Memoryblock is an AI memory layer for seamless context sharing between humans and AI systems. It provides an intuitive way to save, organize, and reference your important context in AI conversations.
The memoryblock project aims to solve the critical challenge of context management in AI interactions. By creating a dedicated system for storing and retrieving personal context, we enable more effective and personalized AI experiences without repeatedly explaining the same information.
Memory blocks are discrete pieces of information that you want AI systems to reference. They can contain:
- Personal context (about yourself, your preferences, etc.)
- Project details and requirements
- Writing style examples
- Technical documentation
- Any information you find yourself repeatedly sharing with AI
Our innovative :: syntax allows you to reference your stored information directly in prompts:
I need you to draft an email using ::my-style and considering ::project-context
This streamlines the process of incorporating your stored context into AI conversations.
The memoryblock ecosystem consists of several components that work together to provide a seamless experience:
- SDK: Core implementation for developers to integrate with memoryblock
- Client Libraries: Language-specific implementations for different platforms
- LangChain Integration: Components for using memoryblock with LangChain
- Browser Extension: Save web content as memory blocks
- VSCode Extension: Developer-focused tools for code snippet management
We believe in the power of open source to drive innovation. All our public repositories are licensed under the MIT License to encourage community contributions and widespread adoption. We welcome contributions from developers who share our vision for improved AI context management.
For developers interested in contributing or integrating with memoryblock, each repository contains detailed documentation to help you get started. See individual repositories for specific setup instructions and examples.