2023 MemGPTTowardsLLMsAsOperatingSys

• (Packer et al., 2023) ⇒ Charles Packer, Vivian Fang, Shishir G. Patil, Kevin Lin, Sarah Wooders, and Joseph E. Gonzalez. (2023). “MemGPT: Towards LLMs As Operating Systems.” doi:10.48550/arXiv.2310.08560

Subject Headings: MemGPT, Conversational AI System with Memory.

Cited By

• http://scholar.google.com/scholar?q=%222023%22+MemGPT%3A+Towards+LLMs+As+Operating+Systems

2023

• https://github.com/cpacker/MemGPT
  • Memory-GPT (or MemGPT in short) is a system that intelligently manages different memory tiers in LLMs in order to effectively provide extended context within the LLM's limited context window. For example, MemGPT knows when to push critical information to a vector database and when to retrieve it later in the chat, enabling perpetual conversations. Learn more about MemGPT in our paper.

Quotes

Abstract

Large language models (LLMs) have revolutionized AI, but are constrained by limited context windows, hindering their utility in tasks like extended conversations and document analysis. To enable using context beyond limited context windows, we propose virtual context management, a technique drawing inspiration from hierarchical memory systems in traditional operating systems that provide the appearance of large memory resources through data movement between fast and slow memory. Using this technique, we introduce MemGPT (Memory-GPT), a system that intelligently manages different memory tiers in order to effectively provide extended context within the LLM's limited context window, and utilizes interrupts to manage control flow between itself and the user. We evaluate our OS-inspired design in two domains where the limited context windows of modern LLMs severely handicaps their performance: document analysis, where MemGPT is able to analyze large documents that far exceed the underlying LLM's context window, and multi-session chat, where MemGPT can create conversational agents that remember, reflect, and evolve dynamically through long-term interactions with their users. We release MemGPT code and data for our experiments at this URL.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2023 MemGPTTowardsLLMsAsOperatingSys	Kevin Lin Joseph E. Gonzalez Shishir G. Patil Charles Packer Vivian Fang Sarah Wooders							10.48550/arXiv.2310.08560		2023

[[title::MemGPT: Towards LLMs As Operating Systems|]]