Screenpipe
ScreenPipe is an open-source application and library designed for continuous screen and microphone capture. It provides a robust framework for developers, businesses, and individual users to craft powerful AI workflows using screen recordings, optical character recognition (OCR), audio input, and transcriptions.
Built with Rust for cross-platform compatibility (Windows, macOS, and Linux), ScreenPipe prioritizes versatility and security, empowering users to maintain data ownership while integrating personalized AI tools.
Features
- 24/7 Media Capture: Continuously captures screen and audio data, storing it locally.
- Personalized AI Integration: Enables AI models to leverage your captured data.
- Open Source and Secure: Your data remains private, giving you full control over its storage and processing.
- Cross-Platform Compatibility: Functions seamlessly across Windows, macOS, and Linux operating systems.
- Multi-Device Support: Supports multiple monitors and audio devices for comprehensive capture.
- Plugin & Pipe Extensibility: Expand functionality with plugins (pipes) written in TypeScript, running within a Deno runtime.
Use Cases
- Meeting Management: Record and transcribe meetings automatically. Extract key discussion points, action items, and decisions for easy review and follow-up. This works with any meeting software, including WhatsApp, Zoom, and Google Meet, without sending your data to the cloud.
- Automated Content Creation: Generate reports, articles, or social media updates based on captured screen activity and audio. Imagine creating a weekly report summarizing your project progress by simply recording your screen as you work.
- Personal Knowledge Base: Build a searchable archive of your digital interactions. Quickly locate information from past presentations, webinars, or online courses.
- Context-Aware Assistants: Develop AI assistants that react to your current digital context. For example, an assistant could automatically provide relevant documentation or code snippets based on the application you’re currently using.
- Automated Data Entry: Streamline data entry into CRM systems or other databases. ScreenPipe can capture information displayed on your screen and automatically populate the required fields, saving time and reducing errors.
How ScreenPipe Works
ScreenPipe captures screenshots and audio, performs OCR and speech-to-text conversion, and stores this data locally in a SQLite database and as MP4 files. You can then access and query this data through an API, allowing you to pipe it into large language models (LLMs) for various applications.
Pros
- Data Privacy: Maintains local data storage by default, ensuring privacy.
- Open Source: Free to use, modify, and distribute.
- Cross-Platform: Works across various operating systems.
- Extensible: Customizable through plugins and pipes for tailored functionality.
- Continuous Capture: Provides 24/7 recording capabilities.
Cons
- Resource Intensive: Continuous capture can consume significant storage space and processing power.
- Technical Expertise: Building from source or using the CLI requires some technical skills.
- Windows Support: Windows support is still experimental.
- Limited Encryption: Encryption options are currently under development.
Installation Options
1. CLI Installation (for technical users):
- Clone the repository
- Install dependencies (Rust, Cargo, etc.)
- Build and run the project
2. Desktop App:
- Paid version: Available for download with priority support and exclusive features
- Free version: Open-source, requires building from source or contributing to the repository
3. Manual Build:
- For users wanting full control, build from the repository (requires Rust and other dependencies)
Related Resources
FAQs
Q: How can I customize capture settings?
A: You can adjust frame rates and resolution within the configuration. Lower values will reduce storage and energy consumption. Improved user-friendliness for these settings is planned for future updates.
Q: What about data privacy when using external LLMs?
A: If you use an external LLM like OpenAI, some data may be transmitted to their servers. For complete privacy, use local LLMs. Enhanced security through encryption is also in development.