GitHub

Screenpipe Project Description

What is the project about?

Screenpipe is an open-source platform that continuously records a user's screen and microphone (24/7) locally, indexes this data, and provides an API for developers to build AI-powered applications. It's described as an "AI app store powered by 24/7 desktop history."

What problem does it solve?

It provides AI applications with rich, contextual data (the user's screen and audio recordings) to enable more personalized and powerful AI experiences. It solves the problem of AI models lacking sufficient context by providing continuous, real-time access to the user's digital environment. It also allows developers to easily monetize their AI apps.

What are the features of the project?

  • 24/7 Local Recording: Continuously records screen and microphone input, storing data locally.
  • Indexing and API: Indexes the recorded data and makes it accessible through an API.
  • Plugin System ("Pipes"): Allows developers to create desktop applications in a sandboxed Next.js environment within the Screenpipe Rust code.
  • App Store & Monetization: Provides a platform for developers to publish and monetize their "pipes" (plugins).
  • Native OCR: Includes native OCR capabilities for Apple and Windows.
  • Developer Friendly: Easy to install and use, with tools for creating and publishing plugins.

What are the technologies used in the project?

  • Rust: Core codebase.
  • Next.js: For building plugins (pipes).
  • Tauri/Electron: Community templates for building desktop apps.
  • Bun: Used for the plugin creation and publishing commands.
  • API: Provides access to the indexed screen and audio data.

What are the benefits of the project?

  • Rich Context for AI: Provides AI applications with a wealth of contextual data.
  • Local Processing: Ensures user privacy by processing data locally.
  • Developer Empowerment: Enables developers to build and monetize context-aware AI applications.
  • Passive Income for Developers: Stripe integration for easy monetization of plugins.
  • Open Source: Fosters community contributions and transparency.

What are the use cases of the project?

  • Personalized AI Assistants: Assistants that understand the user's current context and workflow.
  • Automated Tasks: Automating tasks based on screen content and user activity. Examples include financial automations and file organization.
  • Contextual Search: Searching through past screen activity.
  • Productivity Tools: Tools that analyze screen time and provide insights.
  • Accessibility Tools: Tools that leverage screen and audio data to assist users with disabilities.
  • Agents: Reddit and LinkedIn agents are mentioned as examples.
screenpipe screenshot