LongTermMemory

Abstract base class for long-term memory implementations.

This class provides a time-series memory management system that persists information beyond individual conversation sessions. Long-term memory enables agents to:

• Remember user preferences, habits, and personal information across sessions

• Learn from past interactions and improve over time

• Maintain context for long-running tasks or projects

• Build personalized experiences based on historical data

This class defines the core memory API for framework-level integration:

• #record(List) - Record messages to memory (called by framework)

• #retrieve(Msg) - Retrieve relevant memories (called by framework)

For agent-controlled memory operations (AGENT_CONTROL mode), use LongTermMemoryTools which provides tool functions that adapt these core methods for agent use.

All methods are asynchronous and return Reactor Mono types for non-blocking integration with the agent framework.

Usage Example:

`// Create long-term memory instance
LongTermMemoryBase longTermMemory = Mem0LongTermMemory.builder()
.agentName("Assistant")
.userName("user_123")
.apiBaseUrl("http://localhost:8000")
.build();

// Use in ReActAgent
ReActAgent agent = ReActAgent.builder()
.name("Assistant")
.model(model)
.longTermMemory(longTermMemory)
.longTermMemoryMode(LongTermMemoryMode.BOTH)
.build();
`