transcriber

Audio Transcriber

This project is an audio transcription application with a user-friendly web interface. It allows you to upload audio files and get transcriptions using either AssemblyAI or OpenAI’s Whisper API.

Features

Screenshot of the Transcriber App

Usage

  1. Upload Audio File: Click the “File” button to select an audio file from your computer.
  2. Select API: Choose either AssemblyAI or OpenAI Whisper from the dropdown.
  3. Select Language: Choose the language of your audio or leave it as “Automatic Detection.”
  4. Transcribe: Click the “Transcribe” button.
  5. View History: Your transcriptions will appear in the “Transcription History” section. You can copy, download, or delete them.

Prerequisites

Environment Variables

The application uses the following environment variables:

Variable Description Accepted Values Default
TZ The timezone for the application. Any valid timezone string (e.g., Europe/Amsterdam, America/New_York) UTC
ASSEMBLYAI_API_KEY Your API key for AssemblyAI. Your AssemblyAI API key None (required)
OPENAI_API_KEY Your API key for OpenAI Whisper. Your OpenAI API key None (required)
DEFAULT_TRANSCRIBE_API The default transcription API to use when the application loads. assemblyai or openai assemblyai
DEFAULT_LANGUAGE The default language to use for transcription when the application loads. auto, en, nl, fr, es auto

Installation and Deployment

You have two primary options for installation and deployment:

This is the easiest way to get started. You can pull the pre-built image from Docker Hub and run it directly.

  1. Pull the Docker Image:

     docker pull arnoulddw/transcriber-app:latest

  2. Run the Docker Container:

     docker run -d -p 5001:5001 \
   -e TZ="Your/Timezone" \
   -e ASSEMBLYAI_API_KEY="your_assemblyai_api_key" \
   -e OPENAI_API_KEY="your_openai_api_key" \
   -e DEFAULT_TRANSCRIBE_API="assemblyai" \
   -e DEFAULT_LANGUAGE="auto" \
   --name transcriber-app \
   arnoulddw/transcriber-app:latest
    • Replace "Your/Timezone" with your desired timezone (e.g., Europe/London).
    • Replace "your_assemblyai_api_key" and "your_openai_api_key" with your actual API keys.
    • You can change the DEFAULT_TRANSCRIBE_API and DEFAULT_LANGUAGE if needed.
    • The -d flag runs the container in detached mode (in the background).
    • The -p 5001:5001 flag maps port 5001 on your host machine to port 5001 in the container.
    • --name transcriber-app gives your container a name for easier management.

Option 2: Using Docker Compose (For Development or Customization)

If you want to customize the application or develop it further, you can use Docker Compose to build and run the image locally.

Step 1: Clone the Repository

  1. Open a terminal.
  2. Navigate to the directory where you want to store the project.

  3. Clone this repository:

     git clone https://github.com/arnoulddw/transcriber
 cd [Your-Project-Name]

Step 2: Configure Environment Variables in docker-compose.yml

  1. Open the docker-compose.yml file.

  2. Add your API keys and other environment variables under the environment section. Make sure to replace the placeholder values with your actual API keys:

     services:
   transcriber:
     build:
       context: .
       dockerfile: Dockerfile
     ports:
       - "5001:5001"
     volumes:
       - ./backend:/app/backend
       - ./temp_uploads:/app/temp_uploads
     environment:
       - TZ=${TZ:-UTC}
       - ASSEMBLYAI_API_KEY=your_assemblyai_api_key
       - OPENAI_API_KEY=your_openai_api_key
       - DEFAULT_TRANSCRIBE_API=${DEFAULT_TRANSCRIBE_API:-assemblyai}
       - DEFAULT_LANGUAGE=${DEFAULT_LANGUAGE:-auto}
     restart: unless-stopped

Step 3: Build and Run with Docker Compose

  1. In the project’s root directory, run the following command:

     docker-compose up -d --build

    This will build the Docker image and start the container in detached mode.

Step 4: Access the Application

  1. Open your web browser and go to:

     http://localhost:5001

Development (Local Setup)

If you want to develop or test the application locally before deploying it with Docker, follow these steps:

Step 1: Set up a Virtual Environment

  1. Open your terminal and navigate to the project directory.

  2. Create a virtual environment:

     python3 -m venv venv

  3. Activate the virtual environment:

     # On Linux/macOS
 source venv/bin/activate

 # On Windows
 venv\Scripts\activate

Step 2: Install Dependencies

  1. Install the required Python packages:

     pip install -r backend/requirements.txt

Step 3: Configure Environment Variables (Local)

  1. You can either set the environment variables temporarily in your terminal:

     # Example for Linux/macOS:
 export ASSEMBLYAI_API_KEY=your_assemblyai_api_key
 export OPENAI_API_KEY=your_openai_api_key
 export TZ=Europe/London
 # ... other variables

  2. Or, you can create a .env file locally (but don’t commit it to Git) and add the variables there. Then, use python-dotenv to load them in your app.py (you’ll need to install it: pip install python-dotenv).

Step 4: Run the Application

  1. Start the Flask development server:

     python backend/app.py

  2. Access the application in your browser at http://127.0.0.1:5001/.

Troubleshooting

Contributing

If you’d like to contribute to this project, please feel free to submit pull requests or open issues on the GitHub repository.

License

This project is licensed under the MIT License.

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