Show HN: I accidentally built "SQLite for AI memory" (Memvid) (github.com)

Memvid, a newly developed single-file memory layer for AI agents, has been introduced as a portable solution that enables instant retrieval and long-term memory without requiring complex databases. Unlike traditional retrieval-augmented generation (RAG) pipelines, Memvid allows for fast data access directly from a compact file, making it a model-agnostic and infrastructure-free memory layer. The system organizes memory through a unique structure that resembles video encoding, featuring "Smart Frames"—immutable units that combine content with timestamps and metadata. This design facilitates efficient memory management, allowing AI agents to efficiently append, compress, and inspect their historical knowledge. The significance of Memvid lies in its versatility and ease of integration across various real-world applications, such as customer support systems, enterprise knowledge bases, and even complex medical or legal AI agents. Its features, including fast memory access, timeline debugging, and the ability to create self-contained, shareable memory capsules, set it apart as an accessible solution for developers in the AI/ML community. With support in multiple programming languages and a focus on offline functionality, Memvid is poised to become an essential tool for building long-running AI agents and improving workflow automation.