First commit of local Closed Caption App

INSTALL_WHISPER.md

@@ -0,0 +1,141 @@
+# Installing Whisper for Local Transcription
+
+This guide explains how to install OpenAI's Whisper for local speech-to-text transcription.
+
+## Prerequisites
+
+- Python 3.8 or newer
+- pip (Python package manager)
+- ffmpeg
+
+## Installation Steps
+
+### 1. Install Python Dependencies
+
+```bash
+# Install Whisper
+pip install openai-whisper
+
+# Or install with specific version
+pip install openai-whisper==20230918
+```
+
+### 2. Install ffmpeg
+
+#### Ubuntu/Debian:
+```bash
+sudo apt update
+sudo apt install ffmpeg
+```
+
+#### macOS (using Homebrew):
+```bash
+brew install ffmpeg
+```
+
+#### Windows:
+1. Download ffmpeg from https://ffmpeg.org/download.html
+2. Extract the archive
+3. Add the bin folder to your PATH
+
+### 3. Verify Installation
+
+```bash
+# Test Whisper installation
+whisper --help
+
+# Test with an audio file
+whisper audio.mp3 --model base
+```
+
+## Available Models
+
+Whisper offers several models with different speed/accuracy tradeoffs:
+
+| Model  | Parameters | Relative Speed | Required VRAM |
+|--------|------------|----------------|---------------|
+| tiny   | 39 M       | ~32x           | ~1 GB         |
+| base   | 74 M       | ~16x           | ~1 GB         |
+| small  | 244 M      | ~6x            | ~2 GB         |
+| medium | 769 M      | ~2x            | ~5 GB         |
+| large  | 1550 M     | 1x             | ~10 GB        |
+
+## Configuration
+
+Set your preferred model in the `.env` file:
+
+```env
+WHISPER_MODEL=base  # Options: tiny, base, small, medium, large
+```
+
+## GPU Acceleration Setup
+
+### NVIDIA GPUs (CUDA)
+```bash
+# Install PyTorch with CUDA support
+pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
+
+# Verify CUDA is available
+python -c "import torch; print(f'CUDA available: {torch.cuda.is_available()}')"
+```
+
+### AMD GPUs (ROCm) - Linux Only
+```bash
+# Install ROCm (Ubuntu/Debian)
+wget -q -O - https://repo.radeon.com/rocm/rocm.gpg.key | sudo apt-key add -
+echo 'deb [arch=amd64] https://repo.radeon.com/rocm/apt/debian/ ubuntu main' | sudo tee /etc/apt/sources.list.d/rocm.list
+sudo apt update
+sudo apt install rocm-dkms
+
+# Install PyTorch with ROCm support
+pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm5.4.2
+
+# Add user to render/video groups
+sudo usermod -a -G render,video $USER
+# Logout and login for group changes to take effect
+```
+
+### Intel GPUs (OpenVINO)
+```bash
+# Install OpenVINO toolkit
+pip install openvino-dev[pytorch]
+
+# For Arc GPUs, you may need the compute runtime
+# Ubuntu/Debian:
+wget -qO - https://repositories.intel.com/graphics/intel-graphics.key | sudo apt-key add -
+sudo apt-add-repository 'deb [arch=amd64] https://repositories.intel.com/graphics/ubuntu focal main'
+sudo apt update
+sudo apt install intel-opencl-icd intel-level-zero-gpu level-zero
+
+# Note: You may need a Whisper fork with OpenVINO support
+pip install git+https://github.com/openvinotoolkit/whisper.git
+```
+
+## Troubleshooting
+
+### Issue: "whisper: command not found"
+- Make sure Python's Scripts directory is in your PATH
+- On Windows: `C:\Users\[Username]\AppData\Local\Programs\Python\Python3X\Scripts`
+- On macOS/Linux: `~/.local/bin`
+
+### Issue: GPU not detected
+- Use the "Detect GPU" button in the app's settings page
+- For NVIDIA: Ensure `nvidia-smi` command works
+- For AMD: Ensure `rocm-smi` command works
+- For Intel: Check `lspci | grep -i intel` shows your GPU
+
+### Issue: CUDA out of memory
+- Try using a smaller Whisper model (tiny or base)
+- Reduce batch size or use CPU for very long audio
+
+### Issue: Audio Format Not Supported
+Whisper works best with WAV, MP3, and M4A files. The app automatically converts audio to a compatible format.
+
+## Alternative: Docker Installation
+
+You can also run Whisper in a Docker container:
+
+```bash
+docker pull openai/whisper
+docker run -it -v $(pwd):/app openai/whisper audio.mp3 --model base
+```