Audio/Video Transcription Web App

A web application for transcribing audio and video files using WhisperX, with support for YouTube videos and optional summarization using Ollama.

Features

• Transcribe local audio/video files
• Process YouTube videos (with subtitle extraction when available)
• Automatic language detection
• Multiple WhisperX model options
• Optional text summarization using Ollama
• Modern web interface with Gradio
• Configurable settings via config.ini

Requirements

• Python 3.8+
• CUDA-compatible GPU (recommended)
• FFmpeg installed on your system
• Ollama (optional, for summarization)

Installation

1. Clone the repository:

git clone <repository-url>
cd whisperapp

2. Install the required packages:

pip install -r requirements.txt

3. Install FFmpeg (if not already installed):

• Ubuntu/Debian:

sudo apt update && sudo apt install ffmpeg

• macOS:

brew install ffmpeg

• Windows: Download from FFmpeg website

4. Copy the example configuration file:

cp .env.example .env

5. Edit the configuration files:

• .env: Set your environment variables
• config.ini: Configure WhisperX, Ollama, and application settings

Configuration

Application Settings (config.ini)

[whisper]
default_model = base
device = cuda
compute_type = float32
batch_size = 16
vad = true

[app]
max_duration = 3600
server_name = 0.0.0.0
server_port = 7860
share = true

[models]
available_models = tiny,base,small,medium,large-v1,large-v2,large-v3

[languages]
available_languages = en,es,fr,de,it,pt,nl,ja,ko,zh

[ollama]
enabled = false
url = http://localhost:11434
default_model = mistral
summarize_prompt = Please provide a comprehensive yet concise summary of the following text. Focus on the main points, key arguments, and important details while maintaining accuracy and completeness. Here's the text to summarize: 

Usage

1. Start the application:

python app.py

2. Open your web browser and navigate to:

http://localhost:7860

3. Use the interface to:
   • Upload and transcribe local audio/video files
   • Process YouTube videos
   • Generate summaries (if Ollama is configured)

Features in Detail

Local File Transcription

• Supports various audio and video formats
• Automatic language detection
• Multiple WhisperX model options
• Optional summarization with Ollama

YouTube Video Processing

• Supports youtube.com, youtu.be, and invidious URLs
• Automatically extracts subtitles if available
• Falls back to transcription if no subtitles found
• Optional summarization with Ollama

Summarization

• Uses Ollama for text summarization
• Configurable model selection
• Customizable prompt
• Available for both local files and YouTube videos

Notes

• For better accuracy, use larger models (medium, large)
• Processing time increases with model size
• GPU is recommended for faster processing
• Maximum audio duration is configurable (default: 60 minutes)
• YouTube videos will first try to use available subtitles
• If no subtitles are available, the video will be transcribed
• Ollama summarization is optional and requires Ollama to be running

License

This project is licensed under the MIT License - see the LICENSE file for details.