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Video Transcribe and Analyze

This project transcribes video content using Hugging Face's Transformers library (with Whisper model) and analyzes the transcript for politically incorrect or sensitive information using various LLMs (Anthropic's Claude, Google's Gemini, or OpenAI's GPT).

Features

  • Transcribe video files using Hugging Face's Transformers (Whisper model)
  • Analyze transcripts for sensitive content
  • Write analysis results to a text file
  • Easy-to-use command-line interface

Installation

  1. Clone the repository:

    git clone https://github.com/yourusername/video-transcribe-analyze.git
cd video-transcribe-analyze

  2. Create and activate a virtual environment:

    • For Windows:

      python -m venv venv
venv\Scripts\activate

    • For macOS and Linux:

      python3 -m venv venv
source venv/bin/activate

  3. Install the required packages:

    pip install -r requirements.txt

    If you encounter any issues, try upgrading pip first:

    pip install --upgrade pip

    Then retry the installation.

  4. Set up your API keys:

    • Create a copy of the .env.example file and name it .env:
      • For Windows: 
        copy .env.example .env
      • For macOS and Linux: 
        cp .env.example .env
    • Open the .env file and replace your_api_key_here with your actual Anthropic API key: 
      ANTHROPIC_API_KEY=your_actual_api_key
GOOGLE_API_KEY=your_google_api_key
OPENAI_API_KEY=your_openai_api_key

Usage

Run the script with a video file as an argument:

  • For Windows:

    python src\video_transcribe_analyze\main.py path\to\your\video.mp4 --llm=anthropic

  • For macOS and Linux:

    python src/video_transcribe_analyze/main.py /path/to/your/video.mp4 --llm=gemini

Available LLM options: anthropic, gemini, openai

The script will create a text file in the current directory with the transcript and analysis results. The filename will be [original_video_name]_analysis.txt.

Troubleshooting

If you encounter issues with package installation or compatibility:

  1. Ensure you're using a recent version of Python (3.8 or later is recommended).

  2. Try upgrading pip before installing the requirements:

    pip install --upgrade pip

  3. Ensure you have FFmpeg installed and added to your system PATH.

  4. If you're using a GPU and encounter CUDA-related issues, ensure that your CUDA toolkit version is compatible with the installed PyTorch version.

Credit

Project idea from Divide-By-0 and MIT SOUL