> ## Documentation Index
> Fetch the complete documentation index at: https://java.agentscope.io/llms.txt
> Use this file to discover all available pages before exploring further.

# Overview

`LongTermMemory` is the AgentScope interface for persisting user preferences, facts, and key takeaways across multiple turns and sessions. The `agentscope-extensions-*` repository ships ready-to-use implementations for the major memory stores:

| Extension                                    | Backend                                         | Best for                                                                           |
| -------------------------------------------- | ----------------------------------------------- | ---------------------------------------------------------------------------------- |
| [Mem0](/v2/en/integration/memory/mem0)       | [Mem0](https://mem0.ai/) Platform / self-hosted | General-purpose semantic memory with multi-tenant isolation and metadata filtering |
| [Bailian](/v2/en/integration/memory/bailian) | Alibaba Cloud Bailian memory service            | Cloud-managed memory with rerank / judge / rewrite features                        |
| [ReMe](/v2/en/integration/memory/reme)       | Self-hosted ReMe service                        | Workspace-level memory with trajectory summarization                               |

All three implement the same `io.agentscope.core.memory.LongTermMemory` interface and are wired into an Agent the same way:

```java theme={null}
ReActAgent agent = ReActAgent.builder()
    .name("Assistant")
    .model(model)
    .longTermMemory(memory)                       // any of the three implementations
    .longTermMemoryMode(LongTermMemoryMode.BOTH)  // record AND retrieve
    .build();
```

## Choosing an implementation

* **Want a single `docker run` to start locally** → Mem0 or ReMe
* **Already on Alibaba Cloud Bailian** → Bailian
* **Need metadata filtering (slice memory by business dimension)** → Mem0
* **Care about end-to-end conversation trajectory summarization** → ReMe

The implementations only differ in initialization parameters and filter semantics; they are transparent to the Agent itself. See each subpage for details.