mediascribe 0.2.1

TUI-first tool for transcribing, translating, and analyzing audio/video media

mediascribe

TUI-first tool for transcribing, translating, and analyzing audio/video media.

mediascribe takes audio or video files and produces transcriptions, translations, subtitles, and AI-powered analysis. It supports local (faster-whisper) and cloud (OpenAI) transcription, speaker diarization, multi-language translation, and customizable prompt profiles.

Install

From PyPI (recommended)

pipx install mediascribe          # isolated install
pip install mediascribe            # or into current environment

With optional extras

pip install mediascribe[tui]       # Textual TUI interface
pip install mediascribe[diarize]   # speaker diarization (pyannote.audio)
pip install mediascribe[all]       # everything

From Homebrew (after first PyPI release)

brew tap shawnpetros/mediascribe
brew install mediascribe

Note: This requires the tap repo to exist — see Publishing > Homebrew for setup instructions.

From source

git clone https://github.com/shawnpetros/mediascribe.git
cd mediascribe
make install                       # editable install with dev tools

Requirements

• Python 3.12+
• FFmpeg 6+ — install via brew install ffmpeg or apt install ffmpeg
• OpenAI API key — for translation and API transcription mode

Quick Start

# Transcribe a video (auto-detects language)
mediascribe transcribe video.mp4

# Transcribe Japanese audio → English subtitles
mediascribe transcribe podcast.mp3 --lang ja --translate en

# Use the anime profile with multiple output formats
mediascribe transcribe anime.mkv --translate en --profile anime --formats srt,vtt

# Translate an existing SRT file
mediascribe translate subtitles.srt --target en --profile anime

# Batch process a folder
mediascribe batch ./recordings/ --translate en --formats srt,txt,json

# Enable speaker diarization and AI analysis
mediascribe transcribe meeting.mp4 --diarize --analyze --formats srt,txt,json

# Launch the interactive TUI
mediascribe tui

Configuration

# Show current settings
mediascribe config show

# Set your API key
mediascribe config set openai_api_key sk-...

# Initialize config directory with profile templates
mediascribe config init

# List available profiles
mediascribe config profiles

Configuration is loaded from (highest priority first):

1. CLI flags
2. Environment variables (MEDIASCRIBE_*)
3. .env file in working directory
4. ~/.config/mediascribe/config.toml
5. Built-in defaults

Profiles

Profiles are named config presets. Built-in profiles: general, anime, podcast, meeting.

Create custom profiles as TOML files in ~/.config/mediascribe/profiles/:

# ~/.config/mediascribe/profiles/lectures.toml
description = "University lecture transcription"

[transcription]
mode = "local"
model = "large-v3"

[translation]
target_language = "en"
enable_review = true
custom_instructions = """
Preserve technical terminology accurately.
Format mathematical expressions clearly.
"""

[output]
formats = ["srt", "txt", "json"]

Development

git clone https://github.com/shawnpetros/mediascribe.git
cd mediascribe
make install          # install editable + dev deps
make test             # run test suite (184 tests)
make lint             # run ruff linter
make format           # auto-format code
make typecheck        # run mypy
make check            # all of the above
make build            # build sdist + wheel
make help             # show all targets

Make Targets

Target	Description
make install	Install package in editable mode with dev extras
make install-all	Install with all optional extras (tui, diarize, dev)
make test	Run test suite
make test-cov	Run tests with coverage report
make lint	Run ruff linter
make format	Auto-format code with ruff
make typecheck	Run mypy type checker
make check	Run all checks (lint + format + types + tests)
make build	Build sdist and wheel
make build-check	Build and validate distribution with twine
make publish-test	Publish to TestPyPI
make publish	Publish to PyPI
make clean	Remove all build/cache artifacts
make version	Show current package version

Publishing

Fully automated (recommended)

The entire release pipeline is automated. To ship a new version:

# 1. Bump version in both files
#    - pyproject.toml:  version = "0.2.0"
#    - src/mediascribe/__init__.py:  __version__ = "0.2.0"
# 2. Commit and merge to main
git add -A && git commit -m "release: v0.2.0"
git push

What happens automatically on merge to main:

1. release.yml detects the version change in pyproject.toml, creates a v0.2.0 tag
2. publish.yml triggers on the new tag:
   • Runs full CI (tests, lint, typecheck)
   • Builds sdist + wheel
   • Smoke tests the built wheel (CLI loads, commands respond)
   • Publishes to PyPI via trusted publisher (OIDC)
   • Creates a GitHub Release with auto-generated notes
   • Updates the Homebrew tap formula with the new version + SHA256

One-time setup

PyPI: Configure trusted publisher in your PyPI project settings to trust the publish.yml workflow from your GitHub repo.

Homebrew tap:

1. Create a GitHub repo named shawnpetros/homebrew-mediascribe with a Formula/ directory
2. Add a repo secret HOMEBREW_TAP_TOKEN in the mediascribe repo — a personal access token with repo scope on the tap repo
3. Optionally set a repo variable HOMEBREW_TAP_REPO if the tap is at a different path (defaults to shawnpetros/homebrew-mediascribe)

After setup, users install via:

brew tap shawnpetros/mediascribe
brew install mediascribe

Manual publishing

make build-check     # build + validate
make publish-test    # upload to TestPyPI first
make publish         # upload to PyPI

Architecture

Input File(s)
    │
    ▼
[Detect] → file type, duration, codec
    │
    ▼
[Normalize] → 16kHz mono WAV
    │
    ▼
[Transcribe] → segments (overlap-chunked + validated + deduped)
    │
    ├──▶ [Diarize] → speaker labels (optional)
    │
    ▼
[Timing] → subtitle timing optimization
    │
    ▼
[Translate] → target language (optional, batched + context overlap)
    │
    ▼
[Review] → AI quality check (optional)
    │
    ▼
[Analyze] → summary, topics, action items (optional)
    │
    ▼
[Export] → SRT, VTT, TXT, JSON

See docs/SPEC.md for the full specification and docs/PROJECT.md for implementation status.

License

MIT