Transcription with Whisper

Cloud Whisper (Default)

Tip: Cloud Whisper uses the Groq API, which offers a generous free tier. A 10-minute video typically costs well under a cent.

Uses Groq Cloud Whisper API for fast transcription with Whisper. Requires a Groq API key in .env.

$
python -m summarizer --source "URL"

Cloud Whisper is the default in both CLI and Docker.

Local Whisper

Runs transcription with Whisper on your machine instead of using Groq Cloud Whisper. This removes the Groq API requirement, but CPU-only runs are much slower.

$
# Add Local Whisper support
$
pip install -e .[whisper]
$
$
# Optional: install CUDA-enabled PyTorch for GPU acceleration
$
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu124
$
$
# Use it
$
python -m summarizer --source "URL" --force-download --transcription "Local Whisper" --whisper-model "small"

If you only need CPU transcription with Whisper, pip install -e .[whisper] is enough. GPU detection is automatic when PyTorch can see a CUDA device.

Model Sizes

Playback Speed

Use the speed setting to change playback rate before Whisper transcription. Groq Whisper is priced by audio duration, so a 2× speed-up roughly halves the API cost. Higher speeds may reduce accuracy.

$
# Moderate speed-up
$
python -m summarizer --source "URL" --speed 2.0
$
$
# Aggressive speed-up (CLI accepts any positive value)
$
python -m summarizer --source "URL" --speed 5.0

Set the default in summarizer.yaml:

1
defaults:
2
  speed: 1.0

YouTube captions and speed

YouTube captions are plain text and cannot be sped up. When speed is not 1.0, the app skips the caption path and downloads audio instead so the speed setting is honored. You do not need --force-download for this — a non-default speed alone triggers the audio download path.

Docker Note

The Docker image does not include Local Whisper or GPU-oriented PyTorch. It targets lightweight VPS deployments where GPUs are usually unavailable. In Docker, Cloud Whisper is the practical default. Use Local Whisper on the host machine if you have the hardware.