🎙️ Enstruct

Transcribe. Structure. Free.

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🚀 Overview

Enstruct is a professional, production-ready, open-source audio toolkit that wraps OpenAI's Whisper model (powered by the high-performance faster-whisper engine). Designed to run fully locally or on free cloud instances, Enstruct offers a free, private alternative to expensive paid services like Otter.ai, Transkriptor, and AssemblyAI.

Key Features

• ⚡ Ultra-Fast Transcription: Powered by faster-whisper utilizing CTranslate2 for up to 4x speedups over standard Whisper.
• 🌐 Any-to-English Translation: Translate speech from dozens of languages directly to fluent English transcripts.
• 📝 Multi-Format Export: Generates professional SRT and VTT subtitle files, alongside raw TXT transcripts.
• 📂 Batch Folder Processing: Automatically transcribes entire folders of audio/video files with beautiful progress indicators.
• 🎬 YouTube Integration: Transcribe and translate YouTube video content directly via url input.
• ☁️ Google Drive Storage: Seamless automatic drive mounting and file saving inside Google Colab.
• 🎙️ Flexible Interfaces: Supports a robust Command Line Interface (CLI) and a sleek, interactive Gradio Web UI with activity history.
• 🧠 Auto-Hardware Detection: Dynamically utilizes CUDA if an NVIDIA GPU is available, falling back safely to highly-optimized CPU execution.

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📊 Comparison: Enstruct vs Paid Services

Feature	Enstruct (Ours)	Otter.ai	Transkriptor	AssemblyAI
Cost	🆓 100% Free	Paid Subscription	Paid / Minute	Paid / Minute
Hosting	💻 Fully Local / Self-Hosted	Cloud-only	Cloud-only	API-only
Privacy	🔒 Zero data shared, fully private	Processed on third-party	Processed on third-party	Processed on third-party
Batch Support	✅ Built-in CLI & API	Limited	Limited	Paid API-only
Translation	✅ Any-to-English	Limited	Paid	Paid
Open Source	🔓 Yes (AGPL v3 License)	No	No	No

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🛠️ Installation

pip install enstruct

Note: Enstruct requires ffmpeg to process audio/video container formats.

• Ubuntu/Debian: sudo apt install ffmpeg
• macOS: brew install ffmpeg
• Windows: choco install ffmpeg

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💻 Usage

ENstruct is designed to work seamlessly both as a command-line tool and as a Python library.

1. Command Line Interface (CLI)

# Transcribe an audio file into default SRT format
enstruct transcribe voice_note.mp3

# Transcribe with target language and VTT format
enstruct transcribe audio.wav --language es --format vtt --output subtitle.vtt

# Translate a Spanish audio file directly to English
enstruct translate foreign_audio.mp4 --format txt --output english_transcript.txt

# Batch process an entire directory of mixed audio/video files
enstruct batch /path/to/audios --output /path/to/subtitles --format srt

# Detect spoken language of an audio file
enstruct detect-language conversation.wav

2. Python API

Standard Transcription

from enstruct.core.transcriber import EnstructTranscriber

# Initialize the transcriber (automatically uses GPU if available)
transcriber = EnstructTranscriber(model_size="large-v3", device="auto")

# Transcribe audio file
result = transcriber.transcribe("interview.m4a")

print(f"Detected Language: {result['language']}")
print(f"Transcript: {result['text']}")

# Generate subtitle formats using SubtitleGenerator
from enstruct.tools.subtitle import SubtitleGenerator

generator = SubtitleGenerator()
generator.generate(result["segments"], "interview.srt", format="srt")

YouTube Downloader

from enstruct.tools.youtube import YouTubeDownloader

downloader = YouTubeDownloader()
# Download best-quality audio from YouTube URL and save as MP3
audio_file = downloader.download_audio("https://www.youtube.com/watch?v=dQw4w9WgXcQ")
print(f"Downloaded audio to: {audio_file}")

Google Drive Manager (Google Colab only)

from enstruct.integrations.drive import DriveManager

drive_manager = DriveManager()
# Mount Google Drive
drive_manager.mount_drive()
# Save transcript directly to Drive: /content/drive/MyDrive/Enstruct/outputs
drive_manager.save_file("transcript.srt", "Subtitles content...")

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🌐 Gradio Web Interface

Enstruct comes with an interactive, beautiful browser-based Web UI featuring dynamic source input switching and session logs history.

To start the Web UI locally:

python -m interfaces.web.app

Then, open http://localhost:7860 in your browser. You can:

1. Choose Audio Source: Select between "Upload / Microphone", "Google Drive" (Colab path), or "YouTube URL".
2. Configure options: Choose model sizes (tiny to large-v3), output formats (SRT, VTT, TXT), and task (Transcribe or Translate).
3. Activity Logs & History: Track session logs inside the "History" tab, refresh listings, or clear all history logs.
4. Execute & Download: Run transcription, preview results, and download output files immediately.

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💼 Commercial Use

Enstruct is free under AGPL v3 for open-source and personal use.

If you want to use Enstruct in a closed-source or commercial product, a commercial license is required. See COMMERCIAL_LICENSE.md for pricing and details.

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🤝 Contributing

We welcome contributions from the open-source community!

1. Fork the Repository.
2. Create your Feature Branch (git checkout -b feature/AmazingFeature).
3. Set up development environment and run tests:

   pip install pytest
   pytest

4. Commit your Changes (git commit -m 'Add some AmazingFeature').
5. Push to the Branch (git push origin feature/AmazingFeature).
6. Open a Pull Request.

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📄 License

Distributed under the AGPL v3 License. See LICENSE for more information. Commercial licensing and bespoke features are also available.