> ## Documentation Index
> Fetch the complete documentation index at: https://docs.mem0.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Python SDK Quickstart

> Install the Mem0 Python SDK, configure your environment, and store your first memory in under five minutes.

Get started with Mem0's Python SDK in under 5 minutes. This guide shows you how to install Mem0 and store your first memory.

## Prerequisites

* Python 3.10 or higher
* OpenAI API key ([Get one here](https://platform.openai.com/api-keys))

Set your OpenAI API key:

```bash theme={null}
export OPENAI_API_KEY="your-openai-api-key"
```

<Note>
  Uses OpenAI by default. Want to use Ollama, Anthropic, or local models? See [Configuration](/open-source/configuration).
</Note>

## Installation

<Steps>
  <Step title="Install via pip">
    ```bash theme={null}
    pip install mem0ai
    ```
  </Step>

  <Step title="Initialize Memory">
    ```python theme={null}
    from mem0 import Memory

    m = Memory()

    ```
  </Step>

  <Step title="Add a memory">
    ```python theme={null}
    messages = [
        {"role": "user", "content": "Hi, I'm Alex. I love basketball and gaming."},
        {"role": "assistant", "content": "Hey Alex! I'll remember your interests."}
    ]
    m.add(messages, user_id="alex")
    ```
  </Step>

  <Step title="Search memories">
    ```python theme={null}
    results = m.search("What do you know about me?", filters={"user_id": "alex"})
    print(results)
    ```

    **Output:**

    ```json theme={null}
    {
      "results": [
        {
          "id": "mem_123abc",
          "memory": "Name is Alex. Enjoys basketball and gaming.",
          "user_id": "alex",
          "categories": ["personal_info"],
          "created_at": "2025-10-22T04:40:22.864647-07:00",
          "score": 0.89
        }
      ]
    }
    ```
  </Step>
</Steps>

<Snippet file="star-on-github.mdx" />

<Note>
  By default `Memory()` wires up:

  * OpenAI `gpt-5-mini` for fact extraction and updates
  * OpenAI `text-embedding-3-small` embeddings (1536 dimensions)
  * Qdrant vector store with on-disk data at `/tmp/qdrant`
  * SQLite history at `~/.mem0/history.db`
  * No reranker (add one in the config when you need it)
</Note>

## What's next?

<CardGroup cols={3}>
  <Card title="Memory operations" icon="database" href="/core-concepts/memory-operations/add">
    Search, update, and manage memories with the full CRUD API.
  </Card>

  <Card title="Configure for production" icon="sliders" href="/open-source/configuration">
    Swap in your own LLM, embedder, and vector store.
  </Card>

  <Card title="Add to your framework" icon="plug" href="/integrations">
    Wire Mem0 into LangChain, CrewAI, LangGraph, and 20+ more.
  </Card>
</CardGroup>

If you have any questions, please feel free to reach out:

<Snippet file="get-help.mdx" />