# ConversationBufferMemory

> **Class** in `langchain_classic`

📖 [View in docs](https://reference.langchain.com/python/langchain-classic/memory/buffer/ConversationBufferMemory)

A basic memory implementation that simply stores the conversation history.

This stores the entire conversation history in memory without any
additional processing.

Note that additional processing may be required in some situations when the
conversation history is too large to fit in the context window of the model.

## Signature

```python
ConversationBufferMemory()
```

## Extends

- `BaseChatMemory`

## Properties

- `human_prefix`
- `ai_prefix`
- `memory_key`
- `buffer`
- `buffer_as_str`
- `buffer_as_messages`
- `memory_variables`

## Methods

- [`abuffer()`](https://reference.langchain.com/python/langchain-classic/memory/buffer/ConversationBufferMemory/abuffer)
- [`abuffer_as_str()`](https://reference.langchain.com/python/langchain-classic/memory/buffer/ConversationBufferMemory/abuffer_as_str)
- [`abuffer_as_messages()`](https://reference.langchain.com/python/langchain-classic/memory/buffer/ConversationBufferMemory/abuffer_as_messages)
- [`load_memory_variables()`](https://reference.langchain.com/python/langchain-classic/memory/buffer/ConversationBufferMemory/load_memory_variables)
- [`aload_memory_variables()`](https://reference.langchain.com/python/langchain-classic/memory/buffer/ConversationBufferMemory/aload_memory_variables)

## ⚠️ Deprecated

Deprecated since version 0.3.1. Use langchain.agents.create_agent instead. Will be removed in version 2.0.0. For agents that need to remember prior interactions, use `create_agent` with checkpointing or the `Store` API. See https://docs.langchain.com/oss/python/langchain/short-term-memory and https://docs.langchain.com/oss/python/langchain/long-term-memory

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[View source on GitHub](https://github.com/langchain-ai/langchain/blob/185119f98e6286253a2326d7cf4f59592678023d/libs/langchain/langchain_classic/memory/buffer.py#L13)