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OpenTranscribe v0.1.0 - First Official Release

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@davidamacey davidamacey released this 06 Nov 05:05
· 367 commits to master since this release
v0.1.0
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OpenTranscribe v0.1.0 - First Official Release

Release Date: November 5, 2025
License: GNU Affero General Public License v3.0 (AGPL-3.0)

Overview

We're thrilled to announce the first official release of OpenTranscribe! After 6 months of intensive development starting in May 2025, what began as a weekend experiment has evolved into a production-ready, fully-featured AI transcription platform.

OpenTranscribe is a powerful, self-hosted AI-powered transcription and media analysis platform that combines state-of-the-art AI models with a modern web interface to provide high-accuracy transcription, speaker identification, AI summarization, and advanced search capabilities.

Why AGPL-3.0?

We've chosen the GNU Affero General Public License v3.0 to:

  • Protect open source - Ensure the code remains open and accessible to everyone
  • Prevent proprietary forks - Require that modifications, especially network services, remain open
  • Ensure transparency - Network users have the right to access the source code
  • Build community - Foster collaboration and shared improvements

Key Highlights

🎧 Professional-Grade Transcription

  • 70x realtime speed on GPU with large-v2 model
  • Word-level timestamps using WAV2VEC2 alignment
  • 50+ languages supported with automatic translation
  • Universal format support - Audio and video files up to 4GB

👥 Advanced Speaker Intelligence

  • Automatic speaker diarization using PyAnnote.audio
  • Cross-video speaker recognition with voice fingerprinting
  • AI-powered speaker suggestions using LLM context analysis
  • Global speaker profiles that persist across all recordings
  • Speaker analytics with talk time, pace, and interaction patterns

🤖 AI-Powered Insights

  • LLM integration - Support for OpenAI, Claude, vLLM, Ollama, OpenRouter, and custom providers
  • BLUF format summaries - Bottom Line Up Front structured analysis
  • Custom AI prompts - Unlimited prompts with flexible JSON schemas
  • Intelligent sectioning - Handles transcripts of any length automatically
  • Local or cloud processing - Privacy-first local models or powerful cloud AI

🔍 Powerful Search & Discovery

  • Hybrid search - Keyword + semantic search with OpenSearch 3.3.1
  • 9.5x faster vector search - Significantly improved performance
  • 25% faster queries with 75% lower p90 latency
  • Advanced filtering - Search by speaker, tags, collections, date, duration
  • Interactive navigation - Click-to-seek on transcripts and waveforms

⚡ Enterprise Performance

  • Multi-GPU scaling - Optional parallel processing (4+ workers per GPU)
  • Specialized work queues - GPU, CPU, Download, NLP, and Utility queues
  • Non-blocking architecture - Parallel processing saves 45-75s per 3-hour file
  • Model caching - Efficient ~2.6GB cache with automatic persistence
  • Complete offline support - Full airgapped deployment capability

Installation

Quick Install (Recommended)

curl -fsSL https://raw.githubusercontent.com/davidamacey/OpenTranscribe/master/setup-opentranscribe.sh | bash
cd opentranscribe
./opentranscribe.sh start

Access at: http://localhost:5173

Docker Hub Images

Pre-built multi-platform images (AMD64, ARM64):

  • davidamacey/opentranscribe-backend:v0.1.0
  • davidamacey/opentranscribe-frontend:v0.1.0

From Source

git clone https://github.com/davidamacey/OpenTranscribe.git
cd OpenTranscribe
git checkout v0.1.0
cp .env.example .env
# Edit .env with your settings
./opentr.sh start dev

What's Included

Core Features

✅ Transcription - WhisperX with faster-whisper backend
✅ Speaker Diarization - PyAnnote.audio integration with auto-labeling and profile generation
✅ Media File Upload - Direct upload of audio/video files up to 4GB with drag-and-drop
✅ Video File Size Detection - Client-side audio extraction option for large video files
✅ YouTube Support - Direct URL and playlist processing for batch transcription
✅ Browser Microphone Recording - Built-in recording (localhost or HTTPS) with background operation
✅ AI-Powered Summaries - Multi-provider LLM integration with customizable formats
✅ AI Topic Generation - Automatic tag and collection suggestions from transcript content
✅ Timestamp Comments - User annotations anchored to specific video moments
✅ Search Engine - OpenSearch 3.3.1 with hybrid keyword and vector search
✅ Collections - Organize media into themed groups with AI suggestions
✅ Analytics - Speaker metrics and interaction analysis
✅ Waveform Visualization - Interactive audio timeline
✅ PWA Support - Installable progressive web app
✅ Dark/Light Mode - Full theme support

Infrastructure

✅ Docker Compose - Multi-environment orchestration
✅ PostgreSQL - Relational database with JSONB
✅ MinIO - S3-compatible object storage
✅ Redis - Message broker and caching
✅ Celery - Distributed task processing
✅ NGINX - Production web server
✅ Flower - Task monitoring dashboard

Security

✅ Non-root containers - Principle of least privilege
✅ RBAC - Role-based access control
✅ Encrypted secrets - Secure API key storage
✅ Security scanning - Trivy and Grype integration
✅ Session management - JWT-based authentication

System Requirements

Minimum

  • CPU: 4 cores
  • RAM: 8GB
  • Storage: 50GB (including ~3GB for AI models)
  • GPU: Optional (CPU-only mode available)

Recommended

  • CPU: 8+ cores
  • RAM: 16GB+
  • Storage: 100GB+ SSD
  • GPU: NVIDIA GPU with 8GB+ VRAM (RTX 3070 or better)

Supported Platforms

  • OS: Linux, macOS (including Apple Silicon), Windows (via WSL2)
  • Architectures: AMD64, ARM64
  • GPUs: NVIDIA CUDA, Apple MPS (Metal)

Performance Benchmarks

Metric Performance
Transcription Speed (GPU) 70x realtime
Vector Search Improvement 9.5x faster
Query Performance 25% faster, 75% lower p90 latency
Multi-GPU Throughput 4 videos simultaneously (4 workers)
Model Cache Size ~2.6GB total

Documentation

📚 Complete Documentation: https://docs.opentranscribe.app

Key resources:

Roadmap to v1.0.0

We're committed to delivering a stable, production-ready v1.0.0 release. While we'll strive for backwards compatibility, we cannot guarantee it until v1.0.0. Breaking changes will be clearly announced.

Planned features for future releases:

  • Real-time transcription for live streaming
  • Enhanced speaker analytics and visualization
  • Better speaker diarization models
  • Google-style text search
  • LLM powered RAG Chat with transcript text
  • Other refinements along the way!

Known Issues

No critical issues at release time. See GitHub Issues for community-reported items.

Contributing

We welcome contributions from the community! See our Contributing Guide for details.

Ways to contribute:

  • 🐛 Report bugs and issues
  • 💡 Suggest new features
  • 🔧 Submit pull requests
  • 📚 Improve documentation
  • 🌍 Translate the interface
  • ⭐ Star the repository

Support & Community

Acknowledgments

OpenTranscribe builds upon amazing open-source projects:

  • OpenAI Whisper - Foundation speech recognition model
  • WhisperX - Enhanced alignment and diarization
  • PyAnnote.audio - Speaker diarization toolkit
  • FastAPI - Modern Python web framework
  • Svelte - Reactive frontend framework
  • PostgreSQL - Reliable database system
  • OpenSearch - Search and analytics engine
  • Docker - Containerization platform

Special thanks to the AI community and all contributors who helped make this release possible!

License

OpenTranscribe is licensed under the GNU Affero General Public License v3.0 (AGPL-3.0).

See LICENSE for full details.

Built with ❤️ by the OpenTranscribe community

OpenTranscribe demonstrates the power of AI-assisted development while maintaining full local control over your data and processing.

Download: v0.1.0 Release
Docker: Backend | Frontend
Docs: docs.opentranscribe.app

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