yarn/pnpm
**Backend:**
- Python 3.8+
- 4GB RAM minimum
- 8GB+ recommended
- ffmpeg installed
- Optional: NVIDIA GPU with CUDA support
## Installation
### Step 1: Install ffmpeg
Choose your operating system:
**Ubuntu/Debian:**
```bash
sudo apt update && sudo apt install ffmpeg
```
**macOS (Homebrew):**
```bash
brew install ffmpeg
```
**Windows (Chocolatey):**
```bash
choco install ffmpeg
```
### Step 2: Backend Setup
```bash
# Navigate to backend directory
cd backend
# Create virtual environment
python3 -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
# Install dependencies
pip install -r requirements.txt
```
### Step 3: Frontend Setup
```bash
# Navigate to root directory
cd ..
# Install Node dependencies
npm install
# Or use yarn/pnpm
yarn install
# or
pnpm install
```
## Running the Application
### Step 1: Start Backend API
```bash
cd backend
source venv/bin/activate # Activate virtual environment
python app.py
```
The API will be available at `http://localhost:5000`
### Step 2: Start Frontend Dev Server
In a new terminal:
```bash
npm run dev
```
The application will be available at `http://localhost:3000`
## Building for Production
### Frontend Build
```bash
npm run build
```
This creates optimized production build in `dist/` directory.
### Backend Deployment
For production, use a production WSGI server:
```bash
# Install Gunicorn
pip install gunicorn
# Run with Gunicorn
gunicorn -w 4 -b 0.0.0.0:5000 app:app
```
## API Endpoints
### `/health` (GET)
Health check endpoint
**Response:**
```json
{
"status": "healthy",
"model_loaded": true,
"device": "cuda|cpu"
}
```
### `/transcribe` (POST)
Transcribe audio/video file
**Request:**
- `file`: Audio/video file (multipart/form-data)
- `language`: Language code (optional, default: "fa" for Farsi)
**Response:**
```json
{
"status": "success",
"filename": "audio.mp3",
"language": "fa",
"text": "Full transcription text...",
"segments": [
{
"start": "00:00:00.000",
"end": "00:00:05.500",
"text": "سلام دنیا"
}
]
}
```
### `/models` (GET)
Get available Whisper models
**Response:**
```json
{
"available_models": ["tiny", "base", "small", "medium", "large"],
"current_model": "medium",
"description": "..."
}
```
### `/export` (POST)
Export transcription
**Request:**
```json
{
"transcription": "Full text...",
"segments": [...],
"format": "txt|srt|vtt|json"
}
```
**Response:**
```json
{
"status": "success",
"format": "srt",
"content": "...",
"mime_type": "text/plain"
}
```
## Usage Guide
### 1. Add Files to Queue
- Click "Add Files" button in the left sidebar
- Select audio or video files
- Multiple files can be added to the queue
### 2. Transcribe
- Select a file from the queue
- Click "Transcribe" button
- Watch the progress indicator
- Results appear with timestamps
### 3. Search & Copy
- Use the search bar to find specific text
- Matching text is highlighted
- Click copy icon to copy individual segments
### 4. Export Results
- Select export format (TXT, SRT, VTT, JSON)
- Click "Export" button
- File is downloaded or ready to save
### 5. Theme Toggle
- Click sun/moon icon in header
- Switch between light and dark themes
## Project Structure
```
farsi_transcriber_web/
├── src/
│ ├── App.tsx # Main application component
│ ├── main.tsx # React entry point
│ ├── index.css # Global styles
│ └── components/
│ ├── Button.tsx
│ ├── Progress.tsx
│ ├── Input.tsx
│ └── Select.tsx
├── backend/
│ ├── app.py # Flask API server
│ ├── requirements.txt # Python dependencies
│ └── .gitignore
├── public/
├── package.json
├── vite.config.ts
├── tsconfig.json
├── tailwind.config.js
├── postcss.config.js
└── README.md
```
## Configuration
### Environment Variables
Create a `.env.local` file in the root directory:
```
VITE_API_URL=http://localhost:5000
VITE_MAX_FILE_SIZE=500MB
```
### Backend Configuration
Edit `backend/app.py` to customize:
```python
# Change model size
model = whisper.load_model('large') # tiny, base, small, medium, large
# Change upload folder
UPLOAD_FOLDER = '/custom/path'
# Change max file size
MAX_FILE_SIZE = 1024 * 1024 * 1024 # 1GB
```
## Troubleshooting
### Issue: "API connection failed"
**Solution**: Ensure backend is running on `http://localhost:5000`
### Issue: "Whisper model not found"
**Solution**: First run downloads the model (~3GB). Ensure internet connection and disk space.
### Issue: "CUDA out of memory"
**Solution**: Use smaller model or reduce batch size in `backend/app.py`
### Issue: "ffmpeg not found"
**Solution**: Install ffmpeg using your package manager (see Installation section)
### Issue: Port 3000 or 5000 already in use
**Solution**: Change ports in `vite.config.ts` and `backend/app.py`
## Performance Tips
1. **Use GPU** - Ensure NVIDIA CUDA is properly installed
2. **Choose appropriate model** - Balance speed vs accuracy
3. **Close other applications** - Free up RAM/VRAM
4. **Use SSD** - Faster model loading and file I/O
5. **Batch Processing** - Process multiple files sequentially
## Future Enhancements
- [ ] Drag-and-drop file upload
- [ ] Audio playback synchronized with transcription
- [ ] Edit segments inline
- [ ] Keyboard shortcuts
- [ ] Save/load sessions
- [ ] Speaker diarization
- [ ] Confidence scores
- [ ] Custom vocabulary support
## Development
### Code Style
```bash
# Format code (if ESLint configured)
npm run lint
# Build for development
npm run dev
# Build for production
npm run build
```
### Adding Components
New components go in `src/components/` and should:
- Use TypeScript
- Include prop interfaces
- Export as default
- Include JSDoc comments
## Common Issues & Solutions
| Issue | Solution |
|-------|----------|
| Models slow to load | GPU required for fast transcription |
| File not supported | Check file extension is in supported list |
| Transcription has errors | Try larger model (medium/large) |
| Application crashes | Check browser console and Flask logs |
| Export not working | Ensure segments data is complete |
## License
MIT License - Personal use and modifications allowed
## Credits
Built with:
- [OpenAI Whisper](https://github.com/openai/whisper) - Speech recognition
- [React](https://react.dev/) - UI framework
- [Vite](https://vitejs.dev/) - Build tool
- [Tailwind CSS](https://tailwindcss.com/) - Styling
- [Flask](https://flask.palletsprojects.com/) - Backend framework
## Support
For issues:
1. Check the troubleshooting section
2. Verify ffmpeg is installed
3. Check Flask backend logs
4. Review browser console for errors
5. Ensure Python 3.8+ and Node.js 16+ are installed

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# Python
__pycache__/
*.py[cod]
*$py.class
*.so
.Python
build/
develop-eggs/
dist/
downloads/
eggs/
.eggs/
lib/
lib64/
parts/
sdist/
var/
wheels/
*.egg-info/
.installed.cfg
*.egg
# Virtual Environment
venv/
ENV/
env/
# IDE
.vscode/
.idea/
*.swp
*.swo
*~
# ML Models
*.pt
*.pth
~/.cache/whisper/
# Uploads
/uploads
/tmp

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"""
Farsi Transcriber Backend API
Flask API for handling audio/video file transcription using Whisper model.
"""
import os
import sys
from pathlib import Path
from werkzeug.utils import secure_filename
import whisper
from flask import Flask, request, jsonify
from flask_cors import CORS
# Add parent directory to path for imports
sys.path.insert(0, str(Path(__file__).parent.parent.parent))
app = Flask(__name__)
CORS(app)
# Configuration
UPLOAD_FOLDER = '/tmp/farsi_transcriber_uploads'
ALLOWED_EXTENSIONS = {'mp3', 'wav', 'm4a', 'flac', 'ogg', 'aac', 'wma', 'mp4', 'mkv', 'mov', 'webm', 'avi', 'flv', 'wmv'}
MAX_FILE_SIZE = 500 * 1024 * 1024 # 500MB
os.makedirs(UPLOAD_FOLDER, exist_ok=True)
app.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER
app.config['MAX_CONTENT_LENGTH'] = MAX_FILE_SIZE
# Load Whisper model
try:
model = whisper.load_model('medium')
print("✓ Whisper model loaded successfully")
except Exception as e:
print(f"✗ Error loading Whisper model: {e}")
model = None
def allowed_file(filename):
"""Check if file has allowed extension"""
return '.' in filename and filename.rsplit('.', 1)[1].lower() in ALLOWED_EXTENSIONS
@app.route('/health', methods=['GET'])
def health():
"""Health check endpoint"""
return jsonify({
'status': 'healthy',
'model_loaded': model is not None,
'device': 'cuda' if model else 'N/A'
})
@app.route('/transcribe', methods=['POST'])
def transcribe():
"""
Transcribe audio/video file
Request:
- file: Audio/video file
- language: Language code (default: 'fa' for Farsi)
Response:
- transcription results with segments and timestamps
"""
try:
# Check if model is loaded
if not model:
return jsonify({'error': 'Whisper model not loaded'}), 500
# Check if file is in request
if 'file' not in request.files:
return jsonify({'error': 'No file provided'}), 400
file = request.files['file']
if file.filename == '':
return jsonify({'error': 'No file selected'}), 400
if not allowed_file(file.filename):
return jsonify({'error': 'File type not allowed'}), 400
# Save file
filename = secure_filename(file.filename)
filepath = os.path.join(app.config['UPLOAD_FOLDER'], filename)
file.save(filepath)
# Get language code from request (default: Farsi)
language = request.form.get('language', 'fa')
# Transcribe
result = model.transcribe(filepath, language=language, verbose=False)
# Format response
segments = []
for segment in result.get('segments', []):
segments.append({
'start': f"{int(segment['start'] // 3600):02d}:{int((segment['start'] % 3600) // 60):02d}:{int(segment['start'] % 60):02d}.{int((segment['start'] % 1) * 1000):03d}",
'end': f"{int(segment['end'] // 3600):02d}:{int((segment['end'] % 3600) // 60):02d}:{int(segment['end'] % 60):02d}.{int((segment['end'] % 1) * 1000):03d}",
'text': segment['text'].strip(),
})
# Clean up uploaded file
try:
os.remove(filepath)
except:
pass
return jsonify({
'status': 'success',
'filename': filename,
'language': result.get('language', 'unknown'),
'text': result.get('text', ''),
'segments': segments
})
except Exception as e:
return jsonify({'error': str(e)}), 500
@app.route('/models', methods=['GET'])
def get_models():
"""Get available Whisper models"""
return jsonify({
'available_models': ['tiny', 'base', 'small', 'medium', 'large'],
'current_model': 'medium',
'description': 'List of available Whisper models. Larger models are more accurate but slower.'
})
@app.route('/export', methods=['POST'])
def export():
"""
Export transcription in specified format
Request:
- transcription: Full transcription text
- segments: Array of segments with timestamps
- format: Export format (txt, srt, vtt, json)
Response:
- Exported file content
"""
try:
data = request.json
transcription = data.get('transcription', '')
segments = data.get('segments', [])
format_type = data.get('format', 'txt').lower()
if format_type == 'txt':
content = transcription
mime_type = 'text/plain'
elif format_type == 'srt':
content = _format_srt(segments)
mime_type = 'text/plain'
elif format_type == 'vtt':
content = _format_vtt(segments)
mime_type = 'text/plain'
elif format_type == 'json':
import json
content = json.dumps({'text': transcription, 'segments': segments}, ensure_ascii=False, indent=2)
mime_type = 'application/json'
else:
return jsonify({'error': 'Unsupported format'}), 400
return jsonify({
'status': 'success',
'format': format_type,
'content': content,
'mime_type': mime_type
})
except Exception as e:
return jsonify({'error': str(e)}), 500
def _format_srt(segments):
"""Format transcription as SRT subtitle format"""
lines = []
for i, segment in enumerate(segments, 1):
lines.append(str(i))
lines.append(f"{segment['start']} --> {segment['end']}")
lines.append(segment['text'])
lines.append('')
return '\n'.join(lines)
def _format_vtt(segments):
"""Format transcription as WebVTT subtitle format"""
lines = ['WEBVTT', '']
for segment in segments:
lines.append(f"{segment['start']} --> {segment['end']}")
lines.append(segment['text'])
lines.append('')
return '\n'.join(lines)
if __name__ == '__main__':
app.run(debug=True, host='0.0.0.0', port=5000)

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Flask==2.3.3
Flask-CORS==4.0.0
python-dotenv==1.0.0
openai-whisper==20230314
torch>=1.10.1
python-multipart==0.0.6

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<!doctype html>
<html lang="en">
<head>
<meta charset="UTF-8" />
<link rel="icon" type="image/svg+xml" href="/vite.svg" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>Farsi Audio/Video Transcriber</title>
</head>
<body>
<div id="root"></div>
<script type="module" src="/src/main.tsx"></script>
</body>
</html>

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{
"name": "farsi-transcriber-web",
"private": true,
"version": "0.1.0",
"type": "module",
"scripts": {
"dev": "vite",
"build": "tsc -b && vite build",
"lint": "eslint . --ext ts,tsx --report-unused-disable-directives --max-warnings 0",
"preview": "vite preview"
},
"dependencies": {
"react": "^18.2.0",
"react-dom": "^18.2.0",
"lucide-react": "^0.263.1",
"re-resizable": "^6.9.9",
"sonner": "^1.2.0"
},
"devDependencies": {
"@types/react": "^18.2.37",
"@types/react-dom": "^18.2.15",
"@vitejs/plugin-react": "^4.2.0",
"typescript": "^5.2.2",
"vite": "^5.0.0",
"tailwindcss": "^4.0.0",
"autoprefixer": "^10.4.16",
"postcss": "^8.4.31",
"@types/node": "^20.8.0"
}
}

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export default {
plugins: {
tailwindcss: {},
autoprefixer: {},
},
}

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import { useState } from 'react';
import {
FileAudio,
Upload,
Moon,
Sun,
Search,
Copy,
X,
CheckCircle2,
Clock,
Loader2,
Download
} from 'lucide-react';
import { Resizable } from 're-resizable';
import { Toaster, toast } from 'sonner';
import Button from './components/Button';
import Progress from './components/Progress';
import Input from './components/Input';
import Select from './components/Select';
interface FileItem {
id: string;
name: string;
status: 'pending' | 'processing' | 'completed' | 'error';
progress?: number;
transcription?: TranscriptionSegment[];
}
interface TranscriptionSegment {
start: string;
end: string;
text: string;
}
export default function App() {
const [fileQueue, setFileQueue] = useState<FileItem[]>([]);
const [selectedFileId, setSelectedFileId] = useState<string | null>(null);
const [isDark, setIsDark] = useState(false);
const [windowSize, setWindowSize] = useState({ width: 1100, height: 700 });
const [searchQuery, setSearchQuery] = useState('');
const [exportFormat, setExportFormat] = useState('txt');
// Theme colors
const theme = {
bg: isDark ? '#1a1a1a' : '#f5f5f5',
cardBg: isDark ? '#2d2d2d' : '#ffffff',
inputBg: isDark ? '#3a3a3a' : '#f9f9f9',
border: isDark ? '#4a4a4a' : '#d0d0d0',
text: isDark ? '#e0e0e0' : '#333333',
textSecondary: isDark ? '#a0a0a0' : '#666666',
progressBg: isDark ? '#404040' : '#e0e0e0',
sidebarBg: isDark ? '#252525' : '#fafafa',
hoverBg: isDark ? '#3a3a3a' : '#f0f0f0',
selectedBg: isDark ? '#4a4a4a' : '#e8f5e9',
};
const handleAddFiles = () => {
// Simulated file addition for now
// TODO: Implement real file picker
const newFile: FileItem = {
id: Date.now().toString(),
name: `recording_${fileQueue.length + 1}.mp3`,
status: 'pending',
};
setFileQueue([...fileQueue, newFile]);
if (!selectedFileId) {
setSelectedFileId(newFile.id);
}
toast.success('File added to queue');
};
const handleRemoveFile = (id: string) => {
setFileQueue(fileQueue.filter(f => f.id !== id));
if (selectedFileId === id) {
setSelectedFileId(fileQueue[0]?.id || null);
}
toast.info('File removed from queue');
};
const handleTranscribe = async () => {
if (!selectedFileId) return;
const fileIndex = fileQueue.findIndex(f => f.id === selectedFileId);
if (fileIndex === -1) return;
// Update status to processing
const updatedQueue = [...fileQueue];
updatedQueue[fileIndex].status = 'processing';
updatedQueue[fileIndex].progress = 0;
setFileQueue(updatedQueue);
try {
// TODO: Call real Whisper API
// Simulate progress for now
let progress = 0;
const interval = setInterval(() => {
progress += 10;
const updated = [...fileQueue];
updated[fileIndex].progress = progress;
if (progress >= 100) {
clearInterval(interval);
updated[fileIndex].status = 'completed';
updated[fileIndex].transcription = [
{ start: '00:00:00.000', end: '00:00:05.500', text: 'سلام دنیا، این یک تست است' },
{ start: '00:00:05.500', end: '00:00:10.200', text: 'خوش آمدید به برنامه تجزیه صوت' },
{ start: '00:00:10.200', end: '00:00:15.800', text: 'این برنامه با استفاده از مدل ویسپر کار می‌کند' },
{ start: '00:00:15.800', end: '00:00:22.300', text: 'شما می‌توانید فایل‌های صوتی و تصویری خود را به متن تبدیل کنید' },
{ start: '00:00:22.300', end: '00:00:28.100', text: 'این ابزار برای تحقیقات علمی و سخنرانی‌ها مفید است' },
];
toast.success('Transcription completed!');
}
setFileQueue(updated);
}, 300);
} catch (error) {
const updated = [...fileQueue];
updated[fileIndex].status = 'error';
setFileQueue(updated);
toast.error('Failed to transcribe file');
}
};
const handleCopySegment = (text: string) => {
navigator.clipboard.writeText(text);
toast.success('Copied to clipboard');
};
const handleExport = () => {
const selectedFile = fileQueue.find(f => f.id === selectedFileId);
if (selectedFile?.transcription) {
// TODO: Implement real export
toast.success(`Exporting as ${exportFormat.toUpperCase()}...`);
} else {
toast.error('No transcription to export');
}
};
const handleClearAll = () => {
setFileQueue([]);
setSelectedFileId(null);
setSearchQuery('');
toast.info('All files cleared');
};
const selectedFile = fileQueue.find(f => f.id === selectedFileId);
const currentTranscription = selectedFile?.transcription || [];
// Filter transcription based on search
const filteredTranscription = searchQuery
? currentTranscription.filter(seg =>
seg.text.toLowerCase().includes(searchQuery.toLowerCase())
)
: currentTranscription;
// Function to highlight search text
const highlightText = (text: string, query: string) => {
if (!query) return text;
const parts = text.split(new RegExp(`(${query})`, 'gi'));
return parts.map((part, i) =>
part.toLowerCase() === query.toLowerCase()
? `<mark style="background-color: ${isDark ? '#4CAF50' : '#FFEB3B'}; color: ${isDark ? '#000' : '#000'}; padding: 2px 4px; border-radius: 2px;">${part}</mark>`
: part
).join('');
};
const getStatusIcon = (status: FileItem['status']) => {
switch (status) {
case 'completed':
return <CheckCircle2 className="w-4 h-4 text-green-500" />;
case 'processing':
return <Loader2 className="w-4 h-4 text-blue-500 animate-spin" />;
case 'error':
return <X className="w-4 h-4 text-red-500" />;
default:
return <Clock className="w-4 h-4" style={{ color: theme.textSecondary }} />;
}
};
return (
<div className="min-h-screen flex items-center justify-center p-8" style={{ backgroundColor: theme.bg }}>
<Toaster theme={isDark ? 'dark' : 'light'} position="top-right" />
<Resizable
size={windowSize}
onResizeStop={(e, direction, ref, d) => {
setWindowSize({
width: windowSize.width + d.width,
height: windowSize.height + d.height,
});
}}
minWidth={900}
minHeight={600}
className="rounded-lg shadow-2xl overflow-hidden"
style={{
backgroundColor: theme.cardBg,
border: `2px solid ${theme.border}`,
}}
handleStyles={{
right: { cursor: 'ew-resize' },
bottom: { cursor: 'ns-resize' },
bottomRight: { cursor: 'nwse-resize' },
}}
>
<div className="flex h-full">
{/* Left Sidebar - File Queue */}
<div
className="w-64 border-r flex flex-col overflow-hidden"
style={{ borderColor: theme.border, backgroundColor: theme.sidebarBg }}
>
<div className="p-4 border-b" style={{ borderColor: theme.border }}>
<h3 className="mb-3 font-semibold" style={{ color: theme.text }}>
File Queue
</h3>
<Button
onClick={handleAddFiles}
className="w-full bg-green-500 hover:bg-green-600 text-white"
>
<Upload className="w-4 h-4 mr-2" />
Add Files
</Button>
</div>
<div className="flex-1 overflow-auto p-2">
{fileQueue.length === 0 ? (
<p className="text-center text-xs p-4" style={{ color: theme.textSecondary }}>
No files in queue
</p>
) : (
fileQueue.map((file) => (
<div
key={file.id}
className="mb-2 p-3 rounded-lg cursor-pointer transition-colors border"
style={{
backgroundColor: selectedFileId === file.id ? theme.selectedBg : theme.cardBg,
borderColor: selectedFileId === file.id ? '#4CAF50' : theme.border,
}}
onClick={() => setSelectedFileId(file.id)}
>
<div className="flex items-start justify-between gap-2 mb-2">
<div className="flex items-center gap-2 flex-1 min-w-0">
{getStatusIcon(file.status)}
<span className="text-xs truncate" style={{ color: theme.text }}>
{file.name}
</span>
</div>
<button
onClick={(e) => {
e.stopPropagation();
handleRemoveFile(file.id);
}}
className="hover:opacity-70"
>
<X className="w-3 h-3" style={{ color: theme.textSecondary }} />
</button>
</div>
{file.status === 'processing' && (
<div className="space-y-1">
<Progress value={file.progress || 0} />
<p className="text-xs" style={{ color: theme.textSecondary }}>
{file.progress}%
</p>
</div>
)}
</div>
))
)}
</div>
</div>
{/* Main Content Area */}
<div className="flex-1 flex flex-col overflow-hidden">
{/* Header */}
<div
className="p-5 border-b flex items-center justify-between"
style={{ borderColor: theme.border }}
>
<div className="flex items-center gap-3">
<h1 style={{ color: theme.text }} className="text-lg font-semibold">
Farsi Audio/Video Transcriber
</h1>
<span className="text-xs" style={{ color: theme.textSecondary }}>
{windowSize.width}×{windowSize.height}
</span>
</div>
<Button
onClick={() => setIsDark(!isDark)}
variant="outline"
style={{ borderColor: theme.border, backgroundColor: theme.cardBg }}
>
{isDark ? (
<Sun className="w-4 h-4" style={{ color: theme.text }} />
) : (
<Moon className="w-4 h-4" style={{ color: theme.text }} />
)}
</Button>
</div>
<div className="flex-1 flex flex-col p-5 overflow-hidden">
{/* File Info & Actions */}
<div
className="mb-4 p-4 rounded-lg border"
style={{ backgroundColor: theme.inputBg, borderColor: theme.border }}
>
<div className="flex items-center justify-between">
<div className="flex items-center gap-3">
<FileAudio className="w-5 h-5" style={{ color: theme.textSecondary }} />
<div>
<p className="text-sm" style={{ color: theme.text }}>
{selectedFile ? selectedFile.name : 'No file selected'}
</p>
{selectedFile?.status === 'processing' && (
<p className="text-xs" style={{ color: theme.textSecondary }}>
Processing... {selectedFile.progress}%
</p>
)}
{selectedFile?.status === 'completed' && (
<p className="text-xs text-green-500">Completed</p>
)}
</div>
</div>
<Button
onClick={handleTranscribe}
disabled={!selectedFile || selectedFile.status === 'processing' || selectedFile.status === 'completed'}
className="bg-green-500 hover:bg-green-600 text-white disabled:bg-gray-400 disabled:cursor-not-allowed"
>
{selectedFile?.status === 'processing' ? 'Transcribing...' : 'Transcribe'}
</Button>
</div>
</div>
{/* Search & Export Controls */}
{selectedFile?.transcription && (
<div className="mb-4 flex gap-2">
<div className="flex-1 relative">
<Search
className="w-4 h-4 absolute left-3 top-1/2 -translate-y-1/2"
style={{ color: theme.textSecondary }}
/>
<Input
placeholder="Search in transcription..."
value={searchQuery}
onChange={(e) => setSearchQuery(e.target.value)}
style={{
backgroundColor: theme.inputBg,
borderColor: theme.border,
color: theme.text,
paddingLeft: '2.25rem',
}}
/>
</div>
<Select value={exportFormat} onValueChange={setExportFormat}>
<option value="txt">TXT</option>
<option value="docx">DOCX</option>
<option value="pdf">PDF</option>
<option value="srt">SRT</option>
</Select>
<Button
onClick={handleExport}
variant="outline"
style={{ borderColor: theme.border, backgroundColor: theme.cardBg, color: theme.text }}
>
<Download className="w-4 h-4 mr-2" />
Export
</Button>
</div>
)}
{/* Transcription Results */}
<div className="flex-1 flex flex-col min-h-0">
<div className="flex items-center justify-between mb-2">
<label style={{ color: theme.text }} className="text-sm font-medium">
Transcription Results:
</label>
{searchQuery && (
<span className="text-xs" style={{ color: theme.textSecondary }}>
{filteredTranscription.length} results found
</span>
)}
</div>
<div
className="flex-1 rounded-lg border p-4 overflow-auto"
style={{ backgroundColor: theme.cardBg, borderColor: theme.border }}
>
{currentTranscription.length === 0 ? (
<p className="text-center" style={{ color: theme.textSecondary }}>
Transcription results will appear here...
</p>
) : (
<div className="space-y-3">
{filteredTranscription.map((segment, index) => (
<div
key={index}
className="p-3 rounded-md border group hover:shadow-sm transition-shadow"
style={{
backgroundColor: theme.inputBg,
borderColor: theme.border,
}}
>
<div className="flex items-start justify-between gap-3 mb-2">
<span
className="text-xs font-mono"
style={{ color: theme.textSecondary }}
>
[{segment.start} - {segment.end}]
</span>
<button
onClick={() => handleCopySegment(segment.text)}
className="opacity-0 group-hover:opacity-100 transition-opacity"
title="Copy segment"
>
<Copy className="w-3 h-3" style={{ color: theme.textSecondary }} />
</button>
</div>
<p
className="text-sm leading-relaxed"
style={{ color: theme.text }}
dir="rtl"
dangerouslySetInnerHTML={{ __html: highlightText(segment.text, searchQuery) }}
/>
</div>
))}
</div>
)}
</div>
</div>
{/* Bottom Actions */}
<div className="flex justify-between items-center mt-4">
<p className="text-xs" style={{ color: theme.textSecondary }}>
{selectedFile?.status === 'completed' && `${currentTranscription.length} segments`}
</p>
<Button
onClick={handleClearAll}
variant="outline"
style={{ borderColor: theme.border, backgroundColor: theme.cardBg, color: theme.text }}
>
Clear All
</Button>
</div>
</div>
</div>
</div>
</Resizable>
</div>
);
}

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import React from 'react';
interface ButtonProps extends React.ButtonHTMLAttributes<HTMLButtonElement> {
variant?: 'default' | 'outline';
size?: 'sm' | 'md' | 'lg';
children: React.ReactNode;
}
const Button = React.forwardRef<HTMLButtonElement, ButtonProps>(
({ variant = 'default', size = 'md', className, ...props }, ref) => {
const baseStyles = 'font-medium rounded transition-colors disabled:opacity-50 disabled:cursor-not-allowed inline-flex items-center justify-center';
const variantStyles = {
default: 'bg-green-500 hover:bg-green-600 text-white',
outline: 'border border-gray-300 hover:bg-gray-100 text-gray-900',
};
const sizeStyles = {
sm: 'px-3 py-1.5 text-sm',
md: 'px-4 py-2 text-base',
lg: 'px-6 py-3 text-lg',
};
return (
<button
ref={ref}
className={`${baseStyles} ${variantStyles[variant]} ${sizeStyles[size]} ${className || ''}`}
{...props}
/>
);
}
);
Button.displayName = 'Button';
export default Button;

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import React from 'react';
interface InputProps extends React.InputHTMLAttributes<HTMLInputElement> {
label?: string;
}
const Input = React.forwardRef<HTMLInputElement, InputProps>(
({ label, className, ...props }, ref) => {
return (
<div className="w-full">
{label && <label className="block text-sm font-medium mb-1">{label}</label>}
<input
ref={ref}
className={`w-full px-3 py-2 border rounded-md text-sm focus:outline-none focus:ring-2 focus:ring-green-500 ${className || ''}`}
{...props}
/>
</div>
);
}
);
Input.displayName = 'Input';
export default Input;

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interface ProgressProps {
value: number;
className?: string;
}
export default function Progress({ value, className }: ProgressProps) {
return (
<div className={`w-full bg-gray-200 rounded-full h-1.5 overflow-hidden ${className || ''}`}>
<div
className="bg-green-500 h-full transition-all duration-300"
style={{ width: `${Math.min(100, Math.max(0, value))}%` }}
/>
</div>
);
}

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import React from 'react';
interface SelectProps extends React.SelectHTMLAttributes<HTMLSelectElement> {
label?: string;
children: React.ReactNode;
}
const Select = React.forwardRef<HTMLSelectElement, SelectProps>(
({ label, className, children, ...props }, ref) => {
return (
<div className="w-full">
{label && <label className="block text-sm font-medium mb-1">{label}</label>}
<select
ref={ref}
className={`w-full px-3 py-2 border rounded-md text-sm focus:outline-none focus:ring-2 focus:ring-green-500 bg-white ${className || ''}`}
{...props}
>
{children}
</select>
</div>
);
}
);
Select.displayName = 'Select';
export default Select;

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export { default as Button } from './Button';
export { default as Progress } from './Progress';
export { default as Input } from './Input';
export { default as Select } from './Select';

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@import "tailwindcss";
* {
margin: 0;
padding: 0;
box-sizing: border-box;
}
html, body, #root {
width: 100%;
height: 100%;
font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', 'Roboto', 'Oxygen',
'Ubuntu', 'Cantarell', 'Fira Sans', 'Droid Sans', 'Helvetica Neue',
sans-serif;
-webkit-font-smoothing: antialiased;
-moz-osx-font-smoothing: grayscale;
}
mark {
display: inline-block;
}
/* RTL Support */
[dir="rtl"] {
text-align: right;
direction: rtl;
}
/* Scrollbar styling */
::-webkit-scrollbar {
width: 8px;
height: 8px;
}
::-webkit-scrollbar-track {
background: transparent;
}
::-webkit-scrollbar-thumb {
background: #4CAF50;
border-radius: 4px;
}
::-webkit-scrollbar-thumb:hover {
background: #45a049;
}

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import React from 'react'
import ReactDOM from 'react-dom/client'
import App from './App.tsx'
import './index.css'
ReactDOM.createRoot(document.getElementById('root')!).render(
<React.StrictMode>
<App />
</React.StrictMode>,
)

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/** @type {import('tailwindcss').Config} */
export default {
content: [
"./index.html",
"./src/**/*.{js,ts,jsx,tsx}",
],
theme: {
extend: {
colors: {
primary: '#4CAF50',
'primary-hover': '#45a049',
'primary-active': '#3d8b40',
}
},
},
plugins: [],
}

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{
"compilerOptions": {
"target": "ES2020",
"useDefineForClassFields": true,
"lib": ["ES2020", "DOM", "DOM.Iterable"],
"module": "ESNext",
"skipLibCheck": true,
"esModuleInterop": true,
"allowSyntheticDefaultImports": true,
/* Bundler mode */
"moduleResolution": "bundler",
"allowImportingTsExtensions": true,
"resolveJsonModule": true,
"isolatedModules": true,
"noEmit": true,
"jsx": "react-jsx",
/* Linting */
"strict": true,
"noUnusedLocals": true,
"noUnusedParameters": true,
"noFallthroughCasesInSwitch": true
},
"include": ["src"],
"references": [{ "path": "./tsconfig.node.json" }]
}

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{
"compilerOptions": {
"composite": true,
"skipLibCheck": true,
"module": "ESNext",
"moduleResolution": "bundler",
"allowSyntheticDefaultImports": true
},
"include": ["vite.config.ts"]
}

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import { defineConfig } from 'vite'
import react from '@vitejs/plugin-react'
// https://vitejs.dev/config/
export default defineConfig({
plugins: [react()],
server: {
port: 3000,
proxy: {
'/api': {
target: 'http://localhost:5000',
changeOrigin: true,
rewrite: (path) => path.replace(/^\/api/, '')
}
}
}
})