MemoriPy is an open-source memory layer for AI agents that helps LLM-based systems retain context over time and respond more consistently.
Built for developers and agent systems
MemoriPy is designed for developers building assistants, autonomous agents, and more complex AI applications. It adds both short-term and long-term memory to an LLM workflow, so important facts and events can be stored and later recalled when they matter.
Key capabilities include:
- Short-term and long-term memory storage
- Saving important facts, events, and user context
- Retrieving only the most relevant memories for a specific query
Token efficiency through smarter retrieval
By searching memory intelligently and injecting only relevant context, MemoriPy can reduce unnecessary LLM calls and shrink prompt size. This helps keep conversations coherent while making infrastructure more cost-efficient and easier to scale.
Open-source and flexible to integrate
Because the project is open-source, it can be inspected, extended, and adapted to existing pipelines and stacks. MemoriPy can also serve as a foundation for custom memory layers, personal assistants, and internal enterprise AI systems.
