ReCALL-Lite is a lightweight memory system that enables AI agents and language models to store, retrieve, and summarize long-term contextual information. It allows AI systems to maintain persistent knowledge across conversations without retraining the underlying model.
Modern language models do not naturally remember past interactions. ReCALL Lite introduces a persistent memory layer that allows AI agents to store important information, retrieve relevant context during conversations, and continuously build knowledge over time.
This enables AI systems to behave more like adaptive assistants rather than stateless chatbots.
Persistent Memory
Stores user interactions and important information as structured memory nodes.
Semantic Memory Graph
Memories are organized into a graph structure that captures relationships between information.
Automatic Memory Summarization
Older memories are summarized into compact representations to maintain scalability.
Hybrid Memory Retrieval
Combines summarized knowledge and detailed memory nodes to retrieve relevant context.
Developer-Friendly API
Easily integrate memory into AI systems using a simple Python interface.
FOR MORE INFORMATION: https://pypi.org/project/lite-recall/