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

# Memory

The `Memory` class from `superagentx.memory` is designed to provide a persistent storage mechanism for storing and retrieving context,
data, and state during interactions with agents in a pipeline. `Memory` allows the system to “remember” information
across agent actions and queries, which is particularly useful for complex workflows or tasks that span multiple steps.

The `Memory` class is initialized with a configuration that defines how it interacts with the agent pipeline.
It can be used to persist important data, store intermediate results, or maintain context across different
stages of the agent’s execution.

### Memory config Parameters

| Attribute                     | Parameters     | Description                                                 |
| :---------------------------- | :------------- | :---------------------------------------------------------- |
| **LLM Client**                | `llm_client`   | Configuration for the LLM.                                  |
| **Vector Store** *(optional)* | `vector_store` | Configuration for the vector store. Default is `Chroma db`. |
| **DB Path** *(optional)*      | `db_path`      | Path to the history database. Default `Sqlite memory`.      |

### Parameters

| Attribute         | Parameters      | Description          |
| :---------------- | :-------------- | :------------------- |
| **Memory Config** | `memory_config` | Memory configuration |

```python theme={null}
from superagentx.memory import Memory

memory = Memory(memory_config={"llm_client": llm_client})
```