diff --git a/farsi_transcriber_web/.gitignore b/farsi_transcriber_web/.gitignore new file mode 100644 index 0000000..9d231bb --- /dev/null +++ b/farsi_transcriber_web/.gitignore @@ -0,0 +1,34 @@ +# 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 diff --git a/farsi_transcriber_web/README.md b/farsi_transcriber_web/README.md new file mode 100644 index 0000000..1737d96 --- /dev/null +++ b/farsi_transcriber_web/README.md @@ -0,0 +1,384 @@ +# 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 diff --git a/farsi_transcriber_web/backend/.gitignore b/farsi_transcriber_web/backend/.gitignore new file mode 100644 index 0000000..801d628 --- /dev/null +++ b/farsi_transcriber_web/backend/.gitignore @@ -0,0 +1,42 @@ +# 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 diff --git a/farsi_transcriber_web/backend/app.py b/farsi_transcriber_web/backend/app.py new file mode 100644 index 0000000..e92d820 --- /dev/null +++ b/farsi_transcriber_web/backend/app.py @@ -0,0 +1,199 @@ +""" +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) diff --git a/farsi_transcriber_web/backend/requirements.txt b/farsi_transcriber_web/backend/requirements.txt new file mode 100644 index 0000000..3f1a28f --- /dev/null +++ b/farsi_transcriber_web/backend/requirements.txt @@ -0,0 +1,6 @@ +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 diff --git a/farsi_transcriber_web/index.html b/farsi_transcriber_web/index.html new file mode 100644 index 0000000..8cf5754 --- /dev/null +++ b/farsi_transcriber_web/index.html @@ -0,0 +1,13 @@ + + + + + + + Farsi Audio/Video Transcriber + + +
+ + + diff --git a/farsi_transcriber_web/package.json b/farsi_transcriber_web/package.json new file mode 100644 index 0000000..19f8a99 --- /dev/null +++ b/farsi_transcriber_web/package.json @@ -0,0 +1,30 @@ +{ + "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" + } +} diff --git a/farsi_transcriber_web/postcss.config.js b/farsi_transcriber_web/postcss.config.js new file mode 100644 index 0000000..2e7af2b --- /dev/null +++ b/farsi_transcriber_web/postcss.config.js @@ -0,0 +1,6 @@ +export default { + plugins: { + tailwindcss: {}, + autoprefixer: {}, + }, +} diff --git a/farsi_transcriber_web/src/App.tsx b/farsi_transcriber_web/src/App.tsx new file mode 100644 index 0000000..4550c0a --- /dev/null +++ b/farsi_transcriber_web/src/App.tsx @@ -0,0 +1,449 @@ +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([]); + const [selectedFileId, setSelectedFileId] = useState(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() + ? `${part}` + : part + ).join(''); + }; + + const getStatusIcon = (status: FileItem['status']) => { + switch (status) { + case 'completed': + return ; + case 'processing': + return ; + case 'error': + return ; + default: + return ; + } + }; + + return ( +
+ + + { + 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' }, + }} + > +
+ {/* Left Sidebar - File Queue */} +
+
+

+ File Queue +

+ +
+ +
+ {fileQueue.length === 0 ? ( +

+ No files in queue +

+ ) : ( + fileQueue.map((file) => ( +
setSelectedFileId(file.id)} + > +
+
+ {getStatusIcon(file.status)} + + {file.name} + +
+ +
+ {file.status === 'processing' && ( +
+ +

+ {file.progress}% +

+
+ )} +
+ )) + )} +
+
+ + {/* Main Content Area */} +
+ {/* Header */} +
+
+

+ Farsi Audio/Video Transcriber +

+ + {windowSize.width}×{windowSize.height} + +
+ +
+ +
+ {/* File Info & Actions */} +
+
+
+ +
+

+ {selectedFile ? selectedFile.name : 'No file selected'} +

+ {selectedFile?.status === 'processing' && ( +

+ Processing... {selectedFile.progress}% +

+ )} + {selectedFile?.status === 'completed' && ( +

Completed

+ )} +
+
+ +
+
+ + {/* Search & Export Controls */} + {selectedFile?.transcription && ( +
+
+ + setSearchQuery(e.target.value)} + style={{ + backgroundColor: theme.inputBg, + borderColor: theme.border, + color: theme.text, + paddingLeft: '2.25rem', + }} + /> +
+ + +
+ )} + + {/* Transcription Results */} +
+
+ + {searchQuery && ( + + {filteredTranscription.length} results found + + )} +
+ +
+ {currentTranscription.length === 0 ? ( +

+ Transcription results will appear here... +

+ ) : ( +
+ {filteredTranscription.map((segment, index) => ( +
+
+ + [{segment.start} - {segment.end}] + + +
+

+

+ ))} +
+ )} +
+
+ + {/* Bottom Actions */} +
+

+ {selectedFile?.status === 'completed' && `${currentTranscription.length} segments`} +

+ +
+
+
+
+ +
+ ); +} diff --git a/farsi_transcriber_web/src/components/Button.tsx b/farsi_transcriber_web/src/components/Button.tsx new file mode 100644 index 0000000..f1abd72 --- /dev/null +++ b/farsi_transcriber_web/src/components/Button.tsx @@ -0,0 +1,36 @@ +import React from 'react'; + +interface ButtonProps extends React.ButtonHTMLAttributes { + variant?: 'default' | 'outline'; + size?: 'sm' | 'md' | 'lg'; + children: React.ReactNode; +} + +const Button = React.forwardRef( + ({ 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 ( +